Weather-Based Neural Network, Stepwise Linear and Sparse Regression Approach for <i>Rabi</i> Sorghum Yield Forecasting of Karnataka, India

Weather-Based Neural Network, Stepwise Linear and Sparse Regression Approach for <i>Rabi</i> Sorghum Yield Forecasting of Karnataka, India

Sorghum is an important dual-purpose crop of India grown for food and fodder. Prevailing weather conditions during the crop growth period determine the yield of sorghum. Hence, the crop yield forecasting models based on weather parameters will be an appropriate option for policymakers and researcher...

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Bibliographic Details
Main Authors: Shankarappa Sridhara, Nandini Ramesh, Pradeep Gopakkali, Bappa Das, Soumya D. Venkatappa, Shivaramu H. Sanjivaiah, Kamalesh Kumar Singh, Priyanka Singh, Diaa O. Al-Ansary, Eman A. Mahmoud, Hosam O. Elansary
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Agronomy
Subjects:
sorghum yield
neural network
LASSO
ENET
weather variables
yield forecasting
Online Access:https://www.mdpi.com/2073-4395/10/11/1645

Internet

https://www.mdpi.com/2073-4395/10/11/1645

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