Background: Cattle husbandry in India is a cornerstone of the agricultural sector, supporting the livelihoods of millions of farmers. However, the industry grapples with challenges such as disease outbreaks, low productivity and limited access to veterinary services. The TNAU Cattle Expert System Application represents a digital innovation aimed at addressing these challenges by providing farmers with real-time guidance on various aspects of cattle management. Methods: The study was meticulously conducted in Tamil Nadu over the years of both 2022 and 2023. Feedback was systematically collected from 523 users of the TNAU Cattle Expert System Application. Text analysis tools were employed to categorize sentiments as positive, negative or neutral using Azure machine learing sotware in MS Excel. Log Regression was carried out to identify the variance of feedback sentiments followed by cluster analysis through jamovi further classified feedback into distinct groups, revealing patterns in user engagement. Result: Positive feedback praised the application’s detailed information on cattle protection and disease precautions, particularly for FMD, BRD, Mastitis, Johne’s disease, Brucellosis, Clostridia diseases and BVD. “Delicate” users (38.54%) gave appreciative feedback, “Arbitrator” users (26.04%) offered diverse opinions, “Eloquent” users (18.75%) expressed positive sentiments, while “Criticizer” (12.50%) and “Harsh stringer” users (4.17%) provided critical insights.

Background: The range of synthetic medications and growth promoters fed to broilers is expensive, negatively impacts the health of the birds and has long-term side effects. Refocusing their efforts, poultry farmers are looking for herbal extracts that have therapeutic properties and may be used safely to boost productivity. This study was conducted to assess the effect of Garlic (Allium sativum), Ginger (Zingiber officinale) and Cinnamon (Cinnamomum zeylanicum) on the growth performance of broiler chickens. Methods: One hundred and forty day old broiler chicks were distributed randomly into seven treatment groups viz., T0 (Control: basal diet), T1 (basal diet + 0.5% Garlic), T2 (basal diet + 0.5% Ginger), T3 (basal diet + 0.5% Cinnamon), T4 (basal diet + 0.25% Garlic + 0.25% Ginger), T5 (basal diet + 0.25% Garlic + 0.25% Cinnamon), T6 (basal diet + 0.25% Ginger + 0.25% Cinnamon) having 70 chicks in each group with 10 replicates. Result: The results (0-6 weeks) of present study indicated that supplementation of 0.25% garlic and 0.25% ginger to the basal diet of broilers (T4) significantly improved overall average daily gain (ADG), better feed conversion ratio (FCR) and broiler performance efficiency index (BPEI) and body weight (BW) of broilers followed by diet supplemented with combination of 0.25% ginger and 0.25% cinnamon (T6) were better than control as well as other groups. Highest profit per bird (Rs. 25.17) and benefit cost ratio (1.59) was observed in T4 followed by T6. It can be concluded that dietary supplementation of garlic (0.25 %) along with ginger (0.25%) has the potential to improve growth performance of broiler chickens.

Background: Groundnut (Arachis hypogaea L.) holds significant importance as a staple food legume and a key economic crop, serving as a valuable source of edible oil and protein in India. However, its full yield potential is often hampered by excessive vegetative growth, which leads to suboptimal yields. With this background, a field experiment was conducted at the Perunthalaivar Kamaraj Krishi Vigyan Kendra in Puducherry during 2020 and 2021. The objective was to investigate the influence of different concentrations and timing of paclobutrazol (PBZ) application on the growth and yield of groundnut. Methods: The experiment was laid out in a split-plot design with three replications, six main plot treatments (Including PBZ concentrations of 25, 50, 100, 150, 200 ppm and a control) and three sub-plot treatments (Involving single sprays at 30 days after emergence (DAE), single sprays at 50 DAE and double sprays at 30 and 50 DAE). Result: The results revealed that the application of paclobutrazol at different concentrations had a positive effect on reducing plant height during the later stages of growth, particularly when a double spray was applied at 30 and 50 DAE. Notably, the application of paclobutrazol at a concentration of 200 ppm in groundnut cultivation proved to be economically viable, resulting 29% increase in pod yield compared to the control group. Specifically, PBZ at 200 ppm, with a double spray, significantly boosted the total pod yield to 2724 kg ha-1. Furthermore, the correlation and regression analyses indicated a positive relationship between growth and yield.

Background: Blackgram [Vigna mungo (L.) Hepper] has significant agronomic and nutritional significance. Its productivity is insufficient to fulfil the expanding local demand in India. Increasing its productivity using appropriate agronomic practices is crucial. With this background, an experiment was conducted to study the effect of foliar application of liquid organic bio-stimulants on development, production and physiological characteristics of blackgram under irrigated conditions. Methods: Seven treatments comprising recommended dose of fertilizers (RDF) with foliar spray of dhasagavya, liquid rhizobium, fish amino acid, panchagavya, PPFM and seaweed extract at 1% and 3%, respectively were tested in randomised block design with three replications. The dimension of blackgram quantitative characters, viz., grain yield, plant height, number of branches per plant, dry matter production (DMP), leaf area index (LAI), number of pods per plant, number of seeds per pod, pod weight per plant, pod length, crop growth rate, total chlorophyll content, soluble protein content and nitrate reductase activity were reduced using principal component analysis (PCA). Result: The PCA was performed on all the attributes as correlation between the quantitative characters was found to be stronger among most of the biometric observations. It was noticed that almost 67% of the data’s total variability, as reflected by the first two principal components. It demonstrated that grain production, DMP, nitrate reductase activity, pods per plant and leaf area index were the primary contributors.

Split plot design experiments were conducted to assess the performance of growth regulating compounds for mitigating moisture stress and the incidence of Brown Plant Hopper (BPH) in rice. The main plot treatments (4) comprised moisture stress free control (M1), moisture stress during panicle initiation stage alone (M2), moisture stress during flowering stage alone (M3), and moisture stress during both panicle initiation and flowering stages (M4). The sub-plot treatments (5) were foliar application of growth regulating compounds including chlormequat chloride at 200 ppm (S1), mepiquat chloride at 200 ppm (S2), brassinolide at 0.1 ppm (S3), pink pigmented facultative methylotrophs (PPFM) at 1% (S4), and no spray control (S5). The reduced plant growth attributes were registered under moisture stress at both panicle initiation and flowering stages. The spraying of 1% PPFM during the flowering or both at panicle initiation and flowering stages led to better performance than the other treatments. Also, spraying 1% PPFM brought down the population of BPH to a considerable level during both years of experiments. This suggests that spraying 1% PPFM in the post-flowering stage helps to mitigate the ill effect the moisture stress and BPH incidence.

Background: Groundnut or peanut (Arachis hypogaea L.) is known as the ‘king’ of oilseeds. It is one of the most important food and cash crop of India. Among different constraints that limit the productivity of groundnut, weed menace is one of the serious bottlenecks. A field experiment was conducted at Perunthalaivar Kamaraj Krishi Vigyan Kendra, Puducherry during 2019 to 2020 to study the tank mix application of post-emergence herbicides for efficient weed control in Groundnut. Methods: The experiment was laid out in randomized block design with 13 treatments and replicated thrice. The treatments consisted of weed management practices viz., pre emergence herbicide pendimethalin and post emergence herbicide viz., imazethapyr, quizalofop-ethyl and those herbicides used either alone or combined with hand weeding once. In addition, hand weedings twice at 15 and 30 DAS were tested with unweeded check. Result: The experiment results of the two years study revealed that the Pendimethalin @ 1.5 kg ai ha-1 (PE) + tank mix of Imazethpyr (40%) + Quizalofop ethyl (60%) at 20-30 DAS recorded maximum plant height (58.17 cm), DMP (36.81 g plant-1), Significantly higher pod yield (3752 kg ha-1), highest net income (₹ 90,762 ha-1) and B:C ratio (2.80). Correlation and Regression analysis also indicated that the yield attributes had a positive impact on groundnut yield.

Background: In India, the dairy business is expanding dramatically. Tamil Nadu milk cooperatives significantly contribute to the growth of the dairy sector in the state. In terms of delivering economic income for dairy smallholders and satisfying customer demand, the identification of milk production is one of the primary financial operations made in India. Considering this, it is crucial to understand future production to enhance and sustain the sector’s growth and development. Methods: The present investigation attempts to predict and forecast milk production in Tamil Nadu using time series models. Yearly milk data from 1976 to 2020 was taken. The study considered Auto-Regressive Integrated Moving Average (ARIMA) and Artificial Neural Network (ANN) to select the appropriate stochastic model for forecasting milk production in Tamil Nadu. Further statistical modeling procedures employed for milk production reveal that the selection of a suitable time series model will always depend on the nature of the data. Result: Results revealed that the ARIMA model is selected as the best model despite ANN, even if it is considered the most powerful model. The CAGR for forecasted milk production from 2020-2025 was 0.02%. Model adequacy criteria like RMSE, MAPE and MAE are used. Based on observation ARIMA model (1, 1, 2) is chosen as the best model over the ANN model.

Background: The productivity of blackgram is not adequate to meet the domestic demand of the growing Indian population. Consequently, there is an urgent need for enhancement of productivity through proper management practices. With this background, a research experiment was conducted to investigate the effect of liquid rhizobium with organic bio-stimulants on physiological and biochemical characters, antioxidant enzymes and yield of blackgram. Methods: A field experiment was laid out in randomized block design with three replications during 2021 (Kharif and Rabi) season. The treatments include 100% recommended dose of NPK along with foliar application of dasagavya, liquid rhizobium, fish amino acid, panchagavya, pink pigmented facultative methylotrophs (PPFM) and Sea weed extract with different concentration (1% and 3%, respectively) in addition to control. Organic bio stimulants were sprayed at 30 and 45 days after the sowing of blackgram. Result: The experiment results revealed that the application of 100% RDF+Liquid Rhizobium @ 1% registered maximum physiological and biochemical characters viz., CGR, total chlorophyll content, soluble protein content, nitrate reductase activity, catalase activity, peroxidase activity and number of root nodules plant-1, yield attributes viz., number of pods plant-1, number of seeds pod-1, grain yield (kg ha-1), haulm yield (kg ha-1). Correlation and Regression analysis also indicated that the yield attributes had a positive impact on the grain yield.

Background: Blackgram [Vigna mungo (L.) Hepper] is one of the most important cultivated legume crops with high nutritive value and agricultural importance. The productivity of blackgram is not adequate to meet the domestic demand of the growing Indian population. Consequently, there is an urgent need for enhancement of productivity through proper agronomic practices. With this background, a research was conducted to investigate the effect of liquid rhizobium with organic bio-stimulants on growth, yield attributes, yield and economics of irrigated blackgram. Methods: A field experiment was laid out in randomized block design with three replications during 2021 (Kharif and Rabi) season. The treatments include 100% RDF foliar application of Dasagavya, liquid rhizobium, fish amino acid, panchagavya, pink pigmented facultative methylotrophs (PPFM) and sea weed extract with different concentration (1% and 3%, respectively) in addition to control. Result: The experiment results revealed that the application of 100% RDF + liquid rhizobium @ 1% recorded higher growth characters viz., plant height (cm), number of branches plant-1, dry matter production (kg ha-1), leaf area index, yield attributes, grain and haulm yield (kg ha-1). Correlation and regression analysis also indicated that the yield attributes had a positive impact on the grain yield.

Pulses are staple protein-rich food for Indian vegetarians, and India is one of the largest producers in the world.Pulse production is influenced by a variety of elements such as rainfall, fertilizer, crop area as well as productivity.Analysis of production behavior, modeling and forecasting of productivity taking all these factors in to consideration play vital roles in human nutritional security.The present investigation is an attempt to predict and forecast the productivity of total pulses in Tamil Nadu using time series data.The present study was carried out to efficiently forecast the productivity of black gram, chickpea, green gram, horse gram, red gram, and total pulses in Tamil Nadu.Yearly data were used for the period from 1970 to 2020.based onthe results of model adequacy criteria, the most suitable ARIMA (autoregressive integrated moving average) model and Holt's Linear Trend model are chosen to capture the pulse productivity.Results revealed that Holt's linear trend model fits best for black gram, chickpea, green gram, and red gram.ARIMA (0,1,1) fits best for horse gram and ARIMA (3,1,0) fits best for the total pulses productivity.The forecasted value of pulses using the bestfitted model shows that there is a steady increase in the productivity of pulses.The productivity of total pulse increases in 2021,2022,2023 but slightly decreases in 2024 and again increases in 2025.This study will play an important role in determining the gap between the productivity of and demand for pulses in the future.

Aims: The main aim of this study is to assess the resource use efficiency and technical efficiency of banana production and to determine factors that influence the technical efficiency of banana production in Tiruchirappalli district of Tamil Nadu. Place and Duration of Study: The study was carried out using the primary data from the sample banana farmers of Tiruchirappalli district from April 2022 – May 2022. Methodology: The Cobb Douglas production function and Stochastic Frontier Analysis was used to find resource use efficiency and technical efficiency of banana production in the study area. Results: The results shows that organic manure, chemical fertilizer, and micronutrient were significant resources. An increase in the usage of these resources will increase the yield, and the other resources which are not significant should be appropriately used to increase the yield. The mean technical efficiency of banana farmers in the Tiruchirappalli district is around seventy per cent, which shows that thirty per cent of farmers were not technically sound. Conclusion: The finding of the study reveals that the good quality suckers and appropriate chemical fertilizers should be incorporated to increase production and productivity. Government should concentrate on extension activities by properly disseminating information to farmers, such as correct production technologies and the required quantities of inputs used, and create awareness about the availability of good quality suckers in the formal institutions.

Dairy farming is the subsidiary occupation for millions of farmers in India. Due to risks and uncertainties in rainfed areas, crop production alone was not much remunerative. Diversifying dairy with the crop and allied activities would generate better income, nutritional security, and regular employment to the farming community and ensure risk reduction. This study investigates the extent and determinants of income diversification among dairy farm households in Tamil Nadu using the Simpson Index of Diversity (SID) and the Tobit regression model. Primary data were collected from dairy farm households during the year 2021-22. The results show that two-thirds of the total household income was shared by on-farm income and the remaining one-third by off-farm and non-farm activities to the total household income. Simpson Index of Diversity (0.38) indicated that the households were diversified with milch animals, but the degree of the diversification was low since high degree of diversification requires more labour and high cost. Further, education, family size, landholding size, herd size, proximity to agricultural or allied industry, access to credit, and membership in farmer producer organizations were the important determinants of income diversification. This study indicates that farm households should adopt a concentric approach that requires targeted research, information dissemination, infrastructure development, and agricultural technical institution establishments to boost income diversification and livelihood.

Dairying has been an important auxiliary enterprise and regular source of income to the farmers. Indian dairy industry has grown commendably with the seven-fold rise in milk output since independence; however, the productivity of the milch animals was relatively low owing to inadequate fodder and inefficient input management. This study investigates the factors influencing milk production under enhanced fodder production in Tamil Nadu using the two-stage least square method. Primary data were obtained from 407 dairy farm households during the year 2021-22. Two models using single-cut and multi-cut fodder were employed to assess the factors determining milk production in dairy farms. The findings of the first stage regression of both models show that fertilizers, seeds, area under fodder, herd size, machinery, farming experience and education were the determinants of the fodder production. In the second stage, factors that influence milk production were fodder, concentrates, herd size, dairy experience, and education. Efficient utilization of feed coupled with concentrates will enhance milk production. The adoption of multi-cut fodder will offer succulent nutrient-rich fodder throughout the year to the cattle, even in the lean season and as a result, it improves the productivity of milk in the dairy farms.

This study employed a comprehensive technique for the systematic estimate of the water balance in Thenpennaiyaru river basin irrigation systems (TRB-IS) in Tamil Nadu, India. KRP reservoir and Sathanur reservoir in TRB are the primary water sources in the study area. We computed the actual water loss in open canals (e.g., leakage and evaporation). A water balance technique provides for the accounting of various system volume inputs (e.g., water abstraction, imported water, water volume owing to precipitation or surface runoff), authorized consumptions, and water losses in canals and intermediate reservoirs. The proposed methodology enables the evaluation of various water loss components (e.g., evaporation losses, unauthorized uses, metering errors, leakage, and discharges) and the calculation of water loss performance indicators that enable the identification of the most significant water loss problems and provide guidance for managing water losses. The approach is evaluated and implemented using a hybrid irrigation system. Results indicate that discharges in canal systems account for over half of the total volume of water loss, followed by leakage in canals and metering problems. These findings emphasize the need to enhance the everyday operation of these systems and restore their infrastructures.

Background: Blackgram [Vigna mungo (L.) Hepper] is one of the most important cultivated legume crops with high nutritive value and agricultural importance. The productivity of blackgram is not adequate to meet the domestic demand of the growing Indian population. Consequently, there is an urgent need for enhancement of productivity through proper agronomic practices. With this background, a research experiment was conducted in a farmer’s field at Pudhupalayam, Coimbatore to investigate the effect of foliar application of PPFM, plant growth regulating compounds and nutrients on growth, yield attributes, yield and economics of irrigated blackgram. Methods: A field experiment was laid out in randomized block design with three replications during 2019 (kharif and rabi) season. The treatments include 100% recommended dose of NPK along with foliar application of diammonium phosphate (DAP), brassinolide (Br), salicylic acid (SA) and pink pigmented facultative methylotrophs (PPFM) with different concentration (1%, 2%, 1 ppm, 2 ppm, 50 ppm, 100 ppm, respectively) in addition to control. PPFM and PGRs were sprayed at 30 and 45 days after the sowing of blackgram. Result: The experiment results of the two seasons study revealed that the application of 100% RDF + PPFM @ 2% recorded higher growth characters viz., plant height (cm), number of branches plant-1, leaf area index and yield attributes viz., number of pods plant-1, number of seeds pod-1, pod weight (g), pod height (cm), 100 seed weight (g) and yield viz., grain yield (kg/ha), straw yield (kg/ha) and harvest index (%). As well as the same treatment recorded higher net return and B:C ratio. Correlation and regression analysis also indicated that the yield attributes had a positive impact on the grain yield with a magnitude of 1.91 and 1.67, respectively. Therefore, application of 100% RDF+2% PPFM spray can be recommended as the best technology to improve the yield and economics of blackgram.