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Article
Agriculture 4.0 technologies like Artificial Intelligence (AI), the Internet of Things, Computer Vision, and Robotics, have revolutionized the agricultural sector. But the adoption of digital technologies has arguably created new or exacerbated [...]
Article
Water scarcity is a pressing global issue that needs to be faced. The United Nations highlights that only about 31 percent of the population is not characterized by water stress, meaning that the world?s freshwater resources are unevenly distrib[...]
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The past decade has witnessed the rapid development and adoption of machine and deep learning (ML & DL) methodologies in agricultural systems, showcased by great successes in applications such as smart crop management, smart plant breeding, smar[...]
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M.T. Kuska ; M. Wahabzada ; S. Paulus |Since the launch of the “Generative Pre-trained Transformer 3.5”, ChatGPT by Open, artificial intelligence (AI) has been a main discussion topic in public. Especially large language models (LLM), so called “intelligent” chatbots, and the possibi[...]
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Agriculture is the backbone of numerous developing and emerging economies, supporting millions of livelihoods and playing a crucial role. The transformative integration of AI-driven tools, big-data analytics, and advanced technologies, such as d[...]
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Article
Agriculture is the backbone of many economies across the globe [...]
Article
O. Rozenstein ; Y. Cohen ; V. Alchanatis ; K. Behrendt ; D.J. Bonfil ; G. Eshel ; A. Harari ; W.E. Harris ; I. Klapp ; Y. Laor ; R. Linker ; T. Paz-Kagan ; S. Peets ; S.M. Rutter ; Y. Salzer ; J. Lowenberg-DeBoer |Sustainability in our food and fiber agriculture systems is inherently knowledge intensive. It is more likely to be achieved by using all the knowledge, technology, and resources available, including data-driven agricultural technology and preci[...]
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M. Vasileiou ; L.S. Kyrgiakos ; C. Kleisiari ; G. Kleftodimos ; G. Vlontzos ; H. Belhouchette ; P.M. Pardalos |In the face of increasing agricultural demands and environmental concerns, the effective management of weeds presents a pressing challenge in modern agriculture. Weeds not only compete with crops for resources but also pose threats to food safet[...]
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This article presents findings from interviews that were conducted with agriculture and food system researchers to understand their views about what it means to conduct ‘responsible’ or ‘trustworthy’ artificial intelligence (AI) research. Findin[...]
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This paper presents an idea analysis of AI in the policy documents and reports of the United Nations, the European Union, and the World Economic Forum. The three organisations expect AI to contribute to sustainability and a prosperous future wit[...]
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Emerging technologies associated with Artificial Intelligence (AI) have enabled improvements in global food security situations. However, there is a limited understanding regarding the extent to which stakeholders are involved in AI modelling re[...]
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This article discusses the potential of artificial intelligence (AI) in providing human-like intelligence from data to support intelligent decision-making and proposes a few researchable issues for addressing challenges making AI useful in agric[...]
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A. Patel ; A. Kethavath ; N.L. Kushwaha ; A. Naorem ; M. Jagadale ; K.R. Sheetal ; P.S. Renjith |The challenges of urbanization, land degradation, water scarcity, and climate change are threatening agricultural systems and food security. Therefore, it is essential to manage land and water resources sustainably to improve productivity and ad[...]
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E.M.B.M. Karunathilake ; A.T. Le ; S. Heo ; Y.S. Chung ; S. Mansoor |Precision agriculture employs cutting-edge technologies to increase agricultural productivity while reducing adverse impacts on the environment. Precision agriculture is a farming approach that uses advanced technology and data analysis to maxim[...]
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In the context of water scarcity, soil erosion, and biodiversity decline, the Mediterranean basin urges to manage its nearly hundred coastal watersheds in a coordinated manner. To this end, we propose an integrated approach to model socio-ecolog[...]
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H. Onyeaka ; P. Tamasiga ; U.M. Nwauzoma ; T. Miri ; U.C. Juliet ; O. Nwaiwu ; A.A. Akinsemolu |Food waste is a global issue with significant economic, social, and environmental impacts. Addressing this problem requires a multifaceted approach; one promising avenue is using artificial intelligence (AI) technologies. This article explores t[...]
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A. Taneja ; G. Nair ; M. Joshi ; S. Sharma ; S. Sharma ; A.R. Jambrak ; E. Roselló-Soto ; F.J. Barba ; J.M. Castagnini ; N. Leksawasdi ; Y. Phimolsiripol |Artificial intelligence (AI) involves the development of algorithms and computational models that enable machines to process and analyze large amounts of data, identify patterns and relationships, and make predictions or decisions based on that [...]
Article
R.A. El Behairy ; H.M. El Arwash ; A.A. El Baroudy ; M.M. Ibrahim ; E.S. Mohamed ; N.Y. Rebouh ; M.S. Shokr |Developing countries all over the world face numerous difficulties with regard to food security. The purpose of this research is to develop a new approach for evaluating wheat’s suitability for cultivation. To this end, geographical information [...]
Article
T.P. Tomich ; C. Hoy ; M.R. Dimock ; A.D. Hollander ; P.R. Huber ; A. Hyder ; M.C. Lange ; C.M. Riggle ; M.T. Roberts ; J.F. Quinn |Public interest in where food comes from and how it is produced, processed, and distributed has increased over the last few decades, with even greater focus emerging during the COVID-19 pandemic. Mounting evidence and experience point to disturb[...]
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Article
F. Mohammadi Kashka ; Z. Tahmasebi Sarvestani ; H. Pirdashti ; A. Motevali ; M. Nadi ; M. Valipour |The increase in population has increased the need for agricultural and food products, and thus agricultural production should be increased. This goal may cause increases in emissions and environmental impacts by increasing the consumption of agr[...]
Article
Machine learning (ML) and its branch, deep learning (DL), is rapidly evolving and gaining popularity as it outperforms other, more traditional methods in different areas of agriculture. However, ML and DL techniques must be correctly applied to [...]
Rapport, Expertise, Working Paper
J. De Baerdemaeker, coord. ; S. Hemming ; G. Polder ; A. Chauhan ; A. Petropoulou ; F. Rovira-Más ; D. Moshou ; G. Wyseure ; T. Norton ; B. Nicolai ; F. Hennig-Possenti ; I. Hostens | Strasbourg [France] : European Parliament | 2023An increasingly digitised society involves recording human activity and monitoring products and processes. In the agri-food sector this gives rise to large quantities of data. At the same time, data is also generated for research and scientific [...]
Ouvrage
Il a fallu 3 600 jours à Netflix pour atteindre 100 millions d’utilisateurs, il en aura fallu seulement 60 à ChatGPT L’essor fulgurant de l’IA conversationnelle et générative redéfinit notre monde à une vitesse encore jamais vue à l’ère technol[...]
Article
N. Chamara ; M.D. Islam ; G. Bai ; Y. Shi ; Y. Ge |CONTEXT Automated monitoring of the soil-plant-atmospheric continuum at a high spatiotemporal resolution is a key to transform the labor-intensive, experience-based decision making to an automatic, data-driven approach in agricultural production[...]
Article
L. Mohimont ; F. Alin ; M. Rondeau ; N. Gaveau ; L.A. Steffenel |During the last decades, researchers have developed novel computing methods to help viticulturists solve their problems, primarily those linked to yield estimation of their crops. This article aims to summarize the existing research associated w[...]
Article
Predicting crop yields is one of the most challenging tasks in agriculture. It plays an essential role in decision making at global, regional, and field levels. Soil, meteorological, environmental, and crop parameters are used to predict crop yi[...]
Article
The digitalization of data has resulted in a data tsunami in practically every industry of data-driven enterprise. Furthermore, man-to-machine (M2M) digital data handling has dramatically amplified the information wave. There has been a signific[...]
Article
A. Sharma ; M. Georgi ; M. Tregubenko ; A. Tselykh ; A. Tselykh |The increasing demand of smart agriculture has led to the significant growth and development in the field of crop estimation and prediction improving its productivity. The analysis of crop age status is very important to prevent the excessive fe[...]
