Nicolas Gengler

Mid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems, and countries

Increasing consumer concern exists over the relationship between food composition and human health. Because of the known effects of fatty acids on human health, the development of a quick, inexpensive, and accurate method to directly quantify the fatty acid (FA) composition in milk would be valuable for milk processors to develop a payment system for milk pertinent to their customer requirements and for farmers to adapt their feeding systems and breeding strategies accordingly. The aim of this study was (1) to confirm the ability of mid-infrared spectrometry (MIR) to quantify individual FA content in milk by using an innovative procedure of sampling (i.e., samples were collected from cows belonging to different breeds, different countries, and in different production systems); (2) to compare 6 mathematical methods to develop robust calibration equations for predicting the contents of individual FA in milk; and (3) to test interest in using the FA equations developed in milk as basis to predict FA content in fat without corrections for the slope and the bias of the developed equations. In total, 517 samples selected based on their spectral variability in 3 countries (Belgium, Ireland, and United Kingdom) from various breeds, cows, and production systems were analyzed by gas chromatography (GC). The samples presenting the largest spectral variability were used to calibrate the prediction of FA by MIR. The remaining samples were used to externally validate the 28 FA equations developed. The 6 methods were (1) partial least squares regression (PLS); (2) PLS+repeatability file (REP); (3) first derivative of spectral data+PLS; (4) first derivative+REP+PLS; (5) second derivative of spectral data+PLS; and (6) second derivative+REP+PLS. Methods were compared on the basis of the cross-validation coefficient of determination (R2cv), the ratio of standard deviation of GC values to the standard error of cross-validation (RPD), and the validation coefficient of determination (R2v). The third and fourth methods had, on average, the highest R2cv, RPD, and R2v. The final equations were built using all GC and the best accuracy was observed for the infrared predictions of C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, C16:0, C18:0, C18:1 trans, C18:1 cis-9, C18:1 cis, and for some groups of FA studied in milk (saturated, monounsaturated, unsaturated, short-chain, medium-chain, and long-chain FA). These equations showed R2cv greater than 0.95. With R2cv equal to 0.85, the MIR prediction of polyunsaturated FA could be used to screen the cow population. As previously published, infrared predictions of FA in fat are less accurate than those developed from FA content in milk (g/dL of milk) and no better results were obtained by using milk FA predictions if no corrections for bias and slope based on reference milk samples with known contents of FA were used. These results indicate the usefulness of equations with R2cv greater than 95% in milk payment systems and the usefulness of equations with R2cv greater than 75% for animal breeding purposes.

Candidate gene markers associated with somatotropic axis and milk selection

One of the obstacles to progress in dairy cattle selection is that milk production traits are only expressed after the first calving. However, the use of the quantitative trait loci (QTL) technology will improve the efficiency of dairy industry with a positive image for the consumers. QTL are part of the genome showing a preponderant action and explaining the major part of variation of the trait production. At the present time, the two major strategies developed to detect such QTL are the candidate gene approach and the positional genetics approach. The somatotropic axis contains the most promising candidates in this respect, as it strongly regulates milk production. Then, the identification of favorable QTL associated with the somatotropic axis that are significantly correlated with genetic merits for milk production could lead to more effective selection programs.

Potential estimation of major mineral contents in cow milk using mid-infrared spectrometry

Milk and dairy products are a major source of minerals, particularly calcium, involved in several metabolic functions in humans. Currently, several dairy products are enriched with calcium to prevent osteoporosis. The development of an inexpensive and fast quantitative analysis for minerals is required to offer dairy farmers an opportunity to improve the added value of the produced milk. The aim of this study was to develop 5 equations to measure Ca, K, Mg, Na, and P contents directly in bovine milk using mid-infrared (MIR) spectrometry. A total of 1,543 milk samples were collected between March 2005 and May 2006 from 478 cows during the Walloon milk recording and analyzed by MIR spectrometry. Using a principal component approach, 62 milk samples were selected by their spectral variability and separated in 2 calibration sets. Five outliers were detected and deleted. The mineral contents of the selected samples were measured by inductively coupled plasma atomic emission spectrometry. Using partial least squares combined with a repeatability file, 5 calibration equations were built to estimate the contents of Ca, K, Mg, Na, and P in milk. To assess the accuracy of the developed equations, a full cross-validation and an external validation were performed. The cross-validation coefficients of determination (R(2)cv) were 0.80, 0.70, and 0.79 for Ca, Na, and P, respectively (n = 57), and 0.23 and 0.50 for K and Mg, respectively (n = 31). Only Ca, Na, and P equations showed sufficient R(2)cv for a potential application. These equations were validated using 30 new milk samples. The validation coefficients of determination were 0.97, 0.14, and 0.88 for Ca, Na, and P, respectively, suggesting the potential to use the Ca and P calibration equations. The last 30 samples were added to the initial milk samples and the calibration equations were rebuilt. The R(2)cv for Ca, K, Mg, Na, and P were 0.87, 0.36, 0.65, 0.65, and 0.85, respectively, confirming the potential utilization of the Ca and P equations. Even if new samples should be added in the calibration set, the first results of this study showed the feasibility to quantify the calcium and phosphorus directly in bovine milk using MIR spectrometry.

Genetic parameters of saturated and monounsaturated fatty acid content and the ratio of saturated to unsaturated fatty acids in bovine milk.

Fatty acid composition influences the nutritional quality of milk and the technological properties of butter. Using a prediction of fatty acid (FA) contents by mid-infrared (MIR) spectrometry, a large amount of data concerning the FA profile in bovine milk was collected. The large number of records permitted consideration of more complex models than those used in previous studies. The aim of the current study was to estimate the effects of season and stage of lactation as well as genetic parameters of saturated (SAT) and monounsaturated (MONO) fatty acid contents in bovine milk and milk fat, and the ratio of SAT to unsaturated fatty acids (UNSAT) that reflect the hardness of butter (SAT:UNSAT), using 7 multiple-trait, random-regression test-day models. The relationship between these FA traits with common production traits was also studied. The data set contained 100,841 test-day records of 11,626 Holstein primiparous cows. The seasonal effect was studied based on unadjusted means. These results confirmed that milk fat produced during spring and summer had greater UNSAT content compared with winter (63.13 vs. 68.94% of SAT in fat, on average). The effect of stage of lactation on FA profile was studied using the same methodology. Holstein cows in early first lactation produced a lower content of SAT in their milk fat. Variance components were estimated using a Bayesian method via Gibbs sampling. Heritability of SAT in milk (0.42) was greater than heritability of SAT in milk fat (0.24). Estimates of heritability for MONO were also different in milk and fat (0.14 vs. 0.27). Heritability of SAT:UNSAT was moderate (0.27). For all of these traits, the heritability estimates and the genetic and phenotypic correlations varied through the lactation.

Invited review: overview of new traits and phenotyping strategies in dairy cattle with a focus on functional traits

For several decades, breeding goals in dairy cattle focussed on increased milk production. However, many functional traits have negative genetic correlations with milk yield, and reductions in genetic merit for health and fitness have been observed. Herd management has been challenged to compensate for these effects and to balance fertility, udder health and metabolic diseases against increased production to maximize profit without compromising welfare. Functional traits, such as direct information on cow health, have also become more important because of growing concern about animal well-being and consumer demands for healthy and natural products. There are major concerns about the impact of drugs used in veterinary medicine on the spread of antibiotic-resistant strains of bacteria that can negatively impact human health. Sustainability and efficiency are also increasingly important because of the growing competition for high-quality, plant-based sources of energy and protein. Disruptions to global environments because of climate change may encourage yet more emphasis on these traits. To be successful, it is vital that there be a balance between the effort required for data recording and subsequent benefits. The motivation of farmers and other stakeholders involved in documentation and recording is essential to ensure good data quality. To keep labour costs reasonable, existing data sources should be used as much as possible. Examples include the use of milk composition data to provide additional information about the metabolic status or energy balance of the animals. Recent advances in the use of mid-infrared spectroscopy to measure milk have shown considerable promise, and may provide cost-effective alternative phenotypes for difficult or expensive-to-measure traits, such as feed efficiency. There are other valuable data sources in countries that have compulsory documentation of veterinary treatments and drug use. Additional sources of data outside of the farm include, for example, slaughter houses (meat composition and quality) and veterinary labs (specific pathogens, viral loads). At the farm level, many data are available from automated and semi-automated milking and management systems. Electronic devices measuring physiological status or activity parameters can be used to predict events such as oestrus, and also behavioural traits. Challenges concerning the predictive biology of indicator traits or standardization need to be solved. To develop effective selection programmes for new traits, the development of large databases is necessary so that high-reliability breeding values can be estimated. For expensive-to-record traits, extensive phenotyping in combination with genotyping of females is a possibility.

Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows

This study investigates the feasibility to predict individual methane (CH(4)) emissions from dairy cows using milk mid-infrared (MIR) spectra. To have a large variability of milk composition, two experiments were conducted on 11 lactating Holstein cows (two primiparous and nine multiparous). The first experiment aimed to induce a large variation in CH(4) emission by feeding two different diets: the first one was mainly composed of fresh grass and sugar beet pulp and the second one of maize silage and hay. The second experiment consisted of grass and corn silage with cracked corn, soybean meal and dried pulp. For each milking period, the milk yields were recorded twice daily and a milk sample of 50 ml was collected from each cow and analyzed by MIR spectrometry. Individual CH(4) emissions were measured daily using the sulfur hexafluoride method during a 7-day period. CH(4) daily emissions ranged from 10.2 to 47.1 g CH(4)/kg of milk. The spectral data were transformed to represent an average daily milk spectrum (AMS), which was related to the recorded daily CH(4) data. By assuming a delay before the production of fermentation products in the rumen and their use to produce milk components, five different calculations were used: AMS at days 0, 0.5, 1, 1.5 and 2 compared with the CH(4) measurement. The equations were built using Partial Least Squares regression. From the calculated R(2)(cv), it appears that the accuracy of CH(4) prediction by MIR changed in function of the milking days. In our experimental conditions, the AMS at day 1.5 compared with the measure of CH(4) emissions gave the best results. The R(2) and s.e. of the cross-validation were equal to 0.79 and 5.14 g of CH(4)/kg of milk. The multiple correlation analysis performed in this study showed the existence of a close relationship between milk fatty acid (FA) profile and CH(4) emission at day 1.5. The lower R(2) (R(2) = 0.76) obtained between FA profile and CH(4) emission compared with the one corresponding to the obtained calibration (R(2)(c) = 0.87) shows the interest to apply directly the developed CH(4) equation instead of the use of correlations between FA and CH(4). In conclusion, our preliminary results suggest the feasibility of direct CH(4) prediction from milk MIR spectra. Additional research has the potential to improve the calibrations even further. This alternative method could be useful to predict the individual CH(4) emissions at farm level or at the regional scale and it also could be used to identify low-CH(4)-emitting cows.

Phenotypic and genetic variability of production traits and milk fatty acid contents across days in milk for Walloon Holstein first-parity cows.

The objective of this study was to assess the phenotypic and genetic variability of production traits and milk fatty acid (FA) contents throughout lactation. Genetic parameters for milk, fat, and protein yields, fat and protein contents, and 19 groups and individual FA contents in milk were estimated for first-parity Holstein cows in the Walloon Region of Belgium using single-trait, test-day animal models and random regressions. Data included 130,285 records from 26,166 cows in 531 herds. Heritabilities indicated that de novo synthesized FA were under stronger genetic control than FA originating from the diet and from body fat mobilization. Estimates for saturated short- and medium-chain individual FA ranged from 0.35 for C4:0 to 0.44 for C8:0, whereas those for monounsaturated long-chain individual FA were lower (around 0.18). Moreover, de novo synthesized FA were more heritable in mid to late lactation. Approximate daily genetic correlations among traits were calculated as correlations between daily breeding values for days in milk between 5 and 305. Averaged daily genetic correlations between milk yield and FA contents did not vary strongly among FA (around -0.35) but they varied strongly across days in milk, especially in early lactation. Results indicate that cows selected for high milk yield in early lactation would have lower de novo synthesized FA contents in milk but a slightly higher content of C18:1 cis-9, indicating that such cows might mobilize body fat reserves. Genetic correlations among FA emphasized the combination of FA according to their origin: contents in milk of de novo FA were highly correlated with each other (from 0.64 to 0.99). Results also showed that genetic correlations between C18:1 cis-9 and other FA varied strongly during the first 100 d in milk and reinforced the statement that the release of long-chain FA inhibits FA synthesis in the mammary gland while the cow is in negative energy balance. Finally, results showed that the FA profile in milk changed during the lactation phenotypically and genetically, emphasizing the relationship between the physiological status of cow and milk composition.

Evaluation of heat stress effects on production traits and somatic cell score of Holsteins in a temperate environment

This study was aimed to evaluate the degree of thermal stress exhibited by Holsteins under a continental temperate climate. Milk, fat, protein, and somatic cell count test-day records collected between 2000 and 2011 from 23,963 cows in 604 herds were combined with meteorological data from 14 public weather stations in Luxembourg. Daily values of 6 different thermal indices (TI) weighted in term of temperature, relative humidity, solar radiation, and wind speed were calculated by averaging hourly TI over 24h. Heat stress thresholds were first identified by a broken-line regression model. Regression models were thereafter applied to quantify milk production losses due to heat stress. The tipping points at which milk and protein yields declined were effectively identified. For fat yield, no valid threshold was identified for any of the studied TI. Daily fat yields tended to decrease steadily with increasing values of TI. Daily somatic cell score patterns were marked by increased values at both lowest and highest TI ranges, with a more pronounced reaction to cold stress for apparent temperature indices. Thresholds differed between TI and traits. For production traits, they ranged from 62 (TI(1)) to 80 (TI(3)) for temperature-humidity indices (THI) and from 16 (TI(5)) to 20 (TI(6)) for apparent temperature indices. Corresponding somatic cell score thresholds were higher and ranged from 66 (TI(1)) to 82 (TI(3)) and from 20 (TI(5)) to 23 (TI(6)), respectively. The largest milk decline per unit of mild, moderate, and extreme heat stress levels of 0.164, 0.356, and 0.955 kg, respectively, was observed when using the conventional THI (TI(1)). The highest yearly milk, fat, and protein losses of 54, 5.7, and 4.2 kg, respectively, were detected by TI(2), the THI index that is adjusted for wind speed and solar radiation. The latter index could be considered as the best indicator of heat stress to be used for forecast and herd management in a first step in temperate regions under anticipated climate changes.

Variation of Δ9-Desaturase Activity in Dairy Cattle

The endogenous production of unsaturated fatty acids (FA), particularly some monounsaturated FA (%MONO) and nearly all conjugated linoleic acids, is regulated by the Delta(9)-desaturase activity. The aims of this study were to assess the variation of this enzymatic activity within lactation, across dairy breeds, and to estimate its genetic parameters. The ratios of C14:1 cis-9 to C14:0, C16:1 cis-9 to C16:0, and C18:1 cis to C18:0 were calculated from FA contents predicted by mid-infrared spectrometry. Variance components and standard errors were estimated using average information REML. The multitrait mixed model included as fixed effects herd x test date x class of lactation number, class of days in milk x class of lactation number, class of age x class of lactation number, and regressions on breed composition. Four random effects were also included: animal genetic effect, 2 permanent environments (within and across lactations), and residual effect. Under the assumption that the calculated ratios are an approximate measurement of Delta(9)-desaturase activity, this study showed different sources of variation for this enzymatic activity. A slight difference was observed within lactation. The ratios of C14:1 cis-9 to C14:0 and C16:1 cis-9 to C16:0 increased as a function of days in milk. Differences across 7 dairy breeds were observed. The values of Delta(9)-desaturase indices observed for Jersey and Brown-Swiss cows were lower compared with Holstein. The opposite was observed for dual-purpose Belgian Blue cows. Values of heritability for the ratios of C14:1 cis-9 to C14:0, C16:1 cis-9 to C16:0, and C18:1 cis to C18:0 were 20, 20, and 3%, respectively. Negative genetic correlations observed between fat or protein contents and the 3 indices suggested that an increased activity of Delta(9)-desaturase could inhibit the synthesis of fat and protein in bovine milk. Negative correlations were also observed between fat or protein contents and the contents of 3 studied unsaturated FA in milk fat (C14:1 cis-9, C16:1 cis-9, and C18:1 cis). The positive genetic correlations observed between %MONO and the ratios of C14:1 cis-9 to C14:0 (0.72), C16:1 cis-9 to C16:0 (0.62), and C18:1 cis to C18:0 (0.97) showed that %MONO is linked to the Delta(9)-desaturase activity.

Phenotypic variation in live weight and live-weight changes of lactating Holstein-Friesian cows

This study quantified individual phenotypic variation in live weight and live-weight changes during the first three lactations and estimated the effects of age, lactation week and pregnancy on live weight. Data comprised weekly averaged live weight (calculated from daily observations) during 452 lactations of 239 Holstein-Friesian cows. Unadjusted mean live weights were 553 (s.d. 50), 611 (s.d. 55) and 654 (s.d. 57) kg during first, second and third parity, respectively. Estimated effect of growth during parity was 46, 52 and 23 kg for the first three parities. Mean maximum weight loss was 26, 22 and 22 kg for first, second and third parity and variation was large among individuals. Week of lactation when cows had their maximum weight loss ranged from 7 weeks in first lactation to 13 weeks in third lactation. Estimated maximum effect of pregnancy on live weight during the lactation varied from 27 to 59 kg. Phenotypic variance in live weight increased with parity. Repeatabilities of live-weight observations within parity were 0.85 . Across parities, high repeatabilities were found for calving weight and mean live weight but not for parameters associated with maximum weight loss. Correlations between weekly means and mean live weight during the whole of lactation were high. It was concluded that single live-weight observations of heifers are a good measurement of mean live weight during the first three panties.