Predicting the shear value and intramuscular fat in meat from Nellore cattle using Vis-NIR spectroscopy

Area of Science:

• Agricultural Science
• Food Science
• Spectroscopy

Background:

• Intramuscular fat (IMF) and Warner-Bratzler Shear Force (WBSF) are key indicators of beef quality.
• Nellore cattle are a significant beef breed, and objective quality assessment is crucial.
• Visible and near-infrared spectroscopy (Vis-NIRS) offers a non-destructive method for meat analysis.

Purpose of the Study:

• To evaluate the efficacy of Vis-NIRS in predicting IMF and WBSF in Nellore steers.
• To assess the performance of Vis-NIRS models for beef aged for 2 and 7 days.

Main Methods:

• Beef samples from longissimus thoracis of Nellore steers were analyzed.
• Spectra were collected using Vis-NIRS across the 400-1395 nm wavelength range.
• Partial least squares regression models were developed to predict WBSF and IMF.

Main Results:

• Calibration models for WBSF showed determination coefficients ranging from 0.17 to 0.53.
• Vis-NIR accurately classified 100% of tough samples (>45 N) aged for 2 days but misclassified all tender samples (≤45 N).
• Calibration models for IMF yielded low determination coefficients (0.12 to 0.14).

Conclusions:

• Vis-NIRS is a valuable tool for identifying tough beef, particularly in samples aged for 2 days.
• The technique's effectiveness is limited for predicting tender beef and IMF.
• Further research is needed to develop more robust models for IMF prediction in intact Nellore beef.