Abstract
The potential of visible (VIS) and near infrared (NIR) spectroscopy for identifying seed sources and parents of Pinus sylvestris L. was studied. Seeds of a single family (clones AC1005 × BD1178) collected from three localities in Sweden—Sävar (north), Röskär (central) and Degeberga (south)—and seeds from four maternal (clone no. BD1032, AC1014, BD1178 and AC1005) and four paternal (Y3020, BD1178, AC1014 and BD1032) parents were used to evaluate the method. VIS and NIR reflectance spectra were recorded on individual seeds using a NIRSystems Model 6500 spectrometer from 400 to 2,498 nm with a resolution of 2 nm. The VIS + NIR spectroscopic data were pre-treated with multiplicative signal correction, and analysed by soft independent modelling of class analogy (SIMCA) and partial least squares-discriminant analysis (PLS-DA). The computed models were later applied to classify samples in the external test sets. The results show that seed sources were identified with 100% classification accuracy using PLS-DA models in the VIS + NIR, VIS and NIR regions. The average classification accuracy for maternal parents ranged from 92% to 96%, while paternal parents were identified with 91.2–96% accuracies. The classification accuracy using the SIMCA approach was relatively low for seed sources as well as maternal and paternal parents. It can be concluded that VIS + NIR spectroscopy could be employed as a rapid and non-destructive method for monitoring putative seed sources. The result underscores the prospect of the technique for characterizing seeds based on genotype, thereby serving as a tool in tree improvement and breeding.
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Acknowledgements
The Swedish Council for Forestry and Agricultural Research and the Kempe Foundation financially supported the study. The Department of Organic Chemistry, Umeå University is acknowledged for allowing us to use their NIR instrument. Thanks are due to Daniel Tiveau and Dillon Chrimes for reading the manuscript
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Tigabu, M., Oden, P. & Lindgren, D. Identification of seed sources and parents of Pinus sylvestris L. using visible–near infrared reflectance spectra and multivariate analysis. Trees 19, 468–476 (2005). https://doi.org/10.1007/s00468-005-0408-5
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DOI: https://doi.org/10.1007/s00468-005-0408-5