Feed efficiency of lactating Holstein cows is repeatable within diet but less reproducible when changing dietary starch and forage concentrations

Improving feed efficiency has become an important target for dairy farmers to produce more milk with fewer feed resources. With decreasing availability of arable land to produce feeds that are edible for human consumption, it will be important to increase the proportion of feeds in the diets for dairy cattle that are less edible for human consumption. The current research analyzed the ability of lactating dairy cows to maintain their feed efficiency when switching between a high starch diet (HS diet: 27% starch, 29% NDF, 47.1% forages on a DM basis) and a low starch diet (LS diet: 13% starch, 37% NDF, 66.4% forages on a DM basis). Sixty-two lactating Holstein cows (137 ± 23 days in milk (DIM) at the start of experiment), of which 29 were primiparous cows, were utilized in a crossover design with two 70-d experimental periods, including a 14-d adaption period for each. Feed efficiency was estimated as the individual deviation from the population average intercept in a mixed model predicting DM intake (DMI) with net energy in milk, maintenance and BW gain and loss. Repeatability was estimated within each diet by comparing feed efficiency estimated over the first 28-day period and the second 28-day period within each diet, using Pearson’s and intraclass correlations, and the estimation of error of repeatability. Similarly, reproducibility was estimated by comparing the second 28-day period of one diet with the first 28-day period of the other diet. Feed efficiency was less reproducible across diets than repeatable within the same diet. This was shown by lower intraclass correlations (0.399) across diets compared to that in the HS diet (0.587) and LS diet (0.806), as well as a lower Pearson’s correlation coefficient (0.418) across diets compared to that in the HS diet (0.630) and LS diet (0.809). In addition, the estimation of error of repeatability was higher (0.830 kg DM/d) across diets compared to that in the HS diet (0.761 kg DM/d) and LS diet (0.504 kg DM/d). This means that the feed efficiency of dairy cows is more likely to change after a diet change than over subsequent lactation stages. Other determinants, such as digestive processes, need to be further investigated to determine its effects on estimating feed efficiency.     

Effect of forage-to-concentrate ratio on production efficiency of low-efficient high-yielding lactating cows

Feed is usually the costliest input in lactating cow's farms. Therefore, the developing of methods for a better adjustment of feed intake to cow's energetic needs in order to improve efficiency is desired. The aim of this study was to improve feed efficiency of low-efficient (LE) cows through a moderate increase in diet forage-to-concentrate ratio. We studied the effects of replacing 8.2% corn grains in a control low-fiber (LF) diet that contained 17.5% forage neutral detergent fiber (NDF) with 7.5% wheat straw + 0.7% soybean meal for a high-fiber (HF) diet that contained 23.4% forage NDF. Based on efficiency data of individual cows from the Agricultural Research Organization's herd measured in our previous study, 15 pairs of pre-classified LE multiparous mid-lactating Israeli Holstein dairy cows were selected, each pair with similar performance, intake, and efficiency data; each member of a pair was then adapted for 2 weeks to one or the other dietary treatment. Traits examined during the 5 weeks of the experiment were DM intake (DMI), eating behavior, milk production, in vivo digestibility, and estimation of feed efficiency [energy-corrected milk (ECM)/DMI and energy balance]. Cows fed the HF diet showed slower eating rate, smaller visit and meal sizes, longer daily eating time, higher visit frequency, and longer meal duration, compared to those fed the LF diet. The DMI of cows fed the HF diet was 9.1% lower, their DM digestibility decreased from 65.7 to 62.2%, and their ECM yield was 7.0% lower than in cows fed the LF diet. Feed efficiency, measured as net energy captured/digestible energy intake, improved in the cows fed the HF vs. LF diet while feed efficiency measured as ECM/DMI remained similar. Our results thus show the potential of improving feed efficiency for milk production in LE cows by increasing the forage-to-concentrate ratio.     

Effects of an artificial hay aroma and compound feed formulation on feed intake pattern,rumen function and milk production in lactating dairy cows

The Kempen system is a dairy feeding system in which diet is provided in the form of a compound feed (CF) and hay offered ad libitum. Ad libitum access to CF and hay allows cows in this system to achieve a high DM intake (DMI). Out of physiological concerns, the voluntary hay intake could be increased and the consumption pattern of CF could be manipulated to maintain proper rumen functioning and health. This study investigated the effects of an artificial hay aroma and CF formulation on feed intake pattern, rumen function and milk production in mid- to late-lactating dairy cows. Twenty Holstein–Friesian cows were assigned to four treatments in a 4 × 4 Latin square design. Diet consisted of CF and grass hay (GH), fed separately, and both offered ad libitum, although CF supply was restricted in maximum meal size and speed of supply by an electronic system. Treatments were the combination of two CF formulations – high in starch (CHS) and fibre (CHF); and two GH – untreated (UGH) and the same hay treated with an artificial aroma (TGH). Meal criteria were determined using three-population Gaussian–Gaussian–Weibull density functions. No GH × CF interaction effects on feed intake pattern characteristics were found. Total DMI and CF intake, but not GH intake, were greater (P < 0.01) in TGH treatment, and feed intake was not affected by type of CF. Total visits to feeders per day, visits to the GH feeder, visits to the CF feeder and CF eating time (all P < 0.01) were significantly greater in cows fed with TGH. Meal frequency, meal size and meal duration were unaffected by treatments. Cows fed CHF had a greater milk fat (P = 0.02), milk urea content (P < 0.01) and a greater milk fat yield (P < 0.01). Cows fed TGH had a greater milk lactose content and lactose yield (P < 0.05), and milk urea content (P < 0.01). Cows fed TGH had smaller molar proportions of acetic acid and greater molar proportions of propionic acid compared with UGH. In conclusion, treatment of GH with an artificial aroma increased CF intake and total DMI, but did not affect hay intake. Additionally, GH treatment increased the frequency of visits to both feeders, and affected rumen volatile fatty acid profile. Type of CF did not affect meal patterns, ruminal pH, nor fermentation profiles.     

Feeding behavior improves prediction of dairy cow voluntary feed intake but cannot serve as the sole indicator

Low-cost feeding-behavior sensors will soon be available for commercial use in dairy farms. The aim of this study was to develop a feed intake model for the individual dairy cow that includes feeding behavior. In a research farm, the individual cows’ voluntary feed intake and feeding behavior were monitored at every meal. A feed intake model was developed based on data that exist in commercial modern farms: ‘BW,’ ‘milk yield’ and ‘days in milking’ parameters were applied in this study. At the individual cow level, eating velocity seemed to be correlated with feed intake (R²=0.93 to 0.94). The eating velocity coefficient varied among individuals, ranging from 150 to 230 g/min per cow. The contribution of feeding behavior (0.28) to the dry matter intake (DMI) model was higher than the contribution of BW (0.20), similar to the contribution of fat-corrected milk (FCM)/BW (0.29) and not as large as the contribution of FCM (0.49). Incorporating feeding behavior into the DMI model improved its accuracy by 1.3 (38%) kg/cow per day. The model is ready to be implemented in commercial farms as soon as companies introduce low-cost feeding-behavior sensors on commercial level.     

Effects of lowering crude protein supply alone or in a combination with essential oils on productivity,rumen function and nutrient utilization in dairy cows

Lowering dietary protein concentration is known to decrease urinary nitrogen (N) losses and increase milk N efficiency in dairy cows, but it may negatively affect animal productivity. Plant-derived essential oils (EO) may alleviate these negative effects by improving the efficiency of rumen fermentation in cows fed reduced feed protein diets. The experiment was conducted to investigate the effects of lowering crude protein (CP) supply alone or in a combination with an EO product on feed intake, milk production and composition, rumen fermentation, total tract digestibility and N utilization in dairy cows. Twenty-one Holstein cows were used in a replicated 3 × 3 Latin square design experiment. Each period consisted of 14 days for adaptation and 14 days for data collection and sampling. Cows were randomly assigned to one of three experimental diets: a 165 g/kg CP diet (control), a 155 g/kg CP diet (LCP) and LCP supplemented with 35 g/day per cow EO (LCPEO). The dry matter (DM) intake was decreased by LCP and LCPEO compared with the control; there was no effect of EO on DM intake. Milk yield and composition and feed efficiency were similar among treatments. Ruminal pH, lactate, ammonia and volatile fatty acids concentrations were not affected by treatment, except increased valerate concentration by LCPEO compared with LCP. The supplementation of EO tended to decrease protozoal counts. The LCP and LCPEO increased total tract digestibility of DM and organic matter and decreased CP digestibility compared with the control. Supplementation with EO did not affect total tract digestibility of dietary nutrients compared with the control or LCP. The LCP and LCPEO decreased urinary and fecal N excretions and increased milk N efficiency; nitrogen losses were not affected by EO. In this study, lowering dietary CP by 10 g/kg decreased urinary and fecal N excretion without affecting productivity. The supplementation of EO to LCP had only minor effects on rumen fermentation and did not affect productivity, digestibility and N excretion in lactating dairy cows.     

Milk production responses and rumen fermentation of dairy cows supplemented with summer brassicas

Forage brassicas, such as summer turnip (ST; Brassica rapa) and forage rape (FR; Brassica napus), are used as supplementary crops during summer. However, studies with lactating dairy cows fed these forages are limited and report inconsistent productive responses. The aim of this study was to determine dry matter intake, rumen fermentation and milk production responses of dairy cows in mid-lactation supplemented with and without summer (‘ST’ or ‘FR’) brassicas. Twelve multiparous lactating dairy cows were randomly allocated to three dietary treatments in a replicated 3 × 3 Latin square design balanced for residual effects over three 21-day periods. The control diet consisted of 16.2 kg DM of grass silage, 2.25 kg DM of commercial concentrate and 2.25 kg DM solvent-extracted soybean meal. For the other two dietary treatments, 25% of the amounts of silage and concentrates were replaced with FR or ST. The inclusion of forage brassicas had no effects on milk production (24.2 kg cow/day average) and composition (average milk fat and protein 43.2 and 33.6 g/l, respectively). Dry matter intake was 0.98 kg and 1.12 kg lower for cows supplemented with FR and ST, respectively, resulting in a greater feed conversion efficiency (1.35 kg milk/kg DM for ST and FR v. 1.27 kg milk/kg DM for the control diet). Intraruminal pH was lower for cows supplemented with ST compared to the control diet; however, it did not decrease below pH 5.8 at any time of the day. After feeding, the concentrations of total short-chain fatty acids (SCFAs) in rumen contents increased with ST supplementation compared to the control diet. Inclusion of FR in the diet increased the molar proportion of acetate (68.5 mmol/100 mmol) in total SCFA at the expense of propionate, measured 6 h after feeding of the forage. The molar proportion of butyric acid was greater with ST and FR supplementation (13.1 and 12 mmol/100 mmol, respectively) than in control cows. The estimated microbial nitrogen (N) flow was 89.1 g/day greater when supplementing FR compared to the control diet. Based on the haematological measures, the inclusion of summer brassica forages did not affect the health status of the animals. These results indicate that mid-lactation dairy cows fed brassicas are able to maintain production despite the reduced intake, probably due to improved rumen fermentation and therefore nutrient utilization.     

Evaluation of production efficiencies at pasture of lactating suckler cows of diverse genetic merit and replacement strategy

Feed costs account for the largest proportion of direct cost within suckler beef production systems. By identifying the cow type with enhanced capability of converting grazed herbage to beef output across lactations, suckler cow systems would become more efficient and sustainable. The objective of this study was to estimate grass DM intake (GDMI) and production efficiency among lactating suckler cows of diverse genetic merit for the national Irish maternal index (Replacement Index) which includes cow efficiency components such as milk yield and feed intake. Data from 131 cows of diverse genetic merit within the Replacement Index, across two different replacement strategies (suckler or dairy sourced), were available over two grazing seasons. Milk yield, GDMI, cow live weight (BW) and body condition score (BCS) were recorded during early, mid and late-lactation, with subsequent measures of production efficiency extrapolated. Genetic merit had no significant effect on any variables investigated, with the exception of low genetic merit (LOW) cows being 22 kg heavier in BW than high genetic merit (HIGH) cows (P < 0.05). Beef cows were 55 kg heavier in BW (P < 0.001), had a 0.31 greater BCS (P < 0.05) and 0.30 Unité Fourragère Lait (UFL) greater energy requirement for maintenance compared to dairy sourced beef × dairy crossbred (BDX) cows (P < 0.001). The BDX had 0.8 kg greater GDMI, produced 1.8 kg more milk (P < 0.001), had a 0.8 UFL greater energy requirement for lactation and produced weanlings that were 17 kg heavier in BW than beef cows (P < 0.05). Subsequent efficiency variables of milk per 100 kg BW (P < 0.001), milk per kg GDMI (P < 0.001) and GDMI per 100 kg BW (P < 0.001) were more favourable for BDX. The correlations examined showed GDMI had moderate positive correlations (P < 0.001) with intake per 100 kg BW, net energy intake per kg milk yield, RFI and intake per 100 kg calf weaning weight but was weakly negatively correlated to milk yield per kg GDMI (P < 0.001). No difference was observed across genetic merit for beef cows for any of the traits investigated. Results from the current study showed that, while contrasting replacement strategies had an effect on GDMI and production efficiency, no main effect was observed on cows diverse in genetic merit for Replacement Index. Nonetheless, utilising genetic indexes in the suckler herd is an important resource for selecting breeding females for the national herd and phenotypic performance generated from this study can be included in future genetic evaluations to improve reliability of genetic values.     

Determinations of feed–milk–manure relationships on grazing-based dairy farms

Feed conversion into milk, nutrient excretion in manure and subsequent environment impacts of manure management are highly influenced by the diets that farmers feed their lactating cows (Bos taurus). On confinement-based dairy farms, determinations of diet composition are relatively straightforward because the types, amounts and nutrients contained in stored feeds are often well known. However, on grazing-based dairy farms, diet composition is more difficult to determine because forage intake during grazing must be estimated. The objectives of this study were to determine relationships between (1) feed N intake (NI), milk production, milk urea N (MUN), feed N use efficiency (FNUE) and excreted manure N (ExN); and (2) between feed P intake (PI), dung P concentrations (g/kg dry matter (DM)) and excreted manure P (ExP) for grazing-based lactating cows having a very wide range of diets and milk production. An additional objective was to evaluate how well these relationships compare with similar relationships based on more direct measurement of feed–milk–manure on confinement-based dairy farms. Four dairy farms located in southeastern Australia were visited during autumn and spring, and data were collected on feed, milk and dung of 18 cows on each farm. Estimated dry matter intake (DMI) from pasture comprised 12% to 75% of total diet DMI, and the crude protein (CP) concentrations in the total diets ranged from 167 to 248 g/kg. During spring, as diet CP increased FNUE declined. Total diet DMI and NI provided the best predictors of ExN, and PI provided the most accurate prediction of ExP. These results indicated accuracy in the study's indirect estimates of pasture DMI. Likely due to high levels and great variability in dietary CP and P concentrations associated with use of diet supplements, MUN did not appear to be a good indicator of dietary CP, and P in dung was not a good indicator of dietary P.     

Milk fatty acids as indicators of negative energy balance of dairy cows in early lactation

Most dairy cows experience negative energy balance (NEB) in early lactation because energy demand for milk synthesis is not met by energy intake. Excessive NEB may lead to metabolic disorders and impaired fertility. To optimize herd management, it is useful to detect cows in NEB in early lactation, but direct calculation of NEB is not feasible in commercial herds. Alternative methods rely on fat-to-protein ratio in milk or on concentrations of non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) in blood. Here, we considered methods to assess energy balance (EB) of dairy cows based on the fatty acid (FA) composition in milk. Short- and medium-chain FAs (primarily, C14:0) are typically synthesized de novo in the mammary gland and their proportions in milk fat decrease during NEB. Long-chain FAs C18:0 and C18:1 cis-9 are typically released from body fat depots during NEB, and their proportions increase. In this study, these FAs were routinely determined by Fourier-transform infrared spectroscopy (FTIR) of individual milk samples. We performed an experiment on 85 dairy cows in early lactation, fed the same concentrate ration of up to 5 kg per day and forage ad libitum. Daily milk yield and feed intake were automatically recorded. During lactation weeks 2, 4, and 6 after calving, two milk samples were collected for FTIR spectroscopy, Tuesday evening and Wednesday morning, blood plasma samples were collected Thursday morning. Net energy content in feed and net energy required for maintenance and lactation were estimated to derive EB, which was used to compare alternative indicators of severe NEB. Linear univariate models for EB based on NEFA concentration (deviance explained = 0.13) and other metabolites in blood plasma were outperformed by models based on concentrations of metabolites in milk: fat (0.27), fat-to-protein ratio (0.18), BHB (0.20), and especially C18:0 (0.28) and C18:1 cis-9 (0.39). Analysis of generalized additive models (GAM) revealed that models based on milk variables performed better than those based on blood plasma (deviance explained 0.46 vs. 0.21). C18:0 and C18:1 cis-9 also performed better in severe NEB prediction for EB cut-off values ranging from −50 to 0 MJ NEL/d. Overall, concentrations of C18:0 and C18:1 cis-9 in milk, milk fat, and milk BHB were the best variables for early detection of cows in severe NEB. Thus, milk FA concentrations in whole milk can be useful to identify NEB in early-lactation cows.     

Predicting feed intake using modelling based on feeding behaviour in finishing beef steers

Current techniques for measuring feed intake in housed cattle are both expensive and time-consuming making them unsuitable for use on commercial farms. Estimates of individual animal intake are required for assessing production efficiency. The aim of this study was to predict individual animal intake using parameters that can be easily obtained on commercial farms including feeding behaviour, liveweight and age. In total, 80 steers were used, and each steer was allocated to one of two diets (40 per diet) which consisted of (g/kg; DM) forage to concentrate ratios of either 494:506 (MIXED) or 80:920 (CONC). Individual daily fresh weight intakes (FWI; kg/day) were recorded for each animal using 32 electronic feeders over a 56-day period, and individual DM intakes (DMI; kg/day) subsequently calculated. Individual feeding behaviour variables were calculated for each day of the measurement period from the electronic feeders and included: total number of visits to the feeder, total time spent at the feeder (TOTFEEDTIME), total time where feed was consumed (TIMEWITHFEED) and average length of time during each visit to the feeder. These feeding behaviour variables were chosen due to ease of obtaining from accelerometers. Four modelling techniques to predict individual animal intake were examined, based on (i) individual animal TOTFEEDTIME relative expressed as a proportion of the dietary group (GRP) and total GRP intake, (ii) multiple linear regression (REG) (iii) random forests (RF) and (iv) support vector regressor (SVR). Each model was used to predict CONC and MIXED diets separately, giving eight prediction models, (i) GRP_CONC, (ii) GRP_MIXED, (iii) REG_CONC, (iv) REG_MIXED, (v) RF_CONC, (vi) RF_MIXED, (vii) SVR_CONC and (viii) SVR_MIXED. Each model was tested on FWI and DMI. Model performance was assessed using repeated measures correlations (R²_RM) to capture the repeated nature of daily intakes compared with standard R², RMSE and mean absolute error (MAE). REG, RF and SVR models predicted FWI with R²_RM = 0.1–0.36, RMSE = 1.51–2.96 kg and MAE = 1.19–2.49 kg, and DMI with R²_RM = 0.13–0.19, RMSE = 1.15–1.61 kg and MAE = 0.9–1.28 kg. The GRP models predicted FWI with R²_RM = 0.42–0.49, RMSE = 2.76–3.88 kg and MAE = 2.46–3.47 kg, and DMI with R²_RM = 0.32–0.44, RMSE = 0.32–0.44 kg, MAE = 1.55–2.22 kg. Whilst more simplistic GRP models showed higher R²_RM than regression and machine learning techniques, these models had larger errors, likely due to individual feeding patterns not being captured. Although regression and machine learning techniques produced lower errors associated with individual intakes, overall precision of prediction was too low for practical use.     

The effect of temporal variation in feed quality and quantity on the diurnal feeding behaviour of dairy cows

The diurnal feeding patterns of dairy cows affects the 24 h robot utilisation of pasture-based automatic milking systems (AMS). A decline in robot utilisation between 2400 and 0600 h currently occurs in pasture-based AMS, as cow feeding activity is greatly reduced during this time. Here, we investigate the effect of a temporal variation in feed quality and quantity on cow feeding behaviour between 2400 and 0600 h as a potential tool to increase voluntary cow trafficking in an AMS at night. The day was allocated into four equal feeding periods (0600 to 1200, 1200 to 1800, 1800 to 2400 and 2400 to 0600 h). Lucerne hay cubes (CP = 19.1%, water soluble carbohydrate = 3.8%) and oat, ryegrass and clover hay cubes with 20% molasses (CP = 11.8%, water soluble carbohydrate = 10.7%) were offered as the ‘standard’ and ‘preferred’ (preference determined previously) feed types, respectively. The four treatments were (1) standard feed offered ad libitum (AL) throughout 24 h; (2) as per AL, with preferred feed replacing standard feed between 2400 and 0600 h (AL + P); (3) standard feed offered at a restricted rate, with quantity varying between each feeding period (20:10:30:60%, respectively) as a proportion of the (previously) measured daily ad libitum intake (VA); (4) as per VA, with preferred feed replacing standard feed between 2400 and 0600 h (VA + P). Eight non-lactating dairy cows were used in a 4 × 4 Latin square design. During each experimental period, treatment cows were fed for 7 days, including 3 days habituation and 4 days data collection. Total daily intake was approximately 8% greater (P < 0.001) for the AL and AL + P treatments (23.1 and 22.9 kg DM/cow) as compared with the VA and VA + P treatments (21.6 and 20.9 kg DM/cow). The AL + P and VA treatments had 21% and 90% greater (P < 0.001) dry matter intake (DMI) between 2400 and 0600 h, respectively, compared with the AL treatment. In contrast, the VA + P treatment had similar DMI to the VA treatment. Our experiment shows ability to increase cow feeding activity at night by varying feed type and quantity, though it is possible that a penalty to total DMI may occur using VA. Further research is required to determine if the implementation of variable feed allocation on pasture-based AMS farms is likely to improve milking robot utilisation by increasing cow feeding activity at night.     

Estimating the impact of clinical mastitis in dairy cows on greenhouse gas emissions using a dynamic stochastic simulation model: a case study

The increasing attention for global warming is likely to contribute to the introduction of policies or other incentives to reduce greenhouse gas (GHG) emissions related to livestock production, including dairy. The dairy sector is an important contributor to GHG emissions. Clinical mastitis (CM), an intramammary infection, results in reduced milk production and fertility, increases culling and mortality of cows and, therefore, has a negative impact on the efficiency (output/input) of milk production. This may increase GHG emissions per unit of product. Our objective was to estimate the impact of CM in dairy cows on GHG emissions of milk production for the Dutch situation. A dynamic stochastic simulation model was developed to simulate the dynamics and losses of CM for individual lactations. Cows receive a parity (1 to 5+), a milk production and a calving interval (CI). Based on the parity, cows have a risk of CM, with a maximum of three cases in a lactation. Pathogens causing CM were classified as gram-positive bacteria, gram-negative bacteria, or other. Based on the parity and pathogen combinations, cows had a reduced milk production, discarded milk, prolonged CI and a risk of removal (culling and mortality) that reduce productivity of dairy cows and therefore increase GHG emissions per unit of product. Using life cycle assessment, emissions of GHGs were estimated from cradle to farm gate for processes along the milk production chain that are affected by CM. Processes included were feed production, enteric fermentation, and manure management. Emissions of GHGs were expressed as kg CO₂ equivalents per ton of fat-and-protein-corrected milk (kg CO₂e/t FPCM). Emissions of cows with CM increased on average by 57.5 (6.2%) kg CO₂e/t FPCM compared with cows without CM. This increase was caused by removal (39%), discarded milk (38%), reduced milk production (17%) and prolonged CI (6%). The GHG emissions increased by 48 kg CO₂e/t FPCM for cows with one case of CM, by 69 kg CO₂e/t FPCM for cows with two cases of CM and by 92 kg CO₂e/t FPCM for cows with three cases of CM compared with cows without CM. Preventing CM can be an effective strategy for farmers to reduce GHG emissions and can contribute to sustainable development of the dairy sector, because this also can improve the income of farmers and the welfare of cows. The impact of CM on GHG emissions, however, will vary between farms due to environmental conditions and management practices.     

Effects of replacing soybean meal with pumpkin seed cake and dried distillers grains with solubles on milk performance and antioxidant functions in dairy cows

Pumpkin seed cake (PSC), a byproduct of pumpkin seed oil processing, is used in ruminant feed as a beneficial protein source. Experiments were conducted to evaluate PSC as a substitute for soybean meal in the diets of lactating cows based on performance, rumen fermentation, antioxidant function and nitrogen partitioning. Six multiparous lactating cows were used in a replicated 3 × 3 Latin square experiment with 27-day periods. The cows were randomly divided into three treatment groups: group (1) was fed a diet containing no PSC (0PSC), and groups (2) and (3) were fed diets in which soybean meal was replaced with PSC and dried distillers grains with solubles (DDGS) at levels of 50% (50PSC) and 100% (100PSC), respectively. The diets were isonitrogenous and contained identical roughage but different proportions of PSC and DDGS. Replacement of soybean meal with PSC and DDGS did not influence rumen degradation, milk performance, rumen fermentation, DM intake or apparent total tract digestibility, and nitrogen partitioning between milk, feces and urine did not differ in the animals fed the three diets. However, compared with a diet containing no PSC, the total antioxidant capacity (P < 0.05) and antioxidant enzymes (total superoxide dismutase, glutathione peroxidase and catalase) activities (P < 0.05) were increased in the animals that received the 50PSC and 100PSC diets. In contrast, addition of PSC significantly reduced concentrations of aspartate transaminase (P < 0.05), alkaline phosphatase (P < 0.05) and malondialdehyde (P < 0.05) in the plasma. These results demonstrate that PSC can be completely substituted for soybean meal in the diet of dairy cows without any negative impact on milk performance, rumen fermentation or apparent digestibility and that this dietary change improves antioxidant functions and blood parameters in dairy cows, indicating that PSC has the potential for use as a feed source for dairy cows.     

Suitability of feeding and chewing time for estimation of feed intake in dairy cows

Monitoring of feeding and rumination behaviour can provide useful information for dairy herd management. The feeding behaviour of dairy cows can be recorded by different techniques, such as video cameras, weighing troughs or chewing sensors. Among feeding characteristics, individual feed intake of cows is of utmost interest, but as weighing troughs have high space and cost requirements they are used primarily in research studies. The objective of the present study was to evaluate whether records on feeding time or chewing activity or a combination of both contain enough information to estimate feed intake with sufficient accuracy. Feed intake and feeding time per cow were recorded by means of weighing troughs. Concurrently, chewing activity of seven cows was recorded by MSR-ART pressure sensors during five to eight measuring days per cow. Feeding and chewing behaviour were evaluated in time slots (1 min) and additionally assigned to feeding bouts for further analysis. The 1 min time slots were classified into feeding/no feeding or chewing/no chewing by the two systems, and agreement was found in 92.2% of the records. On average, cows spent 270±39 min/day at the feeding troughs and chewed 262±48 min/day. The average fresh matter intake (FMI) was 49.6±5.1 kg/day. Feed intake was divided into 9.7 bouts/day during which cows fed in average 27.8±21.7 min/bout and chewed 27.0±23.1 min/bout. The correlation between FMI and feeding time was r=0.891 and between FMI and chewing time r=0.780 overall cows. Hence, both systems delivered suitable information for estimating feed intake.     

Animal board invited review: Specialising and intensifying cattle production for better efficiency and less global warming: contrasting results for milk and meat co-production at different scales

Cattle are the world’s largest consumers of plant biomass. Digestion of this biomass by ruminants generates high methane emissions that affect global warming. In the last decades, the specialisation of cattle breeds and livestock systems towards either milk or meat has increased the milk production of dairy cows and the carcass weight of slaughtered cattle. At the animal level and farm level, improved animal performance decreases feed use and greenhouse gas emissions per kg of milk or carcass weight, mainly through a dilution of maintenance requirements per unit of product. However, increasing milk production per dairy cow reduces meat production from the dairy sector, as there are fewer dairy cows. More beef cows are then required if one wants to maintain the same meat production level at country scale. Meat produced from the dairy herd has a better feed efficiency (less feed required per kg of carcass weight) and emits less methane than the meat produced by the cow-calf systems, because the intake of lactating cows is largely for milk production and marginally for meat, whereas the intake of beef cows is entirely for meat. Consequently, the benefits of breed specialisation assessed at the animal level and farm level may not hold when milk and meat productions are considered together. Any change in the milk-to-meat production ratio at the country level affects the numbers of beef cows required to produce meat. At the world scale, a broad diversity in feed efficiencies of cattle products is observed. Where both productions of milk per dairy cow and meat per head of cattle are low, the relationship between milk and meat efficiencies is positive. Improved management practices (feed, reproduction, health) increase the feed efficiency of both products. Where milk and meat productivities are high, a trade-off between feed efficiencies of milk and meat can be observed in relation to the share of meat produced in either the dairy sector or the beef sector. As a result, in developing countries, increasing productivities of both dairy and beef cattle herds will increase milk and meat efficiencies, reduce land use and decrease methane emissions. In other regions of the world, increasing meat production from young animals produced by dairy cows is probably a better option to reduce feed use for an unchanged milk-to-meat production ratio.     

The partial replacement of soyabean meal and rapeseed meal with feed grade urea or a slow-release urea and its effect on the performance, metabolism and digestibility in dairy cows

The objectives of the study were to determine the effect of the partial replacement of soyabean meal and rapeseed meal with feed grade urea or a slow-release urea on the performance, metabolism and whole-tract digestibility in mid-lactation dairy cows. Forty-two Holstein–Friesian dairy cows were allocated to one of three dietary treatments in each of three periods of 5 weeks duration in a Latin square design. Control (C) cows were offered a total mixed ration based on grass and maize silages and straight feeds that included 93 g/kg dry matter (DM) soyabean meal and 61 g/kg DM rapeseed meal. Cows that received either of the other two treatments were offered the same basal ration with the replacement of 28 g/kg DM soyabean and 19 g/kg DM rapeseed meal with either 5 g/kg DM feed grade urea (U) or 5.5 g/kg DM of the slow-release urea (S; Optigen^R; Alltech Inc., Kentucky, USA), with the content of maize silage increasing. There was no effect (P > 0.05) of dietary treatment on DM intake, which averaged 22.5 kg/day. Similarly, there was no effect (P > 0.05) of treatment on daily milk or milk fat yield but there was a trend (P = 0.09) for cows offered either of the diets containing urea to have a higher milk fat content (average of 40.1 g/kg for U and S v. 38.9 g/kg for C). Milk true protein concentration and yield were not affected by treatment (P > 0.05). Milk yield from forage and N efficiency (g milk N output/g N intake) were highest (P < 0.01) in cows when offered S and lowest in C, with cows receiving U having intermediate values. Cows offered S also tended to have the highest live weight gain (0.38 kg/day) followed by U (0.23 kg/day) and C (0.01 kg/day; P = 0.07). Plasma urea concentrations were higher (P < 0.05) at 2 and 4 h post feeding in cows when offered U and lowest in C, with animals receiving S having intermediate values. There was no effect (P > 0.05) of treatment on whole-tract digestibility. In conclusion, the partial replacement of soyabean meal and rapeseed meal with feed grade urea or a slow-release urea can be achieved without affecting milk performance or diet digestibility, with the efficiency of conversion of dietary N into milk being improved when the slow-release urea was fed.     

Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle

In response to the increased concern over agriculture’s contribution to greenhouse gas (GHG) emissions, more detailed assessments of current methane emissions and their variation, within and across individual dairy farms and cattle, are of interest for research and policy development. This assessment will provide insights into possible changes needed to reduce GHG emissions, the nature and direction of these changes, ways to influence farmer behavior and areas to maximize the adoption of emerging mitigation technologies. The objectives of this study were to (1) quantify the variation in enteric fermentation methane emissions within and among seasonal calving dairy farms with the majority of nutritional requirements met through grazed pasture; (2) use this variation to assess the potential of new individual animal emission monitoring technologies and their impact on mitigation policy. We used a large database of cow performance records for milk production and survival from 2 398 herds in New Zealand, and simulation to account for unobserved variation in feed efficiency and methane emissions per unit of feed. Results showed an average of 120 ± 31.4 kg predicted methane (CH₄) per cow per year after accounting for replacement costs, ranging 8.9–323 kg CH₄/cow per year. Whereas milk production, survival and predicted live weight were reasonably effective at predicting both individual and herd average levels of per cow feed intake, substantial within animal variation in emissions per unit of feed reduced the ability of these variables to predict variation in per animal methane output. Animal-level measurement technologies predicting only feed intake but not emissions per unit of feed are unlikely to be effective for advancing national policy goals of reducing dairy farming enteric methane output. This is because farmers seek to profitably utilize all farm feed resources available, so improvements in feed efficiency will not result in the reduction in feed utilization required to reduce methane emissions. At a herd level, average per cow milk production and live weight could form the basis of assigning a farm-level point of obligation for methane emissions. In conclusion, a comprehensive national database infrastructure that was tightly linked to animal identification and movement systems, and captured live weight data from existing farm-level recording systems, would be required to make this effective. Additional policy and incentivization mechanisms would still be required to encourage farmer uptake of mitigation interventions, such as novel feed supplements or vaccines that reduce methane emissions per unit of feed.     

Isolating the cow-specific part of residual energy intake in lactating dairy cows using random regressions

The ability to properly assess and accurately phenotype true differences in feed efficiency among dairy cows is key to the development of breeding programs for improving feed efficiency. The variability among individuals in feed efficiency is commonly characterised by the residual intake approach. Residual feed intake is represented by the residuals of a linear regression of intake on the corresponding quantities of the biological functions that consume (or release) energy. However, the residuals include both, model fitting and measurement errors as well as any variability in cow efficiency. The objective of this study was to isolate the individual animal variability in feed efficiency from the residual component. Two separate models were fitted, in one the standard residual energy intake (REI) was calculated as the residual of a multiple linear regression of lactation average net energy intake (NEI) on lactation average milk energy output, average metabolic BW, as well as lactation loss and gain of body condition score. In the other, a linear mixed model was used to simultaneously fit fixed linear regressions and random cow levels on the biological traits and intercept using fortnight repeated measures for the variables. This method split the predicted NEI in two parts: one quantifying the population mean intercept and coefficients, and one quantifying cow-specific deviations in the intercept and coefficients. The cow-specific part of predicted NEI was assumed to isolate true differences in feed efficiency among cows. NEI and associated energy expenditure phenotypes were available for the first 17 fortnights of lactation from 119 Holstein cows; all fed a constant energy-rich diet. Mixed models fitting cow-specific intercept and coefficients to different combinations of the aforementioned energy expenditure traits, calculated on a fortnightly basis, were compared. The variance of REI estimated with the lactation average model represented only 8% of the variance of measured NEI. Among all compared mixed models, the variance of the cow-specific part of predicted NEI represented between 53% and 59% of the variance of REI estimated from the lactation average model or between 4% and 5% of the variance of measured NEI. The remaining 41% to 47% of the variance of REI estimated with the lactation average model may therefore reflect model fitting errors or measurement errors. In conclusion, the use of a mixed model framework with cow-specific random regressions seems to be a promising method to isolate the cow-specific component of REI in dairy cows.     

Feeding corn germ instead of corn grain on the performance of Holstein dairy cows fed low-forage diet and human-edible feed conversion efficiency

Using corn germ (CG) instead of corn grain could maintain dairy cow performance and might increase the efficiency of human food production. The primary objective of this study was to evaluate the effects of replacing corn grain with CG on the performance, nutrient intake, and digestibility of dairy cows. It also aimed to investigate the effect of CG on the efficiency of human food production in high-producing Holstein dairy cows in early lactation. Nine multiparous Holstein cows with 65.6 ± 8.5 DIM, milk yield of 55.6 ± 4.5 kg/d, and body weight of 611.3 ± 43.3 kg (mean ± SD) were used in a 3 × 3 Latin square design with 21-d periods. Treatments were (1) control treatment (CT, diet contains corn grain), (2) alternative treatment (AT, diet where corn grain was replaced with CG), and (3) balanced treatment (BT, diet where corn grain was replaced with CG but with the same energy content as CT). Control and balanced diets were isoenergetic (6.61 MJ/kg of DM); however, AT had higher energy (6.77 MJ/kg of DM). Treatments had no effect on dry and organic matter intake. NDF intake, however, was higher in CG diets compared with CT (P = 0.0001). Total-tract digestibility of DM tended to be reduced (P = 0.08), and OM digestibility was reduced (P = 0.05) by the inclusion of CG in diets. Whole and energy-corrected milk production were greater in AT compared with CT and BT (P < 0.05). Milk yield was similar in cows fed CT and BT. Treatments had no effect on milk composition or feed efficiency. Diet CT, when compared with CG diets, had lower efficiency in terms of human-edible feed conversion efficiency (HeFCE) and net food production (P < 0.05). Diet BT had greater HeFCE and net production of human-edible CP than AT (P < 0.05). Plasma BHBA, non-esterified fatty acids, and glucose concentrations were not affected by treatments, but plasma cholesterol was higher in cows that consumed CG diets (P = 0.04). The results indicate that, in high-producing early lactation dairy cows fed high concentrate diets, net food protein production can be substantially improved without lowering milk production through the reduction of dietary starch from 30.2 to 24.8% by replacing corn grain with CG.     

Evaluation of feeding behaviour traits to predict efficiency traits in pigs using partial least square regression

The improvement of efficiency traits, such as protein efficiency (PE), digestible energy efficiency (EnE) and lipid gain (LipG), are relevant given their associations with environmental pollution, cost of production, and the quality of meat. However, these traits are difficult to measure and usually require slaughtering of pigs. Efficiency traits are complex, and several factors, such as genetic predisposition, feed composition, but also individual feeding behaviour may contribute to efficiency. The objective of this study was therefore to evaluate the potential of using feeding behaviour traits to predict efficiency traits under dietary protein restriction. A total of 587 Swiss Large White pigs, consisting of 312 females and 275 castrated males, had ad libitum access to feed and water, and were fed a protein-reduced diet (80% of recommended digestible protein and essential amino acids) from 22.5 ± 1.6 to 106.6 ± 4.6 kg BW. Individual feed intake was monitored and carcass composition (lean and fat mass) at slaughter was determined by dual-energy X-ray absorptiometry. The PE and EnE were calculated as the ratio of protein or energy in the carcass (estimated by dual-energy X-ray absorptiometry) to the total protein or energy consumed. Feeding behaviour traits monitored were daily feed intake, feed intake per meal, number of daily meals, duration per meal, feeding rate, and feeder occupation. A partial least square (PLS) regression was used to predict PE, EnE and LipG from feeding behaviour traits, while including farrowing series (for PE only), age at slaughter and BW at slaughter. Accuracy of PLS regression was assessed based on RMSE and R² for calibration and validation sets, and on concordance correlation coefficient, which were estimated over 100 replicates of calibration and validation sets. Models with a number of latent variables of 5, 2 and 3 were identified as optimal for PE, EnE, and LipG, which explained 34.64%, 55.42% and 82.68% of the total variation in PE, EnE, and LipG, respectively. Significant concordance correlation coefficient was found between predicted and observed values for PE (0.50), EnE (0.70), and LipG (0.90). In conclusion, individual feeding behaviour traits can better predict EnE and LipG than for PE under dietary protein restriction when fed ad libitum.