Foundation models in smart agriculture: Basics, opportunities, and challenges
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 …
learning (ML & DL) methodologies in agricultural systems, showcased by great successes in …
[HTML][HTML] Advancements in Agricultural Ground Robots for Specialty Crops: An Overview of Innovations, Challenges, and Prospects
Robotic technologies are affording opportunities to revolutionize the production of specialty
crops (fruits, vegetables, tree nuts, and horticulture). They offer the potential to automate …
crops (fruits, vegetables, tree nuts, and horticulture). They offer the potential to automate …
Large language models can help boost food production, but be mindful of their risks
Coverage of ChatGPT-style large language models (LLMs) in the media has focused on
their eye-catching achievements, including solving advanced mathematical problems and …
their eye-catching achievements, including solving advanced mathematical problems and …
Feasibility of machine learning-based rice yield prediction in India at the district level using climate reanalysis and remote sensing data
D De Clercq, A Mahdi - Agricultural Systems, 2024 - Elsevier
CONTEXT Yield forecasting, the science of predicting agricultural productivity before the
crop harvest occurs, helps a wide range of stakeholders make better decisions around …
crop harvest occurs, helps a wide range of stakeholders make better decisions around …
[HTML][HTML] Digital evolution and twin miracle of sugarcane breeding
Context Sugarcane, as an important economic crop, faces challenges such as long breeding
cycles, low genetic improvement efficiency, and complex breeding operations. Method In …
cycles, low genetic improvement efficiency, and complex breeding operations. Method In …
[HTML][HTML] Security threats to agricultural artificial intelligence: Position and perspective
In light of their remarkable predictive capabilities, artificial intelligence (AI) models driven by
deep learning (DL) have witnessed widespread adoption in the agriculture sector …
deep learning (DL) have witnessed widespread adoption in the agriculture sector …
[PDF][PDF] Reconnoitering Precision Agriculture and Resource Management: A Comprehensive Review from an Extension Standpoint on Artificial Intelligence and …
Introduction: The agriculture sector is a crucial driver of global economic growth, especially
in the face of the increasing demand for food production to sustain a growing population …
in the face of the increasing demand for food production to sustain a growing population …
Levelling the field: A review of the ICT revolution and agricultural extension in the Global South
Abstract Information and communications technology has evolved significantly over the last
seven decades, beginning with radio and video vans and culminating in the rise of …
seven decades, beginning with radio and video vans and culminating in the rise of …
[HTML][HTML] Silicon Savannah and smallholder farming: How can digitalization contribute to sustainable agricultural transformation in Africa?
CONTEXT The development of smallholder agriculture in Africa faces numerous challenges.
While digitalization is seen as a transformative opportunity for the continent's agricultural …
While digitalization is seen as a transformative opportunity for the continent's agricultural …
AgXQA: A benchmark for advanced Agricultural Extension question answering
Large language models (LLMs) have revolutionized various scientific fields in the past few
years, thanks to their generative and extractive abilities. However, their applications in the …
years, thanks to their generative and extractive abilities. However, their applications in the …