AIMC Topic: Agriculture

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

Scientific reports
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...

A lightweight and explainable CNN model for empowering plant disease diagnosis.

Scientific reports
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...

Automated weed and crop recognition and classification model using deep transfer learning with optimization algorithm.

Scientific reports
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...

A new framework for evaluating land suitability for Goji (Lycium barbarum L.) cultivation across China.

Journal of environmental management
As a valuable Chinese medicinal herb and functional food, Goji (Lycium barbarum L.) berries have been consumed for more than 4500 years in China and have received extensive international attention. However, stakeholders have adopted traditional manag...

Maximizing multi-source data integration and minimizing the parameters for greenhouse tomato crop water requirement prediction.

Scientific reports
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...

Study on the effect of light distribution on the greenhouse environment in Chinese solar greenhouse.

PloS one
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...

Exploring the carbon rebound effect of agriculture and policy response: Lessons from zero growth of fertiliser action.

Environmental research
Agricultural technological progress is theoretically regarded as the core driving force to curb carbon emissions, but its possible rebound effect often leads to systematic offsetting of emission reduction. Based on the panel data of 267 cities in Chi...

Mapping hotspots and identifying drivers of lead bioaccumulation in Oryza sativa L. in tropical agroecosystems.

Journal of hazardous materials
Tropical rice systems exhibit high annual rates of heavy metal accumulation, requiring accurate identification of accumulation drivers in rice-growing ecosystems to ensure regional food security. Therefore, we collected 229 paired soil and rice sampl...

Evaluating crop yield prediction models in illinois using aquacrop, semi-physical model and artificial neural networks.

Scientific reports
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...

Predicting wheat yield using deep learning and multi-source environmental data.

Scientific reports
Accurate forecasting of crop yields is essential for ensuring food security and promoting sustainable agricultural practices. Winter wheat, a key staple crop in Pakistan, faces challenges in yield prediction because of the complex interactions among ...