Central Sericultural Research and Training Institute

Soil organic carbon (SOC), a major terrestrial C sink essential for climate regulation, has received relatively less attention in mountainous ecosystem research. Insights into altitude-driven variations in SOC are critical for anticipating responses to global environmental change. To this end, we investigated SOC fractions and identified key drivers using generalized linear mixed-effects models across 44 forest plots spanning five altitudinal zones in the Kashmir Himalaya. SOC and associated fractions exhibited a non-linear altitudinal pattern, characterized by consistently higher stocks in Zone II (2107-2406 m) and lower in Zone IV (2707-3006 m). Among the soil parameters, electrical conductivity (EC), bulk density, soil moisture, nitrogen (N), and C: N ratio also varied significantly among zones and soil sampling depths. SOC was predominantly characterized by recalcitrant SOC (C fraction (CF)IV) and passive C pool (PCP), reflecting its potential for C stabilization. The magnitude and direction of all potential drivers are fraction-dependent, with soil moisture and depth being the principal drivers, exerting contrasting effects on very labile SOC (CF I) and active C pool (ACP) storage. In contrast, stem density, EC, and N predominantly determine CF IV and PCP. For labile SOC (CF II), precipitation emerged as the most important predictor. All mono-dominant stands stored significantly higher CF IV and PCP relative to mixed stands, while Cedrus deodara- and Pinus wallichiana-dominated stands exhibited significantly lower less labile SOC (CF III). Our findings demonstrate the pivotal role of analyzing SOC composition and considering fraction-specific stabilization and destabilization processes as indicators of forest condition. Such insights are essential for evidence-based SOC management, conservation strategies, and reliable predictions to protect fragile mountain ecosystems.

The Bundelkhand region is historically more vulnerable to climate change and experienced drought once every 16 years during the 18th and 19th centuries, whereas it increased thrice from 1968 to 1992, and now it has become a recurrent annual phenomenon. The study was conducted from February to June 2023, and primary data from 180 farm households across eight blocks in Banda, Hamirpur, and Mahoba districts of Bundelkhand were collected using a pretested structured interview schedule. The research used the vulnerability analysis method of the IPCC and the climate change vulnerability index of the entire three districts. The results revealed that the “index values” of biological exposition/exposure sub-indicators show that farmers (D3) were highly exposed to climate change with a vulnerability index value of “0.77,” and index values of the Farm susceptibility sub-indicators indicate that farmers (D3) exhibit a high susceptibility to climate change “(0.86),” while index values of the Institutional adaptive capacity sub-indicators indicate that farmers (D1) exhibit a high exposure to climate change, with a vulnerability index of “0.93.” The findings revealed that farmers predominantly adopted strategies such as crop diversification, varietal changes, calendar adjustments, and crop insurance. Binary probit analysis highlighted several significant factors influencing adaptation decisions, including age, education, farm size, access to credit, household size, extension services, and perceptions of changing rainfall and flooding patterns. The findings emphasize the need to strengthen agricultural extension services, enhance credit availability, and improve educational outreach to enable effective, context-specific climate adaptation. The study calls for targeted policy support to boost climate resilience among vulnerable farming populations in Bundelkhand and similar ecologically fragile regions, ensuring their livelihoods remain sustainable amid growing climatic uncertainties.

Maruca vitrata, the legume pod borer, causes yield losses of up to 80% in grain legumes. Increasing insecticide resistance and environmental concerns necessitate sustainable pest management alternatives. In the present study, the complete vitellogenin (Vg) coding sequence (CDS), a key reproductive gene involved in oogenesis and embryonic development, was cloned and molecularly characterised from M. vitrata. The assembled Vg CDS (∼5.3 kb) shared 99.04% sequence identity with the reported M. vitrata Vg sequence (MG799570.1). Phylogenetic analysis demonstrated close evolutionary association with related Lepidopteran species, while protein domain analysis identified three conserved domains, namely LPD_N, DUF1943, and VWD. Among these, the single exon-encoded LPD_N domain was selected as the target region for CRISPR/Cas9-mediated editing. Homology models of Vg and vitellogenin receptor (VgR) (Global Model Quality Estimation (GMQE): 0.58 and 0.51) showed a favourable interaction by protein-protein docking (score: -295.66). Three single-guide RNAs (sgRNAs) were designed, synthesised through in-vitro transcription, and evaluated using in vitro cleavage assays. sgRNA1 targeting the LPD_N domain and sgRNA2 targeting the signal peptide region exhibited efficient site-specific cleavage activity, whereas sgRNA3 failed to induce cleavage because of an unfavourable secondary structure that likely impaired Cas9-sgRNA complex formation. Overall, this study provides the first CRISPR-oriented functional characterisation and sgRNA validation of the M. vitrata Vg gene, together with structural characterisation of VgR and Vg-VgR interaction analysis, providing preliminary molecular resources for future CRISPR/Cas9 studies and supporting future embryo microinjection and heritable genome editing for sustainable management of M. vitrata.

Cotton (Gossypium hirsutum L.) is one of the most important global crops that supports the textile industry and provides a living for millions of farmers. The constantly increasing demand needs a significant rise in cotton production. Genome editing technology, specifically with clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) tools, has opened new possibilities for trait development in cotton. It allows precise and efficient manipulation within the cotton genome when compared with other genetic engineering tools. Current developments in CRISPR/Cas technology, including prime editing, base editing, and multiplexing editing, have expanded the scope of traits in cotton breeding that can be targeted. CRISPR/Cas genome editing has been employed to generate effectively CRISPRized cotton plants with enhanced agronomic traits, including fiber yield and quality, oil improvement, stress resistance, and enhanced nutrition. Here we summarized the various target genes within the cotton genome which have been successfully altered with CRISPR/Cas tools. However, some challenges remain, cotton is tetraploid genome having redundant gene sets and homologs making challenges for genome editing. To ensure specificity and avoiding off-target effects, we need to optimize various parameters such as target site, guide RNA design, and choosing right Cas variants. We outline the future prospects of CRISPR/Cas in cotton breeding, suggesting areas for further research and innovation. A combination of speed breeding and CRISPR/Cas might be useful for fastening trait development in cotton. The potentials to create customized cotton cultivars with enhanced traits to meet the higher demands for the agriculture and textile industry.

Conservation agriculture (CA) presents a promising substitute to the tillage-intensive rice–wheat cropping system (RWS) prevalent in the Indo-Gangetic plains (IGPs). In the northwestern IGPs, on-farm studies examining the impact of CA durations on soil properties and quality are limited. This study assessed the effects of CA practised for 2 (CA2), 4 (CA4), 8 (CA8), and 12 (CA12) years and conventional tillage (CT) on soil quality in the Nilokheri block of Haryana, India. The collected soil samples from 0–5 to 5–15 cm were analyzed for 22 different soil parameters, and a soil quality index (SQI) was developed using principal component analysis (PCA) for each scenario. The results showed that scenarios CA8 and CA12 had 9.8–10.7 and 11.1–11.3% lower bulk density, respectively, compared to CT. Mean weight diameter, saturated hydraulic conductivity, and water holding capacity were significantly higher in CA8 and CA12 over CT at both soil layers. Microbial biomass carbon and dehydrogenase activity increased by 32 and 42.7%, 14.9 and 32.3% in CA8 and CA12, respectively, over CT in the surface soil. Most of the chemical parameters were significantly influenced by CA, except for pH, electrical conductivity, and available Cu. Key soil quality indicators identified through PCA included Ks, WHC, β-glucosidase activity, dehydrogenase activity, available S, available Fe, and available Cu. The highest SQI was observed in CA12, followed by CA8 and CA4, and the lowest in CT at both depths. The derived regression coefficients revealed a strong positive relationship between SQI and both rice equivalent yield and wheat yield. This finding highlights the potential of enhancing soil quality to boost agricultural productivity under CA, thereby fostering sustainable farming. Such improvements are vital for building climate-resilient cropping and supporting the widespread adoption of CA practices. Therefore, it may be concluded that adopting CA for more than 8 years could help restore soil health and sustain productivity in the rice–wheat cropping system of northwest IGPs.