Development of Automated Leaf Disease Detection in Pomegranate Using Alexnet Algorithm

Abstract

Fruits and vegetables play very important role in our day-to-day life because of their nutrition parameters. In recent years organic cultivation is more popular as there is more demand for organic fruits and vegetables. Due to very high nutrition benefits and considering the easily availability of banana, it is most demandable and afforded by common man. Consumer decides the quality of banana based on their physical characteristics. Simple experiment was carried out to study and analyse physical properties, nutritional properties of two varieties of banana Cavendish Banana and Velchi banana. The study shows that the colour of banana changes gradually from dark green to yellow with brown spots which increases in ripeness. The banana weight goes on reducing with ripening days. The 21.83% and 9.8% reduction weight is observed in Cavendish and Velchi Banana respectively. The pulp to peel ratio increases with increase in ripening. Ratio varied from 1.69 to 1.77 for cavendish and 3.2 to 4.8 for Velchi. The pH value goes on increasing during the ripening days whereas once fruit is overripe it starts decreasing. The pH value varies from 4.2 to 5.4. Total Soluble Sugar gradually increases till banana becomes overripe. TSS varies from 4.5 to 26.7. The majority characteristics used for grading are colour, pulp to peel ratio, TSS and pH. This paper represents the analysis of Cavendish banana and Velchi banana based on colour, TSS and pH. The study shows TSS goes on increasing with ripening whereas pH decreases once banana overripe

i-PomDiagnoser: A Real-Time Pomegranate Disease Management System

“…VGGNet 2019 (13) Sugarcane Images Size: 2100 Accuracy: 95.4% Deep CNN 2020 (14) Kiwifruit Leaf Images Size: 11322 Accuracy: 98.54% CNN-Inception V3 Model 2020 (15) Plum fruit Images Size:87,848 Accuracy: 92% CNN Model Grad-CAM 2021 (16) Coffee Leaf Images Size: 1560 Accuracy: 98% AlexNet Model 2023 (17) Pomegranate Leaf Images Size: 1245 Accuracy: 97.60% Fruit/Crop disease forecasting (Data-Driven Approach) LSTM 2019 (18) Cotton: Weather parameters AUC: 0.97…”

Classification of Apple Plant Leaf Diseases Using Deep Convolutional Neural Network

“…Smart farming now helps farmers make better decisions. Instead of using old methods, farmers usually check their crops for diseases in a smarter way (WAKHARE, 2023). Apple black rot is an apple disease that affects apple trees and fruit that happens due to warm and humid weather also caused by fungus.…”