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Journal of Spectroscopy
Volume 2017 (2017), Article ID 9740295, 12 pages
https://doi.org/10.1155/2017/9740295
Research Article

Application of Near-Infrared Spectroscopy to Quantitatively Determine Relative Content of Puccnia striiformis f. sp. tritici DNA in Wheat Leaves in Incubation Period

1College of Plant Protection, China Agricultural University, Beijing 100193, China
2College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China

Correspondence should be addressed to Haiguang Wang; nc.ude.uac@gnaugiahgnaw

Received 15 April 2017; Accepted 27 June 2017; Published 6 August 2017

Academic Editor: Wee Chew

Copyright © 2017 Yaqiong Zhao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is a devastating wheat disease worldwide. Potential application of near-infrared spectroscopy (NIRS) in detection of pathogen amounts in latently Pst-infected wheat leaves was investigated for disease prediction and control. A total of 300 near-infrared spectra were acquired from the Pst-infected leaf samples in an incubation period, and relative contents of Pst DNA in the samples were obtained using duplex TaqMan real-time PCR arrays. Determination models of the relative contents of Pst DNA in the samples were built using quantitative partial least squares (QPLS), support vector regression (SVR), and a method integrated with QPLS and SVR. The results showed that the kQPLS-SVR model built with a ratio of training set to testing set equal to 3 : 1 based on the original spectra, when the number of the randomly selected wavelength points was 700, the number of principal components was 8, and the number of the built QPLS models was 5, was the best. The results indicated that quantitative detection of Pst DNA in leaves in the incubation period could be implemented using NIRS. A novel method for determination of latent infection levels of Pst and early detection of stripe rust was provided.