MILK Symposium review: Improving the productivity, quality, and safety of milk in Rwanda and Nepal.

Dairy production plays an important role in the lives of many people in Rwanda and Nepal. The aim of the Feed the Future Innovation Lab for Livestock Systems (LSIL; Gainesville, FL) is to introduce new location-appropriate technologies and to improve management practices, skills, knowledge, capacity, and access to inputs across livestock value chains in developing countries such as Rwanda and Nepal. To assist LSIL, our first aim was to describe gaps in the management of cows and in milk processing that constrain milk quality and quantity in Rwanda and Nepal. Our second aim was to describe training-of-trainers workshops in both countries as an initial response to the findings from the first objective. We conducted literature reviews and did rapid needs assessments in both countries. The literature reviews revealed similar aspects of the challenges of smallholder crop-livestock mixed farming systems in both countries. Many farms are struggling with feed quality, reproduction, and health of dairy cows. Milk production per cow and quality is often low. Fresh milk is collected by milk collection and cooling centers. Hygiene and milk processing capability and shelf life of products can be improved. Local rapid needs assessments were conducted in 2016 (Rwanda) and 2017 (Nepal) through visits to farms, milk collection and chilling centers, and processing plants, and through discussions with local dairy officials. The assessments supplemented and completed our understanding of stakeholders' needs in management and processing of milk. Limiting factors to improving the productivity, quality, and safety of milk in Rwanda and Nepal were a combination of sometimes limited knowledge in areas such as feeding, mastitis control, and hygiene, and a lack of access to resources such as quality feeds, transportation, and cooling that hindered implementation of existing knowledge. Training-of-trainers workshops in milk processing and hygiene were developed and given in Rwanda and Nepal based on the rapid needs assessments, and these were well received. We concluded that Rwanda and Nepal both have smallholder dairy farms that often face similar challenges such as lack of quality feeds, needs for basic dairy management education, low cattle productivity, and undesirable milk quality. Training-of-trainers programs to address these basic issues may be successful. Continued improvements in the dairy value chain depend on available resources for education.

Within-milking variation in milk composition and fatty acid profile of Holstein dairy cows.

Changes in milk composition during a milking are well characterized, but variation in milk fatty acid (FA) profile is not well described and may affect the accuracy of in-line milk composition analyzers and could potentially be used for selective segregation of milk. Within-milking samples were collected from 8 multiparous high-producing Holstein cows (54.86 ± 6.8 kg of milk/d; mean ± standard deviation). A milk-sampling device was designed to allow collection of multiple samples during a milking without loss of vacuum or interruption of milk subsampling. Milk was collected during consecutive morning and afternoon milkings (12-h intervals) and was replicated 1 wk later. Each sample represented approximately 20% of the milking and was analyzed for fat, true protein, and lactose concentration and FA profile. Milk fat concentration markedly increased over the course of milk let down (4.4 and 4.2 percentage units at the a.m. and p.m. milking, respectively), whereas milk fat globule size did not change. Milk protein and lactose concentration decreased slightly during milking. Modest changes in milk FA profile were also observed, as milk de novo and 16-C FA concentrations increased approximately 10 and 8%, respectively, whereas the concentration of preformed FA decreased about 7% during the milking. In agreement, mean milk FA chain length and unsaturation modestly decreased during milking (0.59 and 0.014 U, respectively). The observed changes in milk fat concentration during a milking are consistent with previous reports and reflect the dynamic nature of milk fat secretion from the mammary gland. Changes in milk FA profile are not expected to practically affect the accuracy of spectroscopy methods for determination of milk fat concentration. Furthermore, the small variation in FA profile during a milking limits the use of within-milking milk segregation to tailor milk FA profile.

Influence of fatty acid chain length and unsaturation on mid-infrared milk analysis.

Our first objective was to optimize center wavelengths and bandwidths for virtual filters used in a Fourier transform mid-infrared (MIR) milk analyzer. Optimization was accomplished by adjusting center wavelengths and bandwidths to minimize the size of intercorrection factors. Once optimized, the virtual filters were defined as follows: fat B sample, 3.508 microm (2,851 cm(-1)), and bandwidth of 0.032 microm (26 cm(-1)); fat B reference, 3.556 microm (2812 cm(-1)), and bandwidth of 0.030 microm (24 cm(-1)); lactose sample, 9.542 microm (1,048 cm(-1)), and bandwidth of 0.092 microm (20 cm(-1)); lactose reference, 7.734 microm (1,293 cm(-1)), and bandwidth of 0.084 microm (14 cm(-1)); protein sample, 6.489 microm (1,541 cm(-1)), and bandwidth of 0.085 microm (20 cm(-1)); protein reference, 6.707 microm (1491 cm(-1)), and bandwidth of 0.054 microm (12 cm(-1)); fat A sample, 5.721 microm (1,748 cm(-1)), and bandwidth of 0.052 microm (16 cm(-1)); fat A reference, 5.583 microm (1,791 cm(-1)), and bandwidth of 0.050 microm (16 cm(-1)). The bandwidth and its proximity to areas of intense water absorption had the largest effect on the intercorrection factors. The second objective was to quantify the impact of fatty acid chain length and unsaturation on fat B and fat A MIR measurements. Increasing the chain length increased the difference (i.e., MIR minus reference) between MIR prediction and reference chemistry by 0.0429% and by -0.0566% fat per unit of increase in carbon number per 1% change in fat, for fat B and fat A, respectively. Increasing the unsaturation decreased the difference (i.e., MIR minus reference) between MIR prediction of fat and chemistry for fat B by -0.4021% and increased fat A by 0.0291% fat per unit of increase in double bonds per 1% change in fat concentration.

Impact of fatty acid composition on the accuracy of mid-infrared fat analysis of farm milks.

Our objective was to determine whether data from a previous study using model milk emulsions to characterize the influence of variation in fatty acid chain length and unsaturation on mid-infrared (MIR) fat predictions could be used to identify a strategy to improve the accuracy of MIR fat predictions on a population of farm milks with a wide variation in fatty acid chain length and unsaturation. The mean fatty acid chain length for 45 farm milks was 14.417 carbons, and the mean unsaturation was 0.337 double bonds per fatty acid. The range of fatty acid chain lengths across the 45 farm milks was 1.23 carbons, and the range in unsaturation was 0.167 double bonds per fatty acid. Fat B (absorbance by the carbon-hydrogen stretch) MIR predictions increased and fat A MIR (absorbance by the ester carbonyl stretch) predictions decreased relative to reference chemistry with increasing fatty acid chain length. When the fat B MIR fat predictions were corrected for sample-to-sample variation in unsaturation, the positive correlation between fat B and fatty acid chain length increased from a coefficient of determination of 0.42 to 0.89. A 45:55 ratio of fat B corrected for unsaturation and fat A gave a smaller standard deviation of the difference between MIR prediction and reference chemistry than any ratio of the fat B (without correction for unsaturation) and fat A or either fat B or fat A alone. This demonstrates the technical feasibility of this approach to improve MIR testing accuracy for fat, if a simple procedure could be developed to determine the unsaturation of fat in milk rapidly and to correct the fat B reading for the effect of unsaturation before being combined with fat A.

Lipolysis and proteolysis of modified and producer milks used for calibration of mid-infrared milk analyzers.

Our objective was to determine if lipolysis or proteolysis of calibration sets during shelf life influenced the mid-infrared (MIR) readings or calibration slopes and intercepts. The lipolytic and proteolytic deterioration was measured for 3 modified milk and 3 producer milk calibration sets during storage at 4 degrees C. Modified and producer milk sets were used separately to calibrate an optical filter and virtual filter MIR analyzer. The uncorrected readings and slopes and intercepts of the calibration linear regressions for fat B, fat A, protein, and lactose were determined over 28 d for modified milks and 15 d for producer milks. It was expected that increases in free fatty acid content and decreases in the casein as a percentage of true protein of the calibration milks would have an effect on the MIR uncorrected readings, calibration slopes and intercepts, and MIR predicted readings. However, the influence of lipolysis and proteolysis on uncorrected readings was either not significant, or significant but very small. Likewise, the amount of variation accounted for by day of storage at 4 degrees C of a calibration set on the calibration slopes and intercepts was also very small. Most of the variation in uncorrected readings and calibration slopes and intercepts were due to differences between the optical filter and virtual filter analyzers and differences between the pasteurized modified milk and raw producer milk calibration sets, not due to lipolysis or proteolysis. The combined impact of lipolysis and proteolysis on MIR predicted values was <0.01% in most cases.

Calibration of infrared milk analyzers: modified milk versus producer milk.

Mid-infrared (MIR) milk analyzers are traditionally calibrated using sets of preserved raw individual producer milk samples. The goal of this study was to determine if the use of sets of preserved pasteurized modified milks improved calibration performance of MIR milk analyzers compared with calibration sets of producer milks. The preserved pasteurized modified milk sets exhibited more consistent day-to-day and set-to-set calibration slope and intercept values for all components compared with the preserved raw producer milk calibration sets. Pasteurized modified milk calibration samples achieved smaller confidence interval (CI) around the regression line (i.e., calibration uncertainty). Use of modified milk calibration sets with a larger component range, more even distribution of component concentrations within the ranges, and the lower correlation of fat and protein concentrations than producer milk calibration sets produced a smaller 95% CI for the regression line due to the elimination of moderate and high leverage samples. The CI for the producer calibration sets were about 2 to 12 times greater than the CI for the modified milk calibration sets, depending on the component. Modified milk calibration samples have the potential to produce MIR milk analyzer calibrations that will perform better in validation checks than producer milk-based calibrations by reducing the mean difference and standard deviation of the difference between instrument values and reference chemistry.

Modified versus producer milk calibration: mid-infrared analyzer performance validation.

Our objective was to determine the validation performance of mid-infrared (MIR) milk analyzers, using the traditional fixed-filter approach, when the instruments were calibrated with producer milk calibration samples vs. modified milk calibration samples. Ten MIR analyzers were calibrated using producer milk calibration sample sets, and 9 MIR milk analyzers were calibrated using modified milk sample sets. Three sets of 12 validation milk samples with all-laboratory mean chemistry reference values were tested during a 3-mo period. Calibration of MIR milk analyzers using modified milk increased the accuracy (i.e., better agreement with chemistry) and improved agreement between laboratories on validation milk samples compared with MIR analyzers calibrated with producer milk samples. Calibration of MIR analyzers using modified milk samples reduced overall mean Euclidian distance for all components for all 3 validation sets by at least 24% compared with MIR analyzers calibrated with producer milk sets. Calibration with modified milk sets reduced the average Euclidian distance from all-laboratory mean reference chemistry on validation samples by 40, 25, 36, and 27%, respectively for fat, anhydrous lactose, true protein, and total solids. Between-laboratory agreement was evaluated using reproducibility standard deviation (s(R)). The number of single Grubbs statistical outliers in the validation data was much higher (53 vs. 7) for the instruments calibrated with producer milk than for instruments calibrated with modified milk sets. The s(R) for instruments calibrated with producer milks (with statistical outliers removed) was similar to data collected in recent proficiency studies, whereas the s(R) for instruments calibrated with modified milks was lower than those calibrated with producer milks by 46, 52, 61, and 55%, respectively for fat, anhydrous lactose, true protein, and total solids.

Performance of selected milk fat fractions in cold-spreadable butter.

Based on solid fat content profiles, milk fat fractions produced by fractional crystallization procedures employing melted milk fat and milk fat dissolved in acetone were selected for incorporation into soft butter samples. Butter samples made from low melting liquid fractions or a combination of primarily low melting liquid fractions and a small amount of high melting solid fractions exhibited good spreadability at refrigerator temperature (4 degrees C) but were almost melted at room temperature (21 degrees C). Butters made with a high proportion of low melting liquid fraction, a small proportion of high melting solid, and a small proportion of very high melting solid fractions were still spreadable at refrigerator temperature and maintained their physical form at room temperature. Very high melting fractions, which provided key structural functionality in spreadable butter, were obtained from acetone fractionation. Because the use of acetone in processing may hinder or prevent commercialization of these fractions, other means to obtain very high melting fractions from milk fat should be pursued.