Predicting CO2 production of lactating dairy cows from animal, dietary, and production traits using an international dataset.

Automated measurements of the ratio of concentrations of methane and carbon dioxide, [CH4]:[CO2], in breath from individual animals (the so-called "Sniffer-technique") and estimated CO2 production can be used to estimate CH4 production, provided that CO2 production can be reliably calculated. This would allow CH4 production from individual cows to be estimated in large cohorts of cows, whereby ranking of cows according to their CH4 production might become possible and their values could be used for breeding of low CH4 emitting animals. Estimates of CO2 production are typically based on predictions of heat production, which can be calculated from body weight (BW), energy-corrected milk yield, and days of pregnancy. The objectives of the present study were to develop predictions of CO2 production directly from milk production, dietary, and animal variables, and furthermore develop different models to be used for different scenarios, depending on available data. An international data set with 2,244 records from individual lactating cows including CO2 production and associated traits, as dry matter intake (DMI), diet composition, BW, milk production and composition, days in milk and days pregnant, was compiled to constitute the training data set. Research location and experiment nested within research location were included as random intercepts. The method of CO2 production measurement (respiration chamber (RC) or GreenFeed (GF)) was confounded with research location, and therefore excluded from the model. In total, 3 models were developed based on the current training data set: Model 1 ("Best Model"), where all significant traits were included, Model 2 ("On-Farm Model"), where DMI was excluded, and Model 3 ("Reduced On-Farm Model"), where both DMI and BW were excluded. Evaluation on test data sets either with RC data (n = 103), GF data without additives (n = 478) or GF data only including observations where nitrate, 3-nitrooxypropanol (3-NOP), or a combination of nitrate and 3-NOP were fed to the cows (GF+: n = 295), showed good precision of the 3 models, illustrated by low slope bias both in absolute values (-0.22 to 0.097) and in percentage (0.049 to 4.89) of mean square error (MSE). However, the mean bias (MB) indicated systematic over-prediction and under-prediction of CO2 production when the models were evaluated on the GF and the RC test data set, respectively. To address this bias, the 3 models were evaluated on a modified test data set, where the CO2 production (g/d) was adjusted by subtracting (where measurements were obtained by RC) or adding absolute MB (where measurements were obtained by GF) from evaluation of the specific model on RC, GF, and GF+ test data sets. By this modification, the absolute values of MB and MB as percentage of MSE became negligible. In conclusion, the 3 models were precise in predicting CO2 production from lactating dairy cows.

Dry period length affects rumen adaptation in dairy cattle precalving and during the first weeks after calving.

Omitting or shortening the dry period may result in a fairly constant ration throughout the transition period of dairy cows, reducing the need for adaptation of cow metabolism and rumen function to a new lactation. The objective of this study was to determine the effect of dry period length on rumen adaptation and cow metabolic state during the transition period. Twelve pregnant, rumen-cannulated Holstein Friesian dairy cows at the end of their first lactation were assigned to one of 3 treatments: a conventional (60 d), short (30 d) or no dry period (0 d). At dry-off, cows received a dry cow ration until calving. Lactating cows received a lactation ration. Cows were monitored from 8 wk before calving until 8 wk after calving for milk yield and dry matter intake (DMI). Rumen biopsies were taken from 3 locations in the rumen at 60, 40 and 10 d before calving and 3, 7, 14, 28 and 56 d after calving to assess papillae dimensions. Blood was sampled weekly from 3 wk before until 8 wk after calving, and liver biopsies were taken at wk -2, wk 2 and wk 4 relative to calving. Prepartum, DMI and milk yield were greater for cows with a short or no dry period, compared with cows with a conventional dry period. Postpartum, DMI was greater for cows with a short dry period compared with cows with a conventional dry period. Plasma glucose concentration was greater for cows without a dry period, compared with the other dry period lengths postpartum. Plasma concentrations of nonesterified fatty acids and ß-hydroxybutyrate, and liver triglyceride content, did not differ among dry period. Rumen papillae differed in size based on biopsy location, but there was no interaction between biopsy location and the effect of dry period length. Rumen papillae surface area for cows managed for a 30 d or 60 d dry period decreased toward calving. At 40 d prepartum, papillae surface area was greater for short and no dry period treatment compared with a conventional dry period. At 10 d prepartum, papillae surface area was greater for the no dry period treatment compared with both other treatments, and this difference was still present 3 d postpartum. Cows managed for a short dry period showed faster increase in papillae dimensions after calving compared with cows managed for a conventional dry period. From d 28 onwards, no differences in papillae surface area were observed. The faster rumen adaptation postpartum may be related to the increased DMI during the first weeks postpartum for cows managed for a short dry period. However, this did not result in improved metabolic status or milk yield. The results from the present study demonstrate that the dietary changes related to a conventional dry period length affected rumen papillae development, not only prepartum but also early postpartum. Further optimization of dry period length as well as dietary composition throughout the transition period may support cows in their adaptation to a new lactation.

SNAPIG: a model to study nutrient digestion and absorption kinetics in growing pigs based on diet and ingredient properties.

Current feed formulation and evaluation practices rely on static values for the nutritional value of feed ingredients and assume additivity. Hereby, the complex interplay among nutrients in the diet and the highly dynamic digestive processes are ignored. Nutrient digestion kinetics and diet × animal interactions should be acknowledged to improve future predictions of the nutritional value of complex diets. Therefore, an in silico nutrient-based mechanistic digestion model for growing pigs was developed: "SNAPIG" (Simulating Nutrient digestion and Absorption kinetics in PIGs). Aiming to predict the rate and extent of nutrient absorption from diets varying in ingredient composition and physicochemical properties, the model represents digestion kinetics of ingested protein, starch, fat, and non-starch polysaccharides, through passage, hydrolysis, absorption, and endogenous secretions of nutrients along the stomach, proximal small intestine, distal small intestine, and caecum + colon. Input variables are nutrient intake and the physicochemical properties (i.e. solubility, and rate and extent of degradability). Data on the rate and extent of starch and protein hydrolysis of different ingredients per digestive segment were derived from in vitro assays. Passage of digesta from the stomach was modelled as a function of feed intake level, dietary nutrient solubility and diet viscosity. Model evaluation included testing against independent data from in vivo studies on nutrient appearance in (portal) blood of growing pigs. When simulating diets varying in physicochemical properties and nutrient source, SNAPIG can explain variation in glucose absorption kinetics (postprandial time of peak, TOP: 20-100 min observed vs 25-98 min predicted), and predict variation in the extent of ileal protein and fat digestion (root mean square prediction errors (RMSPE) = 12 and 16%, disturbance error = 12 and 86%, and concordance correlation coefficient = 0.34 and 0.27). For amino acid absorption, the observed variation in postprandial TOP (61 ± 11 min) was poorly predicted despite accurate mean predictions (58 ± 34 min). Recalibrating protein digestion and amino acid absorption kinetics require data on net-portal nutrient appearance, combined with observations on digestion kinetics, in pigs fed diets varying in ingredient composition. Currently, SNAPIG can be used to forecast the time and extent of nutrient digestion and absorption when simulating diets varying in ingredient and nutrient composition. It enhances our quantitative understanding of nutrient digestion kinetics and identifies knowledge gaps in this field of research. Already useful as research tool, SNAPIG can be coupled with a postabsorptive metabolism model to predict the effects of dietary and feeding-strategies on the pig's growth response.

Short communication: Quantifying postruminal starch fermentation in early-lactation Holstein-Friesian cows.

It has previously been shown that fermentation may contribute substantially to small intestinal carbohydrate disappearance. The fact that the energetic efficiency of starch fermentation is considerably less than that of enzymatic digestion of starch, makes it of nutritional importance to quantify the level of postruminal starch fermentation for dairy cows. Hence, we subjected six rumen-fistulated Holstein-Friesian dairy cows (48 ± 17 days in milk) to 5 d of continuous abomasal infusions of 0.0, 2.5, and 5.0 mol NH4Cl/d, with and without 3 kg ground maize/d, followed by 2 d of rest in a 6 × 6 Latin square design. A total mixed ration (TMR) consisting of (DM basis) 70% grass silage and 30% concentrate was fed at 95% of ad libitum intake. Separation of postruminal starch disappearance into enzymatically digested starch and fermented starch was based on the measurement of natural 13C enrichment of the TMR, abomasally infused ground maize, and resulting 13C enrichment of faeces. Within each cow, 0.0, 2.5, and 5.0 mol NH4Cl/d without ground maize served as control for the same levels of NH4Cl with 3 kg ground maize/d. Abomasal infusion of ground maize was associated with increased total DM and starch intake, faecal starch excretion, and digestibility of starch, and with decreased digestibility of DM and N. The increased faecal volatile fatty acid (VFA) output and 13C enrichment of the individual VFA indicate increased starch fermentation with abomasally infused ground maize. On average, 1 311 g starch/d was postruminally fermented, representing 60.8% of total starch intake. Overall, postruminal starch fermentation of early-lactation dairy cows abomasally infused with 3 kg ground maize/d is considerable and may result in substantial amounts of VFA rather than glucose production.

Prediction of nitrogen excretion from data on dairy cows fed a wide range of diets compiled in an intercontinental database: A meta-analysis.

Manure nitrogen (N) from cattle contributes to nitrous oxide and ammonia emissions and nitrate leaching. Measurement of manure N outputs on dairy farms is laborious, expensive, and impractical at large scales; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were (1) to collate an international database of N excretion in feces and urine based on individual lactating dairy cow data from different continents; (2) to determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and (3) to develop robust and reliable N excretion prediction models based on individual data from lactating dairy cows consuming various diets. A raw data set was created based on 5,483 individual cow observations, with 5,420 fecal N excretion and 3,621 urine N excretion measurements collected from 162 in vivo experiments conducted by 22 research institutes mostly located in Europe (n = 14) and North America (n = 5). A sequential approach was taken in developing models with increasing complexity by incrementally adding variables that had a significant individual effect on fecal, urinary, or total manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models including experiment as a random effect. Simple models requiring dry matter intake (DMI) or N intake performed better for predicting fecal N excretion than simple models using diet nutrient composition or milk performance parameters. Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI, but simple models using milk urea N (MUN) and N intake performed even better for urinary N excretion. The full model predicting fecal N excretion had similar performance to simple models based on DMI but included several independent variables (DMI, diet crude protein content, diet neutral detergent fiber content, milk protein), depending on the location, and had root mean square prediction errors as a fraction of the observed mean values of 19.1% for intercontinental, 19.8% for European, and 17.7% for North American data sets. Complex total manure N excretion models based on N intake and MUN led to prediction errors of about 13.0% to 14.0%, which were comparable to models based on N intake alone. Intercepts and slopes of variables in optimal prediction equations developed on intercontinental, European, and North American bases differed from each other, and therefore region-specific models are preferred to predict N excretion. In conclusion, region-specific models that include information on DMI or N intake and MUN are required for good prediction of fecal, urinary, and total manure N excretion. In absence of intake data, region-specific complex equations using easily and routinely measured variables to predict fecal, urinary, or total manure N excretion may be used, but these equations have lower performance than equations based on intake.

Essential amino acid profile of supplemental metabolizable protein affects mammary gland metabolism and whole-body glucose kinetics in dairy cattle.

This study investigated mammary gland metabolism and whole-body (WB) rate of appearance (Ra) of glucose in dairy cattle in response to a constant supplemental level of metabolizable protein (MP) composed of different essential AA (EAA) profiles. Five multiparous rumen-fistulated Holstein-Friesian dairy cows (2.8 ± 0.4 lactations; 81 ± 11 d in milk; mean ± standard deviation) were abomasally infused according to a 5 × 5 Latin square design with saline (SAL) or 562 g/d of EAA delivered in different profiles where individual AA content corresponded to their relative content in casein. The profiles consisted of (1) a complete EAA mixture (EAAC), (2) Ile, Leu, and Val (ILV), (3) His, Ile, Leu, Met, Phe, Trp, Val (GR1+ILV), and (4) Arg, His, Lys, Met, Phe, Thr, Trp (GR1+ALT). A total mixed ration (58% corn silage, 16% alfalfa hay, and 26% concentrate on a dry matter basis) was formulated to meet 100 and 83% of net energy and MP requirements, respectively, and was fed at 90% of ad libitum intake on an individual cow basis. Each experimental period consisted of 5 d of continuous abomasal infusion followed by 2 d of no infusion. Arterial and venous blood samples were collected on d 4 of each period for determination of mammary gland AA and glucose metabolism. On d 5 of each period, D-[U-13C]glucose (13 mmol priming dose; continuous 3.5 mmol/h for 520 min) was infused into a jugular vein and arterial blood samples were collected before and during infusion to determine WB Ra of glucose. Milk protein yield did not differ between EAAC, GR1+ILV, and GR1+ALT, or between SAL and ILV, and increased over SAL and ILV with EAAC and GR1+ILV. Mammary plasma flow increased with ILV infusion compared with EAAC and GR1+ILV. Infusion of EAAC tended to increase mammary gland net uptake of total EAA and decreased the mammary uptake to milk protein output ratio (U:O) of non-EAA compared with SAL. Infusion of ILV increased mammary net uptake and U:O of Ile, Leu, and Val markedly over all treatments. The U:O of total Ile, Leu, and Val increased numerically (25%) with GR1+ILV infusion compared with EAAC, and the U:O of total Arg, Lys, and Thr tended to decrease, primarily from decreased U:O of Lys. During GR1+ALT infusion, U:O of total Arg, Lys, and Thr was greater than that during EAAC infusion, whereas U:O of Ile, Leu, and Val did not differ from EAAC. Glucose WB Ra increased 16% with GR1+ALT over SAL, and increased numerically 8 and 12% over SAL with EAAC and GR1+ILV, respectively. The average proportion of lactose yield relative to glucose WB Ra did not differ across treatments and averaged 0.53. On average, 28% of milk galactose arose from nonglucose precursors, regardless of treatment. In conclusion, intramammary catabolism of group 2 AA increased to support milk component synthesis when the EAA profile of MP was incomplete with respect to casein. Further, WB and mammary gland glucose metabolism was flexible in support of milk component synthesis, regardless of absorptive EAA profile.

Effects of dietary phosphorus concentration during the transition period on plasma calcium concentrations, feed intake, and milk production in dairy cows.

Our aim was to evaluate the effects of a low or high dietary phosphorus (P) concentration during the dry period, followed by either a high or low dietary P concentration during the first 8 wk of lactation, on plasma Ca concentrations, feed intake, and lactational performance of dairy cattle. Sixty pregnant multiparous Holstein Friesian dairy cows were assigned to a randomized block design with repeated measurements and dietary treatments arranged in a 2 × 2 factorial fashion. The experimental diets contained 3.6 (Dry-HP) or 2.2 (Dry-LP) g of P/kg of dry matter (DM) during the dry period, and 3.8 (Lac-HP) or 2.9 (Lac-LP) g of P/kg of DM during 56 d after calving period. In dry cows, plasma Ca concentrations were 3.3% greater when cows were fed 2.2 instead of 3.6 g of P/kg of DM. The proportion of cows being hypocalcemic (plasma Ca concentrations <2 mM) in the first week after calving was lowest with the low-P diets both during the dry period and lactation. Plasma Ca concentrations in wk 1 to 8 after calving were affected by dietary P level in the dry period and in the lactation period, but no interaction between both was present. Feeding Dry-LP instead of Dry-HP diets resulted in 4.1% greater plasma Ca values, and feeding Lac-LP instead of Lac-HP diets resulted in 4.0% greater plasma Ca values. After calving, plasma inorganic phosphate (Pi) concentrations were affected by a 3-way interaction between sampling day after calving, and dietary P levels during the dry period and lactation. From d 1 to d 7 postpartum, cows fed Lac-HP had increased plasma Pi concentrations, and the rate appeared to be greater in cows fed Dry-LP versus Dry-HP. In contrast, plasma Pi concentrations decreased from d 1 to d 7 postpartum in cows fed Lac-LP, and this decrease was at a higher rate for cows fed Dry-HP versus Dry-LP. After d 7, plasma Pi concentrations remained rather constant at 1.5 to 1.6 mM when cows received Lac-HP, whereas with Lac-LP plasma Pi concentrations reached stable levels (i.e., 1.3-1.4 mM) at d 28 after calving. Milk production, DM intake, and milk concentrations of P, Ca, fat, protein, and lactose were not affected by any interaction nor the levels of dietary P. It is concluded that the feeding of diets containing 2.2 g of P/kg of DM during the last 6 wk of the dry period and 2.9 g of P/kg of DM during early lactation increased plasma Ca levels when compared with greater dietary P levels. These low-P diets may be instrumental in preventing hypocalcemia in periparturient cows and do not compromise DM intake and milk production. Current results suggest that P requirements in dairy cows during dry period and early lactation can be fine-tuned toward lower values than recommended by both the National Research Council and the Dutch Central Bureau for Livestock Feeding. Caution however is warranted to extrapolate current findings to entire lactations because long-term effects of feeding low-P diets containing 2.9 of g/kg of DM on production and health needs further investigation.

Short communication: Identifying key parameters for modelling the impacts of livestock health conditions on greenhouse gas emissions.

Improved animal health can reduce greenhouse gas (GHG) emissions intensity in livestock systems while increasing productivity. Integrated modelling of disease impacts on farm-scale emissions is important in identifying effective health strategies to reduce emissions. However, it requires that modellers understand the pathways linking animal health to emissions and how these might be incorporated into models. A key barrier to meeting this need has been the lack of a framework to facilitate effective exchange of knowledge and data between animal health experts and emissions modellers. Here, these two communities engaged in workshops, online exchanges and a survey to i) identify a comprehensive list of disease-related model parameters and ii) test its application to evaluating models. Fifty-six parameters were identified and proved effective in assessing the potential of farm-scale models to characterise livestock disease impacts on GHG emissions. Easy wins for the emissions models surveyed include characterising disease impacts related to feeding.

Antimethanogenic effects of nitrate supplementation in cattle: A meta-analysis.

Supplementing a diet with nitrate is regarded as an effective and promising methane (CH4) mitigation strategy by competing with methanogens for available hydrogen through its reduction of ammonia in the rumen. Studies have shown major reductions in CH4 emissions with nitrate supplementation, but with large variation in response. The objective of this study was to quantitatively investigate the effect of dietary nitrate on enteric CH4 production and yield and evaluate the variables with high potential to explain the heterogeneity of between-study variability using meta-analytical models. A data set containing 56 treatments from 24 studies was developed to conduct a meta-analysis. Dry matter (DM) intake, nitrate dose (g/kg of DM), animal body weight, roughage proportion of diet, dietary crude protein and neutral detergent fiber content, CH4 measurement technique, and type of cattle (beef or dairy) were considered as explanatory variables. Average DM intake and CH4 production for dairy cows (16.2 ± 2.93 kg/d; 311 ± 58.8 g/d) were much higher than for beef cattle (8.1 ± 1.57 kg/d; 146 ± 50.9 g/d). Therefore, a relative mean difference was calculated and used to conduct random-effect and mixed-effect model analysis to eliminate the large variations between types of animal due to intake. The final mixed-effect model for CH4 production (g of CH4/d) had 3 explanatory variables and included nitrate dose, type of cattle, and DM intake. The final mixed-effect model for CH4 yield (g of CH4/kg of DM intake) had 2 explanatory variables and included nitrate dose and type of cattle. Nitrate effect sizes on CH4 production (dairy: -20.4 ± 1.89%; beef: -10.1 ± 1.52%) and yield (dairy: -15.5 ± 1.15%; beef: -8.95 ± 1.764%) were significantly different between the 2 types of cattle. When data from slow-release nitrate sources were removed from the analysis, there was no significant difference in type of cattle anymore for CH4 production and yield. Nitrate dose enhanced the mitigating effect of nitrate on CH4 production and yield by 0.911 ± 0.1407% and 0.728 ± 0.2034%, respectively, for every 1 g/kg of DM increase from its mean dietary inclusion (16.7 g/kg of DM). An increase of 1 kg of DM/d in DM intake from its mean dietary intake (11.1 kg of DM/d) decreased the effect of nitrate on CH4 production by 0.691 ± 0.2944%. Overall, this meta-analysis demonstrated that nitrate supplementation reduces CH4 production and yield in a dose-dependent manner, and that elevated DM intake decreases the effect of nitrate supplementation on CH4 production. Furthermore, the stronger antimethanogenic effect on CH4 production and yield in dairy cows than in beef steers could be related to use of slow-release nitrate in beef cattle.

Applying a mechanistic fermentation and digestion model for dairy cows with emission and nutrient cycling inventory and accounting methodology.

In mitigating greenhouse gas (GHG) emissions and reducing the carbon footprint of dairy milk, the use of generic estimates in inventory and accounting methodology at farm level largely ignores variation of on-farm GHG emissions. The present study aimed to implement results of an extant dynamic, mechanistic Tier 3 model for enteric methane (CH4) (applied in Dutch national GHG inventory) in order to capture variation in enteric CH4 emission, and in faecal N and organic matter (OM) digestibility, ultimately required to predict manure CH4 and ammonia emission. Tier 3 model predictions were translated into calculation rules that could easily be implemented in an annual nutrient cycling assessment tool including GHG emissions, which is currently used by Dutch dairy farmers. Calculations focussed on (1) enteric CH4 emission, (2) apparent faecal OM digestibility and (3) apparent faecal N digestibility. Enteric CH4 was expressed in CH4 yield indicated with the term emission factor (EF; g CH4/kg DM) for individual dietary components and feedstuffs. Factors investigated to cover predicted variation in EF value included the level of feed intake, the type of roughage fed (proportions of grass silage and maize silage) and the quality of roughage fed. A minimum number of three classes of roughage type (i.e. 0. 40% and 80% maize silage in roughage DM) appeared necessary to obtain correspondence between interpolated EF values from EF lists and Tier 3 model predictions. A linear decline in EF value with 1% per kg increase in DM intake is adopted based on model simulations. The quality of roughage was represented by the effect of maturity of harvested grass or of the whole plant maize at cutting, based on a survey of modelling as well as experimental work. Also, predictions were assembled for apparent faecal OM digestibility which could be used in national inventory and in farm accounting. Apparent faecal N digestibility (as a major determinant of predicted urinary N excretion) was predicted, to support current Dutch national ammonia emission inventory and to correct the level of N digestibility in farm accounting. Compared to generic values or values retrieved from the Dutch feeding tables, predicted OM and N digestibility and enteric CH4 are better rooted in physiological principles and better reflect observed variation under experimental conditions. The present results apply for conditions with fairly intensive grassland management in temperate regions.

Review: Rumen sensors: data and interpretation for key rumen metabolic processes.

Rumen sensors provide specific information to help understand rumen functioning in relation to health disorders and to assist in decision-making for farm management. This review focuses on the use of rumen sensors to measure ruminal pH and discusses variation in pH in both time and location, pH-associated disorders and data analysis methods to summarize and interpret rumen pH data. Discussion on the use of rumen sensors to measure redox potential as an indication of the fermentation processes is also included. Acids may accumulate and reduce ruminal pH if acid removal from the rumen and rumen buffering cannot keep pace with their production. The complexity of the factors involved, combined with the interactions between the rumen and the host that ultimately determine ruminal pH, results in large variation among animals in their pH response to dietary or other changes. Although ruminal pH and pH dynamics only partially explain the typical symptoms of acidosis, it remains a main indicator and may assist to optimize rumen function. Rumen pH sensors allow continuous monitoring of pH and of diurnal variation in pH in individual animals. Substantial drift of non-retrievable rumen pH sensors, and the difficulty to calibrate these sensors, limits their application. Significant within-day variation in ruminal pH is frequently observed, and large distinct differences in pH between locations in the rumen occur. The magnitude of pH differences between locations appears to be diet dependent. Universal application of fixed conversion factors to correct for absolute pH differences between locations should be avoided. Rumen sensors provide high-resolution kinetics of pH and a vast amount of data. Commonly reported pH characteristics include mean and minimum pH, but these do not properly reflect severity of pH depression. The area under the pH × time curve integrates both duration and extent of pH depression. The use of this characteristic, as well as summarizing parameters obtained from fitting equations to cumulative pH data, is recommended to identify pH variation in relation to acidosis. Some rumen sensors can also measure the redox potential. This measurement helps to understand rumen functioning, as the redox potential of rumen fluid directly reflects the microbial intracellular redox balance status and impacts fermentative activity of rumen microorganisms. Taken together, proper assessment and interpretation of data generated by rumen sensors requires consideration of their limitations under various conditions.

To what extent is climate change adaptation a novel challenge for agricultural modellers?

Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers' views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change.

Energy and nitrogen balance of dairy cattle as affected by provision of different essential amino acid profiles at the same metabolizable protein supply.

Amino acid composition of metabolizable protein (MP) is important in dairy cattle diets, but effects of AA imbalances on energy and N utilization are unclear. This study determined the effect of different AA profiles within a constant supplemental MP level on whole-body energy and N partitioning in dairy cattle. Five rumen-fistulated Holstein-Friesian dairy cows (2.8 ± 0.4 lactations; 81 ± 11 d in milk; mean ± standard deviation) were randomly assigned to a 5 × 5 Latin square design in which each experimental period consisted of 5 d of continuous abomasal infusion followed by 2 d of rest. A total mixed ration consisting of 58% corn silage, 16% alfalfa hay, and 26% concentrate (dry matter basis) was formulated to meet 100 and 83% of net energy and MP requirements, respectively, and was fed at 90% of ad libitum intake by individual cow. Abomasal infusion treatments were saline (SAL) or 562 g/d of essential AA delivered in 4 profiles where individual AA content corresponded to their relative content in casein. The profiles were (1) a complete essential amino acid mixture (EAAC), (2) Ile, Leu, and Val (ILV), (3) His, Ile, Leu, Met, Phe, Trp, Val (GR1+ILV), and (4) Arg, His, Lys, Met, Phe, Thr, Trp (GR1+ALT). The experiment was conducted in climate respiration chambers to determine energy and N balance in conjunction with milk production and composition, digestibility, and plasma constituents. Compared with SAL, infusion of EAAC increased milk, protein, and lactose yield, increased energy retained as body protein, and did not affect milk N efficiency. Total N intake and urine N output was higher with all AA infusions relative to SAL. Compared with EAAC, infusions of GR1+ILV and GR1+ALT produced the same milk yield and the same yield and content of milk fat, protein, and lactose, and had similar energy and N retention. Milk N efficiency was not different between EAAC and GR1+ILV, but was lower with GR1+ALT compared with EAAC, and tended to be lower with GR1+ALT compared with GR1+ILV. Infusion of ILV tended to decrease dry matter intake compared with the other AA infusions. Milk production and composition was not different between ILV and SAL. Compared with EAAC, infusion of ILV decreased or tended to decrease milk, protein, and lactose yields and milk protein content, and increased milk fat and lactose content. Milk N efficiency decreased with ILV compared with SAL, EAAC, and GR1+ILV. Milk urea concentration was not affected by essential amino acid (EAA) infusions. Plasma urea concentration did not differ between EAAC and SAL, tended to increase with ILV and GR1+ILV over SAL, and increased with GR1+ALT compared with EAAC and SAL. In conclusion, removing Arg, Lys, and Thr or removing Ile, Leu, and Val from a complete EAA profile when the total amount of EAA infused remained constant did not impair milk production, but milk N efficiency decreased when Ile, Leu, and Val were absent. Infusion of only Ile, Leu, and Val decreased milk protein yield and content and reduced milk N efficiency compared with a complete EAA profile.

Mammary gland metabolite utilization in response to exogenous glucose or long-chain fatty acids at low and high metabolizable protein levels.

We investigated mammary gland metabolism in lactating dairy cattle in response to energy from glucogenic (glucose; GG) or lipogenic (palm olein; LG) substrates at low (LMP) and high (HMP) metabolizable protein levels. According to a 6 × 6 Latin square design, 6 rumen-fistulated second-lactation Holstein-Friesian dairy cows (97 ± 13 d in milk) were abomasally infused with saline (LMP-C); isoenergetic infusions (digestible energy basis) of 1,319 g/d glucose (LMP-GG), 676 g/d palm olein (LMP-LG), or 844 g/d essential AA (EAA; HMP-C); or isoenergetic infusions of 1,319 g/d glucose + 844 g/d EAA (HMP-GG) or 676 g/d palm olein + 844 g/d EAA (HMP-LG). Each experimental period consisted of 5 d of continuous infusion followed by 2 d of rest. A total mixed ration (42% corn silage, 31% grass silage, and 27% concentrate on a dry matter basis) formulated to meet 100 and 83% of net energy and metabolizable protein requirements, respectively, was fed at 90% of ad libitum intake by individual cow. Arterial and venous blood samples were collected on d 5 of each period. Infusing GG or LG at the HMP level did not affect milk yield or composition differently than at the LMP level. Neither GG nor LG infusion stimulated milk protein or lactose yield, but fat yield tended to decrease with GG and tended to increase with LG. Infusion of GG increased arterial plasma concentrations of glucose and insulin and decreased concentrations of ß-hydroxybutyrate (BHB), nonesterified fatty acids, long-chain fatty acids (LCFA), total AA, EAA, and group 2 AA. Infusion of LG increased arterial triacylglycerides (TAG) and LCFA but did not affect EAA concentrations. Compared with the LMP level, the HMP level increased arterial concentrations of BHB, urea, and all EAA groups and decreased the concentration of total non-EAA. Mammary plasma flow increased with GG and was not affected by LG or protein level. Uptake and clearance of total EAA and group 2 AA were affected or tended to be affected by GG × AA interactions, with their uptakes being lower and their clearances higher with GG, but only at the LMP level. Infusion of LG did not affect uptake or clearance of any AA group. The HMP level increased uptake and decreased clearance of all EAA groups and decreased non-EAA uptake. Infusion of GG tended to increase mammary glucose uptake, and tended to decrease BHB uptake only at the LMP level. Infusion of LG increased mammary uptake of TAG and LCFA and increased or tended to increase clearance of TAG and LCFA. We suspect GG increased mammary plasma flow to maintain intramammary energy and AA balance and stimulated lipogenesis in adipose, accounting for depressed arterial BHB and group 2 AA concentrations. Mammary glucose uptake did not cover estimated requirements for lactose and fat synthesis at the HMP level, except during HMP-GG infusion. Results of this study illustrate flexibility in mammary metabolite utilization when absorptive supply of glucogenic, lipogenic, and aminogenic substrate is increased.

Expression of genes related to energy metabolism and the unfolded protein response in dairy cow mammary cells is affected differently during dietary supplementation with energy from protein and fat.

Secretory capacity of bovine mammary glands is enabled by a high number of secretory cells and their ability to use a range of metabolites to produce milk components. We isolated RNA from milk fat to measure expression of genes involved in energy-yielding pathways and the unfolded protein response in mammary glands of lactating cows given supplemental energy from protein (PT) and fat (FT) tested in a 2 × 2 factorial arrangement. We hypothesized that PT and FT would affect expression of genes in the branched-chain AA catabolic pathway and tricarboxylic acid (TCA) cycle based on the different energy types (aminogenic versus lipogenic) used to synthesize milk components. We also hypothesized that the response of genes related to endoplasmic reticulum (ER) homeostasis via the unfolded protein response would reflect the increase in milk production stimulated by PT and FT. Fifty-six multiparous Holstein-Friesian dairy cows were fed a basal total mixed ration (34% grass silage, 33% corn silage, 5% grass hay, and 28% concentrate on a dry matter basis) for a 28-d control period. Experimental rations were then fed for 28 d, consisting of (1) low protein, low fat (LP/LF); (2) high protein, low fat (HP/LF); (3) low protein, high fat (LP/HF); or (4) high protein and high fat (HP/HF). To obtain the high-protein (HP) and high-fat (HF) diets, intake of the basal ration was restricted and supplemented isoenergetically (net energy basis) with 2.0 kg/d rumen-protected protein (soybean + rapeseed, 50:50 mixture on dry matter basis) and 0.68 kg/d hydrogenated palm fatty acids on a dry matter basis. RNA from milk fat samples collected on d 27 of each period underwent real-time quantitative PCR. Energy from protein increased expression of BCAT1 (branched-chain amino acid transferase 1) mRNA, but only at the LF level, and tended to decrease expression of mRNA encoding the main subunit of the branched-chain keto-acid dehydrogenase complex. mRNA expression of malic enzyme, a proposed channeling route for AA though the TCA cycle, was decreased by PT, but only at the LF level. Expression of genes associated with de novo fatty acid synthesis was not affected by PT or FT. Energy from fat had no independent effect on genes related to ER homeostasis. At the LF level, PT activated XBP1 (X-box binding protein 1) mRNA. At the HF level, PT increased mRNA expression of the gene encoding GADD34 (growth arrest and DNA damage-inducible 34). These findings support our hypothesis that mammary cells use aminogenic and lipogenic precursors differently for milk component production when dietary intervention alters AA and fatty acid supply. They also suggest that mammary cells respond to increased AA supply through mechanisms of ER homeostasis, dependent on the presence of FT.

Invited review: Nitrogen in ruminant nutrition: A review of measurement techniques.

Nitrogen is a component of essential nutrients critical for the productivity of ruminants. If excreted in excess, N is also an important environmental pollutant contributing to acid deposition, eutrophication, human respiratory problems, and climate change. The complex microbial metabolic activity in the rumen and the effect on subsequent processes in the intestines and body tissues make the study of N metabolism in ruminants challenging compared with nonruminants. Therefore, using accurate and precise measurement techniques is imperative for obtaining reliable experimental results on N utilization by ruminants and evaluating the environmental impacts of N emission mitigation techniques. Changeover design experiments are as suitable as continuous ones for studying protein metabolism in ruminant animals, except when changes in body weight or carryover effects due to treatment are expected. Adaptation following a dietary change should be allowed for at least 2 (preferably 3) wk, and extended adaptation periods may be required if body pools can temporarily supply the nutrients studied. Dietary protein degradability in the rumen and intestines are feed characteristics determining the primary AA available to the host animal. They can be estimated using in situ, in vitro, or in vivo techniques with each having inherent advantages and disadvantages. Accurate, precise, and inexpensive laboratory assays for feed protein availability are still needed. Techniques used for direct determination of rumen microbial protein synthesis are laborious and expensive, and data variability can be unacceptably large; indirect approaches have not shown the level of accuracy required for widespread adoption. Techniques for studying postruminal digestion and absorption of nitrogenous compounds, urea recycling, and mammary AA metabolism are also laborious, expensive (especially the methods that use isotopes), and results can be variable, especially the methods based on measurements of digesta or blood flow. Volatile loss of N from feces and particularly urine can be substantial during collection, processing, and analysis of excreta, compromising the accuracy of measurements of total-tract N digestion and body N balance. In studying ruminant N metabolism, nutritionists should consider the longer term fate of manure N as well. Various techniques used to determine the effects of animal nutrition on total N, ammonia- or nitrous oxide-emitting potentials, as well as plant fertilizer value, of manure are available. Overall, methods to study ruminant N metabolism have been developed over 150 yr of animal nutrition research, but many of them are laborious and impractical for application on a large number of animals. The increasing environmental concerns associated with livestock production systems necessitate more accurate and reliable methods to determine manure N emissions in the context of feed composition and ruminant N metabolism.

Energy and nitrogen partitioning in dairy cows at low or high metabolizable protein levels is affected differently by postrumen glucogenic and lipogenic substrates.

This study tested the effects of energy from glucogenic (glucose; GG) or lipogenic (palm olein; LG) substrates at low (LMP) and high (HMP) metabolizable protein levels on whole-body energy and N partitioning of dairy cattle. Six rumen-fistulated, second-lactation Holstein-Friesian dairy cows (97 ± 13 d in milk) were randomly assigned to a 6 × 6 Latin square design in which each experimental period consisted of 5 d of continuous abomasal infusion followed by 2 d of rest. A total mixed ration consisting of 42% corn silage, 31% grass silage, and 27% concentrate (dry matter basis) was formulated to meet 100 and 83% of net energy and metabolizable protein requirements, respectively, and was fed at 90% of ad libitum intake by individual cow. Abomasal infusion treatments were saline (LMP-C), isoenergetic infusions (digestible energy basis) of 1,319 g/d of glucose (LMP-GG), 676 g/d of palm olein (LMP-LG; major fatty acid constituents are palmitic, oleic, and linoleic acid), or 844 g/d of essential AA (HMP-C), or isoenergetic infusions of 1,319 g/d of glucose + 844 g/d of essential AA (HMP-GG) or 676 g/d of palm olein + 844 g/d of essential AA (HMP-LG). The experiment was conducted in climate respiration chambers to determine energy and N balance in conjunction with milk production and composition, nutrient digestibility, and plasma constituents. Infusion of GG and LG decreased dry matter intake, but total gross energy intake from the diet plus infusions was not affected by GG or LG. Furthermore, GG or LG did not affect total milk, protein, or lactose yields. Infusing GG or LG at the HMP level did not affect milk production differently than at the LMP level. Infusion of GG stimulated energy retention in body tissue, increased plasma glucose and insulin concentrations, decreased lipogenic metabolites in plasma, and decreased milk fat yield and milk energy output. Nitrogen intake decreased and milk N efficiency increased in response to GG, and N retention was not affected. Infusion of LG tended to increase metabolizable energy intake, increased milk fat yield and milk energy output, increased plasma triacylglycerides and long-chain fatty acid concentrations, and had no effect on energy retention. Infusion of LG decreased N intake but did not affect milk N efficiency or N retention. Compared with the LMP level, the HMP level increased dry matter intake, gross and metabolizable energy intake, and total milk, fat, protein, and lactose yields. Milk energy output increased at the HMP level, and protein level did not affect total energy retention. Heat production increased at the HMP level, but only when GG and LG were infused. The HMP level increased N intake, milk N output, and plasma urea concentration, tended to increase N retention, and decreased milk N efficiency. Regardless of protein level, GG promoted energy retention and improved milk N efficiency, but not through increased milk protein yield. Infusion of LG partitioned extra energy intake into milk and had no effect on milk N efficiency.

Mammary gland utilization of amino acids and energy metabolites differs when dairy cow rations are isoenergetically supplemented with protein and fat.

Mammary gland utilization of AA and other metabolites in response to supplemental energy from protein (PT) and supplemental energy from fat (FT) was tested in a 2 × 2 factorial arrangement using a randomized complete block design. Fifty-six Holstein-Friesian dairy cows were adapted during a 28-d control period to a basal total mixed ration consisting of 34% grass silage, 33% corn silage, 5% grass hay, and 28% concentrate on a dry matter (DM) basis. Experimental rations were fed for 28 d immediately following the control period and consisted of (1) low protein, low fat (LP/LF), (2) high protein, low fat (HP/LF), (3) low protein, high fat (LP/HF), and (4) high protein, high fat (HP/HF). To obtain the high-protein (HP) and high-fat (HF) diets, intake of the basal ration was restricted and supplemented isoenergetically [net energy (MJ/d) basis] with 2.0 kg/d rumen-protected protein (soybean + rapeseed, 50:50 mixture on a DM basis) and 0.68 kg/d hydrogenated palm fatty acids on a DM basis. Arterial and venous blood samples were collected on d 28 of both periods. Isoenergetic supplements (MJ/d) of protein and fat independently and additively increased milk yield, PT increased protein yield, and FT increased fat yield. A PT × FT interaction affected arterial concentration of all essential AA (EAA) groups, where they increased in response to PT by a greater magnitude at the LF level (on average 35%) compared with the HF level (on average 14%). Mammary gland plasma flow was unaffected by PT or FT. Supplementation with PT tended to decrease mammary clearance of total EAA and decreased group 1 AA clearance by 19%. In response to PT, mammary uptake of total EAA and group 2 AA increased 12 and 14%, respectively, with significantly higher uptake of Arg, Ile, and Leu. Energy from fat had no effect on mammary clearance or uptake of any AA group. The mammary gland uptake:milk protein output ratio was not affected by FT, whereas PT increased this ratio for EAA and group 2 AA. Arterial plasma insulin concentration decreased in response to FT, in particular on the HP/HF diet, as indicated by a PT × FT interaction. Arterial concentrations of nonesterified fatty acids, triacylglycerol, and long-chain fatty acids increased in response to FT, and concentrations of ß-hydroxybutyrate and acetate decreased in response to FT only at the HP level. Mammary clearance and uptake of triacylglycerol and long-chain fatty acids increased in response to FT. Energy from PT and FT increased lactose yield despite no change in arterial glucose concentration or mammary glucose uptake. Mammary-sequestered glucose with PT or FT was used in the same amount for lactose synthesis, and a positive net mammary glucose balance was found across all treatments. Results presented here illustrate metabolic flexibility of the mammary gland in its use of aminogenic versus lipogenic substrates for milk synthesis.

Multi-criteria evaluation of dairy cattle feed resources and animal characteristics for nutritive and environmental impacts.

On-farm nutrition and management interventions to reduce enteric CH4 (eCH4) emission, the most abundant greenhouse gas from cattle, may also affect volatile solids and N excretion. The objective was to jointly quantify eCH4 emissions, digestible volatile solids (dVS) excretion and N excretion from dairy cattle, based on dietary variables and animal characteristics, and to evaluate relationships between these emissions and excreta. Univariate and Bayesian multivariate mixed-effects models fitted to 520 individual North American dairy cow records indicated dry matter (DM) intake and dietary ADF and CP to be the main predictors for production of eCH4 emissions and dVS and N excreta (g/day). Yields (g/kg DM intake) of eCH4 emissions and dVS and N excreta were best predicted by dietary ADF, dietary CP, milk yield and milk fat content. Intensities (g/kg fat- and protein-corrected milk) of eCH4, dVS and N excreta were best predicted by dietary ADF, dietary CP, days in milk and BW. A K-fold cross-validation indicated that eCH4 and urinary N variables had larger root mean square prediction error (RMSPE; % of observed mean) than dVS, fecal N and total N production (on average 24.3% and 26.5% v. 16.7%, 15.5% and 16.2%, respectively), whereas intensity variables had larger RMSPE than production and yields (29.4%, 14.7% and 14.6%, respectively). Univariate and multivariate equations performed relatively similar (18.8% v. 19.3% RMSPE). Mutual correlations indicated a trade-off for eCH4 v. dVS yield. The multivariate model indicated a trade-off between eCH4 and dVS v. total N production, yield and intensity induced by dietary CP content.