Late Leaf Spot Detection and Its Effect on Pod Quality of Groundnut Plants Using Deep Neural Networks: A Review

Late Leaf Spot [LLS] [1], caused by various pathogens such as fungi and bacteria, is a significant foliar disease that affects groundnut (Arachis hypogaea) plants, impacting both agricultural productivity and food security. This survey aims to provide a comprehensive overview of the state-of-the-art research on late leaf spot detection and its subsequent effects on the quality of groundnut pods. The study establishes the importance of groundnut cultivation and emphasizes the relevance of understanding late leaf spot’s impact on pod quality. Various techniques ranging from visual observation to sophisticated image processing [2] are evaluated in terms of their accuracy, efficiency, and applicability. The study further delves into the implications of late leaf spot on pod quality. Drawing from past studies, evidence is presented on the disease’s adverse effects on pod size, weight, oil content, and nutritional value. The correlations between disease severity and pod quality deterioration are examined, highlighting the potential repercussions for groundnut-based industries and nutrition security. This survey not only underscores the significance of understanding the relationship between late leaf spot and pod quality but also addresses the broader implications for agricultural practices and decision-making. The potential economic, environmental, and societal consequences of disease management strategies are considered, underscoring the need for sustainable approaches.