Ashok Kumar Parihar

Mungbean Yellow Mosaic India Virus (MYMIV) is a major disease of urdbean (black gram) crop, which is one of India's most widely consumed pulses. In the present study, RNA‐Seq‐mediated differential gene expression analysis was conducted between a resistant variety (PU‐31) and a susceptible variety (LBG‐17) of urdbeans for the identification of resistant genes for the MYMIV disease. This resulted in the generation of a total of 827,157,878 clean reads through NovaSeq 6000 sequencing from the 12 samples of resistant and susceptible varieties evaluated under control (disease‐free) and treatment conditions (disease condition). A trinity‐based de novo assembly was developed with 553,889 coding regions of the urdbean genome. A set of 16 transcripts related to disease resistance that had high expression values in the present study was analyzed for differential gene expression using RT‐PCR. Among these, two validated transcripts, TRINITY_DN4785_c0_g1_i9 (F‐box/LRR resistance gene) and TRINITY_DN21430_c0_g3_i1 (Tobacco Mosaic Virus resistance gene), were used to develop DNA‐based PCR markers. Using Sanger sequencing, five SNPs were found for an “F‐box/LRR” resistance gene and a single SNP in the case of the “TMV” resistance gene. Using these SNPs, polymorphic PCR usable primers were designed and validated in a panel of urdbean genotypes. Utilizing SNP‐445 of the “TMV” resistance gene, CAPS (Cleaved Amplified Polymorphic Sequence) and TSP (Temperature Switch PCR) markers were developed, and a TSP marker using SNP‐361 was developed for the “F‐box/LRR” resistance gene. Several urdbean varieties examined in the present study were found to harbor resistance alleles of the “TMV” and “F‐box/LRR” genes, which likely contribute to the durability of resistance in these varieties. The molecular markers developed could be readily applied in marker‐assisted selection for MYMIV resistance genes in urdbean.

Hardseededness, characterized by a water‐impermeable seed coat, is a common trait in blackgram that influences seed quality, cooking time, and tolerance to pre‐harvest sprouting. Understanding environmental and genotype regulation of this trait could help identify the optimal season for enhancing seed quality and abiotic stress tolerance; however, this remains poorly understood. A panel of 127 blackgram genotypes was evaluated during the summer and rainy seasons over two consecutive years. Crop phenology, stage‐specific weather variables, and seed physical traits were recorded and analysed to examine their relationships with hardseededness. Multivariate analyses were used to explore the association of phenological and climate factors with hardseededness and to identify stable genotypes with consistently high or low hard seeds. Seeds harvested during the rainy season had more hard seeds (40%–48%) compared to those from the summer season (3%–7%), irrespective of genotype. Combined ANOVA revealed that crop season was the major contributor to variability in hardseededness (72.7%), while genotype contributed 7.7%. Rainfall during the vegetative period, relative humidity during reproductive period, and longer maturity duration were positively associated with hardseededness, whereas higher maximum temperatures during the reproductive period negatively influenced this trait. Furthermore, there were seasonal variations in seed phenolic profiles, with p‐hydroxybenzoic acid, catechin hydrate, and syringic acid showing positive associations with hardseededness. Genotypes PKJU1, CN35‐15, WBU108 had the highest hardseededness during the rainy season, while IPU30, IPU99‐23, PLU 44 had the lowest. The results highlight significant genotypic and seasonal influences on hardseededness in blackgram, offering valuable insights for improving seed quality. Genotypes identified to have either high or low levels of hard seeds can be utilized to improve pre‐harvest sprouting tolerance or optimize germination, respectively.

This study aimed to evaluate the impact of diverse environments on agronomic traits of small‐seeded lentils in India and to identify strategic environment(s) for crop improvement using empirical approaches. Sixteen small‐seeded lentil genotypes were tested across 16 locations, covering North Hill Zone (NHZ), North Western Plain Zone (NWPZ), and North Eastern Plain Zone (NEPZ). Crop yield exhibited a quadratic response to maximum temperature during flowering (TMAX_F) and minimum temperature during reproductive period (TMIN_RP), indicating that both higher and lower TMAX_F (optimal = 23.5°C) and TMIN_RP (optimal = 12.0°C) negatively affected yield. Low temperatures extended crop duration, and correlation analysis confirmed that environment‐induced variations in vegetative or maturity periods significantly influenced yield, as further validated by regression models and principal component analysis. While an extended reproductive period increased seed weight, its association with grain yield was non‐significant. Among the tested zones, NWPZ recorded the highest average yield (1359 kg ha⁻¹), while NEPZ (1269 kg ha⁻¹) demonstrated greater yield consistency across locations. Genotype, environment, and genotype‐by‐environment interaction (GEI) contributed 6%, 53%, and 36% of the total yield variation, respectively. Biplot analysis identified three distinct mega‐environments, with Durgapura (NWPZ), Varanasi (NEPZ), Faizabad (NEPZ), and Berthin (NHZ) emerging as ideal testing sites. This study highlights the significant influence of diverse agroclimatic conditions on crop yield and emphasizes the need for region‐specific breeding to harness positive GEI (at mega‐environment scale) and to prioritize early flowering and optimal seed traits to achieve broader adaptability across Indian climates.

Understanding crop performance across diverse agro‐ecologies is crucial for developing region‐specific breeding strategies. This multi‐location study examined the impact of diverse environments on crop eco‐phenology and genotype‐by‐environment interactions (GEI) of tall‐type field pea breeding lines. Empirical methods were employed to identify strategic locations that support higher yields and unique genotypic traits. The results revealed significant variations across locations, with coefficients of variation for key traits as follows: days to flowering (31%), days to maturity (20%), reproductive period (19%), yield (35%), and seed weight (31%). Environmental component accounted for the largest yield variation (78%), followed by GEI (13%). Correlation analysis indicated a significant influence of both temperature extremes, particularly maximum temperature during flowering, on crop yields. Higher minimum temperatures during flowering and reproductive period were associated with reduced yields, while extended crop duration in cooler regions also negatively impacted yields. A significant quadratic relationship between seed weight and yield underscored the importance of seed weight as a yield‐stabilising trait. GGE‐biplot analysis identified four mega‐environments, and designated Faizabad, Pantnagar, Varanasi, and Kota as ideal testing sites for selecting genotypes with broader adaptability. These findings provide valuable insights for redesigning field pea breeding programmes at the national level.

Characterization of crop-growing environments in relation to crop’s genotypic performance is crucial to harness positive genotype-by-environment interactions (GEI) in systematic breeding programs. Given that, the study aimed to delineate the impact of diverse environments on crop phenology and yield traits of dwarf-statured field pea, pinpointing location(s) favoring higher yield and distinctiveness within breeding lines. We tested twelve field pea breeding lines across twenty locations in India, covering Central Zone (CZ), North Western Plain Zone (NWPZ), North Eastern Plain Zone (NEPZ), and Northern Hill Zone (NHZ). Across these locations, maximum and minimum temperatures during flowering (TMAX_F, TMIN_F) and reproductive period (TMAX_RP, TMIN_RP) ranged 18.9–28.3, 3.3–18.0, 15.0-30.8, and 7.9-22.1^oC, respectively. Meanwhile, notable variations in phenological and agronomic traits (coefficient of variation) were observed: flowering (31%), days to maturity (21%), reproductive period (18%), grain yield (48%), and 100-seed weight (18%). Combined ANOVA demonstrated an oversized impact of environment (81%) on yield, while genotype and GEI effects were 2% and 14%, respectively. The variables TMIN_F, TMIN_RP, and cumulative growing degree-day showed positive correlations with yield, while extended vegetative and maturity durations negatively influenced yield (p < 0.05). Additionally, linear mixed-models and PCA results explained that instability in crop phenology had significant influence on field pea yield. Seed weight was markedly varied within the locations (9.9–20.8 g) and both higher and lower seed weights were associated with lower yields (Optimal = 17.1 g). HA-GGE biplot-based on environment focus-scaling demonstrated three mega-environments and specific locations viz. Kota (CZ), SK Nagar (CZ), Raipur (CZ), Sehore (CZ), and Pantnagar (NWPZ) as the ideal testing-environments with high efficiency in selecting new genotypes with wider adaptability. The study findings highlight distinct impact of environments on crop phenology and agronomic traits of field pea (dwarf-type), hold substantial value in designing efficient field pea (dwarf-type) breeding program at mega-environment scale.

Occurrence of physical dormancy or hard seed coat prevents proper utilization and conservation of wild species ofCajanusandRhynchosia, which offers a source of many useful traits. Hence, an attempt has been made to understand the variability in hardseededness and the pretreatments (hot air treatment for 3, 5, 7, and 14 days; hot air treatment for 30 and 60 min; sulfuric acid scarification for 2 and 5 min; partial incision on seed coat) to overcome it in 44 accessions of 10 wild pigeon pea species. The level of hardseededness varied from 36% to 100% with an average of 76.5%. Likewise, time to 1% germination or time taken to initiate germination (T1), time to 50% germination (T50), and mean germination time (MGT) varied between 16.18–249.9 h, 94.7–607.7 h, and 37.5–153.2 h, respectively. Overall, all the treatments reduced hardseededness and improved germination over the control, with partial incision on seed coat being the best treatment for all the species recording 70%–98% germination, except forRhynchosia aurea(30%) andCajanus cajanifolius(59%). The hot water treatment for 30 and 60 min was the best treatment forC. cajanifoliusrecording germination of 66%–70% as compared to 11% in control. The sulfuric acid scarification for 2 min was the best pretreatment for overcoming dormancy and improving germination inRhynchosia bracteata,Rhynchosia rothii, andRhynchosia rufescens. The result indicated a significant inter‐ and intraspecific variation in the effectiveness of pretreatments in overcoming physical dormancy, suggesting that the optimum pretreatment for overcoming hardseededness should be standardized for each accession. Also, the dormancy‐breaking pretreatments not only reduced hardseededness and improved final germination percent but it also reduced time for T1, T50, and MGT, suggesting that use of such pretreatments before sowing could result into higher, uniform, and rapid germination.

Although chickpea (Cicer arietinum L.) has high yield potential, its seed yield is often low and unstable due to the impact of abiotic stresses, such as drought and heat. As a result of global warming, both drought and heat are estimated to be major yield constraints between one-quarter and one-third per annum. In the present review, genomic-mediated breeding strategies to increase resilience against global warming. Exacerbated drought and heat stresses have been examined to understand the latest advancement happening for better management of these challenges. Resistance mechanisms for drought and heat stresses consist of (i) escape via earliness, (ii) avoidance via morphological traits such as better root traits, compound leaves, or multipinnate leaves and double-/multiple-podded traits, and (iii) tolerance via molecular and physiological traits, such as special tissue and cellular abilities. Both stresses in chickpeas are quantitatively governed by minor genes and are profoundly influenced by edaphic and other environmental conditions. High-yield genotypes have traditionally been screened for resistance to drought and heat stresses in the target selection environment under stress conditions or in the simulacrum mediums under controlled conditions. There are many drought- and heat-tolerant genotypes among domestic and wild Cicer chickpeas, especially in accessions of C. reticulatum Ladiz., C. echinospermum P.H. Davis, and C. turcicum Toker, J. Berger, and Gokturk. The delineation of quantitative trait loci (QTLs) and genes allied to drought- and heat-related attributes have paved the way for designing stress-tolerant cultivars in chickpeas. Transgenic and “omics” technologies hold newer avenues for the basic understanding of background metabolic exchanges of QTLs/candidate genes for their further utilization. The overview of the effect of drought and heat stresses, its mechanisms/adaptive strategies, and markers linked to stress-related traits with their genetics and sources are pre-requisites for framing breeding programs of chickpeas with the intent of imparting drought tolerance. Ideotype chickpeas for resistance to drought and heat stresses were, therefore, developed directly using marker-aided selection over multiple locations. The current understanding of molecular breeding supported by functional genomics and omics technologies in developing drought- and heat-tolerant chickpea is discussed in this review.