By employing machine-learning models, this study utilizes agronomical and molecular features to predict powdery mildew disease resistance in Barley (Hordeum Vulgare L). A 130-line F8-F9 barley population caused Badia and Kavir to grow at the Gonbad K...
Mulberry leaf disease detection is vital for maintaining the health and productivity of mulberry crops. In this paper, a novel approach was proposed by integrating explainable artificial intelligence (XAI) techniques with a convolutional neural netwo...
International journal of molecular sciences
Jun 1, 2025
Harnessing state-of-the-art technologies to improve disease resistance is a critical objective in modern plant breeding. Artificial intelligence (AI), particularly deep learning and big model (large language model and large multi-modal model), has em...
Agriculture and its yields are indispensable to human life all over the planet. It is an essential part of many countries' economies and without it the world's population can not be fed. As such, guaranteeing harvest with minimal loss is a primary ob...
Accurate diagnosis of apple diseases is vital for tree health, yield improvement, and minimizing economic losses. This study introduces a deep learning-based model to tackle issues like limited datasets, small sample sizes, and low recognition accura...
The agricultural sector faces critical challenges, including significant crop losses due to undetected plant diseases, inefficient monitoring systems, and delays in disease management, all of which threaten food security worldwide. Traditional approa...
Pine forests are increasingly threatened by needle diseases, including Brown Spot Needle Blight (BSNB), caused by . BSNB leads to needle loss, reduced growth, significant tree mortality, and disruptions in global timber production. Due to its severit...
Neural networks : the official journal of the International Neural Network Society
May 6, 2025
The occurrence of crop diseases exhibits nonlinear and dynamic spatial-temporal correlations. How to realize real-time and accurate regional disease prediction is an emerging challenge in smart agriculture. Existing research is hindered by difficulti...
Journal of the science of food and agriculture
May 5, 2025
BACKGROUND: Automated fruit defect detection plays a critical role in improving postharvest quality assessment and supporting decision-making in agricultural supply chains. Guava defect detection presents specific challenges because of diverse diseas...
Early blight, caused by Alternaria alternata, poses a critical challenge to tomato (Solanum lycopersicum L.) production, causing significant yield losses worldwide. Despite advancements in plant disease detection, existing methods often lack the robu...
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