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

Abstract

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%.

Artificial Intelligence Techniques for the Pest Detection in Banana Field: A Systematic Review

“…Instead, they seek to more precisely identify and quantify the starting points of bioagressor assaults in order to choose the best course of action. (Anasta et al, 2021) describes a method for use a thermal camera to find ill leaf areas on banana plants. The suggested method works well for locating disease-related spots on banana leaves.…”

“…Future observations will be required to gauge the disease's development and develop preventive strategies. (Anasta et al, 2021) concentrated on automatically detecting and classifying banana plants on the Sunshine Coast in Queensland, Australia, in order to make it easier to locate banana plants and raise the inspection rate for Banana Bunchy Top Virus. With a final visual phase to validate or deny the possibilities, a novel method of object-based image analysis was created to automatically find and classify possible banana plants.…”

“…One may assess the effectiveness of the suggested technique by taking into account the values of Retention, Accuracy, F-Measure, and Reliability. The (Anasta et al, 2021) method is considered to be very effective if both memory and accuracy scores are more than 60%. The thermal image processing output is compared to the original image in order to identify the positive overall, false negatives, true positive, and genuine negative values.…”

“…The thermal image processing output is compared to the original image in order to identify the positive overall, false negatives, true positive, and genuine negative values. After the 1 km 1 km orthophoto tiles were divided into four groups for batch processing in the eCognition Server software, each picture tile in (Anasta et al, 2021) took between 15 and 20 minutes to process. Individual banana plants were sometimes missed, but clusters of banana plants were often recognized and precisely described using the constructed rule set.…”

Role of 5G Technology in Enhancing Agricultural Mechanization

“…Application of 5G technologies, process of identification of weeds and crops can be more accurate and fine-grained [31]. Disease identification using thermal cameras, image processing [32,33,34], artificial intelligence [35,36,37], can be enhanced effectively with 5G technology.…”