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 R 2 value i.e. 0.747, explaining the effects of minimum temperature, morning relative humidity and rainfall on the anthracnose severity.

中文翻译：

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与天气参数相关的芒果炭疽病发展建模

在 2013 年、2014 年、2015 年、2017 年和 2018 年全年，芒果品种 Dashaheri 以 14 天为间隔记录了芒果叶片炭疽病的严重程度。Logistic 模型最适合 2013、2014、2015、2018 年，这些年份的汇总数据具有较低的均方误差 (MSE) 37.67、91.29、100.84、65.80 和 72.32，以及较高的决定系数（R(Dodd et al. 1991 )) 分别为 0.753、0.532、0.534、0.656 和 0.606。由于最低温度 (27 °C) 和早晨相对湿度 (≥ 90%) 以及降雨的累积效应 (56毫米）。芒果炭疽病的严重程度与最低温度（0.62）呈显着正相关，其次是降雨量（0.