从玉米自交系种子的遗传距离、 近红外光谱距离、 品种鉴别模型性能三方面进行分析, 探索三者间的关系。 采用三组(共15对)遗传关系远近不同的玉米自交系种子作为实验材料, 通过简单重复序列(simple sequence repeats, SSR)标记计算自交系种子间的遗传距离; 种子的近红外光谱经预处理后降维到主成分分析(principal component analysis, PCA)空间中, 计算各个自交系种子样本中心点之间的欧氏距离, 作为对应的近红外光谱距离; 使用仿生模式识别方法建立鉴别模型, 用模型的鉴别正确率评价模型的性能。 分析结果表明, 自交系种子间遗传距离与近红外光谱距离相关性为0.986 8, 与模型鉴别正确率的相关性为0.911 0, 相关性显著。 说明近红外光谱可以反映出玉米自交系种子之间的遗传关系, 遗传关系的远近影响品种鉴别模型的性能, 遗传距离越小, 近红外光谱距离越小, 模型鉴别能力也越差。 实际应用中有望利用近红外光谱技术分析玉米自交系的遗传关系, 对遗传育种、 品种识别、 纯度分选等具有重要意义; 且建立品种鉴别模型时, 应充分考虑遗传关系较近的玉米自交系对模型性能的影响。

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.