Visible and near-infrared spectroscopy (Vis-NIRS) was tested for its effectiveness in predicting intramuscular fat (IMF) and WBSF in Nellore steers. Beef samples from longissimus thoracis, aged for either 2 or 7 days, had their spectra collected for wavelengths ranging from 400 to 1395 nm. Partial least squares regression models were developed for each trait. Determination coefficients of calibration models for WBSF ranged from 0.17 to 0.53. Considering WBSF in samples aged for 2 days, Vis-NIR correctly classified 100% of tough samples (>45 N), but wrongly classified all tender samples (≤45 N) as tough. Determination coefficients of calibration models for IMF ranged from 0.12 to 0.14. Vis-NIRS is a useful tool for identifying tough beef, but it is less effective in predicting tender samples and IMF. Additional studies are necessary to generate more robust models for the prediction of intramuscular fat in intact meat samples of Nellore cattle.

测试了可见和近红外光谱（Vis-NIRS）在预测Nellore牛的肌内脂肪（IMF）和WBSF方面的有效性。年龄为2天或7天的长形胸肉牛肉样品的光谱采集的波长为400至1395 nm。针对每个特征开发了偏最小二乘回归模型。WBSF校准模型的确定系数范围为0.17至0.53。考虑到老化2天的样品中的WBSF，Vis-NIR正确地将100％的坚硬样品（> 45 N）分类为坚硬的，而错误地将所有嫩样品（≤45N）归为坚硬的。IMF的校准模型的确定系数范围为0.12至0.14。Vis-NIRS是识别坚韧牛肉的有用工具，但在预测嫩肉样本和IMF方面效果较差。