Rapid on-site monitoring of fatty acid profile in raw milk using a handheld near infrared sensor

This work is focused on development of a quick and simple to use analytical methodology for on-site monitoring the fatty acid (FA) profile in raw milk at farm level by using a near infrared handheld spectrometer. This novel methodology was developed using a total of 108 liquid milk samples, scanned at room temperature by NIRS without pre-treatment, and analyzed by GC-MS for reference data. Calibration was carried out by multivariate regression combining math pre-treatments and Partial Least Square with internal and external validation. Calibration models displayed good predictive capacity for total saturated, monounsaturated (MUFA) and polyunsaturated FA (PUFA) with high coefficients of determination of cross validation (R2cv > 0.8). Good results were also obtained for prediction of individual FA: caproic, capric, lauric, miristic, palmitic and arachidic as well as for unsaturated FA: oleic, conjugated linoleic acid and omega-6 acids with R2cv values ranged between 0.91- 0.73. Validation statistics have confirmed that the highest R2v (coefficient of determination of external validation) values to quantify FA were for PUFA, linolenic acid (R2v = 0.92), caproic acid and MUFA (R2v = 0.87). These results establish that a profitable classification of milk can be carried out at farm level by including a fatty acid composition labeling.