{
  "abstract": "Within-field diversification, notably through cereal legume intercropping, is a major lever of the agroecological transition. Breeding cultivars adapted to intercropping requires major changes in breeding practices, owing to strong genotype-by-stand-type interactions and the high spatial heterogeneity of low-input field trials. Part of this heterogeneity stems from variation in plant density, a first yield component that strongly influences resource competition and is critical to monitor in intercrops. Given the many plots in such platforms, high-throughput phenotyping of plant density is essential. Over two seasons, we designed a large field trial involving 200 wheat cultivars observed as sole crop as well as intercropped with two pea tester cultivars, in a pseudo-randomized complete block design. Plant density was manually counted on 40 cultivars, alongwith UAV flights at both high and low altitudes. We propose a method to predict plant density from millimeter-resolution RGB images, using linear regression on log-transformed fractional vegetation cover and additional colorimetric and textural indices. We predict total density of wheat or pea in sole crops, or the combined pea+wheat total density in intercrops with relative RMSE of 19.2% and 27.4% depending on season. Thanks to the pipeline, total plant density was predicted across the entire trial, comprising more than 1,000 microplots (200 varieties); this density showed high heritability (0.75-0.85). We provide guidelines regarding the composition of the training set for such intercrop trials. High-throughput phenotyping approaches such as the one proposed here can be instrumental in mobilizing genetic diversity for agroecology.",
  "abstract_shown": true,
  "affiliations": [
    "INRAE - GQE-Le-Moulon"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "V. F. A. FREITAS"
    },
    {
      "name": "j. ENJALBERT"
    },
    {
      "name": "T. FLUTRE"
    },
    {
      "name": "J.-M. GILLIOT"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6gy9y3prm8934.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.09.757598",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.09.757598v1.full",
  "id": "6gy9y3prm8934",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.09.757598v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "genetics"
    ],
    [
      "openalex",
      "1110|Smart Agriculture and AI"
    ]
  ],
  "openalex": "W7222457780",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.09.757598v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-09",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6gy9y3prm8934.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:28:10Z",
      "native_id": "10.64898/2026.10.09.757598",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.09.757598v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:genetics",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "A high-throughput UAV millimetric imaging pipeline for plant density phenotyping reveals high heritability in wheat-pea sole crops and intercrops.",
  "title_text": "A high-throughput UAV millimetric imaging pipeline for plant density phenotyping reveals high heritability in wheat-pea sole crops and intercrops.",
  "type": "preprint",
  "updated_at": "2026-10-30T12:28:10Z",
  "url": "https://research.draconitic.com/paper/6gy9y3prm8934",
  "venue": "bioRxiv",
  "versions": []
}