Prediction of coagulation properties, titratable acidity and pH of bovine milk using mid-infrared spectroscopy

This study investigated the potential application of mid-infrared spectroscopy (MIR 4,000–900 cm−1) for the determination of milk coagulation properties (MCP), titratable acidity (TA), and pH in Brown Swiss milk samples (n = 1,064). Because MCP directly influence the efficiency of the cheese-making process, there is strong industrial interest in developing a rapid method for their assessment. Currently, the determination of MCP involves time-consuming laboratory-based measurements, and it is not feasible to carry out these measurements on the large numbers of milk samples associated with milk recording programs. Mid-infrared spectroscopy is an objective and nondestructive technique providing rapid real-time analysis of food compositional and quality parameters. Analysis of milk rennet coagulation time (RCT, min), curd firmness (a30, mm), TA (SH°/50 mL; SH° = Soxhlet-Henkel degree), and pH was carried out, and MIR data were recorded over the spectral range of 4,000 to 900 cm−1. Models were developed by partial least squares regression using untreated and pretreated spectra. The MCP, TA, and pH prediction models were improved by using the combined spectral ranges of 1,600 to 900 cm−1, 3,040 to 1,700 cm−1, and 4,000 to 3,470 cm−1. The root mean square errors of cross-validation for the developed models were 2.36 min (RCT, range 24.9 min), 6.86 mm (a30, range 58 mm), 0.25 SH°/50 mL (TA, range 3.58 SH°/50 mL), and 0.07 (pH, range 1.15). The most successfully predicted attributes were TA, RCT, and pH. The model for the prediction of TA provided approximate prediction (R2 = 0.66), whereas the predictive models developed for RCT and pH could discriminate between high and low values (R2 = 0.59 to 0.62). It was concluded that, although the models require further development to improve their accuracy before their application in industry, MIR spectroscopy has potential application for the assessment of RCT, TA, and pH during routine milk analysis in the dairy industry. The implementation of such models could be a means of improving MCP through phenotypic-based selection programs and to amend milk payment systems to incorporate MCP into their payment criteria.

Genetic parameters and evaluations from single- and multiple-trait analysis of dairy cow fertility and milk production

Genetic parameters and breeding values for dairy cow fertility were estimated from 62 443 lactation records. Two-trait analysis of fertility and milk yield was investigated as a method to estimate fertility breeding values when culling or selection based on milk yield in early lactation determines presence or absence of fertility observations in later lactations. Fertility traits were calving interval, intervals from calving to first service, calving to conception and first to last service, conception success to first service and number of services per conception. Milk production traits were 305-day milk, fat and protein yield. For fertility traits, range of estimates of heritability (h(2)) was 0.012 to 0.028 and of permanent environmental variance (c(2)) was 0.016 to 0.032. Genetic correlations (r(g)) among fertility traits were generally high ( > 0.70). Genetic correlations of fertility with milk production traits were unfavourable (range -0.11 to 0.46). Single and two-trait analyses of fertility were compared using the same data set. The estimates of h(2) and c(2) were similar for two types of analyses. However, there were differences between estimated breeding values and rankings for the same trait from single versus multi-trait analyses. The range for rank correlation was 0.69-0.83 for all animals in the pedigree and 0.89-0.96 for sires with more than 25 daughters. As single-trait method is biased due to selection on milk yield, a multi-trait evaluation of fertility with milk yield is recommended. (C) 2002 Elsevier Science B.V. All rights reserved.

Comparison of methods for analysis of proteolysis by plasmin in milk

Sensitive methods that are currently used to monitor proteolysis by plasmin in milk are limited due to 7 their high cost and lack of standardisation for quality assurance in the various dairy laboratories. In 8 this study, four methods, trinitrobenzene sulphonic acid (TNBS), reverse phase high pressure liquid 9 chromatography (RP-HPLC), gel electrophoresis and fluorescamine, were selected to assess their 10 suitability for the detection of proteolysis in milk by plasmin. Commercial UHT milk was incubated 11 with plasmin at 37 °C for one week. Clarification was achieved by isoelectric precipitation (pH 4·6 12 soluble extracts)or 6% (final concentration) trichloroacetic acid (TCA). The pH 4·6 and 6% TCA 13 soluble extracts of milk showed high correlations (R2 > 0·93) by the TNBS, fluorescamine and 14 RP-HPLC methods, confirming increased proteolysis during storage. For gel electrophoresis,15 extensive proteolysis was confirmed by the disappearance of α- and β-casein bands on the seventh 16 day, which was more evident in the highest plasmin concentration. This was accompanied by the 17 appearance of α- and β-casein proteolysis products with higher intensities than on previous days, 18 implying that more products had been formed as a result of casein breakdown. The fluorescamine 19 method had a lower detection limit compared with the other methods, whereas gel electrophoresis 20 was the best qualitative method for monitoring β-casein proteolysis products. Although HPLC was the 21 most sensitive, the TNBS method is recommended for use in routine laboratory analysis on the basis 22 of its accuracy, reliability and simplicity.

Meta-analysis of relationships between enteric methane yield and milk fatty acid profile in dairy cattle

Various studies have indicated a relationship between enteric methane (CH4) production and milk fatty acid (FA) profiles of dairy cattle. However, the number of studies investigating such a relationship is limited and the direct relationships reported are mainly obtained by variation in CH4 production and milk FA concentration induced by dietary lipid supplements. The aim of this study was to perform a meta-analysis to quantify relationships between CH4 yield (per unit of feed and unit of milk) and milk FA profile in dairy cattle and to develop equations to predict CH4 yield based on milk FA profile of cows fed a wide variety of diets. Data from 8 experiments encompassing 30 different dietary treatments and 146 observations were included. Yield of CH4 measured in these experiments was 21.5 ± 2.46 g/kg of dry matter intake (DMI) and 13.9 ± 2.30 g/ kg of fat- and protein-corrected milk (FPCM). Correlation coefficients were chosen as effect size of the relationship between CH4 yield and individual milk FA concentration (g/100 g of FA). Average true correlation coefficients were estimated by a random-effects model. Milk FA concentrations of C6:0, C8:0, C10:0, C16:0, and C16:0-iso were significantly or tended to be positively related to CH4 yield per unit of feed. Concentrations of trans-6+7+8+9 C18:1, trans-10+11 C18:1, cis- 11 C18:1, cis-12 C18:1, cis-13 C18:1, trans-16+cis-14 C18:1, and cis-9,12 C18:2 in milk fat were significantly or tended to be negatively related to CH4 yield per unit of feed. Milk FA concentrations of C10:0, C12:0, C14:0-iso, C14:0, cis-9 C14:1, C15:0, and C16:0 were significantly or tended to be positively related to CH4 yield per unit of milk. Concentrations of C4:0, C18:0, trans-10+11 C18:1, cis-9 C18:1, cis-11 C18:1, and cis- 9,12 C18:2 in milk fat were significantly or tended to be negatively related to CH4 yield per unit of milk. Mixed model multiple regression and a stepwise selection procedure of milk FA based on the Bayesian information criterion to predict CH4 yield with milk FA as input (g/100 g of FA) resulted in the following prediction equations: CH4 (g/kg of DMI) = 23.39 + 9.74 × C16:0- iso – 1.06 × trans-10+11 C18:1 – 1.75 × cis-9,12 C18:2 (R2 = 0.54), and CH4 (g/kg of FPCM) = 21.13 – 1.38 × C4:0 + 8.53 × C16:0-iso – 0.22 × cis-9 C18:1 – 0.59 × trans-10+11 C18:1 (R2 = 0.47). This indicated that milk FA profile has a moderate potential for predicting CH4 yield per unit of feed and a slightly lower potential for predicting CH4 yield per unit of milk. Key words: methane , milk fatty acid profile , metaanalysis , dairy cattle

Selenium supplementation of lactating dairy cows: Effect on selenium concentration in blood, milk, urine and feces

The objectives were to determine effects of graded levels of selenized yeast derived from a specific strain of Saccharomyces cerevisiae (CNCM I-3060) on animal performance and in selenium concentrations in the blood, milk, feces, and urine of dairy cows compared with sodium selenite; and to provide preliminary data on the proportion of selenium as selenomethionine in the milk and blood. Twenty Holstein cows were used in a 5 × 5 Latin square design study in which all cows received the same total mixed rations, which varied only in source or concentration of dietary selenium. There were 5 experimental treatments. Total dietary selenium of treatment 1, which received no added selenium, was 0.15 mg/kg of dry matter, whereas values for treatments 2, 3, and 4, derived from selenized yeast, were 0.27, 0.33, and 0.40 mg/kg of dry matter, respectively. Treatment 5 contained 0.25 mg of selenium obtained from sodium selenite/kg of dry matter. There were no significant treatment effects on animal performance, and blood chemistry and hematology showed few treatment effects. Regression analysis noted significant positive linear effects of increasing dietary selenium derived from selenized yeast on selenium concentrations in the milk, blood, urine, and feces. In addition, milk selenium results indicated improved bioavailability of selenium from selenized yeast, compared with sodium selenite. Preliminary analyses showed that compared with sodium selenite, the use of selenized yeast increased the concentration of selenomethionine in the milk and blood. There was no indication of adverse effects on cow health associated with the use of selenized yeast.

Effects of corn silage derived from a genetically modified variety containing two Transgenes on feed intake, milk production, and composition, and the absence of detectable Transgenic deoxyribonucleic acid in milk in holstein dairy cows

The objectives were to compare the chemical composition, nutritive value, feed intake, milk production and composition, and presence in milk of transgenic DNA and the encoded protein Cry1Ab when corn silages containing 2 transgenes (2GM: herbicide tolerance: mepsps and insect resistance: cry1Ab) were fed as part of a standard total mixed ration (TMR) compared with a near isogenic corn silage ( C) to 8 multiparous lactating Holstein dairy cows in a single reversal design study. Cows were fed a TMR ration ad libitum and milked twice daily. Diets contained [ dry matter (DM) basis] 45% corn silage, 10% alfalfa hay, and 45% concentrate (1.66 Mcal of net energy for lactation/kg of DM, 15.8% crude protein, 35% neutral detergent fiber, and 4.1% fat). Each period was 28-d long. During the last 4 d of each period, feed intake and milk production data were recorded and milk samples taken for compositional analysis, including the presence of transgenic DNA and Cry1Ab protein. There was no significant difference in the chemical composition between C and 2GM silages, and both were within the expected range (37.6% DM, 1.51 Mcal of net energy for lactation/kg, 8.6% crude protein, 40% neutral detergent fiber, 19.6% acid detergent fiber, pH 3.76, and 62% in vitro DM digestibility). Cows fed the 2GM silage produced milk with slightly higher protein (3.09 vs. 3.00%), lactose ( 4.83 vs. 4.72%) and solids-not-fat (8.60 vs. 8.40%) compared with C. However, the yield (kg/d) of milk (36.5), 3.5% fat-corrected milk (34.4), fat (1.151), protein (1.106), lactose (1.738), and solids-not-fat ( 3.094), somatic cell count (log(10): 2.11), change in body weight (+ 7.8 kg), and condition score (+ 0.09) were not affected by type of silage, indicating no overall production difference. All milk samples were negative for the presence of transgenic DNA from either trait or the Cry1Ab protein. Results indicate that the 2GM silage modified with 2 transgenes did not affect nutrient composition of the silages and had no effect on animal performance and milk composition. No transgenic DNA and Cry1Ab protein were detected in milk.

Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets

Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.

The survival advantage of milk and dairy consumption: An overview of evidence from cohort studies of vascular diseases, diabetes and cancer

Objectives: To conduct it detailed evaluation, with meta-analyses, of the published evidence on milk and dairy consumption and the incidence of vascular diseases and diabetes. Also to summarise the evidence on milk and dairy consumption and cancer reported by the World Cancer Research Fund and then to consider the relevance of milk and dairy consumption to survival in the UK, a typical Western community. Finally, published evidence on relationships with whole milk and fat-reduced milks was examined. Methods: Prospective cohort studies of vascular disease and diabetes with baseline data on milk or dairy consumption and a relevant disease outcome were identified by searching MEDLINE, and reference lists in the relevant published reports. Meta-analyses of relationships in these reports were conducted. The likely effect of milk and dairy consumption on survival was then considered, taking into account the results of published overviews of relationships of these foods with cancer. Results: From meta-analysis of 15 studies the relative risk of stroke and/or heart disease in subjects with high milk or dairy consumption was 0.84 (95% CI 0.76, 0,93) and 0.79 (0.75, 0.82) respectively, relative to the risk in those with low consumption. Four studies reported incident diabetes as an outcome, and the relative risk in the Subjects with the highest intake of milk or diary foods was 0.92 (0.86, 0.97). Conclusions: Set against the proportion of total deaths attributable to the life-threatening diseases in the UK, vascular disease, diabetes and cancer, the results of meta-analyses provide evidence of an overall survival advantage from the consumption of milk and dairy foods.

A revised Tobit procedure for mitigating bias in the presence of non-zero censoring with an application to milk-market participation in the Ethiopian highlands

Fixed transactions costs that prohibit exchange engender bias in supply analysis due to censoring of the sample observations. The associated bias in conventional regression procedures applied to censored data and the construction of robust methods for mitigating bias have been preoccupations of applied economists since Tobin [Econometrica 26 (1958) 24]. This literature assumes that the true point of censoring in the data is zero and, when this is not the case, imparts a bias to parameter estimates of the censored regression model. We conjecture that this bias can be significant; affirm this from experiments; and suggest techniques for mitigating this bias using Bayesian procedures. The bias-mitigating procedures are based on modifications of the key step that facilitates Bayesian estimation of the censored regression model; are easy to implement; work well in both small and large samples; and lead to significantly improved inference in the censored regression model. These findings are important in light of the widespread use of the zero-censored Tobit regression and we investigate their consequences using data on milk-market participation in the Ethiopian highlands. (C) 2004 Elsevier B.V. All rights reserved.

Alternatives to linear analysis of energy balance data from lactating dairy cows

The current energy requirements system used in the United Kingdom for lactating dairy cows utilizes key parameters such as metabolizable energy intake (MEI) at maintenance (MEm), the efficiency of utilization of MEI for 1) maintenance, 2) milk production (k(l)), 3) growth (k(g)), and the efficiency of utilization of body stores for milk production (k(t)). Traditionally, these have been determined using linear regression methods to analyze energy balance data from calorimetry experiments. Many studies have highlighted a number of concerns over current energy feeding systems particularly in relation to these key parameters, and the linear models used for analyzing. Therefore, a database containing 652 dairy cow observations was assembled from calorimetry studies in the United Kingdom. Five functions for analyzing energy balance data were considered: straight line, two diminishing returns functions, (the Mitscherlich and the rectangular hyperbola), and two sigmoidal functions (the logistic and the Gompertz). Meta-analysis of the data was conducted to estimate k(g) and k(t). Values of 0.83 to 0.86 and 0.66 to 0.69 were obtained for k(g) and k(t) using all the functions (with standard errors of 0.028 and 0.027), respectively, which were considerably different from previous reports of 0.60 to 0.75 for k(g) and 0.82 to 0.84 for k(t). Using the estimated values of k(g) and k(t), the data were corrected to allow for body tissue changes. Based on the definition of k(l) as the derivative of the ratio of milk energy derived from MEI to MEI directed towards milk production, MEm and k(l) were determined. Meta-analysis of the pooled data showed that the average k(l) ranged from 0.50 to 0.58 and MEm ranged between 0.34 and 0.64 MJ/kg of BW0.75 per day. Although the constrained Mitscherlich fitted the data as good as the straight line, more observations at high energy intakes (above 2.4 MJ/kg of BW0.75 per day) are required to determine conclusively whether milk energy is related to MEI linearly or not.

Estimation of milk production from smallholder dairy cattle in the coastal lowlands of Kenya

A study was carried out on 92 smallholder farms in Kwale district in Coast Province of Kenya to estimate the milk yield. The effect of concentrate feed supplementation on milk yield was also evaluated. Data were collected during a one-year observational longitudinal study. Analysis was done for 371 observations following 63 calving events. The mean annual milk offtake was estimated at 2021 kg/cow. Forty-nine (77.8%) of the lactating cows were supplemented with concentrate feeds at varying rates of 0.5-3.0 kg/cow per day. Supplementary feeding of lactating cows led to a significantly higher mean daily milk yield compared to non-supplemented cows throughout the year (p<0.05). The mean annual milk offtake from supplemented cows (2195 kg/cow) was 18.6% more than offtake from non-supplemented cows, a difference that was statistically significant (p<0.05). Therefore, supplementary feeding of commercial feed concentrates was a rational management practice. It was also concluded that milk production from smallholder dairy cows in the coastal lowlands of Kenya was comparable to that from similar production systems but lower than national targets.

Detection of transgenic DNA and protein, in rumen fluid, duodenal digesta, milk, blood and faeces of lactating dairy cows

The objective was to determine the presence or absence of transgenic and endogenous plant DNA in ruminal fluid, duodenal digesta, milk, blood, and feces, and if found, to determine fragment size. Six multiparous lactating Holstein cows fitted with ruminal and duodenal cannulas received a total mixed ration. There were two treatments (T). In T1, the concentrate contained genetically modified (GM) soybean meal (cp4epsps gene) and GM corn grain (cry1a[b] gene), whereas T2 contained the near isogenic non-GM counterparts. Polymerase chain reaction analysis was used to determine the presence or absence of DNA sequences. Primers were selected to amplify small fragments from single-copy genes (soy lectin and corn high-mobility protein and cp4epsps and cry1a[b] genes from the GM crops) and multicopy genes (bovine mitochondrial cytochrome b and rubisco). Single-copy genes were only detected in the solid phase of rumen and duodenal digesta. In contrast, fragments of the rubisco gene were detected in the majority of samples analyzed in both the liquid and solid phases of ruminal and duodenal digesta, milk, and feces, but rarely in blood. The size of the rubisco gene fragments detected decreased from 1176 bp in ruminal and duodenal digesta to 351 bp in fecal samples.

Detection of transgenic and endogenous plant DNA in rumen fluid, duodenal digesta, milk, blood, and feces of lactating dairy cows

The objective was to determine the presence or absence of transgenic and endogenous plant DNA in ruminal fluid, duodenal digesta, milk, blood, and feces, and if found, to determine fragment size. Six multiparous lactating Holstein cows fitted with ruminal and duodenal cannulas received a total mixed ration. There were two treatments (T). In T1, the concentrate contained genetically modified (GM) soybean meal (cp4epsps gene) and GM corn grain (cry1a[b] gene), whereas T2 contained the near isogenic non-GM counterparts. Polymerase chain reaction analysis was used to determine the presence or absence of DNA sequences. Primers were selected to amplify small fragments from single-copy genes (soy lectin and corn high-mobility protein and cp4epsps and cry1a[b] genes from the GM crops) and multicopy genes (bovine mitochondrial cytochrome b and rubisco). Single-copy genes were only detected in the solid phase of rumen and duodenal digesta. In contrast, fragments of the rubisco gene were detected in the majority of samples analyzed in both the liquid and solid phases of ruminal and duodenal digesta, milk, and feces, but rarely in blood. The size of the rubisco gene fragments detected decreased from 1176 bp in ruminal and duodenal digesta to 351 bp in fecal samples.

The use of early lactation milk protein content to predict subsequent fertility performance and likelihood of culling, in commercial dairy cows

A dataset of 1,846,990 completed lactation record,; was created Using milk recording data from 8,967 commercial dairy farms in the United Kingdom over a five year period. Herd-specific lactation curves describing levels of milk, Cat and protein by lactation number and month of calving were generated for each farm. The actual yield of milk and protein proportion at the first milk recording of individual cow lactations were compared with the levels taken from the lactation curves. Logistic regression analysis showed that cows production milk with a lower percentage of protein than average had a significantly lower probability of being in-calf at 100 days post calving and it significantly higher probability of being culled at the end of lactation. The culling rates derived from the studied database demonstrate the current high wastage rate of commercial dairy cows. Well of this wastage is due to involuntary culling as a result of reproductive failure.

Evaluation of milk urea nitrogen as a diagnostic of protein feeding

An evaluation of milk urea nitrogen (MUN) as a diagnostic of protein feeding in dairy cows was performed using mean treatment data (n = 306) from 50 production trials conducted in Finland (n = 48) and Sweden (n = 2). Data were used to assess the effects of diet composition and certain animal characteristics on MUN and to derive relationships between MUN and the efficiency of N utilization for milk production and urinary N excretion. Relationships were developed using regression analysis based on either models of fixed factors or using mixed models that account for between-experiment variations. Dietary crude protein (CP) content was the best single predictor of MUN and accounted for proportionately 0.778 of total variance [ MUN (mg/dL) = -14.2 + 0.17 x dietary CP content (g/kg dry matter)]. The proportion of variation explained by this relationship increased to 0.952 when a mixed model including the random effects of study was used, but both the intercept and slope remained unchanged. Use of rumen degradable CP concentration in excess of predicted requirements, or the ratio of dietary CP to metabolizable energy as single predictors, did not explain more of the variation in MUN (R-2 = 0.767 or 0.778, respectively) than dietary CP content. Inclusion of other dietary factors with dietary CP content in bivariate models resulted in only marginally better predictions of MUN (R-2 = 0.785 to 0.804). Closer relationships existed between MUN and dietary factors when nutrients (CP to metabolizable energy) were expressed as concentrations in the diet, rather than absolute intakes. Furthermore, both MUN and MUN secretion (g/d) provided more accurate predictions of urinary N excretion (R-2 = 0.787 and 0.835, respectively) than measurements of the efficiency of N utilization for milk production (R-2 = 0.769). It is concluded that dietary CP content is the most important nutritional factor influencing MUN, and that measurements of MUN can be utilized as a diagnostic of protein feeding in the dairy cow and used to predict urinary N excretion.