Usability of monthly ERFS (Extended Range Forecast System) to predict maize yield using DSSAT (Decision Support System for Agro-technology Transfer) model over Erode District of Tamil Nadu

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

Studies on the relationship of weather on Fall armyworm damage in maize (Zea mays L.) under different growing environments

Fall armyworm is a recently occurring invasive pest in India, the most important defoliator causing drastic damage to maize production. Hence, the present study aimed to understand the temporal infestation level of Fall armyworms on maize (Zea mays L.) with weather patterns. Field experiments were conducted during Summer (February-May) and Rainy seasons, 2022 (August-December) at Agro Climate Research Centre, Tamil Nadu Agricultural University, Coimbatore. Three different growing environments (GE1, GE2 and GE3) were created by providing staggered sowing. Regression models were developed for per cent leaf damage against three-days lagged (LT3) and seven-day lagged (LT7) weather variables. Results showed that irrespective of growing environments, weather variables showed negative correlation (Tmax: r = -0.57, -0.81*, -0.31; SSH: -0.30, -0.48, -0.39; Tmean: -0.49, -0.23, -0.30; and SR: -0.48, -0.94*, -0.40) during summer season whereas same variables (i.e Tmax =0.62*, 0.41, 0.33; SSH = 0.09, 0.68*, 0.24; Tmean = 0.29, 0.32, 0.44; and SR=0.13, 0 .67*, 0.26 ) showed a positive correlation with PLD. Rainfall exhibits positive relation (0.06, 0.54, 0.53) and negative correlation (-0.64*, -0.10, -0.02) during summer and rainy season, respectively. Among the regression models, LT7 model had higher R2 (0.65 and 0.76) than LT3 (0.57 and 0.68) during summer and rainy seasons, respectively. These models had good regression values of 0.56 and 0.70 during Rainy and Summer, respectively. It was concluded that Tmax (32.9 °C), Tmin (23.7 °C), Tmean (28.3 °C), RH-I (85.6%), RH-II (56.4%), SSH (4.1), SR (274.6 cal cm-2 m-2), afternoon cloud cover (4.8 okta) and weekly total rainfall (10.2 mm) were very conducive for the greater leaf damage

A Study on Astrometeorological Relationship between Planet Azimuth and Temperature

Temperature is one of the key weather parameters, which is a necessity for all life on Earth. Any variation from the normal can impede the physical, chemical, and biological processes of life. Extremes would produce permanent changes that would halt the plant's growth and may cause complete withering. Advance information on temperature events will be helpful in protecting the plant and sustain the productivity under any temperature related disasters. Astrometeorology is one of the oldest organized knowledge systems that interplay between planetary movement and weather. In Tamil Nadu Agricultural University (TNAU), Astrometeorological weather forecast rules for rainfall, wind speed and cyclone events were already well defined. In continuation of this research, identification of Astrometeorological rules for the temperature events had been taken up during 2021-2022 at Agro climate Research Centre, TNAU, Coimbatore. Hourly temperature data from 2011-2016 was collected for 30 districts of Tamil Nadu. In each districts one particular location is selected and is correlated with ephemeris developed for a particular location using Alcyone ephemeris calculator. The findings clearly demonstrated the differential impact of individual planets and their azimuth on the temperature events. The study revealed that low temperature events were influenced when most planets are away (271- 300 degree azimuth) whereas the high temperature events were influenced by the planets that are directly above the location (91 to 120 degrees azimuth) and the in between temperature events were influenced by both 61-90 and 241-270 degrees. The specific azimuth of the Sun, Mercury, Venus, Jupiter, Saturn, Uranus, and Neptune had a makeable influence on a particular temperature event, however all the azimuths of the Moon and Mars had only a mild effect on any temperature event. Based on the results, Astrometeorological rules for the temperature events could be defined and used for the development of hybrid forecasting by overlapping the astromet forecast output on the numerical forecast output. This will produce more accuracy than individual forecast, reduce missing forecast, falls alarms, and improve the usability of forecast

Effect of Varied Phases of Lunar on the Growth and Yield Parameters of Rice Varieties

Aim: To understand and reason out the effect of lunar phases on the rice crop growth and development. Study Design: Experiment was laid out in Factorial Randomized Block Design. Place and Duration of Study: Field trial was conducted in the wetland farm of Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu during the Navarai season (Dec. 2021 – Apr. 2022). Methodology: Treatment consists of two factors viz., Sowing date (4 Nos.) weekly sowing with respect to lunar phases – New moon, first quarter, full moon and third quarter) and Varieties (4 Nos.) in which two organic (i.e. Kullakar, Karunkuruvai) and two conventional varieties (ADT 43, ASD 16). Normal cultivation practices were followed as per the Tamil Nadu Crop Production Guide 2021. Results: The pooled mean value revealed that the seeds sown at full moon gave significant positive influence on the growth parameters such as plant height, number of tillers, leaf area index and dry matter production compared to other sown dates. Whereas the treatments that had flowering stage synchronized with full moon phase were produced more yield and dry matter content. Conclusion: The rice varieties sown in full moon phase exhibited superior growth on compared to other lunar phases and the treatments had flowering synced with full moon phase resulted with more yield and dry matter production

A Decadal, Temporal and Seasonal Variation of Black Carbon Aerosol at High Altitude Region of Ooty, Tamil Nadu, India

Climate change is accelerating at an unprecedented pace due to escalating greenhouse gas emissions, emphasizing the urgency of understanding its drivers. Aerosols present in the atmosphere, play an significant role in the intricate climate system. In this study, we examine the temporal and seasonal trends of black carbon aerosol, a significant contributor to warming, in the high-altitude locale of Ooty, Tamil Nadu, India. Utilizing the Aethalometer instrument, this research presents a comprehensive analysis of black carbon concentrations over a decade (2013-2023). Observations reveal distinct patterns, with higher concentrations during certain months and seasons. Specifically, April consistently exhibited the highest concentrations, while the monsoon season recorded the lowest. The exceptional decline in 2020, attributed to COVID-19 lockdown measures, highlights the significant role of anthropogenic activities. These findings underscore the significance of proactive black carbon monitoring in regions like Ooty. The study contributes valuable insights into the complex interplay between black carbon aerosols and climate systems, especially in high-altitude environments. It underscores the need for continued research to comprehensively understand black carbon's implications on local and global climate dynamics. In conclusion, this research establishes a foundation for grasping the intricate dynamics of black carbon aerosols in Ooty and serves as a stepping stone for broader insights into their role in shaping climate patterns and effects. By addressing these critical knowledge gaps, we can better inform mitigation strategies and policy decisions aimed at tackling climate change

Implementation of K-Means Clustering Technique in Banana Production of Tamil Nadu, India

Aim: The main objectives of this study are to make use of the K-Means clustering approach to cluster the Banana data and to assist with crop yield prediction. Study Design: One of the methods of Big Data Analytics K-Means clustering is usedto cluster the data set. Place and Duration of Study: So far, the period 2010-2020, time series data were collected from the season and crop report, Directorate of Economics and Statistics, Chennai. Methodology: The horticulture industry has a significant impact on India's economic development. In the globe, after China, India ranks second in terms of fruit and vegetable production. Compare to the various fruits Mango and banana are one of the most abundant fruits in India. So, the Banana dataset were collected and dataset were clustered using the K-Means clustering technique and the optimum number of clusters were identify using the elbow approach. Results: According to these results from this study, there is positive relationship between the Area, Soil moisture, Maximum Temperature, Relative Humidity and negative relationship between Rainfall, Wind Speed and Minimum temperature related Banana production. Using K-Means clustering it divides the given dataset into three clusters in which cluster 3 contains high Banana production afterwards two and one. Conclusion: The selection of the most productive clusters is going to tell farmers on where to focus their efforts while planting crops in order to enhance productivity and crop production

Effect of Microbial Consortium for Nutrient Dynamics and Biological Activity of Paddy Field under insitu Decomposition

The production of rice and rice straw are directly proportional to each other and becomes a  major problem in disposal of rice straw. Though there are many suitable methods in the reduction of rice straw few are bane to environment. Thus this study focuses only on the sustainable and ecofriendly manner of straw disposal. Insitu decomposition of rice stubbles using TNAU biomineralizer is the experimental study which was carried out in randomised block design    with six Treatment and four replications. To determine the most effective methods of managing  rice stubble, nutrient dynamics, and growth parameters of the rice crop, CO 53 variety of short duration was selected and laid down at Tamil Nadu Agricultural University, Coimbatore   from 2021 to 2022. The six treatments includes T1: Stubble (Natural degradation), T2: Stubble+ balancing C:N ratio with urea, T3: Stubble applied with TNAU biomineralizer @ 2kg /ton of residue, T4: Stubbles applied with TNAU biomineralizer @ 2kg/ton of residue +balancing C:N ratio with  urea, T5: Stubbles incorporated in soil using rotavator and applied with TNAU biomineralizer @ 2kg/ton of residue, T6: Stubbles incorporated in soil using rotavator and applied with TNAU biomineralizer @ 2kg/ton of residue + balancing C:N ratio with urea. The study findings showed that incorporation of straw with addition of biomineralizer for decomposition of straw @ 2kg/ton of residue along with balancing C:N ratio urea recorded the highest rice crop growth at harvest stage (115.70cm) and nutrient dynamics (N, P K) of 20.9 %, 4.6 % and 19.2 % higher at tillering stage  and micro nutrients Cu-22.0 %, Zn- 20.9 %, Fe- 2.8 %, Mn- 9.7 % in panicle initiation stage of rice crop

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)

Analysis of Trends in Climate Variables and the Adaptation Strategies Used by Cardamom Growers in Idukki District of Kerala, India

Aim: The study's main goal is to find any significant variations in the climatic variables and to analyze the preferences about adaptation strategies by the farmers to lessen the effects of the same. Study Area and Design: An ex-post-facto study was conducted at randomly selected panchayaths in Nedumkandam, Idukki, Kerala. Methodology: The climate data for 30 years (1991-2021) was analyzed using Mann-Kendall test and sen slope estimator. A sample size of 120 farmers was surveyed for identifying their preferences for adaptation measures. Adaptation strategies proposed by various institutions and experts were ranked using the Response Priority Index. Results: Throughout the july month every year, the maximum temperature rise by 0.06◦C, and this increase is significant at 1% level. The minimum temperature increased considerably by 0.06◦C at 5% level in December and by 0.04 ◦C at 10% level in January. For the month of June, there was a 6.15 mm significant decrease at the 0.01 level of significance. March had a rise in precipitation of 0.753 mm, which is noteworthy at the 0.05 level. The increase in rainfall during summer may increase panicle initiation whereas reduction in rainfall during June affects flowering. At the 0.1 criterion, the increase in May was 2.028 mm, which is considerable. And at the 0.1 level of significance, the relative humidity rises by 0.19% and 0.15%, respectively, in March and May. Fluctuation in these parameters resulted in increased pest and disease incidence. 86.66 % of farmers found it important to adopt adaptation measures. The first listed adaptation measure was maintaining a good level of shade. The least effective of the suggested solutions was growing disease and pest-resistant cultivars. Conclusion: The tests confirmed a shift in climate variables, and it is evident that this change affects cardamom production

Performance of Regional Climate Model (WRF 4.3) in Medium Range Rainfall Forecast (MRRF) for Tamil Nadu, India

The weather events are highly dynamic and fluctuating for the next few days due to enormous processes carried out by nature and physics and it is even more highly variable in tropics. The Medium Range Weather Forecast is incredibly helpful and trustworthy for agricultural purposes and rainfall is one of the most imminent events determining productivity. The Medium Range Rainfall Forecast (MRRF) given by Weather Research and Forecast model (WRF v 4.3) is verified using forecast verification scores including Ratio of Root Mean Square Error (RMSE) to the standard deviation of the observations (RSR), Nash-Sutcliffe Efficiency (NSE), Percent Bias (PBIAS), Kling-Gupta Efficiency (KGE), and Root Mean Square Error (RMSE). Scores were computed by comparing forecast generated using two microphysics options viz., WRF Single Moment scheme (WSM-3) and Kessler scheme during South West Monsoon (SWM) and North East Monsoon (NEM) of the year 2021 for five different physiographic regions of Tamil Nadu. WSM-3 microphysics scheme outperformed in predicting MRRF for all the five regions and during both the monsoons