Results 71 to 80 of about 144,958 (323)
Deep convolutional neural network models for weed detection in polyhouse grown bell peppers
Artificial Intelligence in Agriculture, 2022 Conventional weed management approaches are inefficient and non-suitable for integration with smart agricultural machinery. Automatic identification and classification of weeds can play a vital role in weed management contributing to better crop yields ...
A. Subeesh +7 more
doaj +1 more source
Efeitos do solo e clima numa vinha de uva de mesa com cultura de cobertura. Gestão da rega utilizando redes de sensores [PDF]
, 2017 [ENG] TThe use of mulches in vineyards and orchards is a traditional agricultural practice used with the aim of saving moisture, reducing weed growth and improving organic matter content in the soil. In table grape vineyards trained to overhead system in
Ferrara, Giuseppe +5 more
core +2 more sources
Generative Artificial Intelligence Shaping the Future of Agri‐Food Innovation
AgriFood: Journal of Agricultural Products for Food, EarlyView.Emerging use cases of generative artificial intelligence in agri‐food innovation. ABSTRACT The recent surge in generative artificial intelligence (AI), typified by models such as GPT, diffusion models, and large vision‐language architectures, has begun to influence the agri‐food sector.
Jun‐Li Xu +2 more
wiley +1 more source
Targeted weed management of Palmer amaranth using robotics and deep learning (YOLOv7)
Frontiers in Robotics and AIEffective weed management is a significant challenge in agronomic crops which necessitates innovative solutions to reduce negative environmental impacts and minimize crop damage.
Amlan Balabantaray +6 more
doaj +1 more source
Agribusiness, EarlyView.ABSTRACT Smallholder farmers are reverting to traditional production methods due to the high opportunity costs and unintended consequences of new technologies. This study focuses on row planting technology, which is labor‐intensive and slow without mechanized operations.
Emmanuel Tetteh Jumpah +4 more
wiley +1 more source
Agribusiness, EarlyView.ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani +3 more
wiley +1 more source
Combining physical and cultural weed control with biological methods – prospects for integrated non-chemical weed management strategies [PDF]
, 2004 The paper deals with the possibilities of combining physical weed control with biological weed ...
Hatcher, Scientist Paul +1 more
core
Economics of land‐based carbon mitigation
American Journal of Agricultural Economics, EarlyView.Abstract Agricultural land holds tremendous potential to contribute to net zero greenhouse gas emission goals by providing low carbon renewable energy to displace fossil fuels and by serving as a sink for sequestering carbon in the soil with climate‐smart practices. This potential is, however, far from being realized.
Madhu Khanna
wiley +1 more source
Frontiers in AgronomyIntroductionUnderstanding regional weed control practices and stakeholder perspectives is essential to guide the development and adoption of novel weed management technologies.
Zaim Ugljic +5 more
doaj +1 more source
Dataset of annotated food crops and weed images for robotic computer vision control
Data in Brief, 2020 Weed management technologies that can identify weeds and distinguish them from crops are in need of artificial intelligence solutions based on a computer vision approach, to enable the development of precisely targeted and autonomous robotic weed ...
Kaspars Sudars +4 more
doaj +1 more source