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The influence of beef cow weaning weight ratio and cow size on feed intake behavior, milk production, and milk composition

The influence of beef cow weaning weight ratio and cow size on feed intake behavior, milk... Downloaded from https://academic.oup.com/tas/article-abstract/2/suppl_1/S79/5108322 by Ed 'DeepDyve' Gillespie user on 16 October 2018 The influence of beef cow weaning weight ratio and cow size on feed intake behavior, milk production, and milk composition † † † Alyson R. Williams,* Cory T. Parsons, Julia M. Dafoe, Darrin L. Boss, ,2 Jan G. P. Bowman,* and Timothy DelCurto* *Department of Animal and Range Sciences, Montana State University, Bozeman, MT 59717; and Northern Agricultural Research Center, Montana State University, Havre, MT 59501 © The Author(s) 2018. Published by Oxford University Press on behalf of the American Society of Animal Science. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com. Transl. Anim. Sci. 2018.2:S79–S83 doi: 10.1093/tas/txy044 constituents have also been attributed to influence calf INTRODUCTION preweaning ADG but have not been revisited in recent Techniques that identify which beef cows in a pro- years (Totusek et  al., 1973; Mondragon et  al., 1983; duction setting will produce more calf weight weaned Beal et al., 1990). Furthermore, as defined by WWR, per kilogram of feed consumed, often termed cow ef- the effects milk production has on preweaning calf ficiency, has long been sought after in both beef cattle growth and the influence of cow feed intake on cow ef - production settings and research (Dinkel and Brown, ficiency has not been jointly considered. Therefore, the 1978; Scasta et al., 2015; Beck et al., 2016). Previous re- purpose of this study was to evaluate cow–calf WWR, search and applied practice has suggested the ratio of and within WWR, cow size influences on feed intake, calf weight weaned to cow weight, or weaning weight milk production and composition, and subsequent ratio (WWR), is a potential metric to estimate cow ef- calf preweaning performance. ficiency ( Dinkel and Brown, 1978; Kress et al., 2001; Scasta et al., 2015). However, previous research either MATERIALS AND METHODS considered the direct ratio of calf weight weaned to Protocols for this research were approved by cow weight or considered the additional effect of cow the Montana State University Agricultural Animal intake but utilized individual feed bunks with limited Care and Use Committee (#2018-AA02). Lifetime feeding times or fecal markers to estimate cow intake production records from cows with a minimum of (Davis et al., 1983; Kirkpatrick et al., 1985; Kress et al., three calf crops and bred for the forth calf from the 2001). With modern technology (e.g., automated feed Montana State University Northern Agriculture bunks and EID tags), it is easier to acquire accurate, in- Research Center Angus and Angus cross cow herd dividual feed intake data that may include feed intake were used to identify high and low WWR groups. behavior attributes (e.g., time spent feeding, number All calf data were corrected for age of dam, sex of feeding visits per day, and intake per visit), not pre- of calf and equalized to a 205-d adjusted wean- viously reported in the literature. Milk yield and milk ing weight. Likewise, cow weights were adjusted to a standardized body condition before calcu- Appreciation is expressed to the Nancy Cameron lating WWR. All of the multiparous (minimum Endowment, the Bair Ranch Foundation, and the Montana of three weaned calves), Angus cow–calf pairs Stock Growers Association for research funding, and to the (cow initial BW  =  598  ±  55.7  kg) were stratified employees of MSU Northern Agricultural Research Center, for their assistance with this project. by WWR and randomly allotted to high and low Corresponding author: timothy.delcurto@montana.edu WWR (whole plot; ± 0.75 SD from herd mean) Received March 16, 2018. and, within WWR classification groups, allotted to Accepted April 14, 2018. light and heavy weight groups. Because WWR was S79 Downloaded from https://academic.oup.com/tas/article-abstract/2/suppl_1/S79/5108322 by Ed 'DeepDyve' Gillespie user on 16 October 2018 S80 Williams et al. correlated to cow size with smaller cows typically diet designed to meet NRC requirements when con- having higher WWR, cow size was evaluated within sumed at 2.5% of BW (Table 1; CHS Nutrition, Sioux WWR groups. This resulted in a randomized split-plot Falls, SD). Diets were provided in eight design with the following four classification groups: SmartFeedPro feeders, which were fully contained 1)  high WWR–light BW (HL; 57% ± 3% WWR; within two portable trailers (C-Lock Inc., Rapid 509 ± 8.6 kg), 2) high WWR–heavy BW (HH; 54% ± City, SD). Cow–calf pairs had continuous access 1% WWR; 544 ± 16 kg), 3) low WWR–light BW (LL; to water throughout the study period. BW were 42% ± 4% WWR; 591  ±  9  kg), and 4)  low WWR– recorded for the cows and calves, and BCS were heavy BW (LH; 43% ± 2% WWR; 632  ±  12  kg). taken following a 16-h shrink prior to the start of Cow–calf pairs were contained in a dry-lot and fed ad the trial (Table  2). The trial consisted of a 14-d libitum a commercially available pelleted grass/alfalfa adaption period followed by a 7-d data collection period. Only cows that had calved within the first 3-wk of calving were used and mean calf age at trial Table 1. Ingredient and nutrient composition (DM initiation was 66.2 ± 2.8 d post partum (Table 2). As basis) of the fully fortified, alfalfa pellets fed fed, individual cow average daily feed consumption (DFC), average daily feeding bout duration (FBD), Item % number of visits per day (NOV), and time of day Ingredients (TOD) feeding bouts occurred were collected. On Alfalfa, hay 79.3 Corn, ground 20.0 the last day of the feed trial, a weigh-suckle-weigh Trace mineral mix* 0.2 procedure was conducted following the procedures Nutrient composition suggested by Williams et al. (1979). In addition to the DM 91.1 weigh-suckle-weigh protocol, 100 mL milk samples CP 14.7 were collected from each cow, immediately placed NDF 34.4 on ice, and transported to the Montana Central ADF 26.3 Milk Laboratory (Montana Veterinary Diagnostic Ash 7.8 Laboratory, Montana Department of Livestock, *Trace mineral mix: 1.4% Ca, 0.28% P, 0.07% Na, 2.0% K, 0.3% Mg, Bozeman, MT) where the samples were analyzed for 52.3  ppm Mn, 331.0  ppm Fe, 27.4  ppm Cu, 73.4  ppm Zn, 0.4  ppm Co, fat, solids not fat (SNF), total solids (TS), protein, 1.6 ppm I, 0.4 ppm Se, 8.4 ppm organic Mn, 6.3 ppm organic Cu, 18.75 ppm organic Zn, 1.0 IU/kg vitamin A, 0.1 IU/kg vitamin D, 1.7 IU/kg vitamin E. Table 2. Cow BW, cow BCS, cow age, calf BW, calf birth weight, and weight ratio (WR) between calf and cow weight pre and post adaption and feed trial period † ‡ § ¶ High* Low WP SP WP * SP Item Light Heavy Light Heavy SE P value P value P value Start trial a b c cd Cow BW, kg 536.4 586.6 627.7 645.1 11.9 <0.01 <0.01 0.18 Cow BCS 4.8 5 5.2 5.2 0.2 <0.06 0.53 0.75 Cow age, yr 7 7 8 9 0.6 <0.03 0.87 0.52 Calf wt, kg 104.1 104.7 96.6 99.1 4.1 0.11 0.70 0.82 Calf birth wt, kg 42.3 45.2 47.2 42.4 1.6 0.53 0.54 <0.03 Calf age, d 69.3 65.5 66.6 63.4 2.8 0.40 0.22 0.92 ║ a b bc WR, % 19.4 18 15.4 15.5 0.8 <0.01 0.44 0.38 October, 2017 a b Weaning wt, kg 278.5 289.1 257.1 280.7 7.6 <0.09 <0.04 0.40 & a ab c bcd WWR, % 51.6 49.3 41.1 43.9 12.7 <0.01 0.87 0.14 *High = high WWR cows. Low = low WWR cows. Whole plot = cow WWR. Split-plot = cow BW. Whole-split-plot interaction was the interaction between WWR and cow BW. WR = weight ratio at start of trial, calf weight/cow weight. WWR = calf 205-d weaning wt/cow wt at weaning. P values were considered significant at ≤0.05 and were considered as a trend toward significance at ≤0.1. a–d Means within a row with different superscripts differ (P ≤ 0.05). Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/suppl_1/S79/5108322 by Ed 'DeepDyve' Gillespie user on 16 October 2018 Beef cattle weaning ratio and cow size S81 and lactose content. Milk yield was calculated using WWR, were effective in predicting future per- calf weights from the weigh-suckle-weigh protocol. formance. Calf birth weight (44.3  ±  1.6  kg), calf age (66.2  ±  2.8 d) and calf weight start of trial (101.1  ±  4.1  kg) were not different between cow Statistical Analysis classification groups (P > 0.10; Table 2). Calf 205- Individual cow was the experimental unit. Feed d, adjusted weaning weights, taken October 2017, trial data were analyzed as a randomized split-plot were significantly affected by cow BW classifica - design using the PROC MIXED procedure in SAS tion group (276.4 ± 7.6 kg; P < 0.04); however, cow (v. 9.4; SAS Inst. Inc., Cary, NC). Dependent vari- WWR classification tended to effect calf weaning ables were DFC, FBD, NOV, TFC, and TSE. The weight (P  <  0.09; Table  2). Cow WWR classifica - PROC FREQ procedure in SAS was used to de- tion had a significant effect on 2017 cow–calf WWR termine TOD of feeding bouts. Three cows were (P < 0.01), with high WWR classified cows wean - removed from this analysis due to either EID tag ing 50.5% and low WWR classified cows weaning failure and/or unacceptable feed intake variation 42.5% (Table 2). This suggests that cows with higher (>30%). Milk data were analyzed as a randomized WWR may be able to transfer feed nutrients more split-plot design using the PROC MIXED pro- efficiently to their calves from birth to weaning. cedure in SAS. Fat, SNF, TS, protein, and lactose Although cow WWR did not affect feed in- were set as dependent variables. When WWR inter- take expressed as kg per day, cow weight influenced acted with cow size, means were separated using the DFC (P  <  0.01) with heavy cows within WWR LSMEANS procedure of SAS and a Tukey–Kramer groups consuming an average of 6.1 kg more than test was included in both MIXED procedures. P light cows (Table  3). Similar results of heavy cows values ≤0.05 were considered significant and P val- consuming considerably more feed than light cows ues >0.05 and ≤0.10 were considered a tendency. while lactating were reported by Walker et al. (2015) and in nonlactating heifers by Waghorn et al. (2012). RESULTS AND DISCUSSION When expressed as g feed/kg cow BW, however, cow WWR had a significant effect and BW tended to As expected, cow BWs at the beginning effect feed intake (P < 0.02 and P < 0.06, respect- (HL 536.4  ±  25.3  kg; HH 586.6  ±  49.9  kg; LL ively). High WWR cows consumed 34.9  g of feed 627.7  ±  29.2  kg; LH 645.1  ±  33.6  kg) of the trial per kg of BW, whereas low WWR cows consumed were significantly affected by WWR ( P  <  0.01) 30.4  g of feed per kg BW. Heavy cows consumed and BW (P < 0.01) classification groups ( Table 2). 34.2 g and light cows consumed 31.0 g of feed per Additionally, there was a significant difference kg BW (Table  3). Although high WWR cows and (P  <  0.01) in cow–calf weight ratio between high heavy cows consumed more feed per kg of BW than WWR (18.7%) and low WWR (15.5%) cows at the low WWR and light cows, these two groups also initiation of the study (Table  2), suggesting cow had calves that gained more. Possibly suggesting classification protocols, based on previous years Table 3. Cow feed intake and feeding behavior from 16 to 23 May 2017 trial † ‡ § ¶ High* Low WP SP WP * SP Item Light Heavy Light Heavy SE P value P value P value Intake Daily, kg 18.2 20.8 17.6 21.1 0.97 0.98 <0.01 0.69 g/kg cow BW 33.9 35.8 28.1 32.6 1.6 <0.02 <0.06 0.41 Feeding bouts Number/day 31.5 35.1 29.8 31.3 3.3 0.41 0.44 0.76 Duration, min 2.4 2.5 2.65 2.1 0.01 0.11 <0.02 0.39 Total time eating, min 617.6 614.7 452.2 547.1 68 0.08 0.51 0.48 *High = high WWR group. Low = low WWR group. Whole plot = cow WWR. Split-plot = cow BW. Whole-split-plot interaction was the interaction between WWR and cow BW. P values were considered significant at ≤0.05 and were considered as a trend toward significance at ≤0.1. Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/suppl_1/S79/5108322 by Ed 'DeepDyve' Gillespie user on 16 October 2018 S82 Williams et al. that cows classified as high WWR transfer the add - the stimulus of the feeders being filled, as feeding itional feed energy to the calf. occurred between 0800 and 0900 h, daily. Cow BW had a significant effect on average The interaction between cow WWR and FBD (P < 0.02) with light cows eating an average cow BW was observed in respect to milk lac- of 29  s longer per feeding bout than heavy cows tose content (P  <  0.01). High WWR–heavy BW (Table 3). Hafla et al. (2013) reported that low RFI cows had 0.4% more milk lactose than LH cows heifers spent less time feeding than high RFI heif- (P < 0.05) and LL cows tended to have 0.3% more ers, although no significant difference was reported milk lactose than LH cows (P  =  0.093; Table  5). in heifer BW. The highest number of feeding bouts, Percent milk lactose (mean 4.9  ±  0.2) and per- when day was broken into six, 4-h periods, occurred cent fat (3.7  ±  0.1) were comparable to percent in the evening (1700 to 2000 h; Table 4). However, milk lactose and milk fat reported by Mondragon the single hour with the highest number of visits et  al. (1983). Total solids (10.6  ±  0.3) and SNF was 0800 to 0900 h. This was most likely caused by (9.3 ± 0.2) were comparable to results reported by Table 4. Time of day feeding events occurred, categorized by six, 4-h periods: early morning (0100–0400 h), morning (0500–0800 h), late morning (0900–1200 h), afternoon (1300–1600 h), evening (1700–2000 h), and night (2100–0000 h) † ‡ § ¶ High* Low WP SP WP * SP Item Light Heavy Light Heavy SE P value P value P value Time of day Early morning 95 116 66 81 6.0 0.18 0.45 0.90 Morning 408 461 321 382 31.3 0.49 0.66 0.98 Late morning 517 475 325 377 12.6 <0.01 0.92 0.37 Afternoon 426 480 336 417 13.0 0.16 0.22 0.80 Evening 549 639 447 530 17.0 0.14 0.23 0.96 Night 207 280 173 176 23.5 0.45 0.70 0.72 *High = high WWR group. Low = low WWR group. Whole plot = cow WWR. Split-plot = cow BW. Whole-split-plot interaction was the interaction between WWR and cow BW. P values were considered significant at ≤0.05 and were considered as a trend toward significance at ≤0.1. Table 5. Milk analysis results † ‡ § ¶ High* Low WP SP WP * SP Item Light Heavy Light Heavy SE P value P value P value Milk yield Yield, kg 2.1 2.4 1.4 2 0.28 <0.08 0.11 0.45 g/kg cow BW 3.92 4.09 2.14 3.18 0.5 <0.02 0.23 0.39 Milk constituents Fat, % 1.8 1.1 1.2 1.3 0.3 0.46 0.34 0.25 SNF, % 9.3 9.4 9.3 9.1 0.14 0.28 0.84 0.35 TS, % 11 10.6 10.5 10.4 0.29 0.21 0.39 0.49 Protein, % 3.8 3.7 3.6 3.7 0.11 0.34 0.72 0.19 a b Lactose, % 4.8 5.1 5 4.7 0.1 0.57 0.83 <0.01 *High = high WWR group. Low = low WWR group. Whole plot = cow WWR. Split-plot = cow BW. Whole-split-plot interaction was the interaction between WWR and cow BW. P values were considered significant at ≤0.05 and were considered as a trend toward significance at ≤0.1. a,b Means within a row with different superscripts differ (P ≤ 0.05). Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/suppl_1/S79/5108322 by Ed 'DeepDyve' Gillespie user on 16 October 2018 Beef cattle weaning ratio and cow size S83 Beck, P. A., C. B.  Stewart, M. S.  Gadberry, M.  Haque, and Melton et  al. (1967). However, previous studies J.  Biermacher. 2016. Effect of mature body weight and have reported that milk constituents were not cor- stocking rate on cow and calf performance, cow herd effi - related to calf ADG or preweaning growth (Jeffery ciency, and economics in the southeastern United States. J. and Berg, 1971; Totusek et al., 1973; Mondragon Anim. Sci. 94:1689–1702. doi:10.2527/jas.2015-0049 et  al., 1983). Results from this research indicated Davis, M., J. Rutledge, L. Cundiff, and E. Hauser. 1983. Life cycle efficiency of beef production: II. Relationship of cow a WWR and cow BW interaction (P  <  0.05) in efficiency ratios to traits of the dam and progeny weaned. respect to milk lactose content, suggesting that J. Anim. Sci. 57:852–866. doi:10.2527/jas1983.574852x lactose content could influence calf preweaning Dinkel, C. A., and M. A. Brown. 1978. An evaluation of the growth. Additionally, previous studies examining ratio of calf weight to cow weight as an indicator of milk production in beef cows attribute milk yield cow efficiency. J. Anim. Sci. 46:614–617. doi:10.2527/ as an important factor in calf preweaning growth jas1978.463614x Hafla, A., G.  Carstens, T.  Forbes, L.  Tedeschi, J.  Bailey, (Williams et  al., 1979; Mondragon et  al., 1983; J.  Walter, and J.  Johnson. 2013. Relationships between Beal et al., 1990). Results from this research sug- postweaning residual feed intake in heifers and forage gest that high cow WWR tended (P = 0.08) to be use, body composition, feeding behavior, physical activity, higher in milk production and were higher in milk and heart rate of pregnant beef females. J. Anim. Sci. 91: production (P  <  0.05) when expressed on a BW 5353–5365. doi:10.2527/jas.2013–6423 Jeffery, H., and R.  Berg. 1971. Evaluation of milk variables basis. In contrast, cow BW did not influence milk as measures of milk effect on preweaning performance yield within WWR cow groups (P > 0.10; Table 5). of beef cattle. Can. J.  Anim. Sci. 51:21–30. doi:10.4141/ Milk yield reported in this research was consist- cjas71-003 ently lower than milk yield reported in other Kirkpatrick, B. W ., C. A. Dinkel, J. J. Rutledge, and E. R. Hauser. studies using weigh-suckle-weigh or machine 1985. Prediction equations of beef cow efficiency. J. Anim. milking techniques at comparable days post par- Sci. 60:964–969. doi:10.2527/jas1985.604964x Kress, D. D., D. C.  Anderson, J. D.  Stevens, E. T.  Miller, tum (Totusek et al., 1973; Mondragon et al., 1983; T. S.  Hirsch, J. E.  Sprinkle, K. C.  Davis, D. L.  Boss, Walker et al., 2015). D. W.  Bailey, R. P.  Ansotegui, et  al. 2001. Calf weight/ cow weight ratio at weaning as a predictor of beef cow IMPLICATIONS efficiency. Proc. Americ. Soci. Anim. Sci. West. Sec. 52:130–132. Results from this research provide additional Melton, A., J.  Riggs, L.  Nelson, and T.  Cartwright. 1967. information on how cow size, cow–calf WWR, Milk production, composition and calf gains of Angus, and milk production affect cow and production Charolais and Hereford cows. J. Anim. Sci. 26:804–809. doi:10.2527/jas1967.264804x efficiency. Overall, these results indicated that Mondragon, I., J. Wilton, O. Allen, and H. Song. 1983. Stage cows classified as high WWR consumed more of lactation effects, repeatabilities and influences on wean - feed on a g/kg BW bases. Also, cow WWR classi- ing weights of yield and composition of milk in beef cat- fication only had a tendency to affect calf weight tle. Can. J. Anim. Sci. 63:751–761. doi:10.4141/cjas83-090 at weaning whereas cow body size, when consid- Scasta, J. D., L.  Henderson, and T.  Smith. 2015. Drought ered within WWR classifications, had a significant effect on weaning weight and efficiency relative to cow size in semiarid rangeland. J. Anim. Sci. 93:5829–5839. effect. Milk lactose content was effected by the doi:10.2527/jas.2015–9172 interaction between cow weight and WWR clas- Totusek, R., D. W. Arnett, G. Holland, and J. Whiteman. 1973. sification, suggesting that heavy cows classified as Relation of estimation method, sampling interval and high WWR tend to produce more milk lactose, milk composition to milk yield of beef cows and calf gain. which could effect preweaning calf growth. In J. Anim. Sci. 37:153–158. doi:10.2527/jas1973.371153x Waghorn, G., K.  Macdonald, Y.  Williams, S.  Davis, and conclusion, the use of cow–calf WWR as a metric R. Spelman. 2012. Measuring residual feed intake in dairy of cow efficiency needs to be used with caution heifers fed an alfalfa (Medicago sativa) cube diet. J. Dairy because of potential increases in intake, milk pro- Sci. 95:1462–1471. doi:10.3168/jds.2011–4670 duction, and a potential bias to cow age and size. Walker, R., R. Martin, G. Gentry, and L. Gentry. 2015. Impact of cow size on dry matter intake, residual feed intake, metabolic response, and cow performance. J. Anim. Sci. LITERATURE CITED 93:672–684. doi:10.2527/jas.2014–7702 Beal, W., D. R. Notter, and R. Akers. 1990. Techniques for es- Williams, J., D.  Anderson, and D.  Kress. 1979. Milk produc- timation of milk yield in beef cows and relationships of tion in Hereford cattle. I. Effects of separation interval on milk yield to calf weight gain and postpartum reproduc- weigh-suckle-weigh milk production estimates. J. Anim. tion. J. Anim. Sci. 68:937–943. doi:10.2527/1990.684937x Sci. 49:1438–1442. doi:10.2527/jas1979.4961438x Translate basic science to industry innovation http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Translational Animal Science Oxford University Press

The influence of beef cow weaning weight ratio and cow size on feed intake behavior, milk production, and milk composition

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© The Author(s) 2018. Published by Oxford University Press on behalf of the American Society of Animal Science.
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Downloaded from https://academic.oup.com/tas/article-abstract/2/suppl_1/S79/5108322 by Ed 'DeepDyve' Gillespie user on 16 October 2018 The influence of beef cow weaning weight ratio and cow size on feed intake behavior, milk production, and milk composition † † † Alyson R. Williams,* Cory T. Parsons, Julia M. Dafoe, Darrin L. Boss, ,2 Jan G. P. Bowman,* and Timothy DelCurto* *Department of Animal and Range Sciences, Montana State University, Bozeman, MT 59717; and Northern Agricultural Research Center, Montana State University, Havre, MT 59501 © The Author(s) 2018. Published by Oxford University Press on behalf of the American Society of Animal Science. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com. Transl. Anim. Sci. 2018.2:S79–S83 doi: 10.1093/tas/txy044 constituents have also been attributed to influence calf INTRODUCTION preweaning ADG but have not been revisited in recent Techniques that identify which beef cows in a pro- years (Totusek et  al., 1973; Mondragon et  al., 1983; duction setting will produce more calf weight weaned Beal et al., 1990). Furthermore, as defined by WWR, per kilogram of feed consumed, often termed cow ef- the effects milk production has on preweaning calf ficiency, has long been sought after in both beef cattle growth and the influence of cow feed intake on cow ef - production settings and research (Dinkel and Brown, ficiency has not been jointly considered. Therefore, the 1978; Scasta et al., 2015; Beck et al., 2016). Previous re- purpose of this study was to evaluate cow–calf WWR, search and applied practice has suggested the ratio of and within WWR, cow size influences on feed intake, calf weight weaned to cow weight, or weaning weight milk production and composition, and subsequent ratio (WWR), is a potential metric to estimate cow ef- calf preweaning performance. ficiency ( Dinkel and Brown, 1978; Kress et al., 2001; Scasta et al., 2015). However, previous research either MATERIALS AND METHODS considered the direct ratio of calf weight weaned to Protocols for this research were approved by cow weight or considered the additional effect of cow the Montana State University Agricultural Animal intake but utilized individual feed bunks with limited Care and Use Committee (#2018-AA02). Lifetime feeding times or fecal markers to estimate cow intake production records from cows with a minimum of (Davis et al., 1983; Kirkpatrick et al., 1985; Kress et al., three calf crops and bred for the forth calf from the 2001). With modern technology (e.g., automated feed Montana State University Northern Agriculture bunks and EID tags), it is easier to acquire accurate, in- Research Center Angus and Angus cross cow herd dividual feed intake data that may include feed intake were used to identify high and low WWR groups. behavior attributes (e.g., time spent feeding, number All calf data were corrected for age of dam, sex of feeding visits per day, and intake per visit), not pre- of calf and equalized to a 205-d adjusted wean- viously reported in the literature. Milk yield and milk ing weight. Likewise, cow weights were adjusted to a standardized body condition before calcu- Appreciation is expressed to the Nancy Cameron lating WWR. All of the multiparous (minimum Endowment, the Bair Ranch Foundation, and the Montana of three weaned calves), Angus cow–calf pairs Stock Growers Association for research funding, and to the (cow initial BW  =  598  ±  55.7  kg) were stratified employees of MSU Northern Agricultural Research Center, for their assistance with this project. by WWR and randomly allotted to high and low Corresponding author: timothy.delcurto@montana.edu WWR (whole plot; ± 0.75 SD from herd mean) Received March 16, 2018. and, within WWR classification groups, allotted to Accepted April 14, 2018. light and heavy weight groups. Because WWR was S79 Downloaded from https://academic.oup.com/tas/article-abstract/2/suppl_1/S79/5108322 by Ed 'DeepDyve' Gillespie user on 16 October 2018 S80 Williams et al. correlated to cow size with smaller cows typically diet designed to meet NRC requirements when con- having higher WWR, cow size was evaluated within sumed at 2.5% of BW (Table 1; CHS Nutrition, Sioux WWR groups. This resulted in a randomized split-plot Falls, SD). Diets were provided in eight design with the following four classification groups: SmartFeedPro feeders, which were fully contained 1)  high WWR–light BW (HL; 57% ± 3% WWR; within two portable trailers (C-Lock Inc., Rapid 509 ± 8.6 kg), 2) high WWR–heavy BW (HH; 54% ± City, SD). Cow–calf pairs had continuous access 1% WWR; 544 ± 16 kg), 3) low WWR–light BW (LL; to water throughout the study period. BW were 42% ± 4% WWR; 591  ±  9  kg), and 4)  low WWR– recorded for the cows and calves, and BCS were heavy BW (LH; 43% ± 2% WWR; 632  ±  12  kg). taken following a 16-h shrink prior to the start of Cow–calf pairs were contained in a dry-lot and fed ad the trial (Table  2). The trial consisted of a 14-d libitum a commercially available pelleted grass/alfalfa adaption period followed by a 7-d data collection period. Only cows that had calved within the first 3-wk of calving were used and mean calf age at trial Table 1. Ingredient and nutrient composition (DM initiation was 66.2 ± 2.8 d post partum (Table 2). As basis) of the fully fortified, alfalfa pellets fed fed, individual cow average daily feed consumption (DFC), average daily feeding bout duration (FBD), Item % number of visits per day (NOV), and time of day Ingredients (TOD) feeding bouts occurred were collected. On Alfalfa, hay 79.3 Corn, ground 20.0 the last day of the feed trial, a weigh-suckle-weigh Trace mineral mix* 0.2 procedure was conducted following the procedures Nutrient composition suggested by Williams et al. (1979). In addition to the DM 91.1 weigh-suckle-weigh protocol, 100 mL milk samples CP 14.7 were collected from each cow, immediately placed NDF 34.4 on ice, and transported to the Montana Central ADF 26.3 Milk Laboratory (Montana Veterinary Diagnostic Ash 7.8 Laboratory, Montana Department of Livestock, *Trace mineral mix: 1.4% Ca, 0.28% P, 0.07% Na, 2.0% K, 0.3% Mg, Bozeman, MT) where the samples were analyzed for 52.3  ppm Mn, 331.0  ppm Fe, 27.4  ppm Cu, 73.4  ppm Zn, 0.4  ppm Co, fat, solids not fat (SNF), total solids (TS), protein, 1.6 ppm I, 0.4 ppm Se, 8.4 ppm organic Mn, 6.3 ppm organic Cu, 18.75 ppm organic Zn, 1.0 IU/kg vitamin A, 0.1 IU/kg vitamin D, 1.7 IU/kg vitamin E. Table 2. Cow BW, cow BCS, cow age, calf BW, calf birth weight, and weight ratio (WR) between calf and cow weight pre and post adaption and feed trial period † ‡ § ¶ High* Low WP SP WP * SP Item Light Heavy Light Heavy SE P value P value P value Start trial a b c cd Cow BW, kg 536.4 586.6 627.7 645.1 11.9 <0.01 <0.01 0.18 Cow BCS 4.8 5 5.2 5.2 0.2 <0.06 0.53 0.75 Cow age, yr 7 7 8 9 0.6 <0.03 0.87 0.52 Calf wt, kg 104.1 104.7 96.6 99.1 4.1 0.11 0.70 0.82 Calf birth wt, kg 42.3 45.2 47.2 42.4 1.6 0.53 0.54 <0.03 Calf age, d 69.3 65.5 66.6 63.4 2.8 0.40 0.22 0.92 ║ a b bc WR, % 19.4 18 15.4 15.5 0.8 <0.01 0.44 0.38 October, 2017 a b Weaning wt, kg 278.5 289.1 257.1 280.7 7.6 <0.09 <0.04 0.40 & a ab c bcd WWR, % 51.6 49.3 41.1 43.9 12.7 <0.01 0.87 0.14 *High = high WWR cows. Low = low WWR cows. Whole plot = cow WWR. Split-plot = cow BW. Whole-split-plot interaction was the interaction between WWR and cow BW. WR = weight ratio at start of trial, calf weight/cow weight. WWR = calf 205-d weaning wt/cow wt at weaning. P values were considered significant at ≤0.05 and were considered as a trend toward significance at ≤0.1. a–d Means within a row with different superscripts differ (P ≤ 0.05). Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/suppl_1/S79/5108322 by Ed 'DeepDyve' Gillespie user on 16 October 2018 Beef cattle weaning ratio and cow size S81 and lactose content. Milk yield was calculated using WWR, were effective in predicting future per- calf weights from the weigh-suckle-weigh protocol. formance. Calf birth weight (44.3  ±  1.6  kg), calf age (66.2  ±  2.8 d) and calf weight start of trial (101.1  ±  4.1  kg) were not different between cow Statistical Analysis classification groups (P > 0.10; Table 2). Calf 205- Individual cow was the experimental unit. Feed d, adjusted weaning weights, taken October 2017, trial data were analyzed as a randomized split-plot were significantly affected by cow BW classifica - design using the PROC MIXED procedure in SAS tion group (276.4 ± 7.6 kg; P < 0.04); however, cow (v. 9.4; SAS Inst. Inc., Cary, NC). Dependent vari- WWR classification tended to effect calf weaning ables were DFC, FBD, NOV, TFC, and TSE. The weight (P  <  0.09; Table  2). Cow WWR classifica - PROC FREQ procedure in SAS was used to de- tion had a significant effect on 2017 cow–calf WWR termine TOD of feeding bouts. Three cows were (P < 0.01), with high WWR classified cows wean - removed from this analysis due to either EID tag ing 50.5% and low WWR classified cows weaning failure and/or unacceptable feed intake variation 42.5% (Table 2). This suggests that cows with higher (>30%). Milk data were analyzed as a randomized WWR may be able to transfer feed nutrients more split-plot design using the PROC MIXED pro- efficiently to their calves from birth to weaning. cedure in SAS. Fat, SNF, TS, protein, and lactose Although cow WWR did not affect feed in- were set as dependent variables. When WWR inter- take expressed as kg per day, cow weight influenced acted with cow size, means were separated using the DFC (P  <  0.01) with heavy cows within WWR LSMEANS procedure of SAS and a Tukey–Kramer groups consuming an average of 6.1 kg more than test was included in both MIXED procedures. P light cows (Table  3). Similar results of heavy cows values ≤0.05 were considered significant and P val- consuming considerably more feed than light cows ues >0.05 and ≤0.10 were considered a tendency. while lactating were reported by Walker et al. (2015) and in nonlactating heifers by Waghorn et al. (2012). RESULTS AND DISCUSSION When expressed as g feed/kg cow BW, however, cow WWR had a significant effect and BW tended to As expected, cow BWs at the beginning effect feed intake (P < 0.02 and P < 0.06, respect- (HL 536.4  ±  25.3  kg; HH 586.6  ±  49.9  kg; LL ively). High WWR cows consumed 34.9  g of feed 627.7  ±  29.2  kg; LH 645.1  ±  33.6  kg) of the trial per kg of BW, whereas low WWR cows consumed were significantly affected by WWR ( P  <  0.01) 30.4  g of feed per kg BW. Heavy cows consumed and BW (P < 0.01) classification groups ( Table 2). 34.2 g and light cows consumed 31.0 g of feed per Additionally, there was a significant difference kg BW (Table  3). Although high WWR cows and (P  <  0.01) in cow–calf weight ratio between high heavy cows consumed more feed per kg of BW than WWR (18.7%) and low WWR (15.5%) cows at the low WWR and light cows, these two groups also initiation of the study (Table  2), suggesting cow had calves that gained more. Possibly suggesting classification protocols, based on previous years Table 3. Cow feed intake and feeding behavior from 16 to 23 May 2017 trial † ‡ § ¶ High* Low WP SP WP * SP Item Light Heavy Light Heavy SE P value P value P value Intake Daily, kg 18.2 20.8 17.6 21.1 0.97 0.98 <0.01 0.69 g/kg cow BW 33.9 35.8 28.1 32.6 1.6 <0.02 <0.06 0.41 Feeding bouts Number/day 31.5 35.1 29.8 31.3 3.3 0.41 0.44 0.76 Duration, min 2.4 2.5 2.65 2.1 0.01 0.11 <0.02 0.39 Total time eating, min 617.6 614.7 452.2 547.1 68 0.08 0.51 0.48 *High = high WWR group. Low = low WWR group. Whole plot = cow WWR. Split-plot = cow BW. Whole-split-plot interaction was the interaction between WWR and cow BW. P values were considered significant at ≤0.05 and were considered as a trend toward significance at ≤0.1. Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/suppl_1/S79/5108322 by Ed 'DeepDyve' Gillespie user on 16 October 2018 S82 Williams et al. that cows classified as high WWR transfer the add - the stimulus of the feeders being filled, as feeding itional feed energy to the calf. occurred between 0800 and 0900 h, daily. Cow BW had a significant effect on average The interaction between cow WWR and FBD (P < 0.02) with light cows eating an average cow BW was observed in respect to milk lac- of 29  s longer per feeding bout than heavy cows tose content (P  <  0.01). High WWR–heavy BW (Table 3). Hafla et al. (2013) reported that low RFI cows had 0.4% more milk lactose than LH cows heifers spent less time feeding than high RFI heif- (P < 0.05) and LL cows tended to have 0.3% more ers, although no significant difference was reported milk lactose than LH cows (P  =  0.093; Table  5). in heifer BW. The highest number of feeding bouts, Percent milk lactose (mean 4.9  ±  0.2) and per- when day was broken into six, 4-h periods, occurred cent fat (3.7  ±  0.1) were comparable to percent in the evening (1700 to 2000 h; Table 4). However, milk lactose and milk fat reported by Mondragon the single hour with the highest number of visits et  al. (1983). Total solids (10.6  ±  0.3) and SNF was 0800 to 0900 h. This was most likely caused by (9.3 ± 0.2) were comparable to results reported by Table 4. Time of day feeding events occurred, categorized by six, 4-h periods: early morning (0100–0400 h), morning (0500–0800 h), late morning (0900–1200 h), afternoon (1300–1600 h), evening (1700–2000 h), and night (2100–0000 h) † ‡ § ¶ High* Low WP SP WP * SP Item Light Heavy Light Heavy SE P value P value P value Time of day Early morning 95 116 66 81 6.0 0.18 0.45 0.90 Morning 408 461 321 382 31.3 0.49 0.66 0.98 Late morning 517 475 325 377 12.6 <0.01 0.92 0.37 Afternoon 426 480 336 417 13.0 0.16 0.22 0.80 Evening 549 639 447 530 17.0 0.14 0.23 0.96 Night 207 280 173 176 23.5 0.45 0.70 0.72 *High = high WWR group. Low = low WWR group. Whole plot = cow WWR. Split-plot = cow BW. Whole-split-plot interaction was the interaction between WWR and cow BW. P values were considered significant at ≤0.05 and were considered as a trend toward significance at ≤0.1. Table 5. Milk analysis results † ‡ § ¶ High* Low WP SP WP * SP Item Light Heavy Light Heavy SE P value P value P value Milk yield Yield, kg 2.1 2.4 1.4 2 0.28 <0.08 0.11 0.45 g/kg cow BW 3.92 4.09 2.14 3.18 0.5 <0.02 0.23 0.39 Milk constituents Fat, % 1.8 1.1 1.2 1.3 0.3 0.46 0.34 0.25 SNF, % 9.3 9.4 9.3 9.1 0.14 0.28 0.84 0.35 TS, % 11 10.6 10.5 10.4 0.29 0.21 0.39 0.49 Protein, % 3.8 3.7 3.6 3.7 0.11 0.34 0.72 0.19 a b Lactose, % 4.8 5.1 5 4.7 0.1 0.57 0.83 <0.01 *High = high WWR group. Low = low WWR group. Whole plot = cow WWR. Split-plot = cow BW. Whole-split-plot interaction was the interaction between WWR and cow BW. P values were considered significant at ≤0.05 and were considered as a trend toward significance at ≤0.1. a,b Means within a row with different superscripts differ (P ≤ 0.05). Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/suppl_1/S79/5108322 by Ed 'DeepDyve' Gillespie user on 16 October 2018 Beef cattle weaning ratio and cow size S83 Beck, P. A., C. B.  Stewart, M. S.  Gadberry, M.  Haque, and Melton et  al. (1967). However, previous studies J.  Biermacher. 2016. Effect of mature body weight and have reported that milk constituents were not cor- stocking rate on cow and calf performance, cow herd effi - related to calf ADG or preweaning growth (Jeffery ciency, and economics in the southeastern United States. J. and Berg, 1971; Totusek et al., 1973; Mondragon Anim. Sci. 94:1689–1702. doi:10.2527/jas.2015-0049 et  al., 1983). Results from this research indicated Davis, M., J. Rutledge, L. Cundiff, and E. Hauser. 1983. Life cycle efficiency of beef production: II. Relationship of cow a WWR and cow BW interaction (P  <  0.05) in efficiency ratios to traits of the dam and progeny weaned. respect to milk lactose content, suggesting that J. Anim. Sci. 57:852–866. doi:10.2527/jas1983.574852x lactose content could influence calf preweaning Dinkel, C. A., and M. A. Brown. 1978. An evaluation of the growth. Additionally, previous studies examining ratio of calf weight to cow weight as an indicator of milk production in beef cows attribute milk yield cow efficiency. J. Anim. Sci. 46:614–617. doi:10.2527/ as an important factor in calf preweaning growth jas1978.463614x Hafla, A., G.  Carstens, T.  Forbes, L.  Tedeschi, J.  Bailey, (Williams et  al., 1979; Mondragon et  al., 1983; J.  Walter, and J.  Johnson. 2013. Relationships between Beal et al., 1990). Results from this research sug- postweaning residual feed intake in heifers and forage gest that high cow WWR tended (P = 0.08) to be use, body composition, feeding behavior, physical activity, higher in milk production and were higher in milk and heart rate of pregnant beef females. J. Anim. Sci. 91: production (P  <  0.05) when expressed on a BW 5353–5365. doi:10.2527/jas.2013–6423 Jeffery, H., and R.  Berg. 1971. Evaluation of milk variables basis. In contrast, cow BW did not influence milk as measures of milk effect on preweaning performance yield within WWR cow groups (P > 0.10; Table 5). of beef cattle. Can. J.  Anim. Sci. 51:21–30. doi:10.4141/ Milk yield reported in this research was consist- cjas71-003 ently lower than milk yield reported in other Kirkpatrick, B. W ., C. A. Dinkel, J. J. Rutledge, and E. R. Hauser. studies using weigh-suckle-weigh or machine 1985. Prediction equations of beef cow efficiency. J. Anim. milking techniques at comparable days post par- Sci. 60:964–969. doi:10.2527/jas1985.604964x Kress, D. D., D. C.  Anderson, J. D.  Stevens, E. T.  Miller, tum (Totusek et al., 1973; Mondragon et al., 1983; T. S.  Hirsch, J. E.  Sprinkle, K. C.  Davis, D. L.  Boss, Walker et al., 2015). D. W.  Bailey, R. P.  Ansotegui, et  al. 2001. Calf weight/ cow weight ratio at weaning as a predictor of beef cow IMPLICATIONS efficiency. Proc. Americ. Soci. Anim. Sci. West. Sec. 52:130–132. Results from this research provide additional Melton, A., J.  Riggs, L.  Nelson, and T.  Cartwright. 1967. information on how cow size, cow–calf WWR, Milk production, composition and calf gains of Angus, and milk production affect cow and production Charolais and Hereford cows. J. Anim. Sci. 26:804–809. doi:10.2527/jas1967.264804x efficiency. Overall, these results indicated that Mondragon, I., J. Wilton, O. Allen, and H. Song. 1983. Stage cows classified as high WWR consumed more of lactation effects, repeatabilities and influences on wean - feed on a g/kg BW bases. Also, cow WWR classi- ing weights of yield and composition of milk in beef cat- fication only had a tendency to affect calf weight tle. Can. J. Anim. Sci. 63:751–761. doi:10.4141/cjas83-090 at weaning whereas cow body size, when consid- Scasta, J. D., L.  Henderson, and T.  Smith. 2015. Drought ered within WWR classifications, had a significant effect on weaning weight and efficiency relative to cow size in semiarid rangeland. J. Anim. Sci. 93:5829–5839. effect. Milk lactose content was effected by the doi:10.2527/jas.2015–9172 interaction between cow weight and WWR clas- Totusek, R., D. W. Arnett, G. Holland, and J. Whiteman. 1973. sification, suggesting that heavy cows classified as Relation of estimation method, sampling interval and high WWR tend to produce more milk lactose, milk composition to milk yield of beef cows and calf gain. which could effect preweaning calf growth. In J. Anim. Sci. 37:153–158. doi:10.2527/jas1973.371153x Waghorn, G., K.  Macdonald, Y.  Williams, S.  Davis, and conclusion, the use of cow–calf WWR as a metric R. Spelman. 2012. Measuring residual feed intake in dairy of cow efficiency needs to be used with caution heifers fed an alfalfa (Medicago sativa) cube diet. J. Dairy because of potential increases in intake, milk pro- Sci. 95:1462–1471. doi:10.3168/jds.2011–4670 duction, and a potential bias to cow age and size. Walker, R., R. Martin, G. Gentry, and L. Gentry. 2015. Impact of cow size on dry matter intake, residual feed intake, metabolic response, and cow performance. J. Anim. Sci. LITERATURE CITED 93:672–684. doi:10.2527/jas.2014–7702 Beal, W., D. R. Notter, and R. Akers. 1990. Techniques for es- Williams, J., D.  Anderson, and D.  Kress. 1979. Milk produc- timation of milk yield in beef cows and relationships of tion in Hereford cattle. I. Effects of separation interval on milk yield to calf weight gain and postpartum reproduc- weigh-suckle-weigh milk production estimates. J. Anim. tion. J. Anim. Sci. 68:937–943. doi:10.2527/1990.684937x Sci. 49:1438–1442. doi:10.2527/jas1979.4961438x Translate basic science to industry innovation

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Translational Animal ScienceOxford University Press

Published: Sep 27, 2018

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