European Journal of Molecular & Clinical Medicine

One of the biggest revolutions of modern history is the invention of agriculture for a healthier lifestyle. It significantly changed the human culture and played an important role in the development of the population and biological improvements in food production and domestication. Study into agriculture is then planned by improving the disease diagnostics method with the use of newer information technology to enhance efficiency and quantity for agricultural production and its allied operation. This project focuses on the identification and diagnosis of plant leaf diseases of tomatoes and pomegranate based on visual symptoms, anthracnose, and powdery mildew. Machine learning and image processing using SVM, KNN require many steps to identify and distinguish disease signs

With increase in population the need for food is on rise, in such circumstances, plant diseases prove to be a major threat to agricultural produce and result in disastrous consequences for farmers. Early detection of plant disease can help in ensuring food security and controlling financial losses. The images of diseased plants can be used to identify the diseases. Classification abilities of Convolutional Neural Networks are used to obtain reliable output. Google’s pretrained model ‘Inception v3’ is used. The Inception v3 model is trained over a dataset of diseased plants obtained from ‘Plant Village Dataset’. The developed detection approach is evaluated on measures of F1 score, precision and recall.

Alternaria rot disease is a fungal infection affecting plants and trees. The bibliometric analysis had been conducted to understand the active authors, organizations, journals, and countries involved in the research domain of “Alternaria rot”. All published articles related to “Alternaria rot” from “Scopus”, were analyzed using the VOS viewer to develop analysis tables and visualization maps. This article had set the objective to consolidate the scientific literature regarding the “Alternaria rot” and also to find out the trends related to the same. The most active journals in this research domain were identified as Plant Disease, Plant Journal, and Postharvest Biology and Technology. The most active countries were the United States of America and Portugal. The leading organizations engaged in the research regarding Alternaria rot were the Agricultural Research Organization of Israel and USDA Agricultural Research Service of the United States of America. The most active authors who had made valuable contributions related to Alternaria rot disease were Wang Y. and Akimitsu K.

Aphanomyces root rot disease (Aphanomyces euteiches) is a fungal infection caused by oomycetes fungi. The bibliometric analysis had been conducted to understand the active authors, organizations, journals, and countries involved in the research domain of “Aphanomyces root rot”. All published articles related to “Aphanomyces root rot” from “Scopus”, were analyzed using the VOS viewer to develop analysis tables and visualization maps. This article had set the objective to consolidate the scientific literature regarding the “Aphanomyces root rot” and also to find out the trends related to the same. The most active journals in this research domain were identified as Plant Disease and Plant Molecular Biology. The most active countries were the United States of America and Poland. The leading organizations engaged in the research regarding Aphanomyces root rot was the United States Department of Agriculture of the USA. The most active authors who had made valuable contributions related to Aphanomyces root rot disease was Baranger A.