Prediction of Strawberry Growth and Fruit Yield based on Environmental and Growth Data in a Greenhouse for Soil Cultivation with Applied Autonomous Facilities

• Published in: Weon'ye gwahag gi'sulji Vol. 38; no. 6; pp. 840 - 849
• Main Authors: Sim, Ha Seon, Kim, Dong Sub, Ahn, Min Gyu, Ahn, Su Ran, Kim, Sung Kyeom
• Format: Journal Article
• Language: English
• Published: 한국원예학회HST 01.01.2020; 한국원예학회
• Subjects: 농학; forecast; photosynthetic active radiation; air temperature; smart farming; relative humidity
• ISSN: 1226-8763; 2465-8588
• DOI: 10.7235/HORT.20200076

The ability to predict how well crops will grow and how much fruit they will yield is important forfarmers, consumers, and researchers. Advances in environmental and plant measurement equipmentprovide the opportunity for more data to be collected from plant growing operations, which couldresult in more accurate predictions. The objective of this study was to predict the strawberry growthand fruit yield using environmental and growth data collected with this equipment. The correlationcoefficients of the average daily air temperature and soil temperature data for strawberry growthpredictions were higher than the relative humidity, soil moisture content, electronic conductivity,CO2 concentration, photosynthetic active radiation, and vapor pressure deficit data. The correlationcoefficients of photosynthetic active radiation, vapor pressure deficit, and relative humidity forstrawberry yield prediction were higher than the other environmental data and all growth data suchas plant height, crown diameter, and leaf length and width. The regression model using environmentaldata showed high correlation coefficients with the actual yield data (R2= 0.99). These resultsindicate that strawberry growth and fruit yield could be predicted using environmental data. KCI Citation Count: 21