The application of nonlinear programming on ration formulation for dairy cattle.

The objective of this study was to compare the application of iterative linear programming (iteLP), sequential quadratic programming (SQP), and mixed-integer nonlinear programming-based deterministic global optimization (MINLP_DGO) on ration formulation for dairy cattle based on Nutrient Requirements of Dairy Cattle (NRC, 2001). Least-cost diets were formulated for lactating cows, dry cows, and heifers. Nutrient requirements including energy, protein, and minerals, along with other limitations on dry matter intake, neutral detergent fiber, and fat were considered as constraints. Five hundred simulations were conducted, with each simulation randomly selecting 3 roughages and 5 concentrates from the feed table in NRC (2001) as the feed resource for each of 3 animal groups. Among the 500 simulations for lactating cows, 57, 45, and 21 simulations did not yield a feasible solution when using iteLP, SQP, and MINLP_DGO, respectively. All the simulations for dry cows and heifers were feasible when using SQP and MINLP_DGO, but 49 and 11 infeasible simulations occurred when using iteLP for dry cows and heifers, respectively. The average ration costs per animal per day of the feasible solutions obtained by iteLP, SQP, and MINLP_DGO were $4.78 (±0.71), $4.45 (±0.65), and $4.44 (±0.65) for lactating cows; $2.39 (±0.52), $1.48 (±0.26), and $1.48 (±0.26) for dry cows; and $0.98 (±0.72), $0.97 (±0.15), and $0.91 (±0.14) for heifers, respectively. The average computation time of iteLP, SQP, and MINLP_DGO were 0.59 (±1.87) s, 1.15 (±0.62) s, and 58.69 (±68.45) s for lactating cows; 0.041 (±0.070) s, 0.76 (±0.37) s, and 14.84 (±39.09) s for dry cows; and 1.60 (±2.90) s, 0.51 (±0.19) s, and 16.45 (±45.56) s for heifers, respectively. In conclusion, iteLP had limited capability of formulating least-cost diets when nonlinearity existed in the constraints. Both SQP and MINLP_DGO handled the nonlinear constraints well, with SQP being faster, whereas MINLP_DGO was able to return a feasible solution under some situations where SQP could not.

Preweaning cost of bovine respiratory disease (BRD) and cost-benefit of implementation of preventative measures in calves on California dairies: The BRD 10K study.

Bovine respiratory disease (BRD) is a multifactorial disease that is estimated to affect 22% of preweaned dairy calves in the United States and is a leading cause of preweaning mortality in dairy calves. Overall cost of calfhood BRD is reflected in both the immediate cost of treating the disease as well as lifetime decrease in production and increased likelihood of affected cattle leaving the herd before their second calving. The goal of this paper was to develop an estimate of the cost of BRD based on longitudinal treatment data from a study of BRD with a cohort of 11,470 preweaned dairy calves in California. Additionally, a cost-benefit analysis was performed for 2 different preventative measures for BRD, an increase of 0.47 L of milk per day for all calves or vaccination of all dams with a modified live BRD vaccine, using differing assumptions about birth rate and number of calves raised per year. Average short-term cost of BRD per affected calf was $42.15, including the use of anti-inflammatory medications in the treatment protocols across all management conditions. The cost of treating BRD in calves appears to have increased in recent years and is greater than costs presented in previous studies. A cost-benefit analysis examined different herd scenarios for a range of cumulative incidences of BRD from 3 to 25%. Increasing milk fed was financially beneficial in all scenarios above a 3% cumulative incidence of BRD. Use of a modified live vaccine in dams during pregnancy, examining only its value as a form of BRD prevention in the calves raised on the farm, was financially beneficial only if the cumulative incidence of BRD exceeded 10 to 15% depending on the herd size and whether the dairy farm was raising any bull calves. The cost-benefit analysis, under the conditions studied, suggests that producers with high rates of BRD may benefit financially from implementing preventative measures, whereas these preventative measures may not be cost effective to implement on dairy farms with very low cumulative incidences of BRD. The long-term costs of calfhood BRD on lifetime productivity were not factored into these calculations, and the reduction in disease may be associated with additional cost savings and an improvement in calf welfare and herd life.

A goal programming approach for balancing diet costs and feed water use under different environmental conditions.

Water is essential in livestock production systems. In typical dairy production systems, 90% of the total water used by a dairy farm is attributed to feed production. Theoretically, ration manipulation is a method to potentially reduce the irrigation water needed for feed crops without dramatically increasing diet costs. However, published quantitative studies on the relationship between feed production and water use that are integrated with linear programming models are scarce. The overall objective of this study was to develop an optimization framework that could achieve a balance between minimization of dietary costs and dietary irrigation water usage, and that could be used as a framework for future research and models for various livestock production systems. Weighted goal programming models were developed to minimize the dietary costs and irrigation water usage for a hypothetical cow under 8 different environmental scenarios. The environmental conditions used a 2 × 2 × 2 factorial design, including 2 atmospheric CO2 concentrations (400 and 550 ppm), 2 water years (dry and wet), and 2 irrigation methods (furrow and drip). A systematic weighting scheme was used to model the trade-off between minimizing diet cost and minimizing irrigation water use for feedstuffs. Each environmental condition generated a set of distinct diets, which each met the same nutrient requirements of the hypothetical cow but had a different water usage when the weighting scheme was changed from weighting minimum diet costs to minimum irrigation water usage. For water resource planning in areas of dairy production, this set of unique solutions provides the decision maker with different feeding options according to diet cost, water usage, and available feeds. As water was more constrained, dietary dry matter intake increased, concentrations of neutral detergent fiber, ether extract, and energy decreased, and the concentration of lignin increased because less nutritive but more water-saving feedstuffs were included in the diet. Mitigation costs of water usage were calculated from goal programming results and indicated that the potential value of water under water-limited conditions (e.g., in a drought region) was higher than that under water-sufficient conditions. However, a smaller increase in feed costs can initially significantly reduce water usage compared with that of a least-cost diet, which implies that the reduction of water usage through ration manipulation might be possible. This model serves as a framework for the study of irrigation water usage in dairy production and other livestock production systems and for decision-making processes involved in water resources planning in the broader area of animal production.

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.

Short communication: Urea hydrolysis in dairy cattle manure under different temperature, urea, and pH conditions.

The objective of the study was to quantify the rate of urea hydrolysis in dairy cattle manure under different initial urea concentration, temperature, and pH conditions. In particular, by varying all 3 factors simultaneously, the interactions between them could also be determined. Fresh feces and artificial urine solutions were combined into a slurry to characterize the rate of urea hydrolysis under 2 temperatures (15°C and 35°C), 3 urea concentrations in urine solutions (500, 1,000, and 1,500 mg of urea-N/dL), and 3 pH levels (6, 7, and 8). Urea N concentration in slurry was analyzed at 0.0167, 1, 2, 4, 6, 8, 12, 16, 20, and 24 h after initial mixing. A nonlinear mixed effects model was used to determine the effects of urea concentration, pH, and temperature treatments on the exponential rate of urea hydrolysis and to predict the hydrolysis rate for each treatment combination. We detected a significant interaction between pH and initial urea level. Increasing urea concentration from 1,000 to 1,500 mg of urea-N/dL decreased the rate of urea hydrolysis across all pH levels. Across all pH and initial urea levels, the rate of urea hydrolysis increased with temperature, but the effect of pH was only observed for pH 6 versus pH 8 at the intermediate initial urea concentration. The fast rates of urea hydrolysis indicate that urea was almost completely hydrolyzed within a few hours of urine mixing with feces. The estimated urea hydrolysis rates from this study are likely maximum rates because of the thorough mixing before each sampling. Although considerable mixing of feces and urine occurs on the barn floor of commercial dairy operations from cattle walking through the manure, such mixing may be not as quick and thorough as in this study. Consequently, the urea hydrolysis rates from this study indicate the maximum loss of urea and should be accounted for in management aimed at mitigating ammonia emissions from dairy cattle manure under similar urea concentration, pH, and temperature conditions reported in this experiment.

Effect of calving interval and parity on milk yield per feeding day in Danish commercial dairy herds.

The idea of managing cows for extended lactations rather than lactations of the traditional length of 1 yr primarily arose from observations of increasing problems with infertility and cows being dried off with high milk yields. However, it is vital for the success of extended lactation practices that cows are able to maintain milk yield per feeding day when the length of the calving interval (CInt) is increased. Milk yield per feeding day is defined as the cumulated lactation milk yield divided by the sum of days between 2 consecutive calvings. The main objective of this study was to investigate the milk production of cows managed for lactations of different lengths, and the primary aim was to investigate the relationship between CInt, parity, and milk yield. Five measurements of milk yield were used: energy-corrected milk (ECM) yield per feeding day, ECM yield per lactating day, cumulative ECM yield during the first 305 d of lactation, as well as ECM yield per day during early and late lactation. The analyses were based on a total of 1,379 completed lactations from cows calving between January 2007 and May 2013 in 4 Danish commercial dairy herds managed for extended lactation for several years. Herd-average CInt length ranged from 414 to 521 d. The herds had Holstein, Jersey, or crosses between Holstein, Jersey, and Red Danish cows with average milk yields ranging from 7,644 to 11,286 kg of ECM per cow per year. A significant effect of the CInt was noted on all 5 measurements of milk yield, and this effect interacted with parity for ECM per feeding day, ECM per lactating day and ECM per day during late lactation. The results showed that cows were at least able to produce equivalent ECM per feeding day with increasing CInt, and that first- and second-parity cows maintained ECM per lactating day. Cows with a CInt between 17 and 19 mo produced 476 kg of ECM more during the first 305 d compared with cows with a CInt of less than 13 mo. Furthermore, early-lactation ECM yield was greater for all cows and late-lactation ECM yield was less for second-parity and older cows when undergoing an extended compared with a shorter lactation. Increasing CInt increased the dry period length with 3 to 5d. In conclusion, the group of cows with longer CInt were able to produce at least equivalent amounts of ECM per feeding day when the CInt was up to 17 to 19 mo on these 4 commercial dairy farms.

Tomato seeds as a novel by-product feed for lactating dairy cows.

Whole tomato seeds, a novel by-product feedstuff, were fed to lactating Holstein cows to determine the nutritive value of whole tomato seeds by replacing whole cottonseed in the total mixed ration. Four primiparous and 4 multiparous Holstein cows were used in a 4×4 Latin square design and fed 1 of 4 total mixed rations. Whole tomato seeds replaced whole cottonseed on a weight-to-weight basis for lipid. The proportion of whole tomato seeds to whole cottonseed in the diets were 100:0, 50:50, 25:75, and 0:100 on a lipid basis. Thus, tomato seeds were 4.0, 2.4, 1.1, and 0% of the ration dry matter, respectively. Milk yield and the concentrations and yields of protein, lactose, and solids-not-fat did not differ for the effect of diet. However, milk fat concentration decreased and milk fat yield tended to decrease as whole tomato seeds replaced whole cottonseed. Intakes of dry matter, lipid, and crude protein did not differ. Whole-tract apparent digestibility of dry matter and ash-free neutral detergent fiber did not differ, but digestibility of total fatty acids and crude protein decreased with increasing proportion of whole tomato seeds. Urea concentration in milk and plasma both decreased with increasing whole tomato seeds. Fecal concentration of linoleic and α-linolenic acids increased with increasing whole tomato seeds, suggesting that seeds were passing out of the digestive tract undigested. The concentrations of C18:2n-6 and C18:3n-3 in milk fat had small increases, but their yields were not different, suggesting that only a small amount of whole-tomato-seed lipid might have been digested postruminally. Amounts of trans C18:1 fatty acids in milk fat were higher with increasing whole cottonseed, which might suggest a shift in rumen biohydrogenation pathways. At the level of feeding used in the current study, whole tomato seeds replaced whole cottonseed in the diet of lactating dairy cows without a change in production.

Modeling the trade-off between diet costs and methane emissions: A goal programming approach.

Enteric methane emission is a major greenhouse gas from livestock production systems worldwide. Dietary manipulation may be an effective emission-reduction tool; however, the associated costs may preclude its use as a mitigation strategy. Several studies have identified dietary manipulation strategies for the mitigation of emissions, but studies examining the costs of reducing methane by manipulating diets are scarce. Furthermore, the trade-off between increase in dietary costs and reduction in methane emissions has only been determined for a limited number of production scenarios. The objective of this study was to develop an optimization framework for the joint minimization of dietary costs and methane emissions based on the identification of a set of feasible solutions for various levels of trade-off between emissions and costs. Such a set of solutions was created by the specification of a systematic grid of goal programming weights, enabling the decision maker to choose the solution that achieves the desired trade-off level. Moreover, the model enables the calculation of emission-mitigation costs imputing a trading value for methane emissions. Emission imputed costs can be used in emission-unit trading schemes, such as cap-and-trade policy designs. An application of the model using data from lactating cows from dairies in the California Central Valley is presented to illustrate the use of model-generated results in the identification of optimal diets when reducing emissions. The optimization framework is flexible and can be adapted to jointly minimize diet costs and other potential environmental impacts (e.g., nitrogen excretion). It is also flexible so that dietary costs, feed nutrient composition, and animal nutrient requirements can be altered to accommodate various production systems.

Multivariate and univariate analysis of energy balance data from lactating dairy cows.

The objectives of the study were to develop a multivariate framework for analyzing energy balance data from lactating cows and investigate potential changes in maintenance requirements and partial efficiencies of energy utilization by lactating cows over the years. The proposed model accounted for the fact that metabolizable energy intake, milk energy output, and tissue energy balance are random variables that interact mutually. The model was specified through structural equations implemented in a Bayesian framework. The structural equations, along with a model traditionally used to estimate energetic parameters, were fitted to a large database of indirect calorimetry records from lactating cows. Maintenance requirements and partial efficiencies for both models were similar to values reported in the literature. In particular, the estimated parameters (with 95% credible interval in parentheses) for the proposed model were: net energy requirement for maintenance equal to 0.36 (0.34, 0.38) MJ/kg of metabolic body weight·day; the efficiency of utilizing dietary energy for milk production and tissue gain were 0.63 (0.61, 0.64) and 0.70 (0.68, 0.72), respectively; the efficiency of utilizing body stores for milk production was 0.89 (0.87, 0.91). Furthermore, additional analyses were conducted for which energetic parameters were allowed to depend on the decade in which studies were conducted. These models investigated potential changes in maintenance requirements and partial efficiencies over the years. Canonical correlation analysis was used to investigate the association between changes in energetic parameters with additional dietary and animal characteristics available in the database. For both models, net energy requirement for maintenance and the efficiency of utilizing dietary energy for milk production and tissue gain increased in the more recent decades, whereas the efficiency of utilizing body stores for milk production remained unchanged. The increase in maintenance requirements in modern milk production systems is consistent with the literature that describes increased fasting heat production in cows of higher genetic merit. The increase in utilization of dietary energy for milk production and tissue gain was partially attributed to the changes in dietary composition, in particular to the increase in dietary ether extract to levels closer to currently observed in modern milk production systems. Therefore, the estimated energetic parameters from this study can be used to update maintenance requirements and partial efficiencies of energy utilization in North American feeding systems for lactating cows.

Technical note: Alternatives to reduce adipose tissue sampling bias.

Understanding the mechanisms by which nutritional and pharmaceutical factors can manipulate adipose tissue growth and development in production animals has direct and indirect effects in the profitability of an enterprise. Adipocyte cellularity (number and size) is a key biological response that is commonly measured in animal science research. The variability and sampling of adipocyte cellularity within a muscle has been addressed in previous studies, but no attempt to critically investigate these issues has been proposed in the literature. The present study evaluated 2 sampling techniques (random and systematic) in an attempt to minimize sampling bias and to determine the minimum number of samples from 1 to 15 needed to represent the overall adipose tissue in the muscle. Both sampling procedures were applied on adipose tissue samples dissected from 30 longissimus muscles from cattle finished either on grass or grain. Briefly, adipose tissue samples were fixed with osmium tetroxide, and size and number of adipocytes were determined by a Coulter Counter. These results were then fit in a finite mixture model to obtain distribution parameters of each sample. To evaluate the benefits of increasing number of samples and the advantage of the new sampling technique, the concept of acceptance ratio was used; simply stated, the higher the acceptance ratio, the better the representation of the overall population. As expected, a great improvement on the estimation of the overall adipocyte cellularity parameters was observed using both sampling techniques when sample size number increased from 1 to 15 samples, considering both techniques' acceptance ratio increased from approximately 3 to 25%. When comparing sampling techniques, the systematic procedure slightly improved parameters estimation. The results suggest that more detailed research using other sampling techniques may provide better estimates for minimum sampling.

Characterizing bovine adipocyte distribution and its relationship with carcass and meat characteristics using a finite mixture model.

The appreciation of adipose tissue complexity has initiated a new era of multifaceted investigations that continue to provide findings in adipocyte biology, but quantitative descriptions of adipocyte distribution are lacking. The first objective was to develop a finite mixture model to model adipocyte bimodal distribution and to correlate these estimates with carcass and meat characteristics. A secondary objective was to demonstrate within-animal observed variability in adipocyte cellularity. Steers were finished on a high-grain diet (n = 14) or grass (n = 16). One 12-cm thick LM steak from each steer was collected during harvest. A probability density function was developed that partitioned the cell diameter population into small and large populations and described the relative proportions of cells for each animal in these 2 distinct populations. Five parameters were estimated through the finite mixture model: the means (µ(1) and µ(2)) and SD (σ(1) and σ(2)) for the small and large adipocyte populations, respectively, and a proportion parameter (p) describing the proportion of the distribution of the smaller adipocyte populations. The proportion parameter for all animals tended to be different (P = 0.07) between groups with the grain presenting a p of 22.5 ± 12.5% and grass 16.2 ± 4.7%. The µ(2) was correlated with yield grade (YG, P = 0.04), and σ(2) with final BW, HCW, dressing percentage, YG, and quality grade score (P = 0.01). When correlating these parameters with the sensory data, µ(2) and σ(2) were correlated with tenderness (P ≤ 0.05), σ(1) and p with juiciness (P ≤ 0.05), and p with overall palatability (P = 0.01). Adipocyte cellularity variability was measured by examining the results from 5 randomly chosen steers from each group (grain and grass). In this subset, the µ(1) and p ranged from 32.1 to 46.1 µm and 1 to 27% for grass-finished steers, and ranged from 33.7 to 41.0 µm and 10 to 48% for grain-finished steers. The µ(2) and (1 - p) ranged from 75.0 to 105.1 µm and 73 to 99% for grass-finished steers, respectively, and ranged from 84.8 to 124.0 µm and 52 to 90% for grain-finished steers, respectively. The finite mixture model provides a quantitative description of the distribution of adipocytes and contributes to explaining adipocyte biology. Adipocyte cellularity variability among samples within an animal is a topic that should be further evaluated, as well as its correlation with other factors, such as gene expression and hormone secretion.

A linear programming model to optimize diets in environmental policy scenarios.

The objective was to develop a linear programming model to formulate diets for dairy cattle when environmental policies are present and to examine effects of these policies on diet formulation and dairy cattle nitrogen and mineral excretions as well as methane emissions. The model was developed as a minimum cost diet model. Two types of environmental policies were examined: a tax and a constraint on methane emissions. A tax was incorporated to simulate a greenhouse gas emissions tax policy, and prices of carbon credits in the current carbon markets were attributed to the methane production variable. Three independent runs were made, using carbon dioxide equivalent prices of $5, $17, and $250/t. A constraint was incorporated into the model to simulate the second type of environmental policy, reducing methane emissions by predetermined amounts. The linear programming formulation of this second alternative enabled the calculation of marginal costs of reducing methane emissions. Methane emission and manure production by dairy cows were calculated according to published equations, and nitrogen and mineral excretions were calculated by mass conservation laws. Results were compared with respect to the values generated by a base least-cost model. Current prices of the carbon credit market did not appear onerous enough to have a substantive incentive effect in reducing methane emissions and altering diet costs of our hypothetical dairy herd. However, when emissions of methane were assumed to be reduced by 5, 10, and 13.5% from the base model, total diet costs increased by 5, 19.1, and 48.5%, respectively. Either these increased costs would be passed onto the consumer or dairy producers would go out of business. Nitrogen and potassium excretions were increased by 16.5 and 16.7% with a 13.5% reduction in methane emissions from the base model. Imposing methane restrictions would further increase the demand for grains and other human-edible crops, which is not a progressive solution for an industry trying to be sustainable. However, these results might depend on the constraints and inputs used in our model (e.g., feed prices), and more extensive analyses are required before they are used in policy development. The model structure was able to incorporate effects of environmental policies in diet formulation and it can assist dairy producers in meeting limits set by these policies. The model can also assist policy makers examining the effects of policies on the dairy production system.

Physiological and productive responses of multiparous lactating Holstein cows exposed to short-term cooling during severe summer conditions in an arid region of Mexico.

Heat stress generates a significant economic impact for the dairy industry in arid and semi-arid regions of the world, so that heat abatement is an important issue for dairy producers. The objective of this study was to evaluate effects of two short-term cooling periods on physiological and productive status of lactating Holstein cows during hot ambient temperatures. Thirty-nine multiparous cows were blocked by milk yield and assigned to one of three treatments including: control group (C), cows cooled before milking time (0500 and 1700 h daily, 1 h cooling); AM group, cows cooled at 1000 h and before milking (2 h cooling); and AM + PM group, cows cooled at 1100, 1500 and 2200 h, as well as before milking (4 h cooling). The cooling system was placed in the holding pen which the cows were moved through for cooling. Respiratory rate, and temperatures of thurl and right flank, were lower (P < 0.05) in cows from the AM + PM group than AM and C cows during the morning and afternoon. However, udder temperature was higher in the AM + PM group compared to AM and C groups during the afternoon, although lower than the AM group during the morning. Rectal temperature was similar in all groups. Thyroxin concentrations tended (P < 0.10) to be lower in AM + PM relative to the AM and C groups. The AM + PM group had higher (P < 0.05) milk production than C (18.70 vs. 17.43 kg, respectively), and AM + PM cows had a trend (P < 0.10) to increased milk energy output vs. the C and AM groups (13.75 vs. 13.18 and 13.15 Mcal, respectively). Protein and fat in milk, body condition score, glucose, cholesterol, triglycerides and triiodothyronine were similar among the groups. Four hours of cooling with spray and fans during severe summer temperatures only modestly improved milk yield of lactating Holstein cows.

Meta-analysis to predict sweating and respiration rates for Bos indicus, Bos taurus, and their crossbreds.

The overall objective of this work was to develop empirical equations from a meta-analysis study to be used to implement initial values in a mechanistic heat balance model. The meta-analysis was conducted to 1) develop prediction equations for sweating and respiration rate (SR, g·m(-2)·h(-1) and RR, breaths·min(-1), respectively) based on skin and body temperature (T(s) and T(b), °C, respectively) for different breed types: Bos indicus, Bos taurus, and their crossbreds, and 2) evaluate the fit of existing SR equations and the SR and RR equations (from objective 1) against independent data sets. Fourteen studies were collected for the SR analysis, 12 for fitting and 2 for evaluation. The fitted SR equations (Thompson model) for the 3 breeds types were B. indicus, SR = 0.085e(0.22·T(s)); B. taurus, SR = 0.75e(0.15·T(s)); and crossbreds, SR = 0.015e(0.25·T(s)). Twenty-three studies were collected for the RR analysis, 20 for fitting and 3 for evaluation. The fitted RR equations for the 3 breed types were B. indicus, RR = -1,660 + 43.8·T(b); B. taurus, RR = -1,385 + 37·T(b); and crossbreds, RR = -2,226 + 59·T(b). Three SR equations (Maia, McArthur, and Gatenby models) from the literature were evaluated against the Thompson model using the 14 studies. The McArthur model predicted SR within the correct range, but with an increased slope bias because the equation was linear and not the correct shape. The Maia model overpredicted SR for all breed types with the greatest overprediction being for crossbreds. The Gatenby model overpredicted SR for B. taurus (root mean square error of prediction = 506 g·m(-2)·h(-1)), but was the best predictor for B. indicus. The Thompson model overpredicted SR for B. indicus (root mean square error of prediction ranged from 134 to 265 g·m(-2)·h(-1)), but was the best predictor for B. taurus and crossbreds. The Thompson model was a good predictor for RR across all breed types. The meta-analysis showed that the Thompson model outperformed previous models for both RR and SR with the exception of the SR of B. indicus, which was best predicted by the Gatenby model.

Survey of dairy housing and manure management practices in California.

In 2007, a descriptive survey was mailed to all dairies in Glenn (G) and Tulare (T) Counties to identify current and future opportunities of manure management practices on California dairies. The purpose was to provide baseline information for development of outreach curriculum and a decision support tool to quantify potential benefits of various N management options on dairy farms. Such baseline information is valuable to staff regulating dairy facilities (e.g., San Joaquin Valley Unified Air Pollution Control District and Central Valley Regional Water Quality Control Board), dairy trade association representatives, and technology vendors. Response rates for each county were similar at 29.7% (n=19; G) and 26.7% (n=88; T). Mean milking herd size averaged 570 (range 50 to 3,000) cows in G and 1,800 (range 196 to 9,286) cows in T. Survey data are reported by location due to differences between counties in herd size, housing facilities, and climate. Freestalls are common housing facilities (63.2%, G; 38.6%, T) and separated solids and corral scrapings are commonly used as bedding in freestalls (81.8% G and 79.4% T). The most common methods of manure collection were flushing and scraping (18.8%, G; 44.7%, T), only flushing (43.8%, G; 34.1%, T), or only scraping daily or less frequently than daily (37.5%, G; 20.0%, T). Most dairy farms in G (63.2%) and T (70.5%) used some method of separating solids from liquids. However, mechanical separation systems alone were used by 5.3% G and 11.4% T of dairy farms. Storage or treatment ponds were found on 95.9% of dairies. Respondents identified existing manure management practices and did not indicate any new technologies were in use or being considered for manure management. Survey results were used to describe the 2 predominant manure management pathways of manure collection, storage, treatment, and utilization. Survey results will be used to develop and disseminate targeted information on manure treatment technologies, and on-farm evaluation of implemented technologies related to anaerobic digesters, solid liquid separation, and pond additives.

Prediction of ammonia emission from dairy cattle manure based on milk urea nitrogen: relation of milk urea nitrogen to ammonia emissions.

The main objectives of this study were to assess the relationship between ammonia emissions from dairy cattle manure and milk urea N (MUN; mg/dL) and to test whether the relationship was affected by stage of lactation and the dietary crude protein (CP) concentration. Twelve lactating multiparous Holstein cows were randomly selected and blocked into 3 groups of 4 cows intended to represent early [123+/-26 d in milk (DIM)], mid (175+/-3 DIM), and late (221+/-12 DIM) lactation stages. Cows within each stage of lactation were randomly assigned to a treatment sequence within a split-plot Latin square design balanced for carryover effects. Stage of lactation formed the main plots (squares) and dietary CP levels (15, 17, 19, and 21% of diet dry matter) formed the subplots. The experimental periods lasted 7 d, with d 1 to 6 used for adjustment to diets and d 7 used for total collection of feces and urine as well as milk sample collection. The feces and urine from each cow were mixed in the proportions in which they were excreted to make slurry that was used to measure ammonia emissions at 22.5 degrees C over 24 h using flux chambers. Samples of manure slurry were taken before and after ammonia emission measurements. The amount of slurry increased by 22% as dietary CP concentration increased from 15 to 21%, largely because of a greater urine volume (25.3 to 37.1 kg/d). Initial urea N concentration increased linearly with dietary CP from 153.5 to 465.2 mg/dL in manure slurries from cows fed 15 to 21% CP diets. Despite the large initial differences, the final concentration of urea N in manure slurries was less than 10.86 mg/dL for all dietary treatments. The final total ammoniacal N concentration in manure slurries increased linearly from 228.2 to 508.7 mg/dL as dietary CP content increased from 15 to 21%. Ammonia emissions from manure slurries ranged between 57 and 149 g of N/d per cow and increased linearly with dietary CP content, but were unaffected by stage of lactation. Ammonia emission expressed as a proportion of N intake increased with percentage CP in the diet from about 12 to 20%, whereas ammonia emission as a proportion of urinary urea N excretion decreased from 67 to 47%. There was a strong relationship between ammonia emission and MUN [ammonia emission (g/d per cow)=25.0 (+/-6.72)+5.03 (+/-0.373) x MUN (mg/dL); R(2)=0.85], which was not different among lactation stages. Milk urea N concentration is one of several factors that allows prediction of ammonia emissions from dairy cattle manure.

Evaluation of sample preservation methods for poultry manure.

When poultry manure is collected but cannot be analyzed immediately, a method for storing the manure is needed to ensure accurate subsequent analyses. This study has 3 objectives: (1) to investigate effects of 4 poultry manure sample preservation methods (refrigeration, freezing, acidification, and freeze-drying) on the compositional characteristics of poultry manure; (2) to determine compositional differences in fresh manure with manure samples at 1, 2, and 3 d of accumulation under bird cages; and (3) to assess the influence of 14-d freezing storage on the composition of manure when later exposed to 25 degrees C for 7 d as compared with fresh manure. All manure samples were collected from a layer house. Analyses performed on the manure samples included total Kjeldahl nitrogen, uric acid nitrogen, ammonia nitrogen, and urea nitrogen. In experiment 1, the storage methods most similar to fresh manure, in order of preference, were freezing, freeze-drying, acidification, and refrigeration. Thoroughly mixing manure samples and compressing them to 2 to 3 mm is important for the freezing and freeze-dried samples. In general, refrigeration was found unacceptable for nitrogen analyses. A significant effect (P < 0.0001) of time for refrigeration was found on uric acid nitrogen and ammonia nitrogen. In experiment 2, the total Kjeldahl nitrogen and uric acid nitrogen were significantly lower (P < 0.05) for 1, 2, and 3 d of accumulation compared with fresh manure. Manure after 1, 2, and 3 d of accumulation had similar nitrogen compositions. The results from experiment 3 show that nitrogen components from fresh manure samples and thawed samples from 14 d of freezing are similar at 7 d but high variability of nitrogen compositions during intermediate times from 0 to 7 d prevents the recommendation of freezing manure for use in subsequent experiments and warrants future experimentation. In conclusion, fresh poultry manure can be frozen for accurate subsequent nitrogen compositional analyses but this same frozen manure may not be a reliable substitute for fresh manure if a subsequent experiment is performed.

Effects of shade and sprinklers on performance, behavior, physiology, and the environment of heifers.

The objective was to measure effects of cooling technique (shade vs. water sprinklers) on performance, behavior, physiology, and the environmental effect of 40 Holstein heifers housed in drylot corrals during the hot summer months. The experiment was a replicated crossover design with four 21-d periods and 2 treatments: 1) shades installed in the front half of the pen or 2) sprinklers, which applied water to the pen surface at 2-h intervals from 1100 to 1900 h. Animal performance measures were dry matter intake, average daily gain, and feed efficiency (gain:feed). Behavioral measures, elimination patterns, and corral spatial distribution were measured in 5-min scan frequencies over four 24-h periods. Physiological measures were rectal temperature, respiration rate, urinary urea N, and blood urea N. Environmental measures were corral soil surface temperature and moisture, particulate matter, and surface NH(3) volatilization; meteorological measures were also collected. Shaded compared with sprinkled heifers had increased dry matter intake (3.4%), increased average daily gain (14%), and increased feed efficiency (11%). Heifers in shaded vs. sprinkler treatments had decreased respiration rates (13%). Behavioral differences between the treatments varied by time of day. Heifers spent most time in either the shaded or sprinkled areas of their corrals (65.9 and 64.2%, respectively). Elimination behavior occurred predominantly at the front of the corral in close proximity to the feed bunks and additionally at the water trough in sprinkled corrals. Sprinkler treatment had a 31.7% greater average corral surface moisture than the shaded treatment. Corral surface temperature varied based on areas of surface moisture, shade location, and elimination concentration within the corral. Sprinkled corrals had less particulate matter emissions than shaded (25%), but NH(3) emissions were 46% greater in sprinkler vs. shaded treatment. Overall, the use of shade in heifer corrals improved heifer performance and physiological measures, but sprinkler treatment had less PM [corrected] emissions from corral surfaces under heat stress conditions. Both cooling techniques affected spatial distribution and behaviors of the heifers, which affected pen usage and surface characteristics.

Development and evaluation of empirical equations to interconvert between twelfth-rib fat and kidney, pelvic, and heart fat respective fat weights and to predict initial conditions of fat deposition models for beef cattle.

The Davis growth model (DGM) simulates growth and body composition of beef cattle and predicts development of 4 fat depots. Model development and evaluation require quantitative data on fat weights, but sometimes it is necessary to use carcass data that are more commonly reported. Regression equations were developed based on published data to interconvert between carcass characteristics and kilograms of fat in various depots and to predict the initial conditions for the DGM. Equations include those evaluating the relationship between the following: subcutaneous fat (SUB, kg) and 12th-rib fat thickness (mm); visceral fat (VIS, kg) and KPH (kg); DNA (g) in intermuscular, intramuscular, subcutaneous, and visceral fat depots and empty body weight; and contributions of fat (kg) in intramuscular (INTRA), SUB, and VIS fat depots and total body fat (kg). The intermuscular fat (INTER, kg) contribution was found by difference. The linear regression equations were as follows: SUB vs. 12th-rib fat thickness (n = 75; P < 0.01) with R(2) = 0.88 and SE = 10.00; VIS vs. KPH (kg; n = 78; P < 0.01) with R(2) = 0.95 and SE = 2.82; the DNA (g) equations for INTER, INTRA, SUB, and VIS fat depots vs. empty body weight (n = 6, 5, 6, and 6; P = 0.08, P < 0.01, P < 0.01, and P = 0.05) with R(2) = 0.57, 0.93, 0.93, and 0.66, and SE = 0.03, 0.003, 0.02, and 0.03, respectively; and initial contribution of INTRA, SUB, and VIS fat depots vs. total body fat (n = 23; P < 0.01) for each depot, with R(2) = 0.97, 0.99, and 0.97, and SE = 0.61, 0.93, and 1.41, respectively. All empirical equations except for DNA were challenged with independent data sets (n = 12 and 10 for SUB and VIS equations and n = 9 for the initial INTER, INTRA, SUB, and VIS fat depots). The mean biases were -2.21 (P = 0.12) and 2.11 (P < 0.01) kg for the SUB and VIS equations, respectively, and 0.05 (P = 0.97), -0.37 (P = 0.27), 1.82 (P = 0.08), and -1.50 (P = 0.06) kg for the initial contributions of INTER, INTRA, SUB, and VIS fat depots, respectively. The random components of the mean square error of prediction were 73 and 26% for the SUB and VIS equations, respectively, and similarly were 99, 85, 62, and 61% for the initial contributions of INTER, INTRA, SUB, and VIS fat depots, respectively. Both the SUB and VIS equations predicted accurately within the bounds of experimental error. The equations to predict initial fat contribution (kg) were considered adequate for initializing the fat depot differential equations for the DGM and other beef cattle simulation models.

Prediction of ammonia emission from dairy cattle manure based on milk urea nitrogen: relation of milk urea nitrogen to urine urea nitrogen excretion.

The objectives of this study were to assess the relationship between urinary urea N (UUN) excretion (g/d) and milk urea N (MUN; mg/dL) and to test whether the relationship was affected by stage of lactation and the dietary crude protein (CP) content. Twelve lactating multiparous Holstein cows were randomly selected and blocked into 3 groups of 4 cows intended to represent early [123 +/- 26 d in milk (DIM); mean +/- standard deviation], mid (175 +/- 3 DIM), and late (221 +/- 12 DIM) lactation stages. Cows within each stage of lactation were randomly assigned to a treatment sequence within a split-plot Latin square balanced for carryover effects. Stage of lactation formed the main plots (squares) and dietary CP levels (15, 17, 19, and 21% of diet dry matter) formed the subplots. Graded amounts of urea were added to the basal total mixed ration to linearly increase dietary CP content while maintaining similar concentrations of all other nutrients among treatments. The experimental periods lasted 7 d, with d 1 to 6 used for adjustment to diets and d 7 used for total collection of urine as well as milk and blood sample collection. Dry matter intake and yields of milk, fat, protein, and lactose declined progressively with lactation stage and were unaffected by dietary CP content. Milk and plasma urea-N as well as UUN concentration and excretion increased in response to dietary CP content. Milk and urine urea-N concentration rose at increasing and decreasing rates, respectively, as a function of plasma urea-N. The renal urea-N clearance rate differed among lactation stages and dietary CP contents. The relationship between UUN excretion and MUN differed among lactation stages and diverged from linearity for cows in early and late lactation. However, these differences were restricted to very high MUN concentrations. Milk urea N may be a useful tool to predict the UUN excretion and ultimately NH(3) emission from dairy cattle manure.