Results 41 to 50 of about 283 (97)

Assessing Weed Canopy Cover in No-Till and Conventional Tillage Plots in Winter Wheat Production Using Drone Data

Agronomy
Weed canopy cover assessment, particularly using drone-acquired data, plays a vital role in precision agriculture by providing accurate, timely, and spatially detailed information, enhancing weed management decision-making in response to environmental ...
Judith N. Oppong, Clement E. Akumu, Sam Dennis   +2 more
doaj   +1 more source

Deep learning for image-based detection of weeds from emergence to maturity in wheat fields

Smart Agricultural Technology
Effective weed control in wheat (Triticum aestivum L.) fields is crucial for optimizing production and ensuring food security in semi-arid regions. The implementation of deep learning for weed detection could enable precise weed management, leading to ...
Mustafa Guzel, Bulent Turan, Izzet Kadioglu, Alper Basturk, Bahadir Sin, Amir Sadeghpour   +5 more
doaj   +1 more source

Making Weed Management Maps by Artificial Neural Networks for Using in Precision Agriculture

Journal of Agricultural Machinery, 2011
With the rise of new powerful statistical techniques and neural networks models, the development of predictive species distribution models has rapidly increased in ecology. In this research, a learning vector quantization (LVQ) and multi layer perceptron (MLP) neural network models have been employed to predict, classify and map the spatial ...
A Rohani, H Makarian
openaire   +3 more sources

Precision Weed Control Using Unmanned Aerial Vehicles and Robots: Assessing Feasibility, Bottlenecks, and Recommendations for Scaling

NDT
Weeds cause significant yield and economic losses by competing with crops and increasing production costs. Compounding these challenges are labor shortages, herbicide resistance, and environmental pollution, making weed management increasingly difficult.
Shanmugam Vijayakumar, Palanisamy Shanmugapriya, Pasoubady Saravanane, Thanakkan Ramesh, Varunseelan Murugaiyan, Selvaraj Ilakkiya   +5 more
doaj   +1 more source

Herbicide Resistance in Plants

Plants, 2020
Herbicide resistance in weeds is perhaps the most prominent research area within the discipline of weed science today. Incidence, management challenges, and the cost of multiple-resistant weed populations are continually increasing worldwide.
Hugh J Beckie
doaj   +1 more source

Focus on the Crop Not the Weed: Canola Identification for Precision Weed Management Using Deep Learning

Remote Sensing
Weeds pose a significant threat to agricultural production, leading to substantial yield losses and increased herbicide usage, with severe economic and environmental implications. This paper uses deep learning to explore a novel approach via targeted segmentation mapping of crop plants rather than weeds, focusing on canola (Brassica napus) as the ...
Michael Mckay, Monica F. Danilevicz, Michael B. Ashworth, Roberto Lujan Rocha, Shriprabha R. Upadhyaya, Mohammed Bennamoun, David Edwards   +6 more
openaire   +2 more sources

PMDNet: An Improved Object Detection Model for Wheat Field Weed

Agronomy
Efficient and accurate weed detection in wheat fields is critical for precision agriculture to optimize crop yield and minimize herbicide usage. The dataset for weed detection in wheat fields was created, encompassing 5967 images across eight well ...
Zhengyuan Qi, Jun Wang
doaj   +1 more source

Development and evaluation of a machine vision and deep learning-based smart sprayer system for site-specific weed management in row crops: An edge computing approach

Journal of Agriculture and Food Research
Traditional weed management often involves blanket herbicide spraying, resulting in substantial herbicide wastage, environmental concerns, and herbicide resistant issues.
Arjun Upadhyay, Sunil G C, Yu Zhang, Cengiz Koparan, Xin Sun   +4 more
doaj   +1 more source

Evaluating precision sprayers for targeted weed management in corn and soybean

Agrosystems, Geosciences & Environment
AbstractA targeted application of herbicides in commercial crop fields is desirable for reducing chemical inputs and promoting environmental sustainability. Precision sprayers, equipped with cameras and sensors, detect weeds in real‐time and apply herbicides only where needed.
Adam Leise, Mandeep Singh, Nicolas Cafaro La Menza, Stevan Knezevic, Amit J. Jhala   +4 more
openaire   +2 more sources

Modelling individual plants’ growth: competition of Viola arvensis and wheat

Frontiers in Agronomy
IntroductionCompetition by weeds is a severe threat to agricultural crops. While these days the broadcast of herbicides over the entire field is common praxis, new technologies promise to reduce chemical output by reducing the area sprayed.
Christoph von Redwitz, Janin Lepke, Janin Lepke, Otto Richter   +3 more
doaj   +1 more source