Due to current global population growth, resource shortages, and climate change, traditional
agricultural models face major challenges. Precision agriculture (PA), as a way to realize the …

Swift identification of leaf diseases is crucial for sustainable rice farming, a staple grain
consumed globally. The high costs and inefficiencies of manual identification underline the …

Plant disease detection has played a significant role in combating plant diseases that pose a
threat to global agriculture and food security. Detecting these diseases early can help …

In the realm of smart agriculture technology's rapid advancement, the integration of various
sensors and Internet of Things (IoT) devices has become prevalent in the agricultural sector …

This study presents PlanteSaine, a novel mobile application powered by Artificial
Intelligence (AI) models explicitly designed for maize, tomato, and onion farmers in Burkina …

Yellow vein mosaic virus (YVMV) is a destructive plant virus that commonly affects crops,
particularly okra, in India. The virus is transmitted by whiteflies and poses significant …

Deep learning models have achieved remarkable success in various tasks, especially in
classification. This success is particularly evident in the precise classification of plant …

More than 80% of the human diet depends on plants. Diseases in plants can cause food
insecurity, colossal crop loss, and low profit for growers. Therefore, autonomous systems are …

Spilocaea oleagina is a common and dangerous fungal disease in olive trees that
significantly reduces olive production. The early and accurate detection of this disease is …

An analysis of machine learning (ML) techniques such as K-Nearest Neighbor (KNN),
Support Vector Machine (SVM), Random Forest (RF) and Naive Bayes (NB) was done to …