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SYNTHESIS AND CHARACTERIZATION OF NANO-COMPOSITES AS SLOW RELEASE ENVIRONMENT
FRIENDLY FERTILIZER
By
Ambreen Lateef
Under the supervision of
Dr. Nadia Jamil
M.Sc. (Pb), Ph.D. (Pakistan)
Dr. Rabia Nazir
M.Sc. (Pb), Ph.D. (Pakistan)
Dr. Shafiq ur Rehman
M.Sc.Hons (UAF), Ph.D. (China)
A Thesis submitted for Partial Fulfillment of the Requirement for the degree of Doctorate of Philosophy
COLLEGE OF EARTH & ENVIRONMENTAL SCIENCES UNIVERSITY OF THE PUNJAB, LAHORE-PAKISTAN
SESSION 2011-2016
DEDICATION
This thesis dedicated
to
my beloved Parents and Family
CERTIFICATE OF APPROVAL
I hereby certify that this research work is based on the results of experimental work
carried out by Ms. Ambreen Lateef under our supervision. We have personally gone
through all data / results / materials reported in the manuscript and certify their
correctness/ authenticity. We further certify that the materials included in this thesis
have not been used in part or full in the manuscript already submitted or in the process
of submission in partial / complete fulfillment for the award of any other degree from
any other institution. Ms. Ambreen has fulfilled all conditions established by the
University of the Punjab for the submission of PhD thesis through the official
procedure of the University.
Dr. Nadia Jamil Supervisor / Associate Professor College of Earth and Environmental Sciences University of the Punjab Lahore-Pakistan
Dr. Rabia Nazir Supervisor / Senior Scientific Officer Applied Chemistry Research Center,
PCSIR Laboratories complex, Lahore- Pakistan
Dr. Shafiq ur RehmanRabia Nazir Supervisor/ Assistant Professor College of Earth and Environmental Sciences, University of the Punjab. Lahore-Pakistan
CERTIFICATE OF TYPOS AND GRAMMATICAL ERROS
It is hereby certified that this thesis is based on the results of the experimental work
carried out by Ms. Ambreen Lateef under my supervision. I have personally gone
through all the data / results / material reported in the manuscript and certify that there
are no typos and grammatical errors. I further certify that the material included in this
thesis has not been used in part or full in a manuscript already submitted or in process
of submission in partial / complete fulfillment for award of any other degree from any
other institution.
Ms. Ambreen Lateef has fulfilled all conditions established by the University of the
Punjab for the submission of this dissertation and I endorse its evaluation for the award
of PhD degree in the field of Environmental Sciences through the official procedures
of the University.
Dr. Nadia Jamil Associate Professor / Supervisor College of Earth and Environmental Sciences University of the Punjab Lahore-Pakistan
DECLARATION CERTIFICATE
The thesis being submitted for the degree of PhD in the University of the Punjab does
not contain any material which has been submitted for the award of PhD degree in
any other University and to the best of my knowledge and belief, neither does this
thesis contain any material published or written previously by another person, except
when due reference is made to the source in the text of the thesis.
Ambreen Lateef
PhD Scholar College of Earth and Environmental Sciences
University of the Punjab, Lahore
AUTHOR’S DECLARATION
I, Ambreen Lateef hereby stated that my PhD Thesis titled “Synthesis and
characterization of Nano-Composites as Slow Release Environment Friendly
Fertilizer” is my own work and has not been submitted previously by me for taking
any degree from the University of the Punjab, Lahore, Pakistan or anywhere else in
the country / world. At any time if my statement is found to be incorrect even after my
graduation the University has the right to withdraw my PhD degree.
Ambreen Lateef
PhD Scholar College of Earth and Environmental Sciences
University of the Punjab, Lahore Dated: 19.12. 2017
PLAGIARISM UNDERTAKING
I, solemnly declare that research work presented in the thesis titled “Synthesis and
characterization of Nano-Composites as Slow Release Environment Friendly
Fertilizer” is solely my research work with no significant contribution from any other
person. Small contribution / help wherever taken has been duly acknowledged and
that complete thesis has been written by me.
I understand the zero tolerance policy of the HEC and University of the Punjab,
Lahore, Pakistan towards plagiarism. Therefore I as an Author of the above titled
thesis declare that no portion of my thesis has been plagiarized and any material used
as reference is properly referred / cited.
I undertake that if I am found guilty of any formal plagiarism in the above titled thesis
even after award of PhD degree, the University reserves the rights to withdraw / revoke
my PhD degree and that HEC and the University has the right to publish my name on
the HEC / University Website on which names of students are placed who submitted
plagiarized thesis.
Ambreen Lateef
PhD Scholar College of Earth and Environmental Sciences
University of the Punjab, Lahore Dated: 19.12. 2017
i
ABSTRACT
Agriculture is the back bone of economic development of any agricultural country
and it has been transformed into a vast industry fulfilling the primary needs of the
masses. Sustainability in agriculture sector is a serious concern specifically in the
perspective of environmental conservation as well as maintaining rather improving the
crop productivity. This research work was designed to prepare environmentally
friendly slow release nano-fertilizer as a substitute for conventional chemical fertilizers
that could protect the environment from deleterious effects of conventional chemical
fertilizers without compromising agricultural productivity.
Two types of nano-composites, based on zeolite (ZNC) and biochar (BNC), with
a particle size of 6.05 and 55.6nm, were synthesized by adopting two-step approach
and compared with conventional chemical fertilizers. In the first step support materials
i.e. nano zeolite (NZ) and biochar of corncob (CB) were synthesized and in the second
step support materials were impregnated/ doped with micro and macro nutrients.
Physiochemical properties of both the support materials (NZ & CB) and their nano-
composites (ZNC & BNC) were determined using standard methods. While the
structure, morphological features, chemical composition, size and thermal stability
were determined by fourier transmission infrared spectroscopy (FT-IR), powder x-ray
diffraction (XRD), scanning electron microscopy (SEM), energy dispersive x-ray
spectroscopy (EDX), atomic force microscopy (AFM) and thermogravimetric analysis
(TGA).
Slow release properties of ZNC & BNC carried out in water as well as in soil for
7 and 14 days, respectively, that confirmed the gradual release and long time
availability of all the doped nutrients (N, P, K, Ca, Mg, Fe, Zn). Concurrently, the
synthesized nano-composites showed excellent water absorbance, salt index and
water retention capacities that is good to enhance the soil condition without imparting
negative impacts to the crops. The nano-composites’ capability to enhance crop
production in comparison to conventional fertilizers was accessed primarily by
performing greenhouse experiments on wheat – a major cash crop of Pakistan that is
widely grown and serving the purpose of staple food in Pakistan. The completely
randomized design with five treatments (control, urea, NPK, ZNC and BNC) was laid
ii
down, to study the germination parameters; time for 50% germination (T50), mean
germination time (days), final germination percentage (%) and germination index. The
results indicated early sprouting and germination in ZNC followed by BNC than
conventional fertilizers (i.e. urea and NPK).
After positive germination results of greenhouse experiment, the field trials
were carried on using the same approach i.e. RCBD with three replicates of each
treatment to examine the effect of nano-composites on growth and yield parameters
for two consecutive years (2014 - 2016). The results were statistically analyzed using
one- way ANOVA (LSD at 0.5%) and means were separated by standard errors. The
results of field trials demonstrated that nano-composites (ZNC & BNC) positively
influenced growth and yield of wheat crop as compared to conventional fertilizers
(urea and NPK) and control. In the first year, the highest grain yield was found for ZNC
followed by BNC, NPK, urea and lowest for control treatment. While in the second
year the scenario was slightly changed and the highest yield was observed in BNC
followed by ZNC; the rest of the pattern is same as previous i.e. NPK > urea >control.
The proximate, antioxidant and nutritional analysis of wheat grain were
performed to determine the comparative effect of nano-composites (ZNC & BNC) with
conventional fertilizers. The results demonstrated that nano-composites had marked
influence on nutritional quality, antioxidant activity and proximate analysis of wheat
grain as compared to urea and NPK. Similarly, comparison of pre and post-crop-
harvest analysis of soil confirmed that use of nano-composites improve the quality of
the soil.
Finally, the viability of these nano-composites was quantified through economic
analysis for the feasibility of this new approach in field application. The results showed
that nano-composites significantly enhanced the gross benefit as compared to
conventional fertilizers. Hence, it can be safely concluded that use of these nano-
composites will not only protect the environment but also enhance the yield, nutritional
quality of crops and income of farmers by reducing the fertilizer input cost thereby
ensuring sustainable agriculture development.
iii
ACKNOWLEDGMENTS
First of all I bow my head before the creator of universe, ALLAH Almighty, who is
the most Beneficent and Merciful. I thank God, “The Gracious and Sympathetic” that I
have been able to undertake and complete this research work. Also, my sincere regards
and thanks to Holy Prophet Hazrat Muhammad (PBUH) who is our ultimate leader and
without his blessings and mercy upon us, we can never achieve our goals.
I express my deep sense of gratitude towards my supervisor, Dr. Nadia Jamil,
Associate Professor, College of Earth and Environmental Sciences, University of the
Punjab, Lahore, for her immaculate sincerity, kind supervision, keen attention, constant
encouragement, expert guidance and constructive criticism during my research.
I pay my deep thankfulness towards Dr. Rabia Nazir, Senior Scientific Officer,
PCSIR Laboratories complex, Lahore, for her precious instructions, sincere inspiration,
devoted co-operation and continuous mediations directed me throughout the study
period.
I also very obliged to Dr. Shafiq ur Rehman, Assistant Professor, College of Earth
and Environmental Sciences, University of the Punjab, Lahore, for his guidance, valuable
and timely suggestions during critical time of my research period.
I am very thankful to Prof. Dr. Sajid Rashid Ahmad, Principal, College of Earth and
Environmental Sciences, University of the Punjab, for his help and guidance for my
study.The financial support of Higher Education Commission (HEC), Pakistan under
Indigenous PhD Fellowship for 5000 Scholars, Phase - II is greatly acknowledged for this
study.I am also very thankful to Mr. Javed Iqbal, Institute of Agricultural Sciences,
University of the Punjab, Lahore, for me facilities and space in greenhouse chamber for
my experiments.
I feel my acknowledgements are incomplete unless and until, I express my sincere
thanks to my father Muhammad Latif, my mother and siblings for their love,
encouragement, moral and financial support and sincere wishes made possible to
complete this modest study.
Ambreen Lateef
iv
LIST OF TABLES
Table 3.1 Water analysis using Standard Methods 54
Table 3.2 Weather data for the study period (2014-2016) of two
consecutive years
59
Table 3.3 Physiochemical Analysis of Soil before Sowing 60
Table 4.1 Physical Analysis of NZ and ZNC 71
Table 4.2 Results of water analysis 85
Table 4.3 Proximate and Physical Analysis of CB and BNC 89
Table 4.4 Properties of the prepared samples as applicability for
the slow release fertilizer
100
Table 4.5 Effect of Different treatments on germination parameters
of Wheat
105
Table 4.6 Comparative effect of different treatments on the
proximate analysis of wheat grain(as average of two
consecutive years)
124
Table 4.7 Concentration of macro and micro nutrients in grains for
two consecutive years
129
Table 4.8 Post-harvest soil analysis of different treatments of two
consecutive years
135
Table 4.9 Economic Analysis of Nano-composites and
conventional fertilizer for the first year (2014-2015)
137
Table 4.10 Economic Analysis of Nano-composites and
conventional fertilizer for the first year (2015- 2016)
139
v
LIST OF FIGURES
Figure 1.1 Schematic representations of top down and bottom up
approaches
8
Figure 1.2 Schematic representation of co-precipitation method 9
Figure 1.3 Release of nutrient is synchronized with nutrients demand
of crops in case of ideal fertilizer
11
Figure 1.4 The concept of enhanced efficiency of fertilization:
Application of nitrogen fertilizer in numerous steps
12
Figure 1.5 Release pattern of urea coated granule fertilizer 13
Figure 1.6 Different types of slow release fertilizer 15
Figure 2.1 Structure of Zeolite showing tetrahedral arrangement 26
Figure 3.1 Schematic diagram of synthesis of nano-zeolite (NZ) 40
Figure 3.2 Schematic representation of synthesis of corncob biochar
by the pyrolysis of corncob at high temperature in the
furnace
41
Figure 3.3 Schematic diagram for the impregnation of nutrient into
support with constant stirring
42
Figure 3.4 Flow chart shows the characterization and application
scheme of synthesized nano-composites
43
Figure 3.5 Column study for the estimation of nutrient release pattern
of the nanocomposite in soil medium for 14 days periods.
56
Figure 4.1 FTIR spectra of NZ (A) and ZNC (B) represents slight
changes in intensities of peaks in ZNC due to
incorporation of nutrients
73
Figure 4.2 Powder XRD of NZ (A) and ZNC (B) showing amorphous
nature of samples
74
Figure 4.3 SEM micrographs of NZ at resolution of 10 and 1 µm (A &
B) respectively.
75
vi
Figure 4.4 SEM images of ZNC at resolution of 10 and 1µm (A & B),
respectively.
76
Figure 4.5 EDX spectra showing elemental composition of nano
zeolite
77
Figure 4.6 EDX spectra of ZNC represents the detailed composition
of doped micro and macro nutrients.
78
Figure 4.7 AFM images in (A) 2D shows the narrow distribution of
particles and (B) 3D of ZNC showing particle size in range
of 6.05 nm.
79
Figure 4.8 TGA (black line) and DSC (blue line) spectra of NZ
showing minor weight loss.
81
Figure 4.9 TGA (black line) and DSC (blue line) spectra of ZNC
showing incremental weight loss.
82
Figure 4.10 Water retention capacity of control (soil without ZNC) and
of soil with ZNC.
84
Figure 4.11 Slow release pattern of doped nutrients in tap water for
seven days studies from ZNC.
86
Figure 4.12 Slow release pattern of doped nutrients in soil for 14 days
studies from ZNC.
87
Figure 4.13 FT-IR spectra of CB (A) and BNC (B) representing shifting
of peaks in BNC, which affirms the adsorption of nutrients.
90
Figure 4.14 Powder XRD Diffracto-gram of CB (A) and BNC (B). 92
Figure 4.15 SEM images of CB at resolutions of 5 µm (A) and 1µm (B),
respectively, showing porous structure of CB.
93
Figure 4.16 SEM images of BNC at resolutions of 5 µm (A) and 1µm
(B), respectively, showing rounded particles and white
color represents the impregnation of nutrients.
94
Figure 4.17 EDX spectra showing elemental composition of corncob
biochar (CB)
95
Figure 4.18 EDX spectra of BNC represents the detailed composition
of doped micro and macro nutrients.
95
vii
Figure 4.19A 2D image represents the narrow distribution of particles 96
Figure 4.19B 3D AFM images of confirms the size of BNC 97
Figure 4.20 TGA thermogram (black line) and DSC curve (blue line)
depicting thermal stability of CB
98
Figure 4.21 TGA thermogram (black line) and DSC curve (blue line)
describing thermal stability of BNC.
99
Figure 4.22 Water retention capacity of control (soil without BNC) and
of soil with BNC.
101
Figure 4.23 Release pattern of doped nutrients for 7 days in tap water
from BNC.
102
Figure 4.24 Release pattern of doped nutrients for 14 days in soil from
BNC.
103
Figure 4.25 Comparative effects of different treatments on shoot and
root length of wheat
106
Figure 4.26 Comparative Effect of different treatments on the shoot
and root fresh and dry weight of wheat.
107
Figure 4.27 Comparative effect of different treatments on number of
leaves and leaf area index of wheat
108
Figure 4.28 Effect of different treatments on the plant height of wheat
for two consecutive years.
110
Figure 4.29 Effect of different treatments on the shoot fresh weight of
wheat for two consecutive years.
111
Figure 4.30 Effect of different treatments on the shoot dry of wheat for
two consecutive years.
112
Figure 4.31 Effect of different treatments on number of tillers per plant
of wheat for two consecutive years.
113
Figure 4.32 Effect of different treatments on number of productive
tillers per plant of wheat for two consecutive years.
114
Figure 4.33 Effect of different treatments on spike length and number
of spikelet per spike of wheat for two consecutive years.
115
viii
Figure 4.34 Effect of different treatments on number of grains per
spike of wheat for two consecutive years.
116
Figure 4.35 Effect of different treatments on 1000 grains weight of
wheat for two consecutive years.
118
Figure 4.36 Effect of different treatments on biomass yield of wheat for
two consecutive years.
119
Figure 4.37 Effect of different treatments on the grain yield of wheat
for two consecutive years.
121
Figure 4.38 Effect of different treatments on the harvest index of wheat
for two consecutive years.
122
Figure 4.39 Effect of different treatments on the antioxidant activity of
wheat grain for as average of two consecutive years.
131
ix
ABBREVIATIONS
AFM Atomic force microscopy
BNC Biochar based Nanocomposite
CB Corncob biochar
CEC Cation exchange capacity
CRFs Controlled release fertilizers
DSC Differential scanning calorimetry
EDX Energy dispersive x-ray spectroscopy
EWC Equilibrium water content
FT-IR Fourier transform infrared spectroscopy
NPK Nitrogen Phosphorus Potassium
NZ Nano Zeolite
SEM Scanning electron microscopy
SRFs Slow release fertilizers
SR Swelling ratio
TGA Thermogravimetric analysis
WR Water retention
WA Water absorbance
XRD X-ray diffraction
ZNC Zeolite based Nanocomposite
TABLE OF CONTENTS
Abstract i
Acknowledgments iii
List of Tables iv
List of Figures v
Abbreviations ix
CHAPTER ONE INTRODUCTION 1
1.1 Conventional Fertilizers and their Environmental Impacts 2
1.2 Pakistan is an Agro based Country 4
1.3 Implication of Nanotechnology in Agriculture 6
1.4 Nano-fertilizer as an Innovative Approach 7
1.5 Nano-composite 8
1.5.1 Co-precipitation method 9
1.5.2 Sol-gel method 10
1.5.3 Hydrothermal method 10
1.6 Slow Release Fertilizer 10
1.6.1 Types of SRFs 14
1.6.2 Advantages of SRFs 16
1.6.3 Disadvantages of SRFs 16
1.7 Significance of Topic 17
1.8 Objectives 18
CHAPTER TWO LITERATURE REVIEW 19
2.1 Nano based Slow Release Fertilizers 22
2.2 Zeolites and Nanoporous Zeolites 25
2.3 Biochar 32
CHAPTER THREE MATERIAL AND METHODS 39
3.1 Materials 39
3.2 Synthesis of Nano-composites 39
3.2.1 Synthesis of support materials 39
3.2.1.1 Nano zeolite 39
3.2.1.2 Corncob biochar 40
3.2.1.3 Impregnation of nutrients 41
3.3 Characterization 43
3.3.1 Physical analysis 44
3.3.1.1 Moisture content (%) 44
3.3.1.2 pH and electrical conductivity 44
3.3.1.3 Ash content (%) 45
3.3.1.4 Bulk and tap densities 45
3.3.1.5 Cation exchange capacity. 46
3.3.1.5.1 Cation exchange capacity of NZ and ZNC 46
3.3.1.5.2 Cation exchange capacity of CB and BNC 48
3.3.2 Fourier transform infrared spectroscopy 49
3.3.3 Powder X-ray diffraction 49
3.3.4 Scanning electron microscopy and Energy dispersive X-ray
spectroscopy 50
3.3.5 Atomic force microscopy 50
3.3.6 Thermogravimetric analysis 51
3.4 Slow Release Properties of Nano-compoistes 51
3.4.1 Salt index 52
3.4.2 Swelling ratio and equilibrium water content 52
3.4.3 Water absorbance studies 52
3.4.4 Water retention studies 53
3.4.5 Slow release studies 53
3.4.5.1 Slow release studies in water 53
3.4.5.2 Slow release studies in soil 55
3.5 Greenhouse Experiment Series 56
3.5.1 Time for 50% Germination 57
3.5.2 Mean germination time 58
3.5.3 Germination index 58
3.5.4 Final germination percentage 58
3.6 Field Trial 59
3.7 Soil Analysis 60
3.8 Morphological parameters 61
3.8.1 Plant height 61
3.8.2 Plant fresh and dry weight 61
3.8.3 Number of tillers 61
3.9 Yield related Parameters 61
3.9.1 Number of productive tillers 61
3.9.2 Spike length 61
3.9.3 Number of spikelets per spike 61
3.9.4 Number of grains per spike 62
3.9.5 1000 grain weight 62
3.9.6 Biomass yield 62
3.9.7 Grain yield 62
3.9.8 Harvest index (%) 62
3.10 Grain Analysis of Wheat 62
3.10.1 Proximate analysis 62
3.10.1.1 Moisture content (%) 62
3.10.1.2 Ash content (%) 63
3.10.1.3 Crude protein (%) 64
3.10.1.3.1 Sample digestion 64
3.10.1.3.2 Steam distillation 64
3.10.1.4 Fat (%) 65
3.10.1.5 Crude fiber (%) 65
3.10.1.6 Carbohydrates (%) 66
3.10.2 Determination of macro and micro nutrients 66
3.10.3 Antioxidant analysis 67
3.11 Economic Analysis of Nano-composites 68
3.11.1 Total production cost 68
3.11.2 Gross benefit 68
3.11.3 Profitable return 68
3.12 Statistical Analysis 69
CHAPTER FOUR RESULTS AND DISCUSSION 70
4.1 Synthesis and Characterization of Nano-composites 70
4.2 Zeolite based nanocomposite 70
4.2.1 Synthesis of nano- zeolite (NZ) and zeolite based nano-
composite (ZNC) 70
4.2.2 Physical analysis 70
4.2.3 Fourier Transform Infrared Spectroscopy (FT-IR) 72
4.2.4 Powder X-ray Diffraction (XRD) 72
4.2.5 Scanning Electron Microscopy (SEM) 75
4.2.6 Energy Dispersive X-ray Spectroscopy (EDX) 77
4.2.7 Atomic Force Microscopy (AFM) 78
4.2.8 Thermogravimetric analysis 80
4.2.9 Salt Index 82
4.2.10 Water absorbance (WA), swelling ratio (SR) and equilibrium
water content (EWC) determination 83
4.2.11 Water retention (WR) 83
4.2.12 Slow Release Studies 84
4.3 Synthesis and Characterization of Biochar based Nano-composite 88
4.3.1 Synthesis of corncob biochar (CB) and biochar based nano-
composite (BNC) 88
4.3.2 Physical and proximate analysis 88
4.3.3 Fourier transform infrared spectroscopy (FT-IR) 89
4.3.4 Powder X-ray diffraction (XRD) 91
4.3.5 Scanning electron microscopy (SEM) 91
4.3.6 Energy dispersive x-ray spectroscopy (EDX) 95
4.3.7 Atomic force microscopy 96
4.3.8 Thermal gravimetric analysis (TGA) 97
4.3.9 Salt index (SI) 99
4.3.10 Water Absorbance (WA), Swelling Ratio (SR) and
Equilibrium Water Content (EWC) 100
4.3.11 Water Retention (WR) 100
4.3.12 Slow Release Studies 101
4.4 Greenhouse Experiment Series 104
4.4.1 Germination studies 104
4.5 Field Trials 109
4.5.1 Morphological and yield related traits 109
4.5.1.1 Plant height 109
4.5.1.2 Shoot fresh and dry weight 110
4.5.1.3 Number of tillers and productive tillers per plant 112
4.5.1.4 Spike length and number of spikelet per spike 115
4.5.1.5 Number of grains per spike 116
4.5.1.6 1000 grain weight 117
4.5.2 Biomass yield (tons/ha) 118
4.5.3 Grain Yield (tons/ha) 120
4.5.4 Harvest index (%) 121
4.6 Grain Analysis of Wheat 123
4.6.1 Proximate analysis 123
4.6.1.1 Moisture content (%) 123
4.6.1.2 Ash (%) 125
4.6.1.3 Protein (%) 125
4.6.1.4 Crude fat (%) 126
4.6.1.5 Crude fiber (%) 126
4.6.1.6 Carbohydrates (%) 127
4.6.2 Concentration of macro and micro nutrients in grain 127
4.6.3 Antioxidant analysis 130
4.7 Soil analysis 133
4.8 Economic analysis 136
Conclusion 140
Reference 142
Annexure-1 Experimental Setup of Nano zeolite synthesis 178
Annexure-2 Germination studies in Greenhouse 179
Annexure-3 Field trials of Wheat 180
Annexure-4 List of Publications 181
Chapter One Introduction
1
CHAPTER ONE
INTRODUCTION
Agriculture practices are very important for humans all over the world for
providing quality food and also plays a significant role in strengthening the economy
of any country. World population is increasing rapidly and expected to reach at the
level of 8.1 and 9.6 billion in 2025 and 2050, respectively from its current level of 7.3
billion (Chen and Yada, 2011). This will increase the enormous burden on the
agricultural system in perspectives of climate change, urbanization, sustainability and
environmental impacts such as nutrient leaching, global warming, accumulation of
pesticides and fertilizers etc. (Ditta, 2012). All these constrains have led to the need
for designing new strategies and adopt appropriate practices to enhance food
production for a sustainable supply of food.
To overcome the difference between demand and food supply, the main focus
of farmers is shifted towards repeated crop cultivation that resulted in nutrient-
depleted soils. To replenish the nutrients deficiency, excessive use of chemical
fertilizers are practiced which appeared as a curse in disguise (Mura et al., 2013;
Veronica et al., 2015). Globally, the consumption of fertilizers increases promptly to
improve agriculture productivity. Hence, the demand of world for fertilizers increase
rapidly at a rate of 1.8% per year from 2014 and estimated to reach to approximately
200 Mt by 2020 (Lubkowski, 2016).
This excessive use of agrochemicals, no doubts improve the crop yield but
deteriorates the quality of soil and impose an immense economic burden. The picture
becomes further gloomier when this surplus use of fertilizers and associated agro-
chemicals demark their negative effects on the ecosystem and humans directly or
indirectly.
Chapter One Introduction
2
1.1 Conventional Fertilizers and their Environmental Impacts
Fertilizers play significant contribution in improving crop production. However,
mismanaged and imbalanced use of these fertilizers has become a serious concern,
as it not only impose burden on the economy but also results in decreased yield. The
conventional fertilizers like urea, nitrogen phosphorus and potassium (NPK) and di-
ammonium phosphate (DAP) etc., when applied in soil, only small amount of these
are taken up by the plants and rest of the fertilizers that account for approximately 40–
70% nitrogen (N), 80–90% phosphorus (P), and 50–90% potassium (K) (Solanki et
al., 2015; Trenkel, 2010) are lost or dispersed into the environment by different
physical and chemical processes like leaching of nutrients, volatilization, rinsing out
and immobilization (Lubkowski, 2016). This leads to the movement of these nutrients
and their respective compounds into the environment globally causing not only
deterioration of the soil and water quality but contributing to global warming as well
(Mosier et al., 2004; Rao and Puttanna, 2000).
The agricultural run-off from soil to water ecosystems, is the main source of
eutrophication and contamination of surface and sea water (Follett et al., 2010).This
results in increased algal growth and reduction of dissolved oxygen levels which leads
to the development of dead zones that directly affects the aquatic ecosystem and
finally decline aquatic fauna as observed in the Black Sea, Baltic Sea and Gulf of
Mexico (Werner, 2000; Killebrew and Wolff, 2010). The pace proliferation of these
natural processes concurrent with severe damage to aquatic and terrestrial
ecosystems.
This loss of nitrogen can cause very severe problems both in humans and
animals (Van Cleemput et al., 2008) which are associated with its conversion to
nitrates by soil microorganisms. Nitrate concentration higher than 10mg/L in drinking
water is traced to many health concerns in humans like blue baby syndrome
(methemaglobinemia) in infants, formation of carcinogenic nitrosamine in stomach
and hypertension (Mosier et al., 2004; Ritter, 2002; Zhang et al., 2003) as well as
become the source of allergies and spreads vector borne diseases like malaria,
cholera and Nile virus (Townsend et al., 2003). Similarly, the presence of higher
Chapter One Introduction
3
concentrations of nitrogenous compounds (nitrates and nitrites) in cereal crops can
adversely affect the human health (Lubkowski, 2016).
These nitrates in the soil can also be converted into nitrous oxide by
denitrification process, which is the third major greenhouse gas after carbon dioxide
and methane (Harrison and Webb, 2001; Savci, 2012). The agriculture sector
produces methane and nitrous oxide, have GWP (global warming potential) of 72 and
296 times greater than carbon dioxide, respectively which contribute more to global
warming (Bernstein et al., 2008; Önder et al., 2011).
Phosphorus is the second major nutrient, required for plant growth after nitrogen
and applied in the soil as ammonium phosphate and superphosphate which are water
soluble compounds. They can freely move in acidic medium and easily taken up by
plants in the form of phosphorus oxides. While in basic conditions, compounds of
phosphorus undergo through different reactions between soluble phosphates and
iron, calcium, manganese and aluminum ions resulting in the production of insoluble
salts that cannot move and leach out from the soil. As a consequence of this, amount
of available phosphorus decreases for plants uptake and phosphate concentration
increases in the soil, which accelerates the eutrophication and affects both aquatic
and terrestrial ecosystems (Chien et al., 2011).
Furthermore, accumulation and contaminations of soil due to trace metals like
chromium, lead, cadmium and uranium are also associated with phosphate fertilizers
(Jiao et al., 2012). Enhanced use of these fertilizers also influences the pH of soil and
degree of salinity, which in turns impacts the production of crops (Dubey et al., 2012).
The imbalance use of fertilizer results in huge wastage of fertilizers and also accounts
for economic losses, as per hectare yield and crops profitability decreased (Ombódi
and Saigusa, 2000; Trenkel, 2010) which can lay massive financial liability on the
society as well as on economy (Ditta and Arshad, 2016).
Chapter One Introduction
4
1.2 Pakistan is an Agro based Country
Agriculture contributes a lot in the economic sector of Pakistan, about 21% of
the gross domestic product (GDP) and 60% to export earnings while accommodating
the employment of more than 44% of total population (Hussain et al., 2015). The
economic development of Pakistan is greatly affected by agriculture sector as it is
interlinked with other industries like textile, sugar, leather etc. Pakistan’s current
population is 198 million and around 67% of the population belongs to rural areas and
depends on agriculture for their living. Population of Pakistan is growing very rapidly
at a rate of 2% per year and expected to reach 300 million in 2050, which in turn will
witness increased demand for food, fiber, protein and energy (Khan et al., 2010). To
satisfy these demands of huge population, different practices and strategies are
adopted in agriculture sector like use of modern machinery, irrigation methods, good
quality hybrid seeds, balanced use of chemical fertilizers and controlled use of
pesticides and herbicides.
In Pakistan, around 22 million hectare area is used for the production of crops
while 80% (18 million hectors) cultivated area is irrigated and remaining area is arid.
It has 10 agro-ecological zones and two major crop seasons namely “Kharif” (sowing
start in April while harvested in November- December) and “Rabi” (beginning in
October-December and ending in April-May). Kharif crops are maize, rice, cotton,
sugar cane and millet, whereas barley, wheat, tobacco, mustard, gram and rapeseed
are Rabi crops (Iqbal et al., 2003). Wheat, rice, cotton and sugarcane are four
important crops of Pakistan and accounts about 75% of the output of total crops hence
contributing a major part of agriculture income. Therefore, production and yield of
these major crops are important from both agricultural production and economy
growth perspectives. Vegetables and fruits recognized as minor crops and also have
the potential for improving economical growth (Iqbal and Ahmad, 2005).
Wheat is the major staple crop and Pakistan lies in world top ten wheat
producing countries, in terms of total production, cultivated area and yield per hectare
(Malghani et al., 2010). It is considered an important element of the diet of people and
constitutes about 60% of a person’s daily diet in Pakistan with an average of 125kg
Chapter One Introduction
5
per capita per annum consumption. Wheat contributes around 10.1% in agriculture
and added approximately 2.2% to GDP of the country (Ali et al., 2016; Hussain et al.,
2015).
Generally, soils of Pakistan have low organic matter and also deficient in
primary nutrients i.e. nitrogen and phosphorus (Ali et al., 2016; Zia et al., 2003).
Deficiencies of macro nutrient potassium (K) and some micro nutrients (zinc, iron,
boron etc.) are also observed in soils of Pakistan (Iqbal et al., 2003; Zia et al., 2003).
Therefore, fertilizers are used for boosting crop growth, to attain optimum yield by
overcoming nutrient deficiencies in the soil. The imbalanced use of fertilizers and their
mismanagement are the major factors that affect the fertilizer use efficacy. Other
factors such as waterlogging, salinity, soil moisture, climatic conditions (temperature,
rainfall), lack of knowledge about soil quality and nutrient status and soil erosion
adversely affect the fertilizer effectiveness but to a minor extent. Due to this
mismanagement, not only the crop production but also its quality suffers badly (Iqbal
and Ahmad, 2005). To overcome this scenario, there is a need for balanced use and
proper management of fertilizers to obtain target yield of the products and economic
development.
However, due to lack of knowledge and guidance, farmers apply fertilizers in
large quantity to increase production. According to National Fertilizer Development
Centre (NFDC), Islamabad, the total usage of fertilizers in Pakistan for the year 2012-
2013 accounts for 3.6 million tons (FAO, 2012) which itself is very high and growing
promptly. This excessive and imbalanced use of costly fertilizers result in degradation
of soil, depletion of nutrients and environmental concerns which leads to low yield per
hectare as compared to other countries (Khan et al., 2010). This will put the burden
on the economic development of the country and creates a gap between food supply
and production (Ali et al., 2016). These limitations depict their negative impacts in
terms of reduction in agricultural productivity as compared to other countries having
same resources and potential. This will further influence the economic balance of
trade in the world together with issues related to survival of agriculture share of
Pakistan in the world market. For that reason, increased and sustained development
Chapter One Introduction
6
in agriculture is imperative to foster economic growth and alleviate poverty in the
country (Iqbal and Ahmad, 2005).
There is the need to change agronomic practices and technologies by designing,
exploring and adopting advanced technologies, which can enhance agricultural
efficiency, addresses public health issues and environmental concerns and also
reduces the cost of resources associated with the agriculture sector. As conventional
technologies have some limitations and their associated risks make them impotent.
So, these new advanced technologies have potential to overcome problems linked
with agriculture and significantly improving productivity and economy by using
resources sustainable basis. Researchers are focusing on development and adoption
of innovative approaches, to synthesize new environment friendly materials for
sustainability of agriculture. The synthesis of slow release nano-fertilizers by
application of nanotechnology gained much importance for improving crop yield and
is among direly needed technology to tackle aforementioned concerns of conventional
farming methodologies.
1.3 Implication of Nanotechnology in Agriculture
Nanotechnology is a promising field of interdisciplinary research and provides a
wide range of opportunities in many fields like medicine, food and agriculture,
pharmaceuticals, water treatment and environment (Masciangioli and Zhang, 2003;
Mauter and Elimelech, 2008). In last few years, nanotechnology has gained more
importance and contributed a lot in the development of innovative methods for
production of new products and materials. These are used as substitutes or
reformulates existing chemicals into new materials to improve their performance and
proficient use (Duncan, 2011). Nanotechnology provides very reliable solutions to the
problems linked with the current methods in a sustainable way (Binns, 2010;
Ramsden, 2011).
Nanotechnology has many potential applications in different areas of agriculture
like it helps in detection of plant diseases, breeding of new varieties of crop,
development of new functional nanomaterials with smart delivery system for
Chapter One Introduction
7
agrochemicals like pesticides, herbicides and fertilizers, vector for slow and controlled
release of nutrients for plant uptake and incorporation of active nano base ingredients
for food processing (Chinnamuthu and Boopathi, 2009; Mousavi and Rezaei, 2011;
Mura et al., 2013).
Nanotechnology is considered as a pioneer for solving current agronomy
concerns, associated with the disproportionate use of chemical fertilizers. This
encompasses nutrient loss due to leaching in the ground and surface water, burning
of plants due to an excessive amount of salt, deterioration in soil quality, mining of
nutrients and global warming by providing slow releases nano-fertilizer as an
alternative to ordinary chemical fertilizers (Chinnamuthu and Boopathi, 2009; Kah,
2015). SRFs release their nutrients slowly to enhance nutrient use efficiency of crops
and provides an excellent opportunity in the fertilizer best management practices for
sustainable crop production and agriculture (Trenkel, 2010).
1.4 Nano-fertilizer as an Innovative Approach
Nano-fertilizers, are nutrient carriers ranging in size from 1 to 100nm. They hold
the nutrient ions because of their small size and large surface area and release them
in a controlled manner, for a prolonged period of time to improve target activity
(Subramanian et al., 2015).This results in enhanced nutrient use efficiency by
facilitating maximum nutrient uptake, which not only has a profound influence on
agricultural outputs but also reduces cost. Apart from this, use of slow release nano-
fertilizers (SRFs) minimize the environmental problems caused by the application of
conventional fertilizers (Mani and Mondal, 2016; Solanki et al., 2015). The application
of SRFs improves the soil fertility by decreasing noxious effects linked with the
excessive use of conventional fertilizers (Lubkowski, 2016).Hence, nano-fertilizers are
considered as more efficient and a better alternative to conventional fertilizers.
Several types of research works have been carried out in this context which dealt
with the development of nanomaterials including nanoparticles and nano-composites
to facilitate plant growth either by direct uptake or by slow release of nutrients (Naderi
and Danesh-Shahraki, 2013; Solanki et al., 2015).
Chapter One Introduction
8
1.5 Nano-composite
The nano-composite is a multiphase solid material, in which nano sized particles
are incorporated into the matrix of support material. Different methods including both
top-down and bottom-up approaches are developed for the synthesis of nanomaterials
including nanoparticles, nano-composites, nanowires etc. (Figure.1.1) (Goddard et al.,
2007).
Figure 1.1: Schematic representations of top down and bottom up approaches
Few of the synthetic methods that are generally used to prepare nano-
composites are discussed under briefly.
Chapter One Introduction
9
1.5.1 Co-precipitation method
In co-precipitation method, homogeneous solutions (in water or solvents) of
inorganic salts (chlorides, nitrates, sulfates) are used as a precursor. By reaction with
an appropriate precipitating agent, these salts are precipitated as hydroxide when the
concentration of ions is attained followed by nucleation and growth phase. The
resulting hydroxides are calcinated to transform into oxides with a crystalline structure.
The schematic layout of the process is presented in Figure.1.2. pH, temperature and
concentration of salt solution greatly affect the shape and particle size of nanoparticles
(Reddy, 2011). The precipitating agents mostly employed are NH4OH, NaOH, and
Na2CO3. This method is simple, low cost, flexible and effective in particle size control
(Jadhav et al., 2009).
Figure 1.2: Schematic representation of co-precipitation method.
Chapter One Introduction
10
1.5.2 Sol-gel method
The sol-gel method comprises of two reaction phases. First is the conversion
of monomers into a colloidal solution (sol), which acts as a precursor and in the second
step for an integrated network (or gel) of either discrete particles or network. The sol-
gel method includes hydrolysis, condensation, drying and thermal decomposition. The
general reaction scheme follows the metal or nonmetallic alkoxide precursor
hydrolysis with water and alcohols. The properties of the end product are influenced
by reaction rate of hydrolysis and condensation (Chiang and Ma, 2002; Gao et al.,
2009). The method is successfully used for the synthesis of metal oxide nanoparticles
like zinc oxide (Vafaee and Ghamsari, 2007), TiO2 (Lee et al., 2010), Fe3O4 (Lemine
et al., 2012) and for nano-composites like TiO2/MMT (BAO et al., 2012), Ag/TiO2
(Zhang and Chen, 2009) etc.
1.5.3 Hydrothermal method
This method involves the heterogeneous reactions occurring in aqueous
solvents under conditions of high temperature and pressure to facilitate the
solubilization of materials that are not soluble under normal conditions (Byrappa and
Adschiri, 2007). The size, shape and properties of the nanoparticles are influenced by
temperature, pressure and reaction time. Mostly autoclave is used to attain the
conditions for hydrothermal reaction. Hydrothermal method is also used in
combination with different techniques such as sol-gel (Li et al., 2005) and microwave
(Verma et al., 2004) to enhance the physical, chemical and structural properties of
nanomaterials (Rao et al., 2006).
1.6 Slow Release Fertilizer
Slow release fertilizers (SRFs) are materials that contain plant nutrients, which
are released into the soil with the delay that is synchronized with the need of plants.
As a result of this, a constant concentration of these nutrients is maintained in the soil
that is basically a balance between nutrients’ uptake by plants and the concentration
being solubilized from the SRFs. This kind of nutrient supply prevents the loss of
Chapter One Introduction
11
fertilizers and leaching of nutrients by runoff (Trenkel, 2010). Moreover, it facilitates
the nutrient uptake efficacy together with enhancement in the nutrient use efficiency
of plants by meeting the nutrient demand of crops for the complete growth period or
season by the single application which not only saves spreading cost but also time
(Shaviv, 2001).
SRFs are defined by Association of American Plant Food Control Officials
(AAPFCO) as “SRFs are products that contain plant nutrient in a form which; a) after
application, extends plant uptake, or b) longer availability of the products compared
with other quick release fertilizers such as urea” (Trenkel, 2010).The fertilizer is
considered to be an ideal, when release pattern of nutrients matches with the nutrient
uptake of crops as presented graphically by the Lammel (2005) in Figure 1.3,
represents a sigmoidal pattern.
Figure 1.3: Release of nutrient is synchronized with nutrients demand of crops
in case of ideal fertilizer
Source: (Adapted from Lammel, 2005)
Chapter One Introduction
12
The sigmoidal pattern of nutrient release ensures the optimal supply of
nutrients to the plant growth by minimizing losses due to different processes which
occur in the soil (Figure 1.4). Slow release fertilizer usually follows the linear or most
often the sigmoidal release pattern of the nutrients to synchronize provision and
uptake of nutrients by the plants (Shaviv, 2005). In 2005, Lammel reported that the
concept of enhanced-efficiency fertilization can be obtained when applied nitrogen
fertilizer followed the sigmoidal pattern of supply of nutrient during plant growth, in the
split application of nitrogen fertilizer (Figure 1.4).
Figure 1.4: The concept of enhanced efficiency of fertilization: Application of nitrogen fertilizer in numerous steps
Source: (Adapted from the Lammel, 2005)
Application of enhanced efficiency fertilization concept in the intensive farming
system can enhance the nutrient use efficiency and also minimize the adverse
environmental impacts. On another hand, the split application is labor intensive, both
in terms of labor required and time needed to do this job hence, putting an excessive
burden on the farmer with an incremental increase in the cost of labor and energy. So,
farmers prefer the single application of SRFs as a replacement for split applications
of conventional fertilizers.
Chapter One Introduction
13
A conceptual model for determining the release rate of these SRFs was
presented by Shaviv, (2005) and Wang et al., (2005) using coated fertilizer (Figure
1.5). These fertilizers are covered with a polymeric layer to ensure controlled delivery
of nutrients that are not affected by soil type (Zhang, 2000).The temporal release
pattern was recorded in this case which was itself a combination of parabolic, linear
and sigmoidal release steps. The last two release patterns i.e. linear and sigmoidal
coincides well with the absorption of nutrient by plants compared to former one i.e. the
parabolic release (Shaviv, 2001; Shaviv, 2005).
Figure 1.5: Release pattern of urea coated granule fertilizer.
Source: (Adapted from the Lammel, 2005)
Generally, sulphur coated urea follows a parabolic release pattern of urea.
Sulphur coated urea will suddenly release almost more than one third of urea, when
in contact with water indicated as burst stage due to cracks (Shaviv, 2005) and
remaining one third releasing after a long time when required by plants (the ‘lock off
effect) (Shaviv, 2001, 2005).Thus, to enhance and maintain the release rate from
sulfur coated urea and to avoid the release from cracks, the double coating was done
with both sulphur and polymer materials (Yang et al., 2006).
Chapter One Introduction
14
The synthesized CRFs and SRFs are categorized by linear and sigmoidal
release types (Shoji and Gandeza, 1992). These fertilizers contain macronutrients (N
or K, NP or NK or NPK alone) or NPK with different micronutrients, and nutrients
release for a prolonged period from 20 days to 18 months (Trenkel, 2010). Hence,
application of slow release nano-fertilizers leads to increase nutrient use efficiency
which subsequently leads to sustainable crop production and also secured water
resources, reduced greenhouse gas emissions, sustained soil fertility and also
contributing towards a better economy.
1.6.1 Types of SRFs
SRFs are classified into three main categories on the basis of their mode of
action like a slow release by the reaction, coating and porous material as presented
in Figure.1.7.
1. Low soluble organic-N compounds: These are further categorized as
biologically decomposable compounds like urea-formaldehyde and chemically
decomposable compounds include isobutylidene-diurea.
2. Coated fertilzers: In this type, the release of nutrients is controlled by coating
the fertilizer (tablets or granules) with hydrophobic polymers or as matrix filled
with active material that ensures the slow dissolution of nutrients. These are
further divided on the basis of coating material used like organic polymers
(thermoplastic or resins), inorganic materials like sulphur or mineral-based
materials. The two types of matrices materials i.e.; hydrophilic (gel forming
polymers) and hydrophobic (polyolefines, rubber) in nature are synthesized to
minimize the dissolution rate and nutrient loss. But the use of these coated
fertilizers is more in practice than the matrices.
3. Inorganic compounds with low solubility like metal ammonium phosphates and
phosphate rock, e.g. magnesium ammonium phosphate (MgNH4PO4), and
partially acidulated phosphate rock, belongs to this type of SRFs.
Chapter One Introduction
15
Figure 1.6: Different types of slow release fertilizer
Chapter One Introduction
16
1.6.2 Advantages of SRFs
1. SRFs release their nutrients slowly as compared to conventional fertilizers
which release nutrients in burst for an entire growth period of the crop, hence
improving the nutrient use efficacy along with the provision of nutrients in
synchrony with plant needs for nutrients (Du et al., 2006; Trenkel, 2010).
2. The risk of plant injury (seed death, leaf burning etc.) reduced, as less quantity
of SRFs is used as compared to conventional fertilizer which increases salt
concentration (Shaviv, 2001).
3. SRFs are coated with organic or inorganic materials, this will help in the slow
pace of nutrients (macro and micro) release and for a prolonged period of time,
that only a single application is enough to meet crop demands which also
reduces the labor cost, energy and time (González et al., 2015).
4. The application of SRFs results in enhanced crop yield diminishes the nutrient
leaching by inhibiting loss of nutrients and environmental problems of
eutrophication and global warming (Guertal, 2009; Shaviv, 2001). SRFs can
reduce the use of conventional fertilizer by 20- 30% of recommended rate,
without affecting the yield of the crops (Liu et al., 2014; Trenkel, 2010).
1.6.3 Disadvantages of SRFs
1. The cost of SRFs is very high due to coating materials, use of advanced
equipment, techniques and energy. Besides, these are not easily available in
the market (Sartain et al., 2004; Trenkel, 2010).
2. In addition, some materials which are used for coating and surface modification
are non-biodegradable and noxious for soil health. In some cases, application
of SRFs changes the pH of the soil, which is injurious to plant health (Liu et al.,
2014).
3. The handling and storage of SRFs need modification to prevent moisture
absorbance and fissuring or cracking of surface coating (Morgan et al., 2009).
4. There is no standardized method, to determine the release pattern of nutrients
yet. Lack of association is found between data collected in laboratory related
Chapter One Introduction
17
to release pattern and actual data obtained from the field leads to be
problematic for efficient use of SRFs as a reliable market commodity or product
(Sartain et al., 2004).
1.7 Significance of Topic
The practice of agriculture has been in use for hundreds of year and its
importance cannot be negated. But on the other hand, agriculture practices cause
detrimental effects on our environment both locally and globally. Pakistan is an
agricultural country and utilizes a large amount of fertilizers to increase crop yield. It
is estimated that only 20% of the total fertilizer is used by the plants while rest is
wasted and leached into the environment and become a source of groundwater
contamination, eutrophication and global warming.
To address these environmental impacts the present research was focused on
the adoption of nanotechnology for the synthesis of low cost nano-composite materials
and their utilization as slow release fertilizer. The aim was avoiding excessive use of
nutrients by maintaining the continuous availability of nutrients to the plants which
thereby have a positive impact on their growth and crop yield. Hence, signifying its
three folds impact on the society by promoting crop yield, decreasing abundant and
disproportionate use of fertilizers and reducing economic burden. So, this study will
be helpful by not only putting a step forward toward inculcating good agriculture
practices but also reducing the environmental issues of leaching, eutrophication and
global warming.
Chapter One Introduction
18
1.8 Objectives
The study is based on the synthesis of nanocomposites by simple route with the
purpose to achieve the following objectives:
1. To synthesis the zeolite and biochar based nano-composites (ZNC and BNC)
and their characterization.
2. To evaluate the role of nano-composites in the slow and continuous availability
of nutrient to the crops in a different environment.
3. To study the comparative effects of these synthesized nano-composites and
conventional fertilizers, greenhouse experiment and field trial were conducted on
germination, growth rate and yield components of wheat.
4. To estimate the economic feasibility of synthesized nano-composites as slow
release fertilizers for field application.
Chapter Two Literature Review
19
CHAPTER TWO
LITERATURE REVIEW
Agriculture marks the back bone of economic development of any country and
sustainability in agriculture sector is a serious concern, which itself is linked with
environmental degradation occurring due to crop husbandry practices. Hence, due
consideration to these two simultaneous aspects needs to be given. This resulted in
the development of many new products designed to meet the requirements of both
sustainability and environmental protection thereby reducing the negative impacts of
conventional fertilizers via their reduced and modified ways of application.
To combat with these both aspects new kind of fertilizers were developed
termed as controlled release fertilizers (CRFs) and slow release fertilizers (SRFs).
These fertilizers (CRFs and SRFs) were prepared to release nutrients gradually to
coincide with the plant nutrient requirements and to reduce the environmental issues.
These were physically prepared, by coating the granules of traditional fertilizers with
different methods to lower the rate of dissolution (Hongfei and Zhenghui, 2005; Shavit
et al., 2003).
The terms of SRFs and CRFs are usually used interchangeably but have some
differences. CRF used for those fertilizers, in which the duration, pattern, and rate of
release are well recognized and managed. On the other side, SRFs characterized
through slow release rate of nutrients than usual, but the duration, pattern, and rate of
release are not very well controlled (Cui et al., 2010; Mikkelsen and Bruulsema, 2005).
CRFs and SRFs have been available since1950s but these materials enjoined
their infancy till the 1980s after which real progress in the development of these
materials took place. Initially, SRFs containing nitrogen base materials like urea
formaldehyde (UF) and isobutyldiene urea (IBDU) were available commercially
(Mikkelsen and Bruulsema, 2005). UF is prepared by the reaction of urea and
formaldehyde under controlled temperature and pH conditions at varying reaction
Chapter Two Literature Review
20
times and the end product is a blend of methylene urea with different long chain
polymers. The nitrogen releases when microorganisms break the long chains into
smaller units resulting in the release of urea. Whereas IBDU is a blend of
isobutyraldehyde and urea from which nitrogen releases by hydrolytic cleavage of the
molecules. The release of nitrogen is faster as particle size decreases and soil
temperature increases (Guertal, 2009).
In 1960’s the encapsulation of fertilizers were done. Since then, coated
fertilizer products were developed as technology has expanded. The fertilizers are
coated with sulfur, resins, polymer, and hybrids of sulfur and polymers, to reduce
leaching losses and improve the nutrient uptake effectiveness compared to ordinary
fertilizers (Hongfei and Zhenghui, 2005; Rai et al., 2015). These coating materials are
discussed briefly one by one.
In the beginning, elemental sulfur was used in a molten form for coating of urea
pills to synthesize sulfur coated urea, as sulfur is inexpensive and have no injurious
influence on the plant growth. Commercially, the initial sulfur coated urea item was
developed for almost 40 years by the Tennessee Valley Authority (Trenkel, 1997,
2010b). A layer of wax sealant is used on sulfur coated urea in order to reduce
microbial degradation and seal cracks in the coating. There is, however one demerit
of this item, is no uniformity in its release rate because of development of cracks in
the surface coating. Generally, the product released one- third very quickly (burst)
while remaining one-third released very slowly (Medina et al., 2009). Later sulfur
coated urea was covered with another layer of resin to control the release of nitrogen
by the Archer Daniels Midland company (Shaviv, 2001; Shaviv and Mikkelsen, 1993).
This coating technique served as the platform for a large number of polymer coated
fertilizer products that are now available in the market.
Alkyd-type called Osmocote (OH, Marysville, Scotts-Sierra Horticultural
Products) is another type of resin coating developed in 1967 in California by use of
dicyclopentadiene as a copolymer with the blend of glycerol ester (Sartain et al.,
2004). The release rate of nutrients from CRFs was regulated by varying the
Chapter Two Literature Review
21
composition or thickness of coating materials. By using this technique, different
fertilizers such as urea and NPK etc. were coated by keeping the weight of coating
material between 10-20% of the fertilizer’s total weight (Budai et al., 2014).
Similarly, thermoplastic resins were also applied as a coating material for
coating of granular fertilizer. The fast-drying chlorinated hydrocarbon solvent was
used for the dissolution of the coatings because of the impermeability of the
thermoplastic polymers, in water. Surfactants and ethylene-vinyl acetate must be
included as a release controlling substances to achieve the desired diffusion
properties. Potentially, the degree of release-controlling agents controls the release
pattern and by twisting the talc into the coating, release rates can also be changed.
This coating material could be used for prilled and granular fertilizers (Sartain and
Kruse, 2001).
After application of the single coating, the modification was done in terms of
changing the properties of fertilizers by increasing the number of coating layers. A
double coating of urea was done to improve both the slow release and water retention
properties and named as double coated slow release water retention urea (DSWU).
The coating consisted of three-layers: the outside coating was cross-linked poly
(acrylic acid-co-acrylamide) superabsorbent, the inside coating was ethyl-cellulose
and the core was pure poly (N-vinyl-pyrrolidone) hydrogel consisting of urea in a
sodium alginate matrix. According to the elemental analysis, 21.1% nitrogen content
was found in the product and water absorbency was 70 times of its own weight. After
being incubated in soil for a period of one month, the slow-release experiment
outcomes yielded that the efficient nutrient release ratio was below 75%. The water-
retention property of soil and water-holding capacity can significantly improve through
the mixing of DSWU into the soil. DSWU can be used for horticulture and agriculture,
particularly in drought-prone regions where there is an insufficiency of water (Ni et al.,
2009).
Chapter Two Literature Review
22
2.1 Nano based Slow Release Fertilizers
Nanotechnology has remarked the revolution in fertilizer technology by the
provision of nano sized controlled-release smart materials that provides enhancement
in nutrient release along with significant cost reduction both in aspects of economics
and environmental pollution (Chinnamuthu and Boopathi, 2009). In this context, it
provides the feasibility of exploiting nanomaterials or nanostructures (size less than
100nm) for development of SRFs or CRFs to enhance nutrient use efficiency through
their smart delivery mechanism of nutrients (DeRosa et al., 2010; Solanki et al., 2015).
Surface coatings of fertilizers with nanomaterials strongly firm the material
because of a higher surface to volume ratio than existing ones thus enabling controlled
release of nutrients in the much improved way. The nano-fertilizers are stable, more
efficient in the provision of nutrients and less eco toxic than ordinary fertilizers (Ditta
and Arshad, 2016; Medina et al., 2009; Naderi and Danesh-Shahraki, 2013). These
nano based fertilizers are available in many forms when talking with respect to their
chemical nature. These include nanoparticles, oxides of nanoparticles, in combination
with conventional fertilizers and as support materials in nano-composites and are
discussed here one by one briefly.
The nanoparticles significantly improve the germination and plant growth.
According to Shah and Belozerova (2009), that different metal nanoparticles like gold
(Au), copper (Cu), silicon (Si) and palladium (Pd) had a positive effect on the growth
of lettuce seed when applied in different concentrations. The Si and Cu were more
effective at higher concentrations while Pd and Au work very well at low
concentrations. Similarly, the nano crystalline powder of copper, iron, and cobalt
applied at very low concentrations on G.max had a profound affect on the germination
as compared to control (Ngo et al., 2014).
The study of Nair et al. (2010), reported that foliar application of zinc oxide
nanoparticles improves the tomato plant growth. They conducted an experiment in
which tomato plants were grown in pots and different concentrations of zinc oxide
nanoparticles were applied in ranges from 0 – 100 mg/L. The results revealed that
Chapter Two Literature Review
23
maximum biomass production and growth was recorded at a concentration of 20 mg
of zinc oxide nanoparticle as compared to the control. Similar positive results in
respect of germination and growth of spinach were found when titanium oxide (TiO2)
nanoparticles were added to the soil. The early germination was detected with
enhanced plant growth (Zheng et al., 2005). As Zhao et al. (2014), studied the
comparative effects of zinc oxide and cesium oxide nanoparticles at a concentration
of 400 ppm on fruit quality of Cucumis sativus. The results showed that fruit quality
improved due to increased starch contents and carbohydrate pattern.
Combination of different nanoparticles and materials in combination with
conventional fertilizers are also tried to facilitate slow release of nutrients. Chitosan
nanoparticles are stable, cationic and biodegradable material that was assimilated
with NPK fertilizer to estimate the release of nutrients and its effectiveness as CRF or
SRF (Corradini et al., 2010). Likewise, urea-formulated hydroxyapatite nanoparticles
prepared with nitrogen fertilizer, and nitrogen release pattren studied were conducted
in the lab for 60 days. Compared to commercial fertilizers, these nanoparticles
subsequently showed the slow release of nitrogen, after initial bursting up to sixty
days. On the other hand, commercial fertilizer showed the release of nutrients to the
level of thirty days only. The stronger attachment of urea on hydroxyapatite surface is
facilitated by large hydroxyapatite area. The strong interaction between urea and
hydroxyapatite nanoparticles added to the controlled and slow release of urea
(Kottegoda et al., 2011).
Similarly, polymers containing mesoporous nanoparticles also proved to be an
effective carrier for agrochemical compounds, which helped in the improvement of
economic utilization and effectiveness. Urea (15.5 %) was entrapped in mesoporous
silica nanoparticles (150 nm) and showed the controlled release of urea in water and
soil with a minimum of fivefold improvement (Wanyika et al., 2012).
Jin et al. (2010), prepared a novel insoluble SRF, biuret poly phosphoramide
(BPAM) by mixing urea, phosphoric acid (H3PO4) and ferric oxide
(Fe2O3) coated with active carbon, acrylic acid, acrylamide, and carboxymethyl
Chapter Two Literature Review
24
chitosan materials. BPAM compositional analysis confirmed the elemental
composition to be 5.66% of nitrogen and 11.7% of phosphorus. The results of studies
revealed that BPAM own excellent capacity for water retention and the tendency for
the steady release of phosphorus along with better cation absorption capacity in saline
soil.
Another kind of slow release membrane-encapsulated urea fertilizer with
26.74% N, moisture preservation and superabsorbent was prepared. Urea granules
were the core of it, and the copolymers of cross-linked starch (the first layer) and AM
and AA (the second layer) were the membrane materials. Compared to its own weight
in tap water, its water absorption rate was around 80 (g/g) times. According to the
water-retaining potential experiment, the greatest water-retaining ratio 12.45%
compared to when the SMUSMP mass ration to soil was 1: 100. As per the water
retention and slow release experiments, it not only had good moisture retention
capacity in soil but also had to batter slow release property. The utilization of water
resources and fertilizer can be improved efficiently through it (Guo et al., 2005).
Urea granules, under the current study, were layered with ethyl cellulose and
polyhydroxy butyrate with differing circumstances while the emulsifiers are present.
The final products and the original granules were featured, and the interaction
between the rates of mass change, and the coating and the granules. In distilled water,
commercial enzyme kit is used to measure the rates of urea release, thereby
presenting a more uniformity. Also, it is observed that there is a reduction of urea
portions dissolution in water by effectively coating the granules with those polymers
(Costa et al., 2013).
The clay based nano-composites are also used as SRFs, in which mostly
montmorillonite or zeolite used as a support matrix. Clay particles have adsorptive
pores which carry nutrients and release them slowly. The results of the study revealed
that clay based nanocomposite (30-40 nm) released nutrients especially nitrogen for
a longer duration than ordinary fertilizers (Subramanian et al., 2015).
Chapter Two Literature Review
25
Pereira et al. (2012), reported that urea augmented with montmorillonite clay
nanocomposite, was prepared by an extrusion process with different urea contents
(50 to 80%) by weight at room temperature and characterized by XRD, DTA, and
SEM-EDX techniques. The diametric comparison test showed that the prepared
nanocomposite is deformable, and dissolution rate of urea was slowed in water which
verified it as effective slow release nano-composite with a low amount of
montmorillonite (10% in weight).
Introduction of organic material into kaoline clays using exfoliation process
under definite pressure and temperature to prepare nano- subnanocomposite. This
material was used for coating of CRFs and SRFs because of its thickness and
potential for adsorption of organic carbon and macro nutrients. The application of this
nano-subnanocomposite improve the soil conditions and enhance the plant growth
(Xiumei et al., 2005).
In recent years, use of zeolite and biochar gained much attraction in the
agriculture. These are renewable materials, have numerous beneficial properties and
potential for providing a solution to the environmental problems caused due to
conventional fertilizers. Their unique physiochemical properties like porous structure,
high cation exchange capacity, large surface area and excellent adsorption capacity
made them more appropriate materials as fertilizer carriers. Past studies had proved
that adsorbed nutrient was found in biologically available forms and had suggested
the potential uses and benefits of nutrient doped biochar and zeolite as SRFs in
agricultural production (Ramesh et al., 2011a; Verheijen et al., 2014). So this research
work focuses on the use of zeolite and biochar as support material for impregnation
of nutrients.
2.2 Zeolites and Nanoporous Zeolites
Zeolites are inorganic porous minerals, have unique physio-chemical
properties which make them the most popular class of minerals after their
identifications in 1756 by a Swedish mineralogist, Alex Fredrik Cronstedt. He gave a
Greek name zeolite, ‘Zeo’ means boil and ‘lite’ means to boil, because of their property
Chapter Two Literature Review
26
to boiled and frothed when heated due to water loss. Later in 1862, St.Claire Deville
claimed the synthesis of zeolite in the laboratory. The real progress in zeolite synthesis
had begun in the 1940s, when Richard Barrer and Robert Milton have made significant
efforts for zeolite synthesis and study its all aspects of practical applications (Polat et
al., 2004; Sangeetha and Baskar, 2016).
Zeolites are crystalline aluminosilicate minerals, having a three-dimensional
tetrahedral arrangement of TO4 (T= tetrahedrally coordinated atom, usually Si4+, Al3+),
linked with each other by oxygen sharing to form a stable honey comb like structure
with open voids and negative charge (Figure 2.1). Zeolite is attracted to cations of
alkali and alkaline metals because of negative charge, which can easily move in and
out of voids (Preetha et al., 2014).These cations may be Na+ (sodium), K+ (potassium),
Rb+(rohbdium), Mg2+(magnesium), Ca2+(calcium) ,NH4+(ammonium), TMA+
(Tetramethylammonium) and other nitrogen containing organic cations. Further, these
cations are bounded by removable water molecules which are exchanged through
other sorbates by ionic redox reactions or ionic migration (Rehakova et al., 2004). The
internal surface area of these channels increases due to the exchange of ions, which
make zeolite an effective ion exchanger (Ramesh et al., 2011b).
Figure 2.1: Structure of Zeolite showing tetrahedral arrangement
Source: (Querol et al., 2002)
Chapter Two Literature Review
27
Generally, zeolites are characterized by this empirical formula that was
proposed by Barrer in 1982 as:
(Mx+, My
2+)[Al(x+2y)Sin-(x+2y)O2n].mH2O.
Where atoms in the tetrahedral framework structure are symbolized within the
brackets, M+ and M2+ are (monovalent and the divalent) cations that balanced
negative charge of structure and water molecules indicate the adsorbed or zeolitic
water (Englert and Rubio, 2005).
Zeolite has the potential to hold water molecules up to 60% of their own weight
due to interconnected voids and pores crystalline structure. Consequently, water
molecules could be absorbed or evaporated from the pores without altering and
damaging the zeolite structure (Polat et al., 2004). Hence enabling zeolites to store
water and provides water for a prolonged period of time in dry and drought lands (Tan
et al., 2010).
Zeolite has complex crystalline structure and have around 193 structure types,
which can be classified by three letter codes on the basis of silica to aluminum ratio
as: low Si : Al ratio (1.0 to 1.5), intermediate Si : Al ratio (2 to 5) and high Si: Al ratio
(10 to several thousands) (Flanigen, 1980). So, the Zeolite categorized with low Si: Al
ratio, represented by letter A and X have high cations and have highest ion-exchange
capacity. Zeolite having intermediate Si: Al ratio, are denoted by Y and zeolite that
have lower Si: Al ratios are known as ZSM-5.The Si: Al ratio is an important property
of zeolite, as it determines the ion exchange potential of zeolite. Si: Al ratio is directly
linked to the thermal stability and inversely linked to the cation content. The Si: Al ratio
increases the zeolite’s surface selectivity alter to hydrophobic from hydrophilic.
Because of these properties, the zeolite is used in different industries as a catalyst,
ion exchanger and for water softening (Saadat et al., 2012).
Zeolite found in abundance both in natural and synthetic form, having different
structures with varying pores sizes. Which can be categorized into three classes:
mesoporous, microporous and nanoporous (Li, 2003). In the 1970s, first nano-sized
Chapter Two Literature Review
28
zeolite (NZ) particles were synthesized in the Lab (Mintova et al., 2006). Which
exhibited new interesting properties because of their small size to volume ratio and
enhanced surface activity. NZ can be synthesized by both tops down and bottom up
approaches using ball mining (Wang and Peng, 2010), sol-gel, hydrothermal (Wang
et al., 2012a) and microwave methods (Sathupunya et al., 2002). The synthesized
zeolite are characterized using different techniques like fourier transform infrared
spectroscopy (FTIR), energy-dispersive X-ray spectroscopy (EDX), x-ray diffraction
(XRD), scanning electron microscope (SEM), atomic force microscopy (AFM), thermal
gravimetric analysis (TGA) etc. for determination of crystallinity, particle size,
morphology and thermal stability.
Zeolite (both natural and synthetic) are frequently used in agriculture as soil
amendments due to its unique molecular sieve structure, high surface to volume ratio,
adsorption, and cation exchange capacity. Thus, application of zeolite improves the
growth of the plant and consequently increased the crop yield (Leggo, 2000; Leggo et
al., 2006). The zeolite not only used as fertilizer in agriculture but also can also act as
carrier or support material for SRF, helps in minimization of leaching loss and
sustainable agriculture (Manik and Subramanian, 2014).
Some of the natural zeolites like Clinoptilolite, Phillipsite, Chabazite, and
Mordenite have been extensively used in agriculture as SRF to improve the soil
quality, water retention and plant growth (Bansiwal et al., 2006). The study of Khan
et al. (2008), revealed that application of zeolite on the soybean planting leads to early
stimulation of vegetative stage on the allophonic soil. Similar results were reported for
tomato when zeolite was added to the soil, in the ratio of one fifth of soil weight (Unlu
et al., 2004).
The reason for this enhanced growth is usually attributed to improved soil
conditions with respect to cation exchange capacity and pH, which ultimately enhance
the availability of nutrients to plants (Ramesh et al., 2011). The addition of zeolite in
the soil, helped in managing and controlling the valuable nutrient, by preventing
release and their harmful impacts to the environment. There are many studies in the
Chapter Two Literature Review
29
literature showing that zeolite application in soil with nitrogen source can enhance the
nitrogen use efficiency. So the use of zeolite as fertilizer reduce environmental issues
and also improve fertilizer competence (Millán et al., 2008). It has been reported that
zeolite when used as SRFs in combination with nitrogen, phosphorus, and potassium
compounds, augments the action these compounds (Naderi and Danesh-Shahraki,
2013).
The results of this study revealed that zeolite (clintopillolite) charged with
ammonium, have the ability to rapidly solubilize the phosphate minerals, leading to
enhanced phosphorus uptake and concurrent positive effect on crop yield (Hua et al.,
2006). Sheta et al. (2003), reported that natural zeolite like clintopillolite had a high
potential for iron and zinc sorption which made it suitable for SRFs. The sequestration
impact of exchange and sparingly solubility of minerals caused the slow release of the
zinc and transmit to zeolite exchange sites the trace nutrients where plants can use
them more readily for uptake (Broos et al., 2007). Zeolite also used to minimize
ammonia volatilization due to surface application of urea, as zeolite had high CEC and
more attraction for NH4 ions (Haruna et al., 2008).
The natural zeolite has some impurities that may affect the availability and
release of nutrients which might hinder or inhibit the plant growth. However, the
synthetic zeolites are used as an alternative to a natural zeolite having the advantage
of no impurities and have the definite crystalline structure (Rehavoka et al., 2004).
Busaidi and his coworkers analyzed the effect of synthetic zeolite on the development
of crop and on soil functionality. They conducted an experiment in both pots and plot
on barley crop by irrigating with saline water in the greenhouse. The outcomes of the
experiment showed that zeolite can amend salinity stress in sandy soil and effectively
improve nutrient balance (Busaidi et al., 2008).
Another experiment was conducted to analyze nitrogen use worth of urea using
microporous natural zeolite (Z) and nanoporous zeolite (NZ) as substrate. According
to the data results, the release of N from urea mixed with NZ (1:1) was 48 days while
urea with a conventional zeolite having the same ratio (1:1) in the mixture, was up to
Chapter Two Literature Review
30
34 days and nitrogen released from urea was finished in just 4 days. So this study
suggests that zeolite based fertilizers can be used for improving crop production as
an alternate strategy (Manik and Subramanian, 2014). Similar results were reported
by Rahale, (2010) which showed that absorption processes are facilitated by NZ due
to a wide surface area for anionic nutrients and cationic nutrients. The stability of the
system was indicated by the value of zeta potentials of the particles ranging from - 30
to - 65.
The research on zeolite based SRF is very limited with respect to loaded
nutrients, in their cationic forms like ammonium (NH4+) and potassium (K+). While the
loading of nutrients on unmodified zeolite, in the anionic forms like phosphate (PO43-
), nitrate (NO3-) and sulfate (SO4
2-) is hardly reported (Hidayat et al., 2015). Therefore,
to load the anionic nutrients onto the zeolite, the modification of its surface becomes
imperative which enhance anionic affinity to promote the loading of anionic nutrients
thereby facilitating its use as SRF.
During last fifteen years, extensive studies have been conducted on surface
modified zeolite by Li et al. (2007), to improve its adsorption capacity. Surface
modification enables the adsorption of the anions, into the surface of zeolite through
anion exchange process as reported in the literature (Bowman, 2003; Faghihian and
Bowman, 2005; Vujaković et al., 2000). For surface modification of zeolite, a cationic
surfactant Hexadecyltrimethylammonium bromide (HDTMABr) was used and results
represent that application of HDTMA bromide enhanced the 200 % of the CEC of
zeolite (Salonki, 2015).Bilayers on zeolite external surfaces were formed by the
surfactant molecules (HDTMABr) with the lower layer occupied by electrostatic
interaction between and the positively charged surfactant head groups and the
negatively charged zeolite surface, while the hydrophobic forces bound the upper and
lower layers together and these forces existed between the surfactant tail groups in
both the layers (Bowman, 2003).
The studies revealed that surface modified zeolite, showed positive results
related to retention of phosphate (Bansiwal et al., 2006) and chromate (Krishna et al.,
Chapter Two Literature Review
31
2001). The study conducted by Bansiwal et al. (2006), in which he used the constant
flow percolation reactor to examine the release behavior of phosphorus in field
conditions and the comparative analysis of the release mechanism of phosphorus
from pure fertilizers, surface modified zeolite and fertilizer-loaded unmodified zeolite.
The results showed a continuous release of phosphorus from surface modified zeolite
loaded with fertilizer for 1080 h, whereas phosphorus release was exhausted within
264 h from KH2PO4. For PO43-, the surface modified zeolite is a fine sorbent and
potentially strong as a fertilizer carrier that helps in the slow release of the phosphorus.
Compared to nitrate, the loading capacity of sulfur on surface modified zeolite
can be owing to the anions’ change impact. One positive charge is contributed by
each HDTMABr molecule and it takes only one negative charge to neutralize. Sulfate
needs two HDTMABr molecules to balance because it is divalent. Meanwhile, there is
no rigidity in the surface configuration of the HDTMABr sue to the surfactant tail-to-tail
interaction. Therefore, in comparison with 1:1 neutralization of HDTMABr by nitrate,
favorability of 2 HDTMABr molecules with one sulfate can be less (Li, 2004; Li, 2003).
The charge generated owing to the hydrogen bonding with the surface and by
the exchange of cations in the pores generates the electrical field which ultimately
influences the nitrogen adsorption on such modified zeolites. Because of the higher
cation exchange capacity, shorter diffusion path lengths, and unique surface qualities,
nanoporous zeolites have drawn much attention in the present context (Ramesh et
al., 2011).
According to Jha and Hayashi (2009), there may be a free and slow release of
ammonium covering the internal zeolite channels, thereby allowing the crop to
progress absorption which can be observed in higher dry matter crop production.
Zeolite mixed with Urea may be applied as SRF which aids the carrying and releasing
of nitrogen from nanozeolite and reduces the nitrogen losses (Ahmed et al., 2010).
Chapter Two Literature Review
32
2.3 Biochar
Biochar is the porous carbonaceous solid, formed in an oxygen free
atmosphere by thermochemical conversion of organic materials. Biochar is a versatile
material and composed of ash, sulfur (S), oxygen (O), hydrogen (H), nitrogen (N), and
carbon (C) in varying proportion depending upon feedstock material (Chan et al.,
2008; Ding et al., 2016; Tang et al., 2013). Thus, biochar is considered a significant
tool, for addressing various important concerns of food insecurity, soil degradation,
agricultural problem, waste management, climate change and as a source for energy
production (Hunt et al., 2010; Kwapinski et al., 2010; Mukome et al., 2013).
Generally, agricultural crop residues are burned in the field for their disposal
and land preparation. Due to this practice, a lot of pollutants emitted into the
atmosphere and become a source of environmental pollution which ultimately led to
global warming issue. Although these crop residues are rich in carbon content that is
abundantly available, so these can be used as biochar source and have potential
applications in agriculture (Sun et al., 2014).
The biochar research gained much importance now a days, because use of
biochar not only reduces the burden of solid waste produced from the different sources
like agriculture, wood etc. (Sohi, 2012) but also indicating better plant growth (Chan
et al., 2008; Singh et al., 2010), enhanced nitrogen retention (Steiner et al., 2008),
and increased bioavailability and plant uptake of supplemented nutrients (Atkinson et
al., 2010; Major et al., 2009).
Different agricultural by-products or residues have been utilized for the
production of biochar like corn cob and corn stalk (Liu et al., 2014; Shariff et al., 2016),
sugar beet tailing (Yao et al., 2011), rice straw (Demirbas et al., 2006; Peng et al.,
2011), waste wood (Abdullah and Wu, 2009; Brown et al., 2006; Chun et al., 2004;
Lucchini et al., 2014) and wheat residues (Chun et al., 2004; Mohanty et al., 2013).
Many researchers are taking interest in the use of biochar for amending the soil
because soil quality improved by the use of biochar. The addition of biochar to the soil
also helpful for carbon sequestration, thus facilitate in mitigation of climate change
Chapter Two Literature Review
33
globally (Laird, 2008; Laird et al., 2009; Woolf et al., 2010; Akbari et al., 2011).It is
estimated that conversion of plant biomass to the stable carbon rich biochar, has the
hypothetical potential of 24 gigatons of carbon absorption from the atmosphere per
year; which is 20% of the total CO2 taken by photosynthesis process (Wang et al.,
2012; Wu et al., 2013).
Biochar is not only helpful in CO2 sequestration but also have a profound effect
on the reduction of other greenhouses gas. According to Renner (2007), emissions of
methane and nitrous oxide were reduced up to 80% in both greenhouse study and
field trials by the use of biochar in Columbia.
Biochar application typically in the Midwestern United States soils resulted in
enhanced water retention, cation exchange capacity and high pH. Moreover, biochar
addition in the soil also decreased the leaching of magnesium (Mg)
, nitrogen, and potassium (Laird et al., 2010). According to Altland and Locke (2012),
almost 10% v/v additions of biochar minimized phosphorus and nitrate leaching by
reducing their release over time. So, it follows that due to the biochar’s capacity to
slow down the release of Nitrate to the roots of the plant, it may be utilized less often.
In addition, there can be a reduction in the application of potassium and phosphorus
because biochar retains these nutrients and release them over time (Altland and
Locke, 2012). Fertilizer potential of biochar has also been indicated by the field studies
(Glaser et al., 2001).
The pyrolysis process greatly affects both physical and chemical properties of
biochar material. Based on the feedstock material and pyrolysis process, there can be
a significant variation in the chemical and physical properties of biochar (Spokas,
2010a). Consequently, the performance of biochar is closely related to both
composition of the source material and production methods used. The feedstock is
important in terms of evaluating the biochar role in the soil. However, there is no
mutual opinion as regards optimal feedstock in respect of both energy production and
soil use, largely owing to the fact that commercial pyrolysis plants were less frequently
available, and those that are available are connected and used in the processing of
Chapter Two Literature Review
34
particular waste streams. The currently used feedstock at research and commercial
facilities includes sewage sludge (Shinogi et al., 2003), dairy manure, chicken litter
(Das et al., 2008), olive waste (Yaman, 2004), distillers grain, sugarcane bagasse,
organic wastes inclusive of paper sludge, switch grass, nut shells, rice hulls, corn
cobs, crop residues including straw, tree bark, wood pellets, and wood chip (Kwapinski
et al., 2010; Sohi et al., 2010).
As appeared from the results of various research works, decrease observed in
the yields of biochar with the increase in temperature (Collins, 2008; Keiluweit et al.,
2010; Ding et al., 2016b). Angin (2013), reported that biochar yields at 400 oC varied
from 34.18% to 29.70% (4.48% changes) with a change in heating rate from 10 to 50
oC/min. Nevertheless, there was 1.76% decrease in biochar yield occurred at 600 oC
with same heating rates.
Heating rate and temperature not only impact the yield but also greatly
influence the chemical properties of biochar. pH values of the biochar also increase
with the increase in temperature (Liang et al., 2006; Inyang et al., 2010; Angın, 2013)
due to the separation of alkali salts separate from organic materials (Yuan et al.,
2012). Increase in carbon content of biochar also results with an increase in pyrolysis
temperature, while the hydrogen and oxygen content reduces in relation to carbon
content (Chun et al., 2004; Chen et al., 2011).
On the other side, the porosity of biochar increases due to increase in
temperature. When the temperature rises, dehydroxylation of water molecules
occurred very speedily and that results in the porous structure of biochar (Demirbas
et al., 2006). Cation exchange capacity is also interlined with the temperature at which
the biochar is produced, that is, cation exchange capacity increases significantly with
the increase in the temperature (Lehmann, 2007).
Owing to various properties of biochar like high surface charge density and high
surface area, it's being exclusively used in soil quality enhancement applications
(Liang et al., 2006). The ability of the soil to reserve plant available water and retain
Chapter Two Literature Review
35
nutrients is increased with the use of biochar which minimizes leaching of agricultural
chemicals and nutrients (Glaser et al., 2001; Lehmann et al., 2006; Laird et al., 2010;).
When biomass is harvested, most of the nutrients are removed, but soil biochar
applications recycle those nutrients. Biomass comprises of base cations (primarily K,
Mg, and Ca) which are converted during pyrolysis into carbonates (ash), hydroxides,
and oxides that are blended with the biochar. Mostly biochar act as a liming agent
during its application to the soil because of the existence of these bases. Soil bulk
density is reduced by biochar because it is a low-density material (Laird et al., 2010;
Rogovska et al., 2012) and as a result, it increases soil aeration, root penetration, and
water infiltration. Moreover, there has been seen an increase in the soil aggregate
stability when biochar is applied (Glaser et al., 2002) however, there is as yet no clarity
as to this effect (Brodowski et al., 2006).
An additional advantage of using biochar for soil enrichment is that facilitates
prolonged water retention because of the porous structure (Dugan et al., 2010; Glaser
et al., 2002; Liang et al., 2006; Sohi et al., 2010). This directly cuts the cost involved
in the irrigation by reducing its frequency and intensity. Further, this also helps in
maintaining the soil pH which directly impacts soil fertility and nutrient availability.
Application of biochar e.g.; rice husk and maize cob reported to enhances soil pH by
20% and 23% on average, respectively which is as good as caused by the lime use
of fertilizer (Nurhidayati and Mariati, 2014).
Zhang et al. (2009), suggested that the increase in the soil pH suppresses the
activity of the enzyme(s) involved in the conversions of nitrite to nitrous oxide thereby
increasing nitrogen availability in the soil. The application of biochar in soil resulted, in
increased CEC which in turn reduced the loss of nutrients through leaching (Lehmann,
2007). Since the biochar possesses high CEC it has the capacity to hold the nutrient
present in the soil, therefore it increases the nutrient use efficiency of the soil which
otherwise get washed away due to precipitation. Fifty percent of carbon in the biomass
retained in its structure during the conversion of biomass into biochar which is more
stable in nature as compared to the biomass which on degradation releases the
Chapter Two Literature Review
36
carbon back into the atmosphere. Thus, biochar production and its application to soil,
later on, create a carbon sink (Kwapinski et al., 2010).
According to Kimetu et al. (2008), biochar addition affects the yield positively
who led to the observation that the non-nutrient improvement to soil function partially
inspired the effects. In Amazonia after clearance of forests, due to biochar enhanced
fertilizer use efficacy was light lighted, which maintain the crop yields, basically a
restoration of terrapreta (Steiner et al., 2008). The sustained and better crop yield
was observed in plots having biochar and NPK as compared to control plots. As in
semi-arid soils of Australia, results showed that application of biochar mixed with
fertilizers have better plant growth in pot trials (Chan et al., 2008), similarly in
Indonesia peanut and maize crop yields were improved, when combination of nitrogen
fertilizer and bark charcoal was applied (Yamato et al., 2006).
The presence of nutrients in soil and their management estimated the response
of crop to biochar was supported through rice experiment (Asai et al., 2009), thereby
suggesting that statistically higher first-season performance was recorded only when
in low yielding crop variety, biochar was applied combined with N fertilizer; based on
a high-yielding (and thus N-demanding) variety, there was a lower yield compared
with the control in a similar assessment. Nevertheless, no appealing yield response is
obtained according to some studies, for instance, Australian study at wheat at low
rates of application (Blackwell et al., 2007).
Many positive results of biochar have been obtained on crop productivity and
soil quality, derived from researches conducted on greatly degraded tropical soils. For
example, in a charcoal kiln sites increase in both biomass yield (44 percent) and corn
grain (91 percent) were noticed relative to control Ghana sites (Oguntunde et al.,
2004). Major et al. (2009), obtained the same results and observed 189% increment
in aboveground biomass after application of 23 t/acre of biochar (measured five
months after) to Typic Haplustox in Columbia. Thus, the effect of biochar application
on plants nutrient uptake and their availability is not completely clear as few reports
showed that nutrient uptake is increasing while in others decreasing. According to
Chapter Two Literature Review
37
Lehmann (2007), biochar addition limits the nitrogen availability in soils which are
nitrogen deficient because of biochar high C/N ratio which decreases crop productivity
temporarily. This holds true for the biochar having high volatile matter content and low
fixed carbon which is biologically available.
Some studies had shown that foliar application of nitrogen concentrations have
reduced when biochar was put to soils. For instance, seventy percent increase in
cowpea biomass production was observed by Lehmann and colleagues (2003), on
highly weathered soil when mixed with ten percent (w/w) biochar in comparison with
control. This research observed significant increase in CEC (from 54.0 to 285.5 mmol
kg-1); potassium content (from 28.1 to 258.3 mmol/kg); nitrogen content (from 3.2 to
4.0 g/kg); carbon content (from 40.0 to 159.4 g/kg); and soil pH (from 5.1 to 5.9).
In the applied biochar, according to the authors, a portion of the carbon was
available for microbial decomposition, which leads to immobilization of nitrogen in soils
which had limited portion of nitrogen. Soils were amended by application of
phosphorus and nitrogen fertilizers on biochar, by contrast, bringing an important yield
feedback that could be ascribed to lead towards the more effective application of
applied nutrients by reducing leaching (Ahmad et al., 2014; Xie et al., 2015). Similar
positive relations persisting between fertilizers and biochar additions have been
observed by several other studies (Chan et al., 2008; Kimetu et al., 2008; Zwieten et
al., 2010).
Li et al. (2007), reported that field experiments of four biochar (organic
/inorganic) pyrolyzed fertilizers by several bio-wastes as compared to conventional
chemical fertilizer in rice, substantiated that at a much lower rate of N input, biochar
compound fertilizer application reduced greenhouse gases emission and improved
nitrogen use efficiency in rice production, thereby ensuring high rice productivity. For
organic/inorganic compound fertilizer, the application of biowaste biochar can be an
alternative to achieve low carbon intensity and high productivity along with preserving
nitrogen fertilizer use in rice sector of Chinese agriculture (Qian et al., 2014).
Chapter Two Literature Review
38
As Deenik et al. (2016), conducted three experiments in the greenhouse to
assess the effects of sewage sludge and corn cob biochar on plant growth and soil
properties in an infertile Oxisol with their anaerobically treated counterparts. The
greatest concentration of bioavailable essential nutrients was shown by the
anaerobically treated sewerage sludge biochar, but in the first crop, the treatment only
aggravated yields for the sewage sludge biochar that was without fertilizer. In
combination with fertilizer, both sewage sludge and corncob biochar doubled plant
development in comparison with the control in the first crop cycle, giving no significant
outcome for the second and in the third cycle, more than tripled plant development for
the sewage sludge biochar.
A persistent liming effect and high ash material with great nutrient amendment
(particularly P) elaborate the sewage sludge biochar’ benefits in respect of plant
growth. The negative impacts of soil manganese toxicity, as was promised by sewage
sludge biochar, were mitigated and cadmium bioavailability was reduced by sewage
sludge, having no prominent influence upon the bioavailability of other potentially toxic
materials than from the control (Wang et al., 2012; Deenik and Cooney, 2016).
Chapter Three Materials and Methods
39
CHAPTER THREE
MATERIAL AND METHODS
3.1 Materials
All chemicals used in this study are of analytical grade and the glass ware was
used, made of Pyrex material.
3.2 Synthesis of Nano-composites
Two types of nano-composites based on zeolite and biochar were synthesized
by adopting two-step approach, in first step support materials i.e. nano zeolite (NZ)
and biochar of corncob (CB) were synthesized and in the second step support
materials were doped with nutrients.
3.2.1 Synthesis of support materials
3.2.1.1 Nano zeolite
Nanozeolite (NZ) was synthesized by using co-precipitation method (Rafiq et
al., 2014) with some modifications. In this method, sodium silicate solution (220 gm /
300 ml distilled water) was taken in a three necked round bottom flask fitted with a
reflux condenser and two quick fit dropping funnels (Figure 3.1). To this ethylene
glycol (25 ml) was added and the contents were stirred hotplate (WiseStir MSH- 20A)
for 30 min while maintaining the temperature at 50 – 60 oC to get a homogenous
mixture. Using the two dropping funnels aluminum sulphate (78.7 g/ 250 ml) and
sodium hydroxide (30 g/ 250 ml) solutions were dropped slowly into the sodium silicate
solution along with continuous stirring and heating (50 – 60 ºC) while neutral pH was
maintained by adding 1N conc. HCl.
Chapter Three Materials and Methods
40
After complete dropping, the contents of the reaction flask were stirred for half
an hr to ensure complete reaction. The material was filtered with Whattman filter paper
42 using filtration assembly and subsequently washed with distilled water followed by
oven (RC- 454) drying at 105 ºC. Then the dried material was crushed in motar and
pestle and transferred to the crucible. The crucible was placed in a furnace (Electra-
CAL) at 650 oC for 5 hrs to attain calcination of the sample which resulted in the gray
colored zeolite.
Figure 3.1: Schematic diagram of synthesis of nano-zeolite (NZ)
3.2.1.2 Corncob biochar
Corncob biochar (CB) was prepared by simple pyrolysis process. Corncobs
were procured from a local vendor, washed with distilled water to remove dirt and
impurities, dried in open air and crushed. The crushed corncobs were put in the
furnace equipped with tubes to provide continuous nitrogen flow at the rate of 1 L/ hr.
The charring process was performed at a slow heating rate (2 ºC/ min) at 350 ºC for
Chapter Three Materials and Methods
41
6 hrs with continued supply of nitrogen (N2 gas) at the rate of 1L/ hr (Budai et al.,
2014). After burning, biochar was allowed to cool to room temperature keeping
nitrogen supply intact. The resulting biochar was ground in a homogenizer and sieved
using 100 mesh sieve. The sieved material was then stored in a zipped plastic bag
(Figure 3.2).
Figure 3.2: Schematic representation of the synthesis of corncob biochar by
the pyrolysis of corncob at high temperature in the furnace.
3.2.1.3 Impregnation of nutrients
The zeolite and biochar based nano-composites (ZNC & BNC) were
synthesized by simple impregnation of nutrients in the support materials (NZ and CB).
200 g of support materials (NZ & CB) was taken in 5L conical flask contains 2L distilled
water. The contents of the flask were stirred using Hotplate (Wisd-2) for 1 hr to get a
homogenous suspension as shown in Figure 3.3. then 5.0% solution of each macro
(N, P, K, Ca, Mg, S) and micronutrients (Fe, Zn, Cu) were prepared from their
respective water soluble salts NaH2PO4 ׅ ׅ ·2H2O, MgSO4·7H2O, Ca3(PO)4,
Chapter Three Materials and Methods
42
ZnSO4·7H2 O, KCl, NaNO3, and FeCl2·4H2O by taking the required amount in 50 ml
distilled water separately(Figure 3.3).
Figure 3.3: Schematic diagram for the impregnation of nutrient into
support with constant stirring
These salt solutions were added to support material suspension and
continuously stir for 3 hrs to get maximum impregnation of nutrients into support
material (NZ & CB). The suspension was then filtered using vacuum suction assembly
and washed with distilled water to get rid of impurities (Figure 3.3). The obtained
material was then dried in an oven at 105 ºC for 5 hrs and ground in a blender to get
finely powdered material which was kept in an airtight jar to prevent from moisture till
further use.
Chapter Three Materials and Methods
43
3.3 Characterization
Both the support materials (NZ & CB) and nano-composites (ZNC & BNC) were
characterized using different techniques to get insight into material properties. After
characterization, slow release studies were conducted to evaluate their feasibility for
a field trial. The plan of this research work is presented in Figure 3.4.
Figure 3.4: Flow chart shows the characterization and application
scheme of synthesized nano-composites.
Chapter Three Materials and Methods
44
3.3.1 Physical analysis
Physical properties of both support materials (NZ & CB) and nano-composites
(ZNC & BNC) were analyzed by using standard procedures.
3.3.1.1 Moisture content (%)
The moisture content of the sample was determined through American Society
of Testing and Materials (ASTM), by the standard method (ASTM- B4643, 2004) of
oven drying the sample at 110 oC. The petri dish was washed and dried in an oven at
110 oC followed by cooling down in a desiccator and weighing ‘A’. The petri dish was
placed in an oven at 110 oC for 4 hrs after adding 2.0g sample and weighing as ‘B’.
Afterwards, the petri dish with the sample was reweighed as ‘C’ once it was cooled
down to room temperature, to obtain a constant weight. The test was conducted in
three replicates. The moisture content (%) was determined using following equation:
Moisture content(%)= (B - C)
(B - A)×100
Where:
A= weight of petri dish
B= weight of petri dish + sample before drying
C= final weight of petri dish + sample after drying
3.3.1.2 pH and electrical conductivity
The pH and electrical conductivity of the sample were determined by standard
methods of ASTM-D4972-13 and ASTM-D1125-14, respectively. The sample was
prepared by taking 1.0 g in 10 ml of distilled water in a beaker and shake well. After
30 min, filter the solution and measured the pH using pH meter (TEMP Meter P25).
Similarly, the EC was measured by an electrical conductivity meter (C.M- 405, TOI
Electronics Ltd) and expressed in µS/cm.
Chapter Three Materials and Methods
45
3.3.1.3 Ash content (%)
Ash content of the sample was measured by furnace incineration using ASTM
method No. D2866 − 94. Which involves vaporization of volatiles and water by burning
of organic substances at a definite high temperature in a muffle furnace. For this, the
crucible was washed with distilled water, dried in an oven at 100 oC, cooled down
these by putting them in desiccator followed by weighing of the crucibles and marked
(A). Then take 2.0g of the sample (finely ground) in a crucible and weighted (B) and
placed this crucible in a muffle furnace and incinerated at 600 oC for 5-6 hrs to obtained
ash. The crucible was allowed to cool to room temperature in a desiccator and re-
weighed as C. Ash content (%) was determined using following formula.
Ash content(%)= (C-A)
(B-A)×100
Where:
A = weight of crucible (g)
B = weight of crucible plus original sample (g) and
C = weight of crucible plus ashed sample (g).
3.3.1.4 Bulk and tap densities
Bulk and tapped densities of the sample were calculated using ASTM method
No. D7481−00.The bulk density was measured by adding about 100g of powder
sample in a dry graduated cylinder (250 ml) capacity. The powder sample was
carefully leveled with the help of specula without compacting and read the apparent
volume of sample nearest to the graduated unit of the cylinder, following equation
used for bulk density:
Bulk density (g
ml) =
Mass of sample(g)
volume of sample(ml)
Chapter Three Materials and Methods
46
While for the measurement of tapped density, the sample was taken in a
measuring cylinder or in a steel vessel, mechanically tapped and compacted with the
device. The mass of compacted sample was measured and calculated by above
equation to obtain the value of tapped density.
3.3.1.5 Cation exchange capacity.
3.3.1.5.1 Cation exchange capacity of NZ and ZNC
The cation exchange capacity (CEC) of NZ and ZNC was determined by pH
titration method as described by Mahmoud, (2015). This method involved the
estimation of moisture content, total cation and total anion exchange capacities. The
moisture content was determined, by taking 2.0 g of sample in a per- weighted prill
vial with lid, weighted and placed in the oven at 600 oC for 24 hrs. Consequently,
removing the closed prill vial from oven and weighed again and the moisture content
was calculated by using equation.
Moisture Weight (%)=(m2 - m3 )
(m2- m1 )×100
Where:
m1 = weight of prill vial with lid
m2 = weight of closed prill vial with 2 g of sample
m3 = weight closed prill vial along with the dried sample.
While the total CEC was calculated by taking 5 .0 g of zeolite sample in a rolling
bottle with 500 ml of HCl (0.1M) for 24 hrs. After that filtration was done and take 10ml
of filtrated and titrated with NaOH (0.1M) solution using mixed indicator. The purple
solution turned to green indicates the completion of the reaction and following
equations were used for calculation of CEC.
C2 HCL= (C NaOH x V NaOH)
V s
Chapter Three Materials and Methods
47
Q (total cat)(meg/g)=[(C1 HCl –C2 HCl )(V)(100-W)]
(100)(m)
Where:
C1 HCl = Initial concentration of HCl (0.1 M)
C2 HCl = Concentration of HCl after cation exchange (M)
C NaOH = Concentration of NaOH (0.1 M)
V NaOH = Volume of NaOH required for titration of the sample of filtrate (ml)
Vs = Volume of filtrate for titration (10 ml)
V = volume of HCl solution (500 ml)
m = mass of zeolite (5.0 g)
W = Moisture weight calculated from above equation
Subsequently, the anion exchange capacity (AEC) was determined by mixing
5.0 g of sample with 500 ml of NaOH (0.1M) in a rolling bottle for 24 hrs. Then filter
the sample and take 10ml of filtrate with HCl (0.1M) using phenolphthalein indicator.
The colorless solution turned to pink on completion of reaction and ACE was
calculated by following equations:
C2 NaOH = C HCl x V HCl
Vs
Q (total an) (meg/g) = [(C1 NaOH – C2 NaOH) (V) (100- W)]
(100) (m)
Where:
C1NaOH = Initial concentration of NaOH (0.1 M)
C2 NaOH = Concentration of NaOH after anion exchange (M)
C HCl = Concentration of HCl (0.1M)
V HCl = Volume of HCl required for titration of the sample of filtrate (ml),
Vs = Volume of the sample titrated (10 ml)
Chapter Three Materials and Methods
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V = Volume of NaOH solution (500 ml)
m = Mass of zeolite (5.0 g)
W= Moisture weight defined by above equation.
3.3.1.5.2 Cation exchange capacity of CB and BNC
The standard sodium acetate method (Denyes et al., 2014) was used to
measure the CEC of synthesized CB and BNC. The sodium acetate solution was
prepared by simply dissolving 136.08 g (NaOAC.3H2O) in 750 ml of double distilled
water. The pH of the solution was adjusted to 8.2 by sodium hydroxide or acetic acid
addition and add distilled water to make the volume 1L. After that prepared the two
rinsing solutions; one was 80% isopropanol (800 ml of isopropanol in 200 ml of double
distilled water) and second was 100% isopropanol. Consequently, the replacing
solution of ammonium chloride (NH4Cl) was prepared by taking 5.35 g in 1L of double
distilled water. The 2.0 g of dried sample was taken in a centrifuge tube (30 ml) and
simultaneously take 5.0 g of sample in a pre-weighed aluminum pan and place this
pan in the oven at 200oC for 2 hrs for moisture content calculation. The 15 ml of
saturated solution was added to the centrifuge tube which contains 2.0 g sample,
centrifuge (NESCO, TGL-16) for 5 min at 3000 speed. The solution was decanted and
carefully removed the supernatant without loss of sample. This step was repeated two
more times followed by addition of 15 ml of 80% isopropanol solution (first rinsing
solution) and centrifuge at 3000 rpm for 5 min.
Again decant and discard the supernatant. Perform this step two times and
measure the electrical conductivity of the supernatant solution until it was below the
conductivity of NaOAc saturated with isopropanol (~6 μS/cm), shift to the second
rinsing solution. Repeat these steps with the sample until the conductivity of the
supernatant drops below 1 μS/cm. then dry the sample and add 15ml of replacing
solution in it, centrifuge for 5min at 3000 rpm. Carefully pour the supernatant into a
volumetric flask (100 ml). Continue this step for further three times and each time pour
the supernatant into flask followed by the makeup of volume with double distilled
Chapter Three Materials and Methods
49
water. The cations were analyzed with atomic absorption spectrophotometer (Perkin
Elmer) previously described, use the following equation:
CEC (cmol/kg) = (C x 0.435)
(W x F)
Where:
F = Weight of air dried and oven dried sample - weight of air dried sample
C = Na concentration (mg/L) in the 100-ml volumetric flask
W = weight (g) of air-dry sample in centrifuge tube
3.3.2 Fourier transform infrared spectroscopy
Fourier transform infrared spectroscopy (FT-IR) is a nondestructive technique
used for the identification of functional groups (chemical bonding) in an unknown
material. The FT-IR spectrum of absorption or emission is obtained as a result of
analysis when infrared radiation passed through the material as a function of
frequency. These frequencies generate fingerprints of material which are used for the
determination of molecular quantitative analysis of organic and inorganic compounds
(Mudunkotuwa et al., 2014). The sample was prepared in pellet form by mixing 4.0 mg
of sample with 200 mg of dried potassium bromide (KBr). The prepared pellet was
analyzed by FT-IR Thermo Nicolet spectrometer series, by scanning in the range of
4000–400 cm-1.
3.3.3 Powder X-ray diffraction
Powder X-ray diffraction (XRD) used for the identification of crystalline or
amorphous phases of solids that helped in the determination of unknown materials
and in measuring the structural features like phase composition, particle size,
composition and lattice parameters (Ingham, 2015).
Chapter Three Materials and Methods
50
The powder XRD analysis was conducted with the help of PANanalytical X’pert
Pro diffractometer by a Philips X-ray generator. Diffraction data was acquired by
exposing powder samples to Cu-Kα X-rays radiation, which has a characteristics
wavelength of 1.5418Ao. X-rays were generated from a Cu anode supplied with a
voltage of 40 kV and a current of 40 mA. The data were collected over a range of 200º
2θ with a step size of 0.05 and nominal time per step is 0.5 second.
3.3.4 Scanning electron microscopy and Energy dispersive X-ray
spectroscopy
Scanning electron microscopy (SEM) provides high-resolution images of the
surface of the sample. These images are used to study surface morphology and to
measure grain (particle) size, the arrangement of particles and shape of the material.
Energy dispersive X-ray spectroscopy (EDX or EDS) is an analytical technique used
for determination of elemental or compositional analysis of the sample. In EDX, a
beam strikes the surface of the sample and excites the electrons present in the inner
shell, resulting in its ejection and creating an electron-hole. While the electrons from
high-energy outer shell move to lower energy inner shell. This movement of electrons
results in the emission or x-rays, which are detected by the energy dispersive
spectrometer (Karkare, 2008).
To study the morphology of the sample SEM analysis was conducted by
coating the sample pellets with a thin layer of gold, to acquire SEM images on Nova
NanoSEM 450. While energy dispersive X-ray spectroscopy (EDX or EDS) used for
determination of elemental analysis of the sample. For this powder sample was spread
on carbon tape, then placed on aluminum studs to obtain EDX spectra, using EDX
Nova 450 at 5.00 kV.
3.3.5 Atomic force microscopy
Atomic force microscopy (AFM) is used to study surface properties like
magnetic, electrical and mechanical with high spatial resolution. AFM can be
functioned properly in media (vacuum or solvent) at different temperatures, and also
Chapter Three Materials and Methods
51
very effective for both conducting and non-conducting materials to produced high-
resolution 2 dimensional (2D) and three dimensional (3D) images. These images were
used to get information about the size, height and surface roughness of sample and
also to measure the force at nano-newton scale (Chicea, 2014).
The topographic images of atomic force microscopy for the prepared nano-
compoistes were recorded with AFM 5500 (Agilent, USA). The probe of silicon nitride,
with a triangle soft cantilever (Veeco, model MLTC-AUHM) having a nominal value of
the spring constant of 0.01 N/m and 0.1 N/m used in the non-contact topography
measurements. An ethanolic solution of the sample (100 µg/ml) was vortexed for 1
min followed by sonication (KQ 500-DE) for 30 min. From this 10 µl solution was taken
and deposited on a freshly cleaved mica surface to obtain images using AFM in
tapping mode.
3.3.6 Thermogravimetric analysis
Thermogravimetric analysis (TGA) was used to determine the composition and
thermal stability of a material by monitoring the loss of weight (mass) with increasing
temperature. As the temperature increases the weight of material increases or
decreases, resulting in emission or absorption of heat. The reaction is either
exothermic or endothermic (Turi, 2012). TGA was carried out using a SDT-Q600
(Germany) instrument; 3.0 mg of sample was taken in an alumina cup and scan was
recorded at a heating rate of 20 ºC/min over the range of 50 – 1000 ºC to find the %
weight loss and thermal stability of material at maximum temperature.
3.4 Slow Release Properties of Nano-compoistes
After physical and structural characterization, the studies like salt index, water
retention, water absorbance and slow release of nutrients were conducted in the lab
to access the suitability of nano-composites as slow-release fertilizer (SRF).
Chapter Three Materials and Methods
52
3.4.1 Salt index
1.0 g of nano-composites (ZNC & BNC) and sodium nitrate were taken in
separate beakers to which 200 ml of distilled water was added. After 24 hrs, solution
conductivities were measured using conductivity meter (CM-40S, TOA) to calculate
salt index as the ratio of these conductivities (He et al, 2007).
3.4.2 Swelling ratio and equilibrium water content
Swelling ratio (SR) and equilibrium water content (EWC) were measured by
taking 1.0 g of each nanocomposite (ZNC & BNC) and the support materials (NZ &
CB) in 200 ml of distilled water and kept for 24 hrs under ambient conditions of
pressure and temperature to swell. After 24 hrs, the contents were filtered using pre
weighted Whattman filter paper. The swelling ratio and equilibrium water contact were
calculated using following formulas, respectively.
SR = Ws - Wd
Wd
EWC (%) = Ws - Wd
Wd × 100
Where:
WS = Wet weight of sample
Wd = Dry weight of sample
3.4.3 Water absorbance studies
Water absorbance studies were conducted by taking 1.0 g of support material
(NZ & CB) and nanocomposite (ZNC & BNC) denoted as (W1) in pre-weighted Petri-
dishes (W2). These petri-dishes were kept in a desiccator for 5 days in a moist
environment and again weighed (W3) to measure the water absorption capacity of
samples using following formula (Company, 1996).
Chapter Three Materials and Methods
53
Water Absorbance (%) =(W3-W2)
W1 ×100
Where:
W1 = Weight of sample
W2 = Weight of sample + petri dish
W3 = Weight of sample + petri dish after 5 days.
3.4.4 Water retention studies
Water retention capacity of soil and nanocomposite (ZNC & BNC) were
measured by taking weights of cups A and B as (WA) and (WB) respectively. Take 50.0
g of sieved soil from the field in cup A and B. In cup B 2.0 g of the nanocomposite was
added and mixed thoroughly. In each cup, 30 ml of distilled water was added and
allowed to seep into the soil for 24 hrs. The cups were then kept in a glass box and
weighted (WA2 and WB2) daily for next 30 days allowing 24 hrs interval between the
readings (Mohamad et al., 2013). Water retention was calculated by following formula,
Water retention (%) =W2
W1
×100
Where:
W1 = Initial weight of sample
W2 = weight of sample recorded daily
3.4.5 Slow release studies
Slow release studies (SRS) were conducted to observe the release pattern of
nutrients from nano-composites (ZNC & BNC) in water and soil.
3.4.5.1 Slow release studies in water
The nutrient release pattern of nano-composites in water was determined by
performing column studies for seven days. This study was carried out in a glass
column (30 ̋ × 0.5 ̋), filled with 5.0 g of nanocomposite and tap water was carefully
Chapter Three Materials and Methods
54
added to prevent breakage of column. The added tap water was analyzed for required
parameters using standard methods as in Table 3.1 to determine the control readings.
Table 3.1: Water analysis using Standard Methods
No Parameter Unit Standard Method
1 pH Number ASTM D1293 – 12
2 Conductivity µs/cm ASTM D1125 – 14
3 Total Hardness(TH) mg/l ASTM D1126-12
4 Total dissolved solids(TDS)
mg/l ASTM D5907-13
5 Chloride (Cl1-) mg/l Silver nitrate titration (ASTM D512-12)
6 Sodium(Na 1+) mg/l Flame photometric method
7 Potassium(K 1+) mg/l Flame photometric Method
8 Magnesium (Mg2+) mg/l Complexometric Titration (ASTM D511-14)
9 Calcium (Ca2+) mg/l Complexometric Titration (ASTM D511-14)
10 Zinc (Zn2+) mg/l Atomic Absorption method (ASTM D1691-12)
11 Iron (Fe3+/2+ ) mg/l Atomic Absorption method (ASTM D1068-15)
11 Phosphate(PO42-) mg/l Colorimetric method
12 Nitrate(NO31-) mg/l Selective Ion Electrode method
25 ml of water from the column was collected daily after 24 hrs and analyzed
for the presence of related parameters (as outlined in table 3.1) to check the release
of nutrients from nanocomposite within the span of seven days. The water level was
maintained in the column throughout the experiment at 50 ml mark (Jamnongkan and
Kaewpirom, 2010).
Chapter Three Materials and Methods
55
3.4.5.2 Slow release studies in soil
The slow release studies in soil were done for 14 days by employing glass
column (size 62 ̋ × 5 ̋). The glass column was filled with 10.0 g of nanocomposite
sample mixed with 400 g of sieved soil. While another column filled with only 400 g of
sieved soil was run as experimental control (Figure 3.5).
Prior to start of experiment the soil was analyzed for pH (ASTM D4972-13),
electrical conductivity (Shah et al., 2013), chloride (volumetric method), total nitrogen
by Kjeldla method (Janssen and koopmann, 2005), phosphorus by olsen method
(Jones , 2001), estimation of calcium, magnesium and iron ions concentration using
atomic absorption spectroscopy, sodium and potassium by flamephotometry (Jaiswal,
2011). Both columns were saturated by adding 180 ml of pre- analyzed tap water
(Table. 3.1).
During the 14 days study period, water from the column was drawn in
increments of 50 ml daily after every 24 hrs time period. To maintain moisture content,
100ml of water was added daily in the column after withdrawing of sample water from
the column. Then these samples were examined to observe the release behavior of
nutrients in soil from nano-composite.
The collected samples from both slow release studies in water and soil, were
analyzed for zinc (Zn2+), iron (Fe2+/3+), calcium (Ca2+), magnesium (Mg2+) by Perkin
Elmer Flame Atomic Absorption Spectrometer, sodium (Na1+) and potassium (K1+) by
flam photometer (Jenway PFP7, Holand). While nitrogen as nitrate (NO3-) by Ion
selective electrode (ISE-930, japan) and phosphate (PO43-) by visible
spectrophotometer (German - 720) method.
Chapter Three Materials and Methods
56
Figure 3.5: Column study for the estimation of nutrient release pattern of the
nanocomposite in soil medium for 14 days periods.
3.5 Greenhouse Experiment Series
After complete characterization of nano-composites, the experiment was
conducted in the greenhouse to examine and compare the effects of these nano-
composites with conventional fertilizers. For the said studies wheat was selected as a
test crop considering the fact that it is one of the major cash crops of Pakistan.
Moreover, separate growth chamber experiments were also performed to see
treatment effects on germination of wheat (Triticum aestivum). The used conventional
fertilizers i.e. urea and NPK (nitrogen, phosphorus, and potassium with a ratio of 5:5:5,
respectively) were purchased from the local market. The experiment was carried out
in Greenhouse at Institute of Agricultural Sciences (IAGS), University of Punjab,
Chapter Three Materials and Methods
57
Lahore in mid of November 2014. The completely randomized design (CRD) was used
with five different treatments which are listed as:
Treatment 1 (T1) = Control
Treatment 2 (T2) = Urea
Treatment 3 (T3) = Nitrogen, Phosphorus & Potassium (NPK)
Treatment 4 (T4) = Zeolite based Nanocomposite (ZNC)
Treatment 5 (T5) = Biochar based Nanocomposite (BNC)
To equate the effect of these treatments on sprouting and germination of the
wheat crop, three replications of each treatment under controlled conditions of
temperature (18-22 oC), humidity (65-75 %), and day and night hours (12/12) were
used in the experiment. The plastic pot (5 × 5 inches size) utilized, were washed with
distilled water to remove impurities and contaminations. The soil was sterilized at a
temperature of 121oC for 1 hr in an autoclave to get rid of soil borne problems
(Miransari et al., 2009). The plastic pots were filled with 650 g of soil, in which 1.0 g of
each fertilizer (urea, NPK, ZNC, BNC) was mixed in upper 2 inch layer of soil and
irrigated with water. Wheat seeds were sterilized with 1.0% sodium hypochlorite
solution (Oyebanji et al., 2009) before sowing. In each pot, 10 healthy seeds of uniform
size seeds were planted. Sprouting of seeds was checked on a daily basis to calculate
germination indices.
3.5.1 Time for 50% Germination
Germination robustness for 50% germination (T50) was measured by the
following formula modified by Farooq et al. (2005),
T50= ti+ (
N2
-ni) (tj-ti)
(nj-ni)
Where:
N= Final number of seeds sprouted
Chapter Three Materials and Methods
58
nj and ni= represents the total count of seeds germinated by respective counts of
times i.e. tj and ti, respectively, when ni < N/2 < nj.
3.5.2 Mean germination time
In order to calculate mean germination time (MGT), a formula devised by Ellis
Robers was employed which is as under:
MGT=∑Dn
n
Where:
n = Number of seeds germinated on day D
D = Number of days counted from the start of germination.
3.5.3 Germination index
Germination index (GI) was determined by following formula described by
Farooq et al. (2005),
GI = No. of germinated seeds
Days of first count+……….+
No.of germinated seeds
Days of final count
3.5.4 Final germination percentage
While final germination percentage (FGP) was calculated using following
expression (Farooq et al., 2005).
FGP(%) =No. of seeds germinated
Total no. of seeds×100
Once germination was completed, shoot and root length, the fresh and dry
weight of shoot and root, number of leaves and leaf area index (LAI) were monitored
Chapter Three Materials and Methods
59
at frequent intervals to observe the effect of fertilizers on plant growth and
development. The experiment continued for 3 weeks.
3.6 Field Trial
After the greenhouse experiment, field trials were conducted in the premises of
Research Area, Pakistan Council of Scientific and Industrial Research (PCSIR),
Lahore during the time period of 2014to2016. The field trials were laid out according
to randomized complete block design (RCBD) with five treatments comprised as T1=
Control, T2= urea, T3= NPK, T4= ZNC and T5= BNC and three replications of each.
The applied conventional fertilizers were purchased from local market. The weather
data for the study period of 2014-2016 was collected from the Pakistan Meteorology
Department, Lahore as presented in Table 3.2.
Table 3.2: Weather data for the study period (2014-2016) of two consecutive
years
Temperature( oC) Relative Humidity (%) Rainfall (mm)
2014-15 2015-16 2014-15 2015-16 2014-15 2015-16
Nov 25 26 26 27 6.0 1.0
Dec 19 21 26 24 0.3 0.2
Jan 18 20 42 36 4.2 8.3
Feb 22 24 45 31 49.8 2.5
March 25 29 54 40 185.6 47.0
April 34 36 33 20 45.5 10.7
May 41 42 41 19 8.2 7.49
Source: Pakistan Meteorological Department weather data
Chapter Three Materials and Methods
60
3.7 Soil Analysis
In field trials, three represented soil samples were taken before and after wheat
crop cultivation from the field at depth of 12 inches (30 cm) randomly for physio-
chemical analyses. After harvesting of wheat crop from each treatment, the soil
samples were again collected from the field to get information about changes in the
soil fertility and leaching of nutrients so that efficacy of conventional fertilizers and
nano-composites on soil fertility profile may be compared. The soil pre-and-post
analysis of pH (ASTM D4972-13), electrical conductivity (Shah et alet al., 2013),
organic matter (ASTM D2974-07), soil texture determined by hydrometer method
(Eshal et alet al., 2004), total nitrogen by Kjeldahl method (Janssen and Koopmann,
2005), available phosphorus using Olsen method (Jones, 2001) and potassium
estimation through flame photometer analysis (Jaiswal, 2011) was conducted and
their results are presented in Table 3.3.
Table 3.3: Physiochemical Analysis of Soil before Sowing
Plantation of crops was done according to recommended formats and time
periods. The calculated amount of each fertilizer was applied to soil all at once before
sowing of seeds and the seeds were sown in each block having area of 10 m2.
Parameters Unit 2014-2015 2015-2016
pH 7.31 7.01
Electrical conductivity ds/m 3.38 3.21
Organic content (%) 3.69 2.54
Nitrogen as N2 (%) 0.18 0.21
Phosphorus as P2O5 (mg/kg) 2.63 2.83
Potassium as K2O (mg/kg) 88 96
Soil texture Clay loam Clay loam
Chapter Three Materials and Methods
61
3.8 Morphological parameters
3.8.1 Plant height
The height of plant was measured in centimeter (cm) from base to top of the
plant, with the help of measuring tape twice a week in a random fashion.
3.8.2 Plant fresh and dry weight
Plant fresh weight was measured by removing the plant from the soil without
damaging, washing with water to remove soil adhered and blot with filter paper to get
rid of surface moisture. The plant was weighed on weighing balance and recorded as
fresh weight. After that, the plant was dried in an oven at a temperature of 70 oC for
24 hrs, and allowed to cool to room temperature followed by its weighing marked as
dry weight of the plant.
3.8.3 Number of tillers
The number of tillers was determined by counting ten randomly selected plants
after their development on weekly basis from each treatment.
3.9 Yield related Parameters
3.9.1 Number of productive tillers
The number of productive tillers were determined at maturity, simply by
counting the ten randomly selected plants from the center of each treatment.
3.9.2 Spike length
Spike length was measured in centimeter (cm) from the bottom to the tip of
spike excluding the awns from ten randomly selected spikes.
3.9.3 Number of spikelets per spike
A number of spikelets were calculated by counting the number of spikelets in
each spike of ten plants.
Chapter Three Materials and Methods
62
3.9.4 Number of grains per spike
Number of grains per spike were counted manually after threshing of the spikes
selected at random.
3.9.5 1000 grain weight
The weight of 1000 grains was weighed on an electronic balance after drying
for unit seed weight.
3.9.6 Biomass yield
The crop was harvested and bundled up and sun dried for 7days. Total wheat
biomass of sundried samples was recorded in kilograms using a digital balance.
3.9.7 Grain yield
Grain yield is also known as agricultural output and was determined when the
crop was harvested. The grain weight of each treatment was recorded by the digital
balance in kilogram and later expressed in tons per hectare.
3.9.8 Harvest index (%)
Harvest index (HI) is calculated as the ratio of grain yield to total above ground
biomass using following formula,
Harvest index=Grian yield
Biomass yield × 100
3.10 Grain Analysis of Wheat
3.10.1 Proximate analysis
3.10.1.1 Moisture content (%)
The moisture content of the sample was determined through Official Methods
of Analysis of AOAC, standard method No. 930.04, by oven drying the sample at 130
oC (AOAC, 2012). The crucible was washed and dried in an oven at 100 oC followed
Chapter Three Materials and Methods
63
by cooling down in a desiccator and weighing (W1). The crucible was placed in an
oven at 130 oC for 4 hrs after adding 2.0g sample and weighing as W2. Afterwards,
the crucible with the sample was reweighed as W3 once it was cooled down to room
temperature, to obtain a constant weight.
The moisture content (%) was determined using following equation,
Moisture content(%)= (W
2- W3 )
(W2- W3 )
×100
Where:
W1= weight of crucibles
W2= weight of crucible+ sample before drying
W3= final weight of crucible + sample after drying
3.10.1.2 Ash content (%)
Ash content of the samples was measured by furnace incineration Official
Methods of Analysis of AOAC method No.930.05 (AOAC, 2012). Which involves
vaporization of volatiles and water by burning of organic substances at a definite high
temperature in a muffle furnace. For this, the finally ground 2.0 g sample, taken in pre-
weighted porcelain crucible (W1), was incinerated in a muffle furnace at 600 oC for 5-
6 hrs to obtain ash. The crucible was allowed to cool to room temperature in a
desiccator and re-weighed as W2. Ash content (%) was calculated by the following
equation,
Ash content(%)= W1-W2
W2
×100
Where:
W1= weight of crucible + sample
W2= weight of crucible+ sample after incineration in furnace
Chapter Three Materials and Methods
64
3.10.1.3 Crude protein (%)
Crude protein was measured using Kjeldahl method (AOAC method
No.970.02) (AOAC, 2012), which includes sample digestion, steam distillation and
titration.
3.10.1.3.1 Sample digestion
For digestion step; sample (0.4 g); selenium / digestion mixture (0.4g) and
conc. H2SO4 (20 ml) were poured into a Kjeldahl flask and heated on low flame with
infrequent shaking till the color of solution changes to transparent from green. The
solution was then taken in 100 ml volumetric flask and volume were marked up to the
level.
3.10.1.3.2 Steam distillation
Markham distillation assembly (capacity 100-150 ml) was employed for this
step. The ammonia gas, released in this step, was captured in a 100 ml conical flask
having 5 ml of boric acid and 1-2 drops of phenolphthalein indicator. This flask was
placed below the condenser of the assembly ensuring that its tip was dipped into the
liquid to avoid the release of ammonia gas. The 5 ml of the digested sample (obtained
from the previous step) was taken into the bulb of apparatus together with 50 ml of
NaOH (60%) solution. This is followed by passage of steam from digest for 4-5 min
leading to increasing in the volume of receiving flask. When the volume in the flask
was approx. doubled, the reaction is stopped and the resulting collected solution was
titrated vs. HCl (N/70) to a colorless endpoint. The blank was also run along with the
sample to calculate the % nitrogen by using expression,
Nitrogen(%) = Vs- VB× Nacid ×100
Where:
Vs = Volume (ml) of acid required to titrate sample
VB = Volume (ml) of acid required to titrate the blank
Chapter Three Materials and Methods
65
N acid = Normality of acid;
W = Weight of the sample (g).
Crude protein (%) of sample was calculated by the following equation,
Crude Protein(%) = N(%) × F
Where:
F = Conversion factor is equivalent to 6.25
3.10.1.4 Fat (%)
Total percentage of fat in samples were estimated using Soxhlet extraction
assembly according to AOAC method No. 978.04 (AOAC, 2012). For this, 2.0 g of
powdered sample was taken in a moisture free thimble and placed in Soxhlet
apparatus filled with n-hexane for 6 hrs. The sample was air dried and oven dried 1 hr
to ensure complete drying. After which the defatted sample was weighed and the
value obtained was used to calculate the percentage of fat using equation,
Fat(%)= (WS+Th1) - (WS+Th2 )
WS×100
Where:
Th1 = Weight of thimble before extraction
Th2 = Weight of thimble after extraction
WS = Weight of sample
3.10.1.5 Crude fiber (%)
Crude fiber was determined by AOAC method No.930.10 (AOAC, 2012) for
which 2.0g defatted sample was taken and refluxed with 150 ml of 1.25% H2SO4
solution for 30 min. The refluxed sample was filtered through silk cloth and washed
with distilled water till the residue became neutral. The washed residue was re-
Chapter Three Materials and Methods
66
refluxed for 30 min in presence of 150 ml of 1.25% NaOH solution. The contents of
the flask were filtered using pre weighed Whattmann filter paper, washed with distilled
water and oven-dried at 130 oC for 1 and a half hour after keeping this filter paper in
the weighed crucible. The crucible was heated in a furnace for about 4-6 hrs to obtain
ash and reweighed. The fiber content was calculated using following formula,
Fiber(%)=weight of sample - weight of ash
weight of sample×100
3.10.1.6 Carbohydrates (%)
All the values of moisture (%), ash (%), protein (%), fat (%) and fiber (%) were
added and subtracted from 100 to calculate as given in equation (AOAC, 2012).
Carbohydrates(%) = 100 - [moisture +ash +protein + fat +fiber]
3.10.2 Determination of macro and micro nutrients
The macro and micro nutrients were determined by the standard methods
used by Oko let al. (2012), from samples. The 2.0 g of the sample was digested with
10 ml of the acid mixture (650 ml c onc. HNO3, 80 ml perchloric acid, 20 ml H2SO4) in
a digestion flask. The digestion flask was heated on burner inside a fuming hood, to
obtain a clear digested solution. This digest solution was then shifted to a 250 ml
volumetric flask and diluted with distilled water up to the mark.
After that, aliquots of this digest was used for estimating the concentration of
calcium (Ca2+), iron (Fe2+,3+) and magnesium (Mg2+) by atomic absorption
spectrophotometry using filters, matched with these nutrients. While sodium (Na1+)
and potassium (K1+) were determined by flame photometry technique. The
concentration of these nutrients (Ca2+ Fe2+, 3+, Mg2+, K1+, and Na1+) was calculated by
plotting their calibration curves, of their standard solutions concentrations against their
relevant absorbance (Oko et al.,(2012).
Phosphorus was estimated by the Vanado-Molybdenum method (APHA-4500-
P). Take 0.5 ml of digested sample in a test tube, add 1ml of conc.HNO3 and 1ml of
Chapter Three Materials and Methods
67
vanadomolybdate reagent followed by agitation. The solution was allowed to stand for
30 min for color development. A standard curve of phosphorus with different
concentrations (ranges 10-100ppm) was developed. The absorbance of phosphorus
standard solutions and sample were measured at 470nm using visible
spectrophotometer (Visible Spectrophotometer-712). The phosphorus concentration
of the sample was determined by plotting a calibration curve of standard solutions
against their respective absorbance.
3.10.3 Antioxidant analysis
The antioxidant activities of grain samples collected from five different
treatments were measured to compare the effects of conventional fertilizers and nano-
composites. The 2, 2-diphenyl- 1-picrylhydrazyl (DPPH) scavenging radical was used
for determination of antioxidant activity (Szabo et al., 2007). Take 0.2 mg of the sample
in dry powdered form and dissolved in ethanol to make a solution. Subsequently, add
0.1 ml of the sample solution into 3 ml of 0.004% DPPH solution, the color of the
solution turned deep violet to yellow which specified the interaction of DPPH radical
with the antioxidant compound. After 30 min of reaction, absorbance was measured
at 517 nm by UV visible spectrophotometer (Visible Spectrophotometer-712). Blank
solution was prepared by mixing ethanol (3.3 ml) and sample (0.5 ml) while the control
solution was a mixture of DPPH (0.3 ml) and ethanol (3.5 ml). The inhibition activity
(%) was calculated using following formula,
Percent Inhibition (%)=(AbsControl - Abssample )
Abscontrol
×100
Where:
Abs control = Absorbance of control
Abs sample = Absorbance of sample
Chapter Three Materials and Methods
68
3.11 Economic Analysis of Nano-composites
The economic analysis or cost benefit analysis of synthesized nano-composites
was done by following the procedure as described by CIMMYT (Program, 1988). In
this procedure, total cost includes input cost that varies and the field price of the crop.
The input cost comprised of the fertilizer cost, labor, machinery used for harvest,
packaging and transport of materials. The conventional fertilizers; urea and NPK
procured from the market at local wage rates while the cost of synthesized nano-
composites (ZNC and BNC) were calculated according to the market price of
chemicals that were used in their synthesis.
3.11.1 Total production cost
Total cost includes both the fixed and variable input cost. The fixed cost
comprised of rent of land, consists of fertilizer cost, field price of crop, harvesting,
threshing, packing, and transportation. The actual yield was adjusted downward by
10% that revealed the difference between the experimental yield and framer yield
obtained from the same treatment.
3.11.2 Gross benefit
Before calculating the gross profit, the yield was adjusted downward by 10%,
because a difference was observed in the yield of framers and researchers for the
same treatment. To figure out the gross return, the current price of wheat (Rs.1300
per 40kg) at which it was available in the local market was taken.
3.11.3 Profitable return
The net benefit was calculated on the basis of total variable cost, simply by
deducting the corresponding cost involved from the gross benefit. While the percent
profitable return was calculated by the subtracting the profitable return of each
treatment from control treatment. This was conducted to have an idea about the
economic feasibility of nano-composites.
Chapter Three Materials and Methods
69
Benefit cost ratio (Mubashir et al., 2010) and investment factor (Mahmoud et
al., 2017) were calculated using following equations:
Benefit cost ratio (BCR) = Profitable return(PR)
Total production cost
Investment factor (IF) = Gross income
Total production cost
The comparative analysis of conventional fertilizers and nano-composites gave
an idea about practical field application and profitability of nano-composites. Because
framers are concerned with the net benefit that they expect to get with the increase in
yield due to adaptation of a technology.
3.12 Statistical Analysis
The results of experiments were analyzed by the Statistical package for social
sciences (SPSS Statistics IBM-version 22). The obtained data were statistically
analyzed by one way analysis of variance (ANOVA) and further subjected to post hoc
least significant difference (LSD) at level of p = 0.05% to compare the effects of
different treatments on the germination and growth parameters of wheat.
Chapter Four Results and Discussion
70
CHAPTER FOUR
RESULTS AND DISCUSSION
The first objective was the synthesis of support materials (NZ and CB), in which
impregnation of nutrients was done to synthesis nano-composites (ZNC and BNC).
After synthesis, these nano-composites were characterized using different techniques
such as FT-IR, XRD, SEM/EDX, AFM and TGA.
4
4.1 Synthesis and Characterization of Nano-composites
The synthesis process of both nano-composites (ZNC & BNC) and their physical
properties and characterizations are discussed here in detail.
4.2 Zeolite based nanocomposite
4.2.1 Synthesis of nano- zeolite (NZ) and zeolite based nano-composite (ZNC)
Nano zeolite (NZ) was prepared by simple co-precipitation method that was
further used to prepare zeolite based nanocomposite (ZNC) by simple impregnation
of macro and micro nutrients. Zeolite in general alumino silicate materials: has a
porous structure (Tago and Masuda, 2010) and use of templating agent further
promotes an increase in porosity and surface area. Hence, when impregnation was
done nutrients penetrated into the pores and from one pore to another pore, ensuring
more adsorption of nutrients leading to enhanced nutrients availability to the plants.
These nutrients will be released to the plant depending upon the pore size, adsorption
level and binding capacity or impregnation level (Khan et al., 2008).
4.2.2 Physical analysis
Upon completion of ZNC synthesis, experiments were conducted to determine
physical parameters i.e. pH, moisture, conductivity, bulk density, tap density, cation
exchange capacity, loss on ignition and ash content for both NZ and ZNC. The results
then obtained are tabulated in Table 4.1.
Chapter Four Results and Discussion
71
Table 4.1: Physical Analysis of NZ and ZNC
No. Parameters unit NZ ZNC
1 pH 6.97 6.0
2 Conductivity at 25 oC (µs/cm) 508.27 555.23
3 Moisture content (%) 2.5 4.48
4 Ash content (%) 91.37 94.27
5 Bulk density (mg/m3) 0.89 1.2
6 Tap density (mg/m3) 1.5 1.8
7 Cation Exchange Capacity(CEC) (meq/g) 2.45 1.37
NZ is a neutral material as observed from the pH of the sample, but there was
a small increase in acidity of ZNC probably due to the incorporation of non-metallic
moieties. A significant increase in conductivity of ZNC from 508.27 to 555.23 µS/ cm
has taken place owing to the inclusion of nutrients and ionic salts into zeolite porous
structure. This inclusion has also resulted in an increase in both tap and bulk densities.
Very high moisture content as indicated by the studies which were in accordance with
the previous studies that state that nano-zeolites with high Si/Al ratio were usually
characterized by high moisture content because of enhancing hydrophobicity induced
by silica (Mahmoud, 2015).
The NZ had cation exchange capacity (CEC) of 2.45 meq/g which compare
able with the clinoptilolite as in literature (Mahmoud, 2015) and anion exchange
capacity was 0.01 meq/g which was very low. While the ZNC had cation exchange
capacity of 1.37 meq/g and anion exchange capacity of 1.96 meq/g. The similar
decrease was observed in CEC of ZNC as compared to NZ owing to the incorporation
of cations into NZ matrix. Low anion exchange capacity was observed in case of NZ
making it specifically cation exchanger (Ming and Dixon, 1987). But for ZNC equally
good anion exchange capacity was observed hence it can be measured as amphoteric
Chapter Four Results and Discussion
72
ion exchanger (Helfferich, 1962) which makes it a better material for agricultural
purposes (Jha and Hayashi, 2009).
4.2.3 Fourier Transform Infrared Spectroscopy (FT-IR)
The comparison of FT-IR spectra of NZ and ZNC is presented in Figure 4.1.
The peaks in the range of 3400-3200 cm-1 are due to the extra bridging of hydroxyl
ion or due to moisture incorporated in the porous structure of zeolite as affirmed from
the incorporation of nutrients in the zeolite structure. Hence, supporting the doping of
nutrients on the NZ as available in the literature (Hidayat et al., 2015) and affirmed by
physical characterization as well. The peaks arising at 1060.85 and 786.96 cm-1 are
assigned to bending and stretching of Al-O and Si-O in zeolite structure (Jahangirian
et al., 2013). The peak shift is observed in FI-TR spectra of ZNC shows 3034.03,
1070.49, 796.60, 594.06, 557.43 and 507.28 which may be attributed to the
incorporation of nutrients in the zeolite structure, supporting the doping of nutrients on
the NZ as available in the literature (Hidayat et al., 2015).
4.2.4 Powder X-ray Diffraction (XRD)
Powder XRD patterns of NZ and ZNC scanned in the range of 2θ = 20 - 80º is
shown in Figure 4.2. The low crystalline structure of NZ is indicated (Figure 4.2A) with
low intensity peaks arising at 2θ values of 23.32º, 25.82º, 28.89º, 31.59º and 33.85º
corresponding to (311), (222), (400), (311) and (421) diffraction planes respectively.
The spectrum is matched with sodium aluminum silicate having cubic crystal system,
code no. CCDC (Cambridge Crystallographic Data Center) No: 01-074-1183. The
ZNC spectra shown in Figure 4.2B, when compared with NZ represents that basic
structure of zeolite is not changed except a slight decline in the intensities resulted
due to the incorporation of nutrients into NZ (El-Din et al., 2011). The presence of low
intensity, broadened peaks are also indicative of small particle size of the samples
prepared (Akbari et al., 2011; Prabhu et al., 2014).
Chapter Four Results and Discussion
73
Figure 4.1: FTIR spectra of NZ (A) and ZNC (B) represents slight changes in intensities of peaks in ZNC due to
incorporation of nutrients
Chapter Four Results and Discussion
74
Figure 4.2: Powder XRD of NZ (A) and ZNC (B) showing amorphous nature of samples
Chapter Four Results and Discussion
75
4.2.5 Scanning Electron Microscopy (SEM)
After structural characterization, SEM analysis was conducted to get insight
into the morphology of the samples prepared. The micrographs of NZ at different
resolutions of 10 and 1 µm were taken (Figure 4.3 A and B) that represents the
crystalline structure.
Figure 4.3: SEM micrographs of NZ at a resolution of 10 and 1 µm (A & B)
respectively.
Chapter Four Results and Discussion
76
While the micrograph of ZNC (Figure 4.4 A and B) corresponds to the spongy
nature of the prepared samples. Increase in the particle size, reduction in porosity and
appearance of white colored coating on the particles in case of ZNC spongy
appearance shows doping effect.
Figure 4.4: SEM images of ZNC at resolution of 10 and 1µm (A & B),
respectively.
Chapter Four Results and Discussion
77
4.2.6 Energy Dispersive X-ray Spectroscopy (EDX)
The EDX spectra of NZ (Figure 4.5) shows compositional analysis of elements.
The chemical formula derived from this composition (Table 4.2) by fitted these values,
in general formula of zeolite (i.e. [AlxSiyO2x+2y] x- where x ≤ y), that points towards the
formation of high silicon zeolite i.e. [AlSi6O12].Na2. The charge (x-) is stabled by
incorporation of an added cation (Na1+, K1+, Ca2+, etc.) as mentioned in the literature
(Akbar et al., 2007; Ramesh et al., 2010).
Figure 4.5: EDX spectra showing elemental composition of nano zeolite
EDX spectra of ZNC gave the compositional analysis of elements and
confirmed the doping of added nutrients (Figure 4.6).
Consequently, the Si/Al ratio was calculated which 6.15 was for the NZ and 10.7 for
ZNC. That also points towards the incorporation of other metallic and non-metallic
impurities and amount of Si or Al exchanged (Mintova et al., 2006). This study is also
in accordance with ion exchange capacity studies discussed earlier.
Chapter Four Results and Discussion
78
Figure 4.6: EDX spectra of ZNC represents the detailed composition of doped
micro and macro nutrients.
4.2.7 Atomic Force Microscopy (AFM)
The particle size of the ZNC was determined using AFM by taking both 2D and
3D images as presented in Figure 5. The 2D image (Figure 4.7) points towards the
narrow distribution of particles in size range of 3 – 6 nm with the majority of particles
having a size of 6.05 nm as confirmed from the 3D image (Figure 4.8). The increase
in particle size as affirmed from SEM (Figure 4.4) and AFM (Figure 4.7) images are
also attributed to high Si/Al ratio in ZNC (Armaroli et al., 2006).
Chapter Four Results and Discussion
79
Figure 4.7: AFM images in (A) 2D shows the narrow distribution of particles
and (B) 3D of ZNC showing particle size in the range of 6.05 nm.
Chapter Four Results and Discussion
80
4.2.8 Thermogravimetric analysis
To determine the stability and thermal degradation pattern of samples
prepared, TGA and DSC analysis were conducted which are given in Figure 4.8 and
4.9 as interlinked spectra. The TGA of NZ (Figure 4.8) thermogram is characterized
by one single slope with continuous but smooth weight loss which is typical of the
spectra recorded for zeolites (Kim et al., 2007; Mahmoud, 2015).
The initial weight loss occurring around 100 ºC is attributed to the loss of water
physically adsorbed which is approximate accounts for wt. loss of 2.5% that is in
conformity with the moisture obtained in physical characterization studies (Table 4.1).
That was followed by further incremental decrease up to 500 ºC associated with loss
of water present in the matrix of NZ (Mahmoud, 2015). The total weight loss is
approximately 8.9%.
As temperature raises, the breakdown of hydroxyl ion increases but in overall,
the de-hydroxylation process of zeolite is slow and occurs in the temperature range of
500-800 oC (Akbar et al., 2007). The weight loss of NZ occurred till 981.86 ºC
accounting for 85.32% residue. The different Si/Al ratio of zeolite was found
responsible for the thermal stability of zeolite, the zeolite with ratio up to 6 shows more
stability than zeolite with a lower ratio (Mintova et al., 2006).
Chapter Four Results and Discussion
81
Figure 4.8: TGA (black line) and DSC (blue line) spectra of NZ showing minor
weight loss.
This trend of NZ thermal degradation when compared with ZNC thermogram
(Figure 4.9), observed to be the same except that small incremental steps can be
noticed which can be attributed to dehydration resulting from weight loss due to
physically bound water (124.97 ºC; Wt. loss 4.56%), matrix bound water (482.16 ºC;
Wt. loss 6.38%) and oxidation of metallic species accompanied by decomposition
nitrates, sulphates and phosphates resulting in evolution of gaseous moieties
(Residue 82.07% at 919.62 ºC) (Bauer et al., 2009). This kind of almost linear behavior
is consistent with earlier studies (Akbar et al., 2007). Overall both the samples showed
high stability. The results of the residue obtained in both the cases are in accordance
with a loss on ignition and ash content studies performed earlier.
Chapter Four Results and Discussion
82
Figure 4.9: TGA (black line) and DSC (blue line) spectra of ZNC showing
incremental weight loss.
DSC curves of NZ and ZNC are given in Figure 4.8 and 4.9 which are
characterized by having dehydroxlation endotherms in range of 50-600 oC with first
low temperature peaks appearing around 100̊C in both samples other shallow peak
appears with minima at 596.30oC corresponding to △H=87.83 J/g for NZ.
In case of ZNC another high temperature board endothermic peak with minima
at 920 oC with high △H= 825.21 J/ g value which probably accounts for decomposition
of non-metallic moieties.
4.2.9 Salt Index
Salt index (SI) is also calculated to assess the probable potential of prepared
fertilizer to cause plant injury; higher the value higher the potential to cause plant
damage leading to less crop yield. The acceptable range for SI is terms of electrical
Chapter Four Results and Discussion
83
conductivity should be less than 2 mmhos/cc (Company, 1996) which in our case for
ZNC comes around 0.5 mmhos/cc. The SI in terms of ratio to NaNO3 (taken as 100)
conductivity comes out to be very low for both the NZ and ZNC, when compared with
urea which has very high SI value. The low value exhibits that the prepared fertilizer
is safe for plant use and is also suitable for the seed row placement in agriculture,
hence can result in high yield crops as well (Gowariker et al., 2009).
4.2.10 Water absorbance (WA), swelling ratio (SR) and equilibrium water content
(EWC) determination
Water absorbance (Wu et al., 2008), the swelling ratio (Bortolin et al., 2013)
and equilibrium water content (He et al., 2007) are essential features for the SRF. The
results of an experiment for NZ and ZNC for all these three parameters were 49%,
63%; 3.28, 3.53 g/g and 76.63, 77.92%, respectively. A small increase in all the three
parameters was observed in case of ZNC as compared to NZ. Zeolite, in general, has
high porosity due to which it can hold water more than half of the weight. Water can
penetrate into the porous structure of ZNC and provides moisture to plants in dry areas
to improve yield (Ramesh et al., 2010). In addition to that presence of water also
enhances the slow release of nutrients to the crops on other hand (Wu et al., 2008).
4.2.11 Water retention (WR)
Water retention is considered as an important feature for SRF and is essential
for agriculture in arid and desert area for saving water to improve growth of plants
(Liang and Liu, 2006). The water holding capacity of ZNC mixed with soil and soil
without ZNC as a control is shown in the Figure 4.10. The soil mixed with ZNC has
water retention capacity of 94.04 and 69.14% on the 3rd and 20th day, respectively,
while soil without ZNC indicated the values of 75.01 and 55.5%, respectively for the
same property. The rate of water retained in case of soil alone is approx. 18% less
than that of soil + ZNC as zeolite can retain the higher capacity of water which is in
accordance with the absorbency studies. This retained water helps in enhancing water
availability to the soil as this water can be released back to the soil as per requirement
of soil and plant (Ramesh et al., 2011).
Chapter Four Results and Discussion
84
Figure 4.10: Water retention capacity of control (soil without ZNC) and of soil
with ZNC.
Each value represents the mean ± S.E of three replicates.
4.2.12 Slow Release Studies
The slow release studies were conducted both in tap water (Figure 4.11) and
in soil (Figure 4.12) separately in order to check the impact of water and soil on the
slow release pattern. In both the cases, the data are expressed as a percentage of
nutrient released out of total available nutrients present in ZNC (Figure 4.6). The data
were presented with standard deviation as the mean of three values. These
measurements facilitate in getting know-how about the exact release of specific
nutrients present in the fertilizer and also their availability to the plant on daily basis.
These kinds of studies were an acceptable approach for selecting the suitability of
40
50
60
70
80
90
100
0 2 4 6 8 10 12 14 16 18 20 22
Wate
r R
ete
ntion (
%)
No. of days
Control( soil without ZNC)
Soil with ZNC
Chapter Four Results and Discussion
85
fertilizer to a crop as reported in the literature (Costa et al., 2013; Pereira et al., 2012).
7-day release studies performed only in pre-analyzed tap water as in Table 4.2.
Table 4.2: Results of water analysis
No. Parameters Units Results
1 pH 7.8
2 Conductivity (µs/cm) 590.50
3 Total Dissolved Solids (TDS) (mg/L) 413.3
4 Total Hardness (TH) (mg/L) 0.7
5 Calcium (Ca2+ ) (mg/L) 0.36
6 Magnesium (Mg2+) (mg/L) 0.34
7 Chloride (Cl1-) (mg/L) 17.75
8 Sodium (Na1+) (mg/L) 2.1
9 Potassium (K1+) (mg/L) 1.0
10 Phosphate (PO42-) (mg/L) 2.4
11 Nitrate (NO32-) (mg/L) 0.9
The results are presented in Figure 4.11, showed a set pattern for release of
nutrients i.e. NO32-, PO4
2-, K2O, Na2O, Fe2+/3+ and Mg2+ i.e. initially the release was
little faster which decreased with the time period except for magnesium and nitrate. In
case of magnesium gradual decrease in the percentage of release was observed with
increase in time while for nitrate the incremental increase with an increase in time was
noticed.
Chapter Four Results and Discussion
86
Figure 4.11: Slow release pattern of doped nutrients in tap water for seven days studies from ZNC.
Each value represents the mean + S.E of three replicates.
Results of nutrient release pattern in soil (Figure 4.11) showed the almost same
trend as was observed in case of tap water but the concentration of nutrients released
is little higher than that in water. The results were well in accordance with previous
studies carried out and the trend observed favors continues supply of nutrients to
plants thereby preventing leaching loses that are commonly observed with tradition
fertilizers (Costa et al., 2013)
This type of trend i.e. availability of high nutrient content in start also supports
early seed sprouting and germination of the plant which facilitates the growth of the
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
0 1 2 3 4 5 6 7 8
Re
lea
se
d a
mo
un
t o
f n
utr
ein
ts (
%)
Chapter Four Results and Discussion
87
healthy plant. After the initial high dose to the plant, continues release supplied by
ZNC helps in early flowering and fruiting leading to high yield crops. The similar trend
has also been observed in previous studies (Khan et al., 2008).
Figure 4.12: Slow release pattern of doped nutrients in soil for 14 days studies
from ZNC.
Each value represents the mean + S.E of three replicates.
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 2 4 6 8 10 12 14 16
Rele
ased a
mount of
nutire
nts
(%
)
No. of days
Chapter Four Results and Discussion
88
4.3 Synthesis and Characterization of Biochar based Nano-
composite
4.3.1 Synthesis of corncob biochar (CB) and biochar based nano-composite
(BNC)
Pyrolysis approach was followed to prepare CB, which was used as support
material. In which impregnation of macro and micro nutrients occurred that finally
resulted in BNC. CB had a porous structure (Budai et al., 2014) which supports and
facilitates the impregnation of nutrients. Earlier studies had also shown the potential
of biochar to store nutrients by either chemisorption or physiosorption (Ding et al.,
2016). Therefore, this property of biochar can be exploited to use this as slow release
fertilizer, as it not only improves soil quality but also ensures the availability of nutrients
to plants for a prolonged period of time.
4.3.2 Physical and proximate analysis
The physical and proximate analysis was performed to determine moisture
content, ash, volatile organic matter (VOM), fixed carbon, pH, conductivity, bulk and
tap densities, and cation exchange capacity (CEC) for CB and BNC; the results are
presented in Table 4.3. Moisture content, ash, VOM and fixed carbon values of CB
and BNC calculated in the current case (Table 4.3) are in accordance with the previous
work (Liu et al., 2014). The small changes were usually observed owing to the
differences in process temperature, conditions and feedstock material (Mukome et al.,
2013; Zornoza et al., 2016).
There was a slight decrease in pH of CB after composite formation shifting from
slightly alkaline (8.46) value to nearly neutral pH i.e. 6.79 which makes it suitable for
agriculture use (Dume et al., 2016). The marginal increase in conductivity of BNC from
1843.46 to 1856.62 µS cm-1 supported the fact of metals/ metal salts incorporation
into the BNC structure. This absorption of salts also gave rise to both tap and bulk
densities. CB had cation exchange capacity (CEC) of 149 meq /100 g while BNC had
197 meq /100 g which are in line with previous studies, reported by Sasai et al., (2004).
Chapter Four Results and Discussion
89
Table 4.3: Proximate and Physical Analysis of CB and BNC
No Parameters Unit CB BNC
1. pH 8.46 6.79
2. Moisture Content (%) 5.38.46 6.98
3. Conductivity at 25 oC (µS/cm) 1843.4 1856.6
5. Ash content (%) 3.61 4.49
6. Volatile Organic Matter (%) 8.6 9.5
7. Fixed Carbon 79.33 79.22
8. Bulk density (mg/m3) 0.27 0.31
9. Tap density (mg/m3) 1.8 2.1
10. Cation Exchange Capacity(CEC) (meq.100/ g) 149 197
4.3.3 Fourier transform infrared spectroscopy (FT-IR)
The FT-IR spectra of CB and BNC were provided information about the
functional groups of structure (Figure 4.13 A and B). Comparison of FT-IR spectra of
CB and BNC showed peaks in the range of 3600-3400 cm-1 due to stretching of
hydroxyl bond (-OH), which might be due to moisture content as it was confirmed by
physical parameters. Peaks arising at 1591 cm-1 represented stretching of the
aromatic ring (C=C), and the peaks at 1230, 1162 and 1035 cm-1 correspond to
vibrations and stretching of C=O bond (Mukome et al., 2013; Zhang et al., 2014;
Zornoza et al., 2016). Peak shift occurred in case of BNC to 1597, 1154 and 1034 cm-
1 positions affirmed incorporation of nutrients in CB structure (Figure 4.13B)
(Nurhidayati and Mariati, 2014; Sohi et al., 2010).
Chapter Four Results and Discussion
90
Figure 4.13: FT-IR spectra of CB (A) and BNC (B) representing a shifting of peaks in BNC, which affirms the
adsorption of nutrients.
Chapter Four Results and Discussion
91
4.3.4 Powder X-ray diffraction (XRD)
Powder XRD diffractogram of CB and BNC scanned in the range of 2θ = 5 -
80º, presented in Figure 4.14, depicted that material has high carbon content as in
(Figure. 4.14A) with low intensity peaks arising at 2θ values of 26.62º, 42.82º, 49.99º
and 61.59º as in literature (Yu et al., 2014; Zornoza et al., 2016). The BNC
diffractogram (Figure. 4.14B), when compared with CB characterizes that basic
structure of CB remains same, a slight phase change was observed in intensities
because of nutrient adsorption into CB.
4.3.5 Scanning electron microscopy (SEM)
SEM gives information about the morphology of synthesized samples (CB and
BNC). The images of CB (Figure 4.15) taken at different resolutions of 5 µm and 1µm
represented the porous structure of CB. Pores augmented the surface area and
enhanced the adsorption capacity of CB by providing more sites for chemical reactions
(Lehmann, 2007; Yu et al., 2014). The factors like pyrolysis temperature and
conditions depicted the final composition of biochar in addition to its source (Spokas,
2010b).
Chapter Four Results and Discussion
92
Figure 4.14: Powder XRD Diffracto-gram of CB (A) and BNC (B).
Chapter Four Results and Discussion
93
Figure 4.15: SEM images of CB at resolutions of 5 µm (A) and 1µm (B),
respectively, showing the porous structure of CB.
Chapter Four Results and Discussion
94
The porous structure of synthesized CB remains same and white color coating
on the surface of CB represented the doping of salts into CB as shown in Figure
4.16(A). The SEM image also demonstrated the distribution of round shape particles
(Figure 4.16 (B)), which was affirmed by the AFM image (Figure 4.16).
Figure 4.16: SEM images of BNC at resolutions of 5 µm (A) and 1µm (B), respectively, showing rounded particles and white color represents the
impregnation of nutrients.
Chapter Four Results and Discussion
95
4.3.6 Energy dispersive x-ray spectroscopy (EDX)
The EDX analysis of CB (Figure 4.17) showed the elemental percentage weight
of carbon (C), oxygen (O) and nitrogen (N), which varied due to pyrolysis temperate,
time of reaction and substrate. The results obtained from CB are consistent with the
earlier findings (Budai et al., 2014).
Figure 4.17: EDX spectra showing elemental composition of corncob biochar
(CB)
The EDX spectra of BNC (Figure 4.18) confirmed the impregnation of macro
and micro nutrients into the CB structure. The variation in this wt. % can be attributed
to the affinity of these ions with the carbon structure and organic moieties present as
suggested by FT-IR (Figure 4.13).
Figure 4.18: EDX spectra of BNC represents the detailed composition of doped
micro and macro nutrients.
Chapter Four Results and Discussion
96
4.3.7 Atomic force microscopy
Atomic force microscopy (AFM) is considered as a versatile technique to
determine the roughness, distribution, shape and size of particles directly because it
enables the atomic level imaging. The shape and particle size of the BNC was
measured using AFM by taking both 2D and 3D images (Figure 4.19 A & B). The 2D
image (Figure 4.19A) points towards the random distribution of particles in size range
of 10-55nm with the majority of particles having a size of 55.6nm as confirmed from
the 3D image (Figure 4.19B). The particles were found round in shape as affirmed
from SEM (Figure 4.16).
Figure 4.19(A): 2D image represents the narrow distribution of particles
Chapter Four Results and Discussion
97
Figure 4.19(B): 3D AFM images confirms the size of BNC
4.3.8 Thermal gravimetric analysis (TGA)
Thermal stability of prepared samples (CB and BNC) was determined by
TGA/DSC analysis. The interlinked spectra of TGA and DSC are presented in Figure.
20 and 21. The thermogram of CB (Figure 4.20) was characterized by steady weight
loss with three non-distinctive steps after which constant decrease in weight was
observed.
The first peak at 147.52 C (Wt. loss 94.54%) was probably due to loss of
moisture, as affirmed by the proximate analysis while second (335.13 C; wt. loss
82.63%) and third peak (481.25 C; wt. loss 63.85%) accounted to pyrolytic
decomposition stage, where maximum mass loss occurred due to emission of gases
(like CO2, CO and CH4) and decomposition of organic compounds (Neves et al.,
2011). After this stage, a constant but slow decline in the spectra was observed which
resulted in 50.59% residue.
Chapter Four Results and Discussion
98
This steady weight loss usually occurred in the carbonization stage, where
thermal decomposition of solid matter (char and inorganic matter) took place leading
to the conversion of biomass to solid biochar which had stable carbon (Liu et al., 2014;
Yu et al., 2014).
Figure 4.20: TGA thermogram (black line) and DSC curve (blue line) depicting
thermal stability of CB
Almost same trend of degradation was observed in BNC thermogram (Figure
4.21) with slight changes at peaks (159.04 °C, wt. 96.37%; 321.14 °C, wt. 83.89%;
451.91 °C, wt. 64.84% and 978.71 °C, wt. 42.66%) compared with CB, represented
the incorporation of doped salts. In short, thermal studies demonstrated the thermally
stable nature of both CB and BNC. DSC curve also indicated the similar trend with
continual change in energy referring to the exothermic loss which was in accordance
with earlier findings (Shang et al., 2015).
Chapter Four Results and Discussion
99
Figure 4.21: TGA thermogram (black line) and DSC curve (blue line) describing
the thermal stability of BNC.
4.3.9 Salt index (SI)
SI measures the probability of synthesized fertilizer to cause plant injury. When
compared with an acceptable tolerable range of SI i.e. 2 mmhos cc-1 (in terms of
conductivity; reference to NaNO3 taken as 100), the BNC value came out to be much
lower (0.08 mmhos cc-1) making it suitable for plant use and consequently for
sustainable agriculture (Gowariker et al., 2009). A higher value of SI in fertilizer is
known to cause damage to plants and lead to less crop yield.
Chapter Four Results and Discussion
100
4.3.10 Water Absorbance (WA), Swelling Ratio (SR) and Equilibrium Water
Content (EWC)
The results of an experiment for CB and BNC are given in Table 4.4 from which
it can be observed that there was a small increase in the values of WA, SR and EWC
as compared to pure biochar. In general, CB was characterized to have the highly
porous structure (Shariff et al., 2016) that can physically adsorb water to be later on
released to soil or plants especially in arid areas (Baiamonte et al., 2015; Ding et al.,
2016; Liu et al., 2014).
Table 4.4 Properties of the prepared samples as applicability for the slow
release fertilizer
No Properties CB BNC
1. WA (%) 64 68
2. SR (g.g-1) 3.56 4.66
3. EWC (%) 78.07 82.33
4.3.11 Water Retention (WR)
Water retention is considered as an important feature for SRF and is essential
for agriculture in arid and desert area for saving water to improve growth of plants
(Liang and Liu, 2006).The graph of water retention (WR) is represented in Figure 4.22,
that showed the water holding capacity of the control (i.e. soil without BNC) and
experimental sample (i.e. soil mixed with BNC). Usually, WR decreases with time as
was the case in both control and soil + BNC. But soil + BNC had higher WR capacity
throughout the experimental span of 20 days. The soil + BNC and control had WR
capacity of 93.78 and 76.33; 76.08 and 67.17 and 62.03 and 55.5% on 2nd, 10th and
20th day, respectively. The rate of water retained in case of soil alone is approx.
16.02% less than that of soil + BNC as corncob biochar can retain the higher capacity
Chapter Four Results and Discussion
101
of water which is in accordance with the absorbency studies. Hence, the retention of
water helps in providing water to soil and subsequently to plants (Dugan et al., 2010).
Figure 4.22: Water retention capacity of control (soil without BNC) and of soil
with BNC.
Each value represents the mean + S.E of three replicates.
4.3.12 Slow Release Studies
Slow release pattern of synthesized BNC was studied in both tap water (Figure
4.23) and soil (Figure 4.24), separately to monitor the release behavior of nutrients.
The experiments were conducted in a set of three replicates to avoid error. The data
were averaged out and presented in percentage of the total nutrients in BNC (Figure
4.23). The results helped in interpreting the release behavior of specific nutrients
which can assist in determining fertilizer suitability for specific crops (Li, 2003;
Manikandan and Subramanian, 2015).
Seven days release studies were conducted in tap water that was previously
analyzed (Table 4.2). The release of nutrients from BNC can be influenced greatly by
pore size, the binding capacity of ions and adsorption level (Manyà, 2012). In general,
0
20
40
60
80
100
120
0 2 4 6 8 10 12 14 16 18 20 22
Wate
r R
ete
ntion(%
)
No. of Days
Contol
Soil + BNC
Chapter Four Results and Discussion
102
the release of macro (NO31-, P2O5, K2O, Mg2+, Ca2+) and micro (Fe2+/3+, Zn2+, Na2O)
nutrients presented in Figure 4.23, was slower in the beginning which gradually
increases to almost constant value at the end of the experiment.
Figure 4.23: Release pattern of doped nutrients for 7 days in tap water from
BNC.
Each value represents the mean + S.E of three replicates.
The nutrient release studies in soil were carried out for 14 days (Figure 4.24)
presented the same trend as determined in tap water studies apart from that release
of nutrients was slightly faster than in water. The release of nutrients (Mg2+, Ca2+,
Fe2+/3+, Zn2+, Na2O, K2O) till the 5th day was slow then gradually increased till 14th day
while in case of NO31- and P2O5 the release was faster till 5th day which then became
stable. Biochar has high nitrate adsorption capacity (Ding et al., 2016) and low for
independent phosphorus, so phosphorus can be enhanced by some organic matter
or by available cations in soil (Xu et al., 2014).
-0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0 1 2 3 4 5 6 7 8
Re
lea
se
d a
mo
un
t o
f n
utr
ien
ts (
%)
No. of Days
Chapter Four Results and Discussion
103
The trends observed can help in continued supply of nutrients to plants as per
their requirement and prevent leaching of nutrients, when compared to conventional
fertilizers (Costa et al., 2013). CB absorbs nutrients because of its high surface area
and porosity and physiochemical binding that ensures reduced leaching of nutrients
(Steiner et al., 2008) thereby facilitating enhanced plant growth (Hunt et al., 2010). All
these reasons favor the use of biochar for enhancing soil fertility and increasing plant
growth. Thus, initially the nutrients supplied by the BNC can enhance the seed
germination which ultimately improves an appropriate number of plants per unit area
growth of plants and ultimately yield.
Figure 4.24: Release pattern of doped nutrients for 14 days in soil from BNC.
Each value represents the mean + S.E of three replicates.
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
0 2 4 6 8 10 12 14 16
Re
lea
se
d a
mo
un
t o
f n
utr
ein
ts (
%)
No. of Days
Chapter Four Results and Discussion
104
4.4 Greenhouse Experiment Series
The third objective of this research work was to study the effects of both
synthesized nano-composites and conventional fertilizers on germination, growth rate
and yield components of wheat. The germination studies were conducted in
Greenhouse of Institute of Agricultural Sciences (IAGS), University of the Punjab,
Lahore while field trials were done in Research area of Pakistan Council of Scientific
and Industrial Research (PCSIR), Laboratories Complex, Lahore for two years (2014-
2016) to determine the impacts on selected parameters.
4.4.1 Germination studies
The comparative effects of nano-composites (ZNC and BNC) and conventional
fertilizers (Urea and NPK) on wheat germination parameters i.e; time for 50%
germination (T50), mean germination time (MGT), final germination percent (FGP) and
germination index (GI) that are presented in Table 4.5.
The values of T50 for five treatments were between 4.81 and 5.03. The highest
values were obtained for ZNC and BNC as compared to NPK, Urea and control.
Similar trends were observed in results of FGP and GI while in case of MGT, the
results of NPK were close to control treatment, but lower than ZNC, BNC and urea
fertilizer. Overall, the higher values for germination parameters were seen in ZNC and
BNC, then NPK, urea and the lowest was in control (Table 4.5).
As depicted from literature, zeolite serves as an excellent growth medium for
the plant growth because of its unique property of CEC. Zeolite released their nutrients
slowly that coincides with the plant need (Subramanian and Rahale, 2012). Although,
the addition of biochar also improves the germination of wheat when added to the soil
(Solaiman et al., 2012).
Chapter Four Results and Discussion
105
Table 4.5: Effect of Different treatments on germination parameters of Wheat
Means were separated using least significance difference (LSD) at 0.05% level: value bearing the same letters are not statistically different. T50= Time for 50% germination, MGT= mean germination time, FGP= final germination percent, GI= germination index, Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
Thus, the application of nano-composites (ZNC and BNC) significantly
improves the wheat germination indices than the use of conventional fertilizers
specified progressive influence on the plant growth. This is in agreement with the
findings of Amirnia et al. (2014).
Both ZNC and BNC had a significant influence on the shoot and root lengths
as compared to NPK, urea and control (Figure 4.25). The maximum shoot length was
recorded in BNC treatment (23.34cm) followed by ZNC (23.14cm), then NPK
(17.24cm), urea (16.51cm) whereas, minimum shoot length was observed in control
treatment (14.65cm) in both the years. The 59.3% and 57.9% increase in shoot length
of plants, respectively, treated with BNC and ZNC were observed as compared to
control. Whereas almost same trend was observed in root length, BNC (6.37 cm)>
ZNC (5.58 cm)> NPK (4.81 cm)> control (3.37cm) while urea (2.82 cm) had the lowest
value (Figure 4.25).
Treatments T50 MGT FGP GI
Control 4.81±0.03b 7.33±0.33bc 51.12± 2.23b 23.55c
Urea 4.84±0.05b 8.33±0.33ab 60.09±3.84ab 25.97c
NPK 4.99±0.03a 7.66±0.33bc 66.66±3.84a 32.36b
ZNC 5.03±0.03a 9.01±0.01a 71.10±4.44a 39.81a
BNC 5.00±0.05a 8.89±0.03a 70.12±7.99a 39.86a
Chapter Four Results and Discussion
106
Figure 4.25: Comparative effects of different treatments on shoot and root
length of wheat.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
The mean values of shoot and root length were corroborating with the reported
results of Shah and Belozerova (2009), who studied the effect of metal nanoparticles
on the germination of lettuce seeds. Similarly, the nanomaterials (TiO2) have also
pronounced effect on the wheat germination as well as on the seedling emergence,
shoot length and dry matter (Feizi et al., 2012).
The fresh and dry weights of shoot and root were found in a similar way to their
respective lengths. The highest value of both shoot fresh and dry weight was observed
in an order of control ˂ urea ˂NPK ˂ BNC˂ ZNC (Figure 4.26). Since the nano scale
c
bb
a a
bcc
abc aba
0
5
10
15
20
25
30
control urea NPK ZNC BNC
Le
ng
th (
cm
)
Shoot length (cm)
Root length (cm)
Chapter Four Results and Discussion
107
nutrients can easily penetrate into roots and translocate to stem, so they had a positive
effect on the fresh and dry weight of both shoot and root. These results aligned with
the earlier studies, which revealed that TiO2 nanoparticles under elevated CO2
concentrates promoted the wheat growth and biomass (Jiang et al., 2017).
Figure 4.26: Comparative Effect of different treatments on the shoot and root fresh and dry weight of wheat.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
Statistically, similar number of leaves were prevailing irrespective of treatments
but leaf area index (LAI) was significantly different (Figure4.27).The LAI observed the
order ZNC (3.5) > BNC(3.09) > urea( 2.81)> NPK(2.81) > control (2.18) .The Leaf
area has a significant influence on growth and is considered an important component
for determination of crop growth (Rouphael et al., 2006).
The leaves of plants under urea and control treatments appeared lacking vigor
and luster than the leaves of plants under treatments of ZNC and BNC. Timely and
ab bab
a
ab
bc c ab a abb b
a a a
a a a a a
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
control urea NPK ZNC BNC
we
igth
(g/ p
lan
t)
Shoot fresh weight (g)
Shoot dry weight (g)
Root fresh weight (g)
Root dry weight (g)
Chapter Four Results and Discussion
108
sufficient availability of nutrients to the plants determines plants appearance including
luster. The nanoferitilizers can easily penetrate into plant seeds, move through plant
cells due to their small size and enhance the growth of plants (Corredor et al., 2009).
As reported that TiO2 nanoparticles enhance plant biomass and improve the
biochemical reactions and photosynthetic activity in leaves of wheat (Feizi et al.,
2012).
Figure 4.27: Comparative effect of different treatments on number of leaves and leaf area index of wheat
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
Consequently, the findings of the greenhouse experiment revealed that both
nano-composites have marked influenced on the germination indices as well as
enhanced the plant growth and development. Pronounced effects were observed on
the shoot and root length, the fresh and dry weight of shoot and root, number of leaves
and on LAI.
ab b abab
a
c
bc bc
a
a
0
0.5
1
1.5
2
2.5
3
3.5
4
control urea NPK ZNC BNC
No.of leafs
Leaf area index(LDI)
Chapter Four Results and Discussion
109
4.5 Field Trials
After completion of greenhouse experiment, the field trials were conducted for
two consecutive years (2014-2016) in PCSIR research field using randomized
completely block design (RCBD) with three replicates of each treatment
4.5.1 Morphological and yield related traits
4.5.1.1 Plant height
Plant height, considered as an indicator of growth, is affected by the application
of different fertilizers hence in this study also the height of wheat plants was monitored
from the first day of germination till harvestation of the crop on weekly basis to assess
the health of the crop. The collected data is presented in Figure 4.28 for the period of
two years.
The results revealed that effect of nano-composites (ZNC and BNC) on the
height of plant was significant in both the years when correlated with other treatments.
The nano-composites improved plant height as compared to conventional fertilizers
as well as a control treatment. The plant height observed the order ZNC > BNC > NPK
> urea > control (Figure 4.28). Considerable growth intensification in terms of plant
height i.e. 18.9% and 15.7% for plants treated with ZNC and BNC was noticed in the
first year, respectively, as compared to control; whereas for same 16.1% and 12.3%
increases in plant height was recorded for the second year.
Greenhouse experiments, performed on nano-zeolite treated maize plant, have
also shown the congruent effect on plant height which was attributed to easy and early
penetration of nanomaterials into the seeds ensuring enhanced availability of nutrients
leading to their early sprouting (Manikandan and Subramanian, 2016). Similar
observations were reported by Zheng et al. (2005), which directly related to the
nanomaterials application with improved germination, early seedlings’ emergence and
enhanced plant growth. Moreover, the application of engineered nanocomposite
containing N, P, K and micronutrients can speed up the grain crops growth owing to
their easy absorption (Abdel-Aziz et al., 2016).
Chapter Four Results and Discussion
110
Figure 4.28: Effect of different treatments on the plant height of wheat for two
consecutive years.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
4.5.1.2 Shoot fresh and dry weight
Shoot weight is an aggregate of leaves and stem. Leaves are vital for light
interception and CO2 assimilation whereas stem provides support to leaves as well as
acts storehouse of photo assimilation. The fresh and dry weights of the shoot were
recorded at the harvestation stage for the years 2014- 2015 and 2015-2016 (Figure
4.29 and 4.30) which depicted the significant impact of nano-composites (ZNC and
BNC) on shoot fresh and dry weights when compared with other treatments for both
the years under study.
The maximum shoot fresh weight was observed in ZNC treatment (15.78 and
16.73 g/plant) followed by BNC (14.37 and 15.45 g/plant), then NPK (13.46 and 14.86
cc
c c
b b
a
aa
ab
0
20
40
60
80
100
120
2014-15 2015-16
Pla
nt h
eig
ht (c
m)
Control
Urea
NPK
ZNC
BNC
Chapter Four Results and Discussion
111
g/plant), urea (12.13 and 13.71 g/plant) and minimum shoot fresh weight was
observed in control treatment (10.88 and 12.43 g/plant). In contrast, to control nano-
composites greatly impacted the shoot fresh weight in cases of ZNC and BNC i.e.
45.12%; 32.01% and 34.59%; 24.29%, respectively for year 1 and 2(
Figure 4.29).
Figure 4.29: Effect of different treatments on the shoot fresh weight of wheat for two consecutive years.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
Similar results were revealed for dry shoot weight (Figure 4.30) which
significantly increased in case of ZNC (13.10 and 12.84 g/plant) and BNC (12.40 and
14.86 g /plant) as compared to NPK (11.23 and 11.96 g/plant), urea (10.53 and 10.48
g/plant) and control (8.76 and 9.67 g/plant) for first and second years, respectively
which is in accordance with earlier researches on wheat (Mahmoodzadeh et al.,
2013).
d
ec
dbc
bc
a
a
b
ab
0
2
4
6
8
10
12
14
16
18
2014-15 2015-16
Sh
oo
t fr
esh w
eig
ht(
g/p
lant)
Control
Urea
NPK
ZNC
BNC
Chapter Four Results and Discussion
112
Figure 4.30: Effect of different treatments on the shoot dry of wheat for two consecutive years.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
This aboveground biomass increase also supports the fact that nano-
composites promote timely availability of nutrients to the growing plant tissues (Du et
al., 2015; Pickering et al., 2002). Earlier studies relate this increase in weight to various
factors like elevated levels of organic components like proteins, chlorophyll, phenols
etc. (Siddiqui and Whaibi, 2014) or to enhanced uptake of water content that further
facilitates the nanomaterials uptake and absorption by the plant (Haghighi and
Pessarakli, 2013).
4.5.1.3 Number of tillers and productive tillers per plant
The yield of wheat is described in terms of a number of tillers produced. For
this purpose, the number of tillers per plant was monitored from the start of vegetative
stage till the end of the reproductive stage. The same pattern of counting was
c
e
b db
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2014-15 2015-16
Sh
oo
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/pla
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NPK
ZNC
BNC
Chapter Four Results and Discussion
113
observed for both the years studied under research tenure. The data obtained are
presented in Figure 4.31. The results depicted the positive influence of nano-
composites (ZNC and BNC) on number of tillers per plant when compared with rest of
the three treatments. The data itself is well in accordance when same treatments are
compared between the years. The percentage increase of 39.01% in number of tillers
per plant of both ZNC and BNC were at par, followed by NPK (23.09%) and urea
(7.62%) over the control in the first year. While in the second year, more number of
tillers were found in BNC (38.04%) than in ZNC (31.21%) as compared to control
(Figure 4.31).
Figure 4.31: Effect of different treatments on number of tillers per plant of wheat for two consecutive years.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
Almost similar trend was observed in number of productive tillers per plant in
both years as in number of tillers, which represented an increase of 30.43% and
43.47% in number of productive tillers were observed in ZNC and BNC treatments in
the first season, respectively as compared to the control. Whereas in the second
season 32.61% and 27.29% increase in number of productive tillers were recorded
for ZNC and BNC, respectively (Figure 4.32). As already discussed that the yield of
ccdd
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2014-15 2015-16
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Chapter Four Results and Discussion
114
wheat is directly linked to the number of productive tillers. Therefore, it can be
concluded safely that quantity and quality of wheat yield are significantly affected by
the type of tillers (Xu, 2015).
According to Fischer (2008), tillers can contribute up to 70% in the grain yield
of wheat. The development of tillers is greatly influenced by number factors like water,
light and availability of nutrients in the soil (Elhani et al., 2007). The growth and
development of both productive and non- productive tillers were significantly impacted
by a deficiency of nutrients that can be improved by the application of fertilizers
(Kondić et al., 2017). It was well noted that productive tillers appeared early on plants
treated with nano-composites as compared to urea, NPK and control which resulted
in the early maturity of the wheat crop and reduction in the life span of the crop; results
are in line with earlier findings (Abdel et al., 2016).
Figure 4.32: Effect of different treatments on number of productive tillers per plant of wheat for two consecutive years.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
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2014-15 2015-16
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BNC
Chapter Four Results and Discussion
115
4.5.1.4 Spike length and number of spikelet per spike
The spike length and number of spikelet per spike vary plant to plant and
interconnected with the crop yield. The length of the spike (cm) and number of spikelet
per spike were recorded at the time of harvest and results are presented in Figure
4.33.
Figure 4.33: Effect of different treatments on spike length and number of
spikelet per spike of wheat for two consecutive years.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
The results showed that effect of nano-composites (ZNC and BNC) on spike
length as well as no. of spikelets per spike was significantly different in both the years
when compared with other treatments. On average the data for two years for the four
treatments followed the order: ZNC (19.68%) > BNC (18.34%) > NPK (7.24%) > urea
(2.69%) for spike length. In case of number of spikelet per spike slightly different trend
was observed in which BNC (22.19%) showed better percent increase than ZNC
(13.71%) when compared with control. Also, the results (Figure 4.33) for NPK and
c
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Spike length(cm) No. of spikelet/Spike
Spike Length(cm) No. of Spikelet/Spikes
2014-15 2015-16
Control
Urea
NPK
ZNC
BNC
Chapter Four Results and Discussion
116
control observed to be similar which revealed to be greater than the ones obtained for
urea treated plants. The data gathered clearly showed the lesser efficiency of urea
concordantly lead to less nutrient availability and hence less number of productive
tillers. On contrary the better and ready nutrient uptake in case of nano-composites
and also for a longer period of time enhances the nutrient availability as per plant
requirements leading to higher spikelet growth (Servin et al., 2015).
4.5.1.5 Number of grains per spike
The number of grains per spike determines the yield of crop and it varies from
plant to plant. Number of grains were counted in each spike of randomly selected
plants from each replication of every single treatment. Moreover, the number of grains
per spike is presented in Figure 4.34 for both the years.
Figure 4.34: Effect of different treatments on number grains per spike of wheat
for two consecutive years.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite
b bb
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a aa
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2014-15 2015-16
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rain
/ sp
ike
Control
Urea
NPK
ZNC
BNC
Chapter Four Results and Discussion
117
The results depicted that influence of nano-composites (ZNC and BNC) on
number of grains per spike was significantly different in both the years. The higher
number of grains was observed in ZNC treatment (41.69) followed by BNC (48.9),
then NPK (41.0), urea (39.33) and lowest number was observed in control treatment
(37.87) in the first year while higher number of grains were found in BNC (51.3)
followed by ZNC (50.6), NPK (43.2) then urea (40.6) and lowest in control (38.9). Even
the increase of 31.15% and 26.74% in number of grains were observed in ZNC and
BNC treatments in the first season, respectively as compared to the control (Figure
4.34). Whereas in the second season 31.18% and 30.6% increase in number of grains
were recorded for BNC and ZNC, respectively. The more the number of grains in
spikes attributed to batter yield of the crop. The ZNC had marked influence on the
number of spikelet per spike and number of grains per spike as results of this research
are in line with results of Chisba, et al, (2017). Similarly, the biochar addition also
improves the number of grains of wheat affrims the results as reported in the literature
(Gebremedhin et al., 2015).
4.5.1.6 1000 grain weight
The 1000 grain weight is a key factor in determining the final grain yield. The
wheat variety, environmental conditions and fertilization are a major factor which can
affect the weight of 1000 grains. The results of 1000 grain weight are presented in
Figure 4.35.The results demonstrated that effect of nano-composites (ZNC and BNC)
on 1000 grains weight was significant for both the years. The maximum weight of 1000
grains was observed in ZNC treatment (35.44g) followed by BNC (34.96g), then NPK
(32.45g), urea (30.89g) and lowest number was observed in control treatment
(28.24g) in the first year while maximum grain weight was found in BNC (34.37g)
followed by ZNC (33.56 g), NPK (27.18g) then urea (26.58g) and lowest in control
(23.43 g) in second year.
The increase of 27.80% and 25.49% in number of grains were observed in ZNC
and BNC treatments in the first season, respectively as compared to the control.
Whereas in the second season 35.18% and 32.06% increase in number of grains were
Chapter Four Results and Discussion
118
recorded for BNC and ZNC, respectively (Figure 4.35). The grain yield increases due
to the addition of nanomaterials similar results were found in case of rice when slow
release nanofertilizers was applied as compared to the control which supports the
results of the current study (Kavoosi, 2007; Leggo, 2000).
Figure 4.35: Effect of different treatments on 1000 grains weight of wheat for two consecutive years.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite
4.5.2 Biomass yield (tons/ha)
Biological yield represents the total above ground dry matter of a plant at the
time of harvest. It is the sum of straw and grain yield of wheat (Sadeghzadeh and
Alizadeh, 2005). The biomass yield for all treatments of two years presented in Figure
4.36. The results depicted that biomass yield was not significantly different for all
treatments. The maximum biomass yield was recorded for ZNC (15.79 tons/ ha)
followed by BNC (14.54 tons/ ha), NPK (13.30 tons/ ha), urea (12.98 tons/ ha) and
lowest for control treatment (11.14 tons/ ha) in first year. While in the second year,
BNC (15.80 tons/ ha) had highest biomass yield then ZNC (14.33 tons/ ha), NPK
a
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2014-15 2015-16
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NPK
ZNC
BNC
Chapter Four Results and Discussion
119
(13.65 tons/ ha) urea (11.73 tons/ha) and minimum were obtained in case of urea
(10.91 tons/ ha).
The increase of 41.74% and 30.52% in biomass yield was observed in ZNC
and BNC treatments in the first season, respectively as compared to the control.
However, in second season 31.34% and 44.79% rise in biomass yield were noted for
BNC and ZNC, respectively (Figure 4.37). The wheat variety and fertilizer application
are important factors which can influence the biomass yield. The increase in biomass
yield occurred in wheat due to the positive influence of nano-composites (ZNC and
BNC) on the absorption of nutrients by roots and easily translocation to stem, leaves
which enhanced the photosynthetic products like protein, sucrose (Corredor et al.,
2009). The findings of this research are supportive with the pervious study of Abdel et
al., (2016) they reported a maximum increase in the above ground dry matter due to
the application of nanofertilizers.
Figure 4.36: Effect of different treatments on biomass yield of wheat for two consecutive years.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
d c
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2014-15 2015-16
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Chapter Four Results and Discussion
120
4.5.3 Grain Yield (tons/ha)
Grain yield is the product of heads per square foot, seeds per head and seed
weight. Grain yield of the wheat is affected by many factors, one of the most important
is fertilization (Godfrey et al., 2010). The application of conventional fertilizers and
nano-composites markedly effect the wheat yield in both years. The comparative
effect of nano-composites (ZNC and BNC) and conventional fertilizer on wheat grain
yield are depicted in Figure 4.37. Which clearly showed that highest gain yield for ZNC
(6.54 tons/ ha) followed by BNC (6.1 tons/ ha), NPK (5.48 tons/ ha), urea (5.32 tons/
ha) and lowest for control treatment (4.43 tons/ ha) in the first year.
In the second year the scenario was slightly changed and highest yield was
observed in BNC (66.3 tons/ ha) followed by ZNC (5.94 tons/ ha); the rest of the
pattern being same as pervious i.e. NPK (5.59 tons/ ha) > urea (4.63 tons/ ha)
>control (4.22 tons/ ha). The increase of 47.62% and 37.69% in yield was observed
in ZNC and BNC treatments in the first season, respectively, as compared to the
control. Whereas in the second season 40.42% and 57.28% increase in number of
grains were recorded for BNC and ZNC, respectively (Figure 4.38). Hence, application
of nanofertilizers had a pronounced effect on grain yield of wheat. These
nanofertilizers provided nutrients slowly and in synchronization with the requirement
of the plant until the end of growth while the conventional fertilizers lost their nutrients
at stages of growth due to leaching (Jyothi and Hebsur, 2017).
However, it seems that there is a direct linkage between crop grain yield and
application of fertilizer, i.e., due to an inadequate supply of fertilizers the crop yield
affected badly as in case of control treatment. Thus, properly applied nitrogen
fertilization has a positive effect on crop yield. At a high level of fertilization, it is
advantageous to apply nitrogen twice or three times to plants at different stages of
crop development (Haile et al., 2012). While in case of nanofertilizer, a single
application of fertilizer was applied at the time of sowing thus making it cost effective
and environmental friendly (Naderi and Danesh-Shahraki, 2013).
Chapter Four Results and Discussion
121
Figure 4.37: Effect of different treatments on the grain yield of wheat for two
consecutive years.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite
4.5.4 Harvest index (%)
Harvest index represents the ratio of the dry matter of harvested part of the
crop (grain yield) to the total above ground dry matter production. In agriculture,
harvest index is used to quantify the yield of the crop in terms of total amount of dry
biomass produced (Zhang et al., 2008). The comparative effect of nano-composites
(ZNC and BNC) and conventional fertilizer on wheat yield are shown in Figure 4.39.
The results of harvest index value was recorded in ZNC (43.06%) followed by BNC
(41.95%), NPK (41.19%), and urea (40.96%) and lowest for control treatment
(39.79%) in the first year whereas in the second year, BNC showed higher harvest
index value of 42.23% then ZNC (41.44%). While the NPK (40.0%) urea (39.51%) and
control (38.74%) were at par (Figure 4.38). The increase in harvest index was due to
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2014-15 2015-16
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Chapter Four Results and Discussion
122
the combined effect of yield related parameters and biomass yield of the crop. Use of
nanofertilizers helps in optimum transportation of nutrients leading to higher grain and
biomass yield. The results of this study are consistent with the findings of Feizi et al.,
(2012) and Valizadeh and Milic (2016).
Figure 4.38: Effect of different treatments on the harvest index of wheat for
two consecutive years.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatments. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite
d
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Chapter Four Results and Discussion
123
4.6 Grain Analysis of Wheat
The comparative effects of nano-composites and conventional fertilizer on grain
quality were evaluated by conducting proximate analysis, mineral contents and
antioxidant activity.
4.6.1 Proximate analysis
After harvestaion of the wheat crop, the proximate analysis of whole grain of
wheat was conducted using standard methods of AOAC- 2012 on dry matter basis.
The results of proximate analysis of two consecutive years were obtained and
tabulated in Table 4.6.
4.6.1.1 Moisture content (%)
The moisture content (MC) is an important factor in determining the quality of
wheat, because milling quality of grain demands on it (Rasper and Walker, 2000). The
maximum MC (12.23%) was observed in the grains grown in ZNC while minimum in
grains of control (10.73%) (Table 4.6). The results of MC was observed in the range
of 9.6 to 12.5 %, which were in accordance with the acceptable range (8-18%)
depending upon the weather conditions and soil (Dev, 2002). The nano-composites
(ZNC and BNC) both were highly porous materials and had the ability to retain water.
Thus, they provided the water for long period of time to plants and enhanced the water
content in grains respective of their control. But the moisture content above that
acceptable range became problematic in terms of storage and processing. The higher
moisture content provides medium for fungal growth that not only deteriorates the
wheat quality but also effects the humans (David et al., 2015).
Chapter Four Results and Discussion
124
Table 4.6: Comparative effect of different treatments on the proximate analysis of wheat grain (average of two
consecutive years)
*Means were separated using least significance difference (LSD) at 0.05% level: value bearing the same letters are not statistically different. *T50= Time for 50% germination, MGT= mean germination time, FGP= final germination percent, GI= germination index, Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
Treatment Moisture
content (%)
Ash (%) Protein (%) Crude fat
(%)
Crude fiber
(%)
Carbohydrates
(%)
Control 10.73±0.31b 1.12±0.07a 10.38±0.35c 1.33±0.17a 4.06±0.25a 71.53±0.33c
Urea 10.96±0.53b 1.41±0.02a 11.96±0.12ab 1.27±0.10a 3.13±0.58a 71.27±0.21c
NPK 11.56±0.47ab 1.29±0.22a 10.98±0.26c 1.12±0.45a 2.28±0.47a 72.77±1.30ab
ZNC 11.96± 0.53a 1.24±0.08a 12.23±1.24ab 1.10±0.42a 2.39±0.18a 71.08±1.72ab
BNC 12.53 ±0.31a 1.25±0.18a 12.51±0.85a 1.19±0.92a 2.65±0.19a 73.31±0.29a
Chapter Four Results and Discussion
125
4.6.1.2 Ash (%)
Ash is expressed in percentage and is a measure of the mineral contents (micro
and macro nutrients) present in wheat grains, also considered as an indicator for the
detection of wheat quality (Jutt et al., 2015). The results showed that effect of nano-
composites (ZNC and BNC) on ash was significantly different in both the years when
compared with other treatments. On average the data for two years for the four
treatments followed the order: ZNC (1.98%) > BNC (1.93%) > NPK (1.72%) > urea
(1.45%) for ash content while the minimum ash content was observed in control
(1.12%) (Table 4.6). Usually, ash content fall in the range of 1.4 –2% (Dev, 2002) and
not affected by the wheat variety. Thus, the results of ash were found in range for
ZNC, BNC, NPK and urea except for the control. However, it seems that amount and
type of fertilization affect the nutrient uptake of wheat, which directly influenced on the
ash content of grains. The ash content found in both ZNC and BNC was more than
NPK and urea, which were also supported by the results of minerals detected in the
grains presented in Table 4.7. These results are supported by the reported findings
of Šramková et al., (2009).
4.6.1.3 Protein (%)
Wheat is an important source of protein for daily intake and has substantially
more protein contents than other cereals. The protein content is prominently
influenced by the genotype, environmental conditions and fertilization. Therefore, the
protein content of wheat can vary quite markedly which range from 10.0 to 16.0%
(Koehler and Wieser, 2013). The protein contents varied substantially among the
treatments; higher value was observed in ZNC (12.75%) and BNC (12.57%), which
were at par to each other, followed by NPK (11.69%) and urea (11.02%). All these
values were in accordance with the value found in the literature (Koehler et al., 2007;
Multari et al., 2016). The results demonstrated the positive effects of nano-composites
(ZNC and BNC) on the protein content of grains which was linked with the availability
of nitrogen and other nutrients for a prolonged period of time due to their slow release
and porous structure of support materials (zeolite and biochar) (Manik and
Chapter Four Results and Discussion
126
Subramanian, 2014). While in case of conventional fertilizers (NPK and urea), lower
values were obtained that indicated less availability of N during grain development
possibly due to leaching of nitrogen (Subramanian et al., 2015). Although findings of
this research lie in harmony with Raliya and Tarafdar (2013), who reported that
nanoparticles of zinc oxide significantly enhanced plant growth, chlorophyll content
and protein synthesis in beans. Similarly, application of nano- chelated micronutrients
fertilizer improved the growth and protein content of maize grain 14% as compared to
their respective conventional NPK (Janmohammadi et al., 2016).
4.6.1.4 Crude fat (%)
Crude fat is a relatively smaller component of wheat grain, but considered as
important nutritionally and for processing of grain (Dev, 2002). The results presented
in Table 4.6, showed that BNC (1.74%) had a higher percentage of fat content,
followed by NPK (1.68%) then ZNC (1.63%), urea (1.52%) and control (1.48%). These
results are supported by a reported range of 1.5 to 2% (Belderok, 2000) except the
control. Diets with high fat content contribute significantly to the energy requirement
for humans. Thus, fat content in wheat grains is considered as a batter source of
energy than other sources (Jutt et al., 2015).
4.6.1.5 Crude fiber (%)
Grains are considered a good source of fibers, also helpful in protection from
different diseases like cancer, heart disorders, diabetes, controls the blood lipids,
constipation and liver diseases. Therefore, fibers are also an important parameter for
quality determination of wheat flour (Belitz et al., 2009). The results (Table 4.6)
demonstrated that effect of nano-composites on fiber was not significantly different in
both years, that the fiber content was not much effected by the nano-composites as
compared to control.
Chapter Four Results and Discussion
127
4.6.1.6 Carbohydrates (%)
Carbohydrates constitute a major part of the dry matter of wheat grains and
classified on the basis of monomers into different categories as monosaccharides,
disaccharides, oligosaccharides and the polysaccharides. Mostly cereal grains
contain 66–76% carbohydrates (Koehler and Wieser, 2013). The results summed up
in Table 4.6 represent that higher carbohydrates were recorded in BNC followed by
ZNC, than NPK, urea and control. The obtained results interpreted are representative
of comparative difference treatments rather than absolute values. The type of wheat
variety and application of fertilizers at different growth stages contribute to the
carbohydrate content (Tranavičienė et al., 2007). According to Mahmoud et al. (2017),
that nano-zeolite loaded nitrogen alone and in combination with biofertilizers seems
to be a good source of essential elements for plant growth. These elements contribute
a significant part in plant metabolism and particularly in the synthesis of
carbohydrates.
4.6.2 Concentration of macro and micro nutrients in grain
The nutrients have a substantial role in the growth of plant and development of
grains. These are considered as basic constituents in the chemical composition of
plants and also important for daily human intake. These nutrients are categorized as
macro and micro nutrients on the basis of their requirement by the plant (Marles,
2017). The grain was analyzed after the harvestation for the macro and micro nutrients
are summarized in Table 4.7 and presented as mean or average of two years.
The results depicted that effects of nano-composites were statistically
significant then conventional fertilizers and control. The nano-composites have a
positive influence on the grain mineral contents, including major macro (N, P, and K)
secondary macro (Ca, Mg) and micro (Zn, Fe) nutrients. All these nutrients have a
remarkable role in the growth of the plant and also in grain dietary composition. The
following sequence of treatments; ZNC > BNC > NPK > urea > control was found for
P, K, Ca, Mg and Fe. While in case of N and Zn with some changes, following
sequence of treatments BNC > ZNC > NPK > urea > control was observed. Generally,
Chapter Four Results and Discussion
128
mineral contents of wheat grain lie in the range 1 to 2.5% (Koehler and Wieser, 2013).
Hence, the nano-composites improved the grain mineral quality appreciably as
compared to conventional fertilizers.
The grain nutrient contents are directly or indirectly associated with the uptake
of available nutrients which is affected by many factors like availability of nutrients in
the soil, absorption by plants, type of fertilization and environmental conditions
(Sarwar et al., 2009). The nanofertilizers improved the mineral content of grains, by
ensuring the availability of nutrients for a prolonged period of time. These nanoscale
fertilizers due to their small size to volume ratio easily penetrate into the plant and take
part in chemical mechanism and development of the plant. These minerals are an
important part of daily intake for humans and grains provided more than 70% of these
minerals (Abrar, 2010).
Chapter Four Results and Discussion
129
Table 4.7: Concentration of macro and micro nutrients in grains for two consecutive years
Treatment Nitrogen
(N)
Phosphorus
(P)
Potassium
(K)
Calcium
(Ca)
Magnesium
(Mg)
Iron
(Fe)
Zinc
(Zn)
(%) (mg/kg)
Control 1.69±0.01e 0.019±0.01c 0.22±0.01e 358.4±1.0d
975.48±5.8e 138.61±3.1c 48.67±0.66b
Urea 1.83±0.01d 0.020±0.01b 0.28±0.01d 368.4±0.34c 1041.6±12.2d 144.3±0.96b 47.95±0.90b
NPK 1.88±0.01c 0.021±0.01b 0.32±0.01c 388.3±0.62b 1184.5±5.7c 145.65±5.77b 46.75±1.15b
ZNC 1.97±0.01b 0.025±0.01a 0.37±0.01a 390.5±0.54b 1274.0±6.3b 249.75±5.19a 53.03±0.08b
BNC 2.02±0.01a 0.024±0.01a 0.34±0.01b 396.9±0.79a 1233.6±0.5a 232.46±0.37a 61.16±0.95a
Means were separated using least significance difference (LSD) at 0.05% level: value with the same letters are not statistically different. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite.
Chapter Four Results and Discussion
130
4.6.3 Antioxidant analysis
Antioxidant are substances naturally present in grains, fruits and vegetables,
responsible for the defense mechanism of humans against the different disease which
is associated with free radicals activities (Huang et al., 2005). Substantial evidence
stems that intake of dietary antioxidant can improve the protection from degenerative
diseases like cancer, Alzheimer diseases or Parkinson (Pisoschi and Negulescu,
2011). Different methods are used to measure the antioxidant capacity of samples by
employing various kind of oxidative and reducing assays such as ABTS radical
scavenging, FRAP (Ferric reducing antioxidant power), DPPH (1, 1-diphenyl-2-
picrylhydrazyl) and ORAC (oxygen radical absorbance capacity) (Alam et al., 2013).
But mostly DPPH assays method is used to estimate the antioxidant activity because
less time is required for analysis (Moharram and Youssef, 2014). The antioxidant
activity of wheat grain obtained from different treatments was estimated by DPPH
assays at different concentrations (20-100 µg/ml) and the results are summarized and
presented by averaging the two years data (Figure 4.39).
The results demonstrated that the nano-composite enhanced the antioxidant
activity of wheat grains as compared to conventional fertilizers. The highest
antioxidant activity values were observed in ZNC (79.02%), then for BNC (78.70%)
followed by NPK (69.38%), control (65.67%) whereas lowest values were found in
urea (58.89%) at 100 (µg/ml) concentration (Figure 4.40). Many types of research
works are conducted on the estimation of the antioxidant activity using DPPH assay
of wheat, but the results vary with the involvement of various factors. Moreover, the
direct relation between the results obtained cannot be compared in a true sense due
to the use of different assay, extraction solvents and also the expression of results in
different units (Moharram and Youssef, 2014).
Chapter Four Results and Discussion
131
Figure 4.39: Effect of different treatments on the antioxidant activity of wheat grain for as average of two consecutive years.
The vertical lines on each bar represent the least significant difference (LSD at P< 0.05%) among different treatments for each parameter and letters on each bar highlight the statistical differences among treatment. Control= without fertilizer, Urea= Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC= zeolite based nanocomposite, BNC= biochar based nanocomposite
d
b
b
b
c
d
c
b cd
c
b
b
b
b
b
b
a
a
a
a
a
a
a
a
0
10
20
30
40
50
60
70
80
90
20 40 60 80 100
% I
nhib
itio
n (
DP
PH
)
Concentration (ug/ml)
Control
Urea
NPK
ZNC
BNC
Chapter Four Results and Discussion
132
The reason of enhancement in antioxidant activity is attributed to the presence
of phytochemicals especially secondary metabolites like total phenols and flavonoids
in wheat grain, because of their potential to scavenge free radicals (Adom et al., 2003).
Further, the genetic makeup and environmental factors have influenced the
antioxidant capacity of wheat grains (Mpofu et al., 2006; Zieliński and Kozłowska,
2000) in addition to environmental factors like the climatic conditions, soil properties,
and fertilization as they directly impact the health of the wheat plant.
Fertilizers play a major role in the improvement of the antioxidant capacity of
wheat. It is reported in the literature that the fertilizer application is a dominant factor
for enhancing the total phenolic contents and flavonoids of wheat which ultimately
resulted in enhancement of the antioxidant capacity of wheat (Okarter et al., 2010).
Ma et al. (2015), reported that the increasing nitrogen fertilizers application rate 180-
300 kg/ha enhances the total phenolic contents, total flavonoid content and antioxidant
activity of wheat. Similarly, Sharafzadeh (2011), reported that N: P: K (1:1:1) had a
significant effect on total phenolic content, and higher results were obtained at fertilizer
application rate of 50 mg/kg of soil.
However, very few research works have been found related to nanomaterials
and their corresponding effects on phytochemical and antioxidant studies. The zinc
nanoparticles enhanced the plant growth and also improved the phenolic contents and
antioxidant potential in plants. As reported by the Jyothi and Hebsur (2017), that
nanofertilizers positively improve the total phenolic content and antioxidant capacity
of rice grains as compared to conventional fertilizers because of nutrient availability to
plant for a prolonged period of time.
Chapter Four Results and Discussion
133
4.7 Soil analysis
The post soil analysis was conducted to evaluate the comparative effects of
nano-composites and conventional fertilizers on soil fertility. The soil samples were
analyzed using standard methods and results are tabulated in Table 4.8 while the soil
analysis before sowing was in Table 3.3.
The results revealed that the nano-composites improve the soil health. The pH
value found for both years between 7.25 and 7.48 for control and BNC, respectively,
except the pH (6.37) of urea. The pH of soil was not significantly different taken from
nano-composites and conventional fertilizers treatments after harvestation. Soil pH
greatly influenced the availability of nutrients to the plants because at low pH the
nutrients are not easily taken up by the plants which in turn deteriorate the plant growth
and soil health. The FAO (2008) report described that optimum pH range of 6.5 and
7.5 is considered suitable for most crops, in which nutrients are available and take up
plants (FAO, 2008). Thus, this represents that results of this study are within range
and suitable for plant growth excluding the results of urea treatment. According to
Lungu and Dynoodt (2008), that addition of ammonium based fertilizers like urea,
ammonium nitrate and ammonium sulfate and aggravated the acidity of soil due to
their fast solubilization. Which results in inhibiting the plant growth by damaging seed
germination and also deteriorate the quality of the soil.
A similar trend was found in case of electrical conductivity (EC) for both the
years. The values of EC observed for two years were ranged from 2.70 ds/m to 3.46
ds/m for BNC and control, respectively. Statistically, results of EC were significantly
different for both years (Table 4.8) and the values found are below 4 ds/m, which is
considered as the safe limit for crops growth (Ramesh et al., 2015).EC is an important
indicator of soil health, affects the availability of plant nutrients, soil water balance
which impacts the crops yield (Doran, 2002). Hence these postharvest results showed
that application of nano-composites (ZNC & BNC) as SRFs maintain the EC of soil
and not affect the soil health.
Chapter Four Results and Discussion
134
The results depicted that higher organic content (OC) was found in the soil of
BNC (4.21%) followed by ZNC (3.81%), then NPK (3.61%), urea (3.41%) and lowest
in control (3.22%) (Table 4.8). The postharvest results are statistically different for the
two year treatments and fall in the range of 2 - 4 % (Jakkula, 2005). Therefore, these
are classified as low in terms of organic content. While the results of BNC treatment
fall in medium (4 -10%) category due to the addition of corncob. According to
Gebremedhin et al., (2015) that postharvest analysis of soil showed that soil health
improves due to the addition of biochar.
The results revealed that macro nutrients includes nitrogen and phosphor follow
the order as; BNC > ZNC > NPK > urea > control (Table 4.8). While in case of
potassium order is slight changed as: ZNC > BNC > NPK > urea > control. The results
are statistically significant, higher values were observed in case of nano-composites
while lower in control and urea. Due to the high solubility of urea fertilizers about 40%
of nitrogen was consumed by the crops and remaining leached out in early days of its
application demanding upon climatic conditions (DeRosa et al., 2010).These results
confirmed that slow release of nutrients and their availability for a prolonged period of
time, till the end of crop growth. These nanofertilizers also prevent the leaching of
nutrients and contamination of water (Subramanian et al., 2015).
Hence, these nano-composites can be used in place of ordinary fertilizers
because they sustain soil fertility by improving physiochemical properties and prevent
from soil degradation.
Chapter Four Results and Discussion
135
Table 4.8: Post harvest soil analysis of different treatments of two consecutive years
Treatment pH Electrical
Conductivity
(ds/m)
Organic content
(%)
Nitrogen
(N)(%)
Phosphorus
as P2O5
(mg/kg)
Potassium
as K2O
(mg/kg)
Control 7.25±0.01c 3.51±0.01a 3.22±0.02c 0.21±0.01b 1.82±0.01bc 396±1.1c
Urea 6.37±0.01d 3.41±0.01a 3.41±0.02b 0.24±0.02b 1.41±0.02c 416±0.33bc
NPK 7.46±0.01b 2.82±0.03bc 3.61±0.03b 0.26±0.02b 1.99±0.02b 435±0.33b
ZNC 7.48±0.01b 2.96±0.01b 3.83±0.03b 0.27±0.01b 2.26±0.01ab 530±0.33a
BNC 7.57±0.01a 2.71±0.02c 4.21±0.03a 0.31±0.01a 2.98±0.01a 509±0.33ab
Means were separated using least significance difference (LSD) at 0.05% level: values with the same letters are not statistically different. Control = without fertilizer, Urea = Urea 46% N, NPK= nitrogen, phosphorus, potassium, ZNC = zeolite based nanocomposite, BNC= biochar based nanocomposite.
Chapter Four Results and Discussion
136
4.8 Economic analysis
The fourth objective was to evaluate the economic feasibility of nano-
composites for sustainable field application. The synthesis cost of the nano-
composites was calculated using the market rates of chemicals. The calculated cost
of nano-composites was not very high as compared to conventional fertilizers. Other
related costs both the variable and fixed costs were also estimated and included in
the analysis to calculate the net benefit. The results calculated are summarized in
Table 4.9 and 4.10
Overall the results showed that nano-composites significantly enhanced the
gross benefit as compared to conventional fertilizers. The results indicated that gross
benefit depends upon wheat yield (grain + straw) and total cost of production. The
total cost of production comprises both the fixed and variable cost involved in the
wheat production, calculated for per hectare. The total variable cost includes the cost
of ploughing, planking, seed price, planting, pesticide spray, harvesting and threshing
was considered same for all treatments in this study. While the only difference was in
cost of fertilizers, plant protection and labour which was studied/investigated to
compare the cost difference between conventional and nano-composites.
The highest gross benefit (192,266 Rs/ha) was observed in ZNC treatment,
followed by BNC (182,104 Rs/ha), then NPK (157,738 Rs/ha), urea (154,678 Rs/ha)
and lowest in control (124,374 Rs/ha). The average increase in gross benefit of 54.5%
and 46.4% was observed in ZNC and BNC, respectively as compared to conventional
fertilizers in the first year (Table 4.9). The cost of ZNC was at par with the urea and
lower than NPK, but the gross benefit was high for ZNC in the first year that confirmed
the profitable outcome of nano-composites. In spite of all this, due to the application
of ZNC the attack or spread of disease got minimized, results in a reduction of
pesticide spray cost that ultimately protect the environment from degradation.
Chapter Four Results and Discussion
137
Table 4.9 Economic Analysis of Nano-composites and conventional fertilizer
for the first year (2014-2015)
Treatments Control Urea NPK ZNC BNC Remarks
Grain yield (tons/ha)
4.43 5.32 5.48 6.54 6.11
Adjusted Grain Yield 3.99 4.79 4.93 5.89 5.49 Bring at framers level (10% less)
Straw yield (tons/ha)
6.67 7.66 7.82 8.44 8.87
Adjusted straw yield
6.01 6.89 7.04 7.59 7.98
Bring at framers level (10% less)
Income from grain
114,05
141,11
145,35
173,47
162,06 Rs.1300/ 40kg
Income from straw
34,022
39,071
39,887
43,050
45,243 Rs.250/40kg
Gross Income(income from grain + straw)
148,08 180,18 185,24
216,56
207,31 Rs/ha
Variable cost
(pranking, labor
harvesting)
Urea 1800
NPK 3600
ZNC 1800
BNC 1250
Labor cost
2000 2000 2000 1000 1000
Pesticide spray
1250
1250 1250 1550
Total cost (variable + fixed cost)
23700
25500
27300
24250
25200
Rs/ha
Profitable return(PR)
124,374 154,678 157,738 192,266 182,104 Rs/ha
PR over control (%) 0 30304 33364 67891 57729
Benefit Cost ratio (BCR)
0 1.18 1.21 2.80 2.31
Investm ent Factor (IF) 6.25 7.06 6.74 8.92 8.22
Chapter Four Results and Discussion
138
Whereas in second year the BNC (197,933 Rs/ha) had maximum gross benefit,
followed by ZNC (174,547 Rs/ha), then NPK (161,479 Rs/ha) and urea (132,742
Rs/ha) (Table 4.10). The increase in gross benefit over control of 61.3% and 42.8%
was observed in BNC and ZNC, respectively, in the second year. The results indicate
a substantial increase in wheat crop yield (grain+ straw) due to nano-composites as
compared to conventional fertilizers. These results are consistent by the research of
Abdel et al. (2016), who reported that wheat yield enhanced (45.02%) by the use of
nano chitosan NPK in sandy soil as compared to conventional NPK fertilizer. Similar
trends were found in the results of benefit cost ratio (BCR) and investment factor (IF)
for both the years (Table 4.10). The IF value found to be more than 3 for ZNC and
BNC treatments, which represents that profitability of nanocomposite for business
point of view (FAO, 2008).
In general, this economic analysis showed that improved crop yield is due to
the application of nano-composites. Corroborating these results with Mahmoud et al.
(2017), findings reflect that with a minimum cost of production, the maximum gross
income can be obtained by the application of nano based fertilizers. Hence, the
economic analysis endorsed the promising influence of nano-composites on the crop
throughout the life cycle. Conclusively, it enhances the income of farmers and
producers, by reducing the input fertilizer cost and also protects the environment.
Chapter Four Results and Discussion
139
Table 4.10: Economic Analysis of Nano-composites and conventional fertilizer
for the first year (2015- 2016)
Treatments Control Urea NPK ZNC BNC Remarks
Grain yield (GY) (tons/ha)
4.22 4.61 5.59 5.96 6.67
Adjusted Grain Yield (AGY)
3.79 4.15 5.03 5.34 6.00 Bring at framers level (10% less)
Straw yield (SY)(tons/ha)
6.78 7.11 8.04 8.39 9.12
Adjusted straw yield (ASY)
6.10 6.40 7.23 7.55 8.21
Bring at framers level (10% less)
Income from grain
111,931
122,283
148,271
157,551
176,912 Rs.1300/ 40kg
Income from straw
34,583
36,266
41,010
42,795
46,518 Rs.250/40kg
Gross Income(income from grain + straw)
146,511 158,541 189,282
200,353
223,431 Rs/ha
Variable cost (pranking, labor harvesting)
Urea 1800
NPK 3600
ZNC 1800
BNC 1250
Labor cost
2000 2000 2000 1000 1000
Pesticide spray
1550
1550 1550 1000 1000
Total cost (variable + fixed cost)
24000
25800
27800
25800
25500
Rs/ha
Profitable return(PR) (Rupees in thousands)
122,512 132,742 161,479 174,574 197,933 Rs/ha
PR over control (%) (Rupees in thousands)
0 9.927 38.664 51.733 75.119 Rs/ha
Benefit Cost ratio (BCR) 0 0.38 1.39 2.00 2.94
Investment Factor (IF) 6.10 6.14 6.80 7.76 8.76
Conclusion
140
CONCLUSION
Nanotechnology has marked the revolution in fertilizer technology by the
provision of nano sized slow release smart materials that provides enhancement in
nutrient release along with significant cost reduction both in aspects of economics and
environmental pollution. This study based on synthesis of nano-composites using
nano- zeolite and corncob biochar as support materials. These nano-composites
(ZNC & BNC) are considered as a potential environmental friendly slow release
fertilizers owing to their natural origin, support materials as well as slow release
nutrient pattern that can be used as an alternative to conventional chemical fertilizers.
The support materials (NZ and CB) have a porous structure which makes them
very effective for impregnation of nutrients that are released slowly. The synthesized
materials were characterized using different techniques which confirmed their
chemical composition, structure, and thermal stability. While the porous structure of
nano-composites improves the water holding and retention capacity of soil that
enhance soil condition without imparting negative impacts. Further, the slow release
studies confirm the gradual supply of nutrients to the plants for a prolonged period of
time that helps in minimizing the leaching impacts of the conventional fertilizers on the
environment and also facilitating the maximum uptake of these nutrients by the plants
that finally facilitate growth and hence nutritional uptake.
The nano-composites release nutrients slowly that helps in early sprouting and
germination than conventional fertilizers. While the results of field trials showed that
ZNC positively impact the morphological parameters (plant height, fresh and dry
weight, number of tillers) as well as agronomic yield parameters (number of productive
tillers, number of spikes, grains per spikes, 1000 grain weight, biomass yield, grain
yield and harvest index) as compared to urea and NPK in the first year. Whereas in
the second year, the scenario was a little bit different, higher results of studied
parameters were recorded in BNC treatment followed by ZNC then NPK, urea and
control. In case of wheat grain quality analysis results were significantly different
Conclusion
141
among the treatments. Higher crop yield was obtained from nano-composites that
resulted in higher economic benefit than other conventional application.
Therefore, it can be safely concluded that the prepared nano-composites are
suitable environmentally friendly nanofertilizers that can be used in place of
conventional chemical fertilizer for sustainable agriculture and environment. These
nanocomposites, when compared between themselves, showed equivalent results for
all the parameters studied during this research work. For the two years, the data
obtained is almost similar with mild discrepancy among the studied parameters that
confirms the applicability and suitability of both ZNC and BNC as slow release
fertilizers. But the comparison between the nanocomposites on the basis of economic
analysis has highlighted that BNC can economically benefit the society and
agronomics practices in a better way than ZNC in terms of wheat grain yield and gross
profit due to low synthesis cost and origin from waste materials that also facilitates in
designing better waste management practices.
Recommendations
The following recommendations are suggested after the completion of this research
work:
Firstly, the field trial should be conducted using varying application rates of
nano-composites on the growth of different crops and at varying geological locations
to determine and optimize the application rate of these nano-composites.
Secondly, further extensive studies should be conducted on different wheat
varieties with a same varying application rate of nano-composites to see varietal
responses of different varieties.
Thirdly, the product should also be used for residual impact studies using
different types of soils and crops to observe how much of nutrients impregnated are
still available for next crop or season.
References
142
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Annexure
178
Annexure-1 Experimental Setup of Nano zeolite synthesis
Figure 1(A): Mixing of aluminum silicate and sodium hydroxide in ethylene
glycol, in three neck round bottom flask fitted with a reflex condenser.
Annexure
179
Annexure-2 Germination studies in Greenhouse
Figure2 (A): Growth of wheat seedlings under different treatments in
greenhouse at 10th day of post germination
Figure 2(B): Growth of wheat seedlings under different treatments in
greenhouse at 15th day of post germination
Annexure
180
Annexure-3 Field trials of Wheat
Figure 3(A): Wheat growth under different treatments in field trials at tillering
stage
Figure3 (B): Wheat growth under different treatments in field trials at harvest
stage
Annexure
181
Annexure-4 List of Publications
1. Synthesis and characterization of zeolite based nano–composite: An
environment friendly slow release fertilizer (2016): Ambreen Lateef, Rabia
Nazir, Nadia Jamil, Shahzad Alam, Raza Shah, Muhammad Naeem Khan,
Murtaza Saleem. Microporous and Mesoporous Materials, volume 232, 174-
183, 2016.
2. Simple Synthetic Approach To Development of Corncob Based Nanocomposite
- A Slow Release Nanofertilizer for Sustainable Agronomy Practices: Ambreen
Lateef, Rabia Nazir, Nadia Jamil, Shafiq ur Rehman, Shahzad Alam, Raza
Shah, Muhammad Naeem Khan, Murtaza Saleem. International Journal of
Agricultural Sustainability (Submitted).