Paulo, R.L.; Garcia, A.P.; Umezu, C.K.; Camargo, A.P.; Soares, F.T.; Albiero, D. Water Stress Index Detection Using a Low-Cost Infrared Sensor and Excess Green Image Processing. Sensors2023, 23, 1318.
Paulo, R.L.; Garcia, A.P.; Umezu, C.K.; Camargo, A.P.; Soares, F.T.; Albiero, D. Water Stress Index Detection Using a Low-Cost Infrared Sensor and Excess Green Image Processing. Sensors 2023, 23, 1318.
Paulo, R.L.; Garcia, A.P.; Umezu, C.K.; Camargo, A.P.; Soares, F.T.; Albiero, D. Water Stress Index Detection Using a Low-Cost Infrared Sensor and Excess Green Image Processing. Sensors2023, 23, 1318.
Paulo, R.L.; Garcia, A.P.; Umezu, C.K.; Camargo, A.P.; Soares, F.T.; Albiero, D. Water Stress Index Detection Using a Low-Cost Infrared Sensor and Excess Green Image Processing. Sensors 2023, 23, 1318.
Abstract
So that the levels of water stress are not harmful to the development of the crop and affect its productivity, its detection and monitoring are necessary, and it can occur in different ways. One of them is through the Crop Water Stress Index (CWSI). This index quantifies water stress through the normalization of leaf temperature between the maximum and minimum plant temperatures as a function of evaporation conditions. The responses of a low-cost infrared (IR) sensor were crossed with image processing through segmentation by the Excess Green model to develop a water stress detection system using CWSI. A soil/plant temperature map was generated through a point-to-point scan of the IR sensor. And when it overlaid with a segmented image of the experimental area, only points identified as plants had their temperature values maintained. The Non-Water-Stressed Baseline (NWSB) equation was parameterized for the same conditions of the experiment and external environmental. The experimental area was divided into three different treatments, maintained under stable water conditions throughout the experiment and the system was able to identify stably different stress values between treatments. Although the relationship between crop and environment affected the results, this work showed that using an irrigation system based on CWSI is possible.
Keywords
Water Stress; Precision Irrigation; Non-Water-Stressed Baseline; Soil Moisture; Infra-Red Sensor.
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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