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Vegetable by-products have great potential for use as animal feeds and thus could improve the sustainability of the food system. The objective was to evaluate the milk production potential of potato by-product (PBP) replacing cereal grains in grass silage-based total mixed ration (TMR). Additionally, a laboratory scale experiment was conducted to assess the effect of PBP and chemical preservatives on the aerobic stability of TMRs. A change-over dairy cow feeding experiment was conducted to evaluate the inclusion of 135 g/kg (on a dry matter (DM) basis) of PBP in TMR. Additionally, the aerobic stability of TMR was evaluated by preparing TMRs with increasing levels of PBP and treated with different doses of formic and propionic acid or salt-based preservatives. The inclusion of PBP in dairy cow diets decreased feed intake, but organic matter digestibility was greater in the PBP diet, resulting in only slightly decreased production (milk protein 1435 vs. 1363 g/day, p &lt, 0.05, milk lactose 1716 vs. 1606 g/day, p &lt, 0.05). The aerobic stability of TMR was negatively affected by the inclusion of PBP, but it could to a limited extent be prolonged using chemical preservatives. The inclusion of PBP decreased feed intake and milk production to some extent when included in the diet of high-producing dairy cows. The utilization of PBP may, however, be justified from a sustainability point of view, as it provides a way to circulate the nutrients of a non-human edible feed material back into the food chain.

Inclusion of feed efficiency traits into the dairy cattle breeding programmes will require considering early lactation energy status to avoid deterioration in health and fertility of dairy cows. In this regard, energy status indicator (ESI) traits, for example, blood metabolites or milk fatty acids (FAs), are of interest. These indicators can be predicted from routine milk samples by mid-IR reflectance spectroscopy (MIR). In this study, we estimated genetic variation in ESI traits and their genetic correlation with female fertility in early lactation. The data consisted of 37 424 primiparous Nordic Red Dairy cows with milk test-day records between 8 and 91 days in milk (DIM). Routine test-day milk samples were analysed by MIR using previously developed calibration equations for blood plasma non-esterified FA (NEFA), milk FAs, milk beta-hydroxybutyrate (BHB) and milk acetone concentrations. Six ESI traits were considered and included: plasma NEFA concentration (mmol/l) either predicted by multiple linear regression including DIM, milk fat to protein ratio (FPR) and FAs C10:0, C14:0, C18:1 cis-9, C14:0 * C18:1 cis-9 (NEFAFA) or directly from milk MIR spectra (NEFAMIR), C18:1 cis-9 (g/100 ml milk), FPR, BHB (mmol/l milk) and acetone (mmol/l milk). The interval from calving to first insemination (ICF) was considered as the fertility trait. Data were analysed using linear mixed models. Heritability estimates varied during the first three lactation months from 0.13 to 0.19, 0.10 to 0.17, 0.09 to 0.14, 0.07 to 0.10, 0.13 to 0.17 and 0.13 to 0.18 for NEFAMIR, NEFAFA, C18:1 cis-9, FPR, milk BHB and acetone, respectively. Genetic correlations between all ESI traits and ICF were from 0.18 to 0.40 in the first lactation period (8 to 35 DIM), in general somewhat lower (0.03 to 0.43) in the second period (36 to 63 DIM) and decreased clearly (−0.02 to 0.19) in the third period (64 to 91 DIM). Our results indicate that genetic variation in energy status of cows in early lactation can be determined using MIR-predicted indicators. In addition, the markedly lower genetic correlation between ESI traits and fertility in the third lactation month indicated that energy status should be determined from the first test-day milk samples during the first 2 months of lactation.

Dairy cows have intense fluctuations in digestive, metabolic and hormonal systems around calving which predispose them to various disorders and health problems. The aim of the current experiment was to investigate feed and nutrient intake, rumen fermentation, rumen bacterial communities, milk production, milk fatty acid composition and plasma biomarker profiles of dairy cows to assess the modulation of these functions by in-feed resin acid inclusion. Thirty-six Nordic Red cows were used in a continuous feeding trial starting 3 weeks prepartum and lasting for 10 weeks into the lactation. The cows were fed grass silage ad libitum and the dietary treatments were 1) control with basal concentrate (CON), 2) CON supplemented with tall oil fatty acids (TOFA; 90 % fatty acids and 9% resin acids) at 7.0 g/cow/day and 3) CON supplemented with resin acid concentrate (RAC; 37.5% resin acids) at 1.7 g/cow/day. The mixture of resin acids in TOFA and RAC, consisting mostly of abietic and dehydroabietic acids, originated from coniferous tree species Pinus sylvestris L. and Picea abies L. Feed intake and milk production were measured throughout the experimental period. Milk and blood samples were collected at weeks 2, 3, 6 and 10, and rumen fluid was sampled at weeks 2 and 10 of lactation to analyse rumen fermentation and rumen bacterial communities. The dynamics in feed intake and milk production with progressing lactation showed typical curvilinear trends (P for time

Green biorefineries provide novel opportunities to use the green biomass efficiently and utilize the ecosystem services provided by grasslands more widely. The effects of the inclusion of fractionated grass silage solid fraction (pulp) on feed intake, rumen fermentation, diet digestion and milk production in dairy cows were investigated. Pulp was separated from grass silage using a screw press simulating a green biorefinery. Partial removal of liquid from forage increased DM concentration from 220 to 432 g/kg and NDF from 589 to 709 g/kg DM while CP decreased from 144 to 107 g/kg DM. A feeding trial using an incomplete changeover design with 24 Nordic Red cows and two 3-week periods was conducted. The pulp replaced grass silage in the diet at 0 (P0), 25 (P25) and 50 (P50) percentage of total forage, which was fed ad libitum with 13 kg of concentrate for all treatments. The forage DM intake was highest on P25 (14.1 kg/day) while P0 and P50 did not differ from each other (13.2 and 13.0 kg/day, respectively). There were no differences between the treatments in rumen pH or ammonia N, but the proportion of acetate increased with increasing pulp inclusion. The digestibility was measured using acid insoluble ash and indigestible NDF (iNDF) as internal markers. Neither of the markers detected differences in NDF digestibility, but according to iNDF, apparent total tract organic matter digestibility decreased with increasing pulp inclusion. The cows maintained milk production at P25, but it showed some decline at P50 (energy-corrected milk at P0 and P25 was 39.8 kg/day while for P50, it was 38.5 kg/day, P = 0.056) and the milk protein yield significantly declined with higher pulp inclusion. Simultaneously, the nitrogen use efficiency in milk production increased. It seems that the fibrous grass-based fraction from a biorefinery process has potential to be used as a feed for ruminants.

The inclusion of feed intake and efficiency traits in dairy cow breeding goals can lead to increased risk of metabolic stress. An easy and inexpensive way to monitor postpartum energy status (ES) of cows is therefore needed. Cows' ES can be estimated by calculating the energy balance from energy intake and output and predicted by indicator traits such as change in body weight (Delta BW), change in body condition score (Delta BCS), milk fat:protein ratio (FPR), or milk fatty acid (FA) composition. In this study, we used blood plasma nonesterified fatty acids (NEFA) concentration as a biomarker for ES. We determined associations between NEFA concentration and ES indicators and evaluated the usefulness of body and milk traits alone, or together, in predicting ES of the cow. Data were collected from 2 research herds during 2013 to 2016 and included 137 Nordic Red dairy cows, all of which had a first lactation and 59 of which also had a second lactation. The data included daily body weight, milk yield, and feed intake and monthly BCS. Plasma samples for NEFA were collected twice in lactation wk 2 and 3 and once in wk 20. Milk samples for analysis of fat, protein, lactose, and FA concentrations were taken on the blood sampling days. Plasma NEFA concentration was higher in lactation wk 2 and 3 than in wk 20 (0.56 +/- 0.30, 0.43 +/- 0.22, and 0.13 +/- 0.06 mmol/L, respectively; all means +/- standard deviation). Among individual indicators, C18:1 cis-9 and the sum of C18:1 in milk had the highest correlations (r = 0.73) with NEFA. Seven multiple linear regression models for NEFA prediction were developed using stepwise selection. Of the models that included milk traits (other than milk FA) as well as body traits, the best fit was achieved by a model with milk yield, FPR, Delta BW, Delta BCS, FPR x Delta BW, and days in milk. The model resulted in a cross-validation coefficient of determination (R(2)cv) of 0.51 and a root mean squared error (RMSE) of 0.196 mmol/L. When only milk FA concentrations were considered in the model, NEFA prediction was more accurate using measurements from evening milk than from morning milk (R(2)cv = 0.61 vs. 0.53). The best model with milk traits contained FPR, C10:0, C14:0, C18:1 cis-9, C18:1 cis-9 x C14:0, and days in milk (R(2)cv = 0.62; RMSE = 0.177 mmol/L). The most advanced model using both milk and body traits gave a slightly better fit than the model with only milk traits (R(2)cv = 0.63; RMSE = 0.176 mmol/L). Our findings indicate that ES of cows in early lactation can be monitored with moderately high accuracy by routine milk measurements.

Currently, routine recordings of dry matter intake (DMI) in commercial herds are practically nonexistent. Recording DMI from commercial herds is a prerequisite for the inclusion of feed efficiency (FE) traits in dairy cattle breeding goals. To develop future on-farm phenotyping strategies, recording strategies that are low cost and less demanding logistically and that give relatively accurate estimates of the animal's genetic merit are therefore needed. The objectives of this study were (1) to estimate genetic parameters for daily DMI and FE traits and use the estimated parameters to simulate daily DMI phenotypes under different DMI recording scenarios (SCN) and (2) to use the simulated data to estimate for different scenarios the associated reliability of estimated breeding value and accuracies of genomic prediction for varying sizes of reference populations. Five on-farm daily DMI recording scenarios were simulated: once weekly (SCN1), once monthly (SCN2), every 2 mo (SCN3), every 3 mo (SCN4), and every 4 mo (SCN5). To estimate reliability of estimated breeding values, DMI and FE observations and true breeding values were simulated based on variance components estimated for daily observations of Nordic Red cows. To emulate realistic on-farm recording, 5 data set replicates, each with 36,037 DMI and FE records, were simulated for real pedigree and data structure of 789 Holstein cows. Observations for the 5 DMI recording scenarios were generated by discarding data in a step-wise manner from the full simulated data per the scenario's definitions. For each of these scenarios, reliabilities were calculated as correlation between the true and estimated breeding values. Variance components and genetic parameters were estimated for daily DMI, residual feed intake (RFI), and energy conversion efficiency (ECE) fitting the random regression model. Data for variance components were from 227 primiparous Nordic Red dairy cows covering 8 to 280 d in milk. Lactation-wise heritability for DMI, RFI, and ECE was 0.33, 0.12, and 0.32, respectively, and daily heritability estimates during lactation ranged from 0.18 to 0.45, 0.08 to 0.32, and 0.08 to 0.45 for DMI, RFI, and ECE, respectively. Genetic correlations for DMI between different stages of lactation ranged from −0.50 to 0.99. The comparison of different on-farm DMI recording scenarios indicated that adopting a less-frequent recording scenario (SCN3) gave a similar level of accuracy as SCN1 when 17 more daughters are recorded per sire over the 46 needed for SCN1. Such a strategy is less demanding logistically and is low cost because fewer observations need to be collected per animal. The accuracy of genomic predictions associated with the 5 recording scenarios indicated that setting up a relatively larger reference population and adopting a less-frequent DMI sampling scenario (e.g., SCN3) is promising. When the same reference population size was considered, the genomic prediction accuracy of SCN3 was only 5.0 to 7.0 percentage points lower than that for the most expensive DMI recording strategy (SCN1). We concluded that DMI recording strategies that are sparse in terms of records per cow but with slightly more cows recorded per sire are advantageous both in genomic selection and in traditional progeny testing schemes when accuracy, logistics, and cost implications are considered.

In high-yielding dairy cattle, severe postpartum negative energy balance is often associated with metabolic and infectious disorders that negatively affect production, fertility, and welfare. Mobilization of adipose tissue associated with negative energy balance is reflected through an increased level of nonesterified fatty acids (NEFA) in the blood plasma. Earlier, identification of negative energy balance through detection of increased blood plasma NEFA concentration required laborious and stressful blood sampling. More recently, attempts have been made to predict blood NEFA concentration from milk samples. In this study, we aimed to develop and validate a model to predict blood plasma NEFA concentration using the milk mid-infrared (MIR) spectra that are routinely measured in the context of milk recording. To this end, blood plasma and milk samples were collected in wk 2, 3, and 20 postpartum for 192 lactations in 3 herds. The blood plasma samples were taken in the morning, and representative milk samples were collected during the morning and evening milk sessions on the same day. To predict plasma NEFA concentration from the milk MIR spectra, partial least squares regression models were trained on part of the observations from the first herd. The models were then thoroughly validated on all other observations of the first herd and on the observations of the 2 independent herds to explore their robustness and wide applicability. The final model could accurately predict blood plasma NEFA concentrations 1.2 mmol/L NEFA, the model clearly underestimated the true level. Additionally, we found that morning blood plasma NEFA levels were predicted with significantly higher accuracy using MIR spectra of evening milk samples compared with MIR spectra of morning samples, with root mean square error of prediction values of, respectively, 0.182 and 0.197 mmol/L, and R2 values of 0.613 and 0.502. These results suggest a time delay between variations in blood plasma NEFA and related milk biomarkers. Based on the MIR spectra of evening milk samples, cows at risk for negative energy status, indicated by detrimental morning blood plasma NEFA levels (>0.6 mmol/L), could be identified with a sensitivity and specificity of, respectively, 0.831 and 0.800. As this model can be applied to millions of historical and future milk MIR spectra, it opens an opportunity for regular metabolic screening and improved resilience phenotyping. ispartof: JOURNAL OF DAIRY SCIENCE vol:103 issue:7 pages:6422-6438 ispartof: location:United States status: published

Microcrystalline cellulose (MCC) has several applications in food and pharmaceutical industries but the nutritional value for dairy cows and effects on in vivo digestion are not known. A feeding experiment was conducted using 24 dairy cows. The cows were offered MCC originating from unbleached softwood kraft pulp at 0, 10 or 100 g per kg diet dry matter (DM) to replace barley grain in the diet. The total daily DM intake was on average 25.6 kg and not significantly affected by the diet. Positive effects on rumen fermentation could not be demonstrated in a feeding situation where total mixed ration and a concentrate proportion of 0.50 on DM basis was used. Diet organic matter digestibility was not affected by MCC inclusion but fibre digestibility improved and the additional MCC fibre was virtually completely digested. The production potential of MCC was lower than that of barley grain as daily yields of energy-corrected milk, milk fat and protein, and milk protein concentration decreased when MCC replaced barley grain in the diet. Based on these results, MCC is not recommended as a dietary component for high-yielding dairy cows.

The main objective of this study was to assess the genetic differences in metabolizable energy efficiency and efficiency in partitioning metabolizable energy in different pathways: maintenance, milk production, and growth in primiparous dairy cows. Repeatability models for residual energy intake (REI) and metabolizable energy intake (MEI) were compared and the genetic and permanent environmental variations in MEI were partitioned into its energy sinks using random regression models. We proposed 2 new feed efficiency traits: metabolizable energy efficiency (MEE), which is formed by modeling MEI fitting regressions on energy sinks [metabolic body weight (BW0.75), energy-corrected milk, body weight gain, and body weight loss] directly; and partial MEE (pMEE), where the model for MEE is extended with regressions on energy sinks nested within additive genetic and permanent environmental effects. The data used were collected from Luke's experimental farms Rehtijarvi and Minkio between 1998 and 2014. There were altogether 12,350 weekly MEI records on 495 primiparous Nordic Red dairy cows from wk 2 to 40 of lactation. Heritability estimates for REI and MEE were moderate, 0.33 and 0.26, respectively. The estimate of the residual variance was smaller for MEE than for REI, indicating that analyzing weekly MEI observations simultaneously with energy sinks is preferable. Model validation based on Akaike's information criterion showed that pMEE models fitted the data even better and also resulted in smaller residual variance estimates. However, models that included random regression on BW0.75 converged slowly. The resulting genetic standard deviation estimate from the pMEE coefficient for milk production was 0.75 MJ of MEI/kg of energy-corrected milk. The derived partial heritabilities for energy efficiency in maintenance, milk production, and growth were 0.02, 0.06, and 0.04, respectively, indicating that some genetic variation may exist in the efficiency of using metabolizable energy for different pathways in dairy cows.

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 (∆BW) 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 ∆BW) 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 ∆BW 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 ∆BW on DMI in all lactation periods. Based on results from RFI model [2], the partial regression coefficients of DMI on ECM, MBW, and ∆BW 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. Key words: residual feed intake, dairy cattle, energy sink, lactation stage, genetic parameter

In high yielding dairy cattle, severe postpartum negative energy status is often associated with metabolic and infectious disorders that negatively affect production, fertility and welfare. Mobilization of adipose tissue associated with a negative energy status is reflected through an increased level of non-esterified fatty acids (NEFA) in the blood plasma. Earlier, identification of a negative energy status through the detection of increased blood plasma NEFA concentration required laborious and stressful blood sampling. More recently there have been attempts to predict blood NEFA concentration from milk samples. This study aimed to develop and validate a model to predict the blood plasma NEFA concentration using milk mid-infrared (MIR) spectra that are routinely measured in the context of milk recording. To this end, blood plasma and milk samples were collected in weeks 2, 3 and 20 post-partum for 192 lactations in 3 different herds. The blood plasma samples were taken in the morning, while representative milk samples were collected during the morning and evening milk session on the same day. To predict the blood plasma NEFA concentration from the milk MIR spectra, partial least squares regression models were trained on part of the observations from the first herd. The models were then thoroughly validated on all other observations of the first herd and on the observations of the two independent herds to explore their robustness and wide applicability. The final model can accurately predict blood plasma NEFA concentrations below 0.6 mmol/L with a root mean square error of prediction (RMSE) of less than 0.143 mmol/L. However, for blood plasma with more than 1.2 mmol/L NEFA, the model clearly underestimates the true level. Additionally, it was found that morning blood plasma NEFA levels were predicted with a significantly higher accuracy (p = 0.009) using MIR spectra of evening milk samples compared to morning samples, with RMSEP values of respectively 0.182 and 0.197 mmol/L and R2 values of 0.613 and 0.502. These results suggest a time delay between variations in blood plasma NEFA and related milk biomarkers. Based on the MIR spectra of evening milk samples, cows at risk for a negative energy status, indicated with detrimental morning blood plasma NEFA levels (> 0.6 mmol/L), could be identified with a sensitivity and specificity of respectively 0.831 and 0.800. As this model can be applied to millions of historical and future milk MIR spectra, it opens opportunities for regular metabolic screening and improved resilience phenotyping.

Digestibility traits included in this study were dry matter digestibility (DMD, g/kg), which was calculated based on the indigestible neutral detergent fibre (iNDF, g/kg of dry matter) content in faeces (iNDFf) and in diet (iNDFd), and iNDFf predicted directly from faecal samples by near infrared reflectance spectroscopy (NIRS). The data set was collected at three research herds in Finland and one in Norway including in total 931 records from 328 lactating Nordic Red Cattle and Holstein cows. Observations were associated with different accuracy, due to the differences in sampling protocols used for collecting faecal samples. Heritability estimates varied between different sampling protocols and ranged from 0.14 ± 0.06 to 0.51 ± 0.24 for DMD and from 0.13 ± 0.05 to 0.48 ± 0.18 for iNDFf. Estimated genetic standard deviations were 10.5 g/kg and 6.2 g/kg dry matter for DMD and iNDFf, respectively. Results of our study indicated that recording only the iNDF content in the faeces is sufficient to determine genetic variation in cows’ ability to digest feed. The coefficient of genetic variation for DMD was rather small (1.7%), but could be utilized if it is supported by a positive analysis of benefits over costs. Genetic parameters for cow-specific digestibility predicted by near infrared reflectance spectroscopy

In this study, we aimed to estimate and compare the genetic parameters of dry matter intake (DMI), energy-corrected milk (ECM), and body weight (BW) as 3 feed efficiency-related traits across lactation in 3 dairy cattle breeds (Holstein, Nordic Red, and Jersey). The analyses were based on weekly records of DMI, ECM, and BW per cow across lactation for 842 primiparous Holstein cows, 746 primiparous Nordic Red cows, and 378 primiparous Jersey cows. A random regression model was applied to estimate variance components and genetic parameters for DMI, ECM, and BW in each lactation week within each breed. Phenotypic means of DMI, ECM, and BW observations across lactation showed to be in very similar patterns between breeds, whereas breed differences lay in the average level of DMI, ECM, and BW. Generally, for all studied breeds, the heritability for DMI ranged from 0.2 to 0.4 across lactation and was in a range similar to the heritability for ECM. The heritability for BW ranged from 0.4 to 0.6 across lactation, higher than the heritability for DMI or ECM. Among the studied breeds, the heritability estimates for DMI shared a very similar range between breeds, whereas the heritability estimates for ECM tended to be different between breeds. For BW, the heritability estimates also tended to follow a similar range between breeds. Among the studied traits, the genetic variance and heritability for DMI varied across lactation, and the genetic correlations between DMI at different lactation stages were less than unity, indicating a genetic heterogeneity of feed intake across lactation in dairy cattle. In contrast, BW was the most genetically consistent trait across lactation, where BW among all lactation weeks was highly correlated. Genetic correlations between DMI, ECM, and BW changed across lactation, especially in early lactation. Energy-corrected milk had a low genetic correlation with both DMI and BW at the beginning of lactation, whereas ECM was highly correlated with DMI in mid and late lactation. Based on our results, genetic heterogeneity of DMI, ECM, and BW across lactation generally was observed in all studied dairy breeds, especially for DMI, which should be carefully considered for the recording strategy of these traits. The genetic correlations between DMI, ECM, and BW changed across lactation and followed similar patterns between breeds.

Increased availability of automated weighing systems have made it possible to record massive amounts of body weight (BW) data in a short time. If the BW measurement is unbiased, the changes in BW reflect the energy status of the cow and can be used for management or breeding purposes. The usefulness of the BW data depends on the reliability of the measures. The noise in BW measurements can be smoothed by fitting a parametric or time series model into the BW measurements. This study examined the accuracy of different models to predict BW of the cows based on daily BW measurements and investigated the usefulness of modeling in increasing the value of BW measurements as management and breeding tools. Data included daily BW measurements, production, and intake from 230 Nordic Red dairy cows. The BW of the cows was recorded twice a day on their return from milking. In total, the data included 50,594 daily observations with 98,418 BW measurements. A clear diurnal change was present in the BW of the cows even if they had feed available 24 h. The daily average BW were used in the modeling. Five different models were tested: (1) a cow-wise fixed second-order polynomial regression model (FiX) including the exponential Wilmink term, (2) a random regression model with fixed and random animal lactation stage functions (MiX), (3) MiX with 13 periods of weighing added (PER), (4) natural cubic smoothing splines with 8 equally spaced knots (SPk8), and (5) spline model with no restriction on knots but a smoothing parameter corresponding to a fit of 5 degrees of freedom (SPdf5). In the original measured BW data, the within-animal variation was 6.4% of the total variance. Modeling decreased the within animal variation to levels of 2.9 to 5.1%. The smallest day-to-day variation and thereafter highest day-to-day repeatabilities were with PER and MiX models. The usability of modeled BW as energy balance (EB) indicator were evaluated by estimating relationships between EB, or EB indicators, and modeled BW change. In all cases the modeling increased the correlation and thus the reliability of the BW measurements. From all of the tested models, the best predictive value was attained by the random regression model with fixed and random animal lactation stage functions. Based on results, modeling of BW significantly increases the usefulness of BW as an EB predictor and management indicator.

This study was designed to obtain information on prediction of diet digestibility from near-infrared reflectance spectroscopy (NIRS) scans of faecal spot samples from dairy cows at different stages of lactation and to develop a faecal sampling protocol. NIRS was used to predict diet organic matter digestibility (OMD) and indigestible neutral detergent fibre content (iNDF) from faecal samples, and dry matter digestibility (DMD) using iNDF in feed and faecal samples as an internal marker. Acid-insoluble ash (AIA) as an internal digestibility marker was used as a reference method to evaluate the reliability of NIRS predictions. Feed and composite faecal samples were collected from 44 cows at approximately 50, 150 and 250 days in milk (DIM). The estimated standard deviation for cow-specific organic matter digestibility analysed by AIA was 12.3 g/kg, which is small considering that the average was 724 g/kg. The phenotypic correlation between direct faecal OMD prediction by NIRS and OMD by AIA over the lactation was 0.51. The low repeatability and small variability estimates for direct OMD predictions by NIRS were not accurate enough to quantify small differences in OMD between cows. In contrast to OMD, the repeatability estimates for DMD by iNDF and especially for direct faecal iNDF predictions were 0.32 and 0.46, respectively, indicating that developing of NIRS predictions for cow-specific digestibility is possible. A data subset of 20 cows with daily individual faecal samples was used to develop an on-farm sampling protocol. Based on the assessment of correlations between individual sample combinations and composite samples as well as repeatability estimates for individual sample combinations, we found that collecting up to three individual samples yields a representative composite sample. Collection of samples from all the cows of a herd every third month might be a good choice, because it would yield a better accuracy.

Our aim was to estimate the genetic parameters of residual energy intake (REI) and energy conversion efficiency (ECE), and their relationships with milk, feed intake and body weight (BW) and condition in Nordic Red dairy cattle with data from 400 animals. These data were analysed with repeatability and random regression models. The highest heritabilities for energy efficiency traits were obtained in the beginning and the end of the 30 week lactation period (0.21–0.40). The results suggest that the energy efficiencies in early- and mid-lactation periods are partially different traits. The genetic correlations of REI were moderate to high and positive with the other studied traits, and high and positive for ECE with milk, but moderate to low and negative with dry matter intake, BW and body condition score. Further improvements are still needed in modelling the energy efficiency traits of cows during lactation.

In a search for novel sustainable feed resources for ruminant livestock, interest towards wood-based feed materials such as bark has risen. To evaluate the feed potential of ground bark, a dairy cow feeding experiment was conducted using 24 high yielding (average milk yield in the beginning of the experiment 38.0 ± 4.53 kg/d) Nordic Red cows in a 3 × 3 Latin square design using 21-day periods. The cows were offered grass silage-based diets supplemented with 3 different concentrate feeds; a control concentrate containing no additional bark meal (C) or two different concentrate feeds containing low (LB, 87 g/kg of dry matter (DM)) or high (HB, 173 g/kg DM) level of dried ground pine bark meal supplement. Experimental concentrates were fed at a level of 12.4 kg per day resulting in feeding of ca. 1 and 2 kg of bark meal per day at low and high levels, respectively. The good quality grass silage used as the basal feed elicited high total daily feed DM intake which was on average 25.6 kg. The palatability of all experimental concentrates was good. Dietary bark meal increased the intakes of silage DM and total DM, but decreased yields of milk, energy-corrected milk, milk fat and protein, and concentrations of milk constituents although numerical differences between treatments were small. Bark meal supplements decreased linearly metabolizable energy intake, but had no significant effect on the estimated intake of amino acids absorbed from the small intestine as the concentrate feeds were balanced by rapeseed meal. Dietary bark meal decreased linearly the feed efficiency. Milk from all treatments had good sensory properties. This study demonstrated that the energy value of bark meal was very low compared to the traditional feeds as demonstrated by the decreased production results. The economic output of bark meal inclusion depends on the savings in replacing traditional feeds with bark meal, and the losses as reduced milk sales. In long term, other aspects may be considered such as potential shortage and elevated prices of traditional feeds and need to use non-human edible feed components in animal production, but under current conditions, it cannot be recommended as a feed component for high producing dairy cows.

Lypsykauden alussa lehmien rehun syönti ei aina pysty kattamaan energian tarvetta, tällöin lehmä joutuu käyttämään kudosvarastojaan lisäenergialähteenä. Tämän seurauksena lypsykauden alussa lehmän elopaino putoaa ja vastaavasti lypsykauden edetessä kudosvarastojen jälleen täydentyessä elopaino nousee. Mikäli elopainonmuutos ja sen koostumus voitaisiin mitata harhattomasti, kuvaisi elopainonmuutos suoraan lehmän energiatasetta. Myös lehmien rehun hyväksikäyttöä arvioitaessa energianmuuntoyhtälön residuaalilla (residual energy intake, REI) ennustevarmuus on ratkaisevasti liitoksissa mitattuun elopainoon ja elopainonmuutokseen. Lypsylehmän yksittäinen elopainopunnitus on riippuvainen useista tekijöistä kuten esimerkiksi ruuansulatuskanavan täyteisyydestä punnittaessa. Tämä aiheuttaa peräkkäisiin punnituksiin ylimääräistä vaihtelua, mikä vaikeuttaa energiataseen ja rehun hyväksikäytön laskemista. Mallintamalla raakahavainnot tilastollisella mallilla, voidaan merkittävästi parantaa tietojen luotettavuutta. Systemaattisten virhetekijöiden vaikutukset kuten dieetinmuutos ja laidunkauden aloitus voidaan ottaa huomioon tilastollisessa mallissa. Lehmäkohtainen vaihtelu voidaan mallintaa olettamalla joka lehmälle oma yksilökohtainen painokäyrä. Tässä tutkimuksessa selvittiin mallintamisen mahdollisuutta parantaa elopainomittausten käyttökelpoisuutta lypsylehmien energiataseen ja rehunkäyttökyvyn ennustamiseen. Tutkimusaineisto koostui MTT:n Jokioisten navetan 211 lehmän päivittäisistä paino- (kaksi mittausta per päivä), syönti -ja tuotosmittauksista sekä kuukausittaisista kuntoluokituksista, kaiken kaikkiaan aineisto sisälsi 48298 havaintopäivää. Ensikoita aineiston lehmistä oli 158. Lehmien lypsykauden keskimääräinen punnittu paino vaihteli 449 kilosta 837 kiloon keskimääräisen painon ollessa 607 kg. Kuntoluokka oli keskimäärin 2,99 vaihdellen yksittäisissä määrityksissä 2,25 – 4,5. Perusmallina käytettiin REI laskelmissa usein käytettyä lehmäkohtaista regressioyhtälöä, jossa painot mallinnetaan lypsykauden vaihetta (days in milk, DIM) kuvaavalla toisen asteen polynomilla ja lypsykauden alussa nopeasti laskevalla funktiolla exp (-0.10*DIM). Perusmallin tuloksia verrattiin satunnaisregressiosekamalliyhtälöllä laskettuihin ennusteisiin, joissa päivittäisvaihtelua kuvattiin punnitusperiodilla ja lehmäkohtaista vaihtelua mallintavilla lehmäkohtaisilla yksilöllisillä painokäyrillä. Lopuksi punnittuja painoja ja perusmallilla sekä sekamalleilla laskettuja lehmäkohtaisia elopainoja ja painomuutoksia käytettiin energiataseen mallintamiseen. Sekamalliyhtälön mukaan arvioitiin lehmät 59,3 kg ensikoita painavammiksi. Lehmien välinen varianssi oli (89,1 kg)2 ja sekamalliyhtälön jäännöstermin varianssi oli (9,1 kg)2. Sekamallin perustella laskettujen päivittäisten painomuutosten korrelaatio laskennalliseen energiataseeseen vaihteli lypsykauden eri vaiheissa, lypsykauden alussa ja lopussa korrelaatio oli yli 0,5, mutta lypsykauden keskivaiheessa selvästi alhaisempi.

Attempts to lower the environmental footprint of milk production needs a sound understanding of the genetic and nutritional basis of methane (CH4) emissions from the dairy production systems. This in turn requires accurate and reliable techniques for the measurement of CH4 output from individual cows. Many of the available measurement techniques so far are either slow, expensive, labor intensive and are unsuitable for large-scale individual animal measurements. The main objectives of this study were to examine and validate a non-invasive individual cow CH4 measurement system that is based on photoacoustic IR spectroscopy (PAS) technique implemented in a portable gas analysis equipment (F10), referred to as PAS-F10 method and to estimate the magnitude of between-animal variations in CH4 output traits. Data were collected from 115 Nordic Red cows of the Minkiö experimental dairy farm, at the Natural Resources Institute Finland (Luke). Records on continuous daily measurements of CH4, milk yield, feed intake and BW measurements over 2 years period were compiled for data analysis. The daily CH4 output was calculated using carbon dioxide as a tracer method. Estimates from the non-invasive PAS-F10 technique were then tested against open-circuit indirect respiration calorimetric chamber measurements and against estimates from other widely used prediction models. Concordance analysis was used to establish agreement between the chamber and PAS-F10 methods. A linear mixed model was used for the analysis of the large continuous data. The daily CH4 output of cows was 555 l/day and ranged from 330 to 800 l/day. Dry matter intake, level of milk production, lactation stage and diurnal variation had significant effects on daily CH4 output. Estimates of the daily CH4 output from PAS-F10 technique compared relatively well with the other techniques. The concordance correlation coefficient between combined weekly CH4 output estimates of PAS-F10 and chamber was 0.84 with lower and upper confidence limits of 0.65 and 0.93, respectively. Similarly, when chamber CH4 measurements were predicted from PAS-F10 measurements, the mean of two separate weekly PAS-F10 measurements gave the lowest prediction error variance than either of the separate weekly PAS-F10 measurements alone. This suggests that every other week PAS-F10 measurements when combined would improve the estimation of CH4 output with PAS-F10 technique. The repeatability of daily CH4 output from PAS-F10 technique ranged from 0.40 to 0.46 indicating that some between-animal variation exist in CH4 output traits.

Dry matter intake (DMI) is a key component of feed efficiency in dairy cattle. In this study, we estimated genetic parameters of DMI over the first 24 lactation weeks in 3 dairy cattle breeds: Holstein, Nordic Red, and Jersey. In total, 1,656 primiparous cows (717 Holstein, 663 Nordic Red, and 276 Jersey) from Denmark, Finland, and Sweden were studied. For each breed, variance components, heritability, and repeatability for weekly DMI were estimated in 6 consecutive periods of the first 24 lactation weeks based on a repeatability animal model. Genetic correlations for DMI between different lactation periods were estimated using bivariate models. Based on our results, Holstein and Nordic Red cows had similar DMI at the beginning of lactation, but later in lactation Holstein cows had a slightly higher DMI than Nordic Red cows. In comparison, Jersey cows had a significantly lower DMI than the other 2 breeds within the first 24 lactation weeks. Heritability estimates for DMI ranged from 0.20 to 0.40 in Holsteins, 0.25 to 0.41 in Nordic Red, and 0.17 to 0.42 in Jerseys within the first 24 lactation weeks. Genetic and phenotypic variances for DMI varied along lactation within each breed and tended to be higher in the middle of lactation than at the beginning of the lactation. High genetic correlations were noted for DMI in lactation wk 5 to 24 in all 3 breeds, whereas DMI at early lactation (lactation wk 1 to 4) tended to be genetically different from DMI in the middle of lactation. The 3 breeds in this study might differ in their genetic variances for DMI, but the differences were not statistically significant in most of the studied periods. Breed differences for the genetic variance tended to be more obvious than for heritability. The potential breed differences in genetic variation for DMI should be considered in a future study using feed intake information from multiple breeds.

Rehukustannus muodostaa suuren osan maidontuotannon kustannuksista, siksi lehmien rehun hyväksikäytöllä on ratkaiseva vaikutus maidontuotannon kannattavuuteen. Myös ympäristön näkökulmasta on lehmien rehun hyväksikäytöllä merkitystä, koska sillä on vahva yhteys ravinne- ja kasvihuonekaasujen päästöihin. Lehmien rehun hyväksikäyttöä ja siinä esiintyvää fenotyyppistä vaihtelua tarkasteltiin Rehtijärven ASMO-karjasta vuosina 2006 - 2009 kerätyn aineiston pohjalta. Aineisto käsitti kaikkiaan 145 ayrshire ensikkoa, joilta oli 3752 viikkohavaintoa. Ensikoilta mitattiin tuotos-. syönti-, paino- ja kuntotiedot poikimisesta laktaatioviikolle 30 asti. Kaikkia eläimiä ruokittiin yhtenevästi. Lehmät saivat vapaasti seosrehua, joka koostui ensimmäisen sadon nurmisäilörehusta sekä kotoisesta väkirehusta. Rehun hyväksikäyttömittareina käytettiin tuotosta syötyä energiayksikköä kohti (=EKM/ME) sekä ns. energianmuuntoyhtälön residuaalia (Residual Energy Intake, REI). REI laskettiin vähentämällä syödystä energiasta maidontuotantoon ja ylläpitoon tarvittava energia sekä painonmuutoksen energian tarve tai saanti joko energiatarvesuositusten mukaan laskettuna (=REI1) tai regressiomallilla itse aineistosta laskettuna (=REI2). Lehmien sisäinen ja välinen vaihtelu rehun hyväksikäytössä estimoitiin käyttäen SAS Mixed-mallia. Eläinten välisiä fenotyyppisiä eroja pyrittiin kuvaamaan myös luokitteluin. Rehun hyväksikäyttömittareiden yhteyksiä lehmien tuotos-, syönti- ja painotekijöihin kartoitettiin. Aineiston lehmien lypsivät keskimäärin 28,8 kg EKM päivässä ja söivät 18,7 kg kuiva-ainetta, mikä vastasi 218,6 ME MJ/pv. Keskielopaino oli suurimmalla lehmällä 752 kg ja pienimmällä 443 kg, keskimääräinen paino aineiston lehmillä oli 586 kg. Keskimääräiset rehun hyväksikäyttöarvot olivat 0,133 (SD=0,02) EKM kg/ME MJ, 3,2 (SD= 23,3) ME MJ/pv (REI1) ja 0.00 (SD=20,5) ME MJ /pv (REI2). Lasketuissa viikoittaisissa rehun hyväksikäyttöarvoissa havaittiin vaihtelua lypsykauden vaiheen mukaan. Lypsykauden vaiheen vaikutus näkyy selvimmin EKM/ME-arvoissa, mikä on ymmärrettävää. sillä ko. mittarissa ei pystytä erottamaan elopainon muutoksen vaikutuksia. Vaihtelu REI-arvoissa voi viitata siihen, että energian hyväksikäytössä olisi vaihtelua lypsykauden eri vaiheissa, osittain tämä kuitenkin lienee seurausta vaikeudesta arvioida painonmuutosta lypsykauden ensimmäisinä viikkoina. Aineiston perusteella todettiin lehmien välillä olevan fenotyyppistä vaihtelua rehun hyväksikäytössä. Eläimen osuus kokonaisvaihtelusta oli 35% (REI1), 30% (REI2) ja 50% (EKM/ME). Kun arviointiperusteena oli EKM-tuotos energiansaanti yksikköä kohti, oli hyväksikäytön paraneminen liitoksissa paitsi alhaisempaan syöntiin (r=-0,51) ja korkeampaan tuotokseen (r=0,58) niin myös lisääntyneeseen painonpudotukseen (r=-0,50). Arvioitaessa hyväksikäyttöä REI:llä oli parempi hyväksikäyttö liitoksissa alhaisempaan syöntiin (REI1: r=0.60; REI2: r=0.74), mutta ei elopainonmuutokseen (REI1: r=0.13; REI2: r=0.00).

Rehukulut ovat maidontuotannon merkittävin kustannuserä, ja lypsylehmien kyky muuttaa rehuenergiaa tehokkaasti maidon energiaksi on tärkeää sekä maidontuotannon taloudellisuuden että ympäristövaikutusten kannalta. Energiatehokkuuden ottaminen suoraan jalostustavoitteeksi saattaisi parantaa maidontuotannon taloudellisuutta ja vähentää sen ympäristövaikutuksia vaarantamatta samalla lehmien terveyttä.Tässä tutkimuksessa hyödynnettiin MTT:n Rehtijärven koetilalta vuosina 1998 – 2009 kerättyä aineistoa, joka käsitti 291:n ensimmäistä tuotantokauttaan lypsävän ASMO-ydinkarjaan kuuluvan lehmän rehunkulutus-, elopaino-, kuntoluokka- ja tuotostiedot laktaatioviikoilta 2 – 30. Näiden tietojen perusteella aineistosta arvioitiin perinnölliset tunnusluvut rehutaulukoiden mukaan arvioidulle energiataseelle ja lehmän energiatehokkuutta kuvaavalle aineiston perusteella lasketulle energianmuuntoyhtälön residuaalille eli “jäännösenergiankulutukselle”. Lisäksi arvioitiin näiden ominaisuuksien perinnölliset yhteydet lehmien maidontuotannon, kuiva-aineen syönnin, elopainon ja kuntoluokan kanssa. Ominaisuudet analysoitiin satunnaisregressiomallilla, jossa kiinteinä tekijöinä olivat lehmän poikimavuosi-kuukausi ja poikimaikä ja satunnaistekijöinä lehmän pysyvät ympäristötekijät ja eläintekijät mallinnettuina toisen asteen Legendre-polynomeilla. Energiataseen ja energiatehokkuuden periytymisasteen arviot olivat korkeimmat heti lypsykauden alussa, putosivat lähelle nollaa laktaatioviikkoina 10 – 20, ja alkoivat sen jälkeen taas nousta kohti laktaatioviikkoa 30. Korkeimmillaan periytymisasteen arviot energiatehokkuusmitoille olivat 0,20 – 0,35. Kumpikin mitta vaikutti koostuvan kahdesta suureksi osaksi erillisestä ominaisuudesta, ja energia suuntautuukin lypsykauden alussa etupäässä maidontuotantoon ja myöhemmässä vaiheessa enemmän lehmien kudosenergiavarastojen täydennykseen ja kasvuun. Energiamittojen välinen geneettinen korrelaatio oli voimakas ja positiivinen, ja yleisesti molempien mittojen geneettiset korrelaatiot muiden ominaisuuksien kanssa olivat samansuuntaisia: kohtalaisia tai voimakkaita ja positiivisia kuiva-aineen syönnin, elopainon ja kuntoluokan kanssa, ja lypsykauden alussa kohtalaisia ja negatiivisia mutta laktaatioviikoilta 6-7 eteenpäin jo positiivisia ja korkeimmillaan kohtalaisia maidontuotannon kanssa. Näin ollen energiatehokkuudeltaan laskennallisesti parempien lehmien suosiminen jalostusvalinnassa johtaisi epäsuorasti elopainoltaan ja rehunkulutukseltaan pienempiin lehmiin, mutta myös lehmien lisääntyneeseen kudosenergian hyödyntämistarpeeseen ja jyrkempään lypsykäyrän muotoon.

The relationship of milk fat–protein ratio (FP), body condition score (BCS), body weight (BW) and their changes (ΔBCS, ΔBW) to energy balance (EB) in early lactation, and usefulness of the traits for predicting of EB of primiparous Finnish Red Dairy Cattle were studied. BW on the first test-day after calving correlated negatively (r=−0.30; P

Lypsylehmät ovat tuotoskauden alkuvaiheessa tyypillisesti negatiivisessa energiataseessa, kun energian tarve kasvaa maitotuotoksen lisääntyessä nopeammin kuin energian saanti rehusta. Energiavajausta täydentääkseen lehmät mobilisoivat kudoksiensa rasvavarastoista rasvahappoja ja glyserolia. Lehmät mobilisoivat kudoksistaan myös aminohappoja, vaikka niillä ei rasvavarastoihin verrattavissa olevia valkuaisvarastoja. Tuotoshuipun jälkeen, rehun syönnin lisääntyessä, energiatase kääntyy vähitellen positiiviseksi ja lehmät alkavat jälleen kartuttaa mobilisoituja kudosvarastojaan. Kudosvarastojen kartuttaminen jatkuu loppulypsykauden ja ummessaolokauden ajan, aina seuraavaan poikimiseen saakka. Tuotoskauden alun negatiivinen energiatase on lehmille luonnollinen sopeutumismekanismi, johon liittyy varsin monimutkainen hormonaalinen säätely. Jalostusvalinta on kuitenkin tuottanut lehmiä, joiden kyky tuottaa runsaasti maitoa perustuu osittain lisääntyneeseen taipumukseen mobilisoida kudosvarastoja, vaikka myös rehunsyöntikyky on lisääntynyt jalostusvalinnan myötä. Lisääntynyt kudosmobilisaatio ja syvempi energiataseen vaje ovat lisänneet lehmien hedelmällisyys- ja terveysongelmia. Voimakkaasti negatiivinen energiatase viivästyttää kiimakiertojen alkamista ja heikentää tiinehtyvyyttä. Runsas rasvahappojen mobilisaatio lisää rasvan kertymistä maksaan, mikä voi haitata maksan toimintaa. Lisääntyneen ketoainetuotannon on todettu heikentävän immuunijärjestelmän toimintaa. Voimakas metabolinen stressi saattaa myös vaikuttaa lehmien käyttäytymiseen ja heikentää niiden hyvinvointia. Lehmien alkulypsykauden energiavajausta pyritään yleensä vähentämään lisäämällä väkirehun osuutta ruokinnassa. Liian runsas väkirehuruokinta lisää kuitenkin pötsin happamoitumisen riskiä, heikentää karkearehun sulavuutta ja on tuotosvasteeltaan tehotonta. Myös valkuaisruokinta vaikuttaa energiataseeseen: runsas aminohappojen saanti pyrkii lisää maitotuotosta ja lisää siten energian tarvetta. Lypsykauden keski- ja loppuosa ja ummessaolokausi, jolloin lehmät ovat yleensä positiivisessa energiataseessa, ovat lehmien terveyden kannalta huomattavasti ongelmattomampia kuin tuotoskauden alku. Tässä vaiheessa on kuitenkin vältettävä yliruokintaa ja lehmien liiallista lihomista, koska lihavien lehmien energiatase poikimisen jälkeen on negatiivisempi kuin normaalikuntoisten. Yliruokinta on myös taloudellisesti tehotonta. Tutkimuksessa mallinnetaan lypsylehmän energiatasetta tuotoskauden eri vaiheissa. Aineistona käytetään aiemmissa kotimaisissa tutkimuksissa kerättyjä lehmäkohtaisia syönti- ja tuotostietoja, jotka analysoidaan meta-analyysin avulla siten, että tutkimusolosuhteiden (mm. paikka) vaikutus huomioidaan mallissa satunnaistekijänä. Väkirehun osuuden ja ruokinnan valkuaispitoisuuden vaikutusta testataan lisäämällä nämä tekijät tilastolliseen malliin. Lisäksi mallissa huomioidaan poikimakerta. Mallinnuksessa saatua tietoa energiataseen muutoksesta tuotoskauden aikana sekä ruokinnan vaikutuksesta energiataseeseen voidaan käyttää ruokinnan suunnittelun kehittämisen työkaluna. Energiataseen mallintamisen lisäksi testataan sen ennustamista tilatasolla käytettävissä olevan tiedon (kuntoluokka, maidon pitoisuuden muutokset) perusteella.

Karkearehun ruokintapaikkojen määrä on usein pihatoissa rajoitettu, eivätkä kaikki lehmät mahdu syömään samanaikaisesti. Lehmillä on kuitenkin luontainen taipumus syödä yhtä aikaa, varsinkin uuden rehun jaon jälkeen ruokintapöydällä on tungosta. Tutkimme ruokintapöytäpaikkojen rajoittamista MTT:n Minkiön pihatossa. Selvitimme myös lehmän poikimakerran ja väkirehunruokintatason nostamisen vaikutukset lehmien tuotantoon, syöntiin ja käyttäytymiseen. Kokeessamme oli 36 ayrshire-lehmää, joista 12 oli ensikoita. Lehmillä oli puolet koeajasta oma ja puolet ajasta kahden muun lehmän kesken jaettu säilörehun syöntipaikka. Jaetulla paikalla oli 1 ensikko, 1 kaksi ja 1 kolme kertaa poikinut lehmä. Kaikilla ruokintapaikoilla oli tarjolla hyvälaatuista säilörehua vapaasti. Väkirehuruokintatasoja oli kaksi; puolella lehmistä oli koko kokeen ajan rehuannoksen kuiva-aineesta 45 % ja puolella 57 % väkirehua. Väkirehu tarjottiin väkirehukioskeista sekä lypsypaikalta. Koe toteutettiin kahdessa 4 viikon jaksossa cross over-kokeena ruokintapaikkojen suhteen. Jaksolla 2 lehmät, joilla jaksolla 1 oli oma ruokintapaikka, jakoivat paikan kahden muun lehmän kanssa ja jaksolla 1 jaetulla paikalla olleet saivat omat paikat. Jaksojen viimeisillä viikoilla rekisteröitiin maitomäärä jokaiselta lypsykerralta ja maitonäytteet neljältä lypsykerralta. Eläinkohtaiset väkirehun syöntimäärät kirjautuivat automaattisesti kioskeista ja säilörehun syöntimäärät, -kerrat ja -ajat vaakakupeista. Eläinten käyttäytyminen rekisteröitiin neljänä päivänä molemmilla jaksoilla paikanpäällä tarkkaillen. Lehmiä havainnoitiin 3 kertaa 1,5 h ajan, yhteensä 36 tuntia. Lehmän sijainti kirjattiin 5 minuutin välein ja kahden lehmän välisiä sosiaalisia tapahtumia havainnoitiin jatkuvasti. Säilörehun ruokintapaikan jakaminen ei vaikuttanut lehmien säilörehun syöntimääriin eikä maitotuotoksiin, mutta vähensi hieman syöntikertoja (10,7 vs 11,3 krt/vrk; P=0,12). Säilörehun syöntiin lehmät käyttivät 141 min/vrk omalla ja 137 min/vrk jaetulla paikalla. Omalla paikalla lehmät seisoivat hieman pidempään, kuin jaetulla paikalla. Jaetun syöntipaikan lehmät käyttivät enemmän aikaa makaamiseen. Runsaampi väkirehuruokinta vähensi syödyn säilörehun määrää, syöntikertoja ja syöntipaikalla vietettyä aikaa. Vähemmän väkirehua saaneet lehmät söivät enemmän säilörehua ja seisoivat pidempään syöntipaikalla. Runsaammin väkirehua saaneet lehmät käyttivät säilörehun syönnistä vapautuneen ajan makaamiseen. Säilörehun syöntipaikan jakaminen lisäsi sosiaalisia yhteenottoja. Erityisesti ensikot olivat sosiaalisissa yhteenotoissa vanhempia lehmiä useammin aggressioita vastaanottavana osapuolena. Hyvälaatuista säilörehua vapaasti tarjottaessa syöntipaikan jakaminen kolmen lehmän kesken ei vaikuta tuotoksiin tai säilörehun syöntiin, mutta lisää lehmien välisiä sosiaalisia yhteenottoja, etenkin ensikoilla. Ruokintapaikan jakamisen vaikutukset syöntikäyttäytymiseen olivat kokeessamme vähäiset, joskin jaettu paikka hieman vähensi syöntikertoja sekä syöntipaikalla seisomista. Voimakkaampi väkirehuruokinta jätti lehmille enemmän aikaa makaamiseen. Vaakakuppipaikalla lehmä saa syödä varsin rauhassa, joten tulosten tulkinnassa on huomioitava, että kokeemme tulokset eivät ole sovellettavissa avoimeen ruokintapöytään.

The differences in body weight (BW) and measurements between the cows of today and the early 70s was evaluated and the usefulness of heart girth (HG), wither height, body length (BL) and body condition score (BCS) as predictors of the BW of modern Finnish Ayrshire cows was estimated. During the last three decades, the BW, HG and BL has increased indicating change in body conformation. The BW prediction equation based on early 70s data underestimate the BW of modern Ayrshire cows. Based on current data it is recommended to use different models to predict BW for primiparous and multiparous cows. From single measurements, HG predicted BW most accurately. Inclusion of BL in model gave slight improve in BW prediction, especially for primiparous cows. An additional term of age or days in milk (DIM) for primiparous cows and BCS or DIM for multiparous cows along with HG increased slightly the accuracy of BW prediction.

Lehmien tuotantokyvyn jalostus on johtanut paitsi tuotosten niin myös lehmien elopainon ja syöntikyvyn lisääntymiseen. Syöntikyvyn lisääntyminen ei kuitenkaan ole riittävä kattamaan suurempien tuotosten ja kookkaampien eläinten ylläpidon vaatimaa energiatarvetta, joten lehmät joutuvat lypsykauden alkussa mobilisoimaan puuttuvan energian kudosvarastoistaan. Tästä johtuen lehmien energiatase (EB) on lypsykauden alussa lähes poikkeuksetta negatiivinen. Runsas kudosvarastojen mobilisointi ei ole suotavaa, sillä se johtaa usein heikentyneeseen hedelmällisyyteen ja lisääntyneeseen sairastavuuteen. Energiataseen laskemista varten tarvitaan paitsi tuotos- ja elopainotiedot niin myös tiedot rehunsyönnistä ja rehujen koostumuksesta (EB= syöty energia – maidon energia – ylläpitoenergia). Rehun syöntikyvyn tai syöntitietojen perusteella lasketun EB huomioiminen jalostusvalinnassa on ongelmallista, koska syödyn rehun määrän luotettava mittaaminen tilatasolla on nykyisin menetelmin hankalaa. Energiataseen huomioiminen jalostusvalinnassa edellyttääkin helpompaa menetelmää taseen arvioimiseen. Tämän tutkimuksen tavoitteena oli selvittää kuntoluokan ja elopainon muutoksen sekä maidon rasva-valkuaisuhteen (R-V suhde) käyttökelpoisuutta EB indikaattorina. Tutkimuksen aineisto koostuu MTTn Rehtijärven ASMO-karjassa vuosina 1998-2001 tehdyissä ruokintakokeisssa kerätystä datasta. Kokeissa oli kaikkiaan 146 ensikkoa. Kokeissa lehmiä ruokittiin seosrehulla, joka sisälsi säilörehua ja väkirehua sekä kahdessa kokeessa myös tuoreleikettä 100 g/ kg ka. Koeruokinnat poikkesivat toisistaan dieetin väkirehu- ja valkuaispitoisuuden suhteen. Keskimäärin väkirehua oli koedieeteissä 470 g/kg ka ja se vaihteli koeasetelman mukaan 450 – 570 g/kg ka. Seosten väkirehun valkuaispitoisuus puolestaan vaihteli 170 –210 g/kg ka. Koeaineisto sisälsi ensikoiden viikoittaiset keskimääräiset rehunsyönti- ja tuotostiedot. Maidon pitoisuudet oli määritetty neljän viikon välein. Elopaino perustui rinnanympärysmittauksiin, rinnanympärys mitattiin koekaudella 5-7 kertaa kokeesta riippuen. Kuntoluokka arvioitiin neljän viikon välein. Havaintojen perusteella eläimille laskettiin viikoittaiset EB. EB-laskuissa energiantarve ylläpitoon ja maidontuotantoon laskettiin MTT 2006 Rehutaulukot ja Ruokintasuositukset- julkaisussa annettujen ylläpito ja maidontuotanto energiantarvekaavojen mukaan. Laskettu keskimääräinen EB oli ensimmäisinä laktaatioviikkoina selvästi negatiivinen ollen alhaisimmillaan -31 MJ ME/pv. Positiiviseksi energiatase muuttui keskimäärin viikolla 11. Keskimääräiset elopainon ja kuntoluokan muutokset tukivat hyvin laskettua EB:tta. Elopaino laski aina viikolle 9 ja kääntyi nousuun viikolla 12. Kuntoluokka oli alhaisimmillaan viikolla 10, jonka jälkeen lähti hitaaseen nousuun. Elopainon muutoksen, kuntoluokan muutoksen sekä maidon R-Vsuhteen korrelaatio laskettuun EB oli kohtalainen. Rasva-valkuaissuhteella korrelaatio oli vierova ja kuntoluokka ja elopainon muutos olivat positiivisessa yhteydessä EB. Elopainon muutoksen ja EB:n välinen korrelaatio oli hieman alhaisempi kuin R-Vsuhteen ja kuntoluokan muutoksen korrelaatio EB:een. Regressio-analyyseissä testattiin eläimen elopainon, kuntoluokan, R-V suhteen, näissä tapahtuneen muutoksen sekä em. tekijöiden yhdysvaikutusten kykyä ennustaa ensimmäisen poikimisen jälkeisen koelypsyviikon energiatasetta. Parhain energiatasetta kuvaava regressio-yhtälö pystyi kuvaamaan vain 32.6 % EBn vaihtelusta. Tärkeimmät selittävät tekijät olivat R-V suhde ja kuntoluokan muutos.

The experiment was conducted to study use of barley fibre and wet distillers’ solubles (WDS), by-products from integrated starch–ethanol production, as feed in dairy cows’ diet. Barley fibre is a fibrous by-product with high content of neutral detergent fibre and low content of starch. Wet distillers’ solubles is the non-fermentable residue after distillation of ethanol. It has a high crude protein content with a high rumen degradability. Ayrshire cows, 12 multiparous and 12 primiparous, were divided into 6 blocks of 4 cows according to parity and calving date. Cows in each block were fed four different total mixed rations (TMR) according to a balanced 4 × 4 Latin Square design within a 2 × 2 factorial arrangement of the treatments. Treatments were two different energy sources (barley (B) or barley + barley fibre (BF, 1:1)) with two protein sources (rapeseed meal (RSM) or RSM + WDS). Thus, the treatments were B, B + WDS, BF and BF + WDS. Grass silage was the forage (400 g/kg diet dry matter). On the B + WDS and BF + WDS diets, the amount of WDS in TMR was 120 g/kg dry matter (DM). The crude protein content of the diets was 180 g/kg DM. Replacing half of the barley grain with barley fibre increased (P versus 33.0 kg/day) but had no effect on DM intake (DMI) (21.5 kg/day versus 21.7 kg/day). Replacement caused a small, but significant (P versus 34.2 g/kg) with no change in protein yield. Inclusion of barley fibre in the diet had no effect on milk fat content but changed (P versus 22.1 kg/day), milk yield (31.7 kg/day versus 33.6 kg/day) and yields of milk components. Inclusion of WDS in the diet decreased efficiency of N utilization. Barley fibre was a good fibrous component in concentrates for dairy cows’ TMR, but WDS was an inferior protein feed to RSM as a feed for lactating Ayrshire dairy cows.

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.

Ruokintatyöpanoksen vähentämiseksi jaetaan seosrehutiloilla rehu usein vain kerran päivässä. Onko seoksen jakokerroilla vaikutusta syöntiin ja maitotuotoksiin ei paljoa ole selvitetty. Joissakin kokeissa on todettu, että jaettaessa seosrehu useamman kerran päivässä saadaan positiivinen vaikutus syöntiin ja tuotoksiin, mutta toisissa kokeissa on havaittu, että harvemmin ruokitut lehmät käyttäytyvät rauhallisemmin, syövät ja tuottavat enemmän. Tämän tutkimuksen tarkoituksena oli selvittää seosrehun ruokintakertojen määrän vaikutusta lehmien syöntiin, maidontuotantoon, maidonkoostumukseen ja käyttäytymiseen. Koelehminä oli 38 Ay lehmää, joista 16 oli ensikoita. Kokeessa puolelle koelehmistä jaettiin seosta kerran (1x) ja puolelle viisi kertaa (5x) päivässä. Lehmät tulivat kokeeseen poikimisen jälkeen ja olivat kokeessa laktaatioviikolle 28 asti. Molempia ryhmiä ruokittiin samalla seoksella, jossa oli nurmisäilörehua ja väkirehuseosta, joka sisälsi (g/kg) ohraa (606), rypsipuristetta (270), melassileikettä (100) ja kivennäistä (24). Väkirehua seoksessa oli 510 g/ kg kuiva-ainetta. Seoksessa oli kuiva- ainekilossa 1,02 ry, 170 g raakavalkuaista ja 101 g OIV:ta. Lehmien maitotuotos, rehunkulutus ja elopaino mitattiin päivittäin. Maidon pitoisuudet määritettiin kahden viikon välein. Lehmät kuntoluokitettiin poikimapäivänä ja tämän jälkeen kahden viikon välein. Lehmien käyttäytymistä seurattiin kolmena päivänä 15 h ajan aikavälillä 6:00 – 21:00. Lehmät söivät seoksen kuiva-ainetta 20,9 kg, kun rehua jaettiin kerran päivässä ja 19,9 kg, kun seosta jaettiin viisi kertaa päivässä (P

Maatiloilla on menossa voimakas rakennekehitys, jonka seurauksena muodostetaan suurempia tuotantoyksiköitä. Tilat ja karjakoot kasvavat, jolloin pihatot yleistyvät ja ruokintasysteemit muuttuvat. Suurissa tuotantoyksiköissä pihatto-olosuhteissa seosrehuruokintastrategia on yleisesti valittu ruokintasysteemi, mutta pihatoissa on usein käytössä myös väkirehukioskit.Tämän tutkimuksen tarkoituksena oli selvittää väkirehukioskin merkitystä seosrehuruokinnan täydentäjänä pihatossa. Tutkimuksessa verrattiin pelkän seosrehuruokinnan sekä ruokinnan, jossa laimeampaa perusseosta täydennetään lypsykauden alussa väkirehuautomaatista saatavalla lisäväkirehuannoksella vaikutusta lypsylehmien syöntiin, maidontuotantoon ja maidonkoostumukseen.Koe suoritettiin MTT:n Minkiön tutkimuspihattossa Jokioisilla. Koelehmiä oli kaikkiaan 39 Ay lehmää. Puolet koelehmistä (ryhmä S) sai ainoana rehuna seosrehua (seos A), jossa väkirehun osuus kuiva-aineesta oli 51% ja puolet (ryhmä KS) seosta (seos B), joissa väkirehun osuus oli kuiva-aineesta 45%. KS-ryhmä sai lisäksi lypsykauden alussa lisäväkirehua kioskista ja annos oli laktaatiopäivinä 1 – 100 useammin poikineilla 6,5 kg/pv ja ensikoilla 5,5 kg/pv. Laktaatiopäivinä 101 – 150 oli lisäväkirehuannos useammin poikineilla 3,0 kg/pv ja ensikoilla 2,5 kg/pv. Loppulypsykaudella (yli 150 päivää poikimisesta) sai KS-ryhmä pelkästään seosta B, lisäväkirehua ei annettu. Seosrehuissa (A ja B) käytettiin samaa nurmisäilörehua ja MTT:llä sekoitettua väkirehua. Väkirehukioskista saatava lisäväkirehu oli teollista täysrehua.Kokeenaikaisiin keskimääräisiin kuiva-aine syönteihin ja ravintoaineiden saantiin ei kioskilisällä ollut vaikutusta. Ensimmäisen 100 lypsypäivän aikana syönti kehittyi samaa vauhtia niin pelkällä seos kuin seos ja kioskiryhmälläkin. Sen sijaan seuraavan 50 päivän aikana oli syönti seosryhmällä korkeampi (P

Fifty primiparous Finnish Ayrshire cows were used in 2×2 factorial study. The factors were the protein-feeding strategy: constant (cCP) or variable (vCP) protein content in concentrate during lactation and the use of a commercial health product from 2 weeks pre- to 8 weeks postpartum. On treatment cCP, the CP content of the concentrate was 180 g/kg in dry matter (DM) throughout the lactation, and on vCP treatment, the CP content was 210, 180 and 150 g/kg DM during lactation days 0–100, 101–200 and 201–305, respectively. The concentrate blends included barley, oats, rapeseed meal, molassed sugar beet pulp and minerals and vitamins. Grass silage and ensiled wet sugar beet pulp (100 g/kg DM in TMR) were used as forage. The forage-to-concentrate ratio in TMR was 55:45 on both treatments. The experimental period was 305 days of the first lactation. The average daily milk yield (cCP: 26.3 kg/day vs. vCP: 27.5 kg/day) was higher (P

The effect of total mixed ration (TMR) with constant (TMR1) or decreasing (TMR3) proportion of concentrate in dry matter (DM) and with different crude protein (CP) content of concentrate (170 or 200 g/kg DM) on the performance of 51 first parity Ayrshire cows was studied. On TMR1 diet the forage to concentrate ratio in DM was 55:45 throughout the lactation. On TMR3 the forage to concentrate ratio was 45:55, 55:45 and 65:35 during the lactation days 0–100, 101–200 and 201–305, respectively. There was no significant interaction between feeding strategy (TMR1 or TMR3) and CP content of the concentrate on the performance parameters studied. Feeding strategy had no effect on energy corrected milk (ECM) production (26.6 vs. 27.1 kg/day), milk composition, DM intake (18.0 vs. 18.2 kg/day) or post partum development of the body condition score of the cows. The higher CP content of the concentrate increased (P

The performance of 45 primiparous Ayrshire cows fed total mixed ration (TMR) with constant (TMR1) or variable (TMR3) proportion of concentrate in dry matter was studied. On TMR1 treatment the forage to concentrate ratio of TMR was 53:47 in dry matter (DM) throughout the lactation. On TMR3 the forage to concentrate ratio increased during the lactation being 43:57, 53:47 and 63:37 on 0–100, 101–200 and 201–305 days post partum, respectively. The experimental period was 305 days of the first lactation. The feeding strategy had no significant effect on average milk yield. The energy corrected milk yield was 24.4 kg/day on TMR1 and 24.3 kg/day on TMR3 treatment. Also milk protein content was not affected by the treatment, but the milk fat content tended (P

A field study was conducted to study the relationships between average daily gain (ADG) of heifers and their first lactation milk yield. To predict the body weight (BW) the heart girth of 4058 heifers was measured by AI-technicians. Based on these measurements and national milk recording data, the ADGs before and after breeding were calculated. Other variables collected were after calving BW, calving age, and milk production yields on first lactation. After edits the final data included 2194 Ayrshire (Ay) and 738 Friesian (Fr) heifers and their 7215 relatives. Data used for calving BW and ADGs after breeding was 43% smaller because of missing information. The average BW and age at breeding were 356 kg and 483 days for Ay and 376 kg and 484 days for Fr, respectively. The after calving BW for Ay was 502 kg and for Fr 520 kg. The weights correspond to ADGs of 660 g (S.D. 99 g) and 695 g (S.D. 114 g) before breeding, and 497 g (S.D. 190 g) and 492 g (S.D. 196 g) after breeding for Ay and Fr breeds, respectively. The average 305-day milk yield for Ay was 6198 kg and for Fr 6440 kg. Positive genetic correlations between growth rate before (0.13±0.11) and after (0.34±0.17) breeding and milk yield as well as calving BW and milk yield (0.26±0.13) were found. The environmental correlation between ADG before breeding and milk yield was positive (0.13±0.04), while the ADG after breeding and milk yield was uncorrelated (−0.01±0.04). Based on the feeding trials a negative environmental correlation between ADG before breeding and milk yield could have been expected. It was concluded that the negative effect could not be estimated, because of the disturbance caused by herd effect. Also, the fact that most of the heifers had been reared within recommended limits of ADG could have affected the results.

The effect of different feeding intensity at two stages of gestation on performance of primiparous cows was studied in 40 pregnant Ayrshire cows. The feeding intensity was either medium (M) or high (H) in period 1 (2–6 months of pregnancy) or period 2 (7–9 months of pregnancy) resulting in treatments MM, MH, HM and HH. Before pregnancy all heifers were reared to gain 650 g/day. In period 1, heifers on H feeding intensity, grew significantly faster than heifers on M (844 vs. 638 g/day; SEM=18.9). Daily gains in period 2 were affected by feeding intensity in period 1 and were 710, 1042, 636 and 874 g on MM, MH, HM, and HH diets, respectively. The body weights at calving were 462, 498, 480 and 499 kg on MM, MH, HM and HH diet, respectively. Feeding intensity in period 1 had no effect on milk production, but H plane of nutrition in period 2 increased milk yield by approximately 11% (22.6 vs. 20.3 kg/day, P

Pre-pubertal (86-220 kg BW) Finnish Ayrshire heifers were used to study the effect of feeding level and nitrogen source on GH, IGF-I, and prolactin (PRL) receptors in mammary and liver parenchymal tissue. The heifers were fed a hay-barley diet supplemented with either urea or rapeseed meal. The treatments were: (1) LU, low feeding level+urea; (2) LR, low feeding level+rapeseed meal; (3) HU, high feeding+urea; (4) HR, high feeding level+rapeseed meal. The average daily gains of the heifers on LU, LR, HU and HR diets were 692, 655, 805 and 890 g. At slaughter, mammary and liver parenchymal tissue was collected for preparation of crude membranes, and ligand-binding assays were performed. Specific binding of bGH to mammary membranes could not be detected. Linear Scatchard plots were obtained showing the presence of a single class of high-affinity binding sites for IGF-I in mammary tissue. Specific binding of IGF-I to mammary membranes was unaffected by feeding level and nitrogen source. Furthermore, Scatchard...

The effect of feeding level and nitrogen source on mammary development and plasma hormone levels of pre-pubertal (86 to 220 kg) Finnish Ayrshire heifers was studied. The treatments were: (1) LU, low feeding level + urea; (2) LR, low feeding level + rapeseed meal; (3) HU, high feeding level + urea; (4) HR, high feeding level + rapeseed meal. The average daily gains of the heifers on LU, LR, HU and HR diets were 692, 655, 805 and 890 g, respectively. There was a significantly higher amount of mammary parenchymal tissue and parenchymal DNA at low (L) compared with high (H) feeding levels, but no difference in mammary weights between nitrogen sources was found. Plasma insulin concentration was greater at H compared with L feeding levels, but plasma growth hormone (GH), insulin-like growth factor-I (IGF-I) and prolactin concentrations were not significantly affected by the feeding level. The amount of mammary parenchymal tissue did not correlate with the mean plasma concentration of prolactin and insu...

The effect of the rate of increase in concentrate allowance after calving with two concentrate mixes (A and B) differing in composition was evaluated using 64 Finnish Ayrshire cows during the first 100 days of lactation. After calving, the concentrate allowance of multiparous cows was increased stepwise from 4 to 17 kg/day, and of primiparous cows from 3 to 13.5 kg/day over 12 days (F rate of increase; multiparous 1.08 kg/day, primiparous 0.88 kg/day) or 24 days (S rate of increase; mutiparous 0.54 kg/day, primiparous 0.44 kg/day). The concentrates were formulated to have similar crude protein and metabolizable energy concentrations but differing starch and NDF concentrations. For concentrate A the starch and NDF concentrations were 421 and 167 g/kg dry matter (DM) and for concentrate B 258 and 251 g/kg DM. All cows received grass silage ad libitum. The higher concentrate intake during weeks 1 to 4 of lactation with F compared with the S rate of increase caused higher DM, energy and protein intake. The higher concentrate intake for F than for S treatment in early lactation did not cause a large decrease in silage intake (8.8 v. 8.3 kg DM/day). The intake of concentrate A and B after calving did not differ for S treatment. However, for F treatment the intake of fibrous concentrate B increased faster than starch-rich concentrate A during weeks 1 to 4 of lactation. The concentrate composition had no effect on energy-corrected milk (ECM) yield during weeks 1 to 4 of lactation for S treatments, but with F treatments the cows fed B concentrate produced more milk. The F rate of increase in concentrate allowance compared with the S rate increased the calculated energy balance after calving. The rate of increase in concentrate feeding post partum or concentrate composition had no effect on DM, energy or protein intake during the whole 100-day experiment. The average ECM yield over days 1 to 100 of lactation was higher for S than for F treatments and tended to be higher with concentrate B than A. Results of this study showed that by the fast rate of increase in concentrate allowance after calving on a grass silage diet, it was possible to improve the energy status of the cows in early lactation. This had, however, no effect on production later in 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 = 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) = −2.9 (±0.56)+0.258 (±0.011) × sECM (kg/day) + 0.0148 (±0.0009) × LW (kg) −0.0175 (±0.001) × DIM −5.85 (±0.41) × exp (−0.03 × DIM) + 0.09 (±0.002) × 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) = −0.10 (±0.33) + 1.004 (±0.019) × 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.

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 Rehtijarvi 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.