干旱区生态环境知识资源中心(Arid): Prediction of Water Stress Episodes in Fruit Trees Based on Soil and Weather Time Series Data

Arid

DOI	10.3390/agronomy12061422
	Prediction of Water Stress Episodes in Fruit Trees Based on Soil and Weather Time Series Data
	Gonzalez-Teruel, Juan D.; Carmen Ruiz-Abellon, Maria; Blanco, Victor; Jose Blaya-Ros, Pedro; Domingo, Rafael; Torres-Sanchez, Roque
通讯作者	González-Teruel, JD
来源期刊	AGRONOMY-BASEL
EISSN	2073-4395
出版年	2022
卷号	12 期号:6
英文摘要	Water is a limited resource in arid and semi-arid regions, as is the case in the Mediterranean Basin, where demographic and climatic conditions make it ideal for growing fruits and vegetables, but a greater volume of water is required. Deficit irrigation strategies have proven to be successful in optimizing available water without pernicious impact on yield and harvest quality, but it is essential to control the water stress of the crop. The direct measurement of crop water status is currently performed using midday stem water potential, which is costly in terms of time and labor; therefore, indirect methods are needed for automatic monitoring of crop water stress. In this study, we present a novel approach to indirectly estimate the water stress of 15-year-old mature sweet cherry trees from a time series of soil water status and meteorological variables by using Machine Learning methods (Random Forest and Support Vector Machine). Time information was accounted for by integrating soil and meteorological measurements within arbitrary periods of 3, 6 and 10 days. Supervised binary classification and regression approaches were applied. The binary classification approach allowed for the definition of a model that alerts the farmer when a dangerous crop water stress episode is about to happen a day in advance. Performance metrics F2 and recall of up to 0.735 and 0.769, respectively, were obtained. With the regression approach a R-2 of up to 0.817 was achieved.
英文关键词	crop water stress stem water potential machine learning time series random forest deficit irrigation soil water content soil matric potential
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000816317800001
WOS关键词	SWEET CHERRY TREES ; DEFICIT IRRIGATION ; PLANT
WOS类目	Agronomy ; Plant Sciences
WOS研究方向	Agriculture ; Plant Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/391754
推荐引用方式 GB/T 7714	Gonzalez-Teruel, Juan D.,Carmen Ruiz-Abellon, Maria,Blanco, Victor,et al. Prediction of Water Stress Episodes in Fruit Trees Based on Soil and Weather Time Series Data[J],2022,12(6).
APA	Gonzalez-Teruel, Juan D.,Carmen Ruiz-Abellon, Maria,Blanco, Victor,Jose Blaya-Ros, Pedro,Domingo, Rafael,&Torres-Sanchez, Roque.(2022).Prediction of Water Stress Episodes in Fruit Trees Based on Soil and Weather Time Series Data.AGRONOMY-BASEL,12(6).
MLA	Gonzalez-Teruel, Juan D.,et al."Prediction of Water Stress Episodes in Fruit Trees Based on Soil and Weather Time Series Data".AGRONOMY-BASEL 12.6(2022).