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菜用大豆施肥后荧光、光谱、光合等参数对产量的预测
引用本文:胡志辉,汪艳杰,张丽琴.菜用大豆施肥后荧光、光谱、光合等参数对产量的预测[J].浙江农业学报,2018,30(8):1355.
作者姓名:胡志辉  汪艳杰  张丽琴
作者单位:1.江汉大学 生命科学学院,湖北省豆类(蔬菜)植物工程技术研究中心,湖北 武汉 430056; 2.长江蔬菜杂志社,湖北 武汉 430023
基金项目:湖北省教育厅科研项目(B2017268)
摘    要:以春风极早、M-3、M-4、绿宝石4个菜用大豆为试材,测定了大豆开花期、结荚期、鼓粒期的叶绿素荧光、光谱、光合等参数,并分别与产量进行逐步回归分析,建立开花期、结荚期、鼓粒期回归方程。结果表明,以结荚期各项数据构建的回归方程拟合程度最好,开花期各项数据构建的回归方程拟合程度最差。该模型可作为预测667 m2产量的最优回归模型Y=2 188.289+5 044.333X2+6.804X4-8 916.411X8+14 236.585X10-0.043X12+2 283.778X15。因此,在实际生产过程中,测定结荚期叶片的叶绿素荧光参数、光谱参数、光合参数,代入该拟合方程,可以对菜用大豆的产量进行预测。

关 键 词:菜用大豆  产量  光谱  荧光  光合  逐步回归分析  
收稿时间:2018-02-03

Prediction of vegetable soybean yield with fluorescence,spectra, photosynthetic parameters after fertilization
HU Zhihui,WANG Yanjie,ZHANG Liqin.Prediction of vegetable soybean yield with fluorescence,spectra, photosynthetic parameters after fertilization[J].Acta Agriculturae Zhejiangensis,2018,30(8):1355.
Authors:HU Zhihui  WANG Yanjie  ZHANG Liqin
Institution:1. College of Life Sciences, Jianghan University, Hubei Province Engineering Research Center for Legume Plants, Wuhan 430056, China;
2. Journal of Changjiang Vegetables, Wuhan 430023, China
Abstract:The parameters of chlorophyll fluorescence, spectrum, photosynthesis and yield of four vegetable soybean species of Chunfengjizao, M-3, M-4 and Lvbaoshi were measured at flowering, podding, seed filling stages. And three stepwise regression analysis equations of different periods between chlorophyll fluorescence, spectrum, photosynthetic parameters and yield were performed, respectively. The results showed that the best regression equation was Y=2 188.29+5 044.33X2+6.80X4-8 916.41X8+14 236.59X10-0.04X12+2 283.78X15 at podding period. These results provided some useful value for forecasting yield at an early period. Therefore, in the practical production when these parameters of chlorophyll fluorescence, spectrum and photosynthesis at podding period were determined, the soybean yield could be forecasted by the equation.
Keywords:vegetable soybean  yield  spectrum  fluorescence  photosynthesis  stepwise regression analysis  
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