Evaluation of Proximate Composition, Cooking Quality, and Texture Profile Analysis in Himalayan Landraces of Black Gram (Vigna mungo)

The black gram is a traditional pulse crop and is a source of different nutritional components. Due to the scientific community's preference for yield and its components, the area of nutritional composition remains unexplored. Therefore, the evaluation of various quality traits such as proximate composition, cooking quality, texture profile, and association between them is keen important for the identification of the traits influencing the selection of the genotypes. This research aimed at the evaluation of the 25 black gram genotypes for their proximate composition, the effect of different cooking methods (conventional and microwave) on cooking quality parameters, and texture profile analysis. The genotypes were screened on 17 parameters, mean and replicated value of each variable were subjected to statistical analysis. The results for proximate composition showed the range from 11.2-11.7%, 24.24-28.22%, 1.25-1.85%, 3.10-4.45%, 5.35-6.60%, 60.23-64.86% and 368.35-372.75 Kcal/100 g for moisture, protein, fat, dietary fiber, ash, utilizable carbohydrate, and gross energy respectively. Cooking time ranged from 33 to 55.5 min (traditional) to 29.5-48.5 min (microwave), L: B ratio from 1.35 to 1.85, WUR from 1.85 to 2.60, and GSL from 0.25 to 11.30%. TPA's cohesiveness, gumminess, and chewiness ranged from 0.19 to 1.44 N, 0.14-1.30 N, 0.58-3.67 N, 1.14-10.81 N, and 0.58-5.29; 1.16-10.50 N in traditional and microwave cooking. Chewiness, gumminess, protein, ash, and cooking time were positively correlated. The first seven PCs have ≥ 1 eigenvalues, accounting for 23.30, 18.00, 13.50, 9.50, 7.40, 6.70%, and 6.40% of total variability. Mandi-2, Kinnour-1, Kirmour-1, Kangra-2, Bilaspur-1, Kangra-3, Kullu-1, Kullu-4, Chamba-3, and Chamba-7 to PCs 1-2 contributed the most to diversity, indicating good selection for subsequent upgrading initiatives.

Nutritional Potential of Adzuki Bean Germplasm and Mining Nutri-Dense Accessions through Multivariate Analysis

The adzuki bean (Vigna angularis), known for its rich nutritional composition, holds significant promise in addressing food and nutritional security, particularly for low socioeconomic classes and the predominantly vegetarian and vegan populations worldwide. In this study, we assessed a total of 100 diverse adzuki bean accessions, analyzing essential nutritional compounds using AOAC's official analysis procedures and other widely accepted standard techniques. Our analysis of variance revealed significant genotype variations for all the traits studied. The variability range among different traits was as follows: moisture: 7.5-13.3 g/100 g, ash: 1.8-4.2 g/100 g, protein: 18.0-23.9 g/100 g, starch: 31.0-43.9 g/100 g, total soluble sugar: 3.0-8.2 g/100 g, phytic acid: 0.65-1.43 g/100 g, phenol: 0.01-0.59 g/100 g, antioxidant: 11.4-19.7 mg/100 g GAE. Noteworthy accessions included IC341955 and EC15256, exhibiting very high protein content, while IC341957 and IC341955 showed increased antioxidant activity. To understand intertrait relationships, we computed correlation coefficients between the traits. Principal Component Analysis (PCA) revealed that the first four principal components contributed to 63.6% of the variation. Further, hierarchical cluster analysis (HCA) identified nutri-dense accessions, such as IC360533, characterized by high ash (>4.2 g/100 g) and protein (>23.4 g/100 g) content and low phytic acid (0.652 g/100 g). These promising compositions provide practical support for the development of high-value food and feed varieties using effective breeding strategies, ultimately contributing to improved global food security.

Mining nutri-dense accessions from rice landraces of Assam, India

The Indian subcontinent is the primary center of origin of rice where huge diversity is found in the Indian rice gene pool, including landraces. North Eastern States of India are home to thousands of rice landraces which are highly diverse and good sources of nutritional traits, but most of them remain nutritionally uncharacterized. Hence, nutritional profiling of 395 Assam landraces was done for total starch, amylose content (AC), total dietary fiber (TDF), total protein content (TPC), oil, phenol, and total phytic acid (TPA) using official AOAC and standard methods, where the mean content for the estimated traits were found to be 75.2 g/100g, 22.2 g/100g, 4.67 g/100g, 9.8 g/100g, 5.26%, 0.40 GAE g/100g, and 0.34 g/100g for respectively. The glycaemic index (GI) was estimated in 24 selected accessions, out of which 17 accessions were found to have low GI (<55). Among different traits, significant correlations were found that can facilitate the direct and indirect selection such as estimated glycemic index (EGI) and amylose content (-0.803). Multivariate analyses, including principal component analysis (PCA) and hierarchical clustering analysis (HCA), revealed the similarities/differences in the nutritional attributes. Four principal components (PC) i.e., PC1, PC2, PC3, and PC4 were identified through principal component analysis (PCA) which, contributed 81.6% of the variance, where maximum loadings were from protein, oil, starch, and phytic acid. Sixteen clusters were identified through hierarchical clustering analysis (HCA) from which the trait-specific and biochemically most distant accessions could be identified for use in cultivar development in breeding programs.

Cowpea Constraints and Breeding in Europe

Cowpea (Vigna unguiculata (L.) Walp.) is a legume with a constant rate of cultivation in Southern European countries. Consumer demand for cowpea worldwide is rising due to its nutritional content, while Europe is constantly attempting to reduce the deficit in the production of pulses and invest in new, healthy food market products. Although the climatic conditions that prevail in Europe are not so harsh in terms of heat and drought as in the tropical climates where cowpea is mainly cultivated, cowpea confronts with a plethora of abiotic and biotic stresses and yield-limiting factors in Southern European countries. In this paper, we summarize the main constraints for cowpea cultivation in Europe and the breeding methods that have been or can be used. A special mention is made of the availability plant genetic resources (PGRs) and their potential for breeding purposes, aiming to promote more sustainable cropping systems as climatic shifts become more frequent and fiercer, and environmental degradation expands worldwide.

Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm

Cowpea (Vigna unguiculata (L.) Walp.) is one such legume that can facilitate achieving sustainable nutrition and climate change goals. Assessing nutritional traits conventionally can be laborious and time-consuming. NIRS is a technique used to rapidly determine biochemical parameters for large germplasm. NIRS prediction models were developed to assess protein, starch, TDF, phenols, and phytic acid based on MPLS regression. Higher RSQ_external values such as 0.903, 0.997, 0.901, 0.706, and 0.955 were obtained for protein, starch, TDF, phenols, and phytic acid respectively. Models for all the traits displayed RPD values of >2.5 except phenols and low SEP indicating the excellent prediction of models. For all the traits worked, p-value ≥ 0.05 implied the accuracy and reliability score >0.8 (except phenol) ensured the applicability of the models. These prediction models will facilitate high throughput screening of large cowpea germplasm in a non-destructive way and the selection of desirable chemotypes in any genetic background with huge application in cowpea crop improvement programs across the world.