AIMC Topic: Agriculture

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Harnessing multi-omics and genome-editing technologies for climate-resilient agriculture: bridging AI-driven insights with sustainable crop improvement.

Plant molecular biology
Environmental challenges such as drought, salinity, heavy metal contamination, and nutrient deficiencies threaten global agricultural productivity and food security. These stressors drastically reduce crop yields, necessitating innovative solutions. ...

Design, simulation, and experimental study of hydrostatic drive system for wide-span farming platform.

PloS one
A versatile, robotic, and multi-functional wide-span farming platform, commonly known as a gantry tractor, can reduce soil compaction and enhance field production efficiency. In order to meet the functional requirements of wide-span farming platforms...

A fusion transfer learning framework for intelligent pest recognition in sustainable agriculture.

Scientific reports
With the fast growth in the population of the world, there is a constantly increasing requirement for sustainable food supplies. Agriculture is the backbone of the global food supply, with vegetables and fruits being essential for a balanced intake. ...

Robust real-time strawberry maturity detection using UAV-mounted deep learning for precision agriculture.

BMC plant biology
BACKGROUND: To address the challenge of real-time plant monitoring in greenhouse environments, this industry-driven research focuses on developing an autonomous quadrotor UAV system specifically designed for monitoring strawberry plants. Traditional ...

Classification of cotton leaf disease using YOLOv8 based k-fold cross validation deep learning method for precision agriculture.

Scientific reports
Cotton production is a crucial agricultural industry, a raw material source for the textiles sector and a major source of livelihood for more than 30 million farmers globally. The yield and quality of cotton (Gossypium) are influenced by different ty...

Remote sensing-based long-term assessment of bioenergy policy impact on agricultural land cover change: A case study of biogas in the Weser-Ems region in Germany.

The Science of the total environment
Climate change, population growth, and other global challenges are putting pressure on the limited land resources, in particular on agricultural land, to satisfy the demands for food, energy carriers, raw materials for the chemical industry, and ecos...

High-resolution agricultural drought hazard mapping using the potential of geospatial data and machine learning approaches.

Environmental monitoring and assessment
Effective delineation of Agricultural Drought Hazard (ADH) zones is crucial for mitigating crop losses and ensuring water security in semi-arid regions. Conventional agricultural drought assessment methods, reliant on single-index approaches or stati...

Towards smart agriculture: AI-driven prediction of key genes for revolutionizing crop breeding.

Planta
AI-driven key gene prediction is revolutionizing crop breeding, enhancing precision, efficiency, and sustainability while paving the way for intelligent, data-driven agricultural innovation. The integration of artificial intelligence (AI) into crop b...

Emerging nanosensor technologies for the rapid detection of heavy metal contaminants in agricultural soils.

Analytical methods : advancing methods and applications
The accumulation of heavy metals in agricultural soils presents a growing threat to food safety and human health. Conventional laboratory-based methods for heavy metal detection, while highly sensitive, are impractical for widespread, real-time soil ...

When crops fail, forests follow: Agricultural shocks and deforestation in Zambia.

Proceedings of the National Academy of Sciences of the United States of America
As climate change makes agricultural production shocks more frequent and severe, it is vital to understand their effect on farmer welfare, land use, and deforestation. Theoretically, a change in agricultural productivity could increase or decrease de...