Envirotype-based delineation of environmental effects and genotype × environment interactions in Indian soybean (Glycine max, L.).

Soybean is a rainfed crop grown across a wide range of environments in India. Its grain yield is a complex trait governed by many minor genes and influenced by environmental effects and genotype × environment interactions. In the current investigation, grain yield data of different sets of 41, 30 and 48 soybean genotypes evaluated during 2019, 2020 and 2021, respectively across 19 locations and twenty years' data on 19 different climatic parameters at these locations was used to study the environmental effects on grain yield, to understand the genotype × environment interactions and to identify the mega-environments. Through analysis of variance (ANOVA), it was found that predominant portion of the variation was explained by environmental effects (E) (53.89, 54.86 and 60.56% during 2019, 2020 and 2021, respectively), followed by genotype × environment interactions (GEI) (31.29, 33.72 and 28.82% during 2019, 2020 and 2021, respectively). Principal Component Analysis (PCA) revealed that grain yield was positively associated with RH (Relative humidity at 2 m height), FRUE (Effect of temperature on radiation use efficiency), WSM (Wind speed at 2 m height) and RTA (Global solar radiation based on latitude and Julian day) and negatively associated with VPD (Deficit of vapour pressure), Trange (Daily temperature range), ETP (Evapotranspiration), SW (Insolation incident on a horizontal surface), n (Actual duration of sunshine) and N (Daylight hours). Identification of mega-environments is critical in enhancing the selection gain, productivity and varietal recommendation. Through envirotyping and genotype main effect plus genotype by environment interaction (GGE) biplot methods, nineteen locations across India were grouped into four mega-environments (MEs). ME1 included five locations viz., Bengaluru, Pune, Dharwad, Kasbe Digraj and Umiam. Eight locations-Anand, Amreli, Lokbharti, Bidar, Parbhani, Ranchi, Bhawanipatna and Raipur were included in ME2. Kota and Morena constitutes ME3, while Palampur, Imphal, Mojhera and Almora were included in ME4. Locations Imphal, Bidar and Raipur were found to be both discriminative and representative; these test locations can be utilized in developing wider adaptable soybean cultivars. Pune and Amreli were found to be high-yielding locations and can be used in large scale breeder seed production.

Improvement of qualitative and quantitative traits in cotton under normal and stressed environments using genomics and biotechnological tools: A review.

Due to the increasing demand for high-quality and high fiber-yielding cotton (Gossypium spp.), research into the development of stress-resilient cotton cultivars has acquired greater significance. Various biotic and abiotic stressors greatly affect cotton production and productivity, posing challenges to the future of the textile industry. Moreover, the content and quality of cottonseed oil can also potentially be influenced by future environmental conditions. Apart from conventional methods, genetic engineering has emerged as a potential tool to improve cotton fiber quality and productivity. Identification and modification of genome sequences and the expression levels of yield-related genes using genetic engineering approaches have enabled to increase both the quality and yields of cotton fiber and cottonseed oil. Herein, we evaluate the significance and molecular mechanisms associated with the regulation of cotton agronomic traits under both normal and stressful environmental conditions. In addition, the importance of gossypol, a toxic phenolic compound in cottonseed that can limit consumption by animals and humans, is reviewed and discussed.

Altered biomass allocation and quality improvement in roots of Indian ginseng Withania somnifera Dunal. Linn. through physiological interventions.

Ashwagandha (W. somnifera Dunal. Linn.), known as Indian ginseng, contains three major bioactive compounds, withaferin-A (WA), 12-deoxywithastramonolide (WO) and withanoloide A (WD). In a field experiment, the impacts of foliar application of growth retardants/promoters was assessed with respect to biomass allocation pattern and major withanoloide content at different phenological stages in W. somnifera. Biomass accumulation pattern showed that foliar application of 500 mg l-1ethrel at 50, 65, 85, 105, and 120 days after sowing (DAS) restricted phenological progression and reduced berry weight by 61% as comparted to the control at 160 DAS. 500 mg l-1 succinic acid foliar application resulted in maximum plant height (56.4 cm), maximum dry stem weight (DWS) and dry root weight (DRW) whereas 500 mg l-1 ethrel had resulted in minimum plant height and DRW at 180 DAS. During last 50 days of crop growth, the accumulation pattern drastically changed with more than 60% of the biomass allotment to the reproductive part, the berries. The WD in roots ranged between 0.325 mg g-1and 0.342 mg g-1 during all growth stages. WA content decreased with increase in progression of crop growth and reached the lowest at 180-190 DAS. In a pot experiment, ethrel application up regulated DWF-5 by 2.44, SQE by 3.79 and CYP450s by 1.17 log2fold in roots 8 h after treatment and succinic acid had up regulated the expression of all these genes by nearly 3 log2fold change. This is in accordance with the withanoloide accumulation pattern in field condition under foliar application of these molecules.