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- W4312699047 abstract "Under the conditions of growing crops in plant factories, timely information about the physiological state of plants makes it possible to maintain crop yields at a high level. In crop production, non-invasive methods of plant diagnostics are most widely used, which helps identify plant stress conditions at an early stage. In the theoretical study applied to plant factories, the authors compared electrophysical monitoring methods (the measurement of biopotential and bioimpedance), thermography methods (the method of registration of xylem sap fl ow and infrared thermography), optical methods (the measurement of refl ective characteristics of leaves, hyper- and multispectral imaging), and the method for measuring chlorophyll fl uorescence. The studied methods were classifi ed and analyzed according to several criteria: measurable indicators, the assessment of plant parameters, the portability of the measuring instrument, the ability to scan at the canopy level. It was concluded that non-invasive methods for diagnosing the physiological state of plants are capable of signaling negative changes at an early stage, provide for indirect assessing plant stress, transpiration, photosynthesis, pigment and elemental composition, and the electrical resistance of tissues. Among the technologies for non-invasive diagnostics of the physiological state of plants for closed regulated agroecosystems, the method of spectral analysis of plant leaves, in particular, spectral visualization, and the fl uorescence method are particularly eff ective. In further studies to evaluate photosynthesis and compose “light recipes”, the authors are planning to compare the fl uorescence method and the spectral imaging method in practical conditions" @default.
- W4312699047 created "2023-01-05" @default.
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- W4312699047 date "2022-01-01" @default.
- W4312699047 modified "2023-10-14" @default.
- W4312699047 title "SCREENING IN PLANT FACTORIES: A REVIEW OF NON-INVASIVE PLANT MONITORING TECHNIQUES FOR CLOSED REGULATED AGROECOSYSTEMS" @default.
- W4312699047 doi "https://doi.org/10.26897/2687-1149-2022-6-70-75" @default.
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