Cascant Mari Merce, Breil Cassandra, Fabiano-Tixier Anne Silvie, Chemat Farid, Garrigues Salvador, de la Guardia Miguel
Department of Analytical Chemistry, University of Valencia, 50 Dr. Moliner Street, Research Building, 46100 Burjassot, Valencia, Spain; Université d'Avignon et des Pays de Vaucluse, INRA, UMR408, GREEN Team Extraction, 84000 Avignon Cedex, France.
Université d'Avignon et des Pays de Vaucluse, INRA, UMR408, GREEN Team Extraction, 84000 Avignon Cedex, France.
Food Chem. 2018 Jan 15;239:865-871. doi: 10.1016/j.foodchem.2017.06.158. Epub 2017 Jun 30.
Near-infrared (NIR) spectroscopy was evaluated as a rapid method for the determination of oleic, palmitic, linoleic and linolenic acids as well as omega-3, omega-6, and to predict polyunsaturated, monounsaturated and saturated fatty acids, together with triacylglycerides, diglycerides, free fatty acids and ergosterol in salmon oil. To do it, Partial Least Squares (PLS) regression models were applied to correlate NIR spectra with aforementioned fatty acids and lipid classes. Results obtained were validated in front of reference procedures based on high performance thin layer and gas chromatography. PLS-NIR has a good predictive capability with relative root mean square error of prediction (RRMSEP) values below or equal to 1.8% and provides rapid analysis without the use of any chemicals making it an environmentally friendly methodology.
近红外（NIR）光谱法被评估为一种快速测定鲑鱼油中油酸、棕榈酸、亚油酸和亚麻酸以及ω-3、ω-6的方法，并用于预测多不饱和脂肪酸、单不饱和脂肪酸和饱和脂肪酸，以及甘油三酯、甘油二酯、游离脂肪酸和麦角固醇。为此，应用偏最小二乘法（PLS）回归模型将近红外光谱与上述脂肪酸和脂质类别相关联。所得结果与基于高效薄层色谱和气相色谱的参考方法相比得到了验证。PLS-NIR具有良好的预测能力，预测相对均方根误差（RRMSEP）值低于或等于1.8%，且无需使用任何化学物质即可进行快速分析，使其成为一种环保方法。
