Indian Institute of Rice Research

Genetic diversity within crop germplasm forms the foundation of plant breeding and crop improvement programs. A broad genetic base enhances the probability of identifying genotypes with superior adaptability, stress tolerance, and yield potential. The present study was carried out at Agriculture Research Station, Gangavati during late kharif 2020 to assess variability for yield and its components among 120 rice genotypes maintained at All India Coordinated Rice Improvement Programme, Agriculture Research Station, Gangavathi. ANOVA revealed significant difference for all the characters except panicle length, kernel length and length/breadth ratio. High phenotypic and genetic coefficient of variance was exhibited by plant height, total number of tillers per hill, number of productive tillers per hill, flag leaf length, panicle weight, test weight, total number of spikelets per panicle, number of filled grains per panicle, kernel breadth and yield per plant. High heritability coupled with genetic advance per cent mean was observed for plant height, total number of tillers per hill, number of productive tillers per hill, flag leaf length, panicle weight, test weight, total number of spikelets per panicle, number of filled grains per panicle, panicle fertility, kernel length, kernel breadth, length/breadth ratio and yield per plant.

Reliable estimation of rice yield is essential for food security planning, climate-resilient agriculture, and informed policy decisions. This review synthesizes recent research on the integration of remote sensing and crop simulation models for rice yield estimation. The analysis shows that optical and Synthetic Aperture Radar (SAR) data are the most commonly used remote sensing sources, with SAR proving especially valuable in monsoon-affected regions due to its ability to provide consistent observations under cloud cover. Among crop simulation models, DSSAT, APSIM, ORYZA, and WOFOST are most frequently applied, either independently or in combination with satellite-derived information. Across the reviewed studies, integrated approaches, particularly those using data assimilation and hybrid modeling, consistently achieve higher accuracy and better spatial representation of yield compared to standalone remote sensing or crop model methods. Despite these advances, limitations related to data availability, model calibration, scale mismatches, and climate-induced uncertainty remain significant. Based on the reviewed evidence, future efforts should focus on developing practical hybrid frameworks, improving multi-sensor data fusion, and designing scalable systems suited to data-limited regions. Overall, integrating remote sensing with crop simulation models offers a robust pathway for improving rice yield forecasting and supporting climate-adaptive agricultural management.

Hydrogen gas is naturally produced by microorganisms from renewable feedstocks, yet industrial hydrogenation relies almost entirely on fossil fuel-derived H2. Despite advances in engineering biology and increasing demand for greener manufacturing, microbial H2 has seen limited application in chemical synthesis. Here we demonstrate that genetically unmodified microorganisms can generate H2 in situ to drive biocompatible alkene hydrogenation at the cell membrane using membrane-bound Pd catalysts. When combined with de novo alkene biosynthesis in engineered Escherichia coli, this system enables the simultaneous in vivo production of both substrate (alkene) and reagent (H2), followed by membrane-associated biohydrogenation to yield new metabolic end products. Quantitative life cycle assessment reveals that hybrid chemo-microbial systems utilizing waste feedstocks can outperform electrolytic hydrogenation and achieve carbon-negative outcomes. Together, this work demonstrates how microbial metabolites can be generated, intercepted and metabolically multiplexed to support biocompatible transition metal catalysis and sustainable chemical synthesis in living cells.

The cotton value chain involves various stakeholders, including farmers, ginners, traders, manufacturers, retailers and consumers. Effective management is key to sustaining the industry and ensuring its economic viability. The study explores how stakeholders make decisions, manage operations and respond to market dynamics, regulations, technology and social factors. It also highlights challenges and opportunities for better collaboration. The study conducted in Telangana, randomly selected 120 stakeholders-80 farmers and 40 others. Findings show that Half of the farmers exhibited low management awareness, whereas a majority of other stakeholders (55%) demonstrated a moderate level of awareness. Most profile factors significantly influenced stakeholders’ understanding, with the exception of annual income (multiple linear regression value: 64.25). To ensure long-term sustainability of the sector, the adoption of innovative technologies and efficient resource utilization is imperative. These findings have direct practical implications for strengthening the cotton value chain. The high proportion of farmers with low management awareness indicates the need for targeted capacity-building programmes focusing on managerial skills such as input planning, cost management, quality control, record maintenance and market-oriented decision-making. Extension agencies and KVKs can use these results to design differentiated training modules for farmers and non-farmer stakeholders rather than adopting a uniform approach. The medium level of awareness among other stakeholders suggests scope for improving inter-stakeholder coordination mechanisms, such as structured platforms for information sharing, price discovery and demand forecasting. Since income was not a significant determinant, interventions should prioritise knowledge access, institutional linkages and behavioural change communication over financial incentives alone. Additionally, promoting the adoption of digital tools, traceability systems and innovative technologies can enhance transparency, efficiency, and collaboration across the cotton value chain, thereby contributing to its long-term economic viability.

The present study was conducted at Regional Agricultural Research Station (RARS), Palem, Nagarkurnool, Professor Jayashankar Telangana Agricultural University, Telangana, India during kharif 2023 and 2024 to evaluate plant density and weed management methods influence on soil enzymes activity. High density planting, recorded significantly higher soil enzyme activities (urease, dehydrogenase, phosphatase and β glucosidase activity) at 30, 60 and 90 DAS except at harvest compared to normal planting. Robotic mechanical intercultivation which was on par with weed free recoded significantly higher soil enzymes activity (urease, dehydrogenase and β glucosidase) compared to herbicides application through drone spaying, robotic spraying and manual spraying at 30 DAS. At 60, 90 DAS and harvest the applied herbicide showed no statistically significant effect on soil enzymes activity, during both the years of experimentation.

The brown planthopper, Nilaparvata lugens Stal is a key pest of rice in Asia, causing extensive crop losses and transmitting major viruses. We analysed mitochondrial cytochrome oxidase I (mtCOI) sequences from 63 field-collected samples representing 21 populations across ten states to understand its genetic structure across India’s diverse agroclimatic zones. Our analysis revealed two highly conserved haplotypes, with one major haplotype shared across over 85% of individuals. This consistent haplotype distribution is supported by a TCS network and minimal mutational steps and this reflects strong genetic cohesion across geographically distant populations. Population genetic parameters, neutrality tests, and mismatch distribution patterns support a recent demographic expansion of N. lugens in India. A majority of genetic variation was observed within populations, with only subtle regional differences, as confirmed by AMOVA and phylogenetic tree topology. These results indicate robust gene flow and suggest that Indian populations are highly interconnected, likely facilitated by seasonal migration and shared agricultural practices. Our study offers one of the most comprehensive mitochondrial diversity assessment of Indian N. lugens to date and provides critical genetic benchmarks for future monitoring, resistance management, and predictive modelling of BPH outbreaks in the subcontinent.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-32756-7.

A consistent supply of nutritious fodder is vital for sustaining livestock productivity and reducing dependence on external feed resources. To bridge the fodder deficit, year-round sustainable fodder production systems with efficient nitrogen management are essential for enhancing biomass yield and forage quality. To address this need, the field experiment was conducted during the rabi (October-February), summer (March-May) and kharif (June-October) season of 2023-24 and 2024-25 at the ZARS, V. C. Farm, Mandya, Karnataka. The primary objective of this research was to identify the most productive cereal-legume cropping system with optimizing nitrogen levels, that enhances quantity and quality of biomass production while reducing the gap between the supply and demand of quality fodder throughout the year. Among cropping systems evaluated, Fodder Oats + Cowpea (3:1) - Fodder Sorghum + Cowpea (3:1) - Fodder Maize + Cowpea (3:1) recorded significantly higher green forage yield (977 q ha-1 year-1), dry matter yield (204 q ha-1 year-1), crude protein yield (28.23 q ha-1 year-1), total carbohydrate yield (150.6 q ha-1 year-1), land equivalent ratio (1.34) and economic profitability (B:C ratio 2.81). Likewise, application of 125 % Recommended Dose of Nitrogen (RDN) significantly increased green forage yield (998 q ha-1 year-1), dry matter yield (214 q ha-1 year-1), crude protein content (14.13 %) and profitability (B:C ratio 2.86). Hence, adopting a diverse fodder cropping system integrated with intercrop cowpea in cereal fodder crops and applying 125 % RDN ensures sustainable year-round fodder production with enhanced yield, nutritive quality and profitability, offering viable strategy for livestock-intensive farming.