Browsing by Subject "dairy cow"

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  • Anttila, Anne (Helsingfors universitet, 2014)
    The aim of this study was to investigate dairy cow performance on faba bean compared to rapeseed meal on silage based diets. Increasing use of grain legumes may improve selfsufficiency of feed protein. The study was conducted at the research farm of University of Helsinki. In the experiment, eight multiparous Finnish Ayrshire cows were used. Four of them were fitted with rumen fistula. In the beginning of the experiment, cows were 100 (± 51) days in milk. Replicated 4x4 Latin square design was used: the other square consisted of cows with rumen fistulas and the other of intact cows. Treatments of the study were concentrate feeds as follows: control (no protein supplement), rapeseed meal, faba bean and mixture of rapeseed meal and faba bean. Concentrates were fed at a rate of 14 kg/d and silage was given ad libitum. Concentrate feeds including protein supplement were isonitrogenous crude protein content being approximately 200 g/kg DM. Protein supplementation increased silage intake (2,4 kg/d) and milk production (1,6 – 4,9 kg/d). Protein supplementation decreased milk fat content (41,2 vs. 45,3 g/kg DM) but increased milk protein content (35,5 vs. 34,3 g/kg). Feed nitrogen utilization to milk, AAT and ME utilizations and ECM yield to feed intake -ratio were decreased on protein supplementation. In this experiment however rapeseed meal did not give responses of same level as was expected according to results of earlier experiments. Diets including faba bean increased silage intake and milk production compared to rapeseed meal diet. Rapeseed meal diet decreased silage intake 2,7 kg and milk yield 2,5 kg compared with faba bean diet. Mixture of rapeseed and faba bean resulted in the highest milk production being 2 kg more than on average on rapeseed meal and faba bean diets. Utilization of ME and ECM yield to feed intake –ratio were increased with rapeseed meal diet. According to this study rapeseed meal as a protein supplement can be substituted by faba bean in dairy cow diets on silage based diets.
  • Niemelä, Kirsi (Helsingfors universitet, 2011)
    The aim of this study was to develop mathematical energy balance models for early and middle lactation period of dairy cows. The traits for predicting were information of diet, feed, milk production, milk composition, body weight and body condition score. This study was a part of development work of KarjaKompassi-project. The data used in this study was based on 12 feeding experiments performed in Finland. The complete data from the studies included 2647 weekly records from multiparous dairy cows and 1070 weekly records from primiparous dairy cows. The data was collected from calving to 8-28 weeks of lactation. Three-fourths of the totals of 344 dairy cows were Finnish Ayshire cows and the rest of the cows were Friesian Cattle. The cows were fed by the Finnish feeding standards. The data was handled by the Mixed-procedure of the SAS-programme. The outliers were removed with Tukey´s method. The relationship between energy balance and predictor traits was studied with correlation analysis. The regression analysis was used to predicting energy balance. To quantify the relationship of lactation day to energy balance, 5 functions were fitted. The random factor was a cow in the experiment. The model fit was assessed by residual mean square error, coefficient of determination and Bayesian information criterion. The best models were validated in the independent data. Ali-Schaeffer achieved the highest fit functions. It was used by the basal model. The error in every model grew after the 12th lactation week, because the number of records decreased and energy balance turned positive. The proportion of concentrate in the diets and concentrate dry matter intake index were the best predictors of energy balance from traits of diet. Milk yield, ECM, milk fat and milk fat-protein ratio were good predictors during lactation period. The RMSE was lower when ECM was standardized. The body weight and body condition score didn’t improve the predictive value of the basal model. The models can be used to predict energy balance in the herd level, but they are not applicable for predicting individual cow energy balance.