Understanding the effect of sex on energy requirements of hair sheep.

Differences and/or similarities in the influence of sex class for hair sheep requirements remain inconclusive. Knowledge of energy requirements allows well-formulated diets to be provided which is crucial for improving animal production. We aimed to determine the effect of sex class on the net energy requirements of growing hair sheep in a multi-study approach. We used a data set composed of individual measurements of 382 hair sheep (299 non-castrated and 83 castrated males) from 11 studies that used the methodology of comparative slaughter. Net energy requirements for maintenance (NEm) were obtained by the regression between heat production and metabolizable energy intake. The metabolizable energy requirements for maintenance (MEm) were calculated by the iterative method, and the efficiency of use of metabolizable energy for maintenance (km) was obtained by NEm divided by MEm. The net energy requirements for gain (NEg) were estimated from retained energy (RE) against empty BW gain (EBWG). The efficiency of energy use for weight gain (kg) was obtained from the relationship between RE and the energy metabolizable intake for gain, removing the intercept. There was an effect of sex on NEg and two equations were generated: NEg (MJ/day) = 1.040 (±0.04055) × EBW0.75 × EBWG0.8767(±0.03293) and NEg (MJ/day) = 1.040 (±0.04055) × EBW0.75 × EBWG0.8300(±0.03468) (R2 = 0.86; MSE = 0.0037; AIC = -468.0) for non-castrated and castrated males, respectively. Sex class did not affect kg (P > 0.05) and one kg was generated (0.29). Sex did not affect kprotein (P = 0.14) and kfat (P = 0.32), assuming an average deposition efficiency of 0.27 for protein and 0.78 for fat. The NEm and MEm did not differ (P > 0.05) between sex classes, with a value of 0.272 and 0.427 MJ/kg0.75 EBW per day, respectively. The km observed was 0.64. In conclusion, non-castrated and castrated male hair sheep have similar maintenance energy requirements although energy requirements for gain differed among them. The Committees overestimate the gain and maintenance requirements for hair sheep. Therefore, the equations generated in this study are recommended.

Protein requirements for pregnant dairy cows.

We aimed to estimate the protein requirements of pregnant Holstein × Gyr cows. A total of 61 Holstein × Gyr (HG) cows were used, with an average initial body weight (BW) of 480 ± 10.1 kg and age 5 ± 0.5 yr. Cows were divided into 3 groups: pregnant (n = 43), nonpregnant (n = 12), and baseline (n = 6). Baseline animals were slaughtered before starting the experiment to estimate the initial body composition of the remaining animals. Pregnant and nonpregnant cows received 2 diets: maintenance and ad libitum. Pregnant cows were slaughtered at 139, 199, 241, and 268 gestation days (GD). First, we used data only from nonpregnant cows to determine the requirements for maintenance and growth in adult cows. The requirements of metabolizable protein for maintenance (MPm; grams of empty metabolic BW [EBW0.75] per day) were estimated using a linear regression between the metabolizable protein intake (MPI, g/d) and average daily gain (g/d), and the MPm was defined as the intercept divided by the average metabolic BW. Net protein requirements for gain (NPg; g/d) were estimated by the first derivative of the allometric equation between final crude protein in the body (kg) and the final empty BW (EBW; kg). The efficiency of use of metabolizable protein for gain (k) was calculated from the regression between the retained protein (g EBW0.75/d) and the MPI (g EBW0.75/d), and k was the slope of this regression. The MPI was estimated by combining microbial protein synthesis (purine derivatives) with the digestible rumen undegradable protein [(total protein intake - rumen-degradable protein) × intestinal digestibility]. Second, an exponential model was used to fit the protein accumulation in the gestational components in the function of GD. The first derivative of that model was considered the net requirement for gestation (NPgest). The efficiency of protein utilization for gestation (kgest) was calculated by the iterative method using the equation Δ = MPI - (MPm + NPg/kg + NPgest/kgest), where kg is efficiency of protein utilization for gain. The iteration was performed aiming at a zero deviation between observed MPI and metabolizable protein (MP) estimated by the requirements determined herein. We obtained a value of 3.88 g EBW0.75/d for MPm. The estimation of NPg can be calculated according to the following equation: NPg = 0.716 × (EBWopen-0.308) × EBGc, where EBWopen is the EBW (kg) for nonpregnant animals and EBGc is the empty body gain (kg/d) corrected for the gestational component. The k was determined as 0.347. The NPgest requirements were determined as NPgest (g/d) = 0.0008722 × exp(0.01784 × GD) × (calf weight/35). The kgest was 0.625. It is important to highlight that different methods of MP estimates should not be mixed and that the proposed method requires the estimation of microbial protein (estimated via urinary estimates), which might limit practical application. In conclusion, new studies should be conducted to validate our results and the methodology adopted to determine protein requirements for pregnancy in dairy cows. Due to the pattern of protein accumulation in the gestational components, we suggest an exponential model to describe protein requirements for pregnancy for dairy cows.

Expression of enzymes involved in the urea cycle and muscle and mammary gland development of Holstein × Gyr heifers in a rotational grazing system supplemented with increasing protein levels.

Studies evaluating the crude protein (CP) supplementation strategies across the year for grazing cattle and its association with the enzymes involved in the urea cycle and muscle and mammary gland developments are scarce. Thus, we aimed to evaluate the effect of supplementation with different levels of CP on the expression of genes involved in the urea cycle and muscle and mammary gland development of Holstein × Gyr crossbreed heifers grazing intensively managed Brachiaria decumbens throughout the year. Thirty-eight heifers with average initial BW of 172.5 ± 11.15 kg (mean ± SE) and 8.2 ± 0.54 mo of age were randomly assigned to 1 of 4 treatments: 3 protein supplements (SUP) fed at 5g/kg of body weight, plus a control group (CON, non-supplemented animals). The supplement CP levels evaluated were: 12, 24, and 36%. The study was divided into 4 seasons: rainy, dry, rainy-dry transition (RDT), and dry-rainy transition (DRT). On the penultimate day of each season, ultrasound images of the carcass and mammary gland were taken. Five animals from each treatment were randomly chosen on the last day of each season, and liver and muscle tissue biopsies were performed. The target genes were the mammalian target of rapamycin (mTOR) and adenosine monophosphate-activated protein kinase (AMPK) in the muscle samples. Carbamoyl phosphate synthetase (CPS), ornithine transcarbamylase (OTC), argininosuccinate synthetase (ASS), arginosuccinate lyase (ASL), and arginase (ARG) were evaluated in the liver samples. Data were analyzed using PROC GLIMMIX of the SAS with repeated measures. We observed a greater rib eye area (cm2) and fat thickness (mm) in SUP animals than in non-supplemented animals. However, we did not observe differences among SUP levels for both variables. No effects of supplementation were detected on mammary gland development. Nevertheless, seasonal effects were observed, where the RDT and dry season had the most and least accumulated fat in the mammary gland. In muscle, we observed greater expression of AMPK in non-supplemented animals than SUP animals. On the other hand, no differences were observed in gene expression between SUP and non-supplemented animals and among SUP animals for mTOR. Season affected both AMPK and mTOR; heifers had a greater AMPK gene expression on rainy than RDT. For mTOR, we observed greater gene expression in RDT and DRT than in rainy. No differences were observed among RDT, dry, and DRT, and between dry and rainy seasons for mTOR. We observed greater CPS, ASL, and ARG gene expression in SUP animals than in non-supplemented animals. Among SUP animals, supplement CP linearly affected CPS. In conclusion, the supplementation strategy did not affect mammary gland development and mTOR expression in muscle tissue. However, we observed a seasonal effect on mammary gland development and AMPK and mTOR expression. The CP supplementation increased the rib eye area and fat thickness, directly affecting AMPK expression in the muscle. Moreover, the CP supplementation increased urea cycle enzyme expression, indicating greater urea production in the liver.

Implications of supplementing mid-lactation multiparous Holstein cows fed high by-product low-forage diets with rumen-protected methionine and lysine in a commercial dairy.

Supplementation of rumen-protected amino acids may improve dairy cow performance but few studies have evaluated the implications of supplementing low-forage diets. Our objective was to evaluate the effects of supplementing rumen-protected methionine (Met) and lysine (Lys) on milk production and composition as well as on mammary gland health of mid-lactating Holstein cows from a commercial dairy farm feeding a high by-product low-forage diet. A total of 314 multiparous cows were randomly assigned to control (CON; 107 g of dry distillers' grains) or rumen-protected Met and Lys (RPML; 107 g dry distillers' grains + 107 g of RPML). All study cows were grouped in a single dry-lot pen and fed the same total mixed ration diet twice a day for a total of 7 weeks. Treatments were top-dressed on the total mix ration immediately after morning delivery with 107 g of dry distillers' grains for 1 week (adaptation period) and then with CON and RPML treatments for 6 weeks. Blood samples were taken from a subset of 22 cows per treatment to determine plasma AA (d 0 and 14) and plasma urea nitrogen and minerals (d 0, 14, and 42). Milk yield and clinical mastitis cases were recorded daily, and milk components were determined bi-weekly. Body condition score change was evaluated from d 0 to 42 of the study. Milk yield and components were analyzed by multiple linear regression. Treatment effects were evaluated at the cow level considering parity and milk yield and composition taken at baseline as a covariate in the models. Clinical mastitis risk was assessed by Poisson regression. Plasma Met increased (26.9 vs 36.0 µmol/L), Lys tended to increase (102.5 vs 121.1 µmol/L), and Ca increased (2.39 vs 2.46 mmol/L) with RPML supplementation. Cows supplemented with RPML had higher milk yield (45.4 vs 46.0 kg/d) and a lower risk of clinical mastitis (risk ratio = 0.39; 95% CI = 0.17-0.90) compared to CON cows. Milk components yield and concentrations, somatic cell count, body condition score change, plasma urea nitrogen, and plasma minerals other than Ca were not affected by RPML supplementation. Results suggest that RPML supplementation increases milk yield and decreases the risk of clinical mastitis in mid-lactation cows fed a high by-product low-forage diet. Further studies are needed to clarify the biological mechanisms for mammary gland responses to RPML supplementation.

Intake, performance, and feeding behavior of Holstein and Holstein × Gyr heifers grazing intensively managed tropical grasses during the rainy season.

Holstein × Gyr and Holstein are the primary dairy breeds used in tropical systems, but when rearing under pasture, feed intake, behavior, and performance might differ between them. This study aimed to evaluate the voluntary intake, nutrient digestibility, performance, and ingestive behavior of Holstein and Holstein × Gyr (½ Holstein × ½ Gyr) heifers managed in a rotational system of Guinea grass (Panicum maximum Jacq. cv. Mombaça). The experiment was conducted during the summer season throughout four periods of 21 d. Two 8-heifers (four Holstein and four Holstein × Gyr) groups, averaging 258.6 ±â€¯24.79 kg and 157.1 ±â€¯24.99 kg BW, were used. Each group grazed a separate set of 16 paddocks, and all heifers received a concentrate supplement daily. Heifers were weighed at the beginning and end of the experiment. Fecal, forage and concentrate samples were evaluated for their DM, CP, crude fat, ash, NDF, and indigestible NDF. Feeding behavior was evaluated through 24 h of live observation for 48 h of each experimental period. Grazing, ruminating, resting, and intake of concentrate times were recorded, and rumination criteria, bout criteria, mealtime, meal frequency, and meal duration were calculated. There was no difference in total dry matter intake (DMI), but forage DMI of Holstein × Gyr was 11.70 % greater than the Holstein heifers. The Holstein × Gyr heifers had greater NDF intake and feed efficiency tended to show greater CP and NDF digestibilities, consequently, they had greater average daily gain (ADG). Holstein grazed less than Holstein × Gyr heifers in the afternoon. Ruminating time was 18.43 % lower for Holstein than Holstein × Gyr heifers, and rumination criteria (i.e. longest non-feeding interval within a rumination event) were greater for Holstein heifers. Holstein heifers presented more prolonged rumination bouts and resting time than Holstein × Gyr heifers. Holstein × Gyr can ingest and ruminate greater amounts of fibrous material, and Holstein heifers needed to spend more time ruminating the cud. Overall, even though the behavior was not markedly different between breeds, rearing young Holstein heifers in tropical pasture conditions is less suitable than Holstein-Gyr because of their lower ADG. Therefore, this management condition seems appropriate for Holstein × Gyr but inappropriate for Holstein dairy heifers.

Association of housing and management practices with milk yield, milk composition, and fatty acid profile, predicted using Fourier transform mid-infrared spectroscopy, in farms with automated milking systems.

Milk fatty acid (FA) profile can be divided into (1) de novo (C4-C14) that are synthesized in the mammary gland; (2) preformed (≥C18) that are absorbed from blood and originate from mobilized adipose tissues or dietary fat; and (3) mixed (C16), which have both origins. Our objectives were to describe the FA profile, as predicted using Fourier transform mid-infrared spectroscopy, of bulk tank milk from automated milking system (AMS) farms and to assess the association of management and housing factors with the bulk tank milk composition and FA profile of those AMS farms. The data used were collected from 124 commercial Canadian Holstein dairy farms with AMS, located in the provinces of Ontario (n = 68) and Quebec (n = 56). The farms were visited once from April to September 2019, and information were collected on barn design and herd management practices. Information regarding individual cow milk yield (kg/d), days in milk, parity, and the number of milking cows were automatically collected by the AMS units on each farm. These data were extracted for the entire period that the bulk tank milk samples were monitored, from April 2019 to April 2020 in Quebec and from August 2019 to May 2020 in Ontario. Across herds, milk yield averaged (mean ± standard error) 35.9 ± 0.4 kg/d, with 3.97 ± 0.01% fat and 3.09 ± 0.01% protein, whereas FA profile averaged 26.2 ± 0.1, 33.1 ± 0.1, and 40.7 ± 0.2 g/100 g of FA for de novo, mixed, and preformed, respectively. The FA yield averaged 0.34 ± 0.01, 0.44 ± 0.01, and 0.54 ± 0.01 kg/d for de novo, mixed, and preformed, respectively. Multivariable regression models were used to associate herd-level housing factors and management practices with milk production, composition, and FA profile. Milk yield was positively associated with using a robot feed pusher (+2.1 kg/d) and the use of deep bedding (+2.6 kg/d). The use of a robot feed pusher, deep bedding, and greater stall raking frequency were positively associated with greater yield (kg/d) of de novo, mixed, preformed, and de novo + mixed FA. Use of deep bedding was negatively associated with concentration of fat, de novo FA, mixed FA, and de novo + mixed FA, expressed in grams per 100 g (%) of milk. A wider lying alley width (≥305 cm) was associated with a greater concentration (g/100 g of milk) of de novo and de novo + mixed FA. Greater frequency of partial mixed ration delivery (>2×/d vs. 1 and 2×/d) was positively associated with a greater proportion (g/100 g of FA) of de novo, mixed, and de novo + mixed FA and negatively associated with the proportion of preformed FA. Overall, these associations indicated that bulk tank FA profile can be used as a tool to monitor and adjust management and housing in AMS farms.

Production costs, economic viability, and risks associated with compost bedded pack, freestall, and drylot systems in dairy farms.

The adoption of intensive production systems, such as compost bedded pack (CB) and freestall (FS), has increased recently in tropical regions, mainly replacing the drylot system (DL). Thus, our objectives were to compare production costs, economic outcomes, and risk of dairy operations in CB, FS, and DL systems. We collected data from 2 181 Brazilian farms over 120 consecutive months; 960 farms (144 CB, 133 FS, and 683 DL) met our selection criteria. All costs were modeled for two animal production categories: milking cows and non-milking animals. We used a regression model that included linear and quadratic parameters, and we added the production system as a fixed variable for all parameters tested with this model. Consultant, year, herd, and herd × system interaction were included in the model as random variables. Further, we simulated annual technical and economic indexes per farm. In addition, we developed a risk analysis to measure the probability of negative profit of the farms based on a 14-year historical series of milk prices. All production costs were affected by the system. Feed, medicine, sundry, and labor costs per farm per year were greater in DL farms when milk yield (MY) was greater than 3 500 L/day. The variables such as milk yield, assets per liter, asset turnover rate, return on assets, operational profit, profit per cow, and per liter of milk variables were greater in CB and FS with high MY (>3 000 L/day). Nonetheless, DL had the greatest economic indexes with a lower MY (<3 000 L/day), lower operating costs, and greater economic outcomes. The risk analysis indicated that the probability of negative profit (risk) was reduced for CB and FS as MY increased, but DL had the lowest risk with low MY levels. In conclusion, we suggest DL as the most attractive system for farms with MY between 150 and 3 000 L of milk/day as the DL had the lowest risk and the greatest profit in this production scale. Despite similar outcomes for CB and FS in most of the farms, the profit per cow ($/year), assets turnover rate (%), risk (%) and expected profit ($/L) analysis indicated that CB could be recommended for farms with MY greater than 3 200 L of milk/day, whereas based on risk (%) and expected profit ($/L), FS would be the most profitable system in dairies producing more than 8 000 L of milk/day per farm.

Associations between dry period length and time to culling and pregnancy in the subsequent lactation.

The association between dry period length (DPL) and time to culling and pregnancy in the subsequent lactation may be important for the economically optimal length of the dry period. Therefore, this study aimed to (1) quantify the association between DPL and hazard of culling and pregnancy in the subsequent lactation; (2) develop continuous functions of DPL for the hazard ratios of culling and pregnancy; and (3) investigate the effect of a cause-specific hazards model and a subdistribution model to analyze competing events. The data used in this observational cohort study were from dairy herd improvement milk test lactation records from 40 states in the United States. After edits, there remained 1,108,515 records from 6,730 herds with the last days dry in 2014 or 2015. The records from 2 adjacent lactations (current, subsequent) were concatenated with the DPL of interest, 21 to 100 d, in between both lactations. We defined 8 DPL categories of 10 d each. Kaplan-Meier survival curves were used to show associations between DPL and time to culling or pregnancy for 3 lactation groups: lactation 1 and 2, lactation 2 and 3, and lactation 3 and greater. To control for confounding factors in Cox proportional models, we included 6 current lactation covariates and 3 time-dependent variables in the survival models. Hazard ratios of culling were estimated for 4 days in milk (DIM) categories from 1 to 450 DIM. Hazard ratios of pregnancy were estimated for 3 DIM categories from 61 to 300 DIM. Competing risk analysis of 8 disposal codes (i.e., farmer reported reasons) for culling and the culling event for pregnancy were conducted by a cause-specific hazards model and a subdistribution model. Hazard ratios were also estimated as quadratic polynomials of DPL. Compared with the reference DPL category of 51 to 60 d, hazard ratios of culling and pregnancy of the other 7 DPL categories ranged between 0.70 and 1.49, and 0.93 and 1.15, respectively. Short DPL were associated with lower risk of culling in the early lactation but not over the entire lactation. Short DPL were associated with greater hazard of pregnancy. Trends in hazard ratios over the ranges of the 8 DPL categories were not always consistent. Competing risk analysis with both models provided little differences in hazard ratios of culling and pregnancy. In conclusion, variations in DPL were associated with meaningful differences in the hazard ratios for culling and pregnancy and minor differences in the relative frequency of disposal codes. Subdistribution hazards models produced hazard ratios similar to cause-specific hazard models. The quadratic polynomials may be useful for decision support on customization of DPL for individual cows.

Economic analysis of the use of in vitro produced embryos transferred during heat stress under dairy herd constraints.

The use of embryo transfer helps to improve reproductive performance during periods of heat stress. In vitro produced embryo transfer (IVP-ET) is more expensive than artificial insemination. We hypothesized that the value IVP-ET in seasonal herds depends on herd constraints, such as the maximum number of milking cows and the maximum number of calvings that can be accommodated throughout the year. Therefore, the objective of this study was to estimate how profitability in dairy herds exposed to summer heat stress is affected by the number of months in which IVP-ET is used, the use of IVP-ET in repeat-breeder cows, IVP-ET cost, and herd constraints. We built and used a nonlinear programming model of a dairy herd with young stock and cows with monthly Markov Chain transitions. The model varied the number of heifers calving in each calendar month to maximize herd profitability. We varied IVP-ET cost ($100 or $200), duration of the IVP-ET program (2 or 4 months), and the breeding number in which IVP-ET started (1st or 3rd). In total, 20 scenarios were simulated. Maximum profitability was obtained when IVP-ET was not used, regardless of herd constraints. The 16 scenarios in which IVP-ET was used showed increased seasonality in milk yield, numbers of milking cows, total cows, total calvings, and heifer calvings because the program tried to limit the number of IVP-ET breedings in the summer. The addition of the calving constraint increased the value of IVP-ET. The breakeven cost per IVP-ET ranged from -$6.79 to $24.38 compared with conventional semen cost of $20. In conclusion, the current market costs of IVP-ET did not warrant application with the objective to increase reproductive performance during heat stress. Herd constraints on the maximum allowable seasonality in the monthly number of milking cows and calvings affected the value of IVP-ET during heat stress.

Development of equations to predict carcass weight, empty body gain, and retained energy of Zebu beef cattle.

The accurate supply of energy is essential to optimize livestock productivity and profitability. Furthermore, replacing empty BW gain (EBG) with carcass gain (CG) might be a suitable alternative to estimate the retained energy (RE) of beef cattle. Thus, this multi-analysis study was conducted aiming to estimate and validate new equations to predict carcass weight (CW), EBG, and RE of Zebu, beef crossbred, and dairy crossbred. A database composed by 1112 animals encompassing bulls, steers, heifers of different genetic groups (Zebu, beef crossbred, and dairy crossbred), and two types of slaughter plants (commercial and experimental) was used for generating the new CW equation. For the development of the EBG and RE equations, a database of 636 observations composed of bulls, steers, and heifers of different genetic groups (Zebu, beef crossbred, and dairy crossbred) was assembled. The validation of new equations was performed using independent databases composed by 137 observations (80 for CW and 57 for EBG and RE). The new approaches for EBG and RE validation also included data from our research group studies (Inside) and independent data from literature publications (Outside). Furthermore, the new RE equation was compared to the current model devised by the nutritional requirements, diet formulation, and performance prediction of Zebu and crossbred cattle (BR-CORTE, 2016). Validation analyses were performed by using the Model Evaluation System (MES; 3.1.13, College Station, US). The CW was accurately estimated by the new equation when using both commercial and experimental data. Also, the equations developed in this study accurately estimated EBG and RE using both inside and outside data. In conclusion, equations proposed in this study accurately and precisely estimated CW, EBG, and RE of Zebu beef cattle that composed validation data set. Therefore, we suggest the following equations to estimate CW, EBG, and RE of Zebu cattle: CW, kg = -11.0±1.56 + P + ((0.609±0.005 + G + B) × SBW); EBG (kg) = 0.044±0.017 + 1.47±0.026 × CG; RE (MJ/d) = 4.184 × (0.082±0.002 × EQEBW0.75 × CG0.777±0.039), where P = slaughter plant effect, if commercial = -10.98, if experimental =0; G = gender effect, if steer = 0, if bull = 0.008169 and if heifer = -0.00612; B = genotype effect, if Zebu = 0, if dairy crossbreds = -0.03301 and if beef crossbreds = -0.01595; SBW = shrunk BW; CG = carcass gain; EQEBW = equivalent empty BW.

Short communication: Development and evaluation of equations to predict growth of Holstein dairy heifers in a tropical climate.

The objective of this study was to develop and validate equations for estimating growth of dairy heifers using measures of withers height, body weight (BW), and age. Measures of BW and withers height of 207 Holstein heifers raised in a tropical climate were taken from birth to calving, totaling to 2,047 observations. To be included in the database, the heifer had to have at least 4 measures recorded. After that, 4 models were built and evaluated as follows: (1) a linear model of BW as function of age (BW~A), (2) a linear model of the BW-to-height ratio as function of age (BW:H~A), (3) a quadratic model, adjusted for a defined plateau, to describe height as function of age (H~A), and (4) an exponential growth model of BW as function of height (BW~H). A cross-validation procedure was performed to evaluate accuracy and precision of the models. The linear relationship of BW~A and BW:H~A were estimated, respectively, by the equations: BW = 42.65 + 0.62 × A and BW:H = 0.70 + 0.0041 × A, where BW is in kilograms, BW:H = BW-to-height ratio (kg/cm), and A = age (d). Using the quadratic plateau for the model H~A, a critical "x" value of ~806 d and a height plateau of 138.6 cm were identified. Therefore, the following equations for estimating the height of animals younger and older than 806 d, respectively, were developed: H = 78.15 + 0.150 × A - 0.00009 × A2 and H = 78.15 + 0.150 × cvx - 0.00009 × cvx2, where H = height (cm) and cvx = 806 (critical "x" value; given in days). Additionally, the exponential model of W~H was estimated by the following equation: BW = 4.25 × exp(0.034 ×H), where BW is in kilograms and H = height (cm). A cross validation demonstrated that all equations had very high accuracy and precision. Overall, these models demonstrated that BW and BW-to-height ratio increase linearly as a function of age, while BW follows an exponential growth pattern as a function of height. Additionally, the H~A model predicted that heifers achieve a maximum height of 138.6 cm at 806 d of age.

Piecewise modeling of the associations between dry period length and milk, fat, and protein yield changes in the subsequent lactation.

Our objective was to develop predictive models of 305-d mature-equivalent milk, fat, and protein yields in the subsequent lactation as continuous functions of the number of days dry (DD) in the current lactation. In this retrospective cohort study with field data, we obtained DHIA milk recording lactation records with the last DD in 2014 or 2015. Cows included had DD from 21 to 100 d. After editing, 1,030,141 records from cows in 7,044 herds remained. Three parity groups of adjacent (current, subsequent) lactations were constructed. We conducted all analyses by parity group and yield component. We first applied control models to pre-adjust the yields in the subsequent lactation for potentially confounding effects. Control models included the covariates mature-equivalent yield, days open, somatic cell score at 180 d pregnant, daily yield at 180 d pregnant, and a herd-season random effect, all observed in the current lactation. Days dry was not included. Second, we modeled residuals from control models with smooth piecewise regression models consisting of a simple linear, quadratic, and another simple linear equation depending on DD. Yield deviations were calculated as differences from predicted mature-equivalent yield at 50 DD. For validation, predictions of yield deviations from piecewise models by DD were compared with predictions from local regression for the DHIA field records and yield deviations reported in 38 experimental and field studies found in the literature. Control models reduced the average root mean squared prediction error by approximately 21%. Yield deviations were increasingly more negative for DD shorter than 50 d, indicating lower yields in the subsequent lactation. For short DD, the decrease in 305-d mature-equivalent milk yield ranged from 43 to 53 kg per DD. For mature-equivalent fat and protein yields, decreases were between 1.28 and 1.71 kg per DD, and 1.06 and 1.50 kg per DD, respectively. Yield deviations often were marginally positive and increasing for DD >50, so that the highest yield in the subsequent lactation was predicted for 100 DD. For long DD, the 305-d mature-equivalent milk yield increased at most 4.18 kg per DD. Patterns in deviations for fat and protein yield were similar to those for milk yield deviations. Predictions from piecewise models and local regressions were very similar, which supports the chosen functional form of the piecewise models. Yield deviations from field studies in the literature typically were decreasing when DD were longer, likely because of insufficient control for confounding effects. In conclusion, piecewise models of mature-equivalent milk, fat, and protein yield deviations as continuous functions of DD fit the observed data well and may be useful for decision support on the optimal dry period length for individual cows.

Energy and protein requirements of Holstein × Gyr crossbred heifers.

Nutrient requirements in cattle are dependent on physiological stage, breed and environmental conditions. In Holstein × Gyr crossbred dairy heifers, the lack of data remains a limiting factor for estimating energy and protein requirements. Thus, we aimed to estimate the energy and protein requirements of Holstein × Gyr crossbred heifers raised under tropical conditions. Twenty-two crossbred (½ Holstein × ½ Gyr) heifers with an average initial BW of 102.2 ± 3.4 kg and 3 to 4 months of age were used. To estimate requirements, the comparative slaughter technique was used: four animals were assigned to the reference group, slaughtered at the beginning of the experiment to estimate the initial empty BW (EBW) and composition of the animals that remained in the experiment. The remaining animals were randomized into three treatments based on targeted rates of BW gain: high (1.0 kg/day), low (0.5 kg/day) and close to maintenance (0.1 kg/day). At the end of the experiment, all animals were slaughtered to determine EBW, empty body gain (EBG) and body energy and protein contents. The linear regression parameters were estimated using PROC MIXED of SAS (version 9.4). Estimates of the parameters of non-linear regressions were adjusted through PROC NLIN of SAS using the Gauss-Newton method for parameter fit. The net requirements of energy for maintenance (NEm) and metabolizable energy for maintenance (MEm) were 0.303 and 0.469 MJ/EBW0.75 per day, respectively. The efficiency of use of MEm was 64.5%. The estimated equation to predict the net energy requirement for gain (NEg) was: NEg (MJ/day) = 0.299 × EBW0.75 × EBG0.601. The efficiency of use of ME for gain (kg) was 30.7%. The requirement of metabolizable protein for maintenance was 3.52 g/EBW0.75 per day. The equation to predict net protein requirement for gain (NPg) was: NPg (g/day) = 243.65 × EBW-0.091 × EBG. The efficiency of use of metabolizable protein for gain (k) was 50.8%. We observed noteworthy differences when comparing to ME and protein requirements of Holstein × Gyr crossbred heifers with other systems. In addition, we also observed differences in estimates for NEm, NEg, NPg, kg and k. Therefore, we propose that the equations generated in the present study should be used to estimate energy and protein requirements for Holstein × Gyr crossbred dairy heifers raised in tropical conditions in the post-weaning phase up to 185 kg of BW.

Weight adjustment equation for hair sheep raised in warm conditions.

To estimate the nutritional requirements of hair sheep, knowledge about the animal's weight and its relationships with growth performances is essential. A study was carried with the objective to establish the relationships between BW, fasting BW (FBW), empty BW (EBW), average daily gain (ADG) and empty BW gain (EBWG) for hair sheep in growing and finishing phases in Brazilian conditions. Databases were obtained from 32 studies, for a total of 1145 observations; there were 3 sex classes (non-castrated male, castrated male and female) and 2 feeding systems (pasture and feedlot). The most representative breeds in the database were Santa Ines (n = 473), Morada Nova (n = 70) and Brazilian Somali (n = 47). The other animals in the database were crossbreeds (n = 555). The FBW (kg), EBW and EBWG (kg/day) were estimated according to linear regression. A random coefficient model was adopted, considering the study as a random effect and including the possibility of covariance between the slope and the intercept. The coefficients obtained from the linear regression of the FBW against the BW, EBW against the FBW and EBWG against the ADG did not differ between sex class (P > 0.05) and genotype (P > 0.05). The equations generated to estimate FBW from the BW, EBW from the FBW and EBWG from the ADG are as follows: FBW = -0.5470 (±0.2025) + 0.9313(±0.019) × BW, EBW = -1.4944 (±0.3639) + 0.8816 (±0.018) × FBW and EBWG = 0.906 (±0.019) × ADG, respectively. The low mean squared error values found in the cross-validation confirmed the reliability of these equations. Considering a sheep with a BW of 30 kg and a 100 g ADG, the estimated FBW, EBW and EBWG calculated using the generated equations are 27, 22.65 and 0.090 kg, respectively. In conclusion, the generated equations can be used in growing hair sheep. The validation procedure applied to the generated equations showed that its use for hair sheep seems to be appropriate.

Review: Overview of factors affecting productive lifespan of dairy cows.

The average productive lifespan is approximately 3 to 4 years in countries with high-producing dairy cows. This is much shorter than the natural life expectancy of dairy cattle. Dairy farmers continue to cull cows primarily for reasons related to poor health, failure to conceive or conformation problems prior to culling. These reasons may indicate reduced welfare leading up to culling. Improvements in health care, housing and nutrition will reduce forced culling related to these welfare reasons. However, productive lifespan has remained similar in decades, despite large improvements in cow comfort and genetic selection for the ability to avoid culling. On the other hand, genetic progress for economically important traits is accelerating within the last decade, which should slightly shorten the average economically optimal productive lifespan. A major driver of productive lifespan is the availability of replacement heifers that force cows out when they calve. The average productive lifespan could be extended by reducing the supply of dairy heifers, which would also have benefits for environmental sustainability. Improvements in culling decision support tools would strengthen economically optimal replacement decisions. In conclusion, major factors of the relatively short productive lifespan of dairy cows are welfare-related, but other economic factors like supply of heifers, genetic progress and non-optimal decision-making also play important roles.

Comparison of microbial fermentation data from dual-flow continuous culture system and omasal sampling technique: A meta-analytical approach.

Although the omasal sampling technique (OST) has been successfully used to estimate ruminal fermentation and nutrient flow, alternatives to invasive animal trials should be pursued and evaluated. The objective of this study was to evaluate carbohydrate and N metabolisms using a meta-analytical approach to compare 2 methods: dual-flow continuous culture system (DFCCS) and OST. To be included, studies needed to report diet chemical composition and report at least 1 of the dependent variables of interest. A total of 155 articles were included, in which 97 used the DFCCS and 58 used the OST. The independent variables used were dietary nonfiber carbohydrate concentration, neutral detergent fiber (NDF) degradability, true crude protein (CP) degradability, and efficiency of microbial protein synthesis (EMPS). In addition, 12 dependent variables were used. Statistical analyses were performed using the Mixed procedure of SAS (SAS Institute Inc., Cary, NC). A random coefficients model was used considering study as a random effect and including the possibility of covariance between the slope and the intercept. The effect of method (DFCCS or OST) was included and tested in the estimates of the intercept, linear, and quadratic effects of the independent variable. There was no method effect when NDF degradability was regressed with total volatile fatty acids concentration, true CP degradability, and EMPS. Molar proportions of acetate and propionate were quadratically associated with NDF degradability. When NDF degradability was regressed with acetate and propionate there was a method effect, differing only in the intercept (ß0) estimate. True organic matter digestibility, bacterial N/total N, efficiency of N utilization, total volatile fatty acid concentration, and molar proportion of butyrate linearly increased as dietary nonfiber carbohydrate concentration increased, and none of these variables were affected by method. Concentration of ammonia N had a linear and positive association with true CP degradability. This was the only variable that had a method effect when regressed with true CP degradability, differing only in the estimate of the intercept (ß0). As EMPS increased, efficiency of N utilization also increased, and it was affected by method. Overall, the majority of DFCCS responses were similar to OST. When a method effect was observed, it was mainly on the estimate of the intercept, demonstrating that the magnitude of these responses was different. However, the relationships between independent and dependent variables were similar across methods.

Production, economic viability and risks associated with switching dairy cows from drylots to compost bedded pack systems.

The use of compost bedded pack systems (CBS) has increased over the past 5 years in tropical countries, and studies associating production traits with economical outcomes of this system are warranted. Our objectives were to evaluate productive traits, economic outcomes and the risks of losses of dairy farms that switched from a drylot system (DLS) to a CBS and to compare these with similar farms that did not change their system. We collected data from 18 farms over 36 consecutive months (August 2014 to July 2017). All farms started the study as DLS, and six farms switched to CBS in the second year. The other 12 farms kept their DLS during the 36 months of evaluation. Annual technical and economic indexes per farm were collected and calculated. Additionally, a risk analysis was performed based on a 10-year historical series of milk prices. The results were analysed using a regression model including year and herd as categorical variables (fixed), system and herd size as quantitative variables (fixed), and system × herd as a random variable. Furthermore, a non-metric multidimensional scaling plot was used to evaluate producers' profiles in each year. Milk fat, milk total solids, and somatic cell count did not change when farms switched from DLS to CBS, and averaged 3.80%, 12.04%, and 256 500 cells/ml, respectively. However, milk protein (%) decreased in CBS farms. The majority of milk production variables were not affected. Nevertheless, farms that switched to CBS increased milk production per cow by 13.3% compared with DLS farms. Total operation costs (296 076.83 $/year) were not affected by the system, and neither were the costs of concentrates, roughage, labour or medicines. Net margin per litre (0.09 $/l), operating profit (14.95%), assets per litre (398.68 $/l per day) and return on assets (10.27%) did not change when farms switched from DLS to CBS. Net margin ($/l and $/cow) and asset turnover rate increased in CBS farms. Risk analysis indicated that the risk was reduced by 38% in CBS farms. Furthermore, our analysis showed that producers who switched to CBS had similar technical and economic indexes in the first year before switching their system. In conclusion, this study demonstrates that CBS systems might be promising for producers in tropical countries who are looking for a more productive and less risky system. We did not observe improvements in animal health as previously reported in the literature.

Nitrogen metabolism and protein requirements for maintenance of growing Red Norte bulls.

Dietary protein adjustments can reduce environmental impact and economic losses in production systems. However, we lack information regarding nitrogen (N) metabolism and protein requirements for maintenance of crossbred animals such as Red Norte breed, precluding a precise dietary management. The objective was to evaluate the effect of increasing dietary CP levels (9%, 11%, 13%, 15% and 17%) on intake, digestibility and N balance, as well as to estimate the metabolizable protein requirements for maintenance (MPm) of growing Red Norte bulls. Thirty five animals averaging 280 ± 4.0 kg BW were fed during 45 days in a 60 : 40 forage : concentrate ratio diet in which the last 5 days were used for the digestibility trial. Intakes of CP and non-fibrous carbohydrates (NFCs) and feed efficiency linearly increased (P < 0.05) as CP levels increased, while DM, NDF, nitrogen efficiency use and ether extract were not influenced by CP levels (P > 0.05). Digestibilities of DM, organic matter, ether extract, NFC and CP as well as metabolizable energy intake linearly increased (P < 0.05), and true digestibility of CP was not affected (P > 0.05) by treatments. Urinary N and retained N linearly increased (P < 0.05) with the increase in dietary N. The MPm were estimated as 4.46 g/BW0.75 and the efficiency of use of MPm was 0.673. In conclusion, obtained MPm requirements of growing Red Norte bulls are greater than the values reported in literature for Zebu cattle and dietary CP levels of 15% and 17% exhibited great responses for growing Red Norte cattle. However, a cost-benefit evaluation should be done before its use.

Meta-analysis of spineless cactus feeding to meat lambs: performance and development of mathematical models to predict dry matter intake and average daily gain.

Spineless cactus is a useful feed for various animal species in arid and semiarid regions due to its adaptability to dry and harsh soil, high efficiency of water use and carbohydrates storage. This meta-analysis was carried out to assess the effect of spineless cactus on animal performance, and develop and evaluate equations to predict dry matter intake (DMI) and average daily gain (ADG) in meat lambs. Equations for predicting DMI and ADG as a function of animal and diet characteristics were developed using data from eight experiments. The dataset was comprised of 40 treatment means from 289 meat lambs, in which cactus was included from 0 to 75% of the diet dry matter (DM). Accuracy and precision were evaluated by cross-validation using the mean square error of prediction (MSEP), which was decomposed into mean bias, systematic bias and random error; concordance correlation coefficient, which was decomposed into accuracy (Cb) and precision (ρ); and coefficient of determination (R2). In addition, the data set was used to evaluate the predicting accuracy and precision of the main lamb feeding systems (Agricultural and Food Research Council, Small Ruminant Nutritional System, National Research Council and Institut National de la Recherche Agronomique) and also two Brazilian studies. The DMI, CP intake (CPI), metabolizable energy (ME) intake and ADG increased when cactus was included up to 499 g/kg DM (P<0.001). In contrast, animals fed high levels of cactus (>500 g/kg DM) had a decreased DMI, CPI and NDF intake, but increased feed efficiency (P<0.001) and similar ADG compared with those without cactus addition. The DMI was positively correlated with initial BW, final BW, concentrate and ADG, while it was negatively correlated with cactus inclusion and ME of the diet. On other hand, ADG was positively correlated with DMI, initial and mean BW and concentrate, and it was negatively correlated with cactus inclusion. The two developed equations had high accuracy (Cb of 0.95 for DMI and 0.94 for ADG) and the random error of MSEP was 99% for both equations. The precision of both equations was moderate, with R2 values of 0.53 and 0.50 and ρ values of 0.73 and 0.71 for DMI and ADG, respectively. In conclusion, the developed equation to predict DMI had moderate precision and high accuracy, nonetheless, it was more efficient than those reported in the literature. The proposed equations can be a useful alternative to estimate intake and performance of lambs fed cactus.

Determination of macromineral requirements for preweaned dairy calves in tropical conditions.

International committees that have published nutrient requirements for dairy cattle have used data from mineral studies conducted in the 1920s to 1970s, and no study has reported data from animals less than 100 kg; therefore, there is a need to update mineral requirements for preweaned dairy calves. Thus, a meta-analysis was performed to estimate the mineral requirements of Ca, P, K, Mg, and Na for Holstein and Holstein × Gyr crossbred preweaned dairy calves using data from 5 studies developed at the Universidade Federal de Viçosa (Viçosa, MG, Brazil). A total of 210 calves were separated into 2 breeds: purebred Holstein calves (animals with a Holstein pedigree higher than 87.5%) and Holstein × Gyr crossbred calves (animals with a Holstein pedigree lower than 87.5%). The comparative slaughter technique was used to estimate animal body composition and empty body weight (EBW). Mineral requirements for maintenance were estimated by the regression between retained mineral and mineral intake, whereas mineral requirements for gain were obtained from the first derivative of the mineral content in the animal's body. In addition, breed effect was tested on the intercept and slope of the models. The effect of breed was not observed for all analyzed variables. Thus, net requirements for maintenance were 12.73, 11.81, 20.28, 3.50, and 6.37 mg/kg of EBW per day for Ca, P, K, Mg, and Na, respectively. Retention coefficients were 73.18, 65.20, 13.16, 29.55, and 24.28% for Ca, P, K, Mg, and Na, respectively. The following equations were determined to estimate net requirements for gain (NRG, g/d): NRG for Ca = 14.402 × EBW-0.139 × empty body gain (EBG); NRG for P = 5.849 × EBW-0.027 × EBG; NRG for K = 1.140 × EBW-0.048 × EBG; NRG for Mg = 0.603 × EBW-0.036 × EBG; and NRG for Na = 1.508 × EBW-0.045 × EBG. Due to the high variation between the data found in this study and in the available literature, we suggest that further studies should be conducted to evaluate the estimates of this study.