Prediction of individual total amino acids and free amino acids in Chinese Holstein cows milk using mid-infrared spectroscopy and their phenotypic variability.

Establishing a high-throughput detection technology for amino acid (AA) content in milk using mid-infrared (MIR) spectroscopy has profound implications for enhancing nutritional value of milk, identifying superior milk sources, producing specialty dairy products, and expanding Dairy Herd Improvement (DHI) metrics. The aim of this study was to evaluate the effectiveness of MIR spectroscopy in predicting the content of 15 individual total AA (TAAs) and 16 free AA (FAAs) in bovine milk as well as to investigate the major factors affecting the phenotypic variability of AA content. From March 2023 to March 2024, 513 milk samples were collected from 10 Holstein dairy farms in China and analyzed using Bentley spectrometers for MIR measurements. Their TAAs and FAAs concentrations were assessed through an AA autoanalyzer. Separate quantitative prediction models were developed for each AA using partial least squares regression; accuracy of prediction was assessed using Cow-independent external validation (CEV) and Farm-independent external validation (FEV) set. In CEV, the ratio of performance to deviation (RPD) of the TAAs models ranged from 1.45 (Ser) to 2.19 (Leu), while the FAA models ranged from 1.15 (Ser) to 2.44 (Met). In FEV, the RPD of the TAAs models ranged from 0.98 (Met) to 1.76 (Asp, Glu, and Ala), and the FAAs models ranged from 0.33 (Phe) to 1.23 (Asp and Tyr). For farms included in the calibration set, MIR spectroscopy provided a rough quantitative estimation for 4 individual TAAs (Ile, Leu, Glu, and Tyr) and 2 FAAs (Met and His), as well as a qualitative determination for high and low values in 9 individual TAAs (Phe, Met, Val, Lys, Thr, Asp, Ala, His, and Arg). For farms outside the calibration set, MIR spectroscopy could only distinguish between high and low contents for 5 individual TAAs (Glu, Asp, Ala, Leu, and Arg). Phenotypically, the variation pattern in TAAs contents mirrored that of protein, while FAAs did not show a clear trend, though mastitis led to a significant elevation of FAAs in milk (p < 0.05). Overall, the application of MIR spectroscopy can be considered very promising for a low-cost, rapid, large-scale assessment of individual TAAs and FAAs contents in milk. After refinement, some models could potentially be incorporated into DHI, which would greatly benefit the milk production and food industries.