Diabetic Retinopathy Detection Using Machine Learning
Volume-4 | Issue-1
Monocular Depth Estimation using a Multi-grid Attention-based Model
Volume-4 | Issue-3
Speedy Image Crowd Counting by Light Weight Convolutional Neural Network
Volume-3 | Issue-3
Construction of Efficient Smart Voting Machine with Liveness Detection Module
Volume-3 | Issue-3
An Economical Robotic Arm for Playing Chess Using Visual Servoing
Volume-2 | Issue-3
Triplet loss for Chromosome Classification
Volume-4 | Issue-1
Unstructured Noise Removal for Industrial Sensor Imaging Unit by Hybrid Adaptive Median Algorithm
Volume-3 | Issue-4
Real Time Sign Language Recognition and Speech Generation
Volume-2 | Issue-2
Analysis of Artificial Intelligence based Image Classification Techniques
Volume-2 | Issue-1
Design of ANN Based Machine Learning Method for Crop Prediction
Volume-3 | Issue-3
A REVIEW ON IOT BASED MEDICAL IMAGING TECHNOLOGY FOR HEALTHCARE APPLICATIONS
Volume-1 | Issue-1
COMPUTER VISION BASED TRAFFIC SIGN SENSING FOR SMART TRANSPORT
Volume-1 | Issue-1
Diabetic Retinopathy Detection Using Machine Learning
Volume-4 | Issue-1
Accurate Segmentation for Low Resolution Satellite images by Discriminative Generative Adversarial Network for Identifying Agriculture Fields
Volume-3 | Issue-4
Deep Learning based Handwriting Recognition with Adversarial Feature Deformation and Regularization
Volume-3 | Issue-4
State of Art Survey on Plant Leaf Disease Detection
Volume-4 | Issue-2
Optimal Compression of Remote Sensing Images Using Deep Learning during Transmission of Data
Volume-3 | Issue-4
OverFeat Network Algorithm for Fabric Defect Detection in Textile Industry
Volume-3 | Issue-4
VIRTUAL RESTORATION OF DAMAGED ARCHEOLOGICAL ARTIFACTS OBTAINED FROM EXPEDITIONS USING 3D VISUALIZATION
Volume-1 | Issue-2
Two-Stage Frame Extraction in Video Analysis for Accurate Prediction of Object Tracking by Improved Deep Learning
Volume-3 | Issue-4
Volume - 5 | Issue - 1 | march 2023
Published
10 May, 2023
Agriculture plays a key role in global economy. Tomato is India's third most prioritized crop after potato and onion, but it is the world's second most prioritized crop after potato. Worldwide, India ranks second in tomato production. However, Tomato crop is constantly threatened by different pest infections. The most significant pest infection that highly affects the tomato crop yield is Spodoptera Litura. Emerging from the family of Noctuidae with vigorous eating pattern, this insect primarily feed on leaves and fruits by leaving the entire crop completely destroyed. Monitoring the pest spread dynamics will reduce the probability of an outbreak. Early detection of pests can assist farmers in taking the required precautions to limit the spread of the infection. This paper provides a brief introduction to performs an assessment on the infection spread by Spodoptera Litura in the tomato plants. Here, the plants are classified as low, moderate and high pest infestation and further the severity of the damage is assessed by analyzing the number of S. Litura Larvae present in Tomato crop and also the percentage of pest infestation in tomato plants. The primary goal of this research study is to detect pests as early as possible and decline the usage of pesticides on the crops by taking early sustainable alternative measures.
KeywordsSpodoptera Litura tomoto leaves disease detection pest dynamics severity analysis
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