scholarly journals A mathematical nutrition model adequately predicts beef and dairy cow intake and biological efficiency

2021 ◽  
Author(s):  
Phillip A Lancaster ◽  
Michael E Davis ◽  
Luis O Tedeschi ◽  
Jack J Rutledge ◽  
Larry V Cundiff
Keyword(s):  
Milk Yield ◽  
Feed Intake ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Beef Cows ◽  
Biological Efficiency ◽  
Production Cycle ◽  
P Value ◽  
Energy Yield ◽  
Beef Cow

Abstract The beef cow-calf sector accounts for 70% of feed consumed and greenhouse gases emitted for the beef industry, but there is no straightforward method to measure biological efficiency in grazing conditions. The objective of this study was to evaluate a mathematical nutrition model to estimate the feed intake and biological efficiency of mature beef cows. Data from dams (N = 160) and their 2 nd and 3 rd progeny (312 pairs) were collected from 1953 through 1980. Individual feed intake was measured at 28-d intervals year-round for dams and during 240-d lactation for progeny. Body weights of progeny were measured at 28-d intervals from birth to weaning, and of dams at parturition and weaning each production cycle. Milk yield of dams was measured at 14-d intervals. Dam ME intake (DMEI) and milk energy yield (MEL) of each cow was predicted using the Cattle Value Discovery System beef cow (CVDSbc) model for each parity. Biological efficiency (Mcal/kg) was computed as the ratio of observed or predicted DMEI to observed calf weaning weight (PWW). Pearson correlation coefficients were computed using corr.test function and model evaluation was performed using the epiR function in R software. Average (SD) dam weight, PWW, DMEI, and observed MEL were 527 (86) kg, 291 (47) kg, 9584 (2701) Mcal/production cycle, and 1029 (529) Mcal, respectively. Observed and predicted DMEI (r = 0.93 and 0.91), and observed and predicted MEL (r = 0.58 and 0.59) were positively correlated for progeny 2 and 3, respectively. The CVDS beef cow model under-predicted DMEI (mean bias = 1120 ± 76 Mcal, 11.7% of observed value) and MEL (mean bias = 30 ± 25 Mcal, 2.9% of observed value). Observed and predicted progeny feed intake were not correlated (r = 0.01, P-value = 0.79). Observed and predicted biological efficiency were positively correlated (r = 0.80 and 0.80, P-value ≤ 0.05) for parity 2 and 3, respectively, and the CVDSbc model under-predicted biological efficiency by 11% (mean bias = 3.59 ± 0.25 Mcal/kg). The CVDSbc provides reasonable predictions of feed intake and biological efficiency of mature beef cows, but further refinement of the relationship between calf feed intake and milk yield is recommended to improve predictions. Mathematical nutrition models can assist in the discovery of the biological efficiency of mature beef cows.

71 Evaluation of the CVDS Beef Cow Model to Estimate Biological Efficiency in Mature Cows

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 119-119
Author(s):  
Phillip A Lancaster ◽  
Mike Davis ◽  
Luis O Tedeschi ◽  
Jack Rutledge ◽  
Larry Cundiff
Keyword(s):  
Milk Yield ◽  
Feed Intake ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Metabolizable Energy ◽  
Biological Efficiency ◽  
Production Cycle ◽  
Energy Yield ◽  
Weaning Weight ◽  
Beef Cow

Abstract There is no clear method to measure biological efficiency in grazing beef cows. The objective of this study was to evaluate a nutrition model to estimate biological efficiency in mature cows. Data from dams (n = 160) and their 2nd and 3rd progeny were collected from 1953 through 1980. Individual feed intake was measured at 28-d intervals for lifetime of dams and during 240-d lactation for progeny. Body weight of progeny were measured at birth and weaning, and dams at parturition and weaning each production cycle. Milk yield of dams was measured at 14-d intervals by hand milking. Metabolizable energy required (MER) and predicted milk energy yield (MEY) of each cow was computed using the CVDS beef cow model for each parity. Biological efficiency was computed as the ratio of cow ME intake (MEI) to calf weaning weight (WW) based on observed (MEI/WW) and predicted (MER/WW) values. Pearson correlation coefficients were computed using corr.test function in R software. Average (SD) cow weight, calf weaning weight, cow MEI, and observed MEY were 507 (81) and 548 (88) kg, 287 (49) and 294 (44) kg, 9406 (2695) and 9721 (2686) Mcal, and 1009 (538) and 1051 (521) Mcal, for progeny 2 and 3, respectively. Cow MEI and MER (0.87 and 0.85), and observed and predicted MEY (0.51 and 0.51) were positively correlated for progeny 2 and 3, respectively. The CVDS model under predicted cow MEI [mean bias = 1685 (1718) and 1658 (1702) Mcal] and MEY [mean bias = 82 (465) and 129 (450) Mcal] for progeny 2 and 3, respectively. Observed and predicted progeny feed intake were not correlated. Observed and predicted biological efficiency were positively correlated (0.63 and 0.61) for progeny 2 and 3, respectively. In conclusion, nutrition models can reasonably predict biological efficiency, but further refinement of the relationship between calf feed intake and milk yield could improve prediction.

72 Relationships Among Lifetime Feed Efficiency Traits in Growing Heifers, Mature Cows and Their Progeny

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 118-119
Author(s):  
Phillip A Lancaster ◽  
Mike Davis ◽  
Jack Rutledge ◽  
Larry Cundiff
Keyword(s):  
Body Weight ◽  
Milk Yield ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Pearson Correlation ◽  
Average Daily Gain ◽  
Random Effect ◽  
Correlation Coefficients ◽  
Test Body ◽  
Production Cycle

Abstract Uncertainty exists in relationships among feed efficiency traits in different production stages. The objective of this study was to evaluate the relationships among feed efficiency traits measured in various stages of production. Data were collected from 1953 through 1980 from dams (n = 160), and their progeny (n = 406). Individual feed intake was measured from 240 d of age through weaning of 3rd calf for dams, and from weaning to slaughter for progeny. Body weight was measured at 28-d intervals until first parturition for heifers and slaughter for progeny, and cows were weighed at parturition and weaning each production cycle. Milk yield of dams was measured at 14-d intervals throughout lactation. Residual feed intake was computed as the residual from linear regression of daily DMI on metabolic mid-test body weight, average daily gain, and milk yield for dams only with year-diet-breed factor as a random effect using lmer function in R software. Pearson correlation coefficients were computed using corr.test function. Pearson correlations of RFI with DMI ranged from 0.58 to 0.74 and with feed:gain or feed:milk ranged from 0.24 to 0.67 within production stage. Heifer RFI was correlated with cow RFI during parity 1 (0.74), but not parity 2 (0.11) or 3 (-0.06). Heifer RFI was correlated with progeny 3 RFI (0.17), but not progeny 1 or 2 RFI. Cow RFI was weakly correlated among parities (0.25 to 0.36) whereas feed:milk was strongly correlated (0.56 to 0.70). Cow RFI was not correlated with progeny RFI of the same parity. In conclusion, RFI was poorly correlated across stage of production.

341 Meta-analysis of the Performance Responses of Replacement Heifers and Beef Cows to Monensin

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 191-192
Author(s):  
Mikayla F Moore ◽  
Shane Gadberry ◽  
David Lalman ◽  
Frank White ◽  
Sara Linneen ◽  
...  
Keyword(s):  
Production Systems ◽  
Meta Analysis ◽  
Physiological State ◽  
Average Daily Gain ◽  
Beef Cows ◽  
Feed Additives ◽  
Production Cycle ◽  
P Value ◽  
Beef Cow ◽  
Cow Calf

Abstract Performance benefits of monensin have been extensively studied in finishing and stocker cattle, but considerably less published work is available evaluating response to monensin supplementation in cow-calf production systems. Feed additives are more difficult to study in cow-calf production systems due to unstable diet characteristics and cow physiological state throughout the production cycle. This meta-analysis investigated the impacts of monensin on performance of extensively raised beef cow-calf and developing replacement heifers. The replacement heifer analysis was conducted with a maximum of 48 treatment means in 18 experiments. The mature cow analysis included 21 publications and 26 mean comparisons. The metaphor package (version 2.4-0; Viechtbauer, 2010) for R (version 4.0.3; www.r-project.org) was used to determine the overall effect size of monensin compared to a negative control. Each study’s n, means, and SEM or P-value was used to calculate the mean difference and estimate of within study variance for responses of interest. For replacement heifers, average daily gain (+0.03 ± 0.008 kg/d), feed efficiency (+0.013 ± 0.008 gain:feed), and percentage cycling before the breeding season (+15.9 ± 5.13%) were increased (P < 0.01), while dry matter intake (-4.3%) and age at puberty (-8.9 ± 1.48 d) were decreased (P < 0.01). Six studies reporting ad libitum forage intake for mature cows showed that monensin decreased (P = 0.008) DMI by 0.85 ± 0.322 kg/day. Six studies showed monesin increased (P = 0.01) milk yield 0.39 ± 0.15 kg/day by mature cows in early lactation. There were no differences in artificial insemination pregnancy nor total pregnancy for either the heifer or mature cow data sets. This analysis also indicates potential for use of monensin in beef cow production systems, but further research is needed to elucidate the effects on DMI and milk production in beef cows.

PSI-1 Assessment of Nursing Calf Feed Intake Equations in Predicting Calf Feed Intake

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 225-225
Author(s):  
Zachary T Buessing ◽  
M E Davis ◽  
Luis O Tedeschi ◽  
B J White ◽  
P A Lancaster
Keyword(s):  
Milk Yield ◽  
Feed Intake ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Farm Animals ◽  
Factors Affecting ◽  
Accuracy And Precision ◽  
Calf Performance ◽  
Animal Growth ◽  
Predicted Values

Abstract Nutrition models are important in predicting animal growth; however, little research has focused on nursing calf performance submodels. This project’s objective was to determine the accuracy and precision of two equations to compute nursing calves’ feed intake. Data were collected on 394 nursing calves from 4 sets of cows (years 1953, 1959, 1964, 1974) of various breeds in which monthly milk yield and butterfat content, individual calf feed intake, and birth and weaning weights were measured during their first three lactations. Cows were milked at 14-d intervals to determine milk yield. The calf feed intake equations used to predict observed feed intake were Equation 9.1 (TED06; Tedeschi et al., 2006, In “Nutrient Digestion and Utilization in Farm Animals: Modeling Approaches”) and Equation 25 (TED09; Tedeschi and Fox, 2009, J. Anim. Sci. 87:3380). Peak milk was estimated from lactation yield using the NASEM (2016) milk yield equation. The average (SD) peak milk, calf ME intake (MEI) over a 240-day preweaning period, and weaning weight were 10.84 (5.64) kg/d, 1,286 (328.71) Mcal of ME, and 280.93 (46.70) kg, respectively. When compared to the observed calf feed intake, TED06 and TED09 had Pearson correlation coefficients of 0.19 and 0.59, respectively. The MEI mean biases were -355.3 and 190.7 Mcal of for TED06 and TED09, respectively, indicating a 27.6% over prediction and 14.8% under prediction, respectively. The RMSE and R2 from linear regression of observed on predicted values of calf MEI were 308.7 Mcal and 0.0365 for TED06, and 253.2 Mcal and 0.3514 for TED09, respectively. In conclusion, neither equation adequately predicted calf feed intake, but the TED09 equation was more accurate and precise than the TED06 equation. Further research is needed to enhance our understanding of factors affecting feed intake of nursing calves to develop better prediction equations.

scholarly journals 70 Effects of copper, zinc, and manganese intake in late gestation on milk, cow plasma, and calf plasma trace mineral concentrations post-calving in beef cattle

2019 ◽  
Vol 97 (Supplement_2) ◽  
pp. 45-45
Author(s):  
Emma L Stephenson ◽  
Abigail R Rathert ◽  
Heather Tucker ◽  
Allison M Meyer
Keyword(s):  
Fixed Effects ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Beef Cows ◽  
Late Gestation ◽  
Experimental Unit ◽  
Beef Cow ◽  
Zn Concentration ◽  
Copper Zinc ◽  
Positive Correlations

Abstract Multiparous, fall-calving beef cows [n = 48; 649 ± 80 (SD) kg BW; 5.3 ± 0.5 BCS] were individually-fed tall fescue-based hay (12.2% CP, 61.5% NDF) and supplemented to meet/exceed nutrient recommendations except Cu, Zn, and Mn. From approximately 90 d pre-calving to 11 d post-calving, cows received: no additional Cu, Zn, or Mn (CON); Cu, Zn, and Mn sulfates (ITM) or metal methionine hydroxy analogue chelates (CTM, MINTREX®, Novus International) supplying 133% NASEM recommendations; or Cu, Zn, and Mn sulfates and chelates supplying 100% recommendations (reduce and replace, RR). Treatment, sampling day, their interaction, and breeding group were fixed effects with cow as the experimental unit. Colostrum and milk Cu and Mn and plasma Mn were generally not detectable. Colostrum Zn was greater (P ≤ 0.03) in CTM and ITM than CON and RR. All treatments had greater (P < 0.001) colostrum Zn than d 35 milk, which was greater (P ≤ 0.03) than d 60. Treatment did not affect (P ≥ 0.19) cow or calf plasma Cu or Zn post-calving. Calf plasma Zn decreased (P ≤ 0.02) from 0 to 35 d of age. Calf plasma Cu increased (P < 0.01) from 0 to 35 d, then decreased (P = 0.01) from 35 to 60 d. Cow plasma Zn and Cu were greater (P ≤ 0.02) at lactation d 35 and 60 than 1 h post-calving. Pearson correlation coefficients were used to determine relationships among cow and calf mineral status. There were weak positive correlations (P ≤ 0.06) between calf plasma and milk Zn at d 35 and 60. Cow and calf plasma Zn immediately post-calving had a weak negative correlation (P = 0.04). These results indicate greater Zn concentration in beef cow colostrum than milk, and suggest calf circulating Zn is partially dependent on milk Zn concentration.

scholarly journals 127 Predicting Dry Matter Intake of Gestating and Lactating Beef Cows

2020 ◽  
Vol 98 (Supplement_2) ◽  
pp. 58-58
Author(s):  
Megan A Gross ◽  
Claire Andresen ◽  
Amanda Holder ◽  
Alexi Moehlenpah ◽  
Carla Goad ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Milk Yield ◽  
Feed Intake ◽  
Beef Cows ◽  
Multiple Regression Equation ◽  
Validation Data ◽  
Data Set ◽  
Lactating Cows ◽  
Downward Bias ◽  
Protein Supply

Abstract In 1996, the NASEM beef cattle committee developed and published an equation to estimate cow feed intake using results from studies conducted or published between 1979 and 1993 (Nutrient Requirements of Beef Cattle). The same equation was recommended for use in the most recent version of this publication (2016). The equation is sensitive to cow weight, diet digestibility and milk yield. Our objective was to validate the accuracy of this equation using more recent published and unpublished data. Criteria for inclusion in the validation data set included projects conducted or published within the last ten years, direct measurement of forage intake, adequate protein supply, and pen feeding (no tie stall or metabolism crate data). The validation data set included 29 treatment means for gestating cows and 26 treatment means for lactating cows. Means for the gestating cow data set was 11.4 ± 1.9 kg DMI, 599 ± 77 kg BW, 1.24 ± 0.14 Mcal/kg NEm per kg of feed and lactating cow data set was 14.5 ± 2.0 kg DMI, 532 ± 116.3 kg BW, and 1.26 ± 0.24 Mcal NEm per kg feed, respectively. Non intercept models were used to determine equation accuracy in predicting validation data set DMI. The slope for linear bias in the NASEM gestation equation did not differ from 1 (P = 0.07) with a 3.5% positive bias. However, when the NASEM equation was used to predict DMI in lactating cows, the slope for linear bias significantly differed from 1 (P &lt; 0.001) with a downward bias of 13.7%. Therefore, a new multiple regression equation was developed from the validation data set: DMI= (-4.336 + (0.086427 (BW^.75) + 0.3 (Milk yield)+6.005785(NEm)), (R-squared=0.84). The NASEM equation for gestating beef cows was reasonably accurate while the lactation equation underestimated feed intake.

Genetic parameters for feed intake and efficiency in lactating beef cows

1996 ◽  
Vol 76 (1) ◽  
pp. 81-87 ◽  
Author(s):  
L. Q. Fan ◽  
J. W. Wilton ◽  
P. E. Colucci
Keyword(s):  
Milk Yield ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
National Research Council ◽  
Beef Cows ◽  
Feed Consumption ◽  
Research Centre ◽  
Total Data

Genetic parameters of feed intake and efficiency and production traits for lactating beef cows were estimated from data collected from 1980 to 1988 at the Elora Beef Research Centre, Guelph, Ontario. Estimates were obtained using restricted maximum likelihood (REML) with an individual animal model with year–season–treatment, sex of calf, parity, breeding system, covariate daily change of backfat depth and direct genetic and permanent environmental effects. The data included 1174 observations, 511 cows, 369 dam–maternal grand dam pairs and 245 sires of cows. Feed efficiency for milk was calculated as milk yield relative to energy consumed for milk and maintenance and residual feed consumption as estimated energy intake minus energy requirements as estimated by the National Research Council. Heritabilities for Herefords alone and total data, respectively, were estimated to be 0.02 and 0.11 for cow's daily ME intake (MEI), 0.26 and 0.26 for daily milk yield (DMY), 0.45 and 0.33 for milk fat percentage (MFP), 0.29 and 0.40 for metabolic body weight (MBW), 0.21 and 0.10 for calf weaning weight as a proportion of cow weight at weaning (PPW), 0.18 and 0.11 for feed efficiency for milk (FE), and 0.23 and 0.03 for residual feed consumption (RFC). Genetic correlations of output (DMY) and input (MEI) were 0.31 for Hereford and 0.75 for the total data. Genetic correlations of RFC with both output (DMY) and input (MEI) were low. Genetically, PPW was positively associated with FE and DMY and negatively associated with MBW. Key words: Genetic parameters, feed efficiency, lactation, beef cow

scholarly journals 29 The effect of fleshing ability on cow and calf performance

2019 ◽  
Vol 97 (Supplement_1) ◽  
pp. 22-22
Author(s):  
Amanda Holder ◽  
Aksel Wiseman ◽  
Adam McGee ◽  
David Lalman ◽  
Claire Andresen
Keyword(s):  
Body Weight ◽  
Milk Yield ◽  
Body Condition ◽  
Body Condition Score ◽  
Beef Cows ◽  
Milk Composition ◽  
Weight Changes ◽  
Beef Cow ◽  
Randomized Design ◽  
Condition Score

Abstract Several factors influence the overall maintenance requirements of a mature beef cow including age, gain, lactation, pregnancy, and fleshing ability. However, limited research is available to distinguish what sets a hard-fleshing cow apart from an easy-fleshing cow. Cows that are hard-fleshing maintain a lower body condition score (BCS) throughout the year compared to easy-fleshing counterparts. The objectives of this experiment are to determine the differences in characteristics and production between cows classified as easy- vs. hard- fleshing. Characteristics of interest include feed intake, milk yield, milk composition, body weight changes, BCS changes, and other body composition measurements, as well as calf weaning weight. In this study, 24 spring-calving, mature Angus beef cows were classified as either hard-fleshing or easy-fleshing based on BCS and ultrasound measurements for back fat and rump fat. The intake study took place during the second trimester, cows were assigned to an easy- or hard-fleshing pen based on treatment where they remained for the entirety of the 45-day intake study. Each treatment was replicated three times in a completely randomized design. Milk data collection began one month after calving with monthly milkings from May-August. There were no differences (P = 0.9) in DMI, although hard-fleshing cows had greater DMI calculated on a metabolic body weight basis (P = 0.05). There was a trend (P = 0.12) for hard-fleshing cows to wean heavier calves, although there was no difference in mean milk yield (P = 0.44). Body condition score was positively correlated with protein and carbohydrate content of milk with easy-fleshing cows having greater contents of both (P = 0.02 and P < 0.01, respectively). Overall, an increase in BCS without an increase in DMI may be beneficial from a reproductive standpoint, though more research in this area is needed.

scholarly journals A Comparison of Three Trapezoid Models Using Optical and Thermal Satellite Imagery for Water Table Depth Monitoring in Estonian Bogs

2020 ◽  
Vol 12 (12) ◽  
pp. 1980 ◽  
Author(s):  
Iuliia Burdun ◽  
Michel Bechtold ◽  
Valentina Sagris ◽  
Viacheslav Komisarenko ◽  
Gabrielle De Lannoy ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Table ◽  
Satellite Imagery ◽  
Landsat Imagery ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Temporal Correlation ◽  
Water Table Depth ◽  
P Value

This study explored the potential of optical and thermal satellite imagery to monitor temporal and spatial changes in the position of the water table depth (WTD) in the peat layer of northern bogs. We evaluated three different trapezoid models that are proposed in the literature for soil moisture monitoring in regions with mineral soils. Due to the tight capillary connection between water table and surface soil moisture, we hypothesized that the soil moisture indices retrieved from these models would be correlated with WTD measured in situ. Two trapezoid models were based on optical and thermal imagery, also known as Thermal-Optical TRApezoid Models (TOTRAM), and one was based on optical imagery alone, also known as the OPtical TRApezoid Model (OPTRAM). The models were applied to Landsat imagery from 2008 to 2019 and the derived soil moisture indices were compared with in-situ WTD from eight locations in two Estonian bogs. Our results show that only the OPTRAM index was significantly (p-value < 0.05) correlated in time with WTD (average Pearson correlation coefficient of 0.41 and 0.37, for original and anomaly time series, respectively), while the two tested TOTRAM indices were not. The highest temporal correlation coefficients (up to 0.8) were observed for OPTRAM over treeless parts of the bogs. An assessment of the spatial correlation between soil moisture indices and WTD indicated that all three models did not capture the spatial variation in water table depth. Instead, the spatial patterns of the indices were primarily attributable to vegetation patterns.

The effect of body condition, feed level and temporary calf separation on the post-partum anoestrous period and LH and FSH levels in beef cows

1997 ◽  
Vol 1987 ◽  
pp. 26-26
Author(s):  
I.A. Wright ◽  
A.J.F. Russel ◽  
T.K. Whyte ◽  
A.J. McBean
Keyword(s):  
Dairy Cows ◽  
Reproductive Performance ◽  
Deleterious Effect ◽  
Post Partum ◽  
Beef Cows ◽  
Biological Efficiency ◽  
Reproductive Efficiency ◽  
Beef Cow ◽  
The Mean ◽  
Farm Livestock

Compared with other species of farm livestock the reproductive performance of beef cows is poor. Mating and calving periods are frequently extended to avoid having a large proportion of barren Cows. vs. For example the ‘average’ MLC recorded herd has a calving period of over 4months. This makes management of beef cow herds difficult and has a deleterious effect on biological efficiency and profitability.One of the major limitations to improvement of reproductive efficiency in beef cattle is the extended post-partum anoestrus. Beef cows have longer post-partum anoestrous periods than dairy cows. In one study of three different herds (Peters and Riley, 1982) the mean length of the anovulatory period ranged from 24 to 88 days.

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