基于氮肥运筹下水稻产量与品质协同的农艺生理指标解析

覃金华, 洪卫源, 冯向前, 李子秋, 周子榆, 王爱冬, 李瑞杰, 王丹英, 张运波, 陈松

Analysis of agronomic and physiological indicators of rice yield and grain quality under nitrogen fertilization management

QIN Jin-Hua, HONG Wei-Yuan, FENG Xiang-Qian, LI Zi-Qiu, ZHOU Zi-Yu, WANG Ai-Dong, LI Rui-Jie, WANG Dan-Ying, ZHANG Yun-Bo, CHEN Song

附图2 不同回归模型对水稻产量和GQI的预测精确度(基于静态指标) A、C、E分别是线性回归、支持向量回归、岭回归模型对水稻产量的预测; B、D、F分别是线性回归、支持向量回归、岭回归模型对GQI的预测。缩写同图6。

Fig. S2 Prediction accuracy of different regression models for rice yield and PC1 A, C, and E represent linear regression, support vector regression, and ridge regression models for predicting rice yield, respectively; B, D, and F represent linear regression, support vector regression, and ridge regression models for predicting grain quality index (GQI), respectively. Abbreviations are the same as those given in Fig. 6.