Tamil Nadu Agricultural University

ABSTRACT Brinjal ( Solanum melongena Linnaeus), a solanaceous crop, is consumed globally as a vegetable. Its production is hampered by insect pests. Among them, the brinjal shoot and fruit borer (BSFB), Leucinodes orbonalis Guenee, is a concern as it causes severe yield loss. Reliance on chemical insecticides has led to challenges, including insecticide resistance, environmental contamination, and adverse effects on nontarget insects. This underscores the need for innovative and sustainable pest management methods. Semiochemical‐based strategies, encompassing sex pheromones and other eco‐friendly techniques, offer a promising alternative to reduce dependence on pesticides and minimize the ecological harm they cause. This review highlights recent advances in semiochemical‐based management strategies for L. orbonalis as sustainable alternatives to conventional insecticides.

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.

Conservation tillage has gained momentum as a sustainable alternative to conventional puddling in rice-based cropping systems, particularly in heavy-textured soils prone to structural degradation. The experiment was conducted during 2024-2025 at the Tamil Nadu Rice Research Institute, Aduthurai, to evaluate the impact of various conservation tillage methods on soil physical properties-namely, bulk density, porosity, penetration resistance and grain yield of rice (Oryza sativa L.) across three consecutive cropping seasons. Twelve treatment combinations were evaluated, including transplanted rice (TPR), non - puddled transplanted rice (NPTR) and direct - seeded rice (DSR), each under three fertiliser levels (100 %, 75 % and 50 % of the recommended dose of fertilisers - RDF), with and without microbial consortia (MC) containing phosphate - solubilising bacteria, potassium - releasing bacteria, zinc - solubilising bacteria and Azospirillum spp. The study revealed that conservation tillage with MC significantly influenced soil physical properties and rice yield. T6 (NPTR with 100 % RDF + MC) had the lowest bulk density (1.40 Mg m-3) at the end of the third season, whereas T1 (TPR with 100 % RDF) maintained the highest bulk density (1.53 Mg m-3), indicating less structural improvement. Soil porosity improved across all treatments, with T6 achieving the highest porosity (52.1 %), representing a 12.28 % increase over the initial value. The mean soil penetration resistance at harvest under T6 had the lowest (135 kPa) at 0–20, 20–40 and 40–60 cm depth in all three seasons. Grain yield was significantly enhanced in T6 (6028 kg ha-¹), followed by T2 (5932 kg ha-1) and T10 (5922 kg ha-1). Hence, the integration of MC with reduced tillage offers a viable strategy to improve soil physical quality and nutrient efficiency by supporting long-term agricultural sustainability.

Thrips (Pseudodentrothrips mori) infestation is an emerging constraint in mulberry cultivation, causing subtle yet significant deterioration in leaf quality that adversely affects silkworm growth and cocoon productivity. Early detection of thrips damage using conventional field scouting is difficult due to the inconspicuous nature of initial symptoms. The present study evaluated the potential of hyperspectral radiometry for non-destructive detection and quantification of thrips-induced stress in mulberry (Morus spp.). The present study evaluated the potential of hyperspectral radiometry for detection, discrimination, and quantification of thrips-induced stress in mulberry through band sensitivity analysis, vegetation index sensitivity analysis, regression analysis and linear correlation intensity analysis. Field experiments were conducted in a V1 mulberry garden using naturally infested and protected control plots in Tamil Nadu Agricultural University, Coimbatore during 2018. Spectral reflectance data were collected using a field-portable hyperspectral spectroradiometer (350–1050 nm) at different crop stages, and vegetation indices including NDVI, Simple Ratio (SR), and GRVI were derived. Thrips infestation resulted in increased reflectance in the visible region and reduced reflectance in the near-infrared region, indicating chlorophyll degradation and internal tissue disruption. Vegetation indices were consistently lower in damaged plants compared to healthy plants, with SR and NDVI showing higher sensitivity to thrips-induced stress. Linear regression analysis revealed strong negative relationships between percent leaf damage and NDVI (R² = 0.886) and SR (R² = 0.791), whereas GRVI exhibited poor predictive capability. Linear correlation intensity analysis identified diagnostically important wavelengths, with the highest positive correlation observed at 689.45 nm (r = 0.94) in the red region and the strongest negative correlation at 763.26 nm (r = −0.10) in the NIR region. Overall, the study demonstrates that hyperspectral radiometry combined with correlation intensity analysis and vegetation indices provides a robust, non-invasive approach for early detection and assessment of thrips damage in mulberry, supporting precision pest management in sericulture systems.

Seventeen advanced clones of sugarcane were analysed for variability in yield, yield related traits and quality parameters. There was significant difference in all characters indicating presence of substantial genetic variation except for stalk diameter, single cane weight and juice extraction per cent. Number of millable canes per hectare at 12 months ranged from 114.37 (CoN 18072) to 68.50 (Co 18002). Co 18024 recorded the highest sucrose per cent (20.07) and brix per cent (21.80), both at 12 months. The clone CoN 18072 recorded the highest cane yield (138.10) which was on par with CoTl 25112 (130.27) and CoTl 25111 (129.61). Number of millable canes per hectare at 12 months was highly correlated with number of shoots per hectare at 240 days (0.83). Commercial cane sugar per cent at 12 months was significantly correlated with sucrose per cent at 12 months (0.99) and brix per cent at 12 months (0.96). Commercial cane sugar per hectare showed positive correlation with extraction per cent at 12 months (0.51). Focus on number of millable canes per hectare, commercial cane sugar per cent and commercial cane sugar tonnes per hectare will improve yield and quality traits in sugarcane.

Abstract: JARVIS, a virtual embedded voice assistant that includes cutting-edge technology based on gTTS and Python in developing a personalized assistant. JARVIS integrates the functionality of AIML and, together with Google, the industry leader, a text-to-speech platform and thus male/female voices into the gTTS libraries powered by the Marvel world. This is often the result of adopting the dynamic base Pyttsx3 Pythons considered wise in contiguous phases of gTTS, facilitating the establishment of essentially fine-tuned dialogues between assistants management and users. It will help end users in their daily activities like general human speech, query search in Google, Bing or Yahoo, video search, image retrieval, live weather, word meaning, predict and remind users of scheduled events and tasks. This is often the sole result of over-contributing by multiple contributors, such as AIML’s usability and ability to dynamically merge with platforms like Python [pyttsx] and gTTS [Google Text to Speech] ] results in the same JARVIS standard structure showing general reusability and almost zero or no maintainability. Keywords: Voice Assistant, NLP, Neural Network, Google Search

ABSTRACT Modern fitness centers require efficient digital systems to manage memberships, attendance, payments, trainers, and equipment. Traditional manual and spreadsheet-based methods lead to data inconsistency, revenue leakage, and operational inefficiencies. This paper presents IRONCORE, a full-stack web-based Gym Management System developed using Node.js, Express.js, MongoDB, and Vanilla JavaScript. The system integrates 14 functional modules including member management, attendance tracking, payment processing, analytics reporting, trainer management, and automated membership expiry alerts. JWT-based authentication ensures secure access control. The system follows RESTful architecture and MVC design principles to achieve modularity and scalability. Experimental deployment in a single-gym environment demonstrated improved administrative efficiency and real-time data visibility. Experimental evaluation indicates improved operational efficiency, reduced administrative workload, and stable system performance under concurrent access conditions. Keywords—Gym Management System, Node.js, MongoDB, REST API, JWT Authentication, Web Application, Fitness Automation