{
  "abstract": "Background: Visible-near infrared (Vis-NIR) spectroscopy is widely used for non-destructive plant monitoring; however, in time-series experiments, signals of interest are frequently masked by diurnal rhythms and systematic measurement drift. This limits the ability to clearly detect plant responses to stress in spectral datasets. Results: This study presents a multi-sensor approach to monitor the onset and recovery dynamics of polyethylene glycol (PEG)-induced osmotic stress in sunflower (Helianthus annuus L.). Initial multivariate exploration using principal component analysis (PCA) indicated that temporal and environmental variability dominated the dataset, more than treatment-related effects. The application of REP-ASCA (Reduction of Repeatability Error for ANOVA-Simultaneous Component Analysis), a design-driven multivariate approach, allowed the separation of stress-related spectral variation from temporal and measurement-related effects. This revealed a rapid divergence between control and PEG-treated plants following PEG application. The REP-ASCA scores associated with the PEG factor showed a reversible trajectory, returning towards control levels after PEG removal, consistent with the transient nature of the applied stress. This behaviour contrasted with the progressive changes observed in pigment-related indices, suggesting that the spectral components extracted by REP-ASCA primarily capture fast and reversible biophysical responses. Conclusions: These results highlight the potential of combining high-resolution Vis-NIR spectroscopy with design-driven multivariate analysis to disentangle treatment effects from strong temporal variability in plant time-series data.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "name": "Ingi Abdelmeguid"
    },
    {
      "name": "Daphné Héran"
    },
    {
      "name": "Maxime Ryckewaert"
    },
    {
      "name": "David Bastidon"
    },
    {
      "name": "Ryad Bendoula"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/35g9j9e8f59kq.bib",
  "cited_by": 0,
  "doi": "10.1007/s42452-026-09299-1",
  "fulltext_url": null,
  "id": "35g9j9e8f59kq",
  "issns": [
    "3004-9261"
  ],
  "landing_url": "https://hal.inrae.fr/hal-05855090v1",
  "language": "en",
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
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  "openalex": "W7213257575",
  "pdf_url": "https://hal.inrae.fr/hal-05855090/document",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-16",
  "publisher": "Springer",
  "ris": "https://research.draconitic.com/paper/35g9j9e8f59kq.ris",
  "sources": [
    {
      "first_seen": "2026-11-07T12:20:25Z",
      "native_id": "hal-05855090",
      "source": "hal",
      "url": "https://hal.inrae.fr/hal-05855090v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "hal:1.sdv.gen",
      "subfield": "genetics-genomics"
    },
    {
      "field": "physics",
      "origin": "hal:2.phys.phys.phys-data-an",
      "subfield": "computational"
    }
  ],
  "title": "Distinguishing plant biophysical stress responses from temporal variability using vis–NIR spectroscopy",
  "title_text": "Distinguishing plant biophysical stress responses from temporal variability using vis–NIR spectroscopy",
  "type": "peer-reviewed",
  "updated_at": "2026-11-08T12:20:49Z",
  "url": "https://research.draconitic.com/paper/35g9j9e8f59kq",
  "venue": "Discover Applied Sciences",
  "versions": []
}