akadidi new (REPAIRED).docx

8/10/2019 akadidi new (REPAIRED).docx

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offensive and potentially dangerous substances which cause pollution and contamination of

receiving ecosystems. Ghosh and Singh (2005) reported that controlled and uncontrolled disposal

of waste, sewage sludge application to agricultural soils, accidental and process spillages are

responsible for the migration of contaminants into the soil. Larson, (2003) reported that Physico-

chemical disturbances are primarily responsible for influencing plant community composition

and the spread of invasive exotics. The plant species found along diversely polluted effluent

channels include highly resilient species that are resistant to high amount of different heavy

metals (Li et al., 2004; Juknevicius et al., 2007; Al-Khashman, 2007; Yetimoglu et al., 2007).

Plants colonizing metal-contaminated soils are classified as resistant and have adapted to this

stressed environment. Heavy metal resistance can be achieved by avoidance and/or tolerance.

Some plant species are able to protect themselves by preventing heavy metal ions from entering

their cellular cytoplasm and are termed Avoiders.Others are able to detoxify metal ions that

may have crossed the plasma membrane and are termed Tolerant species (Millaleo et al.,

2010). A strategy explored by avoiders involves mycorrhizal fungi, where they can extend their

hyphae outside the plant rooting zone up to several tens of meters and transfer the necessary

elements to the plant (Ernst, 2006; Baker, 1987). Plants can also restrict contaminant uptake in

root tissues by immobilizing metals, i.e. through root exudates in the rhizosphere. A series of

root exudates is to chelate metals and stop their entry into the cell. Tolerant plants are protected

internally from the stress of metals that gained entry into the cell cytoplasm (Baker, 1987).

Metallophytes can function normally even when there is a higher plant- internal metal level

by developing heritable tolerance mechanisms over time. Different species from local non

tolerant ancestral plant populations have independently evolved mechanisms to tolerate specific

metals (Schat et al., 2000). Plants exhibit tolerance to metals that are present in excess in soil,


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with each metal under the control of a specific gene (genostasis). It is the restriction of this

genetic variability that limits the evolution of the population/species. Metal tolerance and

accumulation in plants are complex genetic systems. Plants have to modify their physiological

processes in order to be able to survive in the environment in which they have germinated. In

turn, the survival of a population to the contaminated environment is dependent on the

inheritance of favourable traits. Bradshaw, (1991) reported that in the absence of avoidance

pathways, soils contaminated with heavy metal act as a force on the plant population where

plants with tolerant genotype can survive and reproduce. Tolerance mechanisms are heritable

and variable, resulting from genes and gene products (Maestri and Marmiroli 2012). The gene

for tolerance pre-exist at a low frequency in non tolerant populations of certain plant species

(Ernst, 2006; Macnair, 1987).

Baker and Walker, (1990) classified plants based on the strategies used by them as; metal

excluders, indicators and accumulators/hyperaccumulators. The former limits the translocation of

metals, maintaining low levels of contaminants in their aerial tissues over an extensive range of

soil concentrations. The latter (indicators) accumulate metals in their harvestable biomass and

these levels generally are reflective of the metal concentration in the soil. Metal

accumulators/hyperaccumulators are plants that increase internal sequestration, translocation and

accumulation of metals in their harvestable biomass to levels that far exceed those found in the

soil (Mganga et al., 2011; Baker and Walker 1990).Resistance is a quantitative trait that

enables a plant to survive, grow and reproduce in the presence of a particular contaminant (Baker

and Walker, 1989). Plant populations can become resistant to heavy metals by genetic

adaptation or gradual acclimatization to an increasing heavy metal load (Antonovics et al. 1971;

Baker et al.,1986; Dickinson et al.,1991; Punshon and Dickinson 1997). All these strategies,


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allow the establishment of plant communities on metal contaminated soils along an effluent

channel. The accumulation of metals by plants is interesting from an environmental

(bioremediation) or agronomic (biofortification of crops to improve the nutritional value of these

crops) point of view. In industrial sites, accumulator plants could be used for phytoremediation

as they are likely able to remove metals from soils (Salt et al., 1995; Salt et al., 1998). This

therefore, informs the need for the study;

1. To investigate the heavy metal content of the soil along an effluent channel in a brewery

industry and its effect on the plant community.

2.

To evaluate the kind of plants found along the effluent channel and their tolerance level

to heavy metals as well as remediative abilities.


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CHAPTER TWO

2.0 LITERATURE REVIEW

The improper management of the vast amount of waste generated by various

anthropogenic activities, has become one of the most critical problems of developing countries.

The most challenging aspect is the way and manner people go about disposing them into the

immediate environment. This indiscriminate disposal waste is usually carried out on freshwater

bodies, making them unsuitable for primary and even secondary usage (Fakayode, 2005). In

1978, the UN reported consumable water levels at 2.7% of earths water, with ground water

being a major contributor. Present estimates quantify consumable water levels at 1%, ground

water levels also being threatened by pollution either directly or indirectly (Davis and Cornwell,

1991). Kehinde in 1996, defined sustainable utilization of the earths wateras the use of water

resources without any cost whatsoever on future generations, which might arise through misuse

of the resource.

This however is no longer the case as brewery, tannery, pharmaceutical, paper and textile

mills, soap and detergent as well as palm oil mill (POM) effluents are responsible for the

contamination of this natural surface water in developing and densely populated countries like

Nigeria (Kanu et al.,2011). Wastewater from Brewery Industry originates from liquors pressed

from grains and yeast recovery and have the characteristic odour of fermented malt and slightly

acidic (Kanu et al., 2006). Other wastewater from industries includes employees sanitary waste,

process wastes from manufacturing, wash waters and relatively uncontaminated water from

cooling and heating operations (Glyn and Gary, 1996). The increase in the industrialization of

Benin City has led to pollution stress on surface water (Ajayi and Osibanji, 1981). Industrial

effluent is unwanted water generated from industrial activities and are inappropriately discharged


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into the environment or receiving stream. Its characteristics provide basic information about the

integrity of the rivers and streams into which they are discharged (Kanu et al., 2006). Dada, 1997

reported that more than 60% of the industries in Nigeria discharged untreated effluent into

surface water. A study by Uchegbu in 2002 showed that surface water becomes polluted when

harmful substances (effluents) are released into water bodies from either natural or artificial

sources. Fellman et al., (1995) reported that manufacturing companies in United States of

America dumped polychlorinated biphenyls (PCBs) into rivers.

Effluents from industrial activities contain heavy metals (Bichi, 2000) which may

damage aquatic ecosystem, health of aquatic animals and those who eat them (The Guides

Network, 2008). Estuaries and inland water bodies, which are the major sources of drinking

water in Nigeria, are often contaminated by the activities of the adjoining populations and

industrial establishments around the water body (Sangodoyin, 1991). Sangodoyin 1995; Ogbeibu

and Edutie 2002, reported that water bodies (river systems) constitute the primary means for

disposal of waste thus, altering the physical, chemical and biological nature of the receiving

water bodies. The initial introduction of waste into water bodies causes the degradation of the

physical quality of the water, followed by the biological degradation, which becomes seen in

terms of variety, organization and the number of living organism in the water (Gray, 1989).

Wastes entering these water bodies are either in solid or liquid forms or both, with great effects

on the health of the public (Osibanjo et al.,2011). Saad et al., (1984) reported that the increased

population in many African countries accompanied by a sharp increase in urbanization,

agricultural and industrial land use, results in a tremendous increase in discharge of a wide

diversity of pollutants into receiving water bodies. This causes undesirable effects on the

different components of the aquatic environment.


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The availability of quality water needed for maintenance of normal biological function is

on the decline (Odigie and Fajemirokun, 2005). When waste materials are received by the water

bodies, they are assimilated without significant deterioration of some of the qualities, thus

implying the assimilative capacity of the water (Fair et al., 1968). This is however due to the self

purification property of lotic systems (Ifabiyi, 2008). In 2005, studies by Ekhaise and Anyansi

showed that waste introduces foreign microorganisms, organic and inorganic matter, in addition

to indigenous microflora, when discharged into the water bodies. Various levels of pollutants can

be discharged into the environment through public sewer lines based on the type of industry. An

increase in the levels of pollutants in river water systems causes a rise in biological oxygen

demand (BOD), chemical oxygen demand (COD), total dissolved solids (TDS), total suspended

solids (TSS), toxic metals such as Cd, Cr, Ni and Pb and fecal coliform and hence make water

unsuitable for drinking, irrigation and aquatic life (Emongor et al., 2005; Otokunefor and

Obiukwu, 2005).

Organic pollution of inland water systems in Africa, in contrast to the situation in

developed countries of the world, is often the result of extreme poverty as well as economic and

social underdevelopment. Countries with the lowest quality and quantity of water, have the

lowest sanitation and nutrition levels with the worst of diseases most prevalent (Tolba, 1982).

Worse still, are the very few water quality studies for most African inland waters. The practice of

effluent discharge in Nigeria, is yet too crude and the society is in danger, especially in the

industrialized parts of the Cities. Benin is fast becoming a fairly industrialized city, though some

of these industries are situated some distance away from rivers; their effluents are channeled into

such rivers as Ikpoba River (Ogbeibu and Edutie, 2002). Some of these industries are soft drink

industry, alcoholic beverage industry and the wastewater from their operations is conveyed over


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a distance by an underground tunnel and discharged into Eruvbi Stream, a tributary of Ikpoba

River. These effluents, which are rich in organic and inorganic substances, are capable of

producing adverse effects on the physical, chemical and biotic components of the environment

and either directly or indirectly on human health (Mason, 1981; Ogbeibu and Ezeunara, 2002).


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CHAPTER THREE

3.0 MATERIALS AND METHOD

3.1 Study Area

The study was carried out at a site located beside Guinness Nigeria plc, Benin City where their

effluent channel passes through to the Ikpoba River, along the Benin-Agbor Road, Benin City,

Edo state.

Plate 1: The research student on the brewery effluent channel terminating at Ikpoba River, Benin

City.

Effluent at contact

point with water

Brewery effluent

channel


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3.2 Soil and Plant Collection

Plant samples were collected using a quadrant method (Trivedy and Goel, 1986). The quadrants,

1m x 1m was used. Three quadrants randomly placed within 5m along the whole length of the

channel, and plants were identified and counted. Soil samples were also collected from the

quadrants and taken to laboratory for analysis in aluminum foil wraps (Anoliefo et al., 2006).

Plants were identified by using Akobundus 1987 handbook of West Africa weeds.

Plate 2: The study area around Guinness effluent channel some distance away


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3.3 Soil Physiochemical Analyses

3.3.1 Determination of PH

The pH reading was obtained with the aid of an Hanna microprocessor pH multimeter which was

earlier standardized with buffer 4.0, 7.0 and 9.0.Twenty (20) grams of the fresh soil sample was

weighed into a 100 ml glass beaker. Twenty (20) milliters of sterile distilled water was added

and the suspension was stirred continuously for 30 minutes. The mixture was allowed to stand

for another 30minutes undisturbed. A Hanna microprocessor pH meter was dipped into the

solution and steady readings noted (Kalra and Maynard, 1991).

3.3.2 Electrical Conductivity (EC)

Twenty (20) grams of the fresh soil sample was weighed into a 100 ml glass beaker. Twenty (20)

milliters of sterile distilled water was added and the suspension was stirred continuously for 30

minutes. The mixture was allowed to stand for another 30minutes undisturbed. A Digital

Conductivity Meter (Labtech) was used in determining soil conductivity by dipping the sensitive

rod into the mixture and a steady reading taken.

3.3.3 Total Organic Carbon Content (TOC)

Air dried soil was passed through a 2 mm sieve in other to remove large particles, roots, organic

debris and ensure for consistency. This soil sample were used for both carbon and nitrogen

analyses. A weighed amount (1.0g) of prepared soil sample was dispensed into a 250 ml conical

flask. Ten (10) mls of Normal Potassium dichromate was added to the flask followed by the


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addition of 20 ml of concentrated tetraoxosulphate (VI) acid. The flask was shaken for 1 minute

and allowed to cool. Distilled water was then added to the cold solution to make the volume up

to 150 ml. This solution was shaken and allowed to cool. Ten (10) ml of phosphoric acid was

added to the solution followed by the pipetting of 1ml of 1% diphenylamine solution (indicator).

Titration with 0.5 ferrous ammonium sulphate solutions was done until there was colour change

from dark violet to green. A blank determination was done for each soil sample (Onyeonwu,

2000).

Calculation

Blank - Sample Normality of Ferrous Ammonium Sulphate 0.03 1.3 100

Weight of Sample

3.3.4 Determination of Total Nitrogen

The total nitrogen content of the soil samples was determined using micro Kjeldahl digestion and

colorimetric method (Bremmer and Mulvaney, 1982). One gram soil sample was placed into

30ml Kjeldahl digestion flask. One tablet of a catalyst (Kjeldahl) and 10 ml concentrated

H2SO4was added, and the mixture was hand shaken to ensure mixing. At completion of

digestion, the mixture was clear and upon removal from the digestion chamber, it was allowed to

cool. Then, 10 ml distilled water was added and the solution was decanted through a Whatman

filter paper No 42 into a 100ml volumetric flask. The Kjeldahl flask was washed with 2 to 3

small aliquots of distilled water and all the washings were added into the volumetric flask via the

filter paper and made up to volume. The nitrogen content of the filtrate was then determined

colorimetrically. For colorimetric analysis, a standard nitrogen stock solution was prepared using


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dry ammonium sulphate and from the resultant 100 ppm nitrogen stock solution, 5, 10, 15, 20

and 25 ppm nitrogen standards were prepared and in each standard, 4 ml concentrated H 2SO4

and 0.95g anhydrous sodium sulphate was added. A blank solution containing no nitrogen

standard but having the same quantity of acid and anhydrous sodium sulphate was also prepared.

Then, 5 ml of the digested filtrate was pipetted into a 25 ml glass flask, and 2.5ml alkaline

phenol, 1 ml sodium potassium tartrate and 2.5 ml of sodium hypochlorite were added. The

mixture was hand shaken, and made to 25ml mark with distilled water. The solution was read

colorimetrically at 630 nm, using a spectrophotometer.

3.3.5 Available Phosphorus Content

Five (5) grams of the soil sample was weighed and dispensed into plastic bottle. Forty (40)

milliters of the extracting solution (0.03M NH4F in 0.025 M HCl) was added and the bottle was

shaken for 1 minute. The solution was filtered with the aid of a Whatman filter paper No 42. The

clear supernatant was used for determining the phosphorus content of the respective soil samples.

Five (5) milliters of the supernatant was pipetted into a 100 ml flask. The pH of the supernatant

was adjusted to 5 respectively by the addition of 3 drops of p- nitrophenol, and upon the

development of yellow colour, some drops of 2 M NH4OH were added until a deep yellow

colour was developed. Also, 2 M HCl was added dropwise until the supernatant became

colourless. (The resultant pH was between 3 and 5). Thirty (30) milliters of water was added,

followed by the addition of 10 ml of ascorbic acid reagent. The absorbance of the solution was

read at 660 nm using a spectrophotometer (Model). (Onyeonwu, 2000)


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Calculation

P (mg/kg) = Instrument reading Colour volume Extract volume

Weight of sample aliquot taken

3.3.6 Determination of Cation Exchange Capacity (CEC)

Five (5) grams of air dried soil was weighed into a plastic bottle. One hundred (100) milliters of

neutral 1 M ammonium acetate was then added to the soil and the mixture was shaken with the

aid of a mechanical shaker for 30 minutes. The mixture was filtered using a No 42 Whatman

filter paper into a 100 ml volumetric flask. The filtrate was made up to mark with the acetate.

Stock working standards 0,2,4,6,8 and 10 ppm were prepared for sodium, potassium, calcium

and magnesium using 2.54g of oven dried sodium chloride, 100 ml of ammonium acetate, 1.9067

g oven dried potassium chloride, 0.5004g of calcium carbonate (at 1050C) in 5 ml of

hydrochloric acid and 0.1216 g of magnesium turning in volume of 6 M hydrochloric acid. The

concentration of the exchangeable cations (Na, Ca, K and Mg) in the filtrate was determined

using a flame photometer (Model). The flame photometer was adjusted according to its

instruction manual and the standards were aspirated to obtain reliable curves before aspirating

the samples. The blank utilized was ammonium acetate (Onyeonwu 2000).

Calculation

Ca (Meq/100g) = Instrument reading 100

Weight of sample Eq. wt.

K (Meq/ 100g) = Instrument reading 100



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Mg (Meq/ 100 g) = Instrument reading 100


Na (Meq/ 100 g) = Instrument reading 100


CEC (meq/100 g) = Ca + K + Mg + Na

3.3.7 Minerals (Metals) Analyses

The soil sample was spread on a clean plastic sheet placed on a flat surface and air dried under

room condition for 72hrs. The soil was sieved and 5g sample was taken from the sieved soil and

put in a beaker. Ten (10) ml of nitric perchloric acid, ratio 2:1 was added to the sample. The

sample was digested at 105oC. 5ml of HCl was added to the digester again and digested for

30mins. The digest was then removed from the digester and allowed to cool to room

temperature. The cooled digest was washed into a 100ml standard volumetric flask and was

made up to 100ml mark with distilled water. Determination of Iron (Fe), Chromium (Cr),

Manganese (Mn), Zinc (Zn), Vanadium (V), Arsenic (As), Mercury (Hg), Lead (Pb), Copper

(Cu), Cadmium (Cd) and Nickel (Ni) were done by aspirating the solution for (analysed) each

metal analysis into the Atomic Absorption Spectrometer (ASS) PG 550 model (Adelekan and

Abegunde, 2011).

3.3.8 Extraction of Nitrate, Sulphate and Ammonium Nitrogen from Soil

Ten (10) grams of air dried soil was weighed into a plastic bottle. Fifty (50) extraction solutions

(100g of sodium acetate, and 30ml of acetic acid in one litre of distilled water) were added and


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the mixture was shaken with the aid of a mechanical shaker for 30 minutes. The mixture was

filtered using a No 42 Whatman filter paper into a 100 ml volumetric flask. The filtrate was

made up to mark with the distilled water and preserved for nitrate, sulphate, and ammonium

nitrogen determination.

3.3.8.1 Nitrate Determination

Ten milliliter of digest was transfer into fifty milliliter flask, two milliliter of brucine and ten

milliliter of concentrated sulphuric acid were added. The mixture was mixed and allowed to

stand for ten minutes. Stock working standards of 0, 2,4,6,8 and 10 ppm were prepared and

treated in similar way. The optical density (OD) of the samples and standard were taken at

470nm (Onyeonwu 2000).

Calculation

NO3 (mg/kg) = OD x SR x Colour Vol x Ext. vol

Weight of sample x Vol. taken

3.3.8.2 Sulphate Determination

Ten milliliter of digest was transfer into fifty milliliter flask, five milliliter of water, one milliliter

of barium chloride gelatin reagent were added and the solution was allowed to stand for thirty

minutes, and ten milliliter of concentrated sulphuric acid were added. The mixture was mixed

and allowed to stand for ten minutes. Stock working standards 0, 2,4,6,8 and 10 ppm were

prepared and treated in similar way. The optical density (OD) of the samples and standard were

taken spectrophotometrically at 420nm


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Calculation

SO42-

-S(mg/kg) = OD x SR x Colour Vol x Ext. vol


3.3.8.3 Ammonium Nitrogen Determination

Five milliliter of digest was transfer into fifty milliliter flask, two and half (2.5ml) milliliter of

alkaline phenate, one milliliter of sodium potassium tatrate reagent, and two and half (2.5ml)

milliliter of sodium hypochlorite (parazone) were added. The solution was then shaken. Stock

working standards of 0, 2,4,6,8 and 10 ppm were prepared and treated in similar way. The

optical density (OD) of the samples and standard were taken spectrophotometrically at 636nm.

Calculation

NH4+-N(mg/kg) = OD x SR x Colour Vol x Ext. vol


3.3.9 Determination of Metals in Soil/Sediment with AAS Using Wet Acid Extraction

Method (SRL/AM/S01)

Determination of Pb, Cu, As, Zn, Ni, Cd, Fe, Mn, Na, K, Ca, Mg and Al in soil and sediment wet

digestion method.


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Principle

The sample extract was first aspirated into the flame whose high temperature converts the

analyte atoms into ions in vapour state (exited state). Absorption occurred, when a ground state

atom absorbed the energy in the form of light of a specific wavelength and was elevated to an

excited state. The relationship between the amounts of light absorbed by the ion is directly

proportional to the concentration of the ionic molecules in the solution.

Samples processing

The samples were placed in glass Petri dishes and sundry them for 24 hours. After 24 hours of

drying, any lumps present were broken up with a clean glass rod in order to expose the inside for

drying.When the samples appeared to be dried, they were left under the sun for further 24 hours

before grinding. After drying, the soil was grounded. In heavy contaminated soil, it was

necessary to break up the hard pieces using a mortar and pestle.

Extraction Procedure

One gram (1g) of the dried soil sample was transferred into an acid wash 250ml extraction

bottle. 9ml of concentrated HCl, 3ml of HNO3 and 2ml of perchloric acid were added. The

mixture was digested for 5-6 hrs on mechanical shaker hot plate. After digestion was completed,

20 ml if distilled water was added and the solution was filter through a whatman No 42 filter

paper and finally made up to 100ml. Prepare blank samples using the procedure without any


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animal sample. The filtrate were analyzed for Heavy metal and trace metal (Cu, As, Zn, As, Pb,

Cr, V, Ni, Cd, Fe, Mn) using AA PG 550 Spectrometer.

Calibration and Analysis

Single elemental standards were prepared by diluting 1000mg/l stock solutions of the respective

individual elements (Cu, As, Zn, As, Pb, Cr, V, Ni, Cd, Fe, and Mn). A minimum of five

standard working solutions were prepared daily from the stock Solutions, solution ranged from

0.1mg/l to 1mg/l. External calibration was used by running demonized water and a suite of

calibration standards for each element, and Calibration curve was then generated for each

individual metal. The extracted solutions and blank were then run on the AA to obtain the

absorbance values, and the concentrations of each metal in the digested samples were

automatically calculated from the equation of the calibration curve by the AAS equipment.

Quality Assurance: field acidified demonized water is first aspirated as blanks in duplicates and

laboratory control samples were run as QC samples.

SAFTY: Use PVC hand gloves and laboratory coats.


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CHAPTER FOUR

4.0 RESULTS

Physiochemical properties of the soil used in the present study are presented on Table1. Soil used

in the study had a pH of 6.75, 5.55 and 6.05 in quadrants 1, 2 and 3 respectively. The pH mean

and standard deviation for the first, second and third quadrants was 6.12 3.52. Total dissolved

solid for second quadrant was 81.00 mg/kg and for the third was 92.50 mg/kg. Total nitrogen

was 0.13% for the first quadrant, 0.16% and 0.08% for the second and third quadrants

respectively. Exchangeable acidity for the first quadrant stood at 0.14mg/100g, 0.72mg/100g for

the second quadrant and 1.52mg/100g for the third. Heavy metal contents of soil include Fe

(9.73mg/kg), Mn (0.15mg/kg), Zn (2.47mg/kg), Cr (1.23mg/kg), Pb (0.85mg/kg), Ni

(0.11mg/kg) and V (0.14mg/kg) for the first quadrant.


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Table 1: Physicochemical properties of soil used for the present study

Physiochemical

parameters

S.I Unit Quadrant 1 Quadrant 2 Quadrant 3 Mean SD

pH 6.75 5.55 6.05 6.12 3.52

EC uS/cm 137.00 162.00 185.00 37.2 125.7

TDS mg/kg 68.50 81.00 92.50 80.67 9.79

Cl- mg/kg 41.10 48.60 55.50 145.2 96.98

SO4- mg/kg 42.47 50.22 57.35 50.0 6.07

NO3- mg/kg 16.44 19.44 22.20 19.36 2.35

PO4- mg/kg 10.96 12.96 14.80 12.9 1.57

Na+ mg/kg 4.11 4.86 5.55 4.84 0.62

K+ mg/kg 6.85 8.10 9.25 8.07 0.83

Ca+ mg/kg 2.33 2.75 3.15 2.74 0.34

Mg+

mg/kg 1.92 2.27 2.59 2.26 0.28Exc. Base meq/100g 1.52 1.79 2.05 1.79 0.2

Exc. Acid meq/100g 0.14 0.72 1.52 0.79 0.56

ECEC meq/100g 1.66 2.51 3.57 2.58 0.91

Fe+ mg/kg 9.73 11.50 13.14 11.5 1.39

Zn mg/kg 2.47 2.92 3.33 2.91 0.35

Mn+ mg/kg 0.15 0.18 0.20 0.18 0.02

Cu+ mg/kg 0.69 0.81 0.93 0.81 0.095

Ni+ mg/kg 0.11 0.13 0.15 0.13 0.11

Cd

+

mg/kg 0.27 0.32 0.37 0.32 0.0345V

+ mg/kg 0.41 0.49 0.56 0.49 0.22

Cr+ mg/kg 1.23 1.46 1.67 2.54 1.12

Pb+ mg/kg 0.85 1.00 1.15 1 0.13

Hg mg/kg


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Plate 3: Plants growing around the effluent channel at the study area

A combination of all the plant surveyed gave a total of thirteen (13) different species, identified

in the 3 randomly sampled sites (Table 2 4). A total of 176 plants were collected in the three

sites visited. From the 49 plants surveyed in quadrants 1, 2 and 3, there were 3 members of the

Fabaceae family, which included Desmodium scorpiurus, D. tortuosum and Schrankia

leptocarpa;2 Cyperaceae; Kyllinga squamulataand Cyperus esculentus, 1 member each of the

Poaceae, Pontederiaceae, Euphorbiaceae, Malvaceae, Limiaceae, Amaranthaceae, Cucurbitaceae

and Asteraceae families respectively.Poaceae family had the highest number of plants surveyed

in the three quadrants, with a total of 48 plants, followed by Cyperaceae with 37 plants. Others

were Euphorbiaceae 26 plants, Amaranthaceae family 20, Limiaceae and Pontederiaceae with 12

and 11 plants samples respectively. The least number of plants sampled were from the


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Asteraceae family with a total of 5 plants. Plant species that were moderately distributed

includes;Hyptis lancoelata, Cyperus esculentus,Luffa aegyptiaca andGomphrena celosiodes.

Plants that were least distributed in the sites visited are Veronia cinerea Sida acuta and

Schrankia leptocarpa

A total of 11 samples ofEichhornia natansappeared in quadrant 1 but not in quadrants 2 and 3.

Sixteen samples ofKyllinga squamulata,of the Cyperaceae family were surveyed n quadrant 1

compared to 6 samples surveyed in quadrants 2 and non in quadrants 3. Out of the 49 plants

surveyed in Q1 (Table 2), Kyllinga squamulata had the highest frequency of 0.33. This was

followed byEichhornia natansandPhyllanthus amarus with 0.22 respectively.


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Table 2: Distribution of plant species collected from quadrant 1 (Q1), values show the frequency

of occurrence of plant species.

BOTANICAL NAME FAMILY X X - (X - Freq

Kyllinga squamulata Cyperaceae 16 12.23 148.8 0.33

Leptochloa caerulescens Poaceae 3 0.77 0.6 0.06

Eichhornia natans Pontederiaceae 11 7.23 52.3 0.22

Phyllanthus amarus Euphorbiaceae 11 7.23 52.3 0.22

Desmodiumscorpiurus Fabaceae 2 1.77 3.13 0.04

Cyperus esculentus Cyperaceae 6 2.23 4.97 0.12

Desmodiumtortuosum Fabaceae 0 0 0 0

Sida acuta Malvaceae 0 0 0 0

Hyptis lancoelata Limiaceae 0 0 0 0

Gomphrena celosiodes Amaranthaceae 0 0 0 0

Luffa aegyptiaca Cucurbitaceae 0 0 0 0

Veronia cinerea Asteraceae 0 0 0 0

Schrankia leptocarpa Fabaceae 0 0 0 0

TOTAL 49 31.5 262.1

MEAN 3.77 2.4 20.2

Variance = 20.2

Standard deviation =

= 4.49


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Table 3 shows the total number of plants surveyed in the second quadrant (Q2). Of the 58

plants sampled, there were 30 poaceae, 12 cyperaceae and 15 euphorbiaceae. No members of the

pontederiaceae, malvaceae, limiaceae, amaranthaceae, cucurbitaceae and asteraceae families

were sampled. The plant with the highest frequency wasLeptochloa caerulescens, of the poaceae

family


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Kyllinga squamulata Cyperaceae 6 1.54 2.37 0.10


Eichhornia natans Pontederiaceae 0 0 0 0

Phyllanthus amarus Euphorbiaceae 15 10.5 110.3 0.26

Desmodiumscorpiurus Fabaceae 0 0 0 0


Desmodiumtortuosum Fabaceae 1 3.46 11.97 0.02

Sida acuta Malvaceae 0 0 0 0

Hyptis lancoelata Limiaceae 0 0 0 0

Gomphrena celosiodes Amaranthaceae 0 0 0 0

Luffa aegyptiaca Cucurbitaceae 0 0 0 0

Veronia cinerea Asteraceae 0 0 0 0

Schrankia leptocarpa Fabaceae 0 0 0 0

TOTAL 58 42.54 777.3

MEAN 4.46 3.27 59.8

Variance = 59.8


= 7.73


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Table 4 shows the plants surveyed in the third quadrant. Gomphrena celosiodeshad the highest

number of plants surveyed with 20 plant samples. These were followed by Leptochloa

caerulescens(poaceae) with 15 plant samples and Hyptis lancoelata(limiaceae) with 12 plants

sampled.


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Kyllinga squamulata Cyperaceae 0 0 0 0


Eichhornia natans Pontederiaceae 0 0 0 0

Phyllanthus amarus Euphorbiaceae 0 0 0 0

Desmodiumscorpiurus Fabaceae 0 0 0 0


Desmodiumtortuosum Fabaceae 0 0 0 0

Sida acuta Malvaceae 4 1.31 1.72 0.06

Hyptis lancoelata Limiaceae 12 6.69 44.8 0.17

Gomphrena celosiodes Amaranthaceae 20 14.69 215.8 0.29

Luffa aegyptiaca Cucurbitaceae 8 2.69 7.24 0.12

Veronia cinerea Asteraceae 5 0.31 0.1 0.07

Schrankia leptocarpa Fabaceae 2 3.31 10.96 0.03

TOTAL 69 41 379.9

MEAN 5.31 3.15 29.2

Variance = 29.2


= 5.40


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CHAPTER FIVE

5.0 DISCUSSION

The report shows the effects of Guinness brewery effluent on the distribution of plants

along its effluent channel. Some of the effects the indiscriminate dispersal of industrial and urban

wastes generated by human activities are the contamination of the soil and plant communities

and the pollution of the aquatic environment, controlled and uncontrolled disposal of wastes,

accidental and process spillage, mining and smelting of metalliferous ores and sewage sludge

application to agricultural soils. (Ikhajiagbe et al., 2013). These processes are responsible for the

migration of contaminants onto noncontaminated sites (Ghosh and Singh, 2005). Unfortunately,

in developing countries like Nigeria where effluent quality standards imposed by legislation

(where they exist) are sometimes easily flouted, waste water is indiscriminately discharged into

water bodies which are the primary receivers (Okereke, 2007). Industrial effluents are liquid

wastes which are produced in the course of industrial activities. This has however been a major

concern to both government and industrialist.

Even though the disposals of effluents are technologically and economically achievable

for particular standard, industries do not comply with pretreatment requirement. Brewery

industries produce waste waters like spent cooling water, spent grain and hop liquors, liquor

from yeast recovery system and wash down water. Waste such as dry brewery grain and spent

grain are used as animal feedstuff and therefore, do not create disposal problems. Brewery waste

water can be applied to lands after a limited pretreatment (screening and equalization) if the

lands are readily available (Otta and Cable, 1987). There was an observed increase in most of the

parameters studied with little fluctuations in some of the parameters. The introduction of

wastewater, high in organic matter and essential nutrients brings about changes in the microflora


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(Rheinheimer, 1991). The physico-chemical parameters investigated showed some variation

along the sampled sites (Table 1).

The pH of soil is one of the most important physicochemical parameter. It affects mineral

nutrient, soil quality and much microorganism activity (Kiran, 2013). It has been found that soil

pH is correlated with the availability of nutrients to the plant (Gray et al., 1998). Consequently,

as pH decreases, the solubility of metallic elements in the soil increases and they become more

readily available to plants (Oliver et al., 1998; Salam and Helmke, 1998). There were slight

variations in the PH in the three quadrants sampled. The PH values ranged from 5 to 7, an

indication that effluent from the brewery was slightly acidic. The recorded PH values fell within

the effluent limitation guidelines and discharge standards, an indication of the basic nature

(Emmanuel and Jacob, 2013; Kiran, 2013).

The presence of organic nitrogen in effluent in substantial amount like other tested

parameters signifies the need for treatment to avoid the associated adverse effects. The values of

organic nitrogen ranged from 16.44 mg/kg to 22.20 mg/kg (Table 1). These values are slightly

above the value of 20 mg/l given for effluent discharged in aquatic ecosystem by the FEPA 1988

but well below the value of 100 mg/L given by General Standard (Emmanuel and Jacob, 2013).

Many of the ions which are harmless or even beneficial at relatively low concentrations may

become toxic to plants at high concentration, either through direct interference with metabolic

processes or through indirect effects on other nutrients, which might be rendered inaccessible. A

number of elements are normally present in relatively low concentrations, usually less than a few

mg/kg. These are called trace elements and include manganese (Mn) and vanadium (V). Heavy


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metals create health hazard when taken up by plants. Heavy metals include copper (Cu), lead

(Pb), mercury (Hg), arsenic (As), zinc (Zn) and cadmium (Cd).

Cadmium levels in all the soil samples were found in trace amounts between 0.27 0.37 mg/kg.

These values are far below the natural limits of 0.01 3.0 mg/kg in soil (MAFF, 1992 and EC,

1986). The mean level of Pb 1 0.13mg/kg was also, far lower than EC (1986) limits of

300mg/kg and the maximum tolerable levels proposed for agricultural soil of 90400 mg/kg set

by the WHO (1993) and NEPCA (2010). Normal range for calcium is between 0.98 2.45 in soil.

The samples collected from quadrants 2 and 3 (Table 1), were above the normal (Kiran, 2013).

Electrical conductivity (EC) is a measure of the total ionic composition of soil and its

overall chemical richness. It is primarily determined in soil by the presence and levels of

concentration of sodium and magnesium ions and to an extent, calcium ions. Their ions help

buffer the effect of bicarbonate and carbonate ions, thus maintaining the pH of the soil

(Ikhajiagbeet al., 2013). The conductivity range of the various quadrants was wide and varied,

considerably between 137 uS/cm to 185 uS/cm. These values however do not suggest a normal

soil (Kiran, 2013). The electrical conductivity of the soil is a useful indicator of its salinity or

total salt content (Ikhajiagbeet al., 2013).


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CONCLUSION

Treated brewery effluent discharges onto arable agricultural lands will lead to oxygen depletion,

increase in plant biomass, decrease in species diversity and changes in the dominant biota of the

agricultural lands. The studies showed an increase in the concentration of some parameters of

samples collected close to the brewery, with decreases in concentration further away from the

brewery. The increase in concentration leads to an increase in biomass as seen in the result in the

total number of plant species.

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