ArticleComputational intelligence and neuroscience2022
Suitability Evaluation of Crop Variety via Graph Neural Network.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Benchmarking hybrid CNN and transformer backbones with graph convolution networks (GCN) for flower growth-stage classification.Scientific reports · 2026Article
- Ontology-driven dual-channel relational graph convolutional network (DCR-GCN) for lettuce leaf phenotype classification.Plant methods · 2026Article
- AI-enabled Barilai-Borwein-Blinder-Oaxaca-Bernoulli Deep Classifier for Enhanced Crop Yield Prediction.Scientific reports · 2025Article
- Optimizing arable land suitability evaluation using improved suitability functions in the Anning River Basin.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the continuous growth of the global population, insufficient food production has become an urgent problem to be solved in most countries. At present, using artificial intelligence technology to improve suitability between land and crop varieties to increase crop yields has become a consensus among agricultural researchers. However, there are still many problems in existing works, such as limited crop phenotypic data and the poor performance of artificial intelligence models. In this regard, we take maize as an example to collect a large amount of environmental climate and crop phenotypic traits data at multiple experimental sites and construct an extensive dataset. Then, we introduce a graph neural network model to learn crop suitability evaluation and finally achieve a good evaluation effect. The evaluation results of the model can not only provide a reference for expert evaluation but also judge the suitability of the variety to other test trial sites according to the data of the current one, so as to guide future breeding experiments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.