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Soybean is an economically important oilseed crop with diverse uses as food, feed, biofuel and so forth. Although the demand for soybean is growing rapidly worldwide, the narrow genetic base of released cultivars due to meagre utilisation of available wild and untapped genetic resources is a major factor contributing to stagnant production and productivity levels of soybean. Considering the continuously increasing global population, changing dietary habits, ongoing climatic fluctuations, rapidly evolving biotic stresses and shrinking land and water resources, utilisation of novel and diverse sources of variation is required for the genetic enhancement of soybean. To widen the genetic base of commercial soybean cultivars and to improve the genetic gain of the crop focused and systematic pre‐breeding efforts can play a game‐changing role by supplying novel genes in crop improvement programs. This article discusses the rationale of tapping wild and untapped genetic resources of soybean, gene pools, soybean genetic resources conserved ex‐situ and its utilisation status, genetic base of commercial soybean cultivars, identified novel genes and genomic regions in wild genetic resources, pre‐breeding efforts in India and strategies for incorporating desirable traits in the elite cultivated gene pool for fulfilling the requirements of farmers and other end‐users. [ABSTRACT FROM AUTHOR]

The study used the DSSAT model to assess potential soybean yields in different regions of India and validated it under diverse agroecological conditions. The average simulated yield under irrigated conditions was 3794 kg ha−1 relative to the simulated average rainfed yield of 2446 kg ha−1, showing a 35.52% reduction in grain yield due to adverse moisture conditions under rainfed conditions. Relative to simulated yield, the average observed (actual) rainfed yield across 43 districts of India was 1025 kg ha−1, which was 2769 and 1421 kg ha−1 lower than irrigated and rainfed potential yield, respectively. A significant positive correlation was observed between simulated water non-limited yield and solar radiation (R2 = 0.55, p ≤ 0.05). The simulated rainfed grain yield (R2 = 0.66, p ≤ 0.05) had a significant, positive, and curvilinear relationship with growing season rainfall. On the other hand, the actual yield (R2 = 0.008) showed a non-significant relationship with mean crop seasonal rainfall across locations. The gap between simulated yield under irrigated and rainfed conditions is huge at locations with low seasonal rainfall and narrows with increasing rainfall. In addition, the gap between actual yield and simulated yield under rainfed conditions was larger, even in high seasonal rainfall areas. The yield gap under rainfed conditions is due to the non-adoption of improved crop management practices and could be reduced with proper interventions. This includes adapting drought-resistant varieties, conserving rainwater, changing land configuration, and adopting waterlogging-tolerant varieties using improved technology to reduce the soybean yield gap. [ABSTRACT FROM AUTHOR]

Multi‐parent advanced generation inter‐cross (MAGIC) populations have been developed and utilized in crop improvement programs in several economically important crops. In the current study, soybean (Glycine max L.) MAGIC population was evaluated at four locations to identify stable and high‐yielding MAGIC RILs (recombinant inbred lines) and to understand the genotype and environmental interaction for grain yield and attributing traits. For different traits under study, pooled analysis of variance indicated the significant genotype × environmental interactions at p < 0.01. RILs such as G236, G455, G159, G493, and G488 found ideal for grain yield across the four environments. Through multi‐trait genotype‐ideotype distance index ideotype‐MAGIC RILs have been identified for each location. Significant positive correlation of grain yield with pods per plant, 100‐seed weight, plant height, number of nodes per plant, and branches per plant has been identified. Under field conditions, screening of F2:3 generation of MAGIC population revealed that only 59 progenies exhibited adult plant resistance for charcoal rot disease (caused by Macrophomina phaseolina). Although under controlled conditions parental genotypes EC 572136 and EC 572109 found to be partially resistant with least mean necrosis length, MAGIC RILs (F2:8) showed variable reaction. Thus, the study established diverse genetic resources useful for both mapping and varietal development program. Core Ideas: The study on G × E interactions identified number of ideal genotypes performing better across the four locations.These genotypes were valuable resources for direct release as varieties or large‐scale testing under All India Coordinated Research Project (AICRP) trials.Charcoal rot screening revealed significant variation for the mapping studies in the population. [ABSTRACT FROM AUTHOR]

Soybean is a major source of vegetable oil and protein worldwide. Globally, India is among the top five producers where soybean is a major oilseed grown under diverse agro-climatic conditions by small and marginal farmers. The present study aims to identify soybean varieties with higher yield levels, resistance to pestdiseases and adaptability to climatic fluctuations. One hundred and twenty-five (125) indigenous and exotic soybean germplasm accessions and five checks were evaluated and characterized for eight agro-morphological traits at five testing locations and also screened for frog-eye leaf spot (FLS) and yellow mosaic virus (YMV) diseases under hot-spot locations during the rainy season. A wide range of variability was observed among accessions for days to 50% flowering (39–59), plant height (41–111 cm), number of nodes/plant (10–30), pod clusters/plant (14–39), number of pods/plant (40–102), days to maturity (96–115), grain yield/plant (4.89–16.54 g) and 100-seed weight (6.02–13.72 g). Among various traits, 100-seed weight (0.45), number of pods/plant (0.60) and number of pod clusters/plant (0.38) were found to be major yield-contributing traits as they exhibited highly significant correlation with grain yield/plant. Principal components PCI and PCII with eigen value >1 accounted for 42.66 and 27.08% of the total variation, respectively. Accessions G24 (EC 393222) from Taiwan and G40 (IMP-1) from the USA belonging to cluster IV were found promising for multiple yield traits and JS 20–38 from cluster III for earliness as per cluster analysis. GGE biplot average environment coordination (AEC) view revealed that the accessions viz., G11 (EC 333872), G2 (EC 251506) and G47 (TNAU-S-55) were the best performing stable genotypes in terms of grain yield/plant across locations. Twelve accessions had a high level of resistance against both FLS and YMV diseases under natural hot-spot conditions which can be utilized as promising donors in the soybean breeding programme. [ABSTRACT FROM AUTHOR]

Soybean [Glycine max (L.) Merr.] is the predominant rainfed Indian oilseed crop cultivated across diverse agro-climatic zones. Understanding the genotype × environment interaction (GEI) is crucial for development of stable and wider adaptable soybean varieties. In the current study, 10 elite breeding lines were evaluated across 19 diverse locations for days to flowering, days to maturity, plant height, hundred seed weight and grain yield during 2020. The stability index as measured through weighted average of absolute scores (WAASB) identified SL 1213 and DS 1320 to have stable grain yield. WAASBY superiority index, which is based on mean performance and stability, was also higher for SL 1213. Multitrait stability index (MTSI) was employed to select genotypes with higher grain yield, early flowering, early maturity, higher hundred seed weight and plant height, simultaneously and genotypes DS 1320 and SL 1213 were identified through MTSI. Based on the three indices, SL 1213 was found to be the candidate genotype for breeding for higher yield, wider adaptability and for ideotype breeding. Based on cluster analysis, SL 1213 × JS 22-07 and SL 1213 × NRC 149 were found to be the ideal cross combinations for developing high-yielding and wider adaptable genotypes. Through Principal Component Analysis (PCA), grain yield was found to be positively associated with Relative Humidity, Effect of temperature on radiation use efficiency, Deficit by precipitation, Total rainfall precipitation during the crop cycle, Global solar radiation based on latitude and Julian day and Dew-point temperature at 2 m above the surface of the earth. [ABSTRACT FROM AUTHOR]

Triticum militinae Zhuk. et Migusch. belongs to timopheevii [Triticum timopheevii (Zhuk.) Zhuk.] group of wheats with 2n = 4x = 28 chromosomes and genome formula AtAtGG. Triticum militinae Zhuk. et Migusch. is known to carry resistance to fungal diseases including rusts and powdery mildew. Genes from timopheevii wheat can be incorporated into cultivated wheat by either direct hybridization or through development of amphiploids. Three T. militinae derived introgression lines (ILs) Triticum Militinae Derivative (TMD) 6-4, TMD7-5 and TMD11-5 were selected for the current study based on cytological stability. All three ILs showed resistance against wide spectrum of Indian pathotypes of leaf rust. More than 1200 SSR markers were used for genotyping of ILs and parental lines. The ILs showed variable and multiple introgressions in different chromosomes of A, B and D genome of wheat. The introgression points were distributed mostly in the distal regions though significant introgressions were also observed in proximal regions of some chromosomes. The extent of introgression in ILs TMD6-4, TMD7-5 and TMD11-5 was 2.8, 8.3 and 8.6% respectively. The set of ‘informative markers’ in the Molecularly Tagged Chromosome Regions (MTCR) of T. militinae origin can also be used in future for tagging of genes associated with traits of economic importance apart from leaf rust resistance. The transferability of Triticum aestivum L. SSR markers to T. militinae was 96.4% for A genome, 95.8% for B genome and 84.3% for D genome. Transferability of wheat SSR markers to T. militinae can be used in preparing genetic maps in timopheevii group of wheats. [ABSTRACT FROM AUTHOR]