This is the first reported controlled trial of dietary intervention in patients with gout, and suggests that SMP enriched with GMP and G600 may reduce the frequency of gout flares.

A number of studies have focused on bar hardening of protein bars. The instrumental texture analyzer measurement of peak force is known to measure bar hardness or firmness. However, to understand overall bar texture, another important texture dimension, crumbliness/cohesiveness, needs to be considered. This study was based on three functionally modified dairy proteins, including one whey protein concentrate and two milk protein concentrates. A mixture design was used to study the synergistic effects of these three proteins on bar texture. Instrumental texture parameters that correlated with sensory texture were developed. Peak force (Force 1) was correlated with firmness (being opposite of softness) dimension, and maximum negative force (Force 2) was correlated with cohesiveness (being opposite of crumbliness). Mathematical models with R2 > 90% were developed to optimize the texture over a 12‐month storage period, with storage at 20C, for bars using one or more of the three proteins. PRACTICAL APPLICATIONS Protein bar manufacturers will be able to select the type of dairy protein and the level of the proteins in a blend required to achieve desired texture in bars based on the findings of this study. The whey protein concentrate, used in this study, proved to be important to minimize firmness over time. The milk protein concentrates in this study performed differently from each other in bars due to the different modifications made during the manufacture of these ingredients. This study has also shown the importance of the crumbliness/cohesiveness texture dimension and investigated a method to quantify this using instrumental texture analysis. The mixture design approach used in this study could be applied to a bar manufacturer's specific formulation to develop a predictive model that will help them adjust key ingredient levels to manipulate the texture in bars.

Reducing enteric methane (CH 4 ) production and improving feed conversion efficiency of dairy cows is of high importance. Residual feed intake (RFI) is one measure of feed efficiency, with low RFI animals being more efficient in feed conversion. Enteric CH 4 is an important source of digestible energy loss in ruminants and, because research in beef cattle has reported a positive relationship between RFI and daily CH 4 production, we hypothesized that low RFI dairy heifers, which are more feed efficient, would produce less CH 4 /d. We measured the daily methane production (g of CH 4 /d), methane yield [g of CH 4 /kg of dry matter intake (DMI)], and CH 4 per kilogram of body weight (BW) gain for 56 heifers (20-22 mo old) in a 2 × 2 factorial arrangement: factors included 2 breeds (Holstein-Friesian and Jersey; n = 28/breed), with equal numbers of animals previously determined as being either high [+2.0 kg of dry matter (DM)/d] or low RFI (−2.1 kg of DM/d; n = 28/RFI category). All heifers were commingled and offered unrestricted access to the same diet of dried alfalfa cubes. Between RFI categories, heifers did not differ in BW or BW gain but low RFI heifers had 9.3 and 10.6% lower DMI and DMI/kg of BW, respectively, than high RFI heifers. Similarly, RFI category did not affect CH 4 /d or CH 4 /kg of BWg, but CH 4 /kg of DMI was higher in low RFI heifers because of their lower DMI. These results might reflect more complete digestion of ingested feed in the more efficient, low RFI heifers, consistent with previous reports of greater apparent digestibility of organic matter. Holstein-Friesian heifers were heavier and consumed more total DM than Jersey heifers, but breed did not affect DMI/kg of BW or BWg. Jersey heifers produced less CH 4 /d, but not CH 4 /kg of DMI or CH 4 /kg of BWg. We detected no interaction between breed and RFI category in any of the variables measured. In conclusion, differences in RFI in dairy heifers did not affect daily CH 4 production (g/d); however, low RFI heifers had a greater CH 4 yield (g/kg of DMI) on a high forage diet.

Heat-induced gelation (80 degrees C for 30 min or 85 degrees C for 60 min) of whey protein concentrate (WPC) solutions was studied using small deformation dynamic rheology, small and large deformation compression, and polyacrylamide gel electrophoresis (PAGE). The WPC solutions (15% w/w, pH 6.9) were prepared by dispersing WPC powder in water (control), 1% (w/w) sodium dodecyl sulfate (SDS) solution, and N-ethylmaleimide (NEM) solution at a protein/NEM molar ratio of 1:1 or in 10 mM dithiothreitol (DTT) solution. PAGE analyses showed that the heat treatment of control solutions contained both disulfide and non-covalent linkages between denatured protein molecules. Only disulfide linkages were formed in heated SDS-WPC solutions, whereas only non-covalent linkages were formed in DTT-WPC and NEM-WPC solutions during heating. In heated NEM-WPC solutions, the pre-existing disulfide linkages remained unaltered. Small deformation rheology measurements showed that the storage modulus (G') values, compared with those of the control WPC gels (approximately 14000 Pa), were 3 times less for the SDS-WPC gels (approximately 4000 Pa), double for the NEM-WPC gels (approximately 24000 Pa), and even higher for the DTT-WPC gels (approximately 30000 Pa). Compression tests suggested that the rubberiness (fracture strain) of the WPC gels increased as the degree of disulfide linkages within the gels increased, whereas the stiffness (modulus) of the gels increased as the degree of non-covalent associations among the denatured protein molecules increased.

Water use in intensively managed, confinement dairy systems has been widely studied, but few reports exist regarding water use on pasture-based dairy farms. The objective of this study was to quantify the seasonal pattern of water use to develop a prediction model of water use for pasture-based dairy farms. Stock drinking, milking parlor, and total water use was measured on 35 pasture-based, seasonal calving dairy farms in New Zealand over 2 yr. Average stock drinking water was 60 L/cow per day, with peak use in summer. We estimated that, on average, 26% of stock drinking water was lost through leakage from water-distribution systems. Average corrected stock drinking water (equivalent to voluntary water intake) was 36 L/cow per day, and peak water consumption was 72 L/cow per day in summer. Milking parlor water use increased sharply at the start of lactation (July) and plateaued (August) until summer (February), after which it decreased with decreasing milk production. Average milking parlor water use was 58 L/cow per day (between September and February). Water requirements were affected by parlor type, with rotary milking parlor water use greater than herringbone parlor water use. Regression models were developed to predict stock drinking and milking parlor water use. The models included a range of climate, farm, and milk production variables. The main drivers of stock drinking water use were maximum daily temperature, potential evapotranspiration, radiation, and yield of milk and milk components. The main drivers for milking parlor water use were average per cow milk production and milking frequency. These models of water use are similar to those used in confinement dairy systems, where milk yield is commonly used as a variable. The models presented fit the measured data more accurately than other published models and are easier to use on pasture-based dairy farms, as they do not include feed and variables that are difficult to measure on pasture-based farms.