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Development and evaluation of ordinary least squares regression models for predicting irrigated and rainfed maize and soybean yields
V. Sharma,
D. R. Rudnick
, S. Irmak
Daugherty Water for Food Global Institute
Research output
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Contribution to journal
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Article
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peer-review
16
Scopus citations
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Dive into the research topics of 'Development and evaluation of ordinary least squares regression models for predicting irrigated and rainfed maize and soybean yields'. Together they form a unique fingerprint.
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Agricultural and Biological Sciences
Cation Exchange Capacity
44%
Evapotranspiration
100%
Irrigated Conditions
11%
Land Resources
11%
Least Square
100%
Resource Allocation
11%
Soil Chemical Properties
22%
Soil Physical Properties
22%
Soil Type
11%
Soil Water
66%
Water Resources
11%
Keyphrases
Actual Crop Evapotranspiration
14%
Food Security Policy
14%
Land Resource Allocation
14%
Maize Yield Prediction
14%
Regional Food Security
14%
Secure Resource Allocation
14%
Soil Water Capacity
85%
Soybean Yield Prediction
14%
Spline Interpolation
14%
Zonal Model
42%