Year: 2026
Type: article
Abstract: Choosing an optimal crop variety to plant is one of the most important decisions faced by farmers. Nowadays, recommender systems are almost ubiquitous in several human activities, except in agriculture, and more deeply absent in crop variety decision‐making. This commentary presents the potential applications of crop variety recommender systems, describing the elements required for their implementation and adoption, and proposing new research areas to address the major research gaps. This work aims to motivate the scientific community at the intersection of agriculture, environmental science, data science, digital technologies, and computer science to work toward the development and application of recommender systems to support crop variety decision‐making.
DOI: 10.1002/ael2.70057
Author: David Brown
Institution: Cornell University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $1,900
Awards: G1509922050, Cornell University - to develop efficient cassava breeding programs with accelerated genetic gains, leading to the release of improved cassava cultivars that meet the a..., International Potato Center - to develop modern and efficient breeding systems for important root, tuber, and banana staple crops for Sub-Saharan Africa that provide superior pr...
OpenAlex ID: W7125364424