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Applications of visible and near infrared spectroscopy for sorting and identification of tree seeds

Farhadi, Mostafa (2015). Applications of visible and near infrared spectroscopy for sorting and identification of tree seeds. Diss. (sammanfattning/summary) Alnarp : Sveriges lantbruksuniv., Acta Universitatis agriculturae Sueciae, 1652-6880 ; 2015:103
ISBN 978-91-576-8404-2
eISBN 978-91-576-8405-9
[Doctoral thesis]

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Abstract

Seeds are the most commonly used regeneration material for reforestation purpose; hence interest in “precision sowing” among nurseries is high due to the high cost of containerized seedling production. In addition, the increased interest in growing hybrid larch in commercial forestry has raised concerns about the purity of hybrid larch seed lots, as there are large proportions of pure parental seeds mixed with hybrid larch seed lots. The aims of the studies presented in this thesis were to evaluate the application of visible (Vis) and/or near infrared (NIR) spectroscopy combined with multivariate modelling for sorting filled-viable, empty and petrified seeds of Larix sibirica Ledeb., verification of hybrid larch, Larix × eurolepis Henry seeds, identification of seeds of Betula pendula Roth and Betula pubescens Ehrh., and authentication of the origin of Picea abies (L.) Karst seed lots. For these purposes, reflectance spectra were recorded on single seeds using XDS Rapid Content Analyzer (FOSS NIRSystems, Inc.) from 400 – 2500 nm with a resolution of 0.5 nm, and multivariate classification models were developed. The results showed that filled-viable, empty and petrified seeds of L. sibirica can be sorted with 98%, 82% and 87% accuracies, respectively. When the seed lot was sorted into viable and non-viable (empty and petrified combined) classes, the predicted class membership reached 100% for both classes. The technique could separate the hybrid larch seeds from pure parental seeds with 100% accuracy. Seeds of B. pubescens and B. pendula were differentiated with 100% and 99% classification accuracy, respectively. Also, the overall classification accuracy among three B. pendula families was 93% and that of B. pubescens was 98%. NIR spectroscopy discriminated Swedish, Finnish, Norwegian, Polish and Lithuanian seed lots of P. abies with 92% - 100% accuracy. Absorption bands that were accounted for distinguishing the various seed lots examined in this thesis were attributed to differences in seed color, moisture content and chemical composition of the seeds, presumably polysaccharides, proteins and fatty acids, which are the common seed storage reserves. The findings demonstrate the feasibility of Vis + NIR spectroscopy as a robust technique for sorting seed lots according to their viability and for certification of seed lots by species and origin. Thus, concerted efforts should be made to scale-up the technique to on-line sorting system for large-scale tree seed handling operations.

Authors/Creators:Farhadi, Mostafa
Title:Applications of visible and near infrared spectroscopy for sorting and identification of tree seeds
Series/Journal:Acta Universitatis agriculturae Sueciae (1652-6880)
Year of publishing :20 November 2015
Depositing date:20 November 2015
Volume:2015:103
Number of Pages:84
Papers/manuscripts:
NumberReferences
IFarhadi M., Tigabu M., Odén P.C. (2015). Near Infrared Spectroscopy as non-destructive method for sorting viable, petrified and empty seeds of Larix sibirica. Silva Fennica 49, article id 1340, 12p.
IIFarhadi M., Tigabu M., Stener L-G., Odén P.C. (2015). Feasibility of Vis + NIR spectroscopy for non-destructive verification of European × Japanese larch hybrid seeds. New Forests. Published On-line (http://dx.doi.org/10.1007/s11056-015-9514-4).
IIIFarhadi M., Tigabu M., Stener L-G., Odén P.C. Multivariate discriminant modelling of Visible + Near infrared spectra of single seeds differentiates between two birch species and their families (Submitted manuscript).
IVFarhadi M., Tigabu M., Odén P.C. Authentication of Picea abies Seed Origins by Near Infrared Spectroscopy and Multivariate Classification Modelling (Submitted manuscript).
Place of Publication:Alnarp
Publisher:Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences
ISBN for printed version:978-91-576-8404-2
ISBN for electronic version:978-91-576-8405-9
ISSN:1652-6880
Language:English
Publication Type:Doctoral thesis
Full Text Status:Public
Agris subject categories.:F Plant production > F03 Seed production and processing
K Forestry > K10 Forestry production
Subjects:(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Forest Science
Agrovoc terms:forest trees, seed, seed quality, infrared spectrophotometry, grading, sorting equipment, larix sibirica, larix eurolepis, betula pendula, betula pubescens, picea abies, multivariate analysis, models
Keywords:seed quality, near infrared spectroscopy, multivariate analysis, signal pre-processing, Siberian larch, hybrid larch, silver birch, downy birch, Norway spruce
URN:NBN:urn:nbn:se:slu:epsilon-e-3077
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-e-3077
ID Code:12836
Faculty:S - Faculty of Forest Sciences
Department:(S) > Southern Swedish Forest Research Centre
Deposited By: Mr. Mostafa Farhadi
Deposited On:20 Nov 2015 12:43
Metadata Last Modified:07 Feb 2016 18:57

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