Future Projections of Rainfall for Tamil Nadu from Coupled Model Intercomparison Project- 6 (CMIP6)

Precipitation is a crucial input for agriculture and living things in the world, which changes drastically under a warmer climate due to climate change. Hence, the study was carried out to project the changes in annual and seasonal precipitation based on the France Centre National de Recherches Météorologiques (CNRM-CM6) model. In the present study, Coupled Model Intercomparison Project phase six (CMIP6) datasets were used for two SSP scenarios: SSP2-4.5 and SSP5-8.5 and three-time slices for the future viz., near (2021–2050), mid (2051–2080) and end-century (2081–2099) and base period (1991–2020) dataset obtained from the India Meteorological Department (IMD) was used to compare with the future climate over Tamil Nadu. The result revealed that the highest positive mean deviations in annual (81%), SWM (21%), NEM (79%) and summer (163%) were observed in the projected precipitation under the SSP5-8.5 scenario during the Near, mid, near and mid-century respectively. For winter, SSP2-4.5 showed the highest mean deviation of 122% in the near century. According to the three future time scale simulations for the twenty-first century, annual rainfall is predicted to increase by 81% in the near future and 19% in the mid-century, while it is expected to decline by 1.5% at the end of the century under SSP5-8.5. In the SSP2-4.5 scenario, rainfall would increase by 1% in the near future, decrease by 30% in the end century and decrease by 30.5% in the mid-century. From the result, it is concluded that there would be an increase in heavy precipitation occurrences at the near, mid and end of the 21st century under both the SSP5-8.5 and SSP2-4.5 scenarios. These findings might be helpful in framing future agricultural water management regulations to deal with threats from heavy precipitation and researchers to study precipitation changes at the global level.

Effect of Weather Parameters on of Pests and Diseases in Groundnut and Castor in Salem District of Tamil Nadu, India

The roving survey on the incidence of pests and diseases in groundnut and castor was conducted from August, 2020 to March 2021 in Salem district at fortnight intervals revealed that, in groundnut , leaffolder (20.38%), cutworms S. litura (1.63/20 pls), thrips (10.69/20 pls), leaf spot (15.25%) and root rot (6.31%) , similarly in castor pests, whiteflies (23.06/20 pls), A. janata (8.38/20 pls), S. litura (10.19/ 20 pls), thrips (11.63 / 20 pls), C. punctiferalis (7.25/20 pls), alternaria blight (17.56%) and botrytis rot (4.19%) were found feeding /infecting on different parts of the crops. The correlation with weather parameters indicated, positive correlation of rainfall, relative humidity and wind speed on incidence of leaffolder (0.47998, 0.311421 and 0.339961) but rainfall and relative humidity increased root rot (0.433059 and 0.393255) whereas, maximum temperature influenced high infection of leafspot (0.67911) in groundnut. The whiteflies incidence in castor was positively correlated with (0.490967) and rainfall (0.389125) whereas, lepidopteran pests by relative humidity (0.61212) and rainfall (0.49415). The thrips and botrytis rot were influenced by relative humidity and rainfall rot (0.65914 and 0.77965, 0.57456 and 0.82709). But natural enemies in groundnut and castor had non-significant correlation with weather parameters.

Rice Blast Forecasting Using Interval Valued Data at Coimbatore, India

Aims: The persistence of rice blast, caused by the fungus Magnaporthe oryzae, continues to pose a significant threat to rice production worldwide, impacting both yields and food security. The primary goal of this study is to apply interval-valued independent weather data to accurately model the dependent variable of percentage disease incidence.Study Design: In this paper, we present a detailed study on forecasting rice blast outbreaks through the application of Average method, Center method and Min Max method using interval valued weather data and percentage disease incidence.Place and Duration of Study: The blast disease data include percent disease incidence (PDI) collected at the Paddy Breeding Station (PBS), Tamil Nadu Agricultural University, Coimbatore, from 2018 to 2021.And Weather variables includes the following: Maximum Temperature, Minimum Temperature, Relative humidity (morning), Relative humidity (evening) from 2018 to 2021.Methodology: The available interval weather parameter data and disease incidence data are utilized to fit a regression model, specifically employing simple linear regression and multiple linear regression, in the R version 4.3.0.Results: Upon analyzing various methods, it is evident that the variables of Minimum temperature exhibit a significant relationship with a high level of significance, indicating a significance level at P 0.001.Conclusion: Minimum temperature shows more contribution in disease incidence followed by relative humidity at evening.

Assessment of Climate Change Impact and Adaptation Strategies for Rainfed Maize (Zea mays L.)

The study was performed to assess the impact of climate change on spatiotemporal changes in rainfed maize yield. Climate projections data of MIROC-ESM-CHEM model from CMIP6 was used for future climatic scenarios in the maize growing areas of Dindigul and Perambalur districts of Tamil Nadu. The DSSAT model was used to simulate maize yield and evaluate adaptation strategies for base period (1991-2020), the mid (2040-2069) and end centuries (2070-2099) under SSP245 and SSP585 scenarios. The simulation finding shows that, in all scenarios maize yield declined in both Dindigul (7 to 9% and 11 to 12%) and Perambalur (6 to 9% and 11 to 13%) during mid and end centuries respectively from the base period (1991-2020). Following the adaptation strategies such as delayed sowing, the yield was increased in both Dindigul (5 to 6% and 4 to 5%) and Perambalur (4 to 5% and 5 to 6%) with respect to normal sowing date. The results of this study would help in developing adaptation strategies for minimizing the adverse effects of the projected climate in maize-growing districts of Tamil Nadu.

Standardized Precipitation Index Based Drought Assessment over the North Western Zone of Tamil Nadu, India

Drought is a natural disaster that tremendously affect the agriculture production and livelihood. Though the Tamil Nadu state is located at peninsular region of India and contributed from both the monsoons, the frequency of drought is high due to vagaries of monsoonal pattern. A study was conducted at Tamil Nadu Agricultural University to assess the drought characteristics across the north western Agro Climatic Zone (ACZ) of Tamil Nadu using Standardized Precipitation Index (SPI) during the past 30 years (1991-2020). The study clearly indicated that the Salem district had high vulnerability to drought followed by Dharmapuri and Namakkal districts during the South West Monsoon (SWM), whereas the Namakkal had high vulnerability followed by Salem and Dharmapuri during North East Monsoon (NEM).