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Invited Review: Advances in efficiency of growing dairy replacements
Abstract
Purpose
This article reviews the importance of feed efficiency in heifer rearing and discusses potential factors that can modulate feed efficiency and their possible implications in future performance and economics of heifer rearing.
Sources
Herein, we have gathered historical data from the largest contract heifer operation in Europe (Rancho Las Nieves, Mallén, Spain) to describe feed efficiency and economic returns throughout the rearing process. We have also compiled results from peer-review literature.
Synthesis
Heifers represent the sustainability and future of the herd and are responsible for important economic costs as well as a considerable environmental impact. Factors influencing feed efficiency include age, type of ration fed, and environmental conditions. Feed efficiency is ~50% during the first 2 mo and progressively declines to ~7% before calving. Also, feed efficiency is affected by stocking density, physiological status of the animals, and diet nutrient composition, including the ratio between CP and ME.
Conclusions and Applications
Regularly measuring feed intake and BW in dairy replacements is pivotal to improve heifer effectiveness and economics. Considering both, feed costs and feed efficiency, the most economically advantageous stage to foster body accretion in heifers is right after weaning until about 200 d of life. In addition, growth after weaning is positively correlated with future milking performance. Providing excessive amounts of forage after weaning should be avoided. Last, restricting the amount of diet fed to heifers, while maintaining an adequate supply of nutrients, may increase dietary unit costs and total daily feed costs.
... Feed efficiency (FE) was calculated by dividing gram BW gain by average daily total dry matter intake (TDMI; milk DM + starter feed DM). Samples of starter feeds and refusals were collected monthly and then subsamples were mixed thoroughly, dried in a convection oven (60 C • for 48 h), and ground in a mill (Ogaw Seiki CO., Ltd., Tokyo, Japan) to pass a 1-mm screen and analyzed for crude protein (CP; AOAC, 2000; 984.13), ether extract (EE; AOAC, 2000; ID 920.39), ash (AOAC, 2000;ID 942.05), neutral detergent fiber (NDF; Van Soest et al., 1991) without heat-stable α-amylase. The non-fiber-carbohydrate (NFC) component was calculated as 100 -(CP + NDF + EE + ash) (NRC, 2001). ...
... Because of greater feed efficiency, increasing feed intake in the pre-weaning period and in calves below 3 months of age is desirable (Bach et al., 2021). Regardless of the similar BW, ADG and less days to 1 kg starter intake among experimental treatments, cubic relationship clearly indicated that WC33 had the greatest TDMI and especially starter intake compared to others. ...
There is a growing interest in using whole grains as a potential alternative to forage in starter feed due to their adequate particle size and potential prevention of forage’s negative effects in starter feed. This could improve dairy calves’ feed intake and performance. Therefore, to determine the optimum level of whole corn grain in starter feed on feed intake, performance, health, ruminal fermentation, and blood metabolites of dairy calves, forty-eight Holstein calves [4-day-old; 41.10 ± 2.56 kg of body weight (BW), 12 per treatment] were randomly assigned to each of the following four treatments: 1) starter feed contained corn grain as ground with no whole corn grain (WC0); 2) starter feed where 33% of ground corn was replaced with whole corn grain (WC33); 3) starter feed where 66% of ground corn was replaced with whole corn grain (WC66); and 4) starter feed where 100% of ground corn was replaced with whole corn grain (WC100). For the purpose of gathering post-weaning data, the calves were weaned on day 60 and left until day 74. The experimental treatments had no significant effect on BW, but the starter feed and total dry matter intake (TDMI) tended (P = 0.051) to respond cubically with increasing WC inclusion. Throughout the entire period, the wither height tended (P = 0.09) to increase linearly as WC increased in starter feed. The fecal score, respiratory score and days with diarrhea did not differ between treatments. Throughout the research, calves fed the WC0 diet had lower (P = 0.01) rumen pH levels compared with the other treatments, and rumen acetate concentrations decreased (P = 0.02) cubically and acetate-to-propionate ratio tended (P = 0.07) to increase linearly in calves consuming WC. There were no differences in blood metabolites among the experimental groups during the overall period. Given the observed rumen fermentation modulations under the conditions of the current experiment, we concluded that grinding all the corn grain in forage-free starter feeds is not recommended for dairy calves. Feed intake-related data indicated that partial replacement (33%) of ground with whole corn could lead to greater intake.
... Dairy calf management may determine medium-and long-term productive performance of the dairy cattle herd. For example, Bach et al. (2021) reported a positive relationship between initial 70-d average daily gain (ADG) of heifer calves and milk production in the first lactation when using data from a large Spanish dairy operation. However, adverse health events, such as diarrhea, often deplete pre-weaning performance, likely avoiding the achievement of the full productive potential of the herd, with negative effects that last until later in life (Soberon et al., 2012). ...
This study aimed to evaluate the effects of Enterococcus faecium 669 supplementation on performance, health, parasitological, microbiological, and hematological responses of pre-weaning dairy calves. Forty-two newborn Holstein female calves [initial body weight (BW) 44 ± 4.5 kg] were used in the present study. At birth, calves were ranked by initial BW and assigned to 1 of 2 treatment groups: 1) whole milk (CON; n = 21) and 2) whole milk with the addition of E. faecium 669 (DFM; n = 21). During the entire experimental period (63 d), DFM was daily-fed at a rate of 2.5 × 109 colony forming units/head. All calves were offered a mixture of a starter feed and wheat straw for ad libitum consumption. Supplement intake was evaluated daily, whereas calves were weighed on a weekly basis from d 0 to weaning (d 63). Diarrhea was assessed once a day, whereas fecal and blood samples were collected for microbiological, parasitological, and hematological responses. All data were analyzed with SAS and using calf as the experimental unit. A treatment × week interaction was observed for BW, as DFM-supplemented calves were heavier than CON cohorts on d 56 (+ 4.7 kg) and at weaning on d 63 (+ 4.8 kg). A similar interaction was observed for ADG and dry matter intake (DMI), with greater ADG for DFM-supplemented calves from d 35 - 42, greater ADG and DMI from d 49 - 56, and greater DMI from d 56 - weaning. Moreover, diarrhea occurrence tended to be lower, whereas rectal temperature was 0.2°C lower for DFM supplemented calves. Treatment × day interactions were observed for the occurrence and counts of Eimeria spp., as DFM-supplemented calves tended to have a reduced number of positive observations on d 42 of the study vs. CON and a significant reduction in positive animals from d 21 to 42 was observed in DFM, but not in CON calves. For Cryptosporidium spp., no treatment effects were observed on overall occurrence (%), but DFM-supplemented calves had a greater count of oocyst per gram vs. CON. No treatment × day interaction or main treatment effects were observed for any of the blood variables analyzed herein, exception being monocytes concentration. In summary, pre-weaning E. faecium 669 supplementation improved performance, diarrhea occurrence, and reduced the number of calves positively-detected for Eimeria spp.
... As feed efficiency decreases over time, but feed costs also increase as the proportion of dietary forage intake increases, and consequently it is likely to be economically advantageous to maximise growth rates either preweaning, or immediately after weaning (Bach, Ahedo and Kertz, 2021). ...
The effective management of preweaned calves is one of the most important areas of dairy farm management, and can have substantial impacts in terms of health, welfare, and productivity. It is critical that veterinary advisors are able to implement proactive changes to housing and management likely to not only result in the largest improvements, but also be applicable to the majority of farms. The majority of statistical techniques are intended for a relatively low dimensional setting, and conventional statistical approaches are often poorly suited to problems where the number of variables exceed the number of observations. The number of potential variables available in today’s data rich environment is increasing, and the robust identification of causal variables is becoming increasingly important. Statistical learning techniques represent important tools in identifying factors associated with calf health and performance on dairy farms. In Chapter 2, over 21 million cattle deaths were analysed utilising national birth and death registrations from the national British Cattle Movement Service, to quantify the temporal incidence rate, distributional features, and factors affecting variation in mortality rates in calves in GB since 2011. Alongside providing a first benchmark for calf mortality rates in GB, factors associated with mortality rates were further explored utilising multivariate adaptive regression spline models and suggest that environmental conditions such as mean monthly environmental temperature and month of birth play a significant role in calf mortality rates at a national level. To identify the most important factors for optimal calf health and performance, the farm management practices were collected from 60 farms, resulting in a large number of potential housing and management variables affecting calf performance. In Chapter 3, an elastic net was used in combination with stability selection techniques, and these were utilised to identify which factors were most likely to improve calf performance on the majority of farms, and included management areas such as stocking demographics, milk/colostrum feeding, environmental hygiene and environmental temperature. Colostrum samples were also collected from enrolled farms, and in Chapter 4, a first benchmark of bacterial levels within colostrum on GB dairy farms was provided. Bacterial levels in were significantly higher when colostrum was collected using equipment than taken directly from the cow’s teat, suggesting interventions to reduce bacterial contamination should focus on the hygiene of collection and feeding equipment. An automated backwards stepwise mixed effects regression model was utilised in conjunction with stability selection to identify a small number of variables likely to have the largest effect on colostrum hygiene on the largest number of farms and suggest that the cleaning of colostrum collection and feeding equipment after every use should be performed with hot water as opposed to cold water, and hypochlorite or peracetic acid as opposed to water or parlour wash. It is important that associations identified during observational studies are not interpreted as causal, and the most important variables identified in Chapter 2, 3 and 4 were tested as a calf health plan intervention in a randomised controlled trial to elucidate causality, as described in Chapter 5. Health and performance outcomes were analysed for 60 dairy farms randomly allocated to receive the health plan as an intervention. Growth rates were higher for calves on farms receiving the plan for both male or beef and dairy heifer calves, and results from regression models suggest that male or beef calves had significant increased growth rates on farms receiving the plan than those that were not. Model predictions suggest that a farm with the highest number of interventions in place (15) compared to farms with the lowest number of interventions in place (4) would expect an improvement in mean growth rates from 0.65kg/d to 0.81kg/d for male or beef calves, from 0.73kg/d to 0.88kg/d for dairy heifers, a decrease in mortality rates from 10.9% to 2.8% in male or beef calves, and a decrease in diarrhoea rates from 42.1% to 15.1% in dairy heifers. Neonatal calves are relatively susceptible to heat loss, and Chapters 2 and 3 suggested that reduced environmental temperatures are associated with increased calf mortality, and reduced growth rates. The aim of Chapter 6 was to evaluate the impact of calf jackets and supplementary heat sources on the growth rates of preweaned calves in a randomised controlled trial. Seventy-nine calves from a single British dairy farm were randomly allocated to receive heat lamps or calf jackets in a factorial study design. Regression model results suggest 1kW heat lamp usage significantly improved growth rates by around 90g/d, and no effect of jacket were identified. A significant, positive impact of increased pen temperature on calf ADG was also identified in this study and was reinforced when including prior information from Chapter 3 within a Bayesian framework. The research presented in this thesis utilised a range of statistical learning techniques to identify factors associated with calf performance, which have been tested in a randomised controlled trial. To provide farmers and veterinarians with access to the calf health findings of the thesis in interactive form, the University of Nottingham Herd Health Toolkit (www.nottingham.ac.uk/herdhealthtoolkit) was created, including tools relating to the management of colostrum, prediction of mortality rates and ultimately a bespoke calf health plan based on user inputs. A number of statistical learning techniques within the field of stability selection were developed in parallel to this thesis, and the creation of the stabiliser R package to allow these techniques to be utilised by the wider research community.
Longevity of a dairy herd can reflect the health and welfare status of the herd and has a role in terms of public perception of the dairy industry. The natural lifespan of a dairy cow has been reported to be approximately 20 years; however, research has highlighted that it is more like 3.6 lactations (approximately 6 years) in the UK and 2.8 lactations (approximately 5 years) in the USA. This indicates that management decisions are having large impacts on the average productive lifespan of dairy cows, with the removal of cows from a herd due to old age being rare. Increasing the longevity of a dairy herd has been promoted as it decreases the requirement for replacement heifers and increases the average herd production level.
Heifer rearing is a fundamental part of the dairy industry, which represents a significant economic investment by the farmer into the future of the herd, with studies reporting that it contributes to approximately 20% of the overall expenditure of a dairy farm; the target is less than 10%. Research from the UK reported the mean rearing cost of a heifer was approximately £1900, with large variation between farms. The payback time for these costs has been reported to be around second lactation. It is important for farmers and veterinary surgeons to consider the economics of heifer rearing, as well as the health, welfare and longevity of heifers when implementing a rearing plan.
Optimization and support of health and performance of preweaning dairy calves is paramount to any dairy operation, and natural solutions, such as probiotics, may help to achieve such a goal. Two experiments were designed to evaluate the effects of direct-fed microbial (DFM) Enterococcus faecium 669 on performance of preweaning dairy calves. In experiment 1, twenty 4-d-old Holstein calves [initial body weight (BW) 41 ± 2.1 kg] were randomly assigned to either (1) no probiotic supplementation (CON; n = 10) or (2) supplementation with probiotic strain E. faecium 669 during the preweaning period (DFM; n = 10) at 2.0 × 1010 cfu/kg of whole milk. Full individual BW was analyzed every 20 d for average daily gain (ADG) and feed efficiency (FE) determination. In experiment 2, thirty 4-d-old Holstein calves (initial BW 40 ± 1.9 kg) were assigned to the same treatments as in experiment 1 (CON and DFM). The DFM supplementation period was divided into period I (from d 0 to 21) and II (from d 22 to 63), with weaning occurring when animals were 67 d of age. During the entire experimental period, DFM was mixed into the whole milk at a rate of 1.5 × 1010 and 2.5 × 109 cfu/kg of whole milk/calf per day for periods I and II, respectively (6-time reduction). Full individual BW was taken every 21 d. As a routine of the experiment, calves were monitored daily, and diarrhea cases were evaluated using a daily 3-point fecal score. For both experiments, all data were analyzed using calf as the experimental unit. In experiment 1, DFM-supplemented calves were heavier on d 40 (+ 4.5 kg) and 60 (+ 6.5 kg) and had a greater ADG (+ 118 g) versus CON. In experiment 2, supplementation with DFM significantly tended to reduce diarrhea occurrence. Treatment × day and treatment × week interactions were observed for BW, ADG, and gain-to-feed ratio. Dairy calves supplemented with DFM were 1.8 and 3.5 kg heavier on d 42 and at weaning, respectively, and had a greater ADG from d 21 to 42 (+ 52 g) and 42 to 63 (+ 77 g) and gain-to-feed ratio from d 42 to 63 (+ 8.6%). In summary, supplementation of E. faecium 669 to dairy calves improved preweaning performance, even when the dose of the DFM was reduced by 6- to 8-times. Additionally, initial promising results were observed on diarrhea occurrence, but further studies are warranted.
The efficiency of replacement programmes in dairy farms depends largely on the heifers’ growth rate. We provide a case study of control chart application to monitor the weight of dairy replacement heifers. A research dairy farm in Córdoba province, Argentina, provided the monthly samples of BW measurements of 2, 9, and 14.5-month-old heifers born between 2017 and 2019. The data were used to build control charts for the mean and for SD, with moving range control limits in order to consider varying sample sizes. In each age group, control charts for the mean showed at least one out-of-control sample, whereas control charts for SD showed one sample out of control for 9-month-old heifers. Each sample outside the control limits implies that a potentially identifiable cause has occurred. Therefore, the producer could identify the event causing the deviation and make the necessary changes according to the heifer’s age. Control charts provide the producer and consultant with graphical information and quick alerts to support the decision-making process of the replacement programme. These tools are useful at the farm level to monitor heifer weights and support management decisions.
Fifteen Holstein heifers that were 175 +/- 4.0 d old and at BW of 175 +/- 4.9 kg were used to determine the effect of three feeding regimens from 6 to 12 mo of age on growth, blood concentration of several hormones, and milk production during first lactation. The feeding regimens consisted of two periods, the first lasting for 4 mo and the other for the subsequent 2 mo. For group A (restricted) heifers, the diet during period 1 was restricted to 85% of NRC (1988) recommendations (a daily BW gain of .7 kg); during period 2, a high energy, high protein diet was provided for ad libitum intake. Group B (control) heifers received a diet that corresponded to 100 and 90% of the NRC (1988) recommendations in periods 1 and 2, respectively. Group C (ad libitum) intake heifers received a high energy, high protein diet throughout both periods. Daily BW gains of heifers of groups A, B, and C were, respectively, .625, .768, and 1.100 kg for period 1 and 1.162, .705, and .797 kg for period 2. The different feeding regimens influenced the age at which the heifers achieved puberty but did not affect BW at puberty. Milk production during 250 d of lactation was 7056, 6070, and 5975 kg for groups A, B, and C, respectively. A statistical model that included serum derived mitogenic activity and serum prolactin of period 2 accounted for 63% of the difference in milk production at first lactation.
Nutrient Requirements of Dairy Cattle. 7th rev