Lactose has different uses in the dairy, food, and pharmaceutical industries. Being aware of the different forms of lactose and their concentrations can be very helpful in managing dairy product quality, properties, and manufacturing efficiency. Correct measurement and reporting of lactose concentration in milk and other dairy products will be of increased importance in the future as more value-added uses of lactose are developed and as milk lactose data are used in farm management decision making. Lactose should be reported as anhydrous lactose because lactose data will be used to make increasingly important decisions in dairy processing, dairy product labeling, and milk production in the future. Lactose also plays an important role in milk synthesis within a cow. Milk production factors and dairy cattle breed selection influence the amount of high value fat and protein produced per unit of lactose. If the off-farm value of lactose remains low, more attention may be focused on using ultrafiltration to process milk and leave 50 to 60% of the lactose and water from milk at the farm to recover the energy value of the lactose as feed and reduce the hauling cost of the high value components of milk to a dairy product manufacturing factory. Many methods exist to determine lactose concentration, but the most important methods are enzymatic assays, HPLC, and mid-infrared analysis. New, value-added uses for lactose need to be developed. Consistent and accurate methods of lactose measurement and consistent expression of lactose results will support this development process. Starting in January 2017, the USDA Federal Milk Market Laboratories began reporting lactose content of milk as anhydrous lactose and discontinued the reporting of lactose by difference.

Our first objective was to redesign a modified 14-sample milk calibration sample set to obtain a welldistributed range of milk urea nitrogen (MUN) concentrations while maintaining orthogonality with variation in fat, protein, and lactose concentration. Our second objective was to determine the within-and betweenlaboratory variation in the enzymatic spectrophotometric method on the modified milk calibration samples and degree of uncertainty in MUN reference values, and then use the modified milk calibration samples to evaluate and improve the performance of mid-infrared partial least squares (PLS) models for prediction of MUN concentration in milk. Changes in the modified milk calibration sample formulation and manufacturing procedure were made to achieve the desired range of MUN concentrations. A spectrophotometric enzymatic reference method was used to determine MUN reference values, and the modified milk calibration samples were used to calibrate 3 mid-infrared milk analyzers. The within-and between-laboratory variation in the reference values for MUN were 0.43 and 0.77%, respectively, and the average expanded analytical uncertainty for the mean MUN value of the 14-sample calibration set was (mean ± SD) 16.15 mg/100 g ± 0.09 of milk. After slope and intercept adjustment to achieve a mean difference of zero with the calibration samples, it could be seen that the standard deviation of the differences of predicted versus reference MUN values among 3 different instruments and their PLS models were quite different. The orthogonal sample set was used (1) to determine when a PLS model did not correctly model out the background variation in fat, true protein, or anhydrous lactose; (2) to calculate an intercorrection factor to eliminate that effect, and (3) to improve the model performance (i.e., 50% reduction in standard deviation of the difference between instrument predictions and reference chemistry values for MUN).

Our objective was to determine the within and between laboratory performance of an enzymatic spectrophotometric method for milk urea nitrogen (MUN) determination. This method first uses urease to hydrolyze urea into ammonia and carbon dioxide. Next, ammonia (as ammonium ions) reacts with 2-oxoglutarate, in the presence of reduced nicotinamide-adenine dinucleotide phosphate (NADPH) and the enzyme glutamate dehydrogenase (GlDH), to form l-glutamic acid, water, and NADP + . The change in light absorption at 340 nm due to the conversion of NADPH to NADP+ is stoichiometrically a function of the MUN content of a milk sample. The relative within (RSD r ) and between (RSD R ) laboratory method performance values for the MUN enzymatic spectrophotometric method were 0.57% and 0.85%, respectively, when testing individual farm milks. The spectrophotometric MUN method demonstrated better within and between laboratory performance than the International Dairy Federation differential pH MUN method with a much lower RSD r (0.57 vs. 1.40%) and RSD R (0.85 vs. 4.64%). The spectrophotometric MUN method also had similar method performance statistics as other AOAC International official validated chemical methods for primary milk component determinations, with the average of all RSD r and RSD R values being <1%. An official collaborative study of the enzymatic spectrophotometric MUN method is needed to achieve International Dairy Federation, AOAC International, and International Organization for Standardization official method status.

High levels of urea in blood, milk and urine have been linked to poor nitrogen efficiency, increased feed costs, poor reproductive performance and increased environmental impacts of dairy farming. Milk urea nitrogen (MUN) is a commonly used metric to manage herd nitrogen efficiency, with current recommendations for MUN to be between 8–14 mg/dL to maintain milk production and reduce nitrogen losses. However, a previous work suggests commercial analysis of MUN with mid-infrared spectroscopy (MIR) may not be precise enough to determine if a milk sample is within the recommended range. Thus, the objective of this study was to evaluate the precision and accuracy of milk testing lab MUN measurements. Four sets of bulk tank samples were sent to 3 commercial labs and one research lab for analysis by MIR. Samples were sent to commercial labs in duplicate and MUN was also assessed through an enzymatic assay. The Euclidean distance (ED) was calculated as a combined metric of precision and accuracy. The ED was not different between labs and ranged from 0.81–1.27. Repeatability (sr) and reproducibility (sR) were estimated for commercial labs and ranged from (0.297–0.469) and (0.555–0.791) respectively. Differences between individual sample MIR and enzymatic MUN were regressed on the centered enzymatic MUN in a linear mixed model that included a random effect of lab and fixed effects for milk protein and milk fat. Regression results indicate MIR analysis over-predicts MUN at low MUN concentrations and under predicts MUN at high MUN concentrations. Results suggest MIR analysis of MUN is more accurate around milk MUN, protein, and fat concentrations of ~13 mg/dl, 3.4% protein, and 4.2% fat. Further, the combined residual error and random effect of lab suggest the standard error of an MUN MIR measurement is ±1.8.

Cr, V, and Fe amino borohydride complexes were synthesized using a solution based approach. Thermogravimetric Analysis with simultaneous Differential Scanning Calorimetry was used to investigate their decomposition behavior. The synthesized Cr and Fe complexes exhibited significant hydrogen release around 100 °C. The synthesized V complex showed a large mass loss at temperatures between 50 °C and 100 °C and release of amine byproducts. FTIR of decomposed intermediates showed the decomposition of Cr amino borohydride occurs through the simultaneous loss of hydrogen from both the borohydride and amino ligands, while the Fe complex displays preferential dehydrogenation of the borohydride over the amino ligand. The decomposed products take on a BN type structure when heated to 400 °C.