By investigating the possibility of plant species classification based on independent component analysis (ICA) for hyperspectral data with minor difference, the framework of a general plant species classification model that consists of ICA based data reduction, classifier training and verification is proposed in this paper. Five different types of discriminant analysis classifiers including Lin...

High resolution and high throughput, genotype to phenotype studies in plants are underway to accelerate breeding of climate ready crops. Complex developmental phenotypes are observed by imaging a variety of accessions in different environment conditions, however extracting the genetically heritable traits is challenging. In the recent years, deep learning techniques and in particular Convolutio...

Diseases that attack chili plants can be diagnosed early by observing symptoms or changes occur in the leaves and fruit of plant. However, diseases pests within a single plant vary. In this study, YOLO v7 was used to perform leaf segmentation on images, segmented results were then classified for disease using Deep Convolutional Neural Network (DCNN) Transfer Learning with Fine Tuning method. Th...

Feature selection methods have been explored in the literature for the classification techniques, among which correlated feature, information gain, mutual information and chi-square are considered more effective. The leaf images contain inherent noise due to imaging equipment, operating environment and position of the image during image acquisition. In this paper, a method for classification of...

A leaf is an organ of vascular plant and is the principal lateral appendage of the stem. Each leaf has a set of features that differentiate it from the other leaves, such as margin and shape. This paper proposes a comparison of supervised plant leaves classification using different approaches, based on different representations of these leaves, and the chosen algorithm. Beginning with the repre...

The Food and Agriculture Organization of the United Nations suggests increasing food supply by 70% to feed world population 2050, although approximately one third all is wasted because plant diseases or disorders. To achieve this goal, researchers have proposed many deep learning models help farmers detect in their crops as efficiently possible avoid yield declines. These are usually trained on...

Traditional classification systems represent cognitive processes of human cultures in the world. It synthesizes specific conceptions of nature, as well as cumulative learning, beliefs and customs that are part of a particular human community or society. Traditional knowledge has been analyzed from different viewpoints, one of which corresponds to the analysis of ethnoclassifications. In this wo...

A leaf is an organ of vascular plant and is the principal lateral appendage of the stem. Each leaf has a set of features that differentiate it from the other leaves, such as margin and shape. This work proposes a comparison of supervised plant leaves classification using different approaches, based on different representations of these leaves, and the chosen algorithm. Beginning with the repres...

The Plant disease identification is the key which prevent loss and improve quality of agriculture products. plant detection techniques have various phases include pre-processing, segmentation, feature extraction classification. In pre-processing stage, contrast input image increased. points are not visible highlighted. second stage segmentation can help in selecting region interest. phase will ...

BACKGROUND Antimicrobial peptides are a promising alternative to conventional antibiotics. Plants are an important source of such peptides; their pharmacological properties are known since antiquity. Access to relevant information, however, is not straightforward, as there are practically no major repositories of experimentally validated and/or predicted plant antimicrobial peptides. PhytAMP is...