基于逐步—主成分回归的设施番茄果期生长模型研究

doi:10.13733/j.jcam.issn.2095-5553.2023.09.010

摘要/Abstract

摘要： 为研究日光温室内环境要素对番茄果期生长发育的影响，探究环境要素与番茄果实生长发育的量化关系。基于山东省德州市陵城区糜镇智慧农业产业园日光温室秋冬茬番茄果期生长数据和环境数据，分析数据间的相关性和多重共线性，采用逐步回归和主成分回归组合方法，构建设施番茄果期生长模型。结果表明：果实横径与各环境因子累计量存在较强的线性相关关系，果实横径与各环境因子(空气温度、空气湿度、光照强度、CO2浓度、土壤温度)累计量的相关系数分别为0.96、0.95、0.95、0.94、0.94。温室内环境因子间存在较强的多重共线性，通过逐步回归分析出3个显著环境因子：空气温度、光照强度和CO2浓度。通过主成分回归建立的设施番茄果期生长模型确定系数为0.93，拟合效果较好。

关键词: 设施番茄, 番茄果期, 逐步回归, 主成分回归

Abstract: In order to study the influence of environmental factors in the solar greenhouse on the growth and development of facility tomato during the fruiting period, the quantitative relationship between environmental factors and the fruit growth and development of facility tomato was explored. Based on the autumn and winter tomato fruit growth data and environmental data in the Smart Agricultural Industrial Park, Mi Town, Lingcheng District, Dezhou City, Shandong Province, the correlation and multicollinearity between the data were analyzed, and the growth model of facility tomato in fruit stage was constructed by the method of stepwise regression and principal component regression. The results showed that there was a strong linear correlation between the fruit transverse diameter and the cumulative amount of various environmental factors, and the correlation coefficients between the fruit transverse diameter and the cumulative amount of various environmental factors (air temperature, air humidity, light intensity, CO2 concentration, soil temperature) were 0.96, 0.95, 0.95, 0.94, 0.94, respectively. There was a strong multicollinearity among the environmental factors in the greenhouse, and three significant environmental factors were analyzed by stepwise regression, including air temperature, light intensity and CO2 concentration. The determination coefficient of the facility tomato fruit growth model established by principal component regression was 0.93, and the fitting effect was good.

Key words: facility tomato, tomato fruit stage, stepwise regression, principal component regression

中图分类号:

S641.2

王渊龙, , , 张艳, , , 柳平增, , . 基于逐步—主成分回归的设施番茄果期生长模型研究[J]. 中国农机化学报, 2023, 44(9): 66-71.

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