Thermal Imaging Techniques in Agricultural Applications

The effects of plant diseases on agricultural production worldwide contribute to significant economic and post-harvest losses. To maintain the sustainability of the farming sector, the early detection of plant and pathogens is essential. Non - destructive methods for tracking the health conditions of plants in real-time applications are among the most realistic and feasible in this regard. Owing to non - destructive methods and non - contact measuring devices, thermal imaging advancement has become an essential technique in all fields. Thermal imaging operates by emitting infrared irradiation in all materials. The method, therefore, uses radiation to create an image of the thermal distribution of the body surface. This approach is useful for all areas where the difference in temperature helps in the area/object analyses. Therefore, this paper briefly explores the potential for thermal imaging to be used to detect plant disease in the control area and the field.

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Disease detection in banana trees using an image processing-based thermal camera

Setyawan

Anasta

Fitriawan

2021

IOP Conf. Ser.: Earth Environ. Sci.

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Banana is a fruit plant that is widely produced in Indonesia. Unfortunately, this plant is very susceptible to diseases, which can reduce the crop’s quality and quantity. This paper proposes disease detection in banana plants using a thermal camera. The detection is carried out using image processing techniques with multilevel thresholding methods. The image is captured using a thermal camera; then, the image is preprocessed to suit what is desired. After that, the image produced by the thermal camera is carried out by an image registration process so that the position is the same as the image taken using a digital camera. The image processing result is compared with the ground truth image obtained from a digital camera to determine the effectiveness of the proposed method. The proposed method’s effectiveness is measured using the parameters Recall, Precision, F-measure, and Accuracy. The effectiveness of the proposed method is quite effective because it produces parameter values above 80%, namely the recall value of 85.4%, the Precision of 89.35%, the F measure of 87.33%, and the accuracy of 92.8%.

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Thermal Imaging Techniques in Agricultural Applications

Cited by 5 publications

References 60 publications

Estimation of the soil moisture and its influencing factors using an integration approach of sentinel-2 and GLDAS data: A case study of Bagdad city, Iraq

Estimation of the soil moisture and its influencing factors using an integration approach of sentinel-2 and GLDAS data: A case study of Bagdad city, Iraq

Application of thermal imaging for plant disease detection

Disease detection in banana trees using an image processing-based thermal camera

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