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Milk production is a primary factor controlling weaning weight of beef calves. The purpose of this experiment was to develop a practical and reliable on-farm method of estimating milk production and to relate estimates of milk production and milk composition to preweaning weight gain of calves. A second objective was to relate milk production to postpartum ovarian activity. Milk production of spring- and fall-calving grade Angus cows was estimated by machine milking (MM; average of 66, 123 and 189 d postpartum) and weigh-suckle-weigh (WSW; average of 50, 95, 136 and 179 d postpartum) techniques following overnight calf removal. Cows and calves were weighed monthly and the postpartum interval to first ovulation following calving was determined. The repeatability of the estimated milk production by MM (.97) was higher (P less than .01) than by WSW (.35). The correlation of average WSW and average MM estimates of milk production with preweaning calf gain were high and similar (greater than .75). Inclusion of milk composition did not improve the multiple correlation of MM-estimated milk production and calf gain. Neither milk production in early lactation (-.06) nor prebreeding weight change (-.07) was correlated with postpartum interval to ovulation. Machine milking was a repeatable method of estimating milk production of beef cows and can be used to evaluate effects of management variables on lactation of beef cows.
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A method to detect and to adjust or exclude abnormally low or high milk, fat, and protein yields on test-day (TD) was developed. Predicted TD yield is calculated based on preceding and subsequent (if available) TD yields. Observed TD yields that are < 60% or > 150% of predicted TD yield are defined as abnormal. Most abnormal yields are adjusted to this floor or ceiling, but some are excluded. Yields of < 4.5 kg that are identified as from a cow that was sick or that are less than half the mean of adjacent tests are excluded as are yields of > 59 kg above predicted yield. Lactation yields are calculated from the restricted TD yields. When this procedure was applied to 2002 data, 1.8% of milk, 2.4% of fat, and 1.6% of protein yields on TD were below the acceptance range and 0.1% of milk and protein and 0.8% of fat were above. Predicted TD yield was calculated as preceding TD yield plus preceding test interval multiplied by daily yield change (slope) based on days in milk (DIM), DIM2, previous normal TD yield, and interaction between DIM and previous TD yield. To accommodate changes in slope at peak yield, separate coefficients were estimated for < 50 and > or = 50 DIM. Herd mean was used when only one TD was recorded for a cow (or when two were recorded and the second was designated as abnormal based on the first) and to determine an acceptable range for component percentages. Predicted TD yield for first TD was based on subsequent rather than previous normal TD. To test the adjustments, lactation records with one abnormal TD yield or more were matched with subsequent lactation records. Correlation between consecutive lactations increased from 0.692 to 0.693 for milk (561,063 lactation pairs), from 0.653 to 0.660 for fat (951,387 lactation pairs), and from 0.686 to 0.694 for protein (488,653 lactation pairs). Outlier adjustment improved the correlation between consecutive lactation yields and is applied routinely to TD records of cows for calvings since 1997.
Because no instrument technology has been shown to predict beef carcass composition better than USDA yield grades, this study was conducted to determine whether an instrument could be used to augment and improve the accuracy of USDA yield grade placement. Adjusted preliminary yield grade (PYG), ribeye area (REA), estimated percentage of kidney, pelvic, and heart fat (KPH), hot carcass weight (HCW), and USDA yield grade (called and computed) were determined by five on-line USDA graders and two USDA grading supervisors for beef carcasses (n = 550) selected randomly in a commercial beef packing plant. Data were compared (2,737 comparisons) to Gold Standard yield grades and yield grade factors determined by an expert panel of carcass evaluators (unrestrained in access or time to evaluate carcasses). On-line USDA grader PYG were closely related (mean absolute error of .15 +/- .14 yield grade units; r = .91), and on-line REA and KPH were nominally related (mean absolute error of .51 +/- .35, .06 +/- .07 yield grade units and r = .48 and .66, respectively), to Gold Standard yield grade factors. On-line USDA graders determined adjusted PYG effectively, but they may require instrument assistance to evaluate carcass muscling traits and perform time-sensitive computations. To explain why instrument technology may not estimate beef carcass fatness as accurately as USDA yield grades, the absolute mean difference between Gold Standard measured PYG and adjusted PYG were compared. Only 5.6% of the sample population required no PYG adjustment, 94.4% required some adjustment, and 11.0% required over a .5 yield grade unit adjustment. Yield grades for beef carcasses, called by the USDA graders and supervisors at chain speeds, resulted in greater accuracy (absolute mean error of .24 +/- .43 yield grade units; r = .82) than when yield grades were computed for carcasses using the yield grade factors determined by on-line USDA graders and supervisors at chain speeds (absolute mean error of .52 +/- .41 yield grade units; r = .75). Gold Standard yield grade factors were sequentially substituted into the short-cut USDA yield grade equation for the yield grade factors determined at chain speeds by the USDA graders and supervisors. Results suggested that instrument augmentation would improve accuracy and precision of yield grade placement if on-line USDA graders determined PYG and an instrument determined REA and performed the necessary computations, incorporating KPH and actual HCW (P < .05).
Statistical models were presented to estimate daily yields from either morning or evening test results. The 64,451 test-day records from 10,392 lactations of 8800 cows were available for analysis from experiments that were designed to investigate the accuracy of an alternate morning and evening four-weekly milk-testing scheme. The experiments were conducted in 152 herds from six German states and covered a span from 1994 to 1998. Milk yield, fat, and protein percentage were recorded for all of the morning and evening milkings. Seven statistical models were fitted to the data to derive formulas for estimating daily yields from morning or evening yields. In general, use of evening milkings less accurately estimated yields than did use of morning milkings. Among the three yield traits the lowest accuracy of estimation of daily yield was found for fat yield. Although the models do not differ much in the correlation between estimated and true daily yields, systematic under- and overestimation of daily yield at the beginning and end of lactation were observed in all models with the exception of model 6, which accounted for heterogeneous variances by parity class, milking interval class, and lactation stage by fitting separate regression formulas within each combination of the three factors. A study to validate the models showed that model 6 is also robust for the analyzed populations. Smoothing model 6 regression formulas across lactation stages caused a systematic pattern of estimation error, although loss in accuracy was minimal by fitting far fewer parameters in the regression formulas. Differences in the accuracy of alternate milking schemes to predict daily yields were found between traits, between morning and evening milkings, and between parity classes. Compared with true daily yields from different lactation stages, variances and correlations of the estimated yields were reduced, which must be accounted for in genetic evaluation. The use of estimated daily yields from morning or evening milkings has a smaller impact on estimated breeding values of bulls than cows. As a result of lower heritability and repeatability of estimated daily yields than true daily yields, the weight on own test-day records for estimating cows' breeding values is lower when cows are in a.m.-p.m. than conventional monthly testing schemes. However, the difference in the weights between estimated and true daily yields decreases as lactation progresses. Use of estimated daily yields is less reliable for estimating breeding value than use of true daily yields.
Effects on fatty acid profiles and milk fat yield due to dietary concentrate and supplemental 18:3n-3 were evaluated in 4 lactating Holstein cows fed a low- (35:65 concentrate:forage; L) or high- (65:35; H) concentrate diet without (LC, HC) added oil or with linseed oil (LCO, HCO) at 3% of DM. A 4 x 4 Latin square with four 4-wk periods was used. Milk yield and dry matter intake averaged 26.7 and 20.2 kg/d, respectively, across treatments. Plasma acetate and beta-hydroxybutyrate decreased, whereas glucose, nonesterified fatty acids, and leptin increased with high-concentrate diets. Milk fat percentage was lower in cows fed high-concentrate diets (2.31 vs. 3.38), resulting in decreases in yield of 11 (HC) and 42% (HCO). Reduced yields of 8:0-16:0 and cis9-18:1 fatty acids accounted for 69 and 17%, respectively, of the decrease in milk fat yield with HC vs. LC (-90 g/d), and for 26 and 33%, respectively, of the decrease with HCO vs. LCO (-400 g/d). Total trans-18:1 yield increased by 25 (HCO) and 59 (LCO) g/d with oil addition. Trans10-18:1 yield was 5-fold greater with high-concentrate diets. Trans11-18:1 increased by 13 (HCO) and 19 (LCO) g/d with oil addition. Trans13+14-18:1 yield increased by 9 (HCO) and 18 (LCO) g/d with linseed oil. Yield of total conjugated linoleic acids (CLA) in milk averaged 6 g/d with LC or HC compared with 14 g/d with LCO or HCO. Cis9,trans11-CLA yield was not affected by concentrate level but increased by 147% in response to oil. Feeding oil increased yields of trans11,cis13-, trans11,trans13-, and trans,trans-CLA, primarily with LCO. Trans10,cis12-CLA yield (average of 0.08 g/d) was not affected by treatments. Yield of trans11,cis15-18:2 was 1 g/d in cows fed LC or HC and 10 g/d with LCO or HCO. Yields of cis9,trans11-18:2, cis9,trans12-18:2, and cis9,trans13-18:2 were positively correlated (r = 0.74 to 0.94) with yields of trans11-18:1, trans12-18:1, and trans13+14-18:1, respectively. Plasma concentrations of biohydrogenation intermediates with concentrate or linseed oil level followed similar changes as those in milk fat. Milk fat depression was observed when HC induced an increase in trans10-18:1 yield. A correlation of 0.84 across 31 comparisons from 13 published studies, including the present one, was found among the increase in percentage of trans10-18:1 in milk fat and decreased milk fat yield. We observed, however, more drastic milk fat depression when HCO increased yields of total trans-18:1, trans11,cis15-18:2, trans isomers of 18:3, and reduced yields of 18:0 plus cis9-18:1.
The compressive yield strain was measured for 61 specimens of bovine cancellous bone from three distal femora. There was no significant relationship (p = 0.08, R2 = 0.051) between yield strain and the degree of trabecular orientation. There was a significant positive correlation (p less than 0.00001, R2 = 0.319) between yield strain and structural (apparent) density and significant negative correlation (p less than 0.0025, R2 = 0.145) between yield strain and bone density. Yield strain correlated best with bone solid volume fraction Vv (epsilon y = 0.592 +2- 1.446vv, R2 = 0.337). The quantity, yield strain, is highly dependent on specific definitions of the yield point and the point of zero strain. For this study the yield point was defined by a 0.0003 offset criterion, and the point of zero strain was defined as the point where the tangent at 15 percent of yield crosses zero. The results using these definitions were compared with results using yield strain values determined by other definitions of the yield point and zero strain. The correlations between yield strain and trabecular orientation, structural density and bone density changed very little for differing definitions of yield. The results suggest that yield strain in cancellous bone is isotropic or independent of textural anisotropy, so the yield behaviour may be characterized by a maximum strain yield criterion. The results also suggest that the primary mode of yield in cancellous bone is buckling of the trabeculae.
Pseudomonas aeruginosa 142 and a presumed variant were grown axenically in chemostats on salicylate/benzoate or salicylate/glucose binary feeds. Each substrate was supplied at 2, 10, 50, 90, 98, or 100% of the total energy flux. Two experiments were also run with ternary mixtures using the same substrates. Aliquots were transferred to fed-batch reactors receiving the same substrates at the same specific rates as the chemostat, but with one substrate radiolabeled with 14C. Radiolabel incorporated into biomass, 14CO2, and soluble microbial products over a period of 8 minutes was used to establish the biomass yield, CO2 yield, and product yield, respectively, associated with a given substrate. The effect of the percent substrate in the feed on the yields depended on the pair of substrates supplied. When benzoate comprised 50% or more of the applied substrate in salicylate/benzoate feeds, the fraction of benzoate in the feed had a small effect on the yield values associated with benzoate. However, when benzoate constituted 2% or 10% of the feed, CO2 yields were lower, biomass yields were slightly lower, and product yields were higher. In contrast, the percent of salicylate in the feed had little effect on any of the salicylate yields for cells growing on the salicylate/benzoate feeds. When salicylate was mixed with glucose, the yields associated with salicylate behaved quite differently. Biomass and CO2 yields were lower and product yields higher when salicylate was 2% or 10% of the feed than when it was higher. In the same substrate mixtures, glucose-based biomass yields were higher and CO2 yields were lower when glucose constituted 2% or 10% of the feed but were constant for higher percentages. The results suggest that the fate of a substrate is relatively independent of the feed composition as long as the substrate in question constitutes a significant percentage of the mixture. Thus, in those situations the assumption of a constant biomass yield in multicomponent substrate modeling is justified. However, when a given substrate constitutes a small percentage of the feed, significant changes in yield may occur.
OBJECTIVES: Capsule endoscopy (CE) allows for direct evaluation of the small bowel mucosa in patients with Crohn's disease (CD). A number of studies have revealed significantly improved yield for CE over other modalities for the diagnosis of CD, but as sample sizes have been small, the true degree of benefit is uncertain. Additionally, it is not clear whether patients with a suspected initial presentation of CD and those with suspected recurrent disease are equally likely to benefit from CE. The aim of this study was to evaluate the yield of CE compared with other modalities in symptomatic patients with suspected or established CD using meta-analysis. METHODS: We performed a recursive literature search of prospective studies comparing the yield of CE to other modalities in patients with suspected or established CD. Data on yield among various modalities were extracted, pooled, and analyzed. Incremental yield (IY) (yield of CE--yield of comparative modality) and 95% confidence intervals (95% CI) of CE over comparative modalities were calculated. Subanalyses of patients with a suspected initial presentation of CD and those with suspected recurrent disease were also performed. RESULTS: Nine studies (n = 250) compared the yield of CE with small bowel barium radiography for the diagnosis of CD. The yield for CE versus barium radiography for all patients was 63% and 23%, respectively (IY = 40%, p < 0.001, 95% CI = 28-51%). Four trials compared the yield of CE to colonoscopy with ileoscopy (n = 114). The yield for CE versus ileoscopy for all patients was 61% and 46%, respectively (IY = 15%, p= 0.02, 95% CI = 2-27%). Three studies compared the yield of CE to computed tomography (CT) enterography/CT enteroclysis (n = 93). The yield for CE versus CT for all patients was 69% and 30%, respectively (IY = 38%, p= 0.001, 95% CI = 15-60%). Two trials compared CE to push enteroscopy (IY = 38%, p < 0.001, 95% CI = 26-50%) and one trial compared CE to small bowel magnetic resonance imaging (MRI) (IY = 22%, p= 0.16, 95% CI =-9% to 53%). Subanalysis of patients with a suspected initial presentation of CD showed no statistically significant difference between the yield of CE and barium radiography (p= 0.09), colonoscopy with ileoscopy (p= 0.48), CT enterography (p= 0.07), or push enteroscopy (p= 0.51). Subanalysis of patients with established CD with suspected small bowel recurrence revealed a statistically significant difference in yield in favor of CE compared with all other modalities (barium radiography (p < 0.001), colonoscopy with ileoscopy (p= 0.002), CT enterography (p < 0.001), and push enteroscopy (p < 0.001)). CONCLUSIONS: In study populations, CE is superior to all other modalities for diagnosing non-stricturing small bowel CD, with a number needed to test (NNT) of 3 to yield one additional diagnosis of CD over small bowel barium radiography and NNT = 7 over colonoscopy with ileoscopy. These results are due to a highly significant IY with CE over all other modalities in patients with established non-stricturing CD being evaluated for a small bowel recurrence. While there was no significant difference seen between CE and alternate modalities for diagnosing small bowel CD in patients with a suspected initial presentation of CD, the trend toward significance for a number of modalities suggests the possibility of a type II error. Larger studies are needed to better establish the role of CE for diagnosing small bowel CD in patients with a suspected initial presentation of CD.