René Gislum

The Use of Image-Spectroscopy Technology as a Diagnostic Method for Seed Health Testing and Variety Identification

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The Use of Image-Spectroscopy Technology as a Diagnostic Method for Seed Health Testing and Variety Identification. / Vrešak, Martina; Halkjaer Olesen, Merete; Gislum, René; Bavec, Franc; Ravn Jørgensen, Johannes.

In: PLOS ONE, Vol. 11, No. 3, 24.03.2016, p. e0152011.

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Vrešak, Martina ; Halkjaer Olesen, Merete ; Gislum, René ; Bavec, Franc ; Ravn Jørgensen, Johannes. / The Use of Image-Spectroscopy Technology as a Diagnostic Method for Seed Health Testing and Variety Identification. In: PLOS ONE. 2016 ; Vol. 11, No. 3. pp. e0152011.

Bibtex

@article{8d2a404d358543c5b7dc760093133344,
title = "The Use of Image-Spectroscopy Technology as a Diagnostic Method for Seed Health Testing and Variety Identification",
abstract = "Application of rapid and time-efficient health diagnostic and identification technology in the seed industry chain could accelerate required analysis, characteristic description and also ultimately availability of new desired varieties. The aim of the study was to evaluate the potential of multispectral imaging and single kernel near-infrared spectroscopy (SKNIR) for determination of seed health and variety separation of winter wheat (Triticum aestivum L.) and winter triticale (Triticosecale Wittm. & Camus). The analysis, carried out in autumn 2013 at AU-Flakkebjerg, Denmark, included nine winter triticale varieties and 27 wheat varieties provided by the Faculty of Agriculture and Life Sciences Maribor, Slovenia. Fusarium sp. and black point disease-infected parts of the seed surface could successfully be distinguished from uninfected parts with use of a multispectral imaging device (405-970 nm wavelengths). SKNIR was applied in this research to differentiate all 36 involved varieties based on spectral differences due to variation in the chemical composition. The study produced an interesting result of successful distinguishing between the infected and uninfected parts of the seed surface. Furthermore, the study was able to distinguish between varieties. Together these components could be used in further studies for the development of a sorting model by combining data from multispectral imaging and SKNIR for identifying disease(s) and varieties.",
author = "Martina Vrešak and {Halkjaer Olesen}, Merete and Ren{\'e} Gislum and Franc Bavec and {Ravn J{\o}rgensen}, Johannes",
year = "2016",
month = "3",
day = "24",
doi = "10.1371/journal.pone.0152011",
language = "English",
volume = "11",
pages = "e0152011",
journal = "P L o S One",
issn = "1932-6203",
publisher = "public library of science",
number = "3",

}

RIS

TY - JOUR

T1 - The Use of Image-Spectroscopy Technology as a Diagnostic Method for Seed Health Testing and Variety Identification

AU - Vrešak, Martina

AU - Halkjaer Olesen, Merete

AU - Gislum, René

AU - Bavec, Franc

AU - Ravn Jørgensen, Johannes

PY - 2016/3/24

Y1 - 2016/3/24

N2 - Application of rapid and time-efficient health diagnostic and identification technology in the seed industry chain could accelerate required analysis, characteristic description and also ultimately availability of new desired varieties. The aim of the study was to evaluate the potential of multispectral imaging and single kernel near-infrared spectroscopy (SKNIR) for determination of seed health and variety separation of winter wheat (Triticum aestivum L.) and winter triticale (Triticosecale Wittm. & Camus). The analysis, carried out in autumn 2013 at AU-Flakkebjerg, Denmark, included nine winter triticale varieties and 27 wheat varieties provided by the Faculty of Agriculture and Life Sciences Maribor, Slovenia. Fusarium sp. and black point disease-infected parts of the seed surface could successfully be distinguished from uninfected parts with use of a multispectral imaging device (405-970 nm wavelengths). SKNIR was applied in this research to differentiate all 36 involved varieties based on spectral differences due to variation in the chemical composition. The study produced an interesting result of successful distinguishing between the infected and uninfected parts of the seed surface. Furthermore, the study was able to distinguish between varieties. Together these components could be used in further studies for the development of a sorting model by combining data from multispectral imaging and SKNIR for identifying disease(s) and varieties.

AB - Application of rapid and time-efficient health diagnostic and identification technology in the seed industry chain could accelerate required analysis, characteristic description and also ultimately availability of new desired varieties. The aim of the study was to evaluate the potential of multispectral imaging and single kernel near-infrared spectroscopy (SKNIR) for determination of seed health and variety separation of winter wheat (Triticum aestivum L.) and winter triticale (Triticosecale Wittm. & Camus). The analysis, carried out in autumn 2013 at AU-Flakkebjerg, Denmark, included nine winter triticale varieties and 27 wheat varieties provided by the Faculty of Agriculture and Life Sciences Maribor, Slovenia. Fusarium sp. and black point disease-infected parts of the seed surface could successfully be distinguished from uninfected parts with use of a multispectral imaging device (405-970 nm wavelengths). SKNIR was applied in this research to differentiate all 36 involved varieties based on spectral differences due to variation in the chemical composition. The study produced an interesting result of successful distinguishing between the infected and uninfected parts of the seed surface. Furthermore, the study was able to distinguish between varieties. Together these components could be used in further studies for the development of a sorting model by combining data from multispectral imaging and SKNIR for identifying disease(s) and varieties.

U2 - 10.1371/journal.pone.0152011

DO - 10.1371/journal.pone.0152011

M3 - Journal article

C2 - 27010656

VL - 11

SP - e0152011

JO - P L o S One

JF - P L o S One

SN - 1932-6203

IS - 3

ER -