Robust seed germination prediction using deep learning and RGB image data

Abstract Achieving seed germination quality standards poses a real challenge to seed companies as they are compelled to abide by strict certification rules, while having only partial seed separation solutions at their disposal. This discrepancy results with wasteful disqualification of seed lots hol...

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Autores principales:	Yuval Nehoshtan, Elad Carmon, Omer Yaniv, Sharon Ayal, Or Rotem
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e6d8b5732c46423491df96fce6f6479b
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id	oai:doaj.org-article:e6d8b5732c46423491df96fce6f6479b
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spelling	oai:doaj.org-article:e6d8b5732c46423491df96fce6f6479b2021-11-14T12:19:14ZRobust seed germination prediction using deep learning and RGB image data10.1038/s41598-021-01712-62045-2322https://doaj.org/article/e6d8b5732c46423491df96fce6f6479b2021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-01712-6https://doaj.org/toc/2045-2322Abstract Achieving seed germination quality standards poses a real challenge to seed companies as they are compelled to abide by strict certification rules, while having only partial seed separation solutions at their disposal. This discrepancy results with wasteful disqualification of seed lots holding considerable amounts of good seeds and further translates to financial losses and supply chain insecurity. Here, we present the first-ever generic germination prediction technology that is based on deep learning and RGB image data and facilitates seed classification by seed germinability and usability, two facets of germination fate. We show technology competence to render dozens of disqualified seed lots of seven vegetable crops, representing different genetics and production pipelines, industrially appropriate, and to adequately classify lots by utilizing available crop-level image data, instead of lot-specific data. These achievements constitute a major milestone in the deployment of this technology for industrial seed sorting by germination fate for multiple crops.Yuval NehoshtanElad CarmonOmer YanivSharon AyalOr RotemNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yuval Nehoshtan Elad Carmon Omer Yaniv Sharon Ayal Or Rotem Robust seed germination prediction using deep learning and RGB image data
description	Abstract Achieving seed germination quality standards poses a real challenge to seed companies as they are compelled to abide by strict certification rules, while having only partial seed separation solutions at their disposal. This discrepancy results with wasteful disqualification of seed lots holding considerable amounts of good seeds and further translates to financial losses and supply chain insecurity. Here, we present the first-ever generic germination prediction technology that is based on deep learning and RGB image data and facilitates seed classification by seed germinability and usability, two facets of germination fate. We show technology competence to render dozens of disqualified seed lots of seven vegetable crops, representing different genetics and production pipelines, industrially appropriate, and to adequately classify lots by utilizing available crop-level image data, instead of lot-specific data. These achievements constitute a major milestone in the deployment of this technology for industrial seed sorting by germination fate for multiple crops.
format	article
author	Yuval Nehoshtan Elad Carmon Omer Yaniv Sharon Ayal Or Rotem
author_facet	Yuval Nehoshtan Elad Carmon Omer Yaniv Sharon Ayal Or Rotem
author_sort	Yuval Nehoshtan
title	Robust seed germination prediction using deep learning and RGB image data
title_short	Robust seed germination prediction using deep learning and RGB image data
title_full	Robust seed germination prediction using deep learning and RGB image data
title_fullStr	Robust seed germination prediction using deep learning and RGB image data
title_full_unstemmed	Robust seed germination prediction using deep learning and RGB image data
title_sort	robust seed germination prediction using deep learning and rgb image data
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/e6d8b5732c46423491df96fce6f6479b
work_keys_str_mv	AT yuvalnehoshtan robustseedgerminationpredictionusingdeeplearningandrgbimagedata AT eladcarmon robustseedgerminationpredictionusingdeeplearningandrgbimagedata AT omeryaniv robustseedgerminationpredictionusingdeeplearningandrgbimagedata AT sharonayal robustseedgerminationpredictionusingdeeplearningandrgbimagedata AT orrotem robustseedgerminationpredictionusingdeeplearningandrgbimagedata
_version_	1718429321455992832

Robust seed germination prediction using deep learning and RGB image data

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