FOREWARNING MODELS FOR PESTS AND DISEASES OF GROUNDNUT
Acharya N.G. Ranga Agricultural University
The present study “Forewarning models for pests and diseases of groundnut” was mainly aimed at to study the behaviour of climate factors on major pests and diseases of groundnut, to establish association between climatic factors and pests and diseases of various groundnut varieties in different years in groundnut growing seasons, to generate forewarning statistical models for prediction of major pests and diseases based on climatic factors and also to study the influence of pests and diseases on various groundnut varieties with respect to climate factors. The selection of location (Regional Agricultural Research Station (RARS), Tirupati) for data collection was done on the basis of major groundnut grown area and also compatibility. The secondary data on major pests (%) and disease (%) incidence of various groundnut varieties along with climate factors were collected for the period from 2007 to 2016 (10 years) during crop seasons. The correlation studies were under taken to study the relationship between various pests and disease incidence subject to the climate factors. The Multiple Linear Regression (MLR) models were used for predication of groundnut pest and disease incidence. The logistic models were also used for prediction of the probabilities of occurrence /non-occurrence of pests and disease of groundnut in standard weeks of groundnut growing seasons. The descriptive statistics were used to know the behaviour of climate factors along with pests and disease incidence over years during the crop seasons. Analysis of Variance (ANOVA) techniques applied to test the significance between standard weeks/varieties/years with respect to pest and diseases of groundnut. Finally, markov chain models were used to identifying the presence/absence of pest in consequent days effectively. xvii The results revealed that climatic factors from 2007 to 2016 in groundnut growing seasons the rainfall distribution varied greatly within groundnut growing seasons over years (13.61 mm – 36.06 mm). The average minimum temperatures (21.52°C – 22.03°C), maximum temperatures 31.80°C – 34.75°C), morning relative humidity (73.11 - 83.58%) and evening relative humidity (43.81 - 58.36%) were observed. The results revealed that the days with RH > 78 per cent, temperature (13°C - 42°C) and weekly rainfall are most critical factors in the development of leafhopper incidence, the days with RH > 78 per cent, temperature (15°C - 42°C) are the most critical factors in the development of groundnut leaf miner incidence, the days with RH > 77 per cent, temperature (19°C - 37°C) are the most critical factors in the development of thrips incidence and the days with RH > 77 per cent, temperature (15°C - 43°C) are the most critical factors in the development of root grub incidence. The days with RH > 81 per cent, temperature (16°C - 35°C) and weekly rainfall are the most critical factors in the development of late leaf spot incidence and the days with RH > 82 per cent, temperature (21.2°C - 35°C) and weekly rainfall are the most critical factors in the development of rust incidence. Correlation coefficients were computed to ascertain the pattern of relationship between major pests/diseases and climate factors over years (2007-2016) and within year (groundnut growing seasons) under different groundnut varieties. Overall for the years 2007 to 2016 the results of correlation studies revealed that, there was a positive relationship between the leafhopper incidence and climate factors viz., rainfall, evening relative humidity and sunshine hours. There exist positive relationship between the groundnut leaf miner incidence and maximum temperature, minimum temperature, rainfall and evening relative humidity and negative relationship with morning relative humidity and sunshine hours. For thrips there exist positive relationship with temperatures and wind velocity and negative relationship with morning relative humidity, evening relative humidity, rainfall and sunshine hours. In case of root grub there exist positive relationship with temperatures, rainfall, evening relative humidity, wind velocity and negative relationship with morning relative humidity and sunshine hours. The results on late leaf spot revealed that the positive relationship with temperatures, sunshine hours and the negative relationship with morning relative humidity, evening relative humidity and wind velocity. For rust, among the climate factors evening relative humidity, wind velocity and rainfall exhibited negative association and rest of the climate factors were positively associated. xviii The results of ANOVA for major pests/diseases established that there was significant variation between the varieties, between the standard weeks and over years. The MLR models for within year and between years found to be useful in the prediction of various pests and diseases incidence. The logistic models were found to be useful in the prediction of probabilities for occurrence and non-occurrence of various pests and disease incidence of groundnut. The markov chain models revealed that there was significant change occurring of various pests except root grub in consecutive days for the latest period (2012-16). Further, with the help these models one can predict that the occurring of various pests/diseases of groundnut over the period of time.