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Agriculture

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Cyber-agricultural systems for crop breeding and sustainable production.

Trends in plant science
The cyber-agricultural system (CAS) represents an overarching framework of agriculture that leverages recent advances in ubiquitous sensing, artificial intelligence, smart actuators, and scalable cyberinfrastructure (CI) in both breeding and producti...

[Artificial Intelligence and employee's health - new challenges].

Medycyna pracy
BACKGROUND: The presence of artificial intelligence (AI) in many areas of social life is becoming widespread. The advantages of AI are being observed in medicine, commerce, automobiles, customer service, agriculture and production in factory settings...

Semisupervised Deep Learning for the Detection of Foreign Materials on Poultry Meat with Near-Infrared Hyperspectral Imaging.

Sensors (Basel, Switzerland)
A novel semisupervised hyperspectral imaging technique was developed to detect foreign materials (FMs) on raw poultry meat. Combining hyperspectral imaging and deep learning has shown promise in identifying food safety and quality attributes. However...

GACN: Generative Adversarial Classified Network for Balancing Plant Disease Dataset and Plant Disease Recognition.

Sensors (Basel, Switzerland)
Plant diseases are a critical threat to the agricultural sector. Therefore, accurate plant disease classification is important. In recent years, some researchers have used synthetic images of GAN to enhance plant disease recognition accuracy. In this...

Human-Robot Interaction in Agriculture: A Systematic Review.

Sensors (Basel, Switzerland)
In the pursuit of optimizing the efficiency, flexibility, and adaptability of agricultural practices, human-robot interaction (HRI) has emerged in agriculture. Enabled by the ongoing advancement in information and communication technologies, this app...

Dissolved organic matter evolution and straw decomposition rate characterization under different water and fertilizer conditions based on three-dimensional fluorescence spectrum and deep learning.

Journal of environmental management
Straw returning is a sustainable way to utilize agricultural solid waste resources. However, incomplete decomposition of straw will cause harm to crop growth and soil quality. Currently, there is a lack of technology to timely monitor the rate of str...

Development potential of nanoenabled agriculture projected using machine learning.

Proceedings of the National Academy of Sciences of the United States of America
The controllability and targeting of nanoparticles (NPs) offer solutions for precise and sustainable agriculture. However, the development potential of nanoenabled agriculture remains unknown. Here, we build an NP-plant database containing 1,174 data...

Detecting stress caused by nitrogen deficit using deep learning techniques applied on plant electrophysiological data.

Scientific reports
Plant electrophysiology carries a strong potential for assessing the health of a plant. Current literature for the classification of plant electrophysiology generally comprises classical methods based on signal features that portray a simplification ...

Emerging technology in agriculture: Opportunities and considerations for occupational safety and health researchers.

Journal of safety research
INTRODUCTION: A variety of factors are driving the development of robotics and automation in the agriculture industry including the nature of work, workforce shortages, and a variety of economic, climatic, technologic, political, and social factors. ...

Crop pest detection by three-scale convolutional neural network with attention.

PloS one
Crop pests seriously affect the yield and quality of crop. To timely and accurately control crop pests is particularly crucial for crop security, quality of life and a stable agricultural economy. Crop pest detection in field is an essential step to ...