Crop disease has been a severe issue for agriculture, causing economic loss growers. Thus, identification urgently needs to be addressed, especially precision agriculture. As of today, deep learning widely used crop combined with optical imaging sensors. In this study, lightweight convolutional neural network model is designed and validated on two publicly available datasets one self-built data...

Barley production in the Rostov region, as well throughout Russia, has taken its niche agricultural production. Winter barley attracts farmers’ attention with unpretentiousness and high productivity. The relevance of immunology used varieties does not decrease over time. Yield losses due to various leaf diseases can be 30–50 %. most common pathogens region are powdery mildew helminthosporium bl...

Rice, the world’s most extensively cultivated cereal crop, serves as a staple food and energy source for over half of global population. A variety abiotic biotic factors such weather conditions, soil quality, temperature, insects, pathogens, viruses can greatly impact quantity quality rice grains. Studies have established that plant infections significant on crops, resulting in substantial fina...

<span lang="EN-US">Indonesia is a major exporter and producer of coffee, coffee cultivation adds to the nation's economy. Despite this, remains vulnerable several plant diseases that may result in significant financial losses for agricultural industry. Traditionally, are detected by expert observation with naked eye. Traditional methods managing such arduous, time-consuming, costly, espec...

Agriculture is an important research area in the field of visual recognition by computers. Plant diseases affect quality and yields agriculture. Early-stage identification crop disease decreases financial losses positively impacts quality. The manual diseases, which are mostly visible on leaves, a very time-consuming costly process. In this work, we propose new framework for cucumber leaf disea...

The subject under consideration is the issue of detecting agricultural crop diseases. preliminary data for determining phytosanitary status cultivated plants are images their leaves. To tackle this issue, a model diagnostic algorithms has been proposed, which involves creating set preferred characteristics and making decisions based on comparing these features. process establishing outlined. ef...