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Leaf water content is an important physiological parameter that limits plant growth. It limits photosynthesis efficiency and biomass productivity. Also, it encourages plant diseases and weed growth leading to more of 33% of crop losses in agricultural fields. Tree and crop canopies have to be monitored in order to take important production decisions. Orchard and crops are considering remote sensing techniques for precision agriculture. Moisture sensors can be classified as leaf wetness sensors (LWS) and capacitance sensors. LWS predict fungal crop and tree diseases that appear in the leaves. Capacitance sensors were developed and tested in mango leaves and on ornamental plants variety Codiaeum variegatum sp. grown in the house to measure leaf moisture in situ. The correlation between capacitance leaf moisture and leaf moisture obtained from a laboratory oven was 0.96. Mango leaves were classified in 2 stages the ones in the tree and those that fell to the floor.
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Federico Hahn (2022) studied this question.
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