FOREWARNING MODELS FOR PESTS AND DISEASES OF GROUNDNUT
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Date
2017
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Acharya N.G. Ranga Agricultural University
Abstract
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.
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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.
Description
D5486
Keywords
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