AIMC Topic: Poaceae

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Unraveling soil salinity on potentially toxic element accumulation in coastal Phragmites australis: A novel integration of multivariate and interpretable machine-learning models.

Marine pollution bulletin May 5, 2025
Revealing the key mechanisms influencing the behavior of potentially toxic elements (PTEs) in soil-plant systems is of great significance for environmental protection and grassland development in coastal areas. This study utilized redundancy analysis...
Machine Learning Soil Poaceae Salinity Environmental Monitoring Soil Pollutants
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Engineering transverse cell deformation of bamboo by controlling localized moisture content.

Nature communications May 1, 2025
Bamboo's native structure, defined by the vertical growth pattern of its vascular bundles and parenchyma cell tissue, limits its application in advanced engineering materials. Here we show an innovative method that controls localized moisture content...
Sasa Water Poaceae Temperature
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Spatiotemporal modelling of airborne birch and grass pollen concentration across Switzerland: A comparison of statistical, machine learning and ensemble methods.

Environmental research Sep 20, 2024
BACKGROUND: Statistical and machine learning models are commonly used to estimate spatial and temporal variability in exposure to environmental stressors, supporting epidemiological studies. We aimed to compare the performances, strengths and limitat...
Pollen Betula Models, Statistical Air Pollutants Switzerland Poaceae Spatio-Temporal Analysis Environmental Monitoring Machine Learning
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Semi-supervised learning methods for weed detection in turf.

Pest management science Jan 24, 2024
BACKGROUND: Accurate weed detection is a prerequisite for precise automatic precision herbicide application. Previous research has adopted the laborious and time-consuming approach of manually labeling and processing large image data sets to develop ...
Image Processing, Computer-Assisted Plant Weeds Neural Networks, Computer Deep Learning Herbicides Weed Control Supervised Machine Learning Poaceae
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Application technology for bioherbicides: challenges and opportunities with dry inoculum and liquid spray formulations.

Pest management science Nov 29, 2023
Bioherbicides offer many potential benefits as part of an integrated weed management system or a totally biological or organic cropping system. A key factor for success is the selection of appropriate formulation and delivery systems for each target ...
Robotics Plant Weeds Poaceae Pest Control Plant Leaves
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Deep learning-enabled discovery and characterization of HKT genes in Spartina alterniflora.

The Plant journal : for cell and molecular biology Jul 26, 2023
Spartina alterniflora is a halophyte that can survive in high-salinity environments, and it is phylogenetically close to important cereal crops, such as maize and rice. It is of scientific interest to understand why S. alterniflora can live under suc...
Plant Breeding Genes, Plant Deep Learning Oryza Poaceae
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Adapting small jumping robots to compliant environments.

Journal of the Royal Society, Interface Mar 1, 2023
Jumping animals launch themselves from surfaces that vary widely in compliance from grasses and shrubs to tree branches. However, studies of robotic jumpers have been largely limited to those jumping from rigid substrates. In this paper, we leverage ...
Environment Poaceae Trees Animals Robotics
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Grass Cutting Robot for Inclined Surfaces in Hilly and Mountainous Areas.

Sensors (Basel, Switzerland) Jan 3, 2023
Grass cutting is necessary to prevent grass from diverting essential nutrients and water from crops. Usually, in hilly and mountainous areas, grass cutting is performed on steep slopes with an inclination angle of up to 60° (inclination gradient of 1...
Robotics Motion Poaceae Locomotion Humans Water
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Use of synthetic images for training a deep learning model for weed detection and biomass estimation in cotton.

Scientific reports Nov 15, 2022
Site-specific treatment of weeds in agricultural landscapes has been gaining importance in recent years due to economic savings and minimal impact on the environment. Different detection methods have been developed and tested for precision weed manag...
Gossypium Biomass Deep Learning Neural Networks, Computer Poaceae Crops, Agricultural Image Processing, Computer-Assisted Plant Weeds
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Evaluation of deep learning and transform domain feature extraction techniques for land cover classification: balancing through augmentation.

Environmental science and pollution research international Sep 24, 2022
The identification of features that can improve classification accuracy is a major concern in land cover classification research. This paper compares deep learning and transform domain feature extraction techniques for land cover classification of SA...
Poaceae Deep Learning Agriculture Forests
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