Residual feed intake (RFI) is a candidate trait for feed efficiency in dairy cattle. We investigated the influence of lactation stage on the effect of energy sinks in defining RFI and the genetic parameters for RFI across lactation stages for primiparous dairy cattle. Our analysis included 747 primiparous Holstein cows, each with recordings on dry matter intake (DMI), milk yield, milk composition, and body weight (BW) over 44 lactation weeks. For each individual cow, energy-corrected milk (ECM), metabolic BW (MBW), and change in BW (ΔBW) were calculated in each week of lactation and were taken as energy sinks when defining RFI. Two RFI models were considered in the analyses; RFI model [1] was a 1-step RFI model with constant partial regression coefficients of DMI on energy sinks (ECM, MBW, and ΔBW) over lactation. In RFI model [2], data from 44 lactation weeks were divided into 11 consecutive lactation periods of 4 wk in length. The RFI model [2] was identical to model [1] except that period-specific partial regressions of DMI on ECM, MBW, and ΔBW in each lactation period were allowed across lactation. We estimated genetic parameters for RFI across lactation by both models using a random regression method. Using RFI model [2], we estimated the period-specific effects of ECM, MBW, and ΔBW on DMI in all lactation periods. Based on results from RFI model [2], the partial regression coefficients of DMI on ECM, MBW, and ΔBW differed across lactation in RFI. Constant partial regression coefficients of DMI on energy sinks over lactation was not always sufficient to account for the effects across lactation and tended to give roughly average information from all period-specific effects. Heritability for RFI over 44 lactation weeks ranged from 0.10 to 0.29 in model [1] and from 0.10 to 0.23 in model [2]. Genetic variance and heritability estimates for RFI from model [2] tended to be slightly lower and more stable across lactation than those from model [1]. In both models, RFI was genetically different over lactation, especially between early and later lactation stages. Genetic correlation estimates for RFI between early and later lactation tended to be higher when using model [2] compared with model [1]. In conclusion, partial regression coefficients of DMI on energy sinks differed across lactation when modeling RFI. Neglect of lactation stage when defining RFI could affect the assessment of RFI and the estimation of genetic parameters for RFI across lactation.

An empirical regression model for the prediction of total dry matter intake (DMI) of dairy cows was developed and compared with four published intake models. The model was constructed to include both animal and dietary factors, which are known to affect DMI. For model development, a data set based on individual cow data from 10 change-over and four continuous milk production studies was collected (n 5 1554). Relevant animal (live weight (LW), days in milk (DIM), parity and breed) and dietary (total and concentrate DMI, concentrate composition, forage digestibility and fermentation quality) data were collected. The model factors were limited to those that are available before the diets are fed to animals, that is, standardized energy corrected milk (sECM) yield, LW, DIM and diet quality (total diet DMI index (TDMI index)). As observed ECM yield is a function of both the production potential of the cow and diet quality, ECM yield standardized for DIM, TDMI index and metabolizable protein concentration was used in modelling. In the individual data set, correlation coefficients between sECM and TDMI index or DIM were much weaker (0.16 and 0.03) than corresponding coefficients with observed ECM (0.65 and 0.46), respectively. The model was constructed with a mixed model regression analysis using cow within trial as a random factor. The following mixed model was estimated for DMI prediction: DMI (kg DM/day) 5 22.9 (60.56)10.258 (60.011) 3 sECM (kg/day) 1 0.0148 (60.0009) 3 LW (kg) 20.0175 (60.001) 3 DIM 25.85 (60.41) 3 exp (20.03 3 DIM) 1 0.09 (60.002) 3 TDMI index. The mixed DMI model was evaluated with a treatment mean data set (207 studies, 992 diets), and the following relationship was found: Observed DMI (kg DM/day) 5 20.10 (60.33) 1 1.004 (60.019) 3 Predicted DMI (kg DM/day) with an adjusted residual mean square error of 0.362 kg/day. Evaluation of the residuals did not result in a significant mean bias or linear slope bias, and random error accounted for proportionally .0.99 of the error. In conclusion, the DMI model developed is considered robust because of low mean prediction error, accurate and precise validation, and numerically small differences in the parameter values of model variables when estimated with mixed or simple regression models. The Cornell Net Carbohydrate and Protein System was the most accurate of the four other published DMI models evaluated using individual or treatment mean data, but in most cases mean and linear slope biases were relatively high, and, interestingly, there were large differences in both mean and linear slope biases between the two data sets.

Forty Finnish Ayrshire cows, 16 primiparous and 24 multiparous, were randomly assigned to 1 of 2 treatments (FF1 or FF5). Total mixed ration (TMR) was fed once a day on the FF1 treatment and 5 times a day on the FF5 treatment. The experiment began at calving and continued to wk 28 of lactation. The TMR consisted of a grass silage and concentrate mix. The amount of concentrate in the TMR was 51% on a DM basis. The feeding frequency had no effect on milk or energy-corrected milk yields or on milk composition. The average energy-corrected milk yield was 32.8 kg/d on the FF1 treatment and 32.5 kg/d on the FF5 treatment. The less frequent feeding increased the dry matter intake (DMI) of cows. The average DMI during the experiment was 20.9 kg/d on the FF1 treatment and 19.9 kg/d on the FF5 treatment. The difference in DMI was due to the differences in DMI of the mature cows. Energy and protein conversion tended to be lower with feeding once a day compared with feeding 5 times a day. The cows' feeding behavior was also observed. Cows fed 5 times a day tended to eat quite evenly after each delivery, whereas on the FF1 treatment there were 2 clear feeding peaks in the evening after the feed delivery. The time spent eating during the observation period was longer on FF5 than on FF1. The cows fed once a day spent more time lying than the cows fed 5 times a day. Based on the observations of feeding behavior, feeding a TMR 5 times a day seemed to be too frequent based on the increased restlessness and decreased lying time of the cows.

The aim of this paper was to study the genetic parameters for feed intake, milk production, and energy balance in Nordic Red dairy cattle from an experimental data set. The data were collected at the MTT Agrifood Research Finland Rehtijärvi experimental farm in 4 feeding trials between 1998 and 2008, and included lactation wk 2 to 30 for 291 Nordic Red nucleus heifers descending from 72 different sires. The studied traits included weekly averages for energy-corrected milk yield (ECM, kg/d), dry matter intake (kg/d), body weight (BW, kg), body condition score (BCS, score 1 to 5), and energy balance (EB, MJ of metabolizable energy/d). The data were analyzed with both fixed and random regression models. The heritabilities of ECM and BCS were moderate to high and remained fairly constant over the entire lactation period, whereas the heritabilities of BW and EB were the highest in early lactation (0.47 and 0.37, respectively) and declined later on. The heritabilities of DMI were highest (0.33) around lactation wk 5 and again at lactation wk 30, and were somewhat lower at the beginning of the lactation and in the middle period. The genetic correlations between the traits differed considerably between early and later lactation periods, especially for the trait pairs ECM-dry matter intake, ECM-EB, BW-EB, and BCS-EB, being negative or close to zero in lactation wk 2 to 5 but turning moderate to strong and positive by lactation wk 10. The results suggest that the lactating cows express their genetic potential for feed intake and energy utilization most clearly between lactation wk 2 to 10. The best candidate trait for selection might be EB in lactation wk 2 to 5 because it has a moderate heritability and is not genetically correlated with BW or BCS in that period.

Existing variation in energy efficiency and its relationship with milk yield and milk composition, body weight and body condition, feed intake, and energy status was studied in primiparous Nordic Red dairy cattle with data including 3,752 weekly records from 145 cows. Energy efficiency was defined as energy conversion efficiency (ECE) and as residual energy intake (REI) estimated based on Finnish feeding standards (REI₁) or from the current data (REI₂). The results indicated true phenotypic variation in energy efficiency of the cows. The proportion of total variance due to the animal was 0.35 for REI₁, 0.30 for REI₂, and 0.50 for ECE. The high efficiency based on ECE was associated with increased mobilization of body reserves (r = -0.50) and decreased dry matter intake (r = -0.51). With REI as an energy efficiency measure, the increased efficiency was associated with a large decrease in feed intake (REI₁: r = 0.60; REI2: r = 0.74) without any effect on body weight change (REI₁: r = 0.13; REI2: r = 0.00). Increased efficiency based on ECE and REI₁ was associated with increased milk yield (ECE: r = 0.58; REI₁: r = -0.41). A clear effect of stage of lactation on REI was found, which could be caused by true differences in utilization of metabolizable energy during lactation. However, it might also be related, in part, to the lack of knowledge of the composition of body weight change in the beginning of lactation.