糖含量是影响肉类的营养品质和口感风味的重要指标，传统的糖含量分析为破坏性检测，费时费力，近红外光谱分析快速简便，因此提出了题示研究。以低糖组、正常组和高糖组肉组织为研究对象，分别对光谱预处理方法、光谱区间和建模维数（潜变量）进行筛选优化，建立了肉组织糖含量的近红外光谱模型。优化的近红外光谱模型采用矢量归一化进行光谱预处理，光谱区间为4 246~9 403 cm^-1，建模维数为17，其建模集和验证集的相关系数和残留预测偏差分别依次为0.990 3和0.975 6、7.23和4.54，交叉验证均方差为0.057 0，预测验证均方差为0.061 4。

Glucose content is one of crucial factors that affecting the nutritional quality, taste and flavor of meat. As the classical determination method need complex and destructive sample preparation, laborious and tedious time, near infrared spectroscopy could be a reliable method in a rapid, nondestructive and convenient method. Therefore, the study mentioned by the title was proposed. Meat tissue from the hypoglycemia group, normal group, and hyperglycemia group was recorded as research object, and the spectral pre-treatment methods, spectral ranges, and latent variables were screened and optimized to build a near infrared spectral model for determination of glucose in meat tissue. The optimal near infrared spectral model was built with vector normalization for spectral pre-treatment methods, spectral range in 4 246-9 403 cm^-1, and 17 of latent variables. The correlation coefficients and residual predictive deviations of the calibration set and validation set were 0.990 3 and 0.975 6, as well as 7.23 and 4.54, respectively. The root mean square errors of cross-validation and prediction were 0.057 0 and 0.061 4, respectively.