Automatic crop canopy temperature measurement using a low-cost image-based thermal sensor: application in a pomegranate orchard under a permanent shade net house
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Giménez Gallego, Jaime; González Teruel, Juan Domingo; Blaya Ros, Pedro José; Toledo Moreo, Ana Belén; Domingo Miguel, Rafael; [et al.]Área de conocimiento
Ingeniería AgroforestalPatrocinadores
This research was funded by the Agencia Estatal de Investigación (AEI), grant numbers AGL2016-77282-C33-R and PID2019-106226-C22 AEI/10.13039/501100011033; and the Ministerio de Educación y Formación Profesional, grant numbers FPU17/05155 and FPU19/00020.Fecha de publicación
2023-03-08Editorial
MDPICita bibliográfica
Giménez-Gallego, J.; González-Teruel, J.D.; Blaya-Ros, P.J.; Toledo-Moreo, A.B.; Domingo-Miguel, R.; Torres-Sánchez, R. Automatic Crop Canopy Temperature Measurement Using a Low-Cost Image-Based Thermal Sensor: Application in a Pomegranate Orchard under a Permanent Shade Net House. Sensors 2023, 23, 2915. https://doi.org/10.3390/s23062915Revisión por pares
siPalabras clave
precision agriculturedeficit irrigation
crop water stress
Infrared Radiometer
thermography
image segmentation
Resumen
Water scarcity in arid and semi-arid areas has led to the development of regulated deficit
irrigation (RDI) strategies on most species of fruit trees in order to improve water productivity. For a
successful implementation, these strategies require continuous feedback of the soil and crop water
status. This feedback is provided by physical indicators from the soil–plant–atmosphere continuum,
as is the case of the crop canopy temperature, which can be used for the indirect estimation of crop
water stress. Infrared Radiometers (IRs) are considered as the reference tool for temperature-based
water status monitoring in crops. Alternatively, in this paper, we assess the performance of a low-cost
thermal sensor based on thermographic imaging technology for the same purpose. The thermal
sensor was tested in field conditions by performing continuous measurements on pomegranate trees
(Punica granatum L. ‘Wonderful’) and was compared with a commercial IR. A strong correlation
(R2 = 0.976) ...
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