1Regional Agricultural Research Station, Acharya N.G. Ranga Agricultural University, Nandyal-518 503, Andhra Pradesh, India
2Agricultural Research Station, Acharya N.G. Ranga Agricultural University, Utukur-516 003, YSR Kadapa, Andhra Pradesh, India
Agricultural Research Station, Acharya N.G. Ranga Agricultural University, Kadiri-515 591, Sri Sathya Sai, Andhra Pradesh, India
*Corresponding Author: B.H. Chaithanya, Regional Agricultural Research Station, Acharya N.G. Ranga Agricultural University, Nandyal-518 503, Andhra Pradesh, India. Email: bh.chaitanya@angrau.ac.in
Viral diseases are the major constraints in blackgram causing significant yield losses. Among the viral diseases, yellow mosaic virus (YMV) and leaf crinkle are the predominant diseases in the major blackgram growing areas of Andhra Pradesh. The weather parameters play a vital role in development and spread of disease. Therefore, understanding of weather factors and their association with disease incidence is required to provide baseline information for developing a disease prediction system which enables the timely management strategies.
A field experiment in split plot design with three replications evaluated three blackgram varieties (PU-31, TBG-104 and LBG-752) across five sowing dates (October I fortnight to December I fortnight) at Agricultural Research Station, Utukur, YSR Kadapa district of Andhra Pradesh. The standard weekly weather data were correlated with leaf crinkle disease incidence using correlation analysis, multiple linear regression and principal component analysis (PCA) to determine weather-disease relationships.
The significant differences in leaf crinkle disease incidence were observed among the sowing dates and varieties. The lowest disease incidence occurred in October I fortnight sowing (13.4%), while the highest was in December I fortnight sowing (23.0%). Variety PU-31 showed higher incidence (22.42%), whereas TBG-104 recorded lower incidence (16.02%). Highest seed yield was obtained in D2 sowing (1194 kg ha-1). Correlation analysis showed significant negative association of relative humidity with disease incidence. Regression analysis indicated strong influence of weather parameters on disease development (R2: 0.52-0.99). PCA identified temperature and humidity as major factors influencing disease incidence and yield.
Blackgram, Correlation, Leaf crinkle, Principal component analysis, Regression