Modeling for anthracnose development in mango in relation to weather parameters

Abstract

Mango anthracnose severity on leaves was recorded at 14 day intervals throughout the year 2013, 2014, 2015, 2017 and 2018 on mango cultivar Dashaheri. Logistic model was best for the year 2013, 2014, 2015, 2018 and pooled data of these years had lower mean square error (MSE) 37.67, 91.29, 100.84, 65.80 and 72.32 along with high coefficient of determination (R(Dodd et al. 1991)) 0.753, 0.532, 0.534, 0.656 and 0.606, respectively. Maximum anthracnose development i.e. periodical disease progression (6.9%) was highest from 31st to 33th Standard Meteorological Weeks (SMW) because of cumulative effect of minimum temperature (27 °C) and morning relative humidity (≥ 90%) along with the rainfall (56 mm). Mango anthracnose severity was positively and significantly correlated with the minimum temperature (0.62) followed by rainfall (0.46) on all year pooled data basis, whereas the highest correlation 0.65 was observed for the years 2014 and 2015. The regression model based on pooled data has performed better an alternative regression model of each individual year with the highest adjusted R2 value i.e. 0.747, explaining the effects of minimum temperature, morning relative humidity and rainfall on the anthracnose severity.