Crop-water assessment in Citrus (Citrus sinensis L.) based on continuous measurements of leaf-turgor pressure using machine learning and IoT

作者：

Highlights：

• An expert system to determine crop ψstem has been defined based on the IoT and machine learning.

• A novel leaf-turgor pressure sensor has been presented.

• A large experiment has been carried out to validate the expert system.

• A crop irrigation-restriction strategy can be implemented from the ψstem predicted.

• The machine learning experiments carried out to obtain the suitable model are described.

摘要

•An expert system to determine crop ψstem has been defined based on the IoT and machine learning.•A novel leaf-turgor pressure sensor has been presented.•A large experiment has been carried out to validate the expert system.•A crop irrigation-restriction strategy can be implemented from the ψstem predicted.•The machine learning experiments carried out to obtain the suitable model are described.

论文关键词：IoT,Machine learning,Expert system,Turgor pressure,Stem water potential,Irrigation scheduling

论文评审过程：Received 22 April 2021, Revised 28 June 2022, Accepted 20 July 2022, Available online 26 July 2022, Version of Record 3 August 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118255