Order Article Reprints

Sun Q, Zhang Y, Che X, Chen S, Ying Q, Zheng X, Feng A. Coupling Process-Based Crop Model and Extreme Climate Indicators with Machine Learning Can Improve the Predictions and Reduce Uncertainties of Global Soybean Yields. Agriculture. 2022; 12(11):1791. https://doi.org/10.3390/agriculture12111791

Sun, Qing, Yi Zhang, Xianghong Che, Sining Chen, Qing Ying, Xiaohui Zheng, and Aixia Feng. 2022. "Coupling Process-Based Crop Model and Extreme Climate Indicators with Machine Learning Can Improve the Predictions and Reduce Uncertainties of Global Soybean Yields" Agriculture 12, no. 11: 1791. https://doi.org/10.3390/agriculture12111791

Sun, Q., Zhang, Y., Che, X., Chen, S., Ying, Q., Zheng, X., & Feng, A. (2022). Coupling Process-Based Crop Model and Extreme Climate Indicators with Machine Learning Can Improve the Predictions and Reduce Uncertainties of Global Soybean Yields. Agriculture, 12(11), 1791. https://doi.org/10.3390/agriculture12111791