AIMC Topic: Plant Weeds

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The impact of climate change on the invasiveness of Ageratum conyzoides (goat weed) in India: implications for biodiversity conservation.

Environmental monitoring and assessment
Climate change and biological invasions are major drivers of global biodiversity loss. Ageratum conyzoides L. is a highly aggressive invader, yet its ecological risks and potential range dynamics in India remain insufficiently quantified. To assess i...

Harnessing hyperspectral imaging and machine learning techniques for accurate discrimination of peanut plants and weeds.

Scientific reports
Effective weed detection for precise management remains a pertinent issue in modern agriculture. In this study, hyperspectral imaging (HSI) was combined with machine learning (ML) to differentiate between peanut plants and four common weeds found in ...

Detection of commercial crop weeds using machine learning algorithms.

Scientific reports
This work investigates the YOLOv5 object detection algorithms for classifying commercial crops such as tomatoes, chili, and cotton. The data sets comprise 707 images of green chillies, 200 images of tomato crops and 130 images of weeds from Ponnandag...

Associations among weed communities, management practices, and environmental factors in U.S. snap bean (Phaseolus vulgaris) production.

PloS one
Weed species that escape control (hereafter called residual weeds) coupled with changing weather patterns are emerging challenges for snap bean processors and growers. Field surveys were conducted to identify associations among crop/weed management p...

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...

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...

WeedSwin hierarchical vision transformer with SAM-2 for multi-stage weed detection and classification.

Scientific reports
Weed detection and classification using computer vision and deep learning techniques have emerged as crucial tools for precision agriculture, offering automated solutions for sustainable farming practices. This study presents a comprehensive approach...

Hybrid deep learning model for density and growth rate estimation on weed image dataset.

Scientific reports
Agriculture research is particularly essential since crop production is a challenge for farmers in India and around the world. 37% of the crop is impacted by invasive plants (weeds). Those unwelcome plants that interbreed with cultivated crops and de...

Deep learning-based weed detection for precision herbicide application in turf.

Pest management science
BACKGROUND: Precision weed mapping in turf according to its susceptibility to selective herbicides allows the smart sprayer to spot-spray the most pertinent herbicides onto the susceptible weeds. The objective of this study was to evaluate the feasib...

Allelopathic effects of six alfalfa varieties at three stubbles on the germination, seedling and root growth of green foxtail and barnyardgrass.

PloS one
Alfalfa (Medicago sativa) is known to release allelopathic substances to affect the germination and growth of other plants, which have the potential to be applied in controlling weeds. Green foxtail (Setaria viridis) and barnyardgrass (Echinochloa cr...