Abstract
Agriculture is crucial to the economic prosperity and development of India. Plant diseases can have a devastating influence towards food safety and a considerable loss in the production of agricultural products. Disease identification on the plant is essential for long-term agriculture sustainability. Manually monitoring plant diseases is difficult due to time limitations and the diversity of diseases. In the realm of agricultural inputs, automatic characterization of plant diseases is widely required. Based on performance out of all image-processing methods, is better suited for solving this task. This work investigates plant diseases in grapevines. Leaf blight, Black rot, stable, and Black measles are the four types of diseases found in grape plants. Several earlier research proposals using machine learning algorithms were created to detect one or two diseases in grape plant leaves; no one offers a complete detection of all four diseases. The photos are taken from the plant village dataset in order to use transfer learning to retrain the EfficientNet B7 deep architecture. Following the transfer learning, the collected features are down-sampled using a Logistic Regression technique. Finally, the most discriminant traits are identified with the highest constant accuracy of 98.7% using state-of-the-art classifiers after 92 epochs. Based on the simulation findings, an appropriate classifier for this application is also suggested. The proposed technique’s effectiveness is confirmed by a fair comparison to existing procedures.
Highlights
The agricultural sector is a significant and new framework for researchers in the field of computer vision today
Agricultural researchers have focused their efforts on diseases of various fruits and crops
Grapes seem to be a complex fruit to grow because the plants are constantly attacked by viruses, resulting in a significant reduction in grape production [4]
Summary
The agricultural sector is a significant and new framework for researchers in the field of computer vision today. Agricultural researchers have focused their efforts on diseases of various fruits and crops. The researchers devised several methods for detecting and classifying diseases in fruits and crops [2,3]. Grapes seem to be a complex fruit to grow because the plants are constantly attacked by viruses, resulting in a significant reduction in grape production [4]. It is critical to control contaminated crops before they wreak havoc on product quality and quantity. Various bacterial and fungal diseases manifest themselves primarily occur on the surface of leaf area and fruit area. On the other hand, thrive as single cells with a simpler life cycle They reproduce by dividing a single cell into two; a method called binary fusion. The researchers use image processing to determine the diseased part’s location, color, form, scale, and boundaries
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