Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/121808
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Type: Journal article
Title: Identification of the most limiting factor for rice yield using soil data collected before planting and during the reproductive stage
Author: Wang, M.
Rengasamy, P.
Wang, Z.
Yang, F.
Ma, H.
Huang, L.
Liu, M.
Yang, H.
Li, J.
An, F.
Li, Y.
Liu, X.
Liang, Z.
Citation: Land Degradation and Development, 2018; 29(8):2310-2320
Publisher: Wiley
Issue Date: 2018
ISSN: 1085-3278
1099-145X
Statement of
Responsibility: 
Ming-Ming Wang, Pichu Rengasamy, Zhi-Chun Wang, Fu Yang, Hong-Yuan Ma, Li-Hua Huang, Miao Liu, Hao-Yu Yang, Jing-Peng Li, Feng-Hua An, Yang-Yang Li, Xiao-Long Liu, Zheng-Wei Liang
Abstract: Soil parameters, measured before crop planting, are typically used to quantify the relationship between soil properties and crop yield and to identify factors limiting crop yield. However, soil properties during sensitive stages of crop growth may have a greater effect on crop yield than the initial values. We determined if inclusion of soil properties, measured during the reproductive stage, could improve the accuracy of crop yield prediction. Classification and regression trees were used to determine the explanatory power of different soil and rice variables for predicting rice yield in alkaline salt‐affected paddy fields in northeast China. The traditional method explained 77.5% of the rice yield variation and identified soil CO₃²⁻ in the 0‐ to 10‐cm soil layer, with single explanatory power of 53.4%, as the most important predictor. The whole explanatory power of the methods including soil variables during the reproductive stage and yield components, with/without soil variables before planting, increased to 81.3%. The residual sodium carbonate, measured in the 0‐ to 10‐cm soil layer during the reproductive stage, was identified as the most limiting factor due to its single maximum explanatory power of 60.5%. We conclude that inclusion of soil properties, measured during the reproductive stage, has potential for improving the rice yield prediction accuracy by enhancing the explanatory power in identification of the most limiting factor. These results encourage further investigation of the role of soil properties during sensitive stages of crop growth in crop yield prediction under different soil and climatic conditions.
Keywords: Classification and regression tree; residual sodium carbonate; rice; salt‐affected soil; soil constraints
Rights: © 2018 John Wiley & Sons, Ltd.
DOI: 10.1002/ldr.3026
Grant ID: 2016YFC0501200
2018YFD02002
KFJ-STS-ZDTP-029
KZCX2-XB2-13
KFJ-SW-STS-141-01
Appears in Collections:Agriculture, Food and Wine publications
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