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Background: Groundnut (Arachis hypogaea L.), a globally prominent oilseed crop, is experiencing significant losses due to the Groundnut Bud Necrosis Virus (GBNV). The extended range weather forecast (ERWF) provides timely weather information and protects crops from weather-induced biotic and abiotic risks. Methods: An ERWF-based GBNV disease forewarning study was conducted at Coimbatore, Tamil Nadu in 2023 and 2024. The ERWF output from Weather Research and Forecasting (WRFv4.4) with two microphysics (WSM3 and Kessler) were leveraged to forewarn the GBNV disease, using the thumb rule as adapted in Tamil Nadu Agricultural University-Agro Advisory Service (TNAU - AAS): Web cum Mobile App, which is maximum temperature (>33oC), relative humidity (40-70%), wind speed (>5 kmph) and rainfall (0 mm). Result: Among the two microphysics options, the WSM3 performed better and provided more usable ERWF than the Kessler scheme. The WSM3 based ERWF usability percentage was 50 to 100 for rainfall and 80-100 for all other weather variables. The higher performance of ERWF resulted in a more precise forewarning of thrips and GBNV. The first and peak activity of thrips and GBNV incidence was well correlated (70-80%) with the ERWF based forewarning. [ABSTRACT FROM AUTHOR]

Adaptability and significant economic value of the neem tree are well-known, as it can flourish in a variety of environmental conditions. While the neem seed production is highly sensitive to prevailing weather conditions during the reproductive phase and flowering behaviour of the tree. A study was conducted at Tamil Nadu Agricultural University, Coimbatore in 2023 with the primary objective of validating the weather influence on neem seed production using the logics of physiological responses, as a continuation of research conducted the previous year (2022). During the pre-flowering and flowering stages, diverse weather conditions led to notable changes in the physiological traits of neem trees, which displayed varying patterns of flowering. Trees that flowered consistently showed elevated levels of indole acetic acid (IAA) oxidase, relative water content, and nitrate reductase compared to those that lacked flowers or produced intermittently. In the flowering stage, the neem trees responded positively in terms of physiological aspects like IAA oxidase, relative water content, nitrate reductase, and exhibited lower proline levels, which can be attributed to the optimal maximum temperature, rainfall, and soil moisture. Proline levels rose during the pre-flowering stage due to soil moisture deficits but fell during the flowering stage with the onset of rain. These physiological changes, driven by climatic factors, are likely to enhance the flowering, fruiting, and overall yield of neem trees. [ABSTRACT FROM AUTHOR]

Background: In peninsular India, the frequency of climate-related risks is significantly lowering agricultural productivity and farmers' standard of living. Reducing losses in the agriculture sector requires precise and timely weather information, weather based advisories on crop production, protection and post-harvest. Disseminating agromet advisories directly to the farmers using ICT tools allows farmers to adopt appropriate corrective measures, minimize loss and ensure climate resilient agriculture. In this sense, the Tamil Nadu Agricultural University established an Automated Agromet Advisory Web cum Mobile App (TNAU-AAS) in 2018, which sends location, crop and stage specific agromet advisories directly to farmers' mobile App. Methods: TNAU-AAS App was evaluated in pulse crops as "Piloting pulse produce support system through ICT enabled services" between 2019 and 2021 in three TNAU centers under three different eco systems namely irrigated (Coimbatore), rice fallow (Aduthurai) and rainfed (Kovilpatti). Pulse growing farmers were registered in this smartphone application for agromet advisory based response farming. Result: The TNAU-AAS App had delivered approximately 10-12 advisories to each farmer, tailored to their unique crop and stage during the cropping period. Survey results inferred that the farmers received timely notifications on their mobile phones, 2-3 days in advance, which assisted them in preplanning. Occurrences of pests and diseases were well aligned (68-83%) with TNAU-AAS recommendations and the climate vulnerability of non AAS farmers is more than AAS farmer. According to partial budget analysis, the irrigated, rice fallow and rainfed black gram farmers have gained Rs. 2800, Rs. 2300 and Rs. 1900 per ha, respectively. It is concluded that the ICT-enabled agromet advisory system guarantees timely alerts, boosts labor and land productivity, lowers input loss and shields crops from weather-induced pests and diseases as well as climatic variability risk. [ABSTRACT FROM AUTHOR]

Background: Nitrogen plays a crucial role in growth cycling and development, thereby influencing the plant growth and productivity. Understanding the interactions between nitrogen uptake with different irrigation regimes and source of nitrogen fertilizers could provide a valuable insight for optimizing tomato production. Hence, this study aimed to investigate the effect of nitrogen uptake on tomato production under different nitrogen fertilizer and irrigation regimes. Methods: The field experiment was carried out during 2022-2023 in split plot design with two irrigation main plots treatments and five different nitrogen fertilizer subplot treatments. Irrigation treatments consisted of 0.8 and 1.0 IW/CPE ratio and the nitrogen fertilizer treatments comprised of conventional urea, neem coated urea, ammonium sulfate, nano-urea and vermicompost. Result: A higher nitrogen uptake was observed in the treatment combination of 0.8 and 1.0 IW/CPE ratio with vermicompost and nano-urea fertilizer applied treatments. Additionally, optimal irrigation conditions positively influenced nitrogen uptake and subsequent tomato fruit yield. This finding emphasizes the importance of considering nitrogen uptake when determining nitrogen fertilizer rates and irrigation management strategies for tomato production. [ABSTRACT FROM AUTHOR]

The present investigation to determine the effect of date of sowing and crop geometry against fall armyworm (FAW) damage in maize was conducted in TNAU, Coimbatore during the Summer and Rainy seasons using three different crop geometries as precision farming (75 x 25 cm), TNAU recommended spacing (60 x 25 cm) and farmer's practice (45 x 25 cm) in three sowing windows. Among sowing windows, the crop grown in 12th standard meteorological week (SMW) was associated with the highest levels of leaf damage of 11.16, 71.0, and 50.71 per cent recorded at 16, 30, and 60 days after sowing (DAS), whereas the crop sown in 7th SMW experienced the least damage (8.32% at 16 DAS, 23.01% at 30 DAS, 31.71% at 45 DAS, and 22.96% at 60 DAS) and the intermediate damage occurred in 9th SMW in the summer season. Contrarily, during the rainy season, the highest leaf damage occurred in crop sown at 34th SMW (26.20, 46.87 and 30.0 per cent at 30, 45, and 60 DAS, respectively) and the lowest leaf damage of 3.50, 13.01, 27.34 and 17.83 per cent recorded at 16, 30, 45 and 60 DAS, respectively for 39th SMW sown crop. The 37th SMW sown crop exhibited intermediary damage. Among the altered cropping geometries wider spacing (75 x 25 cm) between rows has lesser leaf damage in contrast, dense arrangement (45 x 25 cm) created a favourable microclimate for fall armyworm infestation and 60 x 25 cm has an intermediary infestation with the highest grain yield among the cropping geometries. So, the planting geometry 60x25 cm may be adopted as one of the cultural practices in the integrated pest management of maize considering both yields as well as FAW damage. [ABSTRACT FROM AUTHOR]

Extended Range of Forecast Service (ERFS) is highly useful for planning of cropping season and midterm correction at the farm level. The medium-range and long-range forecast validation have many studies, whereas ERF has less that needs to be studied. Maize is an important field crop in India after rice and wheat. Therefore, the prediction of maize yield has significant importance. In the present study, ERFS data were validated by correlation analysis using monthly observed rainfall frequency and intensity. This data was imported to DSSAT (Decision Support System for Agro-technology Transfer) to simulate maize yield of Erode district of Tamil Nadu. The model output and actual yield data from Erode were compared. Forecasted monthly total rainfall was correlated at a rate of 0.97r value with that observed. Yield simulation of maize was done using DSSAT by integrating ERFS data and the observed monthly data. Mean per cent deviation among the yields of observed weather and the disaggregated one tended to be -15.7 %. The average deviation between the yields of ERF forecasted weather data and actual yield was very high (-29.7 %) for Erode. Mean % deviation between the yields of observed weather and the actual yield was - 14.7 %. Downscaled and accurate weather forecasts could be facilitated for yield prediction of crops by DSSAT model. Yield prediction by the model under observed weather was convenient and usable. Model under-predicted the yields when using ERF data. Both model and ERF forecast need to be improved further for higher resolution. [ABSTRACT FROM AUTHOR]

Astrometeorology is a great science and gift from our ancestors known to humankind. Compared to statistical and numerical methods of forecasting, astrometeorology method has no time restrictions and weather could be forecasted for the next hour to a date far in the future. Wind speed is the weather parameter plays an important role in crop production. A study on the relationship between the wind speed events and the planet's azimuth was conducted at Tamil Nadu Agricultural University during 2017-18 as a part of the formulation of astrometeorological rules for wind speed events. Hourly wind speed observed between 2011 and 2016 from each one location from 31 districts of Tamil Nadu were correlated with the ephemeris developed for the same period in Alcyone ephemeris calculator. It could be concluded from the correlation study on individual planet azimuth and wind speed events that the azimuth range of 61 - 120 of all the planets and 240 - 300 had a good influence on wind speed. The 61 - 90 degrees azimuth of the Sun, Mercury, Saturn and Neptune had good influence on calm to light air wind speed events (0 - 12 km). The 91 - 120 degrees azimuth of all the planets had influenced moderately to heavy wind (19 - 45 km/hour). The Moon, Mars, Jupiter, and Neptune at 60 - 90 degrees azimuth had influenced the extreme wind speed events. The Moon, Mars and Saturn at 271 - 300 degrees azimuth had influenced the moderate to heavy wind (19 - 45 km/hour). [ABSTRACT FROM AUTHOR]

Weather Research and Forecasting (WRF) model is a numerical weather prediction system and having wide range of applications. It offers multiple physics options that could be combined in any way to improve the accuracy of forecast suitable to particular region. Each physics option has it's own individuality and no single scheme could perform better in all locations. In this context, a study was carried out to identify the best WRF microphysics scheme for improvingmedium range rainfallforecastissued by Tami Nadu Agricultural University at block levelforTamil Nadu. Based on the review of previous studies, the present study was restricted to three microphysics options which are suitable for tropical conditions viz. Kessler scheme, WSM3 and WSM6 class schemes. Forecast wasdeveloped daily at 3 km resolution with a lead time of six days for 32 locations of Tamil Nadu and for the first fortnight of November 2017. The simulated forecast values were verified with the observed data collected from the Automatic Weather Stations of TamilNadu Agricultural Weather Network (TAWN) using skill score and root mean square error verification methods. Input data resolution and microphysics option had huge impact on model performance. Data resolution of 0.25 degree performed better than 0.50 degree in all microphysics schemes considered for the study. Among the three microphysics options, the Kessler scheme had higher rainfall forecast accuracy than WSM 3 class scheme and WSM 6 class scheme. Root mean square error was also low in Kessler scheme compared to other two schemes. Kessler scheme produced highly usable forecast than WSM 3 and 6 class schemes. Hence, it is concluded that the Kessler scheme with 0.25o input data resolution produced higher rainfall forecast accuracy for Tamil Nadu region. [ABSTRACT FROM AUTHOR]

Among the pulses, bengal gram (Chickpea) has been considered for the present study in the scenario of uncertain monsoon behaviour where it is an excellent crop benefiting the farmers since its ability to withstand drought condition with lesser rainfall. The present study was under taken intentionally to assess the trends in area, production, productivity and Efficient cropping zones (ECZ) of the emerging pulse crop (Bengal gram) of Tamil Nadu, to identify and analyse the factors influencing the area, production and productivity of bengal gram as well as to key note the available niches over the state (Tamil Nadu). The zones were identified for latest 10 year average (2005-2014). The trend analysis was carried out for 1950-2014, 1950-1979 and 1980-2009 and at decadal scale for state level. The results showed that the trend in area, production and productivity were increasing with the new technologies that could further extend the crop over the efficient cropping zones. The compound growth rate of 2.44 per cent per annum over Tamil Nadu during the time period of 1950-2014 could be achieved as a whole. Coimbatore, Tiruppur, Dindigul and Dharmapuri districts of Tamil Nadu during the latest ten years, 2005 to 2014 were found to be the efficient cropping zones for bengal gram from this study. [ABSTRACT FROM AUTHOR]

A field experiment was conducted at Tamil Nadu Agricultural University, Coimbatore during late Samba season (2017-18) to study the effect of varieties and methods of planting on productivity of organic rice. The experiment was laid out in split plot design with three replications. Four varieties (V1 - Rice CO-52, V2 - Jeeraga samba, V3 - Kitchili samba and V4 - Improved white ponni) were grown in main plot and three planting methods (P1 - Random planting, P2 - Line planting and P3 - SRI method) were allotted to sub-plots. The experimental results revealed that Rice CO-52 registered lesser plant height (113.2 cm), higher drymatter (10330 kg ha-1), LAI (4.70), total number of tillers (441/m²), number of productive tillers (394/m²), total number of grains and filled grains, grain yield (3780 kg ha-1) and harvesting index. Among methods of planting, SRI method of planting registered higher growth characters, yield attributes and yield of rice than other methods of planting. Hence, it is inferred that SRI method enhanced productivity of rice under organic farming. [ABSTRACT FROM AUTHOR]