BACKGROUND: Potato is the fourth largest food crop in the world, but potato cultivation faces serious threats from various diseases and pests. Despite significant advancements in research on potato disease resistance, these findings are scattered acr...
'Akizuki' pear ( Nakai) corky disease is a physiological disease that strongly affects the fruit quality of 'Akizuki' pear and its economic value. In this study, Raman spectroscopy was employed to develop an early diagnosis model by integrating suppo...
In the last few years, the agricultural field has undergone a digital transformation, incorporating artificial intelligence systems to make good employment of the growing volume of data from various sources and derive value from it. Within artificial...
This study develops a hybrid machine learning (ML) algorithm integrated with IoT technology to improve the accuracy and efficiency of soil monitoring and tomato crop disease prediction in Anakapalle, a south Indian station. An IoT device collected on...
With the recent development of smart farms, researchers are very interested in such fields. In particular, the field of disease diagnosis is the most important factor. Disease diagnosis belongs to the field of anomaly detection and aims to distinguis...
Estimating the optimal answer is expensive for huge data resources that decrease the functionality of the system. To solve these issues, the latest groundnut leaf disorder identification model by deep learning techniques is implemented. The images ar...
This paper presents a novel approach to agricultural disease diagnostics through the integration of Deep Learning (DL) techniques with Visual Question Answering (VQA) systems, specifically targeting the detection of wheat rust. Wheat rust is a pervas...
Recent advancements in hyperspectral imaging (HSI) for early disease detection have shown promising results, yet there is a lack of validated high-resolution (spatial and spectral) HSI data representing the responses of plants at different stages of ...
This research introduces a Computer-Aided Diagnosis-system designed aimed at automated detections & classification of tomato leaf diseases, combining traditional handcrafted features with advanced deep learning techniques. The system's process encomp...
This review article provides a comprehensive examination of the state-of-the-art in maize disease detection leveraging Convolutional Neural Networks (CNNs). Beginning with the intrinsic significance of plants and the pivotal role of maize in global a...