Indian Agricultural Research Institute

The online version contains supplementary material available at 10.1007/s11032-026-01653-w.

While several genome-wide association studies (GWAS) have examined rust resistance in diverse Indian wheat germplasm, none have specifically focused on indigenously bred advanced breeding lines. This study investigates the genetic basis of adult plant resistance to leaf rust and stripe rust in such lines, using a high-density single nucleotide polymorphism (SNP) array and the Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) multi-locus GWAS model, complemented with haplotype-based linkage disequilibrium analysis. Multi-environment phenotyping was conducted across three seasons to capture the effects of environmental variation. The analysis identified 17 and 7 significant SNP-trait associations (Marker trait associations, MTAs) for leaf rust and stripe rust, respectively, including both known and novel loci located on chromosomes 3B, 5B, 7B, and 6 A. These MTAs were found in proximity to well-characterized rust resistance genes such as Lr12/Lr31, Yr27/Lr13, Lr18, Lr52/Yr47, and Yr66, confirming previous reports from gene postulation and marker-based studies. LD-block analysis identified the novel quantitative trait loci (QTLs) qLr.iari.3BL.1, qLr.iari.5BL.2, qLr.iari.7BL.3, and qSr.iari.6AL.1, which exhibited strong phenotypic effects and consistent performance across environments, making them promising candidates for marker-assisted selection. Among these, qLr.iari.3BL.1, flanked by SNP AX-94,715,535, emerged as a stable and widely distributed resistance locus in Indian wheat. The QTLs qLr.iari.5BL.2 and qLr.iari.7BL.3 were detected in two environments and appear to reside in genomic regions with no previously reported resistance genes. The findings underscore the continued breeding value of classical resistance genes (e.g., Lr13/Yr27) and the potential of novel loci for developing durable, rust-resistant wheat varieties adapted to Indian conditions. This first GWAS in Indian-bred wheat lines identifies stable, novel QTLs for rust resistance, enabling marker-assisted selection and accelerating the development of climate-resilient, rust-resistant cultivars for improved food security.

This study examines the relationship between communication apprehension (CA) and communication skill gaps among postgraduate students in higher agricultural education in India. Despite extensive research on communication competencies, limited studies have examined the psychological determinants, particularly communication apprehension, influencing communication skill development. A cross-sectional quantitative research design was employed using the Personal Report of Communication Apprehension-24 (PRCA-24) and a Training Need Index (TNI) to assess communication apprehension and skill gaps among 210 postgraduate students from three leading agricultural institutions. The findings indicate that most students exhibit moderate levels of communication apprehension, with higher anxiety observed in group discussions and interpersonal interactions. Writing and speaking skills emerged as the most critical communication gaps. Regression analysis revealed a significant positive relationship between communication apprehension and communication skill gaps (β = 0.635), suggesting that higher apprehension is associated with greater training needs. Grounded in Communication Apprehension Theory and Social Cognitive Theory, the study highlights the role of psychological factors in shaping communication behaviour. The findings underscore the need for targeted, experiential communication training interventions to enhance communication competence and professional readiness among agricultural graduates.

Sesame (Sesamum indicum L.), an important oilseed crop, requires genetic improvement to ensure food security. Exploitation of a small fraction of genetic diversity is a major limiting factor for this crop. ICAR-NBPGR holds a large sesame base collection (6,000 unique accessions), originating from India and other countries. The study aims at the characterization of a sesame germplasm collection and development of working core set representing the variability of entire germplasm collection in the National Genebank. Characterization was carried out in an Augmented Block Design (ABD) under multi-environmental conditions (six locations representing five agro-ecological zones of India) for two consecutive years based on 33 agro-morphological traits, different levels of biotic stress (phyllody, dry root rot), abiotic stress (water logging, drought), and seed quality parameters (oil, protein, lignan, fatty acids). For core set preparation, the coincidence rate (CR%) for range and the variable rate (VR%) for coefficient of variation were maximum. Levene’s test and Newman-Keuls tests were performed to compare the entire and core collection. Diversity between the two (entire and core collection) was compared using Shannon–Weaver diversity index. We developed a sesame core set of 773 accessions, which consists of 12.88% of the entire collection. Developed core set exhibited a Coincidence rate (CR)% of 99.8% and a variable rate (VR%) of CV 103.59%. A multipurpose core set of sesame germplasm was assembled to benefit the plant breeding community (for trait introgression), farmers, and researchers to develop climate-resilient sesame cultivars.

This study employs a hybrid methodology that integrates a physical process-based radiative transfer (RT) model and machine learning regression to assess three key wheat crop traits: leaf area index (LAI), leaf chlorophyll content (LCC), and canopy chlorophyll content (CCC). The non-imaging hyperspectral data collected proximally using the ASD FieldSpec Spectroradiometer were spectrally resampled to 269 spectral bands ranging from 400 to 1000 nm for the retrieval of these crop traits. Upon validating against in situ measurements, good accuracies in terms of NRMSE values, 10.65%, 11.63%, and 13.85%, were achieved for LAI, LCC, and CCC, respectively.

One of the most serious threats to global crop productivity and sustainable weed management in present scenario is herbicide resistance. Dependency on repeated application of herbicides with similar modes of action, simple cropping systems and reduced diversity among agronomic practices turns out to be major reason for evolution of resistant weed populations across different agroecosystems. Currently, around 260 weed species have been reported to be resistant to one or more site of action, leading to increased yield losses, production cost and environmental concerns. Resistant weed populations usually evolve through different mechanisms such as target-site resistance, which mainly occurs due to genetic mutations at the specific herbicide binding site, and non-target-site resistance, which includes different mechanisms like enhanced herbicide metabolism, reduced translocation or sequestration. To delay or avoid the development of herbicide resistance and restore sustainability we have to implement agronomic mitigation strategies which include crop diversification, cultural and mechanical interventions, use of integrated weed management practices (combination of chemical, cultural, mechanical and biological methods) and precise use and application of herbicides Globally, herbicide resistance has started to become a wide spread problem in controlling the weeds. Studies have reported that resistant weed species can easily cause around 20–70% yield losses, depending on the crop, weed species and infestation level. To delay or avoid the development of herbicide resistance and restore sustainability we have to implement agronomic mitigation strategies which include crop diversification, cultural and mechanical interventions, use of integrated weed management practices and precise use and application of herbicides. It proper and timely solution of this problem is not developed or left unchecked than it can cause uncontrolled losses to crop yield.