{
  "abstract": "Non-invasive, high-throughput phenotyping tools are needed that can identify environmental effects on plant structure and function to diagnose factors responsible for reduced growth in commercial and non-commercial settings. In this study, we explored whether the integration of 3D-multispectral (3D) and 2D-hyperspectral imaging (HSI), aided by machine learning (ML), could be used to identify environmental stress treatments imposed during plant growth. Controlled environment-grown Nicotiana Benthamiana plants were subjected to a range of abiotic treatments - including different growth irradiances, heat treatment and drought stress - with the treatments resulting in differences in shoot height, biomass, leaf area and spectral reflectance. ML models were trained to identify these treatments using morphological and spectral traits measured at 27, 29, 31, and 34 days after sowing (DAS). A 3D-multispectral scanner was used to obtain information on plant height, biomass, and leaf area. A visible and near-infrared (VNIR) HSI camera provided detailed spectral information for deriving spectral indices including the Normalised Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI) and Normalised Difference Red Edge (NDRE). Manual measurements provided baseline comparative data. The 3D-multispectral scanner reliably estimated above-ground traits, with high correlations between manual and scanner-derived measurements. The ML models accurately differentiated among environmental stress treatments, with the fused 3D + HSI model achieving the best overall predictive performance across all evaluated metrics compared with models based on either imaging modality alone. Results demonstrated the effectiveness of combining 3D-multispectral and 2D-HSI data with ML analyses for non-destructive, high-throughput phenotyping. The integration of these techniques enabled non-destructive, high-throughput identification of environmental stress treatments imposed during plant growth.",
  "abstract_shown": true,
  "affiliations": [
    "Division of Plant Sciences, Research School of Biology, The Australian National University, Australia.",
    "Australian Plant Phenomics Network, Research School of Biology, The Australian National University, Australia.",
    "School of Computing, The Australian National University, Australia.",
    "Medicago Inc., Québec, Canada.",
    "Direction Générale de la Recherche, des Programmes et des Partenariats, Ministère de l'Agriculture, des Pêcheries et de l'Alimentation du Québec, Québec, QC, Canada.",
    "Biological Data Science Institute, The Australian National University, Australia.",
    "Department of Biology, The University of Western Ontario, Canada.",
    "Nicholas School of the Environment, Duke University, USA.",
    "Agrifood Innovation Institute, The Australian National University, Australia."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 21,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Frederike Stock"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Saswat Panda"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Richard Poiré"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Timothy Brown"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Ayesha Akram"
    },
    {
      "affs": [
        2
      ],
      "name": "Liang Zheng"
    },
    {
      "affs": [
        2
      ],
      "name": "Huan Lei"
    },
    {
      "affs": [
        2
      ],
      "name": "Ruyi Zha"
    },
    {
      "affs": [
        2
      ],
      "name": "Mingrui Zhao"
    },
    {
      "affs": [
        3
      ],
      "name": "Sébastien Isabelle"
    },
    {
      "affs": [
        3
      ],
      "name": "Michèle Martel"
    },
    {
      "affs": [
        3
      ],
      "name": "Marc-André Comeau"
    },
    {
      "affs": [
        3,
        4
      ],
      "name": "Louis-Philippe Hamel"
    },
    {
      "affs": [
        3
      ],
      "name": "Pierre-Olivier Lavoie"
    },
    {
      "affs": [
        3
      ],
      "name": "Marc André D'Aoust"
    },
    {
      "affs": [
        3
      ],
      "name": "Hannah Reithinger"
    },
    {
      "affs": [
        3
      ],
      "name": "Pooja Saxena"
    },
    {
      "affs": [
        5
      ],
      "name": "Eric A Stone"
    },
    {
      "affs": [
        2
      ],
      "name": "Hongdong Li"
    },
    {
      "affs": [
        0,
        1,
        6,
        7
      ],
      "name": "Danielle A Way"
    },
    {
      "affs": [
        0,
        8
      ],
      "name": "Owen K Atkin"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/88be7899cprtg.bib",
  "cited_by": 0,
  "doi": "10.1016/j.plaphe.2026.100291",
  "fulltext_url": "https://europepmc.org/articles/PMC13744376",
  "id": "88be7899cprtg",
  "issns": [
    "2643-6515"
  ],
  "landing_url": "https://europepmc.org/article/MED/42999917",
  "language": "eng",
  "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": [
    [
      "openalex",
      "2303|Remote Sensing in Agriculture"
    ]
  ],
  "openalex": "W7221973649",
  "pdf_url": "https://europepmc.org/articles/PMC13744376?pdf=render",
  "pmcid": "PMC13744376",
  "pmid": "42999917",
  "published": "2026-10-15",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/88be7899cprtg.ris",
  "sources": [
    {
      "first_seen": "2026-11-09T15:20:41Z",
      "native_id": "MED:42999917",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42999917"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:2303|Remote Sensing in Agriculture",
      "subfield": "ecology"
    }
  ],
  "title": "Combining 3D-multispectral and hyperspectral imaging to identify environmental stress treatments imposed during plant growth.",
  "title_text": "Combining 3D-multispectral and hyperspectral imaging to identify environmental stress treatments imposed during plant growth.",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T15:20:41Z",
  "url": "https://research.draconitic.com/paper/88be7899cprtg",
  "venue": "Plant phenomics (Washington, D.C.)",
  "versions": []
}