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Grapevine stem water potential estimation based on sensor fusion

Noa Ohana-Levi, Igor Zachs,Nave Hagag, Liyam Shemesh,Yishai Netzer

Computers and Electronics in Agriculture(2022)

Cited 6|Views5
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Abstract
•Multiple sensors were used to measure vines with various water stress levels.•Thirty-two daily scale factors were extracted based on the sensor measurements.•Seven factors were selected based on their relations to stem water potential (SWP).•A machine learning model for SWP estimation showed high performance levels.•Daily water stress estimation using sensor fusion approach was verified.
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Key words
Machine learning,Smart irrigation,Vitis vinifera,Deficit irrigation,Water stress
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