Author: Mamta*, K.P. Singh and Sharad Pandey
Mango (Mangifera indica L.) is one of the highly demanded fruit in India. However, the crop is vulnerable to numerous diseases at all stages of its development. Among these diseases, powdery mildew caused by Oidium mangiferae is one of the most serious and widespread disease. The purpose of this study was to investigate multiple regression analysis for prediction of powdery mildew in mango. The experiment was conducted on 15 years old plants of twenty cultivars of mango namely Pantsinduri, Dashehari, Amarpalli, Neelum, Hathijhul, Rasgulla, Redtotapari, Langra, Nashpati, Ramkela, Gaurjeet, Golajafrani, Gulabkhas, Gorakhpurlangra, Kalahafus, Karela, Tamancha, Barahmasi, Husnara and Chausa in 2013 and 2014 at Horticulture Research Station (H.R.C.) of G. B. Pant University of Agriculture and Technology, Pantnagar, Distt. Udham Singh Nagar, Uttarakhand. Prevailing weather variables such as temperature, relative humidity and rainfall were obtained corresponding to the mango seasons for both
Mango, powdery mildew, coefficient of multiple determinations R2, Prediction.
The research is very useful for the Mango growers to control powdery mildew of Mango caused by Odium mangiferae. Very little work has been conducted on powdery mildew of Mango. Based on the results obtained in this study one can conclude that the multiple regression analysis for prediction of powdery mildew disease in mango, performed better. The reason for better performance of multiple regression models may be due to consideration of various weather variables. The coefficient of multiple determinations (R2) value of twenty cultivars showed that variation of disease incidence in the development of disease is up to 94% (maximum) in Nashpati and Minimum in Pantsinduri (84%).
-
Mamta, Singh, K.P. and Pandey, S. (2021). Multiple Regression Analysis for Prediction of Powdery Mildew in Mango (Mangifera indica L.). Biological Forum – An International Journal, 13(3): 648-651.