FOREWARNING MODELS FOR PESTS AND DISEASES OF RICE BASED ON CLIMATE FACTORS

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Date
2014
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ACHARYA N.G. RANGA AGRICULTURAL UNIVERSITY
Abstract
The present study “Forewarning models for pests and diseases of rice based on climate factors” was mainly aimed at to study the behavior of climate factors on major pests and diseases of rice, to establish association between climatic factors and pests and diseases of various rice varieties in different years in rice 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 rice varieties with respect to climate factors. The selection of location (Agricultural Research Station, Nellore) for data collection was done on the basis of major rice grown area and also compatibility. The secondary data on major pests (%) and disease(%) incidence of various rice varieties along with climate factors were collected for the period from 2003 to 2013 (11 years ) during crop seasons. The correlation studies were undertaken 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 rice pest and disease incidence. The Logistic models were also used for prediction of the probabilities of occurrence /non-occurrence of pests and disease of rice in standard weeks of rice 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. Finally, Analysis of Variance (ANOVA) techniques applied to test the significance between standard weeks/varieties/years/dates of plantings with respect to pest and diseases of rice. The results revealed that climatic factors from 2003 to 2013 in rice growing seasons the rainfall distribution varied greatly within rice growing seasons over years (10.2 mm – 35.4 mm). The minimum temperatures (220C – 230C), maximum temperatures (280C -300C), morning relative humidity (87-93%) and evening relative humidity (66-72%) were observed. The results revealed that the days with relative humidity (RH) > 92 per cent, temperature (210C - 310C) and weekly rainfall are most critical factors in the development of stem borer incidence, the days with RH > 90 per cent, temperature (210C - 360C) and weekly rainfall are most critical factors in the development of leaf folder incidence and the days with RH > 91per cent, temperature (220C - 310C) are the most critical factors in the development of gall midge incidence. The results revealed that the days with RH > 89 per cent, temperature (200C - 350C) and weekly rainfall are the most critical factors in the development of blast incidence and the days with RH > 91per cent, temperature (200C - 310C) and weekly rainfall are the most critical factors in the development of bacterial leaf blight incidence. Correlation coefficients were computed to ascertain the pattern of relationship between major pests/diseases and climate factors over years (2003-2013) and within year (rice growing seasons) under different rice varieties. Overall for the years 2003 to 2013 the results of correlation studies revealed that, there was positive relationship between the stem borer incidence and climate factors viz., rainfall, maximum temperature, morning relative humidity, evening relative humidity and significant positive relationship with minimum temperature. There existed positive relationship between the leaf folder incidence and rainfall, minimum temperature, morning relative humidity and evening relative humidity and negative relationship with maximum temperature. For gall midge there existed positive relationship with rainfall, relative humidity and negative relationship with temperatures. There results on blast revealed that the positive relationship with morning relative humidity and evening relative humidity and negative relationship with rainfall maximum temperature, minimum temperature. For bacterial leaf blight, among the climate factors minimum temperature exhibited negative association and rest of the climate factors were positively associated while wind velocity imparted significant positive correlation. The results of ANOVA for major pests/diseases established that there was significant variation between the varieties, between the standard weeks and dates of planting . 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 .
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Agricultural Statistics
Citation
162P.
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