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Título: | Thermal Imaging for Plant Stress Detection and Phenotyping |
Autor: | Pineda Dorado, Mónica CSIC ORCID ; Barón Ayala, Matilde CSIC ORCID; Pérez-Bueno, María Luisa CSIC ORCID | Palabras clave: | Remote sensing Proximal sensing Thermography Plant phenotyping |
Fecha de publicación: | 2020 | Editor: | Multidisciplinary Digital Publishing Institute | Citación: | Remote Sensing 13(1): 68 (2021) | Resumen: | In the last few years, large efforts have been made to develop new methods to optimize stress detection in crop fields. Thus, plant phenotyping based on imaging techniques has become an essential tool in agriculture. In particular, leaf temperature is a valuable indicator of the physiological status of plants, responding to both biotic and abiotic stressors. Often combined with other imaging sensors and data-mining techniques, thermography is crucial in the implementation of a more automatized, precise and sustainable agriculture. However, thermal data need some corrections related to the environmental and measuring conditions in order to achieve a correct interpretation of the data. This review focuses on the state of the art of thermography applied to the detection of biotic stress. The work will also revise the most important abiotic stress factors affecting the measurements as well as practical issues that need to be considered in order to implement this technique, particularly at the field scale. | Descripción: | © 2020 by the authors. | Versión del editor: | https://doi.org/10.3390/rs13010068 | URI: | http://hdl.handle.net/10261/225776 | DOI: | 10.3390/rs13010068 | E-ISSN: | 2072-4292 |
Aparece en las colecciones: | (EEZ) Artículos |
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Thermal_Pineda_Art2020.pdf | 545,66 kB | Adobe PDF | Visualizar/Abrir |
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