UNIVERSITY OF

COPENHAGEN

Master’s thesis

Lekka Eleni

Effect of some traditional processing methods on the

protein content of legumes from Ghana

FACULTY OF SCIENCE

DEPARTMENT OF FOOD SCIENCE

Academic supervisors:

Mette Holse (PhD)

Birthe Møller Jespersen (Associate professor)

COPENHAGEN

AUGUST, 2014

I

ACKNOWLEDGEMENTS

The completion of this project was done in the implementation of the Master’s program “Gastronomy and

Health”, which was co-funded by the Act “Scholarship program of the National Scholarship Foundation of

Greece IKY”, with the resources of the Operational Program “Education and Lifelong Learning” of the

European Social Fund (ESF) and the National Strategic Reference Freamework (NSRF) 2007 – 2013.

I would like to thank my supervisors, Mette Holse (PhD) and Assosciate Professor Birthe Møller Jespersen for

trusting me with this project. I strongly appreciate their guidance, advice and comments, as well as their positive

perspective through any adversities that came up during this project. Their valuable knowledge and friendly

attitude helped me finish the present project.

A special thanks to the trainee lab technician Trine Ann–Mirll Lilla Pedersen for her insightful

recommendations and her patience in providing all the technical support.

I would also like to thank Associate Professor Thomas Skov for his assistance during the result analysis, and

Associate Professor Dennis Sandris Nielsen for his for his guidance in developing and delivering the

fermentation process.

Last but not least, I would like to dedicate this project to my parents and brother in Greece, while expressing

my utter love and gratitude to them. Without their support, love and motivation I wouldn’t have made it so far.

II

ABSTRACT

Malnutrition is a major problem in developing countries. The diets of people lack animal protein

sources and consist mainly of starchy roots, cereals and a few legumes. The present trend in

population growth indicates that the protein gap may continue to expand, unless measures are taken.

Alternative sources of protein need to be found, and attention should be directed to plant proteins.

Legumes are a good source of protein, essential amino acids, polyunsaturated fatty acids, minerals

and calories. They also contain, however, anti-nutritional factors that are known to lower the

nutritional quality of legumes. Germination and fermentation are two traditional processing methods

that are believed to reduce the anti-nutritional factors and improve the nutritional composition of the

legumes overall.

In the present study the effect of germination and fermentation on the protein content of legumes

collected in Ghana was examined. Six different legumes, namely soybean, cowpea (two cultivars),

jack bean, velvet bean and bambara groundnut were subjected to germination for 48-72h at 30oC,

and fermentation at 30oC and 37

oC for 48h. The crude protein content of the raw and processed

legumes was determined. Furthermore, the overall composition was assessed using spectroscopic

methods (FT-IR, NIR).

All six legumes showed a notable increase in their crude protein content. The increase was, in most

cases, more pronounced in the fermented samples. Regarding the increase in protein content,

germination for 72h seemed to yield better results than for 48h; however, no conclusive evidence on

the superiority of one temperature over the other was found in the fermented samples. As far as the

overall composition is concerned, both FT-IR and NIR pointed out soybean as the most

differentiated samples with regards to protein, lipid and carbohydrate content.

III

LIST OF ABBREVIATIONS

ANF Anti-Nutritional Factor

CHO Carbohydrates

CVD Cardiovascular Disease

EEA Essential Amino Acids

FAO Food an Agriculture Organization

FR-IR Fourier- Transform infrared

IR Infrared

IVPD In vitro Protein Digestibility

MDGs Millenium Development Goals

MI Myocardial Infraction

NIR Near - infrared

PC Principal Component

PCA Principal Component Analysis

PUFA Polyunsaturated Fatty Acids

RS Resistant Starch

USDA U.S. Department of Agriculture

WHO World Health Organization

IV

TABLE OF CONTENTS

Περιεχόμενα ACKNOWLEDGEMENTS ........................................................................................................................................ I

ABSTRACT ............................................................................................................................................................ II

LIST OF ABBREVIATIONS ..................................................................................................................................... III

TABLE OF CONTENTS .......................................................................................................................................... IV

TABLE OF FIGURES .............................................................................................................................................. VI

TABLE OF TABLES ............................................................................................................................................... VII

INTRODUCTION ................................................................................................................................................... 1

1. Nutrition trends in Africa ......................................................................................................................... 1

2. Legumes ................................................................................................................................................... 4

2.1. Composition..................................................................................................................................... 5

2.2. Health benefits ................................................................................................................................ 9

2.3. Methods of processing and cooking legumes ............................................................................... 10

3. Composition of individual legumes ....................................................................................................... 12

3.1. Soybean (Glycine max, L.) .............................................................................................................. 12

3.2. Cowpea (Vigna unguiculata) ......................................................................................................... 13

3.3. Jack bean (Canavalia ensiformis) ................................................................................................... 15

3.4. Bambara groundnut (Vigna subterranea) ..................................................................................... 17

3.5. Velvet bean (Mucuna pruriens var. utilis) ..................................................................................... 19

4. Processing methods............................................................................................................................... 22

4.1. Germination ................................................................................................................................... 22

4.2. Fermentation ................................................................................................................................. 26

5. Experimental theory .............................................................................................................................. 29

Mid- and Near- Infrared spectroscopy ...................................................................................................... 29

AIM OF THE STUDY ............................................................................................................................................ 32

MATERIALS AND METHODS............................................................................................................................... 33

Screening of samples ..................................................................................................................................... 33

Preparation of samples for analyses ............................................................................................................. 33

Germination of samples ............................................................................................................................ 33

Fermentation of samples........................................................................................................................... 34

V

Control samples ......................................................................................................................................... 34

Defatting of soybean samples for protein determination ........................................................................ 35

Samples’ assessment ..................................................................................................................................... 35

FT-IR (Fourier transform infrared) spectroscopy ....................................................................................... 35

NIR (Near infrared) spectroscopy .............................................................................................................. 35

Determination of moisture content .......................................................................................................... 36

Determination of fat content .................................................................................................................... 36

Determination of protein content ............................................................................................................. 37

Data analysis .................................................................................................................................................. 38

RESULTS AND DISCUSSION ................................................................................................................................ 39

Screening Test ............................................................................................................................................... 39

Proximate Composition ................................................................................................................................. 40

Fourier-Transform Infrared (FT-IR) Spectroscopy ......................................................................................... 41

Near infrared (NIR) spectroscopy .................................................................................................................. 44

Effect of fermentation and germination on protein content ........................................................................ 48

CONCLUSIONS ................................................................................................................................................... 52

PERSPECTIVES .................................................................................................................................................... 52

BIBLIOGRAPHY ................................................................................................................................................... 53

APPENDICES ........................................................................................................................................................... i

Appendix 1 – FT- IR spectra ............................................................................................................................... i

Appendix 2 – NIR spectra ................................................................................................................................ iv

VI

TABLE OF FIGURES

Figure 1: Overview of the main pulse producing countries in 2011 (in million tons). ........................................ 3

Figure 2: Schematic representation of wild/ underutilized legumes, their potential value, and exploitation for

development of new products. ........................................................................................................................... 5

Figure 3: FT-IR PCA scores plot of raw beans .................................................................................................... 39

Figure 4: FT-IR spectra (MSC) of the germinated, fermented, and control samples. ....................................... 41

Figure 5: Mean FT-IR spectra (MSC) of the control legume samples.. .............................................................. 42

Figure 6: PCA scores plot of the FT-IR raw (MSC) spectra (PC-1/PC-2) (a), and PCA loading plots for PC-1 (b)

and PC-2 (c)........................................................................................................................................................ 43

Figure 7: NIR raw spectra (MSC) of the germinated, fermented, and control samples .................................... 44

Figure 8: Mean FT-IR spectra (MSC) of the control legume samples.. .............................................................. 45

Figure 9: PCA scores plot of the NIR raw (MSC) spectra (PC-1/ PC-2).. ............................................................. 46

Figure 10: NIR PCA loadings plots for PC-1 (a), PC-2 (b) and PC-3 (c). .............................................................. 47

Figure 11: PCA scores plot of the NIR raw (MSC) spectra (PC-1/ PC-3).. ........................................................... 48

Figure 12: % Protein content (DM) of the germinated, fermented and control samples. ................................ 49

VII

TABLE OF TABLES

Table 1: Main non-nutrient bioactive pulse compounds and their main potential positive and beneficial

effects .................................................................................................................................................................. 9

Table 2: Proximate composition of the legumes used in the study according to literature. ............................ 21

Table 3: Literature review on the effect of legume germination on protein content and in vitro protein

digestibility. ....................................................................................................................................................... 24

Table 4: Literature review on the effect of legume germination on protein content and in vitro protein

digestibility. ....................................................................................................................................................... 28

Table 5: Proximate composition of the raw bean samples (Moisture, Fat and Protein) .................................. 40

Table 6: % Protein content (DM) of the germinated, fermented and control legume samples (dry weight

basis) .................................................................................................................................................................. 48

1

INTRODUCTION

1. Nutrition trends in Africa

Over the past 20 years the number of undernourished persons in the developing world slowly

decreased from one billion in 1990-1992 to 842 million in 2011-13, which is a reduction of 200

million persons. Still, the reduction is too low, if the goal of 500 million undernourished by the year

2015 as envisaged by the Millennium Development Goals (MDGs) is to be achieved. The percentage

of undernourished persons in developing countries dropped from 23,6% in 1990-92 to 14,3% in

2011-13, which is a reduction of 10%. However, for the same time period in the African region, the

drop was from 32,8% in 1990-92 to 24,8% in 2011-13. So, according to the above results Africa

remains the region with the highest proportion of undernourished people compared to the other

developing countries, and this proportion also declined more slowly (FAO, 2014). Furthermore, in

West Africa, one third of children under five years of age are stunted, and 5-15% are wasted.

Micronutrient deficiencies, particularly lack of vitamin A, iron and iodine, affect mainly women and

children and contribute to some of the highest rates of child mortality in the world (Lopriore &

Muehlhoff, 2003).

However, undernourishment is not the only problem African people face. Within the past generation,

diets have changed, with increased energy and fat intake, but decreased fiber intake (Bourne et al.,

1993). Overweight and obesity are emerging problems in some urban populations, associated with

rising prevalence of the nutrition-related diseases (Lopriore & Muehlhoff, 2003). Thus, major

increases have been observed in obesity in women, hypertension and diabetes in both sexes and

cerebrovascular disease (Walker & Segal, 1997; Walker, 1996).

The causes of malnutrition and food insecurity are not a one-dimensional matter and they include the

agro-ecological, socio-economic and demographic characteristics of the region. Rising incomes,

continuous increase in population principally in urban areas, desertification, as well as HIV/AIDS

have an effect on the food system. Changes in diets and lifestyles, especially in urban areas, include a

shift from the consumption of traditional staples to imported cereals (wheat and rice). Although food

availability has generally improved in the region, the dietary energy and protein supplies are still

inadequate, eminently in Sahelian countries (Lopriore & Muehlhoff, 2003; Perumal Siddhuraju,

2

Vijayakumari, & Janardhanan, 1996). Apart from this, high prices of available staple foods, and

policies constricting food imports are also contributing factors that have been aggravating the food

situation in the developing countries (Weaver, 1994).

The diets of people in many developing countries lack animal sources of proteins, because they are

expensive and out of reach for low-income families, and instead consist mainly of starchy roots,

cereals and a few legumes (Obatolu, Augustine, & Iken, 2007). Honfoga & van den Boom (2003)

attribute the high prevalence of protein inadequacy in the coastal countries to the role of root crops in

the southern diets and their relative absence in those of the north. The lessening role of pulses and

animal products – both eminent sources of protein and micronutrients – indicates that the quality of

the diet in the region has decreased as a result of both deficient supplies and an uneven distribution

of the different groups of food. Furthermore, there are data indicating the growing dominance of

cereals as sources of dietary protein compared with legumes and animal products, particularly in the

coastal countries of West Africa. Cereals and tubers contribute 45% and 25% respectively of the

dietary protein in the coastal zone, whereas animal proteins (including meat, poultry, dairy products,

eggs, etc.) account only for 16% (Lopriore & Muehlhoff, 2003). Alexandratos (1995) points out that

many of the developing world‘s poorest producers and most undernourished households depend on

roots and tubers as a contributing, if not principal, source of food and nutrition. Also, in Nigeria,

cassava was found to be a major national food and cash crop, according to the statistics on cassava

production and consumption (Kolapo, 2011). Between 1990 and 2011, there was an increase in the

share of energy supply derived from cereals, roots and tubers in Central Africa, and East Africa.

Southern Africa experienced no growth, while North Africa and West Africa recorded a slight drop

(FAO, 2014).

Taking all the above into consideration, and counting in the present trend in population growth, it is

believed that the protein gap will continue to increase in the future unless well-planned measures are

taken. Since provision of adequate proteins of animal origin is difficult and expensive, plant proteins

could be a good alternative for improving the nutritional status of the people. Grain legumes are used

in combination with cereals, as they enhance the protein content of cereal-based diets and may

improve their nutritional status (Iqbal, Khalil, Ateeq, & Sayyar Khan, 2006). In Nigeria for example,

popular legumes, such as cowpeas, beans, and groundnuts, are commonly consumed with grains

(rice, maize) and tubers (cassava and yam) to complement their low protein content (Yusuf, Ayedun,

& Sanni, 2008). Legumes could also constitute an affordable and convenient supplement to

commonly used foods for weaning-age, since the nutritional value of complementary foods for

young children is a priority (Lopriore & Muehlhoff, 2003).

3

In 2010-2011 Africa was, in terms of volume, the second largest producer of pulses after Asia. In

general, pulse production in West Africa grew at an annual rate of 6,6% over the years 2000-2010

due to expansion of area (FAO, 2014). An overview of the main legume producing countries of

Africa can be seen on Figure 1.

Figure 1: Overview of the main pulse producing countries in 2011 (in million tons). (Lopriore & Muehlhoff, 2003)

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2. Legumes

Legumes belong to the Leguminosae (or Fabaceae) family, which is the third largest family among

flowering plants, comprising of approximately 650 genera and 20.000 species (Doyle, 1994). All

members of the Leguminosae have the characteristic of bearing pods, but the plants range in size

from the tiny wild vetches of the temperate zones to large tropical trees. The family is divided into

three sub-families: Papilionoideae, Mimosoideae and Caesalpinioideae. Members of the

Papilionoideae are mainly herbaceous, often annual plants, which grow throughout the world, from

the tropics to high mountainous and cool regions. Most of the important legumes in human diets

belong to this sub-family, which amounts to about two-thirds of the Leguminosae species.

Mimosoideae consist of mainly small trees and shrubs of the semi-arid tropics and subtropical

regions, whereas Caesalpinioideae are mainly trees of tropical regions. Generally, the species of

these two sub-families are not cultivated for human consumption; yet the pods and seeds may be

gathered as food in some places of the world, as in the case of Parkia spp. (Caesalpinioideae).

(Aykroyd & Doughty, 1982)

Legumes cultivation history goes back to Neolithic times. They were among the earliest food crops

to be cultivated, when man was transitioning from hunting and food-gathering into the food-

producing stage of human development (Aykroyd & Doughty, 1982). Starchy legumes are known to

be consumed by humans since the earliest practice of agriculture, and medicinal, cultural, as well as

nutritional roles have been attributed to them (Phillips & McWatters, 1991). Legumes have

historically been part of inexpensive meals throughout the world, due to their important role in the

fight against malnutrition (Bamshaiye, Adegbola, & Bamishaiye, 2011)

According to the Food and Agriculture Organization (FAO) statistics for 2001, 274 million metric

tons of grain legumes were produced across the world, compared with 2 trillion metric tons of

cereals. 177 million of them were soybeans (Glycine max; one-half of which were produced in the

U.S.) (FAO, cited from Wang et al., 2003).

Legumes are an important element in the diet of both human and other animals and they constitute

the main protein source in some developing countries (Wang et al., 2003). Although many common

protein-rich edible legumes are available on the market, in many cases the production rate fails to

fulfill the ever-growing demand (Ali & Kumar, 2000). Furthermore, the swift, by a considerable part

of the world‘s population, to a protein-rich vegetarian-based diet has created and unjustified shortage

of plant resources. In this respect, legumes have been pointed out as a good alternative to animal

5

protein, which is at the same time cost effective (Famurewa & Raji, 2005). Taking the above into

consideration, it is crucial that governments, food scientists and nutritionists search for cheap,

reliable, and safe plant-based resources to meet the growing demand for protein-rich foods. Wild and

underutilized legumes, that are unexplored, underutilized or utilized only in specific regions, are a

good alternative that the researchers should focus on (Bhat & Karim, 2009). A schematic

representation of the potential value and exploitation for development of new products of

underutilized legumes is depicted on Figure 2.

Figure 2: Schematic representation of wild/ underutilized legumes, their potential value, and exploitation for development of new

products (Bhat & Karim, 2009).

2.1. Composition

Legumes are a good source of non-processed protein. They have significant amounts of fiber and

resistant starch, making them one of the least glycaemic sources of carbohydrates. Their lipids

mainly constitute of unsaturated fatty acids. They are also rich in minerals and vitamins, ensuring a

high biological value (Aykroyd & Doughty, 1982; Bamshaiye et al., 2011; Bojňanská, Frančáková,

Líšková, & Tokár, 2012).

6

2.1.1. Carbohydrates – Dietary Fiber

Carbohydrates constitute the main fraction of legumes (50–60%, dry basis). The most predominant

components are starch (22–45%, dry basis) and non-starch polysaccharides dietary fiber. Legumes

also contain a small but significant amount of oligosaccharides, especially the rafinose family of

oligosaccharides (Utrilla-Coello, Osorio-Diaz, & Bello-Perez, 2007; Wang et al., 2003).

Starch is used as the main carbon reservoir in many grain legumes (e.g. pea), however a lack of

starch has been reported in some seeds, such as leguminous oilseeds or those containing gum (Wang

et al., 2003; Aykroyd & Doughty, 1982). There is much genetic variation for both the total seed

content and the composition of starch (Wang, Bogracheva, & Hedley, 1998). The starch granule is

composed of a mixture of amylose and amylopectin. Legume starch provides less energy than the

cereal one, due to its almost double amylose content and the properties of the granules. High amylose

content results in delayed starch gelatinization, thus affecting normal cooking properties (Aykroyd &

Doughty, 1982; Wang et al., 2003). Compared to other foods such as cereals, tubers and unripe

foods, raw and processed legumes contain significant amounts of ‗resistant starch‘ (RS) (Utrilla-

Coello et al., 2007) It is known that the formation of RS is at least partially dependent on the content

of amylose in the starch (Tharanathan & Mahadevamma, 2003). RS contributes to the total

unavailable carbohydrates that are considered to be important in fighting certain forms of cancer

(Aranda et al., 2001).

Legumes exhibit a higher sugar content compared to cereals. The major sugar in legumes is sucrose

and they also contain substantial amounts of oligosaccharides. Legumes also contain small quantities

of sucrose (Aykroyd & Doughty, 1982). The oligosaccharides, comprising part of the legumes‘

dietary fiber, are indigestible to the mammalian enzymes and their degradation occurs in the lower

bowel, where they are fermented by the gut microflora, producing flatus that causes discomfort in

humans and diarrhea in animals (Aykroyd & Doughty, 1982; Wang et al., 2003).

Legumes dietary fiber also includes a heterogenous mixture of several types of polysaccharides.

Hulls are typically composed mainly of cellulose, varying levels of hemicelluloses and lignin, which

serve as cell wall structure modifiers, whereas cotyledon fibers typically consist of nonstructural

polysaccharides such as hemicelluloses, pectins and gums. The physiological benefits of high fiber

intake are increased fecal bulk and moisture, reduced plasma cholesterol, and positive influence on

blood glucose and insulin concentration (Dalgetty & Baik, 2003; Sridhar & Seena, 2006;

Tharanathan & Mahadevamma, 2003).

7

2.1.2. Lipids

Most legumes contain only minor amounts of fat (less than 3%), of which oleic and linoleic acids are

the main unsaturated ones, and palmitic acid the saturated. Linoleic acid is an essential fatty acid for

human nutrition. In general, oils from temperate-zone legumes tend to have more unsaturated fatty

acids compared to those of the tropics. Moreover, some legume species contain a considerable

proportion of linolenic acid (Aykroyd & Doughty, 1982).

Of all edible oils, that from soybeans is the most important, with an estimated world production in

1980 of about 15 million metric tons (Aykroyd & Doughty, 1982).

2.1.3. Protein

Legumes are rich in proteins (18–25%). Even the ones with the lowest protein contents, like

Bambara groundnuts, chickpeas and Lima beans, have a protein content about three times higher

than rice (6,4%). Soya bean is unique in containing about 35–43% proteins (Aykroyd & Doughty,

1982; Tharanathan & Mahadevamma, 2003). Compared to meat, our main source of protein,

legumes are deficient in sulfur-containing amino acids (methionine, cystine and cysteine). However,

except for groundnut, they contain adequate amounts of lysine, thus being an appropriate

supplement to cereals, in which lysine is limiting (Aykroyd & Doughty, 1982; Farzana & Khalil,

1999; Phillips et al., 2003; Wang et al., 2003).

The protein of legumes can be classified into two groups: storage proteins and non-storage proteins.

Storage proteins constitute 70-80% of the total legume proteins and are present mainly in the protein

bodies. They are the primary components of the mature seeds and are mostly globulins. They are few

in number and have large molecular weights. Storage proteins are the ones hydrolyzed during

germination to provide nitrogen and carbon skeletons for the developing seedling. Non-storage

proteins are structural components (in membranes and cell walls) and functional components (e.g.

enzymes) of the cell. They account for the rest 20-30% of the legumes‘ protein content and, in

contrast to storage proteins, they are predominantly albumins and glutelins. Most legume protein

contains about 70% globulin, 10-20% albumin and 10-20% glutelin. Other proteins that may be

present in considerable amounts and may have an effect on the overall amino acid composition are

urease, hemagglutinins and trypsin inhibitors (Aykroyd & Doughty, 1982; Sridhar & Seena, 2006;

Wang et al., 2003).

8

2.1.4. Other nutrients

Legumes supplement cereals not only for protein but also for minerals and vitamins of the B

complex. This is of great importance when refined cereals such as milled rice or white wheat flour

are used in a poor diet with few supplementary foods (Aykroyd & Doughty, 1982).

As far as water-soluble vitamins are concerned, legumes have a thiamin content equal or slightly

higher than that of whole cereals (0.3-1.6 mg/ 100g). They contain low quantities of rivoflavin (0.1-

0.4 mg/ 100) and they have a lower content of pantothenic acid, compared to cereals. They are

however, a fairly good source of nicotinic acid (2mg/100g on average) and they have significant

amounts of folic acid, higher than that of most of the common foods. Furthermore, legumes as

consumed are almost devoid of ascorbic acid, with germinated seeds being an exception. Regarding

the fat-soluble vitamins, only vitamin A and vitamin E in legumes have received much attention.

Legumes contain only small amounts of carotenoids (provitamin A) (Aykroyd & Doughty, 1982;

Phillips et al., 2003).

Legume seeds have a potential of providing all 15 of the essential minerals required by man,

although their concentrations depend on both genetic and environmental factors (Grusak, 2002;

Wang et al., 2003). Legumes have a substantially higher calcium content than most cereals (typical

value 100mg/100g); yet, the absorption and utilization of their calcium may be compromised due to

the considerable amounts of phytic acid in legumes. Legumes are also moderately good sources of

iron (7 mg/100g on average) (Aykroyd & Doughty, 1982).

2.1.5. Anti-nutritional factors

Legumes contain a number of bioactive substances (Table 1), which wield metabolic effects on

humans and animals consuming them. Upon regular consumption of pulses, these substances may

have positive, negative or both effects. Most of these bioactive substances have been labeled as ‗anti-

nutritional factors‘ (ANFs) (Champ, 2002). Some of the ANFs such a protease inhibitors, lectins,

tannins, goitrogens, cyanogens, amylase inhibitors and anti-vitamin factors are heat-labile; Whereas

others such as toxic ammo acids, alkaloids, cyanogenic glucosides, saponins, flavones and

isoflavones, and pyrimidine glucosides are heat-stable (Mohan & Janardhanan, 1995). In many cases,

the contents of ANFs in legumes may range depending on the variety and/ or cultivar, climatic

conditions, location, irrigation conditions, types of soil and year during which they are grown

(Fasoyiro, Ajibade, Omole, Adeniyan, & Farinde, 2006) .

The presence of ANFs can affect the protein digestibility of the pulses (Adebowale, Adeyemi, &

Oshodi, 2005). Nevertheless, processing methods such as soaking, boiling and autoclaving have been

9

found to reduce or even eliminate them (Amarowicz & Pegg, 2008; Udensi, Ekwu, & Isinguzo,

2007; Udensi, Onwuka, & Oyewer, 2005) In general, all kinds of thermal treatment inactivate anti-

nutritional enzymes (Tharanathan & Mahadevamma, 2003). Furthermore, there is evidence that

processing methods like fermentation or germination can alter the phenolic composition of the

legumes (Amarowicz & Pegg, 2008).

Table 1: Main non-nutrient bioactive pulse compounds and their main potential positive and beneficial effects (Champ, 2002)

2.2. Health benefits

Addition of legumes into the human diet in developing countries can offer protective effects against

chronic diseases (Amarowicz & Pegg, 2008). Partial replacement of animal foods with legumes, has

been shown to improve nutritional status. Plant foods, including legumes, contain low levels of

cholesterol and high amounts of fiber, which reduces the risk of bowel diseases, including cancer.

Moreover the high calcium levels in legumes can help in the prevention of osteoporosis (Guillon &

Champ, 1996; Sirtori & Lovati, 2001). In several countries, legumes have increasingly been used in

10

dietetic formulations for the prevention of diabetes mellitus, coronary diseases, colon cancer and to

lower blood cholesterol levels (Tharanathan & Mahadevamma, 2003; Utrilla-Coello et al., 2007).

Legumes may protect against cardiovascular disease (CVD) through various mechanisms.

Consumption of legume protein has been shown to reduce plasma low density lipoprotein

(Kabagambe, Baylin, Ruiz-Narvarez, Siles, & Campos, 2005; Phillips et al., 2003). Kabagambe et al.

(2005) found that consumption of one serving of beans per day resulted in a 38% reduction in the

risk of myocardial infarction (MI), independently of other dietary and non-dietary risk factors for MI.

Furthermore, pulses have a relatively low glycaemic index (about one-half that of white bread). Their

starch is digested more slowly than that of cereals and tubers, thus resulting in less abrupt

postprandial blood glucose and insulin response. For this reason, incorporation of legumes in the diet

of people with insulin-dependent diabetes (Type II) can be beneficial (Phillips et al., 2003; Wang et

al., 2003).

2.3. Methods of processing and cooking legumes

Legumes are usually consumed after processing. Appropriate processing of legumes is really

important, not only because it improves palatability of foods but also because it reduces the levels of

anti-nutrients and toxins and results in an increased bioavailability of nutrients (Aykroyd & Doughty,

1982; Tharanathan & Mahadevamma, 2003). The most common processing methods for legumes are

briefly described below.

Dehulling

Whole legumes with intact hulls need a long cooking time to reach a soft consistency. This is

especially true for legumes with tough seed-coats like bambara groundnuts and velvet beans.

Dehulling of the seeds and splitting the cotyledons to form a ‗dhal‘ reduces cooking time and

eliminates tannins that lower protein digestibility, while at the same time the total protein content and

amino acid composition stay almost intact (Aykroyd & Doughty, 1982; Bressani & Elfas, 1980).

Soaking

Soaking is a preliminary step, prior to cooking, common to almost all methods of preparing legumes.

It helps in the removal of the seed-coat, in moistening and softening the seed so as to shorten the

cooking time, and in reducing the legumes‘ toxin content (Aykroyd & Doughty, 1982; Tharanathan

& Mahadevamma, 2003).

11

Germination and Sprouting

Soaking legume seeds to start the process of germination (malting) is common practice in many parts

of the world and especially Asia, already from the ancient times. The seed- coat splits during the

germination process and is removed by washing. A short period of malting gives a more readily

digested product. The seeds may often be roasted and eaten as whole or ground and used in soups or

side dishes (Aykroyd & Doughty, 1982).

The germination process may be extended by spreading presoaked seeds on damp cloth for up to 48

hours, when the length of the sprouts reaches about 1 cm. The sprouted grains can be eaten raw (with

salt), parched or mixed with flavorings and fried or boiled. In India, China and many parts of Asia

longer sprouts are used raw or cooked as vegetables (Aykroyd & Doughty, 1982).

Cooking: Boiling and Steaming

Heat treatment of all kinds inactivates enzymes and enhances the flavor as well as the nutritional

value of legumes (Aykroyd & Doughty, 1982).

Roasting, parching, toasting and frying

Dry heat is used to cook whole legume seeds in many countries. They may be eaten whole as snacks

or pounded (Aykroyd & Doughty, 1982).

Fermentation

Fermentation is probably one of the oldest processing methods of legumes. The naturally-occurring

fermenting organism may be bacteria or fungi. It is particularly useful for hard beans (e.g. locust

beans and sword beans), for legumes with high toxin content (velvet beans) and for soybeans which

combine a high toxin level with an unpleasant flavor, because it overbears the disadvantage of

cooking time, reduces some toxic components such as flatulence-producing factors and leads to a

better digestible product. The process duration may range from a few hours to months or even years,

for some soy sauces (Aykroyd & Doughty, 1982).

12

3. Composition of individual legumes

3.1. Soybean (Glycine max, L.)

Soybean (Glycine max L.) is a leguminous plant of the family Leguminosae, that grows in tropical,

subtropical and temperate climates (Kolapo, 2011; Onwueme & Sinha, 1991). It is not known when

soybeans were first cultivated in China, but the legume is mentioned in a book dated back to 2800

B.C. (Aykroyd & Doughty, 1982). Today soybean is cultivated throughout East and South Asia,

Africa and America (Kolapo, 2011).

Soybean seeds contain an average amount of 36,5–41,0 % protein on a dry weight basis (Medic,

Atkinson, & Hurburgh, 2014; USDA, 2013). Storage proteins account for 65–80 % of the total

protein in the seed. The major legume storage proteins are the globulins legumin and vicilin, which

in soybeans are called glycinin and b-conglycinin, respectively. Soybean proteins are well-balanced

in the essential amino acids. They have a high lysine content, but they are slightly deficient in sulfur-

containing amino acids (methionine and cysteine) and threonine (Bau, Villaume, Nicolas, & Mejean,

1997; Medic et al., 2014)

Globally, soybean is one of the largest sources of vegetable seed oil (Kayembe & Van Rensburg,

2013. The seeds lipid content accounts for 8,1-24,0% (Medic et al., 2014). Soybeans are high in

polyunsaturated fatty acids (PUFA) (85% of the lipid fraction), and contain no cholesterol (Kolapo,

2011). The most abundant fatty acid is linoleic acid, followed by oleic, palmitic, linolenic, and

stearic acids (Medic et al., 2014).

Due to their high protein and lipid content, soybeans contain only moderate amounts of

carbohydrates (29,0-35,0%) (Atiim, 2011; Medic et al., 2014). Structural carbohydrates in soybeans

include cell-wall polysaccharides (cellulose, hemicellulose, and pectins), while non-structural

carbohydrates involve starch and different mono-, di-, and oligosaccharides. The most abundant

soluble sugars in soybeans are sucrose, raffinose and stachyose. In general, approximately half of the

total carbohydrates in soybean seeds are structural carbohydrates, and the other half are non-

structural (Medic et al., 2014).

Soybeans contain around 9,3% dietary fibers (USDA, 2013); they are very rich in hemicellulose and

cellulose, but exhibit low levels of lignin (Bau et al., 1997). Vitamins present in the seed include

thiamin, niacin, riboflavin, cholin, vitamins E and K (Kolapo, 2011), and ascorbic acid (Kayembe &

Van Rensburg, 2013). Soybeans are also a source of calcium, iron, zinc, copper and manganese (Bau

13

et al., 1997). The antinutritional factors in soybeans include α-galactosides, trypsin inhibitors, phytic

acid, lectins (haemagglutinins) and lipase inhibitors (Medic et al., 2014).

Consumption of soybeans has been linked with many beneficial effects. The proportion of potassium

to sodium (3:1-11:1) is believed to prevent high blood sugar level and help keeping blood sugar

levels under control in diabetic patients. Soy protein can also help diabetic patients in preventing

kidney diseases and improving the cholesterol profile. Furthermore, soybean isoflavones have been

associated with lower prevalence of coronary heart disease through controlling cholesterol, blood

pressure, vascular function and direct effects on the cells of the artery wall. They are also related to

reduction of bone loss that typically occurs after menopause, and can help women with low bone

mineral content prevent hip fractures in post menopausal years. Additionally, in areas of the world

with regular soybean consumption, lower rates of colon cancer, as well as some other cancers,

including breast cancer, are observed (Kolapo, 2011).

The nutrient composition of soybean has influenced its history, as far as food preparations are

concerned. The ancient Chinese evolved methods for food preparations – curd, cheese, sauce, paste –

which they used to flavor and enrich their staple diet of cereals. They also used the sprouts of the

seeds as a vegetable, while some evidence also exists that methods of expressing the oil were

evolved about the 4th

century A.D. (Aykroyd & Doughty, 1982). Soybeans have also been used

extensively in fermentation applications, including soy sauce, natto (whole soybean product), soy

pastes and fermented tofu (Hui, 2012). In Africa soybeans are used in many household preparations,

as they are considered an inexpensive source of dietary protein, mineral, and vitamin for both rural

and urban dwellers (Atiim, 2011). These preparations include dawadawa, soups, porridge, fortified

gari and tapioca and weaning food. Furthermore, soymilk and its derived products (soy-coconut milk

based yoghurt, soy-cow milk based yoghurt, soy-corn milk) are becoming more and more popular

due to the health benefits credited to soybeans (Atiim, 2011; Kolapo & Oladimeji, 2008; Kolapo &

Sanni, 2009; Kolapo, 2011). Last but not least, soybeans are also used for biodiesel production

(Salvagiotti et al., 2008)

3.2. Cowpea (Vigna unguiculata)

Cowpea (also known as black-eyed pea) is botanically called Vigna unguiculata sub-species

sesquipedalis. It belongs to the legume family Leguminosae and sub-family Papilionoideae (Mishili

et al., 2009; Udensi et al., 2007). The seeds vary in size, shape, color and texture. They may be erect,

14

crescent shaped or coiled. Usually they are yellow when ripe, but brown and purple color varieties

also exist (Gómez, 2004).

Cowpea is the second most important legume in Africa after groundnut (Arachis hypogaea) (Mishili

et al., 2009). It is one of the most ancient crops cultivated by man and it is probably a native of West

Africa, although today it is widely grown throughout the world (Aykroyd & Doughty, 1982; Gómez,

2004). Cowpeas are a low input crop and they are heat and drought tolerant (Nell, Siebrits, & Hayes,

1992).

The average crude protein content of cowpeas is 22,0 – 25,6% (Antova, Stoilova, & Ivanova, 2014;

Gómez, 2004), although higher contents have also been reported (Nell et al., 1992). The protein itself

is of good nutritional quality, consisting of 90% water-insoluble globulins and 10% water-soluble

albumins (National Research Counsil, 2006a). Cowpeas are rich in glutamic and aspartic acid, and a

good source of the essential amino acids (EAAs) leucine, arginine, methionine and phenylalanine,

whereas tryptophan is the limiting amino acid (Iqbal et al., 2006; Rangel et al., 2004) Cowpea

proteins contain adequate amounts of most EAAs for pre-school children and all EAAs for adults

(Rangel et al., 2004). According to Phillips et al. (2003) the protein digestibility of raw cowpea flour

is 57%.

The lipid content of cowpeas is relatively low (1,3 – 1,9%) (Antova et al., 2014); yet, contents up to

4,8% have been reported (Iqbal et al., 2006). No matter how low the lipid content might be, it has an

extremely high content of biologically active compounds (tocopherols, sterols, and phospholipids).

The predominant fatty acids in the seeds‘ oil are palmitic and linoleic acid, followed by linolenic and

oleic acid (Antova et al., 2014).

Carbohydrates are in the range of 56,0-66,0% (Gómez, 2004). The starch content in the seed is 28,3

– 36,2% (Antova et al., 2014), whereas the indigestible oligosaccharides, raffinose, stachyose, and

verbascose are also present (Phillips et al., 2003). The fiber and ash contents of cowpeas are 1,7 –

3,8% (Antova et al., 2014; Uppal & Bains, 2012) and 3,2 – 4,2% (Antova et al., 2014; Iqbal et al.,

2006), respectively. Cowpeas are a good source of phosphorous, calcium and iron (Gómez, 2004).

The main ANFs in cowpeas, phytate and trypsin inhibitors, can be minimized by processing

methods, like boiling, roasting and autoclaving (Udensi et al., 2007).

Cowpeas are often call the ―poor man‘s meat‖. They are used in food preparations at home, as well

as for production of street foods (Mishili et al., 2009). The seeds are consumed in grain, split and

ground forms. The ground form has traditionally been a favorite of rural households in Northern

Ghana, because cowpea flour is resistant to post-harvest pest damage, and as it can be used in many

different dishes (Gómez, 2004) In home preparations, cowpeas are often added to sauces and stews.

In the street food sector, cowpeas are commonly used in ―kosai‖ (cowpea fritters) in some inland

15

areas and ―akara‖ (popular West African finger food made from soaked, decorticated, wet-milled

cowpeas) in many coastal countries (Mishili et al., 2009). Other preparations with cowpea flour

include baking applications (muffins, cake-type buttermilk doughnuts, tortillas, tortilla and corn

chips), extruded snacks, weaning foods and fortified traditional foods (Phillips et al., 2003).

Furthermore, in industrialized countries such as the United States and Australia, varieties of cowpea

types are cooked, canned or frozen to make them ready to serve (Quinn, 1999).

3.3. Jack bean (Canavalia ensiformis)

The genus Canavalia (Fabaceae) consists of 4 subgenera with 51 reported species (Smartt, 1990).

Canavalia seeds are large and structurally similar, but vary in size, shape, color and thickness of the

seed coat (Sridhar & Seena, 2006). Generally, the plants belonging to this species display desirable

agronomic features enabling them to grow well in tropical conditions such as high cultivation

temperatures and drought, and they are resistant to pests and diseases (P Siddhuraju & Becker,

2001). They are used as manure, soil binders, as well as an ornamental plant (Bhat & Karim, 2009).

Canavalia ensiformis (Synonym: Dolichos ensiformis L.), commonly known as jack bean, is a New

World pulse that originated in South America and is grown in the tropics and subtropics (Smartt,

1990; Sridhar & Seena, 2006). It is cultivated in drought-prone areas of Arizona and Mexico and

used as high protein food and forage crop (in Southwestern United States, Mexico, Central American

countries, Brazil, Peru, Ecuador and West Indies). In Nigeria, it is used as an ornamental plant,

grown near houses and allowed to trail on walls and trees (Udedibie, 1990). Jack bean is considered

one of the few pulses that grow well on the highly nutrient-deficient lowland tropical soils, because it

can grow relatively easily and produce high yields in the regions of low altitude, and high

temperature and relative humidity (Vadivel & Janardhanan, 2001).

Jack bean has a protein content ranging from 22,8 to 35,3 % (Sridhar & Seena, 2006) It is rich in

aspartic acid, glutamic acid and histidine, and its level of the EAAs isoleucine, leucine and tyrosine

are higher compared to some common legumes; however, it is deficient in sulphur containing

aminoacids (V. Mohan & Janardhanan, 1994). Canavalia seeds exhibit low protein digestibility,

due to the large proportion of globulins and the ANFs and secondary metabolites present (Sridhar &

Seena, 2006). However Siddhuraju & Becker (2001) found a relatively high level (69,0%) of in vitro

protein digestibility (IVPD).

16

The lipid content of C. ensiformis varies between 1,6-12,1% (Bhat & Karim, 2009). PUFA of

Canavalia spp. (71.1–77.6%) surpass those of other common beans, with oleic acid being the major

one (38,6-47,4%) (P Siddhuraju & Becker, 2001). The seed are also rich in essential fatty acids

(linoleic and linolenic acid). The predominant fatty acids of C. ensiformis are palmitic acid, oleic

acid and linoleic acid (Arun, Sridhar, Raviraja, Schmidt, & Jung, 2003).

The crude carbohydrates account for 45,8-65.4% of the seed‘s weight (Bhat & Karim, 2009). They

include monosaccharides, oligosaccharides, starch and other polysaccharides. The oligosaccharides

(raffinose, stachyose and verbacose) are liable for flatulence and lower its acceptance as food. The

high energy content of C. ensiformis (1470-1910 kJ/100g) is attributed to the high starch and

amylose levels (Sridhar & Seena, 2006).

The fiber content of the seeds ranges from 4,7-11,4% (Sridhar & Seena, 2006). Nevertheless, in their

study Siddhuraju & Becker (2001) fount a dietary fiber content of 17,5-23,6%. Ash composition of

Canavalia spp. ranged between 2,3% and 5,8% (Bhat & Karim, 2009). As far as minerals are

concerned potassium was found to be the most abundant mineral (Vadivel & Janardhanan, 2001).

The seeds also contain profuse amounts of sodium, magnesium, phosphorus, and calcium (V. Mohan

& Janardhanan, 1994). In fact, Rajaram & Janardhanan (1992) reported the seeds of C. ensiformis to

be a potential source of minerals fulfilling 2/3 of the recommended dietary allowances by NRC/NAS

(1989).

Despite these desirable features, jack beans are not extensively utilized as a food source due to the

relatively high content of ANFs. Raw seeds of Canavalia spp. consist of ANFs such as phenolics,

tannins, saponins, cyanogenic glycosides, concanavalin A, canavanine and hydrogen cyanide. Most

of them are heat-labile. (Sridhar & Seena, 2006)

The immature pods and seeds of Canavalia ensiformis can be eaten as a green vegetable or even

used in the preparation of pickles. However, the use of mature seeds as food requires care in

preparation, to reduce the toxic compounds present in the seeds. They are normally boiled or

processed before being eaten. Processing includes overnight soaking of the beans in water followed

by boiling (with addition of sodium bicarbonate), washing, and pounding. Jack beans are used in the

preparation of various types of curry as well as a substitute for mashed potatoes in some Asian

countries, including India. Furthermore, roasted and ground beans have been reported to be used as a

substitute for coffee. In general, the overall appeal of these beans to the consumer is low and they are

unlikely to find extensive use as a pulse when alternatives are available. The main reasons for their

lack of popularity could be poor texture and flavor (Bhat & Karim, 2009; Smartt, 1990; Vadivel &

Janardhanan, 2001).

17

C. ensiformis is also interesting in terms of its pharmacological importance. Trigonelline and

canavanine extracted from C. ensiformis have exhibited anticancerous properties and were found to

be cytotoxic to human pancreatic cancer cells (Morris, 1999) Furthermore, the seeds have shown a

cholesterol-lowering effect in hypercholesterolaemic rats (Marfo, Wallace, Timpo, & Simpson,

1990). This could be related to the fact that the seed coats of C. ensiformis contain protein with

complete sequence homology to bovine insulin, which is recognized by human insulin antibodies

(Oliveira, Sales, Machado, Fernandes, & Xavier-Filho, 1999).

3.4. Bambara groundnut (Vigna subterranea)

Bambara groundnut belongs to the family of Fabaceae and sub family of Faboidea, and its botanical

name is Voandzeia subterranea (L.) thousars, synonym of Vigna subterranea (Bamshaiye et al.,

2011). Bambara groundnut is considered the third most important food legume in Africa after

groundnuts (Arachis hypogea) and cowpeas (Vigna unguiculata) (Hillocks, Bennett & Mponda,

2012). It is generally classified as bean, but its seeds are actually dug from the ground like peanuts.

They may be round or elliptical in shape with cream to red/brown color, mottled or black – eyed, and

they are defined by pretty local names such as dove eyes, nightjar, and butterfly. (Adebowale,

Schwarzenbolz, & Henle, 2011; National Research Counsil, 2006b; Ojimelukwe & Ayernor, 1992)

Bambara groundnut originated in West Africa but has become widely distributed throughout the

semi-arid zone of sub-Saharan Africa (SSA), with Nigeria being the major producing country.

Nowadays, it is also found in many parts of South America, Asia and Oceania, where it is cultivated

in a lower extend (Bamshaiye et al., 2011; Hillocks, Bennett & Mponda, 2012) It is considered a

‗famine culture‘ cop, because it tolerant to drought, resistant to pests and diseases and it has the

ability to grow in soils too poor to support the growth of other legumes (Bamshaiye et al., 2011;

Brough & Azam-Ali, 1992). Nevertheless, it is usually given less value and priority in land

allocation because it is primarily grown by women, and for that it is seen as a snack or food

supplement, rather than a fruitful cash crop (Bamshaiye et al., 2011).

The seeds of bambara make a complete food, as they contain sufficient quantities of protein,

carbohydrate and fat. Their protein content ranges from 16,0% to 22,0% (Brough & Azam-Ali,

1992), of which the total EAAs amount to an average of 32,7% (Minka & Bruneteau, 2000).

According to Minka & Bruneteau (2000), lysine is the most predominant EAA with average value of

10,3%, but the nuts also contain appreciable amounts of leucine, phenylalanine, histidine and valine.

18

An unusually high content of methionine, compared to other legumes was also reported

(Murevanhema & Jideani, 2013).

The lipid content of bambara seeds accounts for 6,0 – 9,7% (Adebowale et al., 2011; Yusuf et al.,

2008) The PUFA linoleic (44%) and linolenic (21%) and the saturated palmitic acid (30%) were the

most predominant fatty acids while stearic acid was present in small quantities (Minka & Bruneteau,

2000).

V. subterranea consists of 42,0 – 61,3 % carbohydrates and 2,3 – 3,3% fiber (Brough & Azam-Ali,

1992; Fasoyiro et al., 2006; Yusuf et al., 2008) Sugar analysis showed that 30% of the neutral sugars

were present and identified essentially as glucose and galactose (Minka & Bruneteau, 2000). It also

contains 4,0 – 4,4% ash and around 2% minerals (Fasoyiro et al., 2006; Murevanhema & Jideani,

2013). This legume is a good source of calcium, potassium, magnesium, phosphorus and iron

(Amarteifio, Tibe, & Njogu, 2006) Red seeds contain almost twice as much iron as the cream seeds,

and their consumption could be useful in areas where iron deficiency is a problem (Bamshaiye et al.,

2011). Bambara groundnut has also been reported to contain low levels of trypsin inhibitor and

phenolic compounds (Bamshaiye et al., 2011).

Bambara seeds are consumed in various forms either immature or fully mature (Bamshaiye et al.,

2011). Immature bambara groundnuts may be consumed fresh or grilled, whereas the ripe seeds

demand extended periods of soaking and boiling to render them edible (Brough & Azam-Ali, 1992)

The seed coats are usually removed to reduce the ANFs and fiber content, resulting in better

appearance, texture, cooking quality, palatability and digestibility of the products (Bamshaiye et al.,

2011). The bambara seeds can be just boiled and eaten with salt or fried like peanuts. In many

African countries this legume is used in the preparation of numerous traditional recipes, including

cakes, balls, relishes and sauces. Roasted, pulverized seeds of bambara can be incorporated into

soups. The flour can also be used to make a stiff kind of porridge, called ―Aboboi‖. Many times

bambara based foods are accompanied by cassava or corn preparations. Furthermore, bambara flour

could be a potential alternative for the fortification of traditional weaning foods in Africa. Other

applications, involve bambara groundnut milk (a modified version of extraction of cowpea milk) and

fermented products (Bamshaiye et al., 2011; Brough & Azam-Ali, 1992; Hillocks, Bennett &

Mponda, 2012). Last but not least, some tribes in Congo reportedly roast and pound the seeds for oil

extraction, in spite of their relatively low oil content (Bamshaiye et al., 2011).

Additionally, bambara groundnuts have long been used as an animal feed (Bamshaiye et al., 2011),

while in some African countries the bambara plant has been attributed medicinal properties. It has

been used to treat diarrhea, water from boiling the leaves serves as a pesticide and insecticide and the

19

leaves themselves have been employed to cauterize and heal the animals‘ wounds (Bamshaiye et al.,

2011).

3.5. Velvet bean (Mucuna pruriens var. utilis)

Mucuna pruriens - commonly known as velvet bean or devil bean - belongs to the family

Papilionoideae of the order Leguminosae. The genus Mucuna includes about 150 species of annual

and perennial legumes. There is a great taxonomic confusion about the varietal difference of M.

pruriens, but it is now accepted that there are two varieties namely, M. pruriens var. utilis and M.

pruriens var. pruriens (Agbede & Aletor, 2005; Bhat & Karim, 2009; Pugalenthi, Vadivel, &

Siddhuraju, 2005). Different accessions of M. pruriens vary in color from black to white (V. R.

Mohan & Janardhanan, 1995). Initially, it was Mucuna cochinchinensis that was cultivated in parts

of Southern Nigeria and Senegal, and after this, it is believed that it was spread to other tropical

countries, in Southern and Southeastern Asian regions, along with other known accessions and

subspecies (Bhat & Karim, 2009) Mucuna pruriens var. utilis possesses good nutritional qualities,

exhibits tolerance to adverse environmental conditions such as drought, low soil fertility, and high

soil acidity and it is used as food, forage and cover (Pugalenthi et al., 2005; Vadivel & Janardhanan,

2000).

Velvet bean has a crude protein content of 25,1 - 29,3%, although lower and higher values have also

been reported (Ahenkora, Dadzie, & Osei-Bonsu, 1999; Vadivel & Janardhanan, 2000). That means

that its protein content is higher compared to some commonly consumed legumes like chick pea

(Cicer arietinum), green pea (Pisum sativum) and common bean (Phaseolus vulgaris), but lower than

that of soybean (Glycine max) (Mugendi & Njagi, 2010). The major bulk of the seed proteins

comprises of the globulin fraction, followed by albumin, glutelin and prolamin (Vadivel &

Janardhanan, 2000). The results about the amino-acid profile of Mucuna pruriens var. utilis are

contradicting. In general it is found that the seeds are defcient in sulphur-containing aminoacids

(Ezeagu & Gowda, 2006; Pugalenthi et al., 2005; Vadivel & Janardhanan, 2000); yet, Mohan &

Janardhanan (1995) found that the black coat seeds have high levels of cystein. Furthermore, lysine

was found to be a limiting amino acid in black color seeds (V. R. Mohan & Janardhanan, 1995;

Vadivel & Janardhanan, 2000). In general, velvet beans contain high amounts of the EAAs

isoleucine, tyrosine and phenylalanine, and they meet the recommended FAO/WHO (1990)

reference requirements for 2-5yr old, except for methionine and tryptophan (Mohan & Janardhanan,

20

1995). As far as IVPD is concerned, generally, it ranges between 72% and 77% (Bhat & Karim,

2009; Vadivel & Janardhanan, 2000).

The crude lipid content falls within the range of 4,1 – 7,4%, which is slightly higher than that of most

other legumes (Ahenkora et al., 1999; Vadivel & Janardhanan, 2000). Mucuna beans were found to

contain high concentrations of oleic acid, linoleic acid, palmitic acid and steric acid (Mohan &

Janardhanan, 1995; Pugalenthi et al., 2005).The anti-nutritional fatty acid, behenic acid was also

detected in the Mucuna seeds (Mohan & Janardhanan, 1995).

The carbohydrate content of velvet beans ranges from 49,9 to 61,2 % (Vadivel & Janardhanan,

2000). The soluble sugars account for 9,2% to 10,5% of the seed‘s weight, whereas average values of

total, digestible, and RS of the Mucuna seeds are 27,8%, 17,6%, and 10,1%, respectively (Pugalenthi

et al., 2005). The digestibility of the legume‘s starch is affected by the cell-wall structural features as

well as ANFs present in the seed (Siddhuraju & Becker, 2005). It appears that velvet beans have a

high range of carbohydrate, due to the low fat content, which brings their energy range to 1562-1606

kJ/100g DM (Pugalenthi et al., 2005; Vadivel & Janardhanan, 2000).

Crude fiber comprises of cellulose and hemicellulose, a heterogeneous group in which pentosans

usually predominate over lignin, pectic, and cutin substances. In M.utilis the crude fiber content

varies between 5,3 and 11,5% (Pugalenthi et al., 2005). Ash content in velvet beans accounts for 3,1

– 5,5% (Ahenkora et al., 1999; Vadivel & Janardhanan, 2000). Phosphorus (Ahenkora et al., 1999)

and potassium (Pugalenthi et al., 2005) are the predominant minerals. Velvet beans are also good

sources of calcium, iron, manganese, zinc and copper, and they contain low amounts of sodium

(Mohan & Janardhanan, 1995; Pugalenthi et al., 2005; Vadivel & Janardhanan, 2000).

The seeds of M. utilis also contain many ANFs such as total free phenolics, tannins, L-Dopa, lectins,

protease inhibitors, phytic acid, flatulence factors, saponins, and hydrogen cyanide that can have

adverse effects in monogastric animals (including human) upon regular consumption over a long

period of time (Agbede & Aletor, 2005; Pugalenthi et al., 2005). The average L-Dopa content in

mucuna bean is 3,1 – 6,7% (Mugendi & Njagi, 2010). Increased serum levels of L-Dopa from

consumption of velvet beans leads to high concentration of dopamine in peripheral tissues, inducing

antiphysiological effects such as nausea, vomiting, anorexia, paranoid delusions, hallucinations,

delirium and unmasking dementia (Josephine & Janardhanan, 1992). Nevertheless, L-Dopa,

extracted from the seeds of M. utilis is used in the treatment of Parkinson‘s disease (Pugalenthi et al.,

2005).

Velvet bean seeds are used as food, feed, and for pharmaceutical applications (Bhat & Karim, 2009).

The beans have been traditionally used as a food in a number of countries in Africa, Southeast Asia

and Latin America (Pugalenthi et al., 2005). The immature pods and leaves are used as vegetables,

21

while the seeds are consumed boiled or roasted (V. R. Mohan & Janardhanan, 1995; Vadivel &

Janardhanan, 2000). The beans can be eaten either as such or in combination with cereals. Mucuna

beans are used in various preparations, such as sauces, stews, soups, porridge and fried cakes. Velvet

beans are also used in ‗tempeh‘ (a fermented food) production, roasted and consumed as snacks or as

coffee substitute after grinding (Bhat & Karim, 2009; Pugalenthi et al., 2005). Symptoms such as

dizziness, weakness, vomiting and diarrhea have been reported either immediately or few hours after

eating Mucuna (Pugalenthi et al., 2005).

The seed has high viscosity starch, which can be used as a thickening agent for food products, or as

an adhesive in the paper and textile industries (Vadivel & Janardhanan, 2000). Some groups of

people in Nigeria utilize it as a dye. The bean is also used in indigenous ayurvedic medicine (Prakash

& Tewari, 1999). The leaves of Mucuna are used as blood tonic, whereas the seeds have been widely

used against snakebites and scorpion stings, as a uterine stimulant, aphrodisiac and strong emetic.

They are also used to treat nervous disorders and arthritis (Pugalenthi et al., 2005; Vadivel &

Janardhanan, 2000).

An overview of the proximate composition of the legumes described above can be seen on Table 2.

Table 2: Proximate composition of the legumes used in the study according to literature.

Legume Moisture

(%)

Crude

protein (%)

Crude

lipid (%)

Crude

CHO (%)

Crude

fiber (%) Ash (%)

Energy

KJ/100g

Soybean (Glycine max

L.) a 8,5 36,5-41,0 8,1-24,0 29,0-35,0 9,3 6 1866

Cowpea (Vigna

unguiculata)b 9,2-11 22,0-25,6 1,3-1,9 56,0-66,0 1,7-10,6 3,2-4,2 1405

Jack bean (Canavalia

ensiformis)c 3,8-14 22,8-35,3 1,6-12,1 45,8-65,4 4,7-11,4 2,3-6,0 1470-1910

Bambara groundnut

(Vigna subterranea)d 4,3-14 16-22 6-9,7 42-61,3 2,3-3,3 4-4,4 1536-1732

Mucuna bean (Mucuna

pruriens var. utlis)e 6,7-8,5 25,1-29,3 4,1-7,4 49,9-61,2 5,3-11,5 3,1-5,5 1562-1606

a. Atiim, 2011; Kayembe & Van Rensburg, 2013; Medic et al., 2014; USDA, 2013

b. Antova et al., 2014; Gómez, 2004; Iqbal et al., 2006; Olivera-Castillo et al., 2007; USDA, 2013

c. Bhat & Karim, 2009; Sridhar & Seena, 2006

d. Adebowale et al., 2011; Brough & Azam-Ali, 1992; Fasoyiro et al., 2006; Yusuf et al., 2008

e. Ahenkora et al., 1999; Pugalenthi et al., 2005; Vadivel & Janardhanan, 2000

22

4. Processing methods

The nutritive value of a protein depends on its composition, digestibility and bioavailability of

essential amino acids. The nutritive value of grain legumes depends primarily on their nutrient

contents, and presence or absence of anti-nutritional and ⁄ or toxic factors. With the aim of improving

the nutritive value of legumes, preparation techniques, including soaking, germination,

decortications, fermentation and cooking, have been developed to significantly raise the

bioavailability of nutrients (Ramakrishna, Jhansi Rani, & Ramakrishna Rao, 2008; Uppal & Bains,

2012).

In this chapter the effects of germination and fermentation on the composition and especially on the

protein content of legume seeds is briefly presented.

4.1. Germination

The process of germination has been a common practice in many parts of the world for centuries,

especially in Asian countries. Germination seems to be a simple, inexpensive, yet effective

processing method, bringing about desirable changes in nutritional quality. At present, there is an

increase in the consumption of germinated legumes worldwide, in order to enhance the acceptability

and nutrient content of the diets. Sprouts have been traditionally used in culinary preparations, but

nowadays there is a wider selection of seedlings available for consumer. Furthermore, germinated

legume seeds are used to produce flours of high nutritional value (Kuo, Rozan, Lambein, Frias, &

Vidal-Valverde, 2004; Tharanathan & Mahadevamma, 2003; Uppal & Bains, 2012).

It is known that during germination a sequence of metabolic changes results in the degradation of the

reserve materials in the seeds, partly for respiration and partly for synthesis of new cell constituents

of the developing embryo (Sangronis, Rodríguez, Cava, & Torres, 2005; Vidal-Valverde et al.,

2002). In other words, germination is a complex metabolic process during which the lipids,

carbohydrates, and storage proteins within the seed are broken down, due to increased enzymatic

activity, in order to provide the energy and amino acids necessary for the plant‘s development

(Tharanathan & Mahadevamma, 2003; Uppal & Bains, 2012; G Urbano et al., 2005). Therefore,

important changes in the biochemical, nutritional and sensory characteristics of the seeds can be

observed (Kuo et al., 2004; Vidal-Valverde et al., 2002). Germination improves the palatability,

23

digestibility and availability of certain nutrients (Uppal & Bains, 2012). Furthermore, Yamada et al.,

(2005) proposed germination as a process to reduce allergenicity in rice seeds due to the activation

of endogenous proteases. Nevertheless, some of the changes in the compositional and functional

properties in germinated legumes might be undesirable (Phillips et al., 2003).

During germination complex metabolic processes take place, which may alter the content and

composition of proteins and amino acids in legumes improving their nutritional value. The extensive

breakdown of seed-storage proteins can improve the protein digestibility and amino acid content

(Gulewicz et al., 2008; Martínez-Villaluenga, Gulewicz, Frias, Gulewicz, & Vidal-Valverde, 2007;

G Urbano et al., 2005; Gloria Urbano et al., 2005). A high content of free amino acids can be found

in germinated seeds, due to high amino acid biosynthetic activity in the seedling (Kuo et al., 2004;

Mugendi & Njagi, 2010). As sprouting proceeds, the ratio of essential to non essential amino acids

changes, providing more EAAs (Uppal & Bains, 2012). Additional advantages associated with

germination involve the degradation of some undesirable proteins included in the albumin fraction,

such as lypoxigenase, trypsin inhibitors, lectins and urease, which can interfere in the nutritional

quality of legumes (Martínez-Villaluenga et al., 2007). However, the presence of some potentially

toxic non-protein amino acids has been reported in commercially available seedlings (Kuo et al.,

2004).

Fat and carbohydrates are also broken down during germination (Kuo et al., 2004). Germination is

known to reduce the oligosaccharide content of the seeds (Phillips et al., 2003), while higher levels

of maltose are also present in sprouted seeds (Uppal & Bains, 2012). As a result germinated seeds

have improved carbohydrate and starch digestibility (Ghavidel & Prakash, 2007; Sangronis et al.,

2005). Upon germination, dietary fiber increases. Vitamins, minerals, and secondary compounds,

many of which act as antioxidants, also change dramatically during this process (Kuo et al., 2004).

Elevated levels of vitamin E (Torres, Frias, Granito, & Vidal-Valverde, 2007), vitamin C

(Tharanathan & Mahadevamma, 2003), thiamin, niacin and riboflavin (Phillips et al., 2003;

Tharanathan & Mahadevamma, 2003), iron, calcium and magnesium (Ghavidel & Prakash, 2007;

Sangronis et al., 2005), have been reported in germinated seeds. Sprouting has been found to

increase the antioxidant capacity, as well (Torres et al., 2007).

Much evidence exists on the role of germination in diminishing ANF levels that are present in raw

legume seeds. Germination results in reduction in phytates and tannins (Uppal & Bains, 2012). The

amount of other antinutrient factors, such as the flatulence-producing α-galactosides, trypsin and

chymotrypsin inhibitors, which affect the digestion of proteins, is also minimized after germination

(Kuo et al., 2004; Torres et al., 2007).

24

However, the changes in nutrients and in antinutrient factors occurring during germination depend on

the type of legume and on the sprouting conditions (i.e. time, temperature, light cycle) (Kuo et al.,

2004; Uppal & Bains, 2012). In their study Rodríguez et al. (2008) examined the influence of light

and time on the content of various nitrogen fractions. They found that the influence of light during

germination varied according to the legume, but on the whole was less important than the influence

of germination time in quantitative terms. Table 3 shows an overview of earlier findings.

Table 3: Literature review on the effect of legume germination on protein content and in vitro protein digestibility.

Reference Raw material Time Temperature Light Effect on protein

content IVPD

Akpapunam & Achinewhu, 1985

cowpea 1-3 days room

temperature NS ↔ NR

Akpapunam et al., 1996

Soybean Bambara groundnut

5 days 25°C NS ↑ until day 2 ↓ until day 5

NR

Donangelo et al., 1995

Soybean lupin seed black bean

2 days 28°C - ↔ NR

El-adawy, 2002

chickpeas 3 days 25°C - ↑ ↑

Ghavidel & Prakash, 2007

green gram cowpea

lentil chickpea

1day 22-25°C NS ↑ ↑

Gulewicz et al., 2008 Lupin seeds 5 days 20°C - ↑ NR

Kayembe & Van Rensburg, 2013

Soybean 1-6 days room

temperature (22-26°C)

- ↑ ↔

Martínez-Villaluenga et al., 2007

Peas (3 cultivars)

5 days 25°C - ↑ in 2 cultivars (↓) in 1 cultivar

NR

Mugendi & Njagi, 2010

mucuna bean 3 days NS - ↑ ↑

25

Njintang et al. 2001 common beans 2 days 28°C ±2°C NS ↓ ↑

Obatolu, 2002 Millet

soybean 3 days 32°C ±2°C NS ↑ NR

Ramakrishna et al., 2008

Indian bean 8-32 h 27°C ±2°C NS NR ↑

Rodríguez et al., 2008

Peas Beans Lentils

2-6 days 20°C +/- ↑ NR

Sangronis et al., 2005 black and

white beans 5 days 25°C ±2°C + ↑ ↔

Shimelis & Rakshit, 2007

kidney beans 4 days 25°C - NR ↑

Torres et al., 2007 pigeon peas 4 days 20°C - ↔ NR

Trugo et al., 1999

Soybean black bean chickpea

barley

1-2 days 30°C - (↑) NR

Uppal & Bains, 2012 mung bean

chickpea cowpea

12-60h depending

on the legume

25°C NS ↑ ↑

IVPD: In vitro protein digestibility, NS: not stated, NR: not relevant

Arrows in brackets mean that the change is not statistically significant (P≤0,05)

26

4.2. Fermentation

Fermented food products constitute a very interesting group of foods that not only can be produced

with inexpensive ingredients and simple techniques, but also make a significant contribution to

human diet (Hui, 2012). Food fermentation has been for centuries a popular method to preserve

perishable food products (Hansen, 2004). The availability and acceptability of fermented foods differ

among different cultures (Hui, 2012). The raw materials traditionally used for fermentation are

diverse and include fruits and vegetables, cereals, honey, milk, meat, and fish. Fermented products

cover a variety of products including wine, beer, vinegar, bread, soy sauce, sauerkraut, kimchi,

pickled olives, different fermented milk products, a large number of cheeses, and a variety of

sausages (Hansen, 2004).

The microorganisms participating in food fermentation include bacteria, yeasts, and fungi (molds).

As such, there are four main types of food fermentation based on the key microorganisms

responsible: bacterial fermentation, yeast fermentation, fungal fermentation, and mixed culture

fermentation. The majority fermented foods, especially the traditional or indigenous ones, are

produced using mixed cultures of bacteria, yeasts, or fungi. (Liu, 2012)

Regardless of the microorganism involved, fermentation can also be categorized according to the

starting culture used. Fermentations can basically be performed either by spontaneous fermentation,

by back-slopping, or by addition of starter cultures (Josephsen & Jespersen, 2004). The natural

fermentation is the one performed with endogenous microflora. However, this kind of fermentation

may result to fermentation failures, due to the presence of undesirable microorganisms (Granito &

Alvarez, 2006). In back-slopping, a part of a previous batch of a fermented product is used to

inoculate the new batch. This procedure brings about a higher initial number of beneficial

microorganisms than usually found in raw material and ensures a faster and more reliable

fermentation (Josephsen & Jespersen, 2004). Spontaneous fermentation can be optimized through

back-slopping, resulting in dominance of the best adapted strains (Granito & Alvarez, 2006).

Addition of starter cultures is usually used when inactivation of the indigenous flora by heat

treatment of the raw material is possible, permitting the growth of only the added starter

microorganisms (Josephsen & Jespersen, 2004).

The process of food fermentation can also be assorted into alcoholic, acidic, and alkaline fermen-

tations based on the main products formed or pH changes (Liu, 2012). Alkaline-fermentation is the

fermentation process during which the pH of the substrate increases to alkaline values which may be

as high as pH 9 (Omafuvbe, Shonukan, & Abiose, 2000). The increase in pH is a result of

27

degradation of proteins from the raw material into peptides, amino acids and ammonia (Kiers, Van

Laeken, Rombouts, & Nout, 2000; Parkouda et al., 2009). Changes in pH, titratable acidity, and

viscosity of the fermented product depend on the species or combination of species involved in the

process (Phillips et al., 2003).

Apart from preservation (the main role of fermentation), it also results in enhancement of sensory

characteristics (flavor, texture, or color), and transformation of nutrients (improvement of

digestibility and biofortification), while it is also known to reduce ANFs (Barampama & Simard,

1995; Liu, 2012; Phillips et al., 2003; Smit, Wouters, & Meijer, 2004).

During fermentation, microorganisms oxidize carbohydrates and related compounds in order to

produce energy (Josephsen & Jespersen, 2004). As a result, α-galactooligosaccharides (raffinose,

stachyose and verbascose) contents, soluble fiber and resistant starch, the main flatulence-producing

factors in legumes, are reduced (Granito & Alvarez, 2006). Another major metabolic activity during

fermentation is proteolysis. Bacteria degrade the legume proteins and utilize the released amino

acids. This results to decreased protein content, increased in vitro digestibility and formation of

ammonia (Allagheny, Obanu, Campbell-Platt, & Owens, 1996; M. Granito, Torres, Frias, Guerra, &

Vidal-Valverde, 2005). Furthermore, fermentation seems to enhance the nutritive value of legumes

by decreasing the level of antinutrients in the foods. There is evidence on the reduction of some

antinutritional endogenous compounds such as phytic acid and α-galactosides, but the effect of

fermentation on trypsin inhibitor activity (TIA) and tannin content is still controversial (Granito et

al., 2005).

With regards to sensory qualities flavor, one of the attributes mostly affected by fermentation, is

highly correlated to the degradation of nutrients. Food substrates (carbohydrates, proteins, lipids,

organic acids, amino acids, phenolic compounds, glycosides, etc.) are transformed into nonvolatile

and volatile flavor compounds that affect not only taste but also aroma, and thus, food acceptance.

Particularly, the enzymatic degradation of proteins results in the formation of key-flavor

components, while lipolysis leads to the formation of free fatty acids, which can be precursors of

flavor compounds such as methylketones, alcohols, and lactones. The flavor compounds produced

during fermentation contribute to a range of sensory tastes and aromas such as sweetness (e.g.,

mannitol), sourness (e.g., lactic acid), umami (e.g., L-glutamic acid), bitterness (e.g., hydrophobic

peptides), fruitiness (esters), and sulfurous notes (volatile sulfur compounds). The concentration of

these components and the food matrices in which they are produced affect their overall desirability

or undesirability (Liu, 2012; Smit et al., 2004).

Table 4 shows an overview on what has been done so far on legume fermentation.

28

Table 4: Literature review on the effect of legume germination on protein content and in vitro protein digestibility.

Author Legume Strain Ferm. Time

Ferm. Temperature

Protein content

IVPD

Akpapunam & Achinewhu, 1985

cowpea endogenous grain flora 24-72h 30°C ↔ NR

Azekeet al., 2005 African

yambean Lactobacillus plantarum 48h 30°C ↑ ↔

Baik & Han, 2012 Chickpea

lentil soybean

Rhizopus oligosporous 24 h 30°C ↑ ↔

Baik & Han, 2012 green pea Rhizopus oligosporous 25 h 31°C (↑) ↓

Barampama & Simard, 1995

Common bean Lactobacillus fermentum 72 h 37°C ↔ NR

Czarnecka et al., 1998 "Bomba" bean

"Opal" pea Lactobacillus plantarum NS 30°C NR ↑

Granito & Alvarez, 2006

black beans endogenous grain flora

(Lactobacllus casei, Lactobacillus plantarum)

24 h, 48 h

42°C ↓ ↑

Granito et al., 2005 cowpea (two

varieties) endogenous grain flora 48 h 42°C

↓ (Orituco) ↔ (Tuy)

NR

Khattab et al., 2009

cowpea, pea, kidney bean

Saccharomyces cerevicisiae

24h room

temperature NR ↑

Kiers et al., 2000a soybean Bacillus spp. 24h-48h 37°C NR ↑

Kiers et al., 2000b Soybean cowpea

Rhizopus spp. 44h 30°C NR ↑

Mugendi & Njagi, 2010 mucuna bean Bacillus subtilis 72h 32°C ↑ ↑

Reyes-Moreno et al., 2004

chickpeas Rhizopus oligosporus 48 - 72

h 31-36°C ↑ NR

Shekib, 1994 Lentils

chickpeas endogenous grain flora 4 days 32°C ↑ ↑

Starzynska-Janiszewskaet al., 2012

grass pea Rhizopus oligosporus

Aspergillus oryzae 2 h --> 23 h

37°C --> 30°C NR ↓

Stodolak & Starzynska-Janiszewska, 2008

grass pea Rhizopus oligosporus 31 h 32°C ↑ ↑

IVPD: In vitro protein digestibility, NS: not stated, NR: not relevant

Arrows in brackets mean there is no significant difference

29

5. Experimental theory

Mid- and Near- Infrared spectroscopy

Almost any organic or inorganic compound possessing covalent bonds absorbs various frequencies

of electromagnetic radiation in the infrared region of the electromagnetic spectrum. As with other

types of energy absorption, when molecules absorb infrared radiation, they are excited to a higher

energy state. A molecule absorbs only certain frequencies (energies) of infrared radiation, which

correspond to the natural vibration frequencies of the molecule in question. The energy absorbed

results in an increase in the amplitude of the vibrational motions of the bonds in the molecule.

Symmetric bonds, such as H2 or Cl2, do not absorb infrared radiation. In order for energy to be

transferred a bond must present an electrical dipole that is changing at the same frequency as the

incoming radiation. So, only those bonds that have a dipole moment that changes as a function of

time have the ability to absorb infrared radiation (Pavia, Lampman, & Kriz, 2001).

The simplest types of vibrational motion in a molecule that are infrared active are the stretching and

bending modes. Those are the so-called fundamental absorptions (V) and they result from excitation

from the ground state to the lowest-energy excited state. In general, asymmetric stretching vibrations

occur at higher frequencies than bending vibrations. Usually the spectrum is complicated because

weak overtone, combination, and difference bands are also present. Overtones occur when the energy

status of the molecule is raised beyond the first higher (fundamental) level to the second or third, or

higher energy levels, which are integral multiples of the frequency of the fundamental, to produce

the first, second, and higher overtones respectively. In polyatomic molecules, two or more

vibrational modes can interact in such a way as to cause simultaneous energy changes and give rise

to a vibration of a new frequency within the molecule, which is the sum of multiples of each

interacting frequency. When such a vibration is infrared active, it is called a combination band (V̅comb

= V̅1 + V̅2). Difference bands are similar to combination bands, only the observed frequency in this

case results from the difference between the two interacting bands (V̅diff = V̅1 - V̅2). (Batten, 1998;

Blanco & Villarroya, 2002; Pavia et al., 2001)

The fundamental absorptions are the most intense absorption of energy and they occur at the mid-

infrared (IR) region of the spectrum, with wavelengths ranging between 2500–25000 nm (4000 –

400 cm−1

in wavenumbers). The highest wavenumber associated to an infrared active fundamental

vibration appears at 3998 cm−1

for HF; therefore 4000 cm−1

can be somehow considered the border

of the infrared and the near-infrared (NIR). The NIR spectrum is located between the IR and the

30

visible, at wavelengths found in the 800 nm to 2500 nm (or 4000cm−1

- 12500cm−1

). NIR is

sometimes called the overtone region, but, naturally, the first overtone of vibrations of lower

wavenumber is in the IR region. Absorption of energy in the NIR region is almost exclusively

associated with rising of the energy within the molecule to the first and second overtones and to

combinations of fundamental vibrations. Absorption bands in the NIR are broad peaks, rather than

sharp ones, because of the additive effects (combination of absorbances) of two or more bonds at

each wavelength. In general, overtones and combination tones are much weaker than the

fundamentals; the first ones usually by a factor of 10 to 100, whereas the second and higher

overtones and combination tones are even weaker. The intensity of absorption bands is related to the

degree of anharmonicity of the atoms. Hydrogen, the lightest atom, is associated with almost all

absorption bands in the NIR region. The NIR absorption of polymers, especially in the 4000 to 9000

cm−1

region, stems from the overtones of O-H, N-H, C-H, and S-H stretching vibrations as well as

from stretching-bending combinations involving these groups. Additionally, some electronic

transitions may also appear in the upper range of the NIR, close to the visible, especially in the range

of 9000 cm−1

to 12500 cm−1

(Batten, 1998; Blanco & Villarroya, 2002; Pavia et al., 2001; Sandorfy,

Buchet, & Lachenal, 2007).

Every type of bond has a different natural frequency of vibration. Furthermore, two bonds of the

same type in two different compounds are in two slightly different environments. So, no two

molecules of different structure can have exactly the same IR and NIR absorption patterns (IR and

NIR spectra). Thus, the analysis of the molecular bonds of a sample in the IR and NIR spectrum and

creates a characteristic spectrum that acts as a ―fingerprint‖ of the sample. By comparing the spectra

of two substances, one can establish whether they are, in fact, identical. A second and more

important use of the IR and NIR spectra is to determine the structural information about a molecule.

The absorptions of each type of bond (N-H, C-H, O-H, C-X, C=O, C-O, C-C, C=C, C ≡C, C≡N, and

so on) are regularly found only in specific small portions of the vibrational infrared region. A small

range of absorption can be defined for each type of bond, but, outside this range, absorptions are

normally due to some other type of bond. By establishing what kinds of bonds are present in a

sample, one can conclude on its chemical structure (Bevin, Fergusson, Perry, Janik, & Cozzolino,

2006; Pavia et al., 2001). More specifically, Fourier-transform infrared (FT-IR) spectroscopy in the

mid-infrared region is widely used in determinations of the proteins‘ secondary structure. The

characteristic amide I band (stretching vibrations of C=O in the peptide bond) between 1700 and

1600 cm-1

(in the mid- infrared range) provides information on protein secondary structure due to a

sensitivity of the amide I frequency to the hydrogen bonding pattern and dipolar couplings in the

protein backbone. This sensitivity makes it possible to study not only protein folding and unfolding,

31

but also aggregation processes. Furthermore, proteins have complementary but much weaker

fingerprints in the NIR region (Bruun, Holm, Hansen, & Jacobsen, 2006; Carbonaro, Maselli, &

Nucara, 2012)

The main advantage of using spectroscopic techniques is the exploratory character of the

measurements that facilitates concurrent detection of several different and even non-anticipated

constituents (Holse, Larsen, Hansen, & Engelsen, 2011). Other reasons that render spectroscopic

techniques as the preferred analytical method in many laboratories include: minimal sample

preparation/ pretreatment, short analysis time, cost-effective to analyze a single sample or large

batches of samples, non-destructive methods for the samples, no laboratory or skilled operator

needed for routine analyses, no use of hazardous chemical reagents, and, depending on the method,

the results are usually more precise and can be more accurate than, as accurate as, or of acceptable

accuracy, when compared with the method usually employed (Batten, 1998; Blanco & Villarroya,

2002).

32

AIM OF THE STUDY

Legumes are a good and inexpensive source of protein. Therefore, they could be a good alternative to

meat protein in developing countries, where protein deficiency is high.

The aim of the project is to examine the protein content of legumes from Ghana, and evaluate how

some traditional processing methods (germination, fermentation) can alter that protein content, with

the perspective of including them in high-protein snacks.

33

MATERIALS AND METHODS

Screening of samples

The following samples were used in the screening process with FT-IR.

Cowpea: asomdwee, asetenapa and soronko, Soybean: anidaso, nangbaare, jenguma and quarshie,

Lima: koloenu, lima 104 and 204, Bambara groundnut: Nar-4, Mucuna bean and Jack bean.

One replicate of each sample was milled in a coffee mill, frozen at -20 oC and freeze-dried for at

least 24h. FT-IR spectroscopy method (see method below) was performed. A triple determination

was carried out for each sample. The data obtained where used in a Principal Component Analysis

(PCA) model with a scope to identify the most differentiated samples.

Six samples were selected for further analysis. Cowpea: asetenapa and soronko, Soybean: anidaso,

Bambara groundnut, Mucuna bean and Jack bean.

Preparation of samples for analyses

Germination of samples

20g of each sample were weighed in a beaker. Three replicates of each sample were weighed (4

replicates for Bambara groundnut and Jack bean due to mould infection). The samples were soaked

in 100 mL of 1% w/v citric acid solution for 18h at room temperature. The solution was drained off.

The samples were washed with distilled water to neutral pH, and soaked in 100 mL distilled water

for 2 hours at room temperature. The distilled water was drained off and the samples were reweighed

to determine the amount of water absorbed.

The soaked seeds were, then, placed in petri dishes containing two filter papers (Rundfilter MN 615,

9 cm ø, MACHEREY-NAGEL GmbH & Co. KG, Dűren, Germany), and 5 mL distilled water were

sprinkled on top of them. The petri dishes were then put into plastic bags, in order to keep humidity,

and kept in darkness at 30oC for either 48h or 72h. The samples were sprinkled with distilled water

daily.

34

The sprouted samples were ground coarsely (using a kitchen mini-chopper), frozen at -20oC and

freeze-dried for at least 24h. Next, they were milled in a coffee mill and stored in plastic containers

at room temperature.

Fermentation of samples

20g of each sample were weighed in a beaker. Three replicates were weighed for each sample. The

samples were soaked in 100 mL of 1% w/v citric acid solution for 18h at room temperature. The

solution was drained off. The samples were washed with distilled water to neutral pH, and soaked in

100 mL distilled water for 2 hours at room temperature. The distilled water was drained off and the

samples were reweighed to determine the amount of water absorbed. The legumes were placed in 50

mL Eppendorf tubes with excess distilled water and put in a waterbath a 90oC for 30 min (for

cowpea and soybean samples) or 60 min (for bambara groundnuts, mucuna beans and jack beans)

(boiling step). After boiling the distilled water was drained off. The boiled samples were ground

coarsely (using a kitchen mini-chopper) and stored in plastic bags at 5oC overnight.

The next day the samples were left on the lab bench until they acquired room temperature and were

then inoculated with 1,2 mL Bacillus subtilis var. natto solution (7*106 CFU/ mL) and 2 mL distilled

water. The samples were massaged in order to ensure that the bacteria were spread throughout the

sample. The inoculated samples were kept in darkness at either 30oC or 37

oC for 48h. They were

massaged twice a day to maximize the legume surface that the bacteria ferment.

The fermented samples were frozen at -20oC and freeze-dried for at least 24h. They were, then,

milled in a coffee mill and stored in plastic containers at room temperature.

Control samples

20g of each sample were weighed in a beaker. Three replicates were weighed for each sample. The

samples were soaked in 100 mL of 1% w/v citric acid solution for 18h at room temperature. The

solution was drained off. The samples were washed with distilled water to neutral pH, and soaked in

100 mL distilled water for 2 hours at room temperature. The distilled water was drained off and the

samples were reweighed to determine the amount of water absorbed. Next, the control samples were

35

ground coarsely (using a kitchen mini-chopper), frozen at -20oC and freeze-dried for at least 24h.

They were, then, milled in a coffee mill and stored in plastic containers at room temperature.

Defatting of soybean samples for protein determination

Prior to protein determination of the soybean samples, a defatting step was necessary in order to

reduce the fat content below 10%. The method used was modified from L‘hocine, Boye, & Arcand

(2006). 1 g of each soy sample was weighed and put in a 15 mL Eppendorf tube. 5 mL of hexane

were added in the tube and the content of the tube was mixed in a vortex mixer for at least 30 sec.

The samples were then centrifuged for 10 min at 2000 rpm and the supernatant was discarded. The

procedure was repeated two more times. The samples were air-dried in room temperature under a

fume hood for approximately 24 h.

Samples‘ assessment

FT-IR (Fourier transform infrared) spectroscopy

The absorbance measurements were performed on an Arid-Zone MB100 FT-IR instrument (ABB

Bomen, Quebec, Canada) using an Attenuated Total Reflectance (ATR) device with a triple-bounce

diamond crystal. IR spectra were recorded in the range of 4000– 530 cm−1

using a spectral resolution

of 4 cm−1

. The ground legumes were positioned on the crystal surface and squeezed towards the

diamond crystal by use of a concave needle compressor. Each spectrum represents the average of 64

scans ratioed against the background (128 scans) collected with the empty crystal and stored as

absorbance spectra. Each sample was measured in duplicate.

NIR (Near infrared) spectroscopy

The QFA flex near-infrared spectrometer (Q- Interline A/S, Tølløse, Denmark) was used to collect

the spectra. The samples were placed in a 50mm diameter sample bottle. The instrument parameters

were set as following; resolution: 4 cm-1

; Gain: C and Gain: High. Each spectrum represents the

average of 16 scans ratioed against a background (32 scans) measured on an internal white 50mm

36

diameter bottle. The spectrum measured was 4000-14000 cm-1

. Duplicate measurements were

collected from each sample.

Determination of moisture content

Moisture content was estimated by a method modified from ICC-Standard No. 110/1. Double

determination was performed in milled raw legume samples. Clean vessels were dried for 2h at

130°C and cooled down to room temperature in a desiccator. The empty closed vessels were

weighed (W1) and the weight was noted. 1 g of each sample was weighed (W2). The vessels were

placed in the drying cabinet to dry at 130°C for 2 h (180 min set – 1 hour for reaching required

temperature). After drying the vessels were placed in the desiccators (the first 5-10 min with the lid

half-open) to cool down to room temperature. After cooling down, the vessels were weighed again

(W3).

Percent moisture content was calculated as follows;

Moisture % =𝑊2 − 𝑊3 − 𝑊1 ∗ 100

𝑊2

Where,

W1 = tare weight of vessels (with cover) in grams

W2 = initial weight of sample in grams

W3 = dry weight of sample and vessel (with cover) in grams

Determination of fat content

Crude fat was determined using a modified method of AACC Method 30-25 Crude Fat in Wheat,

Corn, and Soy Flour, Feeds, and Cooked Feeds. Beakers were dried at 103°C for 30 min and cooled

down to room temperature in a desiccator. Three glass beads were added in each beaker before

weighing (W4). 3 g of milled freeze-dried sample for samples with <10% fat (cowpeas, jack bean,

bambara bean, mucuna bean) and 2g for samples with >10% fat (soybean) were weighed (W5) in the

extraction holsters. A fat-free cotton cork was added and the holsters were put in the Soxtec

apparatus (Soxtec System HT 1043 Extraction Unit, FOSS Tecator, DK) in the assigned position. 40-

37

50 mL petroleum ether HPLC grade were added in each beaker, before the beakers were also placed

in the Soxtec apparatus. The holsters with the samples were held for 15 min in boiling position,

followed by 30 min in rinsing position. The solvent was collected in the condensers; the beakers

were removed from the apparatus and left under a fume hood for 30 min for any residual solvent to

evaporate. They were then weighed again (W6).

Cotton gloves and magnet forceps were used throughout the procedure, when handling the beakers

and extraction holsters.

Percent crude fat was calculated as follows:

Crude Fat % = 𝑊6 – 𝑊4 ∗ 100

𝑊5

Where,

W4 = tare weight of beaker (with glass beads) in grams

W5 = initial weight of sample in grams

W6 = gross weight of sample fat and beaker (with glass beads) in grams

Determination of protein content

Protein content was determined by a method modified from AOAC Official Method 2001.11 Protein

(Crude) in Animal Feed, Forage (Plant Tissue), Grain, and Oilseeds. 0,5 g milled freeze-dried sample

was weighed for samples with 25-50% protein (soybean, cowpeas, mucuna bean, jack bean) and 1g

for samples with 3-25% protein (bambara groundnut), folded into N-free paper and dropped into a

Kjeldahl tube. Single determinations were carried out. Two catalyst tabs, each containing 3,5 g

K2SO4 with 0,4 g Cu catalyst (CuSO4), and 12 mL concentrated H2SO4 (98%, reagent grade) were

added into each tube. Samples were digested in 420 °C for 1 h in Kjeltec digestion block (Kjeltc

System 2020 Digestor, FOSS Tecator, DK). After digestion samples were cooled for 15-20 min. 50

mL of NaOH (40 % w/w) and 25 mL of receiver solution (H3BO3, 4 % w/v) were used for distillation

(Kjeltc System 1026 Distilling unit, FOSS Tecator, DK). Distillate was titrated with standard 0.1000

N HCl to grey endpoint. Preparing blanks, 2 catalyst tabs were mixed with 12 mL concentrated

H2SO4 and then treated identically to the samples. Blanks evaluate nitrogen from chemicals and

other extraneous sources.

38

Percent nitrogen and percent crude protein can be calculated as shown below.

% 𝑁 = 𝑇 − 𝐵 ∗ 𝑁 ∗ 14,0067 ∗ 100

𝑊

% Protein = % N * F

T – titration volume for sample, mL;

B – titration volume for blank, mL;

N – normality of HCl acid (0.1000 N);

W – sample weight, mg;

F – Conversion factor for Nitrogen to protein – 6.25

(Note: For soybean samples the sample weight was reduced to the original weight before defatting.)

Data analysis

Scatter effects in the IR and NIR raw spectra were removed by application of MSC (Multiplicative

Scatter Correction) in MatLab. The transformed spectra were then imported into LatentiX 2.12

(LatentiX Aps, Frederiksberg, Denmark). Principal Compoonent Analysis (PCA) was performed on

the mean centered spectra, with random cross validation.

Furthermore, the data on the crude protein content of the germinated, fermented, and control samples

were imported in IBM SPSS Statistics 22 (IBM Software). One-way ANOVA was performed with

protein content as the dependent variable and treatment as the independent one. The samples were

checked for their homogeneity using Levene‘s test for equality of variances. In case the assumption

for homogeneity was violated (Sig. ≤0,05) a Welch ANOVA was also performed. Post-hoc analysis

of the samples was carried out using Scheffe test. For jack bean samples Independent Samples T-test

was also performed.

39

RESULTS AND DISCUSSION

Screening Test

Figure 3: FT-IR PCA scores plot of raw beans

Figure 3 shows the scores plot of the data collected in FT-IR for various raw beans, using the first

two principal components. The explained variance for the two principal components accounts for

98,4% of the total variance. In the plot two distinct clusters can be seen; one comprising of all the

soybean samples, on the right of the X-axis, and one consisting of the rest of the bean samples, close

to (0,0). Cowpea ‗Asetenapa‘ seems to be an outlier.

Selection of the sample was made, with the intention of choosing the most diverse samples, both

according to the scores plot and according to species. One sample from the soybean cluster was

selected (soybean ‗Anidaso‘). The outlier cowpea ‗Asetenapa‘ was also included as well as another

cowpea sample (‗Soronko‘) with brown seed coat. Since the rest of the samples were not sufficiently

differentiated, the rest of the samples chosen for further analysis were some underutilized legumes of

Africa (Jack bean, Velvet bean, Bambara groundnut).

The scope of the screening test was to get a vague idea of how similar or different the bean samples

are with one another; therefore, no further analysis, regarding the absorbance bands of the spectra

was performed.

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

SB-ANI2 SB-ANI SB-2ANI SB-QUA2

SB-ANI3 SB-QUA

SB-NAN3 SB-2ANI2 SB-NAN

SB-JEN3

SB-QUA3

SB-JEN2

SB-2ANI3

SB-JEN SB-NAN2

BAM3 BAM2

Scores PC#1 (95.067%)

PCA Scores [Model 1]

BAM

CP-SOR2 CP-SOR

MUC3

MUC4

CP-SOR3

JAC

JAC2

104-4

MUC5

JAC3

MUC6

104

MUC2

LIM3

CP-ASO6

104-3

KOL

CP-ASO4 CP-ASO5

104-2 KOL3 LIM LIM2

KOL2 MUC LIM4

CP-ASE2 CP-ASE CP-ASE3

Score

s P

C#2 (

3.3

39%

) 1 0 4

ΒΒΒ

C P - A S E

C P - A S O

C P - S O R

K O L

L I M

M U C

S B - 2 A N I

S B - A N I

S B - J E N

S B - N A N

S B - Q U A

J A C

40

Proximate Composition

Table 5 summarizes the proximate composition of the raw beans used in the germination and

fermentation processes. Moisture measurement was a double determination of a single raw bean

sample, whereas fat and protein measurements were based on a single determination in the triplicate

control (raw, soaked) samples.

Table 5: Proximate composition of the raw bean samples (Moisture, Fat and Protein)

Legume Moisture% Fat% Pro %

Soybean Anidaso 10,02 19,68 42,87

Cowpea Soronko 13,13 1,06 25,90

Cowpea Asetenapa 12,74 1,49 23,97

Jack bean 13,59 1,21 29,05

Bambara groundnut 10,46 6,71 18,15

Velvet bean 10,54 2,62 29,99

The moisture content falls in the range, and in some cases slightly exceeds, the standard range of 0-

13%, as reported by James (1995). Moisture content in this range is suitable for storage and

processing of legume flours without triglyceride degradation by microorganisms (James, 1995). Jack

bean is found to have the highest moisture content (13,59%), with cowpeas following, whereas the

lowest moisture content is seen in soybeans.

Regarding the fat content of the beans, soybean is, as expected, the one containing the highest

amount of lipids (19,68%). Soybean is the only legume, among the ones studied, that is classified as

an oilseed (Kayembe & Van Rensburg, 2013). The lipid content for the rest legumes examined is in

the lower range levels, or even below them, according to the literature, with cowpea soronko

containing the least fat (1,06%).

As far as protein content is concerned, soybean has, once again, the highest content (42,87%) and

bambara groundnut the lowest (18,15%). These results are in agreement with the results of Fasoyiro

et al., (2006) that found soybeans containing significantly higher protein content (p, 0,05) than other

41

minor grain legumes. They also found bambara groundnut to have the least protein, although

according to them bambara contained 22,1% protein (Fasoyiro et al., 2006).

Fourier-Transform Infrared (FT-IR) Spectroscopy

In the raw (MSC) spectra (Figure 4) the main absorbances are seen. However, it is not possible to

distinguish between the samples, due to the high number of samples and replicates. For this reason,

the mean absorbance spectrum for each sample was calculated. The mean spectra for the control

samples of the six legumes investigated are depicted in Figure 5.

Figure 4: FT-IR spectra (MSC) of the germinated, fermented, and control samples.

1000 1500 2000 2500 3000 3500 4000

-0.01

0

0.01

0.02

0.03

0.04

0.05

cm-1

42

Figure 5: Mean FT-IR spectra (MSC) of the control legume samples. Soybean is shown in blue, Cowpea Asetenapa in green, Bambara groundnut in red, Velvet bean in light blue, Cowpea Soronko in purple, and Jack bean in yellow.

The highest peak for also legumes measured appears at approximately 1080 cm-1

. Peaks at this area

of the spectrum arise from C-N and C-O bonds. Multiple peaks are also seen in the range of 1250 –

1750 cm-1

. The peak at 1550 cm-1

is related to N=O bonds. The one at 1630 cm-1

is due to the

presence of carbonyl group (C=O) and combined with the absorbance near 3300 - 3400 cm-1

(N-H

stretches) indicate the presence of amides. In this sense, it is logical that bambara groundnut, which

has the lowest protein content, exhibits lower absorption than the other samples at those

wavenumbers.

Furthermore, bambara groundnut, together with soybean, exhibit higher peaks at 1750 cm-1

, 2850

cm-1

, and 2915 cm-1

, compared to the other samples. Peaks at 1750 cm-1

arise, once again from C=O

bonds, only this time related to the presence of esters. Absorbances at 2850 – 3000 cm-1

result from

C-H stretches. Peaks arising from C-H stretches result primarily from the CH2 groups in fats,

although C-H bonds from carbohydrates and proteins also contribute (Holse et al., 2011). Since

soybean and bambara groundnut have the highest lipid content, the highest absorbances at these

wavenumbers were not a surprise.

Mean spectra of the germinated and fermented samples for each legume were also created, in order

to examine how the change in the legumes composition affects their spectra (Data shown in

Appendix 1). For all the different legumes, the differences in the composition are mainly translated

1000 1500 2000 2500 3000 3500 4000

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

cm-1

43

as a change in the peak at 3300 – 3400 cm-1

, arising from N-H stretches and related to the primary

and secondary amines and amides. However, the trends for the protein content according to the FT-

IR spectra do not correspond to the trends according to the protein content measured with Kjeldahl.

A PCA model was calculated, using the raw (MSC) spectra. Table 6a shows the scores plot of data

using the first two principal components (PCs), for which the accumulated variance contribution rate

was up to 78, 2%. In the plot the data set was split in three groups; one containing the soybean

samples (colored in the plot), one the bambara groundnut ones (green), and one comprising of the

rest of the samples.

Figure 6: PCA scores plot of the FT-IR raw (MSC) spectra (PC-1/PC-2) (a), and PCA loading plots for PC-1 (b) and PC-2 (c). In the scores plot Soybean samples are colored red, Bambara groundnut green, Velvet bean pink, Cowpea Asetenapa blue, Cowpea Soronko light blue and Jack bean black.

The first PC (PC-1) is thought to be related to the fat content, since the samples with high fat content

(soybean, bambara groundnut) are placed on the left side of the vertical axis, taking negative score

values for PC-1, whereas the ones with lower lipid content have positive score values and are

positioned on the right side of the vertical axis. Furthermore, in the second PC (PC-2) there is a

44

tendency that the samples with the highest protein content (soybean, velvet bean) are placed at the

bottom of the plot, while the ones containing the least protein (bambara groundnut, cowpea

asetenapa) are on the top. The loading plots for PC-1 and PC-2 are depicted in Figure 6b and Figure

6c respectively.

Near infrared (NIR) spectroscopy

NIR spectroscopy measures overtones and combinations of the fundamental molecular vibrations.

The signals arise from anharmonic molecular bonds, namely bonds containing at least one hydrogen

atom. Thus, NIR is excellent at detecting the four bulk components in foods: water (O-H), fat (C-H),

protein (N-H) and carbohydrate (C-H and O-H) (Holse et al., 2011).

From the raw NIR spectra (Figure 7) a difference in the peaks of some samples can be observed.

However, it is not possible to tell which the deviating samples are. Therefore, the mean spectrum for

each sample was calculated, and the mean spectra (MSC) of the control samples are presented in

Figure 8.

Figure 7: NIR raw spectra (MSC) of the germinated, fermented, and control samples

4500 5000 5500 6000 6500 7000 7500 8000 8500 9000 9500

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

cm-1

45

Figure 8: Mean FT-IR spectra (MSC) of the control legume samples. Soybean is shown in blue, Cowpea Asetenapa in green, Bambara groundnut in red, Velvet bean in light blue, Cowpea Soronko in purple, and Jack bean in yellow.

From the mean spectra of the control samples in Figure 8 it seems that the deviating samples in Figure

7 are the soybean samples.

Peaks arising from C-H stretches are visible as combination bands at around 4300 – 4350 cm-1

and as

1st and 2nd overtones at 5650 – 5800 cm-1

and 8200-8400 cm-1

, respectively. As stated earlier the C-

H bonds are primarily related to the CH2 groups in fat, so it is only relevant that soybean exhibits the

highest peaks among the samples at these wavenumbers.

The broad peak at approx. 6300 – 7000 cm-1

is related to the 1st overtones of O-H and N-H stretches,

related to carbohydrates and proteins, respectively. Soybean and velvet bean, the samples with the

highest protein content, have the lowest absorptions in this area of the spectra. So, it could be

assumed that the peaks arise primarily from the O-H stretches, rather than the N-H ones.

Another interesting peak can be seen at 4750 cm-1

, for all the samples but soybean. The peak arises

from a combination band (O-H deformation/ C-O stretch) that is related to starch. Instead, soybean,

together with velvet bean, have a peak at 4600 cm-1

that arises from a combination band (2 * amide I

+ amide III) relevant to protein content.

The peak at 5170 cm-1

is an O-H stretch/ O-H deformation combination band primarily from the

carbohydrates (Holse et al., 2011).

Additional plots were made comparing the mean spectra of all treatments for each legume

individually (plots in Appendix 2). Little variations were observed between different treatments. The

main deviation is seen at 5170 cm-1

related to carbohydrates. It is well established that during

4500 5000 5500 6000 6500 7000 7500 8000 8500 9000 9500

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

cm-1

46

germination carbohydrates are broken down to provide energy for the development of sprouts

(Donangelo et al., 1995; Mugendi & Njagi, 2010). Furthermore, during fermentation microorganisms

hydrolyze non-digestible carbohydrates (poly- and oligo-saccharides) into sugars (Parkouda et al.,

2009).

A PCA model was calculated using the raw (MSC) spectra of all the samples. Figure 9 shows the

scores plot for the first two PCs, accounting for 58,3% and 33,2% of the explained variance,

respectively. The samples are separated in three distinct clusters in the scores plot; soybeans (pink)

are the first cluster, velvet beans (blue) the second and the rest of the samples comprise the third

cluster. It seems as PC-1 (PC-1 loadings plot shown in Figure 10a) is highly correlated to the protein

content, since the beans with the highest protein content are placed on the left of the X- axis, whereas

the rest on the right.

Figure 9: PCA scores plot of the NIR raw (MSC) spectra (PC-1/ PC-2). Soybean samples are colored pink, Bambara groundnut red, Velvet bean blue, Cowpea Asetenapa light blue, Cowpea Soronko green and Jack bean black.

It is not clear how the samples are plotted according to PC-2, but a possible explanation could be that

the samples with the lowest carbohydrate content are placed in the bottom of the plot; especially

since the PC-2 loadings plot (Figure 10b) has a distinct peak at around 4750 cm-1

, correlated to

starch.

-1 -0.5 0 0.5

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

BAMC-1.1 BAMC-1.2 ASEF37-1.2 BAMC-3.1 BAMC-3.2 BAMC-2.1 BAMC-2.2

ASEC-3.2 ASEF37-1.1

BAMG48-4.2 BAMG48-4.1 JACF37-1.2

ASEC-3.1 ASEF37-2.2 ASEC-2.1 ASEC-1.1 ASEC-2.4 ASEC-2.2 SORC-3.2 ASEC-2.3

JACF37-3.2

ASEC-1.2 ASEG48-1.2

JACF37-1.1

BAMG48-3.2 JACF37-3.1 SORC-3.1 BAMG72-3.1 BAMG72-3.2 BAMG48-3.3

JACF37-2.2

ASEG72-2.3 BAMG48-3.1 ASEF37-2.1 ASEF30-1.2

BAMG48-2.2

ASEG72-2.2 SORF37-2.2 JACF37-2.1

ASEF30-1.1

BAMG72-4.1 ASEG72-2.1

BAMC-1.3.

ASEG48-1.1

BAMG48-2.3

ASEG72-3.2

BAMC-1.4 BAMG72-4.2

ASEG48-3.2

BAMG48-2.1 SORF37-2.1 ASEF37-3.2

BAMG72-2.1 SORC-2.1 SORC-2.2 ASEG72-3.1 ASEF37-3.1

BAMG72-2.2

ASEF30-2.2

BAMG72-1.2

SORC-1.2

BAMG72-1.1 SORG48-3.2 BAMG48-1.1

SORC-1.1

BAMG48-1.2 BAMF37-1.2

ASEG48-3.1 ASEF30-2.1

BAMF37-1.1

JACG72-3.2

ASEG72-1.2 SORG48-2.2 ASEG72-1.1

BAMF37-3.2 BAMF37-3.1 JACC-1.1

ASEF30-3.1

JACG48-3.2 JACC-1.2

SORG48-3.1 BAMF30-2.2

ASEG48-2.2

SORF37-3.2

JACC-3.2 JACC-2.2 BAMF30-2.1 SORF37-1.2

ASEF30-3.2

JACG48-3.1 JACF30-1.2

SORG48-2.1 ASEG48-2.1

JACC-3.1 JACF30-3.2 BAMF30-1.2 SORF30-1.2 SORF30-3.2 JACC-2.1 BAMF30-1.1 SORF37-3.1 BAMF30-3.1 BAMF30-3.2 SORF37-1.1

BAMF37-2.1 JACG48-4.2

SORG48-1.2

JACF30-3.1 BAMF37-2.2 JACF30-1.1

SORG48-1.1 SORG72-3.2

JACG72-2.2 JACG48-4.1 JACG72-2.1

SORG72-3.1 SORF30-1.1 JACG48-2.2 SORF30-3.1 SORG72-2.2 SORG72-2.1 JACG48-2.1 SORG72-1.2 SORG72-1.1

JACG72-1.1 JACG72-1.2

SORF30-2.2

JACG72-4.2 JACG72-4.1 JACF30-2.1

SORF30-2.1

JACF30-2.2 JACG72-3.1 JACG48-1.1 JACG48-1.2

Scores PC#1 (58.345%)

PCA Scores [Model 1]

MUCC-1.1 MUCC-1.2 MUCC-3.2 MUCC-2.1 MUCC-2.2 MUCC-3.1

ANIC-2.1 ANIC-2.2 ANIG48-1.1 ANIG48-1.3 ANIG48-1.2 ANIC-1.2 ANIC-1.1 ANIC-3.2

MUCG72-1.2

ANIC-3.1 ANIG48-2.1 ANIG48-2.2 ANIG72-3.1

MUCG72-1.1

ANIG48-3.1 ANIG72-3.2

ANIF37-3.1

ANIG48-3.2

ANIF37-3.2

MUCG48-3.1 MUCG48-3.2

ANIG72-2.2 ANIF37-1.2 ANIF37-1.1

ANIG72-2.1

MUCG48-1.1 MUCG48-1.2 MUCF37-3.1

ANIF37-2.2

MUCF30-1.2 MUCF37-1.2 MUCF37-2.2

ANIG72-1.2 ANIF37-2.1

ANIG72-1.1

MUCF30-2.2 MUCF37-3.2 MUCF30-3.2 MUCF37-2.1 MUCF30-2.1 MUCF30-1.1

ANIF30-1.2 ANIF30-1.1

MUCF37-1.1 MUCF30-3.1

ANIF30-2.2 ANIF30-2.1 ANIF30-3.2 ANIF30-3.1

MUCG48-2.3 MUCG72-2.2 MUCG72-2.1 MUCG72-3.2 MUCG48-2.1 MUCG48-2.2

MUCG72-3.1

Score

s P

C#2 (

33.1

63%

)

S o y b e a n - A n i d a s o

C o w p e a - A s t e n a p a

B a m b a r a g r o u n d n u t

V e l v e t b e a n - M u c u n a

C o w p e a - S o r o n k o

J a c k b e a n

47

Figure 10: NIR PCA loadings plots for PC-1 (a), PC-2 (b) and PC-3 (c).

The explained variance for PC-3 (Figure 10c) seems to be almost exclusively due to the peak at 5200

cm-1

, arising from the C=O stretch second overtone that is related to peptides. So, it was deemed

appropriate to design the PC-1/PC-3 scores plot for all the samples. The plot can be seen in Figure

11.

-1 -0.5 0 0.5

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

BAMC-1.1 BAMC-1.2 ASEF37-1.2 BAMC-3.1 BAMC-3.2 BAMC-2.1 BAMC-2.2

ASEC-3.2

ASEF37-1.1 BAMG48-4.2 BAMG48-4.1

JACF37-1.2

ASEC-3.1

ASEF37-2.2

ASEC-2.1 ASEC-1.1 ASEC-2.4 ASEC-2.2

SORC-3.2

ASEC-2.3

JACF37-3.2

ASEC-1.2

ASEG48-1.2

JACF37-1.1

BAMG48-3.2

JACF37-3.1

SORC-3.1 BAMG72-3.1 BAMG72-3.2

BAMG48-3.3

JACF37-2.2

ASEG72-2.3 BAMG48-3.1

ASEF37-2.1

ASEF30-1.2

BAMG48-2.2

ASEG72-2.2

SORF37-2.2 JACF37-2.1

ASEF30-1.1 BAMG72-4.1

ASEG72-2.1 BAMC-1.3.

ASEG48-1.1

BAMG48-2.3

ASEG72-3.2

BAMC-1.4

BAMG72-4.2

ASEG48-3.2

BAMG48-2.1

SORF37-2.1

ASEF37-3.2

BAMG72-2.1

SORC-2.1 SORC-2.2 ASEG72-3.1

ASEF37-3.1 BAMG72-2.2 ASEF30-2.2

BAMG72-1.2

SORC-1.2

BAMG72-1.1 SORG48-3.2

BAMG48-1.1

SORC-1.1

BAMG48-1.2

BAMF37-1.2

ASEG48-3.1 ASEF30-2.1

BAMF37-1.1

JACG72-3.2

ASEG72-1.2

SORG48-2.2

ASEG72-1.1

BAMF37-3.2 BAMF37-3.1

JACC-1.1

ASEF30-3.1

JACG48-3.2 JACC-1.2

SORG48-3.1

BAMF30-2.2

ASEG48-2.2

SORF37-3.2

JACC-3.2 JACC-2.2

BAMF30-2.1

SORF37-1.2

ASEF30-3.2

JACG48-3.1

JACF30-1.2

SORG48-2.1

ASEG48-2.1

JACC-3.1

JACF30-3.2

BAMF30-1.2

SORF30-1.2 SORF30-3.2 JACC-2.1

BAMF30-1.1

SORF37-3.1

BAMF30-3.1 BAMF30-3.2

SORF37-1.1

BAMF37-2.1

JACG48-4.2 SORG48-1.2

JACF30-3.1

BAMF37-2.2

JACF30-1.1

SORG48-1.1

SORG72-3.2 JACG72-2.2

JACG48-4.1

JACG72-2.1 SORG72-3.1 SORF30-1.1

JACG48-2.2

SORF30-3.1

SORG72-2.2 SORG72-2.1

JACG48-2.1

SORG72-1.2 SORG72-1.1

JACG72-1.1 JACG72-1.2 SORF30-2.2

JACG72-4.2 JACG72-4.1 JACF30-2.1

SORF30-2.1

JACF30-2.2 JACG72-3.1

JACG48-1.1 JACG48-1.2

Scores PC#1 (58.345%)

PCA Scores [Model 1]

MUCC-1.1 MUCC-1.2

MUCC-3.2

MUCC-2.1 MUCC-2.2

MUCC-3.1

ANIC-2.1 ANIC-2.2

ANIG48-1.1 ANIG48-1.3 ANIG48-1.2

ANIC-1.2 ANIC-1.1

ANIC-3.2

MUCG72-1.2

ANIC-3.1

ANIG48-2.1 ANIG48-2.2 ANIG72-3.1

MUCG72-1.1

ANIG48-3.1 ANIG72-3.2

ANIF37-3.1

ANIG48-3.2

ANIF37-3.2

MUCG48-3.1 MUCG48-3.2

ANIG72-2.2

ANIF37-1.2 ANIF37-1.1

ANIG72-2.1

MUCG48-1.1 MUCG48-1.2

MUCF37-3.1 ANIF37-2.2

MUCF30-1.2

MUCF37-1.2

MUCF37-2.2

ANIG72-1.2

ANIF37-2.1

ANIG72-1.1

MUCF30-2.2

MUCF37-3.2

MUCF30-3.2

MUCF37-2.1

MUCF30-2.1 MUCF30-1.1 ANIF30-1.2 ANIF30-1.1

MUCF37-1.1

MUCF30-3.1 ANIF30-2.2 ANIF30-2.1 ANIF30-3.2 ANIF30-3.1

MUCG48-2.3

MUCG72-2.2 MUCG72-2.1

MUCG72-3.2

MUCG48-2.1 MUCG48-2.2

MUCG72-3.1

Score

s P

C#3 (

4.4

52%

)

S o y b e a n - A n i d a s o

C o w p e a - A s t e n a p a

B a m b a r a g r o u n d n u t

V e l v e t b e a n - M u c u n a

C o w p e a - S o r o n k o

J a c k b e a n

48

Figure 11: PCA scores plot of the NIR raw (MSC) spectra (PC-1/ PC-3). Soybean samples are colored pink, Bambara groundnut red, Velvet bean blue, Cowpea Asetenapa light blue, Cowpea Soronko green and Jack bean black.

In the scores plot two well defined groups can be distinguished. One on the left side of the X-axis,

consisting of the soybean and velvet bean samples, and the other on the right side of the X-axis

comprising of the rest of the samples. The grouping of the samples is related to their protein content,

since in the former group there are the legumes with the highest protein content, while in the latter

the ones containing lower amounts of protein.

In general, from both the FT-IR and NIR plots it can be concluded that soybean is the most

differentiated legume. This is logical, since, according to the literature, soybeans contain higher

amounts of protein and lipids and lower amounts of carbohydrates compared to the rest of the

samples (See Table 2).

Effect of fermentation and germination on protein content

The protein content for each sample was determined using the Kjeldahl method. The results are

presented in Table 6.

Table 6: % Protein content (DM) of the germinated, fermented and control legume samples (dry weight basis)

% Protein (DM)

Control Germination

48h

Germination

72h

Fermentation

30°C

Fermentation

37°C

Soybean

Anidaso 1 42,87 ± 1,05

a 47,79 ± 2,17 b

(11,5)

46,95 ± 0,37 ab

(9,5)

50,29 ± 1,78 b

(17,3)

49,99 ± 1,68 b

(16,6)

Cowpea

Soronko 1

25,90 ± 0,00 a

26,49 ± 0,44 ab

(2,3)

28,12 ± 0,20 b

(8,6)

27,95 ± 0,41 ab

(7,9)

27,77 ± 1,48 ab

(7,2)

Cowpea

Asetenapa 1

23,97 ± 0,18 a

24,45 ± 0,36 a

(2,0)

25,79 ± 0,10 b

(7,6)

25,85 ± 0,10 b

(7,8)

26,72 ± 1,20 c

(11,5)

Jack bean 2 29,05 ± 0,17

a

29,14 ± 1,57 ab

(0,3)

31,20 ± 1,13 b

(7,4)

31,07 ± 0,57 b

(7,0)

29,12 ± 1,17 b

(0,2)

Bambara

groundnut 1

18,15 ± 0,31 a

19,76 ± 0,11 b

(8,9)

19,65 ± 0,37 b

(8,3)

20,28 ± 0,41 b

(11,7)

20,86 ± 1,10 b

(14,9)

Velvet bean 1 29,99 ± 0,73

a

31,74 ± 0,37 b

(5,8)

31,86 ± 0,63 b

(6,2)

33,14 ± 0,39 b

(10,5)

33,03 ± 0,53 b

(10,1)

Mean values ± St. Deviation

The numbers in the parentheses refer to the %increase of the protein content compared to the protein content of the control group.

The same superscript in the same row means no significant difference (p≤0,05)

1. The statistical significance was calculated with One-way ANOVA and Scheffe post-hoc test for multiple comparisons.

2. The statistical significance was calculated with independent-samples T-test for each pair of samples.

49

For each legume, an increase in the protein content is seen in the germinated and fermented samples

compared to the control ones. In many cases the increase in the protein content was found to be

statistically significant, according to the analysis of variance (ANOVA). However, the small amount

of samples (3-4) for each group deteriorates the importance of the results. For example, although

Jack bean samples varied significantly according to ANOVA, the post-hoc test failed to reveal where

the significant difference lies. For this reason, maybe a look at the tendencies, by visualization of the

results, could be more appropriate (Figure 12).

Figure 12: % Protein content (DM) of the germinated, fermented and control samples of (a) Soybean Anidaso, (b) Cowpea Soronko, (c) Cowpea Asetenapa, (d) Jack bean, (e) Bambara groundnut and (f) Velvet bean. Coloumn order from left to right: Raw, Germinated 48 hours, Germinated 72 hours, Fermented at 30°C and Fermented at 37°C.

50

The protein content in the germinated samples was found to be higher than the control ones, for all

legumes and this can -in most cases- already be seen from the column charts (Figure 12). This came

to no surprise; most researchers have observed an increase in the protein content of legumes, and

most of the times this increase is statistically significant (El-adawy, 2002; Ghavidel & Prakash,

2007; V. a Obatolu, 2002). Only a few found no changes (Trugo et al., 1999), or even slight decrease

(not significant) (Martínez-Villaluenga et al., 2007; Torres et al., 2007). In the present study the

highest increase in germinated samples was that of soybeans germinated for 48h (11,5%) and the

lowest at jack beans (0,3%), also at 48h. The %increase in protein content for the 48h was highly

deviating, but for 72h it was in the range of 6,2% (velvet bean) to 9,5% (soybean). The big difference

in %increase (6,3 – 7,1%) in the protein content between 48h and 72h, for jack beans and both

varieties of cowpeas, might mean that 48h are not enough for the germination of these legumes. In

general, most of the legumes exhibited higher protein contents after 72h of fermentation, rather than

48h. However, soybean and bambara groundnut had a highest protein content at 48h of germination,

compared to 72h, although the difference was not statistically significant. This is in accordance with

the results of Akpapunam et al. (1996); in their study they germinated soybeans and bambara

groundnuts for 1 – 5 days and they found an increase in the protein content up to 48h and a decrease

thereafter. Nevertheless, they removed the vegetative parts prior to the analysis, so that could be the

reason for their results.

For the fermentation, the increase observed was even higher (Figure 12). Once again, the highest

increase was observed in soybean samples fermented at 30oC (17,3%) and the lowest at jack beans

fermented at 37oC (0,2%). Mugendi & Njagi (2010) examined the effect of fermentation and

germination on the protein content of velvet beans and found that fermentation resulted in 17,87%

versus 3,13% for germination. Other than that, the results are controversial. Many researchers have

found a significant increase in protein in fermented legumes (Azeke et al., 2005; Baik & Han, 2012;

Reyes-Moreno et al., 2004); but there is also a great deal of them that observed a decreased protein

content after fermentation (Allagheny et al., 1996; Granito et al., 2005; Marisela Granito & Alvarez,

2006). The fermentation conditions and the microorganisms used in the studies varied a lot, and that

could be the reason for the contradicting results. The bacteria used in the present study was

B.subtilis, a bacteria naturally found in many traditional fermented products in Africa (Parkouda et

al., 2009).

In this study, there is no doubt that fermentation lead to elevated levels of protein. What is

inconclusive is the effect of temperature on the outcome. Some of the legumes exhibited better

results, regarding the protein content, at 30oC and other at 37

oC. An error during the experimental

work, resulted in one Cowpea Asetenapa sample being fermented for 24h at 30oC followed by 24h at

51

37oC, instead of 48h at 37

oC; nevertheless, the protein content of this sample was comparable to the

other Asetenapa samples fermented at 37oC.

Among the samples, soybeans and bambara groundnuts were the ones with the highest %protein

increase, both for germination and for fermentation, distinctively higher than that of the other

legumes. Both these legumes had the highest fat content. Fat is one of the storage compounds in

seeds that is degraded during germination (Mugendi & Njagi, 2010), and it known that Bacillus spp.

possess lipolytic activity, to a different extend depending on the strain (Ouoba et al., 2003). So,

perhaps the high protein is a result of altered protein proportion on a dry weigh basis rather than

actual increase (Akpapunam et al., 1996).

All in all, the germination and fermentation processes were deemed adequate, although

improvements could be made in the experimental procedure.

52

CONCLUSIONS

The study shows that the proximate composition (protein, fat, moisture) of the legumes examined

falls within the range according to the literature available. Soybean is the most differentiated legume,

of the ones studied, in regards to both fat and protein content, and overall according to spectroscopic

techniques (FT-IR, NIR).

Both germination and fermentation increased the protein content of the legumes considerably.

Germination for 72h resulted in higher protein levels compared to 48h of germination. In fermented

samples, the evidence on the effect of temperature in yielding higher protein contents was

inconclusive. In general fermentation brought about higher protein levels compared to germination.

Spectroscopic methods, showed a change in the protein (FT-IR) and carbohydrate (NIR) content of

the germinated and fermented samples, compared to the control ones.

PERSPECTIVES

Further investigation of the effect of temperature and time on the protein content of germinated and

fermented samples could lead to improved processing techniques.

Additionally, the determination of true protein, instead of crude protein, could be of interest since

alkaline fermentation results in elevated levels of ammonia (Allagheny et al., 1996), that could

tamper with the protein levels as determined by Kjeldahl.

Last but not least, the effect of germination and fermentation on the amino acid profile and protein

digestibility of the legumes could be of utmost importance in designing nutritious and acceptable

food products based on processed legumes.

53

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i

APPENDICES

Appendix 1 – FT- IR spectra

Mean FT-IR (MSC) spectra of the germinated, fermented and control soybean samples. Control sample is coloured blue, Germination

48h is light blue, Germination 72h purple, Fermentation at 30oC is green and Fermentation at 37

oC red.

Mean FT-IR (MSC) spectra of the germinated, fermented and control cowpea asetenapa samples. Control sample is coloured blue,

Germination 48h is light blue, Germination 72h purple, Fermentation at 30oC is green and Fermentation at 37

oC red.

1000 1500 2000 2500 3000 3500 4000

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

cm-1

1000 1500 2000 2500 3000 3500 4000

0

0.005

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0.015

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0.025

0.03

0.035

0.04

cm-1

ii

Mean FT-IR (MSC) spectra of the germinated, fermented and control cowpea soronko samples. Control sample is coloured blue,

Germination 48h is light blue, Germination 72h purple, Fermentation at 30oC is green and Fermentation at 37

oC red.

Mean FT-IR (MSC) spectra of the germinated, fermented and control bambara groundnut samples. Control sample is coloured blue,

Germination 48h is light blue, Germination 72h purple, Fermentation at 30oC is green and Fermentation at 37

oC red.

1000 1500 2000 2500 3000 3500 4000

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

cm-1

1000 1500 2000 2500 3000 3500 4000

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

cm-1

iii

Mean FT-IR (MSC) spectra of the germinated, fermented and control mucuna bean samples. Control sample is coloured blue,

Germination 48h is light blue, Germination 72h purple, Fermentation at 30oC is green and Fermentation at 37

oC red.

Mean FT-IR (MSC) spectra of the germinated, fermented and control jack bean samples. Control sample is coloured blue,

Germination 48h is light blue, Germination 72h purple, Fermentation at 30oC is green and Fermentation at 37

oC red.

1000 1500 2000 2500 3000 3500 4000

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

cm-1

1000 1500 2000 2500 3000 3500 4000

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

cm-1

iv

Appendix 2 – NIR spectra

Mean NIR (MSC) spectra of the germinated, fermented and control soybean samples. Control sample is coloured purple,

Germination 48h is red, Germination 72h light blue, Fermentation at 30oC is blue and Fermentation at 37

oC green.

Mean NIR (MSC) spectra of the germinated, fermented and control cowpea asetenapa samples. Control sample is coloured purple,

Germination 48h is red, Germination 72h light blue, Fermentation at 30oC is blue and Fermentation at 37

oC green.

4500 5000 5500 6000 6500 7000 7500 8000 8500 9000 9500

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

cm-1

4500 5000 5500 6000 6500 7000 7500 8000 8500 9000 9500

0.05

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0.2

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0.3

0.35

0.4

0.45

0.5

cm-1

v

Mean NIR (MSC) spectra of the germinated, fermented and control cowpea soronko samples. Control sample is coloured purple,

Germination 48h is red, Germination 72h light blue, Fermentation at 30oC is blue and Fermentation at 37

oC green.

Mean NIR (MSC) spectra of the germinated, fermented and control bambara groundnut samples. Control sample is coloured purple,

Germination 48h is red, Germination 72h light blue, Fermentation at 30oC is blue and Fermentation at 37

oC green.

4500 5000 5500 6000 6500 7000 7500 8000 8500 9000 9500

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

cm-1

4500 5000 5500 6000 6500 7000 7500 8000 8500 9000 9500

0.05

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0.3

0.35

0.4

0.45

0.5

cm-1

vi

Mean NIR (MSC) spectra of the germinated, fermented and control mucuna bean samples. Control sample is coloured purple,

Germination 48h is red, Germination 72h light blue, Fermentation at 30oC is blue and Fermentation at 37

oC green.

Mean NIR (MSC) spectra of the germinated, fermented and control jack bean samples. Control sample is coloured purple,

Germination 48h is red, Germination 72h light blue, Fermentation at 30oC is blue and Fermentation at 37

oC green.

4500 5000 5500 6000 6500 7000 7500 8000 8500 9000 9500

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

cm-1

4500 5000 5500 6000 6500 7000 7500 8000 8500 9000 9500

0.05

0.1

0.15

0.2

0.25

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0.35

0.4

0.45

0.5

cm-1