Lobos-Ortega Iris, Silva Mariela, Rodríguez-Pereira Romina, Saldaña Rodolfo, Subiabre Ignacio, Rodríguez Marion, Morales Rodrigo
Instituto de Investigaciones Agropecuarias INIA Remehue, Ruta 5 Km 8, Osorno 5290000, Chile.
Escuela de Medicina Veterinaria, Facultad de Recursos Naturales y Medicina Veterinaria, Universidad Santo Tomás, Talca 3460000, Chile.
Foods. 2025 Aug 8;14(16):2767. doi: 10.3390/foods14162767.
The fatty acid (FA) profile of beef is a key indicator of nutritional quality. This study assessed the ability of Near Infrared Spectroscopy (NIRS) to predict the FA profile in beef samples from southern Chile. A total of 81 FAs were analyzed, and 38% of the calibration models achieved RPD ≥ 2.5 (Ratio of Performance to Deviation). Strong predictive performance was observed for major FAs, particularly SFA and MUFA, with Rp > 0.90 (Coefficient of Determination) for palmitic (16:0). Although PUFA and some CLA isomers showed lower predictive accuracy-likely due to low concentrations and spectral overlap-minor FA such as 9,11-18:2 (CLA, rumenic acid) was accurately predicted. External validation confirmed that 77% of FAs showed no significant differences from gas chromatography, highlighting the robustness of NIRS for most compounds analyzed here. NIRS effectively captured FAs related to grass-based diets, such as trans-vaccenic acid and specific CLA isomers. NIRS works as a practical, rapid, and non-destructive tool for FA profiling, with potential uses in nutritional labeling and quality control; however, its application depends on the prior development of robust calibration models, which must be tailored to the specific matrix and analytical objectives.
牛肉的脂肪酸（FA）谱是营养品质的关键指标。本研究评估了近红外光谱（NIRS）预测智利南部牛肉样本中FA谱的能力。共分析了81种脂肪酸，38%的校准模型实现了RPD≥2.5（性能与偏差比）。主要脂肪酸表现出很强的预测性能，尤其是饱和脂肪酸（SFA）和单不饱和脂肪酸（MUFA），棕榈酸（16:0）的决定系数（Rp）>0.90。尽管多不饱和脂肪酸（PUFA）和一些共轭亚油酸（CLA）异构体的预测准确性较低——可能是由于浓度低和光谱重叠——但次要脂肪酸如9,11-18:2（CLA，瘤胃酸）得到了准确预测。外部验证证实，77%的脂肪酸与气相色谱法无显著差异，突出了NIRS对本文分析的大多数化合物的稳健性。NIRS有效地捕捉了与草饲饮食相关的脂肪酸，如反式vaccenic酸和特定的CLA异构体。NIRS是一种实用、快速且无损的脂肪酸分析工具，在营养标签和质量控制方面有潜在用途；然而，其应用取决于稳健校准模型的前期开发，这些模型必须针对特定基质和分析目标进行定制。
