Effects of dry period length on milk production and energy balance in two cow breeds

Shortening the dry period (DP) has been proposed as a strategy to improve energy balance (EB) in cows in early lactation. This study evaluated the effects of shortening the DP on milk yield (MY), EB and residual feed intake (RFI) in two breeds; Swedish Red (SR) and Swedish Holstein (SH). Cows were blocked by breed and parity and then randomly assigned to one of two treatments; short DP of 4 weeks (4W, n=43) or conventional DP of 8 weeks (8W, n=34). Cows were kept and fed under the same conditions, except for the 4 weeks when the 4W group were still lactating prepartum and thus kept with the lactating cows. Milk yield and BW were recorded and body condition score (BCS) was rated from 10 weeks prepartum to 12 weeks postpartum. Dry matter intake (DMI) was recorded for lactating cows postpartum. Milk yield was reduced by 6.75 kg/day during the first 12 weeks postpartum (P<0.001) for the 4W cows compared with 8W cows, but there was no significant difference in total MY (3724 kg compared with 3684 kg, P=0.7) when the milk produced prepartum was included. Protein content was higher in 4W cows (3.42%) than in 8W cows (3.27%) (P<0.001) postpartum. In the 8W group, cows lost more BCS after calving (P<0.05). Cows of SR breed had higher BCS than cows of SH breed (SR=3.7, SH=3.2, P<0.001), but no differences in BW were found between breed and treatment. Energy balance was improved for cows in the 4W group (P<0.001), while feed efficiency, expressed as RFI, was reduced for 4W cows than for 8W cows (5.91 compared with −5.39, P<0.01). Shortening the DP resulted in improved EB postpartum with no difference between the breeds and no milk losses when including the milk produced prepartum.     

An investigation of serum lipoproteins and of their contribution to milk fat in the dairy cow

1. Tritium-labelled olive-oil triglycerides were introduced into the rumens of lactating cows and the specific activities of the lipids of milk and plasma and of serum lipoproteins were measured. 2. On treatment of serum with dextran sulphate it was found that the lipid of the precipitated beta-lipoproteins consistently had a specific activity-time curve with a maximum comparable in value with, and occurring earlier than, that of the milk fat. 3. On fractionation of the lipids of these lipoproteins it was found that only the triglycerides and diglycerides had specific activity-time curves with maxima greater than that of milk fat, and on radioactivity data alone they are the only blood constituents studied that meet the requirements for being the precursor of milk fat. 4. From a consideration of abundances and the mean specific activities over the period of the experiment it is shown that the contribution of the diglycerides to the radioactivity in the milk fat must have been negligible and that only the triglycerides could have been responsible for all the radioactivity found in it. 5. Although no other fraction could alone have been responsible for all the radioactivity in the milk fat, at least one, the phospholipids, could have made some contribution. 6. It is calculated that 35-48% by weight of milk fat was derived from the beta-lipoprotein triglycerides, according to whether the phospholipids made an improbably large contribution or none at all.     

Stakeholder involvement in establishing a milk quality sub-index in dairy cow breeding goals: a Delphi approach

The relative weighting on traits within breeding goals are generally determined by bio-economic models or profit functions. While such methods have generally delivered profitability gains to producers, and are being expanded to consider non-market values, current approaches generally do not consider the numerous and diverse stakeholders that affect, or are affected, by such tools. Based on principles of respondent anonymity, iteration, controlled feedback and statistical aggregation of feedback, a Delphi study was undertaken to gauge stakeholder opinion of the importance of detailed milk quality traits within an overall dairy breeding goal for profit, with the aim of assessing its suitability as a complementary, participatory approach to defining breeding goals. The questionnaires used over two survey rounds asked stakeholders: (a) their opinion on incorporating an explicit sub-index for milk quality into a national breeding goal; (b) the importance they would assign to a pre-determined list of milk quality traits and (c) the (relative) weighting they would give such a milk quality sub-index. Results from the survey highlighted a good degree of consensus among stakeholders on the issues raised. Similarly, revelation of the underlying assumptions and knowledge used by stakeholders to make their judgements illustrated their ability to consider a range of perspectives when evaluating traits, and to reconsider their answers based on the responses and rationales given by others, which demonstrated social learning. Finally, while the relative importance assigned by stakeholders in the Delphi survey (4% to 10%) and the results of calculations based on selection index theory of the relative emphasis that should be placed on milk quality to halt any deterioration (16%) are broadly in line, the difference indicates the benefit of considering more than one approach to determining breeding goals. This study thus illustrates the role of the Delphi technique, as a complementary approach to traditional approaches, to defining breeding goals. This has implications for how breeding goals will be defined and in determining who should be involved in the decision-making process.     

Predicting grass dry matter intake,milk yield and milk fat and protein yield of spring calving grazing dairy cows during the grazing season

Predicting the grass dry matter intake (GDMI), milk yield (MY) or milk fat and protein yield (milk solids yield (MSY)) of the grazing dairy herd is difficult. Decisions with regard to grazing management are based on guesstimates of the GDMI of the herd, yet GDMI is a critical factor influencing MY and MSY. A data set containing animal, sward, grazing management and concentrate supplementation variables recorded during weeks of GDMI measurement was used to develop multiple regression equations to predict GDMI, MY and MSY. The data set contained data from 245 grazing herds from 10 published studies conducted at Teagasc, Moorepark. A forward stepwise multiple regression technique was used to develop the multiple regression equations for each of the dependent variables (GDMI, MY, MSY) for three periods during the grazing season: spring (SP; 5 March to 30 April), summer (SU; 1 May to 31 July) and autumn (AU; 1 August to 31 October). The equations generated highlighted the importance of different variables associated with GDMI, MY and MSY during the grazing season. Peak MY was associated with an increase in GDMI, MY and MSY during the grazing season with the exception of GDMI in SU when BW accounted for more of the variation. A higher body condition score (BCS) at calving was associated with a lower GDMI in SP and SU and a lower MY and MSY in all periods. A higher BCS was associated with a higher GDMI in SP and SU, a higher MY in SU and AU and a higher MSY in all periods. The pre-grazing herbage mass of the sward (PGHM) above 4 cm was associated with a quadratic effect on GDMI in SP, on MY in SP and SU and on MSY in SU. An increase in daily herbage allowance (DHA) above 4 cm was associated with an increase in GDMI in AU, an increase in MY in SU and AU and MSY in AU. Supplementing grazing dairy cows with concentrate reduced GDMI and increased MY and MSY in all periods. The equations generated can be used by the Irish dairy industry during the grazing season to predict the GDMI, MY and MSY of grazing dairy herds.     

Adaptation and evaluation of the GrazeIn model of grass dry matter intake and milk yield prediction for grazing dairy cows

The prediction of grass dry matter intake (GDMI) and milk yield (MY) are important to aid sward and grazing management decision making. Previous evaluations of the GrazeIn model identified weaknesses in the prediction of GDMI and MY for grazing dairy cows. To increase the accuracy of GDMI and MY prediction, GrazeIn was adapted, and then re-evaluated, using a data set of 3960 individual cow measurements. The adaptation process was completed in four additive steps with different components of the model reparameterised or altered. These components were: (1) intake capacity (IC) that was increased by 5% to reduce a general GDMI underprediction. This resulted in a correction of the GDMI mean and a lower relative prediction error (RPE) for the total data set, and at all stages of lactation, compared with the original model; (2) body fat reserve (BFR) deposition from 84 days in milk to next calving that was included in the model. This partitioned some energy to BFR deposition after body condition score nadir had been reached. This reduced total energy available for milk production, reducing the overprediction of MY and reducing RPE for MY in mid and late lactation, compared with the previous step. There was no effect on predicted GDMI; (3) The potential milk curve was reparameterised by optimising the rate of decrease in the theoretical hormone related to secretory cell differentiation and the basal rate of secretory cell death to achieve the lowest possible mean prediction error (MPE) for MY. This resulted in a reduction in the RPE for MY and an increase in the RPE for GDMI in all stages of lactation compared with the previous step; and (4) finally, IC was optimised, for GDMI, to achieve the lowest possible MPE. This resulted in an IC correction coefficient of 1.11. This increased the RPE for MY but decreased the RPE for GDMI compared with the previous step. Compared with the original model, modifying this combination of four model components improved the prediction accuracy of MY, particularly in late lactation with a decrease in RPE from 27.8% in the original model to 22.1% in the adapted model. However, testing of the adapted model using an independent data set would be beneficial and necessary to make definitive conclusions on improved predictions.     

Variation in blood serum proteins and association with somatic cell count in dairy cattle from multi-breed herds

Blood serum proteins are significant indicators of animal health. Nevertheless, several factors should be considered to appropriately interpret their concentrations in blood. Therefore, the objectives of this study were (1) to assess the effect of herd productivity, breed, age and stage of lactation on serum proteins and (2) to investigate association between serum proteins and somatic cell count (SCC) in dairy cattle. Milk and blood samples were collected from 1508 cows of six different breeds (Holstein Friesian, Brown Swiss, Jersey, Simmental, Rendena and Alpine Grey) that were housed in 41 multi-breed herds. Milk samples were analyzed for composition and SCC, while blood samples were analyzed for serum proteins (i.e. total protein, albumin, globulin and albumin-to-globulin ratio (A : G)). Herds were classified as low or high production, according to the cow’s average daily milk energy yield adjusted for breed, days in milk (DIM) and parity. Data were analyzed using a linear mixed model that included the fixed effects of DIM, parity, SCS, breed, herd productivity and the random effect of the Herd-test date within productivity level. Cows in high producing herds (characterized also by greater use of concentrates in the diet) had greater serum albumin concentrations. Breed differences were reported for all traits, highlighting a possible genetic mechanism. The specialized breed Jersey and the two dual-purpose local breeds (Alpine Grey and Rendena) had the lowest globulin concentration and greatest A : G. Changes in serum proteins were observed through lactation. Total protein reached the highest concentration during the 4th month of lactation. Blood albumin increased with DIM following a quadratic pattern, while globulin decreased linearly. As a consequence, A : G increased linearly during lactation. Older cows had greater total protein and globulin concentrations, while albumin concentration seemed to be not particularly affected by age. A linear relationship between serum proteins and SCS was observed. High milk SCS was associated with greater total protein and globulin concentrations in blood. The rise in globulin concentration, together with a decrease in albumin concentrations, resulted in a decline in A : G as SCS of milk increased. In conclusion, such non-genetic factors must be considered to appropriately interpret serum proteins as potential animal welfare indicator and their evaluation represents an important first-step for future analysis based on the integration of metabolomics, genetic and genomic information for improving the robustness of dairy cows.     

Bacterial spore structures and their protective role in biocide resistance

The structure and chemical composition of bacterial spores differ considerably from those of vegetative cells. These differences largely account for the unique resistance properties of the spore to environmental stresses, including disinfectants and sterilants, resulting in the emergence of spore-forming bacteria such as Clostridium difficile as major hospital pathogens. Although there has been considerable work investigating the mechanisms of action of many sporicidal biocides against Bacillus subtilis spores, there is far less information available for other species and particularly for various Clostridia. This paucity of information represents a major gap in our knowledge given the importance of Clostridia as human pathogens. This review considers the main spore structures, highlighting their relevance to spore resistance properties and detailing their chemical composition, with a particular emphasis on the differences between various spore formers. Such information will be vital for the rational design and development of novel sporicidal chemistries with enhanced activity in the future.     

Transient reductions in milk fat synthesis and their association with the ruminal and metabolic profile in dairy cows fed high-starch,low-fat diets

Sub-acute ruminal acidosis (SARA) is sometimes observed along with reduced milk fat synthesis. Inconsistent responses may be explained by dietary fat levels. Twelve ruminally cannulated cows were used in a Latin square design investigating the timing of metabolic and milk fat changes during Induction and Recovery from SARA by altering starch levels in low-fat diets. Treatments were (1) SARA Induction, (2) Recovery and (3) Control. Sub-acute ruminal acidosis was induced by feeding a diet containing 29.4% starch, 24.0% NDF and 2.8% fatty acids (FAs), whereas the Recovery and Control diets contained 19.9% starch, 31.0% NDF and 2.6% FA. Relative to Control, DM intake (DMI) and milk yield were higher in SARA from days 14 to 21 and from days 10 to 21, respectively (P < 0.05). Milk fat content was reduced from days 3 to 14 in SARA (P < 0.05) compared with Control, while greater protein and lactose contents were observed from days 14 to 21 and 3 to 21, respectively (P < 0.05). Milk fat yield was reduced by SARA on day 3 (P < 0.05), whereas both protein and lactose yields were higher on days 14 and 21 (P < 0.05). The ruminal acetate-to-propionate ratio was lower, and the concentrations of propionate and lactate were higher in the SARA treatment compared with Control on day 21 (P < 0.05). Plasma insulin increased during SARA, whereas plasma non-esterified fatty acids and milk β-hydroxybutyrate decreased (P < 0.05). Similarly to fat yield, the yield of milk preformed FA (>16C) was lower on day 3 (P < 0.05) and tended to be lower on day 7 in SARA cows (P < 0.10), whereas yield of de novo FA (<16C) was higher on day 21 (P < 0.01) in the SARA group relative to Control. The t10- to t11-18:1 ratio increased during the SARA Induction period (P < 0.05), but the concentration of t10-18:1 remained below 0.5% of milk fat, and t10,c12 conjugated linoleic acid remained below detection levels. Odd-chain FA increased, whereas branched-chain FA was reduced during SARA Induction from days 3 to 21 (P < 0.05). Sub-acute ruminal acidosis reduced milk fat synthesis transiently. Such reduction was not associated with ruminal biohydrogenation intermediates but rather with a transient reduction in supply of preformed FA. Subsequent rescue of milk fat synthesis may be associated with higher availability of substrates due to increased DMI during SARA.     

Carryover of aflatoxin from feed to milk in dairy cows with low or high somatic cell counts

Aflatoxin M1 (AFM1) residues in milk are regulated in many parts of the world and can cost dairy farmers significantly due to lost milk sales. Additionally, due to the carcinogenicity of this compound contaminated milk can be a major public health concern. Thirty-four lactating dairy cows were utilised to investigate the relationship between somatic cell counts (SCC), milk yield and conversion of dietary aflatoxin B1 (AFB1) into milk AFM1 (carryover (CO)). The AFM1 in milk increased as soon as the first milking after animal ingestion with a pattern of increment up to the observed plateau (between 7th and 12th days of AFB1 ingestion). There was a significant (P < 0.01) effect of the milk yield whereas no effect could be attributed to the SCC levels or to the milk yield × SCC interaction. Similarly, the main effect of milk yield was also observed (P < 0.01) on the total amount of AFM1 excreted during the ingestion period. Although the plasma concentration of gamma-glutamyl transferase was significantly affected by aflatoxin administration, levels of this liver enzyme were within the normal range for lactating dairy cows. The current data suggest that milk yield is the major factor affecting the total excretion of AFM1 and that SCC as an indicator of mammary gland permeability was not related to an increase in AFM1 CO.     

Genetic analysis for mastitis resistance and milk somatic cell score in French Lacaune dairy sheep

Genetic analysis for mastitis resistance was studied from two data sets. Firstly, risk factors for different mastitis traits, i.e. culling due to clinical or chronic mastitis and subclinical mastitis predicted from somatic cell count (SCC), were explored using data from 957 first lactation Lacaune ewes of an experimental INRA flock composed of two divergent lines for milk yield. Secondly, genetic parameters for SCC were estimated from 5 272 first lactation Lacaune ewes recorded among 38 flocks, using an animal model. In the experimental flock, the frequency of culling due to clinical mastitis (5%) was lower than that of subclinical mastitis (10%) predicted from SCC. Predicted subclinical mastitis was unfavourably associated with the milk yield level. Such an antagonism was not detected for clinical mastitis, which could result, to some extent, from its low frequency or from the limited amount of data. In practice, however, selection for mastitis resistance could be limited in a first approach to selection against subclinical mastitis using SCC. The heritability estimate of SCC was 0.15 for the lactation mean trait and varied from 0.04 to 0.12 from the first to the fifth test-day. The genetic correlation between lactation SCC and milk yield was slightly positive (0.15) but showed a strong evolution during lactation, i.e. from favourable (-0.48) to antagonistic (0.27). On a lactation basis, our results suggest that selection for mastitis resistance based on SCC is feasible. Patterns for genetic parameters within first lactation, however, require further confirmation and investigation.     

Dust and ammonia in horse stalls with different ventilation rates and bedding

Airborne particles and ammonia were monitored in horse stalls managed under four conditions. Two ventilation rates, high (27 air changes per h) and low (5 air changes per h) and two bedding types, paper and straw, were employed. At both ventilation rates, the number of airborne particles generated while the stalls were mucked out was higher with straw than with paper. Particles were more efficiently cleared at the higher ventilation rate in both the straw and paper stalls. Ammonia measurements reflected an accumulation over time. In the stalls with low ventilation, ammonia levels were significantly higher than in those stalls with high ventilation regardless of bedding type. Management decisions and their relationships to respiratory disorders are discussed.     

水稻种子的细菌含量和群落结构及其影响因素分析

【目的】种子是植物微生物群代际传递的重要途径,但种子携带的微生物群落尚缺乏系统的研究。本研究以水稻种子为模型,定量分析种子的细菌含量、测定种子的细菌群落结构、探究地域与品种对细菌含量及群落结构的影响和鉴定水稻种子的核心菌群。【方法】选取18个水稻品种,每个品种分别来自中国海南和天津2个地域,共36组样本。每组样本包含5或10个DNA样本,每个DNA样本由3粒种子提取的总DNA构成。使用细菌特异性16S rDNA介导的荧光定量PCR技术测定种子的细菌含量,并分析影响因素;使用16S rDNA扩增子测序技术测定种子的细菌群落结构,并用生物信息学方法分析了影响因素和核心菌群。【结果】本研究测定了1 080粒水稻种子的细菌含量,发现经过表面除菌的水稻种子内部存在共栖细菌,平均每克种子的细菌含量为1.53×10⁶。水稻品种对种子的细菌含量有显著影响,而地域无影响。测定180个扩增子文库的细菌群落结构,发现水稻种子的菌群与水稻植株有相似之处,均以变形菌门为主要的细菌门类;地域对水稻种子的细菌群落结构有重要影响,不同地域的水稻种子在主坐标分析(principal co-ordinate analysis, PCoA)中有明显分离;而粳稻和籼稻之间无显著差异。还发现水稻种子存在核心菌群,且相对丰度高达总菌群的85.56%。【结论】本研究系统地揭示了水稻种子的细菌含量、群落结构及其影响因素,为利用种传微生物促进水稻健康提供了数据和方法支持。     

Dust and ammonia in horse stalls with different ventilation rates and bedding

Airborne particles and ammonia were monitored in horse stalls managed under four conditions. Two ventilation rates, high (27 air changes per h) and low (5 air changes per h) and two bedding types, paper and straw, were employed. At both ventilation rates, the number of airborne particles generated while the stalls were mucked out was higher with straw than with paper. Particles were more efficiently cleared at the higher ventilation rate in both the straw and paper stalls. Ammonia measurements reflected an accumulation over time. In the stalls with low ventilation, ammonia levels were significantly higher than in those stalls with high ventilation regardless of bedding type. Management decisions and their relationships to respiratory disorders are discussed.     

Merging and characterising phenotypic data on conventional and rare traits from dairy cattle experimental resources in three countries

This study set out to demonstrate the feasibility of merging data from different experimental resource dairy populations for joint genetic analyses. Data from four experimental herds located in three different countries (Scotland, Ireland and the Netherlands) were used for this purpose. Animals were first lactation Holstein cows that participated in ongoing or previously completed selection and feeding experiments. Data included a total of 60 058 weekly records from 1630 cows across the four herds; number of cows per herd ranged from 90 to 563. Weekly records were extracted from the individual herd databases and included seven traits: milk, fat and protein yield, milk somatic cell count, liveweight, dry matter intake and energy intake. Missing records were predicted with the use of random regression models, so that at the end there were 44 weekly records, corresponding to the typical 305-day lactation, for each cow. A total of 23 different lactation traits were derived from these records: total milk, fat and protein yield, average fat and protein percentage, average fat-to-protein ratio, total dry matter and energy intake and average dry matter intake-to-milk yield ratio in lactation weeks 1 to 44 and 1 to 15; average milk somatic cell count in lactation weeks 1 to 15 and 16 to 44; average liveweight in lactation weeks 1 to 44; and average energy balance in lactation weeks 1 to 44 and 1 to 15. Data were subsequently merged across the four herds into a single dataset, which was analysed with mixed linear models. Genetic variance and heritability estimates were greater (P < 0.05) than zero for all traits except for average milk somatic cell count in weeks 16 to 44. Proportion of total phenotypic variance due to genotype-by-environment (sire-by-herd) interaction was not different (P > 0.05) from zero. When estimable, the genetic correlation between herds ranged from 0.85 to 0.99. Results suggested that merging experimental herd data into a single dataset is both feasible and sensible, despite potential differences in management and recording of the animals in the four herds. Merging experimental data will increase power of detection in a genetic analysis and augment the potential reference population in genome-wide association studies, especially of difficult-to-record traits.     

Casein haplotypes and their association with milk production traits in the Finnish Ayrshire cattle

Polymorphism of casein genes was studied in half-sib families of artificial insemination bulls of the Finnish Ayrshire dairy breed. Ten grandsires and 300 of their sons were genotyped for the following polymorphisms: α_S1-casein (B, C), β-casein (A¹, A²), the microsatellite within the K-casein gene (ms⁵, ms⁴) and K-casein (A, B, E). Nine different combinations of these alleles, casein haplotypes, were found. Associations between casein haplotypes and milk production traits (milk and protein yield, fat and protein percentage and milking speed) were studied with ordinary least-squares analysis to find a direct effect of the haplotypes or an association within individual grandsire families using the granddaughter design. Estimated breeding values of sons were obtained from cow evaluation by animal model. No direct effect of the casein haplotypes on the traits was found. Within grandsire families, in one out of four families the chromosomal segment characterized by haplotype 3 (B-A²-ms⁴-A) was associated with an increase in milk yield ( P <0.01) and a decrease in fat percentage ( P < 0.01) when contrasted with haplotype 8 (B-A¹-ms⁴-E). The results provide evidence that in the Finnish Ayrshire breed at least one quantitative trait locus affecting the genetic variation in yields traits is segregating linked to either haplotype 3 (B-A²-ms⁴-A) or 8 (B-A¹-ms⁴-E).     

Isolation of microbial pathogens of subclinical mastitis from raw sheep's milk of Epirus (Greece) and their role in its hygiene

The natural raw milk microflora is a factor that expresses its sensorial characteristics. The microbial charge into the mammary gland of healthy animal is low and the application of right and healthy conditions during milking and cheese making procedure, prevents from contaminating as well as maintains the natural microflora in order to lend the particular characteristics of milk.The purpose of the present project was the study of the Total Viable Count (T.V.C.) and the count of total psychrotropic bacteria of raw sheep milk from Boutsiko and Karamaniko breeds, collected from healthy animals, as well as the isolation, identification and enumeration of pathogenic bacteria related with the hygiene and the quality of raw sheep milk (with a particular interest in bacteria that may cause human infection).During the experiment we examined two hundred forty (240) samples of raw sheep milk. In these samples a) Staphylococcus aureus, Salmonella sp., Escherichia coli, Clostridium perfringens (vegetative cells and spores) and Bacillus sp. were isolated and identified b) the Total Viable Count and the total number of psychrotropic bacteria were also specified. The sampling, the preparation of samples and decimal dilutions were based on international methods. The Total viable count was determined using the standard methods of the American Public Health Association, 2002. The total number of psychrotropic bacteria was determined using APHA 1976, 1978 rules. The identification of the bacteria was carried out according to the Bergey’s manual. Microscopic examination of Gram stained cells, catalase, oxidase and biochemical tests were performed when necessary to further identify.From the 240 milk samples tested, only 5% were E. coli positive, with mean counts ranged from 2 × 10³ to 2.4 × 10⁴ cfu/ml. S. aureus was isolated from 24% of the samples and the mean count per ml was ranged from <10 to 3.4 × 10². Meanwhile, Bacillus spp. was also detected in 29% samples. Vegetative forms and spores of C. perfringens were detected in 13% and 63% of the samples respectively. However, microbiological analyses revealed the presence of a small number of selected pathogens in milk samples such as Salmonella, which was only detected in 5% of the samples. Listeria sp., Pseudomonas sp. and Vibrio cholerae were never found.From the experimental results, the Total Viable Count from raw sheep milk samples, fulfils the microbiological criteria of EU Legislation in a percentage of approximately 97%.     

Modelling mammary metabolism in the dairy cow to predict milk constituent yield, with emphasis on amino acid metabolism and milk protein production: model construction

Previous efforts to simulate mammary metabolism have focused on energy, mostly considering amino acids (AA) in aggregate. The main objective of this work was to build a model of mammary metabolism, based on data from arterio-venous difference studies, which considered AA in sufficient detail to predict yields of milk solids. The model contains 19 state variables and considers the removal of 37 metabolites from blood, including 22 AA. It is driven by blood flow and arterial concentrations, and outputs include milk protein, milk lactose, and three classes of milk fat (by chain length). The model was parameterized using a balance version of it and the mean observations from four arterio-venous difference experiments, with a limited number of assumptions, and evaluated against these experiments. In assembling the balance model, milk protein output was not predicted satisfactorily, as some essential AA were not present in quantities great enough to support the rates of milk protein synthesis observed experimentally. Tryptophan showed the greatest deficit, followed by tyrosine plus phenylalanine, methionine, and histidine. In addition, significant quantities of pyruvate were needed to synthesize serine, glycine, and alanine. The supply of alpha-ketoglutarate plus glutamate to synthesize proline and glutamine was provided in part by catabolism of arginine; the remainder was derived from catabolism of other AA and energetic substrates.