Determination of Compositional Characteristics, Functional Properties and Cluster Analysis of Lima Bean Accessions (Phaseolus Lunatus)
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Date
MAY 2015
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Abstract
Demand for alternative sources of protein foods have increased due to population growth especially in developing countries. Lima beans are underutilized legumes of wide importance for human and livestock nutrition. Thirty-one lima accessions have been identified in Ghana but information on their nutritional composition, genetic variability, storage protein content and functionalities is scarce. This research was carried out to determine the proximate composition and mineral content of ten lima bean accessions and to investigate the storage protein content, functional properties of the flour and on this basis classify the genotypes into groups for genetic improvement. A wide variability in seed size, seed weight, nutrient composition, storage protein content and functional properties was observed. Mean seed length ranged from 10.2 to 23.0 mm. Hundred seed weight varied from 34.2 to 138.5 g. Nine of the accessions belonged to the Andean gene pool while one was of a Meso-American origin. The range values of protein, fat, ash, fiber, and carbohydrate contents on dry weight basis was 20.5 to 24.6 %, 0.6 to 1.7 %, 3.29 to 6.7 %, 2.93 to 9.6 %, and 47.0 to 58.1 %, respectively. Mean mineral contents were 893 mg/100 g for potassium, 212 mg/100 g for calcium, 4.9 mg/100 g for iron, and 207.5 mg/100 g for phosphorus. Potassium and phosphorus was the most abundant mineral in lima beans. With regard to storage proteins, globulins were present at 19.27-61.88 % and albumins at 10.53-57.67 %. Glutelins and prolamins occurred at least concentrations of 6.68-35.77 % and 3.13-16.94 %, respectively. Lima bean flour possessed high water and oil binding capacities of 1.00-2.33g/g and 1.01-1.55g/g, respectively. However, emulsion and foaming capacities were low in comparison to soybean and cowpea. Correlation coefficients among the four groups of traits were mostly weak and nonsignificant except between bean size, hundred seed weight, and storage protein content. UPGMA cluster analysis based on seed size, proximate, storage proteins and functional properties clustered the ten accessions into five main groups. Principal component analysis revealed that the first six principal components accounted for 95 % of the variation in the data. Size and weight, protein, fat and carbohydrate, albumin, prolamin, glutelin and the functional properties, water and oil binding capacities, swelling capacity and bulk density were the most important traits that contributed to the variance.
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A thesis submitted to the Department of Food Science and Technology, College of Science, in partial fulfilment of the requirements for the degree of Master of Science in Food Quality Management,