基于可见-近红外高光谱技术对鸡种蛋性别鉴定的研究

目的 为实现鸡种蛋胚胎性别的无损检测，提出了基于可见-近红外高光谱检测海兰褐鸡种蛋胚胎性别的方法。方法 通过分析种蛋0~14 d大头部位的400~1000 nm波段下的光谱，建立基于偏最小二乘判别分析（PLS-DA）和支持向量机（SVM）的种蛋性别判别模型，比较不同孵育天数下的模型判别率，优选出最佳的检测天数；通过分析四种不同的预处理算法，选出最佳的鸡种蛋胚胎高光谱预处理方法，最后构建基于全波段和特征波段光谱信息的判别模型，并对结果进行比较。结果 基于PLS-DA和SVM的模型在第9 d的预测集结果达到最高，分别为80%和82.5%。主成分分析（PCA）结果表明，雄雌种蛋光谱信息可以进行区分；变量标准化（SNV）为最佳预处理方法；全波段相对于连续投影算法（SPA）、竞争性自适应重加权算法（CARS）选择特征波长的模型更优，建模集、预测集准确率分别为90%和85%。结论 研究结果表明可见-近红外高光谱技术可以快速、较准确、无损检测海兰褐种蛋胚胎性别，该技术为褐壳种蛋胚胎性别鉴定实现在线检测提供了一定的理论基础。

Research on sex identification of chicken eggs based on visible-near infrared hyperspectral technology

Objective In order to realize the non-destructive detection of the embryo sex of chicken eggs, a method based on visible-near infrared hyperspectroscopy was proposed to detect the embryo sex of Hylan brown chicken eggs.Methods By analyzing the spectrum in the 400-1000 nm band of the large head of the eggs from 0 to 14 days, an egg sex discrimination model based on Partial Least Squares Discriminant Analysis (PLS-DA) and Support Vector Machine (SVM) was established to compare model discrimination rate at different incubation days, the optimal detection days were selected; by analyzing four different preprocessing algorithms, the optimal hyperspectral preprocessing method for egg embryos was selected, and finally the spectral information based on the full band and characteristic band was constructed, and the results were compared.Results It was found that the models based on PLS-DA and SVM achieved the highest results in the prediction set on the 9th day, with 80% and 82.5%, respectively. The results of principal component analysis (PCA) showed that the spectral information of male and female could be distinguished; variable normalization (SNV) was the best preprocessing method; compared with the continuous projection algorithm (SPA) and the competitive adaptive reweighting algorithm (CARS), the full-band model was better than the model that selects the characteristic wavelength, and the accuracy rates of the modeling set and prediction set were 90% and 85%, respectively. Conclusion The research results show that visible-near infrared hyperspectral technology is able to detect the sex of Hylan brown chicken egg embryos quickly, accurately and non-destructively and this technology provides the theoretical basis for the online detection of brown-shell egg embryo sex detection.