{
  "abstract": "Potato (Solanum tuberosum L.) is a staple crop crucial to global food security, yet its production is severely threatened by late blight (LB), caused by Phytophthora infestans, one of the most destructive plant diseases worldwide. Breeding programs for LB resistance have traditionally relied on labor-intensive and subjective visual assessments, which limit scalability and consistency, particularly in early-generation trials. Unmanned aerial vehicle (UAV)-based remote sensing combined with machine learning (ML) offers a promising alternative for objective, high-throughput disease phenotyping. This study evaluated the potential of this technology to estimate LB severity at the genotype level across two large potato trials in Peru comprising 2,745 breeding clones and 492 genebank accessions. We compared vegetation index–based approaches with a ML framework that integrates K-means clustering and Kernel Ridge Regression (KRR). While NDVI correlated strongly with visually assessed LB severity, particularly at advanced stages, the multispectral KRR approach outperformed linear NDVI models by capturing nonlinear relationships between spectral response and disease progression. Best linear unbiased estimates (BLUEs) of LB severity from both models were strongly and consistently related to the area under the disease progress curve (AUDPC), particularly in later UAV acquisitions. Selection coincidence with AUDPC-based rankings was substantially higher at intermediate to advanced stages of disease progression, indicating that a single UAV inspection at those stages captures enough phenotypic variation to distinguish genotypes. UAV-based multispectral phenotyping integrated with ML, therefore offers a practical, scalable alternative to the time-consuming visual assessments traditionally used in potato breeding programs.",
  "abstract_shown": true,
  "affiliations": [
    "International Potato Center (CIP), Lima, Peru",
    "Universidad de Huánuco, Huánuco, Peru",
    "Pontificia Universidad Católica del Perú, Lima, Peru",
    "Programa Nacional de Investigación Científica y Estudios Avanzados - Prociencia-Concytec, Lima, Peru"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 13,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Hildo Loayza",
      "orcid": "0000-0002-4145-5453"
    },
    {
      "affs": [
        0
      ],
      "name": "Johan Ninanya",
      "orcid": "0000-0001-9499-2503"
    },
    {
      "affs": [
        2
      ],
      "name": "Susan Palacios"
    },
    {
      "affs": [
        0
      ],
      "name": "Luis Silva",
      "orcid": "0000-0002-3660-7344"
    },
    {
      "affs": [
        1
      ],
      "name": "Fernando Pujaico Rivera",
      "orcid": "0000-0002-4970-2818"
    },
    {
      "affs": [
        0
      ],
      "name": "Javier Rinza",
      "orcid": "0000-0001-9320-3146"
    },
    {
      "affs": [
        3
      ],
      "name": "Manuel Gastelo"
    },
    {
      "affs": [
        0
      ],
      "name": "Mariela Aponte"
    },
    {
      "affs": [
        0
      ],
      "name": "Jan F. Kreuze",
      "orcid": "0000-0002-6116-9200"
    },
    {
      "affs": [
        0
      ],
      "name": "Hannele Lindqvist-Kreuze"
    },
    {
      "affs": [
        0
      ],
      "name": "Bettina Heider"
    },
    {
      "affs": [
        0
      ],
      "name": "Moctar Kante"
    },
    {
      "affs": [
        0
      ],
      "name": "David A. Ramírez",
      "orcid": "0000-0003-4546-9745"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6gsf5tsn119g1.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0347446",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13730388/",
  "id": "6gsf5tsn119g1",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0347446",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Agriculture"
    ],
    [
      "heading",
      "Biology and Life Sciences"
    ],
    [
      "heading",
      "Cloning"
    ],
    [
      "heading",
      "Cluster Analysis"
    ],
    [
      "heading",
      "Crop Science"
    ],
    [
      "heading",
      "Crops"
    ],
    [
      "heading",
      "Eukaryota"
    ],
    [
      "heading",
      "K Means Clustering"
    ],
    [
      "heading",
      "Linear Regression Analysis"
    ],
    [
      "heading",
      "Mathematical and Statistical Techniques"
    ],
    [
      "heading",
      "Mathematics"
    ],
    [
      "heading",
      "Molecular Biology"
    ],
    [
      "heading",
      "Molecular Biology Techniques"
    ],
    [
      "heading",
      "Organisms"
    ],
    [
      "heading",
      "Physical Sciences"
    ],
    [
      "heading",
      "Plant Pathology"
    ],
    [
      "heading",
      "Plant Science"
    ],
    [
      "heading",
      "Plants"
    ],
    [
      "heading",
      "Potato"
    ],
    [
      "heading",
      "Regression Analysis"
    ],
    [
      "heading",
      "Research Article"
    ],
    [
      "heading",
      "Research and Analysis Methods"
    ],
    [
      "heading",
      "Solanum"
    ],
    [
      "heading",
      "Statistical Methods"
    ],
    [
      "heading",
      "Statistics"
    ],
    [
      "heading",
      "Vegetable Crops"
    ],
    [
      "heading",
      "Vegetables"
    ],
    [
      "plos",
      "/Biology and life sciences/Agriculture/Crop science/Crops"
    ],
    [
      "plos",
      "/Biology and life sciences/Agriculture/Crop science/Crops/Vegetable crops"
    ],
    [
      "plos",
      "/Biology and life sciences/Molecular biology/Molecular biology techniques/Cloning"
    ],
    [
      "plos",
      "/Biology and life sciences/Organisms/Eukaryota/Plants/Solanum/Potato"
    ],
    [
      "plos",
      "/Biology and life sciences/Organisms/Eukaryota/Plants/Vegetables"
    ],
    [
      "plos",
      "/Biology and life sciences/Organisms/Eukaryota/Plants/Vegetables/Potato"
    ],
    [
      "plos",
      "/Biology and life sciences/Plant science/Plant pathology"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Statistics/Statistical methods/Regression analysis/Linear regression analysis"
    ],
    [
      "plos",
      "/Research and analysis methods/Mathematical and statistical techniques/Cluster analysis/k means clustering"
    ],
    [
      "plos",
      "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Regression analysis/Linear regression analysis"
    ],
    [
      "plos",
      "/Research and analysis methods/Molecular biology techniques/Cloning"
    ]
  ],
  "openalex": null,
  "pdf_url": null,
  "pmcid": "PMC13730388",
  "pmid": "42976195",
  "published": "2026-11-03",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/6gsf5tsn119g1.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T12:20:43Z",
      "native_id": "10.1371/journal.pone.0347446",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.pone.0347446"
    },
    {
      "first_seen": "2026-11-07T12:22:57Z",
      "native_id": "PMC13730388",
      "source": "pmc",
      "url": "https://doi.org/10.1371/journal.pone.0347446"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "plos:molecular biology",
      "subfield": "molecular-biology"
    },
    {
      "field": "biology",
      "origin": "plos:plant science",
      "subfield": "plant-biology"
    },
    {
      "field": "mathematics",
      "origin": "plos:statistical methods",
      "subfield": "statistics"
    }
  ],
  "title": "Prediction of late blight severity in a large panel of potato genotypes using low-altitude aerial images and machine learning methods",
  "title_text": "Prediction of late blight severity in a large panel of potato genotypes using low-altitude aerial images and machine learning methods",
  "type": "peer-reviewed",
  "updated_at": "2026-11-07T12:22:57Z",
  "url": "https://research.draconitic.com/paper/6gsf5tsn119g1",
  "venue": "PLOS One",
  "versions": []
}