光谱学与光谱分析 |
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A Study of the Relationship Among Genetic Distances, NIR Spectra Distances, and NIR-Based Identification Model Performance of the Seeds of Maize Iinbred Lines |
LIU Xu1, JIA Shi-qiang1, WANG Chun-ying2, LIU Zhe1, GU Jian-cheng2, ZHAI Wei2, LI Shao-ming1, ZHANG Xiao-dong1, ZHU De-hai1, HUANG Hua-jun1, AN Dong1* |
1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China 2. Beijing Kings Nower Seed S&T Co., Ltd., Beijing 100080, China |
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Abstract This paper explored the relationship among genetic distances, NIR spectra distances and NIR-based identification model performance of the seeds of maize inbred lines. Using 3 groups (total 15 pairs) of maize inbred lines whose genetic distaches are different as experimental materials, we calculates the genetic distance between these seeds with SSR markers and uses Euclidean distance between distributed center points of maize NIR spectrum in the PCA space as the distances of NIR spectrum. BPR method is used to build identification model of inbred lines andthe identification accuracy is used as a measure of model identification performance. The results showed that the correlation of genetic distance and spectra distancesis 0.986 8, and it has a correlation of 0.911 0 with the identification accuracy, which is highly correlated. This means near-Infrared spectrum of seedscan reflect genetic relationship of maize inbred lines. The smaller the genetic distance, the smaller the distance of spectrum, the poorer ability of model to identify. In practical application, near infrared spectrum analysis technology has the potential to be used to analyze maize inbred genetic relations, contributing much to genetic breeding, identification of species, purity sorting and so on. What’s more, when creating a NIR-based identification model, the impact of the maize inbred lines which have closer genetic relationship should be fully considered.
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Received: 2014-05-16
Accepted: 2014-08-21
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Corresponding Authors:
AN Dong
E-mail: andong@cau.edu.cn
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