浙江农业学报 ›› 2018, Vol. 30 ›› Issue (8): 1355-1362.DOI: 10.3969/j.issn.1004-1524.2018.08.12

• 园艺科学 • 上一篇    下一篇

菜用大豆施肥后荧光、光谱、光合等参数对产量的预测

胡志辉1, 汪艳杰1, 张丽琴2   

  1. 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
  • 收稿日期:2018-02-03 出版日期:2018-08-25 发布日期:2018-08-28
  • 作者简介:胡志辉(1973—),男,湖北武汉人,副研究员,主要从事植物生理生化教学和研究工作。E-mail: huzhihui@jhun.edu.cn
  • 基金资助:
    湖北省教育厅科研项目(B2017268)

Prediction of vegetable soybean yield with fluorescence, spectra, photosynthetic parameters after fertilization

HU Zhihui1, WANG Yanjie1, ZHANG Liqin2   

  1. 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
  • Received:2018-02-03 Online:2018-08-25 Published:2018-08-28

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

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.

Key words: vegetable soybean, yield, spectrum, fluorescence, photosynthesis, stepwise regression analysis

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