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Weather based forecasting of sterility mosaic disease in pigeonpea (Cajanus cajan) using machine learning techniques and hybrid models. Indian Journal of Agricultural Sciences 90: 1952–58.

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Title Weather based forecasting of sterility mosaic disease in pigeonpea (Cajanus cajan) using machine learning techniques and hybrid models. Indian Journal of Agricultural Sciences 90: 1952–58.
 
Creator Paul RK, Vennila S, Yadav  SK, Bhat MN, Kumar M, Chandra P, Paul AK and Prabhakar M
 
Subject ANN, ARIMA, Pigeonpea, SMD, SVR, Weather variables
 
Description Modelling incidence of sterility mosaic disease (SMD) on pigeonpea [Cajanus cajan (L.) Millsp.] for four locations
[S K Nagar (Gujarat), Gulbarga (Karnataka), Rahuri (Maharashtra) and Vamban (Tamil Nadu)] was carried out based
on field data sets generated during six kharif seasons [2011-16]. Mean seasonal incidence amongst all locations
was on the decline during recent periods (0.5-5.3%) over past decades (9.8-12.8%). Correlation analyses of SMD
incidence with weather parameters lagged one and two weeks indicated spatial differences for the variables besides
their significance. While Max T (ºC) lagged by one week alone was significantly positive with SMD at Gulbarga
(KA), Vamban (TN) had negative significance of rainfall (mm/week) and rainy days. S K Nagar (GJ) and Rahuri
(MH) had shown opposite effects of both morning and evening RH (%) of both one and two lagged weeks. Support
vector regression (SVR), artificial neural network (ANN) models and their combination with autoregressive integrated
moving average (ARIMA) models applied for prediction of SMD incidence across locations revealed performance
of hybrid models in general to be better based on the evaluation criteria of root mean square error (RMSE). ARIMASVR>
ARIMA-ANN>SVR>ANN was the order of prediction accuracies at S K Nagar (GJ), Gulbarga (KA), and
Vamban (TN). At Rahuri (MH), individual models performed better over their hybrids with ARIMA. While application
of hybrid model of SVR-ARIMA is applicable under situations of SMD seasonal mean severity exceeding 1%, SVR
model proves better for mean seasonal disease incidence in decimal values less than one.
 
Date 2021-03-26T09:04:33Z
2021-03-26T09:04:33Z
2020-01-01
 
Type Research Paper
 
Identifier Paul RK, Vennila S, Yadav  SK, Bhat MN, Kumar M, Chandra P, Paul AK and Prabhakar M (2020). Weather based forecasting of sterility mosaic disease in pigeonpea (Cajanus cajan) using machine learning techniques and hybrid models. Indian Journal of Agricultural Sciences 90: 1952–58.
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http://krishi.icar.gov.in/jspui/handle/123456789/46275
 
Language English
 
Relation 90;
 
Publisher Indian Journal of Agricultural Sciences