Omics-driven strategies for integrated insect-pest and disease management

Agriculture is increasingly challenged by insect-pests and diseases that threaten global food security, farmer livelihoods, and ecosystem stability. Conventional management strategies, particularly chemical pesticides, have offered short-term solutions but are constrained for resistance development, environmental contamination, and health concerns. This has created an urgent need for innovative, sustainable, and knowledge-driven approaches to crop protection. In this context, omics technologies, including genomics, transcriptomics, proteomics, metabolomics, biopesticides, microbial consortia and microbiomics, have emerged as transformative tools for integrated insect-pest and disease management (IPDM). Omics approaches offer a comprehensive understanding of biological systems by deciphering host-pathogen-pest interactions. Genomics enables the identification of resistance genes and virulence factors, while transcriptomics reveals dynamic gene expression during stress or infection. Proteomics and metabolomics uncover functional proteins and metabolites involved in defense responses, offering insights into biochemical pathways for crop protection. Microbiomics highlights the role of beneficial microbes in enhancing plant immunity and suppressing pests, opening avenues for bio-based interventions. Integration of omics data supports eco-friendly strategies such as molecular diagnostics for early detection, RNA interference (RNAi)-based pest control, and marker-assisted breeding for resistant varieties. Furthermore, omics-driven insights facilitate the development of biopesticides and microbial consortia that complement traditional IPM practices. Beyond pest control, omics contributes to reducing chemical dependency, enhancing biodiversity, improving soil and water health, empowering farmers with knowledge, and advancing climate-smart agriculture. Thus, omics technologies represent a paradigm shift in insect-pest and disease management, enabling a transition from reactive, pesticide-dependent practices to proactive, knowledge-intensive solutions. Their integration into IPDM frameworks promises resilient crops, reduced ecological footprints, and sustainable food security for future generations

Diversity of insect pollinators in different agro-climatic zones of Haryana

The present study was undertaken to document the diversity of insect visitors on major crops across different agro‑climatic zones of Haryana, India during 2023-24. Observations revealed a rich assemblage of pollinators, with 18 species recorded on mustard, 12 on seed spices, 12 on berseem, and 13 on sunflower. These visitors represented five major insect orders: Hymenoptera, Diptera, Lepidoptera, Coleoptera and Hemiptera. Among them, Hymenoptera emerged as the dominant group across all crops and regions, underscoring the central role of bees in pollination. In sunflower, Hymenopterans alone accounted for 69.23% of total visitors, highlighting their overwhelming contribution. Key pollinators included Apis mellifera, A. dorsata, A. florea and A. cerana, which were consistently observed across crops. Maximum diversity was recorded in agro‑climatic zone II (Hisar region), suggesting that regional floral resources and climatic conditions strongly influence pollinator abundance. Diversity indices further indicated that berseem supported higher species richness and evenness compared to other crops, reflecting its suitability as a forage source for diverse insect groups. Interestingly, non‑bee insects such as flies and butterflies also contributed to pollination, demonstrating the complementary role of different taxa in sustaining crop productivity. The variation in diversity patterns across crops and zones was largely shaped by the availability of floral resources and prevailing agro‑climatic conditions. Overall, the findings emphasize the importance of conserving diverse insect pollinators, particularly Hymenoptera, to enhance pollination services and ensure sustainable agricultural productivity in Haryana’s varied agro‑ecosystems

Tribal livelihood patterns of Dhalai District, Tripura: a geographical study

The present paper is an attempt to explore the influence of physical environment on its habitants (tribals) livelihood patterns on the basis of primary data collected from the households at Longtarai valley sub-division in Dhalai district, Tripura (North-East India). The undulating, hilly and sloppy terrains are used for jhum cultivation and rubber plantation and synclinal valleys are used for agricultural practices. The huge forest cover helps them to practice grazing and pasturing. The hot and humid climate of the study area promotes them to work hard in their own working place. Some of the tribals are dependent on forest-based products for their sustainable livelihoods and others are engaged in piggery, goatery, mushroom cultivation and poultry farming as a livelihood pattern for their survival and existence. The study reveals that the livelihood patterns of the tribals are more or less dependent on its physical environment. The present study winds up with a line that ‘physical environment makes an influence on the livelihood patterns but it is the human who utilizes the physical environment to fulfil their own necessities

Impact of climate-resilient practices FLD on wheat crop productivity in Jhunjhunu District, Rajasthan

The increasing variability of climatic conditions poses a significant threat to the sustainability and productivity of agricultural systems, particularly in arid and semi-arid regions such as Rajasthan, India. This study investigates the impact of climate-resilient agricultural practices on wheat crop productivity in the NICRA (National Innovations in Climate Resilient Agriculture) villages of Jhunjhunu District over the 2022-23 to 2024-2025 Rabi seasons. Climate-resilient practices encompassing water-saving techniques, soil health management, heat/ and stress-tolerant varieties, and integrated nutrient and pest management were systematically introduced and monitored to assess their effects on crop yield and sustainability indicators relative to conventional farming practices. Findings indicate that climate-resilient practices led to a significant improvement in wheat productivity with average yield increases ranging from 15.73% to 18.46% over traditional methods. Economic analysis revealed an increase in net returns per hectare by up to ₹9,000, primarily due to reduced input costs and enhanced yield stability. In addition to yield and economic outcomes, adoption gaps were quantified with the technology gap (17.75 q/ha), extension gap (6.74 q/ha) and technology index (26.79%) in wheat during the respective period of study. The role of the NICRA program in facilitating climate-smart interventions and enhancing community resilience in Jhunjhunu district demonstrates a viable model for replication across climate-sensitive districts

Evaluation of artificial nesting materials for domiciliation of Megachile spp. and their impact on pigeonpea yield

A field investigation was conducted to evaluate the nesting preferences of Megachilid bees and their contribution to pigeonpea yield under artificial domiciliation. Two nesting substrates—Sarkanda sticks (Saccharum spontaneum) and bamboo drilled blocks were monitored at 15‑day intervals. Sarkanda sticks exhibited higher acceptance (4.53%), whereas bamboo blocks remained unused throughout the study. Nesting activity peaked in October 2024 with 21 nests (3.96%), followed by November with 16 nests (3.01%). Four Megachilid species were recorded: Megachile lanata, M. sculpturalis, M. bicolor, and M. disjuncta. Among these, M. lanata was dominant, with activity ranging between 2.19–3.12 individuals per minute per square meter. Diversity indices revealed moderate species diversity (Shannon–Wiener index H′: 1.31–1.34; Simpson’s diversity D: 0.70–0.73) coupled with high evenness (0.94–0.97), indicating balanced species distribution across nesting sites. The impact of domiciliation on crop productivity was evident. Pigeonpea plots with artificial nests recorded significantly higher yields (13.89–14.68 q/ha) compared to control plots without nests (9.47 q/ha). This enhancement underscores the role of Megachilid bees as efficient pollinators, directly contributing to improved seed set and yield. Overall, the study highlights Sarkanda sticks as a suitable substrate for domiciliation of Megachilid bees and demonstrates the potential of managed nesting to augment pollination services in pigeonpea. Adoption of such practices could serve as a sustainable strategy to enhance legume productivity while conserving native pollinator diversity

Effect of sulphur and micronutrient embedded fertilization on growth dynamics of wheat under diverse agroecologies

Supplementation of micronutrients is recognized as essential for improving crop growth in intensive cereal-based cropping systems. A two-location study was conducted during 2023 and 2024 at New Delhi and Karnal to evaluate the effects of sulphur (S) and embedded fertilizers on growth dynamics of wheat. Nine treatments were replicated thrice in randomized block design, with combinations of recommended dose of fertilizers (RDF), S, zinc-embedded S (Zn-ES), multimicronutrient embedded S (MM-ES), farmyard manure (FYM), and microbial consortia. A combination of RDF + S (15 kg ha-1) + Zn-ES (10 kg ha-1) + MM-ES (15 kg ha-1) recorded the highest leaf area index, crop growth rate (CGR), relative growth rate (RGR), and net assimilation rate (NAR). At harvest, dry matter accumulation improved by 14.3% at Karnal and CGR (45-90 DAS) reached 14.1 g m-2 day-1. Integrated sulphur and micronutrient embedded fertilization improves growth dynamics, offering a sustainable nutrient management strategy for wheat

Spatiotemporal analysis of melliferous flora in Madhya Pradesh, India: implications for beekeeping and pollinator support

Madhya Pradesh, in central India, is rich in biodiversity and hosts native honey bee species like Apis dorsata, A. florea, and A. cerana, with diverse melliferous flora offering strong potential for beekeeping. However, regional apiculture varies greatly—for example, migratory beekeeping thrives in Bundelkhand and Chambal valley due to seasonal floral abundance and farmer awareness, while areas like Satpura, despite abundant wild bees, show minimal managed beekeeping, likely due to inconsistent forage availability. This study assesses the composition, diversity, and seasonal dynamics of nectar and pollen sources for honey bees across seven ecogeographical zones of Madhya Pradesh, encompassing both agroecosystems and forest ecosystems. Field surveys, literature reviews, and stakeholder consultations were used to document melliferous flora, and statistical analyses identified regional and seasonal patterns of floral resources. In forest ecosystems of Madhya Pradesh, melliferous plant species richness varied regionally, ranging from 22 species in Satpura to 35 species in Madhya Bharat, with Rewa-Panna and Bundelkhand also showing high diversity (34 species each). Results reveal distinct nectar and pollen availability peaks in regions such as Bundelkhand and Madhya Bharat, favoring stationary or migratory beekeeping, while Satpura and Baghelkhand have lower floral resource density and continuity, limiting apicultural expansion. Seasonal dearths, especially in June and post-monsoon months, highlight critical challenges to colony health and productivity. The study emphasizes the ecological importance of forest flora in supporting both wild and managed bee populations and suggests targeted floral enrichment and migratory strategies to enhance sustainable beekeeping. These findings provide a baseline for region-specific apicultural planning, aiming to improve honey production, pollinator conservation, and rural livelihoods across Madhya Pradesh

Modelling crown diameter for Sal trees (Shorea robusta Gaertn. f.) with an artificial neural network

In recent years, Machine Learning algorithms have been frequently used in forest sciences to build Classification and Regression models. Such algorithms are known for their ability to explore complex relationships between the target variable and multiple predictors with minimum tuning and high accuracy. In this article, an Artificial Neural Network (ANN) was used to develop a Crown Diameter (CD) model for Sal trees based on four predictors, viz., Diameter, Height, Basal Area (BA) and Height-to-Diameter ratio (HDR). Trees were growing naturally in the Ranibagh forest area located at the foothills of the Kumaun Himalaya. Results indicated a good model fit (R2adj. = 0.79), i.e., the model explained 79% of the variation in crown diameter based on four predictors. The Pearson Correlation coefficient (r) value between actual and predicted CD came out to be 0.89 (p< 0.001). The residual plots also indicated homoscedasticity. Mean Absolute Percentage Error (MAPE) for the model came out to be 13.26%. HDR was found to be the most influential predictor for the model, followed by tree height, diameter, and Basal Area. One-way Partial Dependence Plot (PDP) demonstrated that diameter, height and BA had a positive impact on CD. In addition, for HDR, the CD-curve increased up to a certain point with an increase in HDR value and then decreased sharply. Two- way PDP further suggested that HDR in combination with Diameter and BA had a negative influence on crown diameter growth, i.e., HDR had masked the positive effect of diameter and BA on CD. The overall model suggested the competitive nature of Sal trees within a forest stand