A meta-QTL analysis was conducted in Indian mustard to identify robust and stable meta-QTLs (MQTLs) by utilizing 1504 available QTLs, which included 891 QTLs for yield-related traits and 613 QTLs for quality traits. For yield-related traits, a total of 57 MQTLs (YRTs_MQTLs) were uncovered from the clustering of 560 projected QTLs, which had a 4.18-fold smaller confidence interval (CI) than that of the initial QTLs, whereas, for quality traits, as many as 51 MQTLs (Quality_MQTLs) were derived from 324 projected QTLs, which had a 2.65-fold smaller CI than that of the initial QTLs. Sixteen YRTs_MQTLs were observed to share chromosomal positions with 16 Quality_MQTLs. Moreover, four most promising YRTs_MQTLs and eight Quality-MQTLs were also selected and recommended for use in breeding programs. Four of these selected MQTLs were also validated with significant SNPs that were identified in previously published genome-wide association studies. Further, in silico functional analysis of some promising MQTLs allowed the detection of as many as 1435 genes, which also involved 15 high-confidence candidate genes (CGs) for yield-related traits and 46 high-confidence CGs for quality traits. After validation, the identified CGs can also be exploited to model the plant architecture and to improve quality traits through marker-assisted breeding, genetic engineering, and genome editing approaches.

Field pea (Pisum sativum L.) is a highly nutritious winter-season pulse crop. It is used as food, feed, and fodder and offers nutritional security to low-income people in developing countries. Different graphical approaches like Principal Component Analysis (PCA) and Genotype + Genotype × Environment (GGE) biplots were used along with the conventional line × tester to identify efficient parents, combining ability effects and distinct heterotic groups in field pea (Pisum sativum L.). The study used a line tester design (9 × 3) for seed yield and its associated traits. In the conventional analysis, lines Aman and HFP 715 and the tester GP02/1108, as well as crosses HFP 715 × GP02/1108, Aman × GP02/1108, and Pant P-243 × HFP 1426 showed the best GCA (General Combining Ability) and SCA (Specific Combining Ability) effects, respectively, for seed yield and its attributes. The ^σ2SCA > ^σ2GCA, and ^σ2D > ^σ2A in almost all the traits indicated control of non-additive gene effects. High manifestations of heterobeltiosis for seed yield were evidenced by the superiority of 24 out of 27 crosses over the better parent. The highest significant heterobeltiosis was observed in the cross HFP 715 × GP02/1108, followed by IPF 14-16 × GP02/1108, IPF 14-16 × HFP 1426, DDR-23 × HFP 1426, DDR-23 × GP02/1108, and Aman × GP02/1108 for yield and its attributes. The biplot techniques were used to analyze data and compare their results with conventional line × tester analysis. Overall, graphical analysis results were very similar to those of traditional analysis. Consequently, it can surely be assumed that these methods could be helpful in presenting data from field pea breeding experiments carried out with line × tester design.

Background: Variety characterization is the foremost important step that should be done by breeders to classify a variety into distinct groups. A significant technique for locating and assessing several genotypes for the registration, protection and production of seeds of superior quality is the Distinctness, Uniformity and Stability (DUS) characterization. Consequently, the current investigation aimed to use DUS descriptors to describe and assess the variance present in mungbean genotypes. Methods: One hundred forty-two mungbean genotypes were examined using 21 agro-morphological qualitative DUS descriptors in a randomized block design with two replications across two seasons, kharif 2021 and kharif 2022. Result: In the twenty-one DUS traits that were examined, four characters’ plant growth habit, leaf shape, leaf size and seed size exhibited trimorphic variance. Three characters (plant habit, stem pubescence and pod pubescence) were found to be identical among all genotypes while fourteen characters displayed dimorphic variance. All of the mungbean genotypes displayed a significant degree of variance for all DUS characteristics. Based on the UPGMA method of clustering, the dendrogram classified all the one hundred forty-two genotypes into three major clusters. The presence of variation among the genotypes under study was demonstrated by the further classification of these primary clusters into five sub-clusters. The majority of the genotypes were found in cluster II (121 genotypes), which was followed by cluster I (18 genotypes) and cluster III (3 genotypes).

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