AIMC Topic: Crops, Agricultural

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Detection of weeds in teff crops using deep learning and UAV imagery for precision herbicide application.

Scientific reports Aug 21, 2025
In Ethiopia, Teff is a vital staple crop, yet its productivity is significantly challenges due to inefficient weed and fertilizer management, threatening food security. Traditional weed control methods rely on manual labor and the indiscriminate appl...
Herbicides Weed Control Deep Learning Remote Sensing Technology Agriculture Ethiopia Crops, Agricultural Plant Weeds Unmanned Aerial Devices
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A lightweight and explainable CNN model for empowering plant disease diagnosis.

Scientific reports Aug 21, 2025
Crop disease is a significant challenge in agriculture, requiring quick and precise detection to safeguard yields and reduce economic losses. Traditional diagnostic methods are slow, labor-intensive, and rely on expert knowledge, limiting scalability...
Agriculture Crops, Agricultural Plant Diseases Neural Networks, Computer
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A machine learning approach for estimating forage maize yield and quality in NW Spain.

PloS one Aug 12, 2025
Crop models simulate crop growth and development according to different climatic, soil and crop management conditions. The CSM-CERES-Maize model (DSSAT) was adapted to simulate forage maize yields by calibrating the genetic parameters of six cultivar...
Crops, Agricultural Spain Machine Learning Zea mays
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Recent Development of Methods and Techniques in the Detection of Mycotoxins in Agricultural Products.

Journal of agricultural and food chemistry Aug 11, 2025
Mycotoxins are produced by fungi and possess cytotoxic properties that cause extensive cellular damage. Mycotoxins pose a significant threat to the harvesting and storage of crops as well as potential carcinogenic, teratogenic, and mutagenic risks to...
Humans Food Contamination Fungi Chromatography Crops, Agricultural Electrochemical Techniques Mycotoxins
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Automated weed and crop recognition and classification model using deep transfer learning with optimization algorithm.

Scientific reports Aug 10, 2025
Weeds and crops contribute to a endless resistance for similar assets, which leads to potential declines in crop production and enlarged agricultural expenses. Conventional models of weed control like extensive pesticide use, appear with the hassle o...
Crops, Agricultural Weed Control Algorithms Deep Learning Agriculture Plant Weeds Artificial Intelligence Machine Learning
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Maximizing multi-source data integration and minimizing the parameters for greenhouse tomato crop water requirement prediction.

Scientific reports Aug 9, 2025
Accurate scientific predicting of water requirements for protected agriculture crops is essential for informed irrigation management. The Penman-Monteith model, endorsed by the Food and Agriculture Organization of the United Nations (FAO), is current...
Crops, Agricultural Agricultural Irrigation Machine Learning Algorithms Water Agriculture Solanum lycopersicum
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Study on the effect of light distribution on the greenhouse environment in Chinese solar greenhouse.

PloS one Aug 7, 2025
Solar greenhouse is a primary agricultural facility in northern China during winter, providing a certain level of security for the demand for vegetables and melons in the northern regions. However, there remains a lack of uniformity between crop requ...
Temperature Soil China Crops, Agricultural Agriculture Sunlight Light
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Improved early-stage crop classification using a novel fusion-based machine learning approach with Sentinel-2A and Landsat 8-9 data.

Environmental monitoring and assessment Aug 6, 2025
Crop classification during the early stages is challenging because of the striking similarity in spectral and texture features among various crops. To improve classification accuracy, this study proposes a novel fusion-based deep learning approach. T...
Satellite Imagery Support Vector Machine Crops, Agricultural Neural Networks, Computer Deep Learning Machine Learning Environmental Monitoring
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An explainable vision transformer with transfer learning based efficient drought stress identification.

Plant molecular biology Jul 31, 2025
Early detection of drought stress is critical for taking timely measures for reducing crop loss before the drought impact becomes irreversible. The subtle phenotypical and physiological changes in response to drought stress are captured by non-invasi...
Support Vector Machine Machine Learning Crops, Agricultural Droughts Solanum tuberosum Deep Learning Image Processing, Computer-Assisted Stress, Physiological
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Evaluating crop yield prediction models in illinois using aquacrop, semi-physical model and artificial neural networks.

Scientific reports Jul 28, 2025
Crop yield is important for agricultural productivity and the country's economy. While crop yield estimation is an essential aspect of modern agriculture, it continues to be one of the most challenging tasks to manage effectively. Corn and soybean ar...
Crops, Agricultural Glycine max Illinois Models, Theoretical Neural Networks, Computer Zea mays Agriculture
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