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Application of near infrared spectroscopy for authentication of Picea abies seed provenance
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- Farhadi, Mostafa (author)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för sydsvensk skogsvetenskap,Southern Swedish Forest Research Centre
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- Tigabu, Mulualem (author)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för sydsvensk skogsvetenskap,Southern Swedish Forest Research Centre
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- Danusevicius, Darius (author)
- Aleksandras Stulginskis University
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- (creator_code:org_t)
- 2017-05-18
- 2017
- English.
- In: New Forests. - : Springer Science and Business Media LLC. - 0169-4286 .- 1573-5095. ; 48, s. 629-642
- Journal article (peer-reviewed)
Abstract
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- Authentication of seed provenance is an importance issue to avoid the negative impact of poor adaptation of progenies when planted outside their natural environmental conditions. The objective of this study was to evaluate the potential of near infrared (NIR) spectroscopy as rapid and non-destructive method for authentication of Picea abies L. Karst seed provenances. For this purpose, five seed lots from Sweden, Finland, Poland and Lithuania each were used. NIR reflectance spectra were recorded on individual seeds (n = 150 seeds x 5 seed lots x 4 provenances = 3000 seeds) using XDS Rapid Content Analyzer from 780 to 2500 nm with a resolution of 0.5 nm. Classification model was developed by orthogonal projection to latent structures-discriminant analysis. The performance of the computed classification model was validated using two test sets-internal (the same seed lots as the model but excluded during model development; n = 600 seeds) and external (seed lots not included in the model; n = 1158 seeds). For the internal test, the model correctly recognized 99% of Swedish, Finnish and Polish samples and 97% of Lithuanian seeds. For the external test samples, the model correctly assigned 81% of Swedish, 96% of Finnish, 98% of Lithuanian and 93% of Polish seeds to their respective classes. The mean classification accuracy was 99 and 95% for internal and external test set, respectively. The spectral differences among seed lots were attributed to differences in chemical composition of seeds, presumably fatty acids and proteins, which are the dominant storage reserves in P. abies seeds. In conclusion, the results demonstrate that NIR spectroscopy is a very promising method for monitoring putative seed provenances and in seed certification.
Subject headings
- LANTBRUKSVETENSKAPER -- Lantbruksvetenskap, skogsbruk och fiske -- Skogsvetenskap (hsv//swe)
- AGRICULTURAL SCIENCES -- Agriculture, Forestry and Fisheries -- Forest Science (hsv//eng)
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