ArticleFrontiers in plant science2023
Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality.
Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Novel approaches for understanding and improving the effectiveness of seed biopriming.Scientific reports · 2026Article
- Mycotoxins and plant diseases in a changing climate: from pathogen ecology to smart surveillance and mitigation strategies.Frontiers in fungal biology · 2026Review
- Towards resilience: Transcriptional insights on flavonoid biosynthesis during peanut seed maturation phases.PloS one · 2025Article
- Detection of Mycotoxin Contamination in Foods Using Artificial Intelligence: A Review.Foods (Basel, Switzerland) · 2024Review
- Tropical peanut maturation scale for harvesting seeds with superior quality.Frontiers in plant science · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The sanitary quality of seed is essential in agriculture. This is because pathogenic fungi compromise seed physiological quality and prevent the formation of plants in the field, which causes losses to farmers. Multispectral images technologies coupled with machine learning algorithms can optimize the identification of healthy peanut seeds, greatly improving the sanitary quality. The objective was to verify whether multispectral images technologies and artificial intelligence tools are effective for discriminating pathogenic fungi in tropical peanut seeds. For this purpose, dry peanut seeds infected by fungi (
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