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Near-infrared spectroscopy analysis of foodstuffs is a relatively recent technique. Its principal advantage is speed of analysis, and it does not require sample pretreatment either. In this paper we review its application to powder dairy products, liquid milk, cheese, butter, and fermented milk products, mainly from the analysis of the major components point of view and also for the detection of adulterations and other determinations as well. Keywords: Near-infrared spectroscopy; dairy products

NIR transflectance spectroscopy was used to analyze fructose, glucose, and moisture in honey. A total of 161 honey samples were collected during 1992 (46), 1995 (58), and 1996 (57). Samples were analyzed by instrumental, enzymatic (fructose and glucose), and refractometric (moisture) methods. Initially, different calibrations were performed for each of the 3 years of sampling. Good predictions were obtained for all three components with equations of the particular year. But good predictions were not always obtained when the equations calculated one year were applied to samples from another year. To perform a lasting calibration, unique calibration (121 samples) and validation (40 samples) sets were built; honeys of the 3 years were included in both sets. Good statistics (bias, standard error of validation (SEV), and R(2)) were obtained for all three components of the validation set. No statistically significant differences (p = 0.05) were found between instrumental and reference methods.

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Near-infrared reflectance (NIR) spectroscopy was used to analyze fat, protein, and total solids in cheese without any sample treatment. A set of 92 samples of cow’s milk cheese was used for instrument calibration by principal components analysis and modified partial least-square regression. The following statistical values were obtained: standard error of calibration (SEC) = 0.388 and squared correlation coefficient (R2) = 0.99 for fat, SEC = 0.397 and R2 = 0.98 for protein, and SEC = 0.412 and R2 = 0.99 for total solids. To validate the calibration, an independent set of 25 cheese samples of the same type was used. Standard errors of validation were 0.47,0.50, and 0.61 for fat, protein, and total solids, respectively, and hf for the regression of measurements by reference methods versus measurements by NIR spectroscopy was 0.98 for the 3 components.

The international standard method for the determination of trypsin inhibitor activity (TIA) in soya products, ISO 14902, was compared with the American Association of Cereal Chemists’ standard AACC 22‐40.01 as modified by Hamerstrand in 1981 (AACC‐based method), using soybean meals as matrices. TIA, expressed as milligram of inhibited trypsin per gram of sample, was determined by both methods in each of 30 samples of soybean meal. TIA values according to ISO 14902 were significantly lower (P < 0.001) than those afforded by the AACC‐based method. This difference, which means that AACC‐based method and ISO 14902 TIA values are not directly comparable, is attributable to between methods differences, in decreasing order of influence: particle size (P < 0.01), trypsin inhibitor extraction method (P < 0.05), and trypsin substrate (P < 0.01). N‐benzoyl‐l‐arginine‐4‐nitroanilide hydrochloride, the ISO 14902 trypsin substrate, affords TIA values 6.4 % higher than the racemic mixture used by the AACC method, but it seems unlikely that in most contexts this advantage would outweigh the disadvantage of its greater cost.

NIR transflectance spectroscopy was used to determine polarimetric parameters (direct polarization, polarization after inversion, specific rotation in dry matter, and polarization due to nonmonosaccharides) and sucrose in honey. In total, 156 honey samples were collected during 1992 (45 samples), 1995 (56 samples), and 1996 (55 samples). Samples were analyzed by NIR spectroscopy and polarimetric methods. Calibration (118 samples) and validation (38 samples) sets were made up; honeys from the three years were included in both sets. Calibrations were performed by modified partial least-squares regression and scatter correction by standard normal variation and detrend methods. For direct polarization, polarization after inversion, specific rotation in dry matter, and polarization due to nonmonosaccharides, good statistics (bias, SEV, and R(2)) were obtained for the validation set, and no statistically (p = 0.05) significant differences were found between instrumental and polarimetric methods for these parameters. Statistical data for sucrose were not as good as those of the other parameters. Therefore, NIR spectroscopy is not an effective method for quantitative analysis of sucrose in these honey samples. However, NIR spectroscopy may be an acceptable method for semiquantitative evaluation of sucrose for honeys, such as those in our study, containing up to 3% of sucrose. Further work is necessary to validate the uncertainty at higher levels.