Abstract

It is not easy to distinguish hybrid pines using their morphological characteristics. Traditional methods of identification, such as chemical analysis or molecular marker technology, are complicated, time-consuming and costly and are not very accurate. They are not, therefore, an ideal means of identification and the use of near-infrared technology, which is comparatively inexpensive and simple to use, is preferable. For the future development of Pinus taedaxP. caribaea var. hondurensis (PTC) hybrid trials and breeding programmes, and to provide a more comprehensive understanding of their physiological and biochemical characteristics, it is necessary to identify PTC among the parents (P. elliottii, P. taeda and P. caribaea var. hondurensis) and other possible hybrids (P. elliottiixP. caribaea var. hondurensis) in order to be able to distinguish them from each other. In this study, partial least-squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) regression modelling are used, The results are as follows: PLS-DA has a low accuracy rate, at 89.09%, but using the PLS-DA scores as the input data into the LDA resulted in LDA distinction models, with accuracy rates reaching 99%, allowing a reliable identification of pure species and hybrids. It is clear from the results that near infrared technology can be used to identify hybrid and purebreds in pine and that the accuracy rate is higher than that derived when using standard molecular techniques.

© 2013 IM Publications LLP

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