文献类型：期刊文献

英文题名：Discrimination of Pinus taedaxP. caribaea var. hondurensis between its allele-species and hybrids using near infrared spectroscopy

作者：Luan, Qi-Fu[1] Li, Yan-Jie[1] Jiang, Jing-Min[1] Yue, Hua-Feng[1] Diao, Song-Feng[1]

第一作者：栾启福

通信作者：Jiang, JM[1]

机构：[1]Chinese Acad Forestry, Res Inst Subtrop Forestry, Fuyang Cty 311400, Zhejiang, Peoples R China

年份：2013

卷号：21

期号：3

起止页码：203-211

外文期刊名：JOURNAL OF NEAR INFRARED SPECTROSCOPY

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000322416600005)】；

基金：The Research is supported by The National Key Technology R&D Program (Grant 2012BAD01B02) and Natural Science Foundation of the Zhejiang Provinces (LY12C16009), China. Thanks to Master degree candidate Li Cheng for his hard work in the collection of the near infrared (NIR) Data in Zhejiang University, China. Thanks also go to Dr Harry X. Wu and all the editors for the review and edits in improving the manuscript.

语种：英文

外文关键词：hybrids; pine needles; near infrared spectroscopy; PLS-DA; LDA

摘要：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 taeda x P. 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. elliottii x P. 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.