Effects of Environmental Factors of Large-Scale Semi-closed Greenhouse on Growth Characteristics of Tomato

被引：0
作者：
An, Chaehong [1 ]
Park, Sungwan [2 ,4 ]
Seonwoo, Hoon [3 ,4 ]
机构：
[1] Heungyang Farming Assoc Corp, Goheung 59545, South Korea
[2] Sunchon Natl Univ, Sunchon 57922, South Korea
[3] Sunchon Natl Univ, Coll Life Sci & Nat Resources, Dept Convergent Biosyst Engn, Sunchon 57922, South Korea
[4] Sunchon Natl Univ, Interdisciplinary Program IT Bio Convergence Syst, Sunchon 57922, South Korea
来源：
JOURNAL OF BIOSYSTEMS ENGINEERING | 2025年 / 50卷 / 01期
基金：
新加坡国家研究基金会;
关键词：
Semi-closed greenhouse; Tomato; Environmental data; Correlation; Multiple regression analysis; Multicollinearity; FOOD SECURITY; REGRESSION; YIELD;
D O I：
10.1007/s42853-025-00253-4
中图分类号：
S2 [农业工程];
学科分类号：
0828 ;
摘要：
PurposeIn order to improve productivity, it is necessary to analyze and consider the relationships between growth data, environmental data, and various factors collected from smart farms and cultivate under optimal growth environmental conditions. This study aimed to analyze the correlation between tomato growth data and environmental data collected from semi-closed greenhouses, a new type of smart farm, and investigate the impact of each data variable on tomato yield through multiple regression analysis models to establish a foundation for finding optimal cultivation environmental conditions for tomatoes in semi-closed greenhouses.MethodData was collected from two different types of greenhouses: a glass greenhouse with natural ventilation and a semi-closed greenhouse with a forced-air circulation system. The collection periods were 30 weeks for the glass greenhouse and 40 weeks for the semi-closed greenhouse. Nine growth variables and two environmental variables were measured weekly. The collected data was analyzed using correlation analysis and multiple regression analysis with multicollinearity diagnostics to identify significant relationships and interactions between variables.ResultMultiple regression analysis revealed distinct patterns in each greenhouse type. In the glass greenhouse, flowering clusters demonstrated the strongest correlation with fruit yield, while in the semi-closed greenhouse, fruit yield was best modeled using average temperature, stem thickness, and cumulative solar radiation. Multicollinearity diagnostics identified issues with fruit-setting clusters in the glass greenhouse, while the semi-closed greenhouse showed mild multicollinearity issues with cumulative solar radiation. The semi-closed greenhouse was more effective at regulating temperatures than the glass greenhouse due to a combination of factors that facilitated precise environmental control.ConclusionsBased on the research findings, improving model stability requires collecting data on various variables, investigating their correlations, making accurate variable selections, and mitigating multicollinearity issues. These research findings can serve as foundational data for future studies and are expected to contribute to improving agricultural productivity. The semi-closed greenhouse's more complex correlation patterns suggest that it offers greater potential for precise environmental control, but also requires more sophisticated management approaches.
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收藏
页码：105 / 116
页数：12
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