At present, the detection and severity estimation of tea diseases mainly rely on manual
methods, which are time consuming and laborious. Existing machine learning and image …

IoT networks have laid a lot of the groundwork for agriculture and development, which will
serve as the foundation for IoT-based agriculture in the future. Earlier farmers had to monitor …

Maize leaf disease is a serious problem in the process of agricultural production. Controlling
maize leaf disease is of great significance to improving maize yield and quality, maintaining …

Medicinal plants have been found and utilized in traditional medical practices from ancient
times. Many medicinal plants play a vital role in curating many life threatening diseases …

Urinary metabolomics coupled with GC-MS has become a leading technology in newborn
screening. Because of non-specificity, complexity and high-variety in clinical characteristics …

Farming is the mainstream of the Indian economy. Plant leaf disease detection mainly
focuses on the health of leaf plants and detecting diseases in their early stages is a tedious …

Maize is the most productive food crop in the world, and its leaves are extremely susceptible
to disease. However, the yearly crop yields are reduced by the disease and its interference …

Plant diseases are a significant concern for the agricultural industry, as they can reduce crop
yields and cause economic losses. Tea is a popular and widely consumed beverage in …

This review explores the effectiveness of Machine Learning (ML) techniques in identifying
and categorizing diseases affecting Tulsi (Ocimum sanctum) leaves. Tulsi, or holy basil, is …

Leaf disease diagnosis is very critical for tea due to its importance for increasing crop
production. Tea leaf disease images pose unique challenges compared to other types of …