RESUMEN
Heat stress (HS) during the dry period can affect animal welfare, health, dry matter intake (DMI), and milk production in the subsequent lactation, which will negatively affect the profitability of dairy farms. In this study, the objective was to model the changes in DMI in pregnant nonlactating heat-stressed dairy cows with or without access to evaporative cooling systems. A database was built, composed of individual DMI records from 244 pregnant nonlactating dairy cows from an average -29.3 d (range: -42 to -21 d; SD: ±7.54 d) to -1 d relative to calving (DRC) and housed in environmental conditions in which temperature-humidity index (THI) ranged from 58.4 to 83.3, with or without access to evaporative cooling systems. Generalized additive mixed-effects models were used to describe the relationships of DMI with HS and DRC. Changes in DMI with the increase in THI and the progression of pregnancy in cows with or without evaporative cooling systems were estimated using differential equations. On average, cows housed in barns without evaporative cooling systems had a reduction in DMI of 1.30 kg/d and increased rectal temperature in 0.22°C in relation to those housed in barns with evaporative cooling systems. Dry matter intake decreased as THI increased, but the reduction was greater for noncooled cows as THI values increased. In addition, regardless of the THI, DMI started to decrease at -14 DRC for cooled cows, whereas for noncooled cows it already started at -30 DRC, relative to the previous days evaluated. The intensity of the reduction was lesser for cows that had access to evaporative cooling systems or were in the dry period in May to June as compared with those that were in the dry period in July to August or September to October. The models generated in this study, which include environmental variables, should lead to more accurate predictions of DMI during HS that can be used to formulate diets to meet the needs of the late pregnant cow because it is possible to predict changes in DMI as the heat load and DRC change. Such models are also expected to help dairy nutritionists to decide when and how to apply the dietary strategies available to attenuate the reductions in DMI with the intensity of HS and progression of pregnancy.
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Calor , Leche , Embarazo , Femenino , Bovinos , Animales , Lactancia , Ingestión de Alimentos , Respuesta al Choque Térmico , Dieta/veterinariaRESUMEN
Some cellulolytic bacteria require 1 or more branched-chain volatile fatty acids (BCVFA) for the synthesis of branched-chain AA and branched-chain long-chain fatty acids because they are not able to uptake branched-chain AA or lack 1 or more enzymes to synthesize branched-chain AA de novo. Supplemental BCVFA and valerate were included previously as a feed additive that was later removed from the market; these older studies and more current studies have noted improvements in neutral detergent fiber digestibility and milk efficiency. However, most studies provided a single BCVFA or else isobutyrate (IB), 2-methylbutyrate (MB), isovalerate, and valerate altogether without exploring optimal combinations. Our objective was to determine a combination of isoacids that is optimal for milk production. Sixty (28 primiparous and 32 multiparous) lactating Jersey cows (106 ± 54 days in milk) were blocked and assigned randomly to either a control (CON) treatment without any isoacids, MB [12.3 mmol/kg dry matter (DM)], MB + IB (7.7 and 12.6 mmol/kg DM of MB and IB, respectively), or all 4 isoacids (6.2, 7.3, 4.2, and 5.1 mmol/kg DM of MB, IB, isovalerate, and valerate, respectively). Cattle were fed the CON treatment for a 2-wk period, then were assigned randomly within a block to treatments for 8 wk (n = 15). There was a trend for an interaction of supplement and parity for milk components. There were no differences in components for primiparous cows, whereas MB + IB tended to increase protein concentration by 0.04 and 0.08 percentage units in multiparous cows compared with the CON and MB treatments, respectively. Feeding MB + IB increased fat concentration by 0.23 to 0.31 percentage units compared with all other treatments in multiparous cows. Milk yield and dry matter intake (DMI) did not change with treatment. Treatment interacted with week for milk net energy for lactation/DMI; MB + IB tended to increase milk net energy of lactation/DMI by 0.10 Mcal/kg compared with MB and approached a trend for CON, mainly during the early weeks of the treatment period, whereas differences decreased during the last 2 wk of the treatment period. Cows fed MB had the highest 15:0 anteiso fatty acids in the total milk fatty acid profile, which was greater than that for CON or MB + IB cows, but not cows supplemented with isoacids. Cows fed MB alone had the numerically lowest milk net energy for lactation/DMI. The combination of MB + IB appeared optimal for increasing feed efficiency in our study and was not at the expense of average daily gain. Further research is needed for evaluating how potential changes in supplemental isoacid dosage should vary under differing dietary conditions.
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Lactancia , Leche , Embarazo , Femenino , Bovinos , Animales , Leche/metabolismo , Lactancia/fisiología , Valeratos/metabolismo , Digestión , Alimentación Animal/análisis , Ácidos Grasos/metabolismo , Dieta/veterinaria , Ácidos Grasos Volátiles/metabolismoRESUMEN
Heat stress (HS) negatively affects dry matter intake (DMI), milk yield (MY), feed efficiency (FE), and free water intake (FWI) in dairy cows, with detrimental consequences to animal welfare, health, and profitability of dairy farms. Absolute enteric methane (CH4) emission, yield (CH4/DMI), and intensity (CH4/MY) may also be affected. Therefore, the goal of this study was to model the changes in dairy cow productivity, water intake, and absolute CH4 emissions, yield, and intensity with the progression (days of exposure) of a cyclical HS period in lactating dairy cows. Heat stress was induced by increasing the average temperature by 15°C (from 19°C in the thermoneutral period to 34°C) while keeping relative humidity constant at 20% (temperature-humidity index peaks of approximately 83) in climate-controlled chambers for up to 20 d. A database composed of individual records (n = 1,675) of DMI and MY from 82 heat-stressed lactating dairy cows housed in environmental chambers from 6 studies was used. Free water intake was also estimated based on DMI, dry matter, crude protein, sodium, and potassium content of the diets, and ambient temperature. Absolute CH4 emissions was estimated based on DMI, fatty acids, and dietary digestible neutral detergent fiber content of the diets. Generalized additive mixed-effects models were used to describe the relationships of DMI, MY, FE, and absolute CH4 emissions, yield, and intensity with HS. Dry matter intake and absolute CH4 emissions and yield reduced with the progression of HS up to 9 d, when it started to increase again up to 20 d. Milk yield and FE reduced with the progression of HS up to 20 d. Free water intake (kg/d) decreased during the exposure to HS mainly because of a reduction in DMI; however, when expressed in kg/kg of DMI it increased modestly. Methane intensity also reduced initially up to d 5 during HS exposure but then started to increase again following the DMI and MY pattern up to d 20. However, the reductions in CH4 emissions (absolute, yield, and intensity) occurred at the expense of decreases in DMI, MY, and FE, which are not desirable. This study provides quantitative predictions of the changes in animal performance (DMI, MY, FE, FWI) and CH4 emissions (absolute, yield, and intensity) with the progression of HS in lactating dairy cows. The models developed in this study could be used as a tool to help dairy nutritionists to decide when and how to adopt strategies to mitigate the negative effects of HS on animal health and performance and related environmental costs. Thus, more precise and accurate on-farm management decisions could be taken with the use of these models. However, application of the developed models outside of the ranges of temperature-humidity index and period of HS exposure included in this study is not recommended. Also, validation of predictive capacity of the models to predict CH4 emissions and FWI using data from in vivo studies where these variables are measured in heat-stressed lactating dairy cows is required before these models can be used.
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Lactancia , Metano , Femenino , Bovinos , Animales , Metano/metabolismo , Leche/química , Dieta/veterinaria , Fibras de la Dieta/metabolismoRESUMEN
Intramammary infections (IMI) in primigravid dairy heifers can affect mammary growth and development, which can reduce first-lactation milk yield. Detection of IMI in heifers most often involves the use of culture-based methods that are not often used in production dairy settings given their labor- and time-consuming nature. The objective of this study was to determine whether mammary secretion somatic cell count (SCC) and viscosity were associated with the infection status of primigravid heifer mammary glands. A total of 270 heifers from a single farm were used, selected based on the farmer's willingness to participate. The study was conducted from June to October 2020. Mammary secretion samples were aseptically collected from a randomly selected quarter of each heifer at 75 d prepartum (75PP), and another quarter of each heifer was sampled at 35 d prepartum (35PP). The remaining 2 quarters of each heifer were not examined. Mammary secretion samples underwent bacteriological examination to determine IMI status and quantitative SCC measurement and were also assessed for secretion viscosity based on visual observation. Prevalence of IMI was 26% (69/270) and 28% (71/255) at 75 and 35 d prepartum, respectively. Uninfected secretion samples had 133.2 [95% confidence interval (CI): 16.8 to >999.9] times greater odds to be thick compared with samples infected with a major pathogen, and 14.4 (95% CI: 8.5 to 24.1) times greater odds to be thick compared with samples infected with non-aureus staphylococci (NAS). The mean secretion SCC of uninfected quarters (6.04 ± 0.03 log10 cells/mL) was significantly lower than that of secretions collected from quarters infected with Staphylococcus chromogenes (6.34 ± 0.04 log10 cells/mL), other NAS species (6.28 ± 0.10 log10 cells/mL), or a major pathogen (6.73 ± 0.08 log10 cells/mL). These results indicate that mammary secretion viscosity and SCC measurement may be useful tools in identifying primigravid heifer quarters with IMI. The ability to evaluate viscosity at time of sampling may be a useful strategy that could be incorporated into interventions designed to diminish the negative effects of prepartum IMI on lactational performance.
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Enfermedades de los Bovinos , Mastitis Bovina , Animales , Bovinos , Recuento de Células/veterinaria , Femenino , Lactancia , Glándulas Mamarias Animales , Leche , Infecciones Estafilocócicas/veterinariaRESUMEN
Many dairy cows succumb to disease after calving. Disease risk may be affected by the cows' social environment and ability to perform maternal behaviors. In nature, cattle isolate from others and find seclusion to give birth; these behaviors may be limited in indoor group pens and could potentially affect the cows' ability to cope. The aim was to determine whether stocking density and a physical blind in prepartum bedded-pack group pens affected physiological biomarkers, disease risk, and hygiene of peripartum dairy cows. A randomized complete block designed with a 2 × 2 factorial arrangement of treatments was used. Approximately 3 wk before calving, 374 cows (primiparous = 127; multiparous = 247) were assigned randomly to 1 of 4 treatment pens with the following 2 factors: (1) high versus low stocking density (7.7 to 12.9 m2 vs. 15.4 to 25.8 m2 lying space per cow), and (2) presence or absence of a blind. The blind was created using plastic road barriers and plywood, a steel gate, and shade cloth. After calving, cows were moved into a freestall pen and milked 3 times per day. Blood was sampled on the day of enrollment (baseline; -24 d) and approximately -14, -7, 3, 7, 10, and 14 d relative to calving, to measure inflammatory (haptoglobin) and metabolic (nonesterified fatty acids and ß-hydroxybutyrate) biomarkers. ß-Hydroxybutyrate (≥1.2 mmol/L) was used to diagnose subclinical ketosis. Vaginal discharge was scored 3, 7, 10, and 14 d after calving, to diagnose metritis (none, mild, or severe). Hygiene was scored on -24, -14, and -7 d before calving. Before calving, haptoglobin was lower in pens with a blind. After calving, cows in pens with low stocking density before calving tended to be at greater odds of being diagnosed with metritis. Cows were more likely to have poorer hygiene scores in high stocking density pens. No treatment effects were detected for pre- and postpartum nonesterified fatty acids, ß-hydroxybutyrate, postpartum haptoglobin, or subclinical ketosis. Results suggest that the provision of a blind and lower stocking density may be beneficial for reducing inflammation before calving. However, low prepartum stocking density might increase the odds of metritis after calving. Although the reason for this paradox is unclear, the effects of prepartum stocking density may require further exploration.
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Biomarcadores/sangre , Enfermedades de los Bovinos/prevención & control , Industria Lechera/métodos , Ácido 3-Hidroxibutírico/sangre , Animales , Bovinos , Enfermedades de los Bovinos/sangre , Ácidos Grasos no Esterificados/sangre , Femenino , Haptoglobinas/metabolismo , Vivienda para Animales , Higiene , Cetosis/sangre , Cetosis/prevención & control , Cetosis/veterinaria , Lactancia , Leche/metabolismo , Periodo Periparto , Densidad de Población , Periodo Posparto , Embarazo , Complicaciones del Embarazo/prevención & control , Complicaciones del Embarazo/veterinariaRESUMEN
In natural settings, dairy cows separate from the herd to give birth. When kept indoors, seeking isolation before calving may be restricted and may depend on space and resources provided in maternity housing. The effect of group maternity pens on behavior around calving and labor progress is unknown. Therefore, the objective of this study was to determine the effects of stocking density and provision of a blind in group bedded pack maternity pens on lying and social behavior as well as length of labor of preparturient dairy animals. The study was conducted as a complete randomized block design with a 2 × 2 factorial arrangement of treatments including stocking density and presence or absence of a blind, resulting in a total of 4 treatments: (1) high stocking density (7.7-12.9 m2 lying space/cow) with a blind, (2) low stocking density (15.4-25.8 m2) with a blind, (3) high stocking density without a blind, and (4) low stocking density without a blind. A total of 127 primiparous heifers and 247 multiparous cows were housed in mixed-parity groups from approximately 3 wk before and immediately after calving. During the 4 h before calving, lying behavior (lying time and bouts) was collected automatically using accelerometers, and social behavior (agonistic interactions, allogrooming, and attention from other cows), stage II labor duration, and frequency of position change during stage II labor were collected using video. Lying behavior was collected with accelerometers. Regardless of treatment, lying time and bouts increased as calving approached. Cows and heifers performed more lying bouts in low stocking density pens compared with high stocking density pens. Agonistic interactions and allogrooming were not different between treatments. Other cows spent more time paying attention to focal animals regardless of stocking density as calving approached, but time spent paying attention was reduced by the presence of a blind during h -2 before calving. The hazard of calving unassisted was greater for cows and heifers in low stocking density pens with a blind compared with all other treatments. Further, animals in pens with a blind tended to change positions fewer times during stage II labor. These results suggest that providing a blind in group maternity pens may improve the calving environment for cows and heifers and, in combination with low stocking density, may reduce the amount of time spent in labor.
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Conducta Animal , Trabajo de Parto , Animales , Bovinos , Femenino , Vivienda para Animales , Lactancia , Paridad , Parto , Embarazo , Conducta SocialRESUMEN
Mammary blood flow is central to mammary growth, development, and productivity, but the development of the vasculature network is poorly understood. The objective of this study was to determine how the vascular system adapts to mammary growth by inducing different levels of mammary growth and examining 2 regions of mammary parenchymal tissue. Holstein heifer calves (n = 12) received daily injections on the days immediately preceding euthanasia at 82 d of age. Treatments were control (CON), short-term estradiol (STE), and long-term estradiol (LTE). The CON calves received corn oil injections, the STE calves received 9 injections of corn oil followed by 3 injections of estradiol, and the LTE calves received 12 estradiol injections. Mammary tissues were collected from the center and edge parenchymal regions of all right rear mammary glands to quantify the tissue area of various tissue structures, the percentage of proliferating epithelial cells, and the number and form of blood vessels. Results showed that LTE calves had a greater tissue area occupied by epithelium than CON and STE calves, and the epithelial area in CON and STE calves was similar. Edge parenchyma had a greater percentage of proliferating epithelial cells than center parenchyma across all treatment groups. In the edge region, LTE calves had the greatest percentage of proliferating epithelial cells, coinciding with greater epithelial area. The number of blood vessels per unit of tissue area was greater in center than in edge parenchyma; the corresponding vessel surface area per unit of tissue area followed the same pattern. Mammary blood vessel measures were not markedly influenced by estradiol treatment. These results highlight the marked difference in the number and organization of blood vessels in different mammary parenchyma regions but indicate that the effects of estradiol on stimulating mammary epithelial proliferation does not directly translate to increasing numbers of blood vessels.
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Estradiol , Glándulas Mamarias Animales , Animales , Bovinos , Recuento de Células/veterinaria , Dieta , Células Epiteliales , Estradiol/farmacología , Estrógenos , FemeninoRESUMEN
Intramammary infections (IMI) are common in primigravid dairy heifers and can negatively affect future milk production. Bismuth subnitrate-based internal teat sealants (ITS) have been used to prevent prepartum IMI in dairy heifers by creating a physical barrier within the teat, preventing pathogens from entering the gland, though determination of when to administer ITS in heifers has yet to be investigated. The objectives of this study were to determine if administration of ITS in primigravid heifers reduced the odds of IMI at calving and if administration of ITS at different stages of gestation (75 vs. 35 d prepartum) affected the odds of IMI at calving. A total of 270 heifers were used at a single farm. One quarter of each heifer was randomly chosen to be aseptically sampled and administered ITS 75 d prepartum (ITS75), another quarter of each heifer was sampled and received ITS 35 d prepartum (ITS35), whereas the remaining 2 quarters of each heifer served as control quarters (CON) and were not sampled before calving. Within 12 h of calving, aseptic colostrum samples were collected from all quarters to determine quarter infection status. When an IMI was caused by mastitis pathogens other than non-aureus staphylococci (NAS), CON quarters were 3 times [95% confidence interval (CI): 1.4-6.3] and 2.5 times (95% CI: 1.2-4.9) more likely to be infected at calving than ITS75 and ITS35 quarters, respectively. For IMI with NAS, CON quarters were 5.8 (95% CI: 3.2-10.5) and 6.4 (95% CI: 3.4-12.0) times more likely to be infected than ITS75 and ITS35 quarters, respectively. Odds of IMI at calving was similar between ITS75 and ITS35 quarters for both NAS (odds ratio = 0.9) and other pathogens (odds ratio = 1.2). Results indicate that ITS administration at either 75 and 35 d prepartum reduced IMI prevalence at calving in primigravid dairy heifers. Farm specific factors may influence prevalence and timing of heifer IMI and earlier administration of ITS provides an extended period of protection for the developing gland.
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Enfermedades de los Bovinos , Mastitis Bovina , Animales , Bovinos , Femenino , Glándulas Mamarias Animales , Mastitis Bovina/prevención & control , Leche , Embarazo , Prevalencia , StaphylococcusRESUMEN
The economic value of milk fat and its responsiveness to management strategies provides strong interest in maximizing milk fat production by minimizing occurrence of biohydrogenation-induced milk fat depression (BH-MFD) and maximizing de novo synthesized fatty acids (FA). Tools that allow a timely diagnosis of BH-MFD would improve nutritional management. Specific milk FA or FA categories correlate to milk fat concentration and are of interest for diagnosing the cause of changes in milk fat concentration. The objective of the current study was to characterize the relationship between milk fat concentration and trans-10 C18:1, a proxy for BH-MFD, and FA <16 carbons that originate solely from de novo lipogenesis using a meta-analysis approach that used data from the literature and unpublished Penn State experiments. Prior to the meta-analysis, the effect of FA methylation method on milk FA profile was tested to determine potential bias between papers. There was no difference between sodium methoxide, acid, and acid-base methylation methods on trans-10 C18:1 concentration, but acid methods resulted in loss of short-chain FA. The relationship between trans-10 C18:1 and milk fat percentage was investigated using a 2-component model, where one component described the fraction unresponsive to BH-MFD and the other described a responsive fraction that is exponentially related to trans-10 C18:1. The 2 fractions where characterized utilizing a Bayesian hierarchical model accounting for between-study variability. The model was defined by the function f(x, θ1, θ2, θ3) = θ1 + θ2exp(θ3), where the unresponsive θ1 fraction was 2.15 ± 0.09%, the responsive θ2 fraction was 1.55 ± 0.08%, and the exponential term θ3 was -0.503 ± 0.07 (posterior mean ± posterior standard deviation from the Bayesian hierarchical model). A Lin's concordance correlation coefficient of 0.67 suggested good agreement between observations and predictions from the Bayesian hierarchical model, computed only with the model's mean population parameters. There was a linear relationship between milk fat concentration and FA <16 C as a percentage of total FA (intercept = 2.68 ± 0.237 and slope = 0.043 ± 0.011; coefficient of determination = 0.31). The relationship between milk FA <16 C and milk fat concentration is weaker than what has been published, likely because multiple factors can reduce de novo FA without reducing milk fat and the broad range of diets present in the literature.
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Grasas/análisis , Ácidos Grasos/análisis , Lípidos/biosíntesis , Leche/química , Animales , Teorema de Bayes , Bovinos , Dieta , Suplementos Dietéticos/análisis , Femenino , Glucolípidos , Glicoproteínas , Hidrogenación , Lactancia , Gotas LipídicasRESUMEN
The objective of this study was to conduct a meta-analysis to quantitatively characterize the effects of mastitis on the reproductive performance of dairy cows as well as to identify factors that interact with this relationship. A total of 29 publications were identified that contributed 24, 41, 27, 38, and 13 trial results to the meta-analysis of how mastitis is related to time to first service (TFS), days open (DO), services per conception (SPC), pregnancies per insemination at first service (FSP/AI) and pregnancy loss (PL), respectively. The meta-analyses were conducted using multilevel linear mixed-effects models. Overall, high levels of heterogeneity were present and meta-regression models only explained a small amount of heterogeneity. Results suggest that cows with mastitis pre-first insemination experience, on average, an additional 13.29 d to first service [95% confidence interval (CI): 6.64, 19.95] when compared with cows with no mastitis in the same time period. Moreover, in relation to cows with no mastitis in the same time period, 22.34 additional DO (95% CI: 12.89, 31.79) were estimated, on average, for cows with clinical mastitis at pre-insemination leading to conception. Additionally, 32.41 added DO (95% CI: 20.58, 44.25) were estimated, on average, for cows with clinical mastitis at pre- or post-insemination leading to conception compared with cows with no mastitis in the same time period. Finally, 20.03 additional DO (95% CI: 3.11, 36.95) were estimated, on average, for cows with subclinical mastitis pre- or post-insemination leading to conception compared with cows with no mastitis in the same time period. Effect size estimates from the meta-regression models for SPC, in relation to cows with no mastitis in the same time period, suggest that, on average, SPC increases by 0.46 inseminations (95% CI: 0.30, 0.62) for a cow experiencing mastitis pre-insemination leading to conception. When mastitis occurs either pre- or post-insemination leading to conception, SPC is expected to increase, on average, by 0.72 inseminations (95% CI: 0.48, 0.95) compared with cows with no mastitis in the same time period. The estimated effect sizes for FSP/AI suggest a risk ratio of conceiving at first insemination of 0.90 (95% CI: 0.82, 0.99) for cows with mastitis diagnosed pre-first insemination with respect to cows with no mastitis in the same time period, and a risk ratio of 0.79 (95% CI: 0.72, 0.86) for cows diagnosed with mastitis either pre- or post-first insemination with respect to cows with no mastitis in the same time period. Publication bias was identified in 4 of the meta-analysis models (TFS, DO, SPC, and FSCR), but no influential trials were identified in any models; the reliability of the meta-analysis results should be interpreted carefully keeping these limitations in mind. Further meta-regression analysis would be valuable as additional studies are published that report other potential sources of heterogeneity.
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Industria Lechera/estadística & datos numéricos , Mastitis Bovina/fisiopatología , Reproducción/fisiología , Animales , Bovinos , Femenino , Fertilización , Inseminación Artificial/veterinaria , Embarazo , Reproducibilidad de los ResultadosRESUMEN
The objective of this study was to develop a modeling framework to predict milk protein yield responses to varying metabolizable protein (MP) supplies and to determine the requirement of MP by lactating dairy cows. The logistic curve was used to model milk protein yield while accounting for a variable efficiency of MP utilization and between-study variability. Models were developed with databases from 2 recently published meta-analyses and based on either total MP supply or MP supply available for milk production. All models provided reasonable fit to data, with root mean square prediction error ranging from 18 to 20% of the average milk protein yield. The estimated horizontal asymptotes were 1.17 (posterior SD = 0.02) and 1.55 (posterior SD = 0.06) in the 2 databases, suggesting that the limiting milk protein yield, as MP supply increases, converges to 1.17 or 1.55 kg/d in the environments determined by the 2 databases. The observed efficiencies ranged from 0.75 to 0.18 when total MP supply was used as the denominator and above 1 to 0.24 when the MP supply available for milk production was used as the denominator. The predicted efficiencies were in good agreement with the data, decreasing nonlinearly with the MP supply. The MP requirement was calculated with a function constructed with the inverse of the logistic model and modified at regions of maximum marginal efficiency and minimum second derivative. This strategy assumes that the MP solution, or the MP needed to predict a given protein yield in the fitted logistic curve, determines the MP requirement for maintenance and lactation. Requirements calculated with the independent variable as total MP supply refer to the total requirement of maintenance plus lactation, whereas the requirement from models based on MP supply available for milk production are referent to the MP required only for lactation. The requirements were, on average, slightly smaller than the ones predicted by the current Northern American feeding system for dairy cows at lower protein yields and greater than currently recommended at high yields.
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Alimentación Animal/análisis , Bovinos/fisiología , Dieta/veterinaria , Proteínas en la Dieta/administración & dosificación , Proteínas de la Leche/metabolismo , Leche/metabolismo , Fenómenos Fisiológicos Nutricionales de los Animales , Animales , Femenino , Lactancia/fisiología , Proteínas/metabolismoRESUMEN
Organic matter (OM) in livestock manure consisting of biodegradable and nonbiodegradable fractions is known as volatile solids (VS). According to the Intergovernmental Panel on Climate Change (IPCC) Tier 2 guidelines, methane produced by stored manure is determined based on VS. However, only biodegradable OM generates methane production. Therefore, estimates of biodegradable VS (dVS; dVS = VS - lignin) would yield better estimates of methane emissions from manure. The objective of the study was to develop mathematical models for estimating VS and dVS outputs of lactating dairy cows. Dry matter intake, dietary nutrient contents, milk yield and composition, body weight, and days in milk were used as potential predictor variables. Multicollinearity, model simplicity, and random study effects were taken into account during model development that used 857 VS and dVS measurements made on individual cows (kg/cow per day) from 43 metabolic trials conducted at the USDA Energy and Metabolism laboratory in Beltsville, Maryland. The new models and the IPCC Tier 2 model were evaluated with an independent data set including 209 VS and dVS measurements (kg/cow per day) from 2 metabolic trials conducted at the University of California, Davis. Organic matter intake (kg/d) and dietary crude protein and neutral detergent fiber contents (% of dry matter) were significantly associated with VS. A new model including these variables fitted best to data. When evaluated with independent data, the new model had a root mean squared prediction error as a percentage of average observed value (RMSPE) of 12.5%. Mean and slope biases were negligible at <1% of total prediction bias. When energy digestibility of the diet was assumed to be 67%, the IPCC Tier 2 model had a RMSPE of 13.7% and a notable mean bias for VS to be overpredicted by 0.4 kg/cow per day. A separate model including OM intake as well as dietary crude protein and neutral detergent fiber contents as predictor variables fitted best to dVS data and performed well on independent data (RMSPE = 12.7%). The Cornell Net Carbohydrate and Protein System model relying on fat-corrected milk yield and body weight more successfully predicted dry matter intake (DMI; RMSPE = 14.1%) than the simplified (RMSPE = 16.9%) and comprehensive (RMSPE = 23.4%) models to predict DMI in IPCC Tier 2 methodology. New models and the IPCC Tier 2 model using DMI from the Cornell Net Carbohydrate and Protein System model predicted VS (RMSPE = 17.7-19.4%) and dVS (RMSPE = 20%) well with small systematic bias (<10% of total bias). The present study offers empirical models that can accurately predict VS and dVS of dairy cows using routinely available data in dairy farms and thereby assist in efficiently determining methane emissions from stored manure.
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Bovinos/fisiología , Estiércol/análisis , Metano/análisis , Animales , Peso Corporal , Dieta/veterinaria , Fibras de la Dieta/metabolismo , Femenino , Lactancia , Maryland , Metano/metabolismo , Leche/metabolismoRESUMEN
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.
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Estiércol , Urea , Amoníaco , Animales , Bovinos , Concentración de Iones de Hidrógeno , Hidrólisis , TemperaturaRESUMEN
Methane generation from dairy liquid storage systems is a major source of agricultural greenhouse gas emissions. However, little on-farm research has been conducted to estimate and determine the factors that may affect these emissions. Six lagoons in south-central Idaho were monitored for 1 yr, with CH4 emissions estimated by inverse dispersion modeling. Lagoon characteristics thought to contribute to CH4 emissions were also monitored over this time period. Average emissions from the lagoons ranged from 30 to 126 kg/ha per day or 22 to 517 kg/d. Whereas we found a general trend for greater emissions during the summer, when temperatures were greater, events such as pumping, rainfall, freeze or thaw of lagoon surfaces, and wind significantly increased CH4 emissions irrespective of temperature. Lagoon physicochemical characteristics, such as total solids, chemical oxygen demand, and volatile solids, were highly correlated with emission. Methane prediction models were developed using volatile solids, wind speed, air temperature, and pH as independent variables. The US Environmental Protection Agency methodology for estimating CH4 emissions from manure storage was used for comparison of on-farm CH4 emissions from 1 of the lagoon systems. The US Environmental Protection Agency method underestimated CH4 emissions by 48%. An alternative methodology, using volatile solids degradation factor, provided a more accurate estimate of annual emissions from the lagoon system and may hold promise for applicability across a range of dairy lagoon systems in the United States.
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Contaminantes Atmosféricos/análisis , Industria Lechera , Monitoreo del Ambiente , Metano/análisis , Animales , Estiércol/análisis , Estaciones del Año , Estados UnidosRESUMEN
Manure nitrogen (N) from cattle production facilities can lead to negative environmental effects, such as contribution to greenhouse gas emissions, leaching and runoff to aqueous ecosystems leading to eutrophication, and acid rain. To mitigate these effects and to improve the efficiency of N use, accurate prediction of N excretion and secretions are required. A genetic algorithm was implemented to select models to predict fecal, urinary, and total manure N excretions, and milk N secretions from 3 classes of animals: lactating dairy cows, heifers and dry cows, and steers. Two tiers of model classes were developed for each category of animals based on model input requirements. A total of 6 models for heifers and dry cows and steers and an additional 2 models for lactating dairy cattle were developed. Evaluation of the models using K-fold cross validation based on all data and using the most recent 6 yr of data showed better prediction for total manure N and fecal N compared with urinary N excretion, which was the most variable response in the database. Compared with extant models from the literature, the models developed in this study resulted in a significant improvement in prediction error for fecal and urinary N excretions from lactating cows. For total manure production by lactating cows, extant and new models were comparable in their prediction ability. Both proposed and extant models performed better than the prediction methods used by the US Environmental Protection Agency for the national inventory of greenhouse gases. Therefore, the proposed models are recommended for use in estimation of manure N from various classes of animals.
Asunto(s)
Bovinos/metabolismo , Modelos Biológicos , Nitrógeno/metabolismo , Lluvia Ácida , Animales , Líquidos Corporales/química , Dieta/veterinaria , Eutrofización , Heces/química , Femenino , Efecto Invernadero , Lactancia/fisiología , Masculino , Leche/química , Estados Unidos , Contaminantes Químicos del AguaRESUMEN
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.
Asunto(s)
Alimentación Animal/economía , Bovinos/fisiología , Costos y Análisis de Costo , Dieta/veterinaria , Ambiente , Metano/metabolismo , Crianza de Animales Domésticos/métodos , Animales , California , Industria Lechera/métodos , Dieta/economía , Femenino , Lactancia , Ganado , Modelos Teóricos , Programación LinealRESUMEN
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.
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Bovinos/fisiología , Dieta/veterinaria , Metabolismo Energético , Leche/química , Animales , Peso Corporal , Femenino , Lactancia , Análisis Multivariante , TermogénesisRESUMEN
The reticulorumen (RR) fractional passage rate (kp; /h) of particles and solutes plays an important role in fiber digestion, methane production, and microbial yield. However, none of the available models for predicting RR kp consider individuals' characteristics of growing goats. The objective was to develop empirical models for predicting the RR kp of particles and solutes in growing goats. Our database involved 175 individual records of castrated males (n = 61), females (n = 57), and intact males (n = 57) growing Saanen goats fed ad libitum, 75% or 50% of ad libitum. Goats were slaughtered around 15, 22, 30, 37, or 45 kg BW. We used Akaike's information criterion to select the best prediction models. We evaluated the predictive ability of these models using Lin's concordance correlation coefficient (CCC) and RMSE of prediction (RMSPE) in a 4-fold cross-evaluation. The DM intake (DMI; kg/day), potentially digestible NDF intake (pdNDFI) level (g/kg BW), and RR wet pool size (kg) demonstrated similar importance in predicting RR kp of solutes (CCC = 0.59; RMSPE = 0.050 /h or 34.43%). However, when RR wet pool size was not included in the model, RR kp of solutes could still be precisely and accurately predicted using only DMI level (g/kg BW) (CCC = 0.47; RMSPE = 0.053 /h or 36.58%). The RR wet tissues and wet pool size (kg), NDF intake (NDFI) (kg/day), and indigestible NDFI (iNDFI):NDFI ratio were important predictors of RR kp of particles (CCC = 0.51; RMSPE = 0.0064 /h or 25.43 %). However, when RR wet tissues and wet pool size were not included in the model, iNDFI:NDFI ratio, NDFI level (g/kg BW), and RR kp of solutes presented greater importance in predicting RR kp of particles (CCC = 0.20; RMSPE = 0.0074 /h or 29.55%). Sex was not a significant predictor variable for the selected models. In summary, the RR kp of solutes was more dependent on feed intake level while the RR kp of particles was more dependent on diet composition and RR kp of solutes. Our models were precise and accurate for predicting RR kp of solutes (CCC = 0.57 and 0.47; RMSPE = 0.051 and 0.054 /h) and particles (CCC = 0.48 and 0.17; RMSPE = 0.0066 and 0.0076 /h) after cross-evaluation. This suggests that our models can be integrated into feeding systems with mechanistic approaches that simulate other reticulorumen functions, such as digestion, microbial growth, and methane emission.
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Dieta , Ingestión de Alimentos , Humanos , Masculino , Femenino , Animales , Dieta/veterinaria , Cabras , Metano , Rumen , Alimentación Animal/análisis , Digestión , Fibras de la DietaRESUMEN
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.
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Industria Lechera/métodos , Dieta/veterinaria , Política Ambiental , Alimentación Animal/economía , Animales , Bovinos/fisiología , Costos y Análisis de Costo/economía , Industria Lechera/economía , Dieta/economía , Política Ambiental/economía , Femenino , Modelos Lineales , MetanoRESUMEN
On-animal sensor systems provide an opportunity to monitor ewes during parturition, potentially reducing ewe and lamb mortality risk. This study investigated the capacity of machine learning (ML) behaviour classification to monitor changes in sheep behaviour around the time of lambing using ear-borne accelerometers. Accelerometers were attached to 27 ewes grazing a 4.4 ha paddock. Data were then classified based on three different ethograms: (i) detection of grazing, lying, standing, walking; (ii) detection of active behaviour; and (iii) detection of body posture. Proportion of time devoted to performing each behaviour and activity was then calculated at a daily and hourly scale. Frequency of posture change was also calculated on an hourly scale. Assessment of each metric using a linear mixed-effects model was conducted for the 7 days (day scale) or 12 h (hour scale) before and after lambing. For all physical movements, regardless of the ethogram, there was a change in the days surrounding lambing. This involved either a decrease (grazing, lying, active behaviour) or peak (standing, walking) on the day of parturition, with most values returning to either pre-partum or near-pre-partum levels (all P < 0.001). Hourly changes also occurred for all behaviours (all P < 0.001), the most marked being increased walking behaviour and frequency of posture change. These findings indicate ewes were more restless around the time of parturition. Further application of this research should focus on development of algorithms that can be used to identify onset of lambing and/or time of parturition in pasture-based ewes.