The effect of a dietary butyrate supplementation on the production of fattening rabbits was examined. The control group (n=70 rabbits) was fed with granulated diet whereas the diet of butyrate group (n=70 rabbit) was supplemented with 0.2% of butyrate. The mortality rate was examined on a larger population (n=1050 rabbits/group). Butyrate group had lower weight gain at the ages of 46-52 and 60-66 days (-20 and - 17 %, respectively; P>0.001) but higher weight gain at 53-59 days of age (+13%; P<0.05). Butyrate group consumed less feed than the control group between 38-45, 46-52 and 60-66 days (-2.4%, P<0.001; -5.7%, P<0.01; - 4.9%, P<0.05, respectively). The feed conversion ratio of the butyrate group was worse between 46-52 days of age (+19%; P<0.01) but favourable at the ages of 53-59 and 67-73 days (-15% and -9%, respectively; P<0.05). Concerning the whole fattening period the weight gain, the feed intake and the feed conversion ratio of the groups did not differ. In the larger examined population, 4.0% and 6.3 % mortality was observed in the control and butyrate groups, respectively. The parasitological tests resulted only negative samples independently of groups. It can be concluded that dietary butyrate supplementation has not improved the performance of the growing rabbits.

Near-infrared (NIR) spectroscopy was employed to determine the differences between forage mixtures of winter cereals and Italian ryegrass and to evaluate fermentation characteristics of mixed silages. Forages were harvested on five phases (Cuts 1–5), with 1 week interval (n = 100). The yield of the last harvest (Cut 5) was ensiled and analyzed on four different days (D0, D7, D14, and D90) (n = 80). Principal component analysis based on the NIR data revealed differences according to the days of harvest, differences between winter cereals and Italian ryegrass forages, and differences in the fermentation stages of silages. The partial least square regression models for crude protein (CP), crude fiber (CF), and ash gave excellent determination coefficient in cross-validation (R²CV > 0.9), while models for ether extract (EE) and total sugar content were weaker (R²CV = 0.87 and 0.74, respectively). The values of root mean square error of cross-validation were 0.59, 0.76, 0.22, 0.31, and 2.36 %DM, for CP, CF, EE, ash, and total sugar, respectively. NIR proved to be an efficient tool in evaluating type and growth differences of the winter cereals and Italian ryegrass forage mixtures and the quality changes that occur during ensiling.