Characterization and classification of selective Indian chickpea cultivars based on physical and hydration properties, using image and multivariate analysis

Abstract

Chickpea (Cicer arietinum) is an important leguminous crop, widely consumed for its high protein content, mainly in Asian countries. India is the largest chickpea-producing country in the world. Chickpea seeds vary in shape and size depending on the cultivars. Physical properties play an important role in designing the equipment for storage and processing. Thus, the present study was carried out with the objective to characterize selected Indian chickpea cultivars based on their physical properties and hydration characteristics. Hydration is an important preprocessing treatment in most processes like germination, cooking, and fermentation, so the water uptake characteristics (water absorption capacity, swelling index, equilibrium moisture content, and weight gain) vary depending on the size and shape of the seeds. The increase in the length of chickpea seeds after hydration was found to be in the range of 18.18% to 32.08% for different cultivars, whereas the percentage increase in width ranged from 25.62% to 45.45%. The maximum increase in sphericity was 7.39%. Weight gain (%) after hydration was observed to be ranging from 98.87 ± 0.64% to 113.53 ± 0.60%. Comparative characteristics of selective chickpea cultivars based on their physical and hydration properties were studied and classify them using multivariate analysis. Principal component analysis and hierarchical cluster analysis (HCA) for multivariate data may be used to classify the chickpea cultivars. First three principal components explained the 90% variation, with PC1 and PC2 explaining the 73.03% variation. Using HCA, all the cultivars were classified into three clusters based on the similarities in their properties. The three-dimensional (3-D) image analysis approach was also employed to study the physical characteristics before and after soaking. It can be a helpful technique for process automation as it is less time consuming.