桉树杂交种与其亲本的近红外光谱判别

doi:10.3964/j.issn.1000-0593(2020)03-0873-05

Abstract
References
Related Citation (13)

Download: PDF (3571 KB)
Export: BibTeX | EndNote (RIS)

Abstract Studying the gene control pattern of interested traits after control pollination is one of the key fields in exploring the law of gene recombination in eucalypt improvement. The accuracy of conventional quantitative analysis for that is often low, and the DNA analysis for that has high professional requirements, and is time consuming and laborious commonly. The aim of the current study is to study the relationship among different genotypes of hybrids, parents, hybrids and their parents in eucalypt based on the near infrared spectroscopy (NIRs) of foliage, and to discuss the practicability and the accuracy of the NIRs discriminant model for the classifying of eucalypt hybrids and their parents. The genetical materials in the study contained three eucalypt parents and their F1 progenies by control pollination. Fresh and healthy leaves from middle to upper crowns in a tree from their field testing trials were collected, and 10 individuals were chosen per genotype. The handheld portable near infrared spectrometer Phazir Px (1624) was used to scan the NIRs of foliage collected. 10 healthy current-year leaves were chosen per individual tree, five scans for NIRs from each side of the middle part of the frontal vein of the leaves were taken, calculated the average of 50 scans as the NIRs data of a leaf, thus 10 NIRs were got for every genotype in totally. The transform of S.G first derivative with second order polynomial fit was performed for the raw NIRs in present study. The successive multivariate analysis was conducted after NIRs pretreatment. To demonstrate the classification of different genotypes by the principal component analysis (PCA) with the NIRs data of hybrids and the patents in eucalypt. Then, two supervised discriminant models, soft independent modeling of class analogy (SIMCA) and partial least squares-discriminant analysis (PLS-DA) pattern recognition, were used to test the accuracy of NIRs model in the classifying for eucalypt hybrids and their cross parents. The scores plot of PC1 and PC2 in PCA demonstrated strong groups among different genotypes, such as cross parents, hybrids, and between hybrids and their parents. The sample distance to parents PCA model in the SIMCA analysis showed that the hybrids to be distinguished can form a clear group differentiated with their parents, and demonstrated the genetic similarity between parents and their progenies directly. The PLS-DA pattern recognition analysis indicated that the hybrids can be discriminated with cross parents by the response values of hybrids predicted by the parents PLS model. All the findings in present study showed that NIRs information of eucalypt leave truly reflects the transmission of genetic information occurring in the process of control pollination, and different genotypes including hybrids and their parents can be discriminated accurately by NIRs models, suggesting that NIRs can be used not only for qualitative identification between eucalypt hybrids and the cross parents, but also for assessing the extent of additive genetic effects in gene recombination, which can provide theoretical reference for the genetic basis analysis and breeding improvement in eucalypt.

Key words：Supervised model; Principal component analysis (PCA); Soft independent modeling of class analogy (SIMCA); Partial least squares-discriminant analysis (PLS-DA)

Received: 2019-01-23 Accepted: 2019-04-07

ZTFLH:

S722.34

Corresponding Authors: LI Peng E-mail: 462227809@qq.com

Cite this article:

URL:

https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2020)03-0873-05 OR https://www.gpxygpfx.com/EN/Y2020/V40/I03/873