The fungus Macrophomina phaseolina is a causative agent of diseases in more than 500 plant species. The fungus is primarily soil‐inhabiting but is also seed‐borne in many crops including soybean. It survives in the soil mainly as microsclerotia that germinate repeatedly during the crop‐growing season. Low C : N ratio in the soil and high bulk density as well as high soil moisture content adversely affect the survival of sclerotia. The disease can be managed to some extent by cultural practices, organic amendments, seed treatment and genetic host resistance. The scattered literature on these aspects is reviewed in this paper.

Soybean [Glycine max (L.) Merr.] is the leading Indian oilseed crop grown under rainfed conditions. Meticulous understanding of genotype × environment interaction patterns is essential to develop superior and widely adaptable soybean varieties. In the current study, 32 soybean genotypes were evaluated at eight locations for two consecutive years. Additive main effect and multiplicative interaction ANOVA revealed that only 41.6% of variance was explained by the first two interaction principal component axes (IPCAs), leaving 58.4% to the remaining 13 IPCs. The weighted average of absolute scores (WAASB) stability index, a best linear unbiased prediction–based mixed model that takes in to account all the IPCAs, has been used in stability analysis. SL1171 (WAASB score, 4.09) was found to be highly stable among the genotypes under study, with grain yield (2,050.87 kg ha−1) lower than the grand mean (2,082.50 kg ha−1). A superiority index that allows weighting between mean performance and stability (WAASBY) was used to select stable and high yielding genotypes. MACS 1620 (WAASBY score, 74.47) was found to be high yielding (2,476.05 kg ha−1) and widely adaptable. A simultaneous selection index (i.e., multi‐trait stability index [MTSI]) has been used for selecting early‐maturing and high‐yielding genotypes. DSb 33 was found to have the lowest MTSI (0.001) and can be used as a parent for breeding for early maturity and higher yield. The 100‐seed weight was found to be positively correlated with grain yield and can be used in direct selection for grain yield. Through genotypic cluster analysis, NRC 146 was found to be more divergent, with the highest mean 100 seed weight (16.39 g), and therefore can be used as a parent for breeding solely for grain yield.

Breeding for higher yield and wider adaptability are major objectives of soybean crop improvement. In the present study, 68 advanced breeding lines along with seven best checks were evaluated for yield and attributing traits by following group balanced block design. Three blocks were constituted based on the maturity duration of the breeding lines. High genetic variability for the twelve quantitative traits was found within and across the three blocks. Several genotypes were found to outperform check varieties for yield and attributing traits. During the same crop season, one of the promising entries, NRC 128,was evaluated across seven locations for its wider adaptability and it has shown stable performance in Northern plain Zone with > 20% higher yield superiority over best check PS 1347. However, it produced 9.8% yield superiority over best check in Eastern Zone. Screening for waterlogging tolerance under artificial conditions revealed that NRC 128 was on par with the tolerant variety JS 97–52. Based on the yield superiority, wider adaptability and waterlogging tolerance, NRC 128 was released and notified by Central Varietal Release Committee (CVRC) of India, for its cultivation across Eastern and Northern Plain Zones of India.

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Aim: To understand the magnitude and pattern of genotype-environment interaction in vegetable type soybeans and to identify mega environment(s) and best performing genotype(s) across environments. Methodology: Five vegetable type soybean genotypes were evaluated across five geographical locations viz., Indore, Parbhani, Adilabad, Bengaluru and Pune, during rainy season of 2018. Genotypes were grown in a plot size of 1.35 x 3 m2 in three replications in randomized block design. Data on green pod yield, green seed test weight, days to 50% flowering, days to maturity and plant height were recorded using standard methods. GGE biplot analysis was performed using software “GGE Biplot version 7.0”. Results: In the present investigation, except in case of green seed test weight, in remaining four traits, major portion of variation was contributed by location (52.95-79.4%) followed by genotype (17.7-42.7%) and genotype x location interaction (2.21-4.29%). Through GGE biplot analysis, Bengaluru was found to be near ideal environment and genotypes Karune and Harasoya were found to be the best performers across the locations with respect to green pod yield. Interpretation: Bengaluru was found to be near ideal environment for vegetable type soybean evaluation. Selection for genotypes having wider adaptability can be conducted at this location. Genotypes Karune and Harasoya were found to be the best performers with respect to green pod yield. These two genotypes can be included as parents for breeding as vegetable type soybean. Key words: GEE biplot, Multienvironmental analyses, Soybean genotypes

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In recent years, soybean [Glycine max (L.) Merrill] has emerged as a major rainy season cash crop in central India. In the present study, the changes in soybean scenario over a period from 2001 to 2013 of Indore district and Madhya Pradesh since 1980 with respect to area sown, production, and productivity are discussed, taking in consideration the changes in climatic variables like rainfall and temperature during the corresponding period. The data related to area, production, and yield of soybean from 2001 to 2013 of Indore district, Madhya Pradesh since 1980, and India were collected from published work. To observe yield changes across seasons, the means of the yield were plotted against the seasons. It was observed that in last 10 years, there is a shift in the peak rainfall from July to August, and the total rainfall during the peak month was reduced. The rainfall during the emergence and vegetative growth of the soybean crop has been reduced. However, the soybean productivity has increased with 21.6 and 13.9 kg/ha/year in Indore district and in Madhya Pradesh, respectively. Release of new cultivars and improvements in farming technology have contributed to this continuous increase in soybean yield. A few studies showed that potential adaptation options for sustained soybean productivity in India include adjustment in cropping calendar and crop rotation, development and promotion of use of high yielding varieties, and sustainable technological applications. Delayed sowing date for soybean crop at all locations in India should be most effective in mitigating the thermal effects of climate change.

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