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From light supplementation to spectral analysis: machine learning and hyperspectral reveals plant health status

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Bibliographic Details
Published in:Journal of Plant Pathology
Format: Online Article RSS Article
Published: 2026
Subjects:
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container_title Journal of Plant Pathology
description
discipline_display Genetics
discipline_facet Genetics
format Online Article
RSS Article
genre Journal Article
id rss_article:91826
institution FRELIP
journal_source_facet Journal of Plant Pathology
last_indexed 2026-06-16T02:03:04.397Z
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle From light supplementation to spectral analysis: machine learning and hyperspectral reveals plant health status
Genetics
General
Genetics
sub_discipline_display General
sub_discipline_facet General
subject_display Genetics
General
Genetics
Genetics
General
Genetics
subject_facet Genetics
General
Genetics
title From light supplementation to spectral analysis: machine learning and hyperspectral reveals plant health status
title_auth From light supplementation to spectral analysis: machine learning and hyperspectral reveals plant health status
title_full From light supplementation to spectral analysis: machine learning and hyperspectral reveals plant health status
title_fullStr From light supplementation to spectral analysis: machine learning and hyperspectral reveals plant health status
title_full_unstemmed From light supplementation to spectral analysis: machine learning and hyperspectral reveals plant health status
title_short From light supplementation to spectral analysis: machine learning and hyperspectral reveals plant health status
title_sort from light supplementation to spectral analysis: machine learning and hyperspectral reveals plant health status
topic Genetics
General
Genetics
url https://link.springer.com/article/10.1007/s42161-026-02232-w