Download
Griffo-Sci Rep-2024.pdf 2,20MB
WeightNameValue
1000 Titel
  • Non-invasive methods to assess seed quality based on ultra-weak photon emission and delayed luminescence
1000 Autor/in
  1. Griffo, Adriano |
  2. Sehmisch, Stefanie |
  3. Laager, Frédéric |
  4. Pagano, Andrea |
  5. Balestrazzi, Alma |
  6. Macovei, Anca |
  7. Börner, Andreas |
1000 Erscheinungsjahr 2024
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-11-05
1000 Erschienen in
1000 Quellenangabe
  • 14(1):26838
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://dx.doi.org/10.1038/s41598-024-74207-9 |
  • https://pmc.ncbi.nlm.nih.gov/articles/PMC11538308/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Seed quality is the set of physical, genetic, and physiological characteristics, reflecting the overall germination potential. Maintaining an optimal seed quality is essential for agriculture and seed banks to preserve genetic diversity. Compared to conventional methods (e.g., germination tests), non-invasive approaches allow a more sustainable and rapid evaluation of seed quality but this is limited by high costs. The measurement of ultra-weak photon emission (UPE) and delayed fluorescence (DL), defined as biological phenomena potentially related to the physiological status of living systems, may represent a suitable approach to estimate seed quality. To test this hypothesis, seeds of five agriculturally relevant legume species (Phaseolus vulgaris L., Lathyrus sativus L., Cicer arietinum L., Pisum sativum L., and Vicia faba L.), stored at different conditions (room temperature or -18 degrees C) for several years, were analysed using a LIANA(c) prototype to collect data regarding DL and UPE occurring after UV excitation. The obtained data were integrated with germination parameters which underline species-specific behaviours in response to storage conditions. The prediction models show variable efficiency in classifying seeds based on germination which underline species-dependent links between photon emission and seed quality. Therefore, these measurements represent novel, non-invasive, and rapid approaches to evaluate seed quality.
1000 Sacherschließung
lokal machine learning
lokal delayed luminescence
lokal seed quality
lokal non-invasive assessment
lokal ultra-weak photon emission
lokal Leguminosae
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/R3JpZmZvLCBBZHJpYW5v|https://frl.publisso.de/adhoc/uri/U2VobWlzY2gsIFN0ZWZhbmll|https://frl.publisso.de/adhoc/uri/TGFhZ2VyLCBGcsOpZMOpcmlj|https://frl.publisso.de/adhoc/uri/UGFnYW5vLCBBbmRyZWE=|https://frl.publisso.de/adhoc/uri/QmFsZXN0cmF6emksIEFsbWE=|https://frl.publisso.de/adhoc/uri/TWFjb3ZlaSwgQW5jYSA=|https://orcid.org/0000-0003-3301-9026
1000 Label
1000 Förderer
  1. Bayer Foundation |
1000 Fördernummer
  1. -
1000 Förderprogramm
  1. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Bayer Foundation |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6489112.rdf
1000 Erstellt am 2024-11-21T13:59:30.658+0100
1000 Erstellt von 325
1000 beschreibt frl:6489112
1000 Bearbeitet von 317
1000 Zuletzt bearbeitet 2025-02-24T14:25:36.139+0100
1000 Objekt bearb. Mon Feb 24 14:25:27 CET 2025
1000 Vgl. frl:6489112
1000 Oai Id
  1. oai:frl.publisso.de:frl:6489112 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

View source