The effect of selected cereals contained in feed ration on the amino acid composition of cows´ milk

369 ACTA UNIVERSITATIS AGRICULTURAE ET SILVICULTURAE MENDELIANAE BRUNENSIS Volume LVIII 43 Number 5, 2010 THE EFFECT OF SELECTED CEREALS CONTAINED IN FEED RATION ON THE AMINO ACID COMPOSITION OF COWS’ MILK M. Šípalová, O. Hanuš, F. Buňka, J. Pozdíšek, V. Mrkvička, S. Kráčmar Received: July 21, 2010 Abstract ŠÍPALOVÁ, M., HANUŠ, O., BUŇKA, F., POZDÍŠEK, J., MRKVIČKA, V., KRÁČMAR, S.: The eff ect of selected cereals contained in feed ration on the amino acid composition of cows’ milk. Acta univ. agric. et silvic. Mendel. Brun., 2010, LVIII, No. 5, pp. 369–376 The aim of this study was to evaluate the possible eff ects of maize replacement in feeding rations on the amino acid content in cows´ milk. Cows were fed total mix ration based on the maize, clover silage and hay. There was a diff erence in the concentrate of the feeding ration. The fi rst group (fed maize) was the control group, another two groups were experimental, one fed wheat and second fed triticale. During six weeks, totally 26 milk samples were taken from dairy cows of Czech Pied breed. Feed groups were preferably balanced in terms of milk yield, stage and number of lactations. The samples of feedstuff s as well as milk were modifi ed for the analysis using acidic and oxidative hydrolyses. The analysis of amino acids content and composition of the sample hydrolysates was performed chromatographically by an AAA 400 analyzer, using Na-citrate buff ers and ninhydrin detection. Total nitrogen content was determined according to Kjehldahl and the crude protein of the samples was determined by conversion from the nitrogen content multiplied by appropriate factor. The high content of crude protein in wheat did not infl uenced composition of milk from dairy cows fed this type of feedstuff . With respect to resulting amino acid content and composition of milk samples, none of the tested grains can be re com men ded as a full-value maize replacement. Each feedstuff is an abundant source of several and ty pi cal amino acids in milk. However, triticale (cultivar Kitaro) seems to be acceptable replacement of maize owing to better crude protein effi ciency, composition and health indicators of milk quality. dairy cow, maize, wheat, triticale, amino acids Number of studies dealing with infl uence of se veral factors on milk yield and milk composition has been published (Masoero et al., 1998; Kuhn et al., 2006; Strusińska et al., 2006). Milk production and milk composition are aff ected by cow diet (e.g. Sinclair et al., 2003; Leiber et al., 2005; Sánchez and Ledin, 2006) and stage of the lactation (Kuhn et al., 2006), as well as cow genotype. Milk composition, and milk protein composition especially, is very important for subsequent milk processing (Leiber et al., 2005). Replacing fermentable carbohydrates with fat in the diet of high-producing dairy cows may limit synthesis of microbial protein in rumen and will decrease the fl ow of microbial protein to the small intestine (Palmquist et al., 1993). In some cases, supplementation with fat may limit the supply of amino acids to the mammary gland and reduce milk protein content (DePeters and Cant, 1992). Two independent studies (Wu and Huber, 1994; Dhiman et al., 2001) confi rm that an increase in dietary fat could decrease milk protein content. As mentioned above, milk yield is aff ected by feeding. Eff ect of diff erent amount of roughage neutral detergent fi ber (NDF) in feeding ration on milk yield was evaluated by Adin et al., (2008) Lower content of roughage NDF (12 %) with soy hulls addition increased milk yield from 32.2 to 34.6 kg and sti mula ted also milk protein production. According to Sinclair et al., (2003), fermented whole crop wheat can provide a comparable milk production to good quality grass silage and the harvesting at a later stage of maturity had negligible eff ect on milk production, although milk protein levels tended to be higher in cows fed feedstuff containing higher starch content. 370 M. Šípalová, O. Hanuš, F. Buňka, J. Pozdíšek, V. Mrkvička, S. Kráčmar Clover silage studies and studies with organically managed cows have shown that grain based supplementation increase milk protein content (Sehested et al., 2003; Cohen et al., 2006; Steinshamn, 2008). The current study is related to research of Pozdíšek and Vaculová (2008), who investigated wheat (Triticum aestivum L.) quality utilized for feeding ruminants using in vitro and in vivo methods. It is also connected to the study conducted by Pozdíšek et al., (2008), in which maize, the commonly used feedstuff , was replaced by wheat and triticale in dairy cow’s feeding ration and compositional and health indicators of milk, such as somatic cell count, lactose and fat content, solid matter content, pH, density and selected macroand micro-elements were determined. However the later study lacks an analysis of amino acids, which are considered as the building blocks of protein. Therefore, our study is aimed for determination and comparison the amino acid content in milk obtained from cows fed maize, wheat and triticale. MATERIALS AND METHODS Tested grain samples Winter wheat (cultivar Sulamit) and winter triticale (cultivar Kitaro) were selected as a substitute for maize. All plants were grown in the fi eld in the Moravia district (Agroječmínek Ltd, Chropyně, Czech Republic) in 2005. Design of the feeding experiment The experimental design comprised three feeding groups of cows. The experiment proceeded for six weeks and 26 cows of Czech Pied breed (n1 = 8; n2 = 9; n3 = 9) were included into the test. Dairy cows were fed total mixed ration on the basis of maize, clover silage and hay. Otherwise, the feeding rations diff ered only in hard fodder as can be seen in the Table I. During the experiment, one cow from the fi rst group was excluded because of illness. Other cows were healthy in terms of occurrence of milk secretion disorders. Feed groups were preferably balanced in terms of milk yield, stage and number of lactations. The tie stable and pipeline milking equipment were used in experiment. Milk sampling Animals were milked twice a day and sampled at morning milking in intervals of about seven days. On the whole, it was obtained 182 samples in the seven sampling terms using Flow milk meter (Tru-Test Ltd., New Zealand). Within groups, the individual milk samples were combined into bulk samples (three groups multiplied by seven sampling periods, n = 21). Sample preparation Prior to analysis, the samples of the grains were crushed with the grain mill (Bosh MUM 4 MUZ 4 GM 2, Robert Bosch GmbH, Stuttgart, Germany) to pass through the 1mm sieve. The milk samples were transported in cold condition (< 10 °C) to the laboratory. Then they were deepfrozen at −80 °C overnight. A erwards, the samples were lyophilisated at – 40°C and vacuum of 12 Pa for 48 hours. Reagents Hydrochloric acid, citric acid monohydrate, sodium citrate dihydrate, sodium chloride, thiodiglycol, boric acid, sodium azide, sodium hy droxide, ninhydrine, methylcellosolve, acetate buff er (pH 5.5) and hydrindantine were provided by Ingos, Ltd., Prague, Czech Republic. Sulphuric acid 96.0% p. a., Acetic acid, 85.0% p. a., peroxide 30%, sodium sulphate, cupric sulphate pentahydrate and mixed indicator 5 solution p.a., for ammonia titrations as well were supplied by Sigma Aldrich and Fluka, Inc., St. Louis, USA. Hydrolysis The sample of grain and milk were treated with acidic and oxidative hydrolysis according to Kráčmar et al., (1998, 2000), Buňka et al., (2009) and Offi - cial Journal (2009). Amino acid analysis Amino acid content and composition were determined using ion-exchange chromatography with post-column ninhydrine derivatization and spectrophotometric detection (440 nm for proline and 570 nm for other amino acids) according to Kráčmar et al., (1998, 2000), and Buňka et al., (2009). Total nitrogen content and crude protein determination Total nitrogen content was determined according to Kjehldahl using Pro-Nitro A (J. P. Selecta, s. a., Spain) apparatus. According to Pozdíšek and Vaculová (2008), the crude protein (CP) of the grain samples was determined by conversion from nitrogen content multiplied by the factor 6.25. According to Hanuš et al., (1995) the CP of the milk samples was determined by conversion from nitrogen content multiplied by the factor 6.38. Statistical methods All obtained data were analysed with Analysis of variance (ANOVA), Duncan test and Pearson correlation coeffi cient (r). The statistical evaluation was performed using UNISTAT v. 5.5 so ware (Unistat Ltd, London, UK, 2003). RESULTS AND DISCUSSION Crude protein (CP) The eff ect of maize replacing by wheat or by triticale caused the changes in milk CP content. The CP of feedstuff s (maize, wheat and triticale) was determined to be of 88.80, 145.80, and 110.50 g / 1000 g, respectively. The CP content in milk samples ob- The eff ect of selected cereals contained in feed ration on the amino acid composition of cows’ milk 371 tained a er feeding (maize, wheat, triticale) showed values of 30.8, 30.5, and 32.3 g / 1000 g, respectively. The high content of CP in wheat did not infl uence CP in milk contrary to situation observed for triticale. Here, higher content of CP in feed resulted in higher content of CP in corresponding milk. HerI: Components of feeding ration for three experimental groups (kg) and analysis of feeding ration Component of feeding ration 1 maize (control group) 2 wheat (tested group) 3 triticale (tested group) clover silage 21.3 21.3 21.3 maize silage 13.1 13.1 13.1 Hay 1.0 1.0 1.0 maize silage grain 3.0 3.0 3.0 squeezing corn 3.0 3.0 3.0 feeding mixture 5.8 5.8 5.8 maize 1.5 - - wheat - 2.0 - triticale - - 2.0 Analysis of feeding ration NEL /kg of dry matter 6.524 6.512 6.491 NL % in dry matter 17.9 18.2 17.9 Fibre % in dry matter 15.96 15.74 15.72 PDIN/PDIE 1.189 1.189 1.191 II: Amino acid composition and crude protein (CP) in the tested feedstuff s (maize, wheat, triticale) (g/1000 g); mean ± SE Amino acids Experimental group 1 (maize) 2 (wheat) 3 (triticale) Thr 2.48 ± 0.058a3.33 ± 0.032b2.70 ± 0.024c Val 4.04 ± 0.052a5.67 ± 0.094b4.44 ± 0.096c Ile 2.76 ± 0.042a4.44 ± 0.063b3.38 ± 0.037c Leu 9.19 ± 0.141a8.56 ± 0.067b6.25 ± 0.065c Phe 4.34 ± 0.073a6.14 ± 0.070b4.51 ± 0.059a His 2.96 ± 0.035a3.60 ± 0.029b2.91 ± 0.025a Lys 2.51 ± 0.038a3.42 ± 0.040b3.18 ± 0.047b Arg 4.25 ± 0.083a6.67 ± 0.075b5.34 ± 0.086c Met 3.31 ± 0.099a2.10 ± 0.019b3.02 ± 0.079a ∑EAA 35.83 ± 0.694a43.93 ± 0.677b35.71 ± 0.411a Asp 5.19 ± 0.079a6.01 ± 0.055b5.47 ± 0.066a Ser 3.31 ± 0.062a5.39 ± 0.058b3.96 ± 0.033c Glu 13.23 ± 0.225a35.23 ± 0.331b23.36 ± 0.172c Pro 6.91 ± 0.095a12.93 ± 0.140b8.96 ± 0.094c Gly 3.01 ± 0.040a4.94 ± 0.047b3.92 ± 0.043c Ala 5.62 ± 0.083a4.28 ± 0.039b3.63 ± 0.044c Tyr 2.94 ± 0.062a3.71 ± 0.066b2.84 ± 0.076a Cys 2.24 ± 0.007a3.18 ± 0.005b3.96 ± 0.055c ∑NEAA 42.45 ± 1.266a75.67 ± 3.837b56.10 ± 2.430c ∑AA 78.28 ± 0.696a119.60 ± 1.865b91.82 ± 1.185c CP 88.80 ± 2.21a145.80 ± 1.16b110.50 ± 2.21c ∑EAA … sum of essential and semi-essential amino acids ∑NEAA … sum of nonessential amino acids ∑AA … sum of all detected amino acids SE … standard error of the mean Means within a row (line) with the same superscript letter do not diff er signifi cantly (P ≥ 0.05) 372 M. Šípalová, O. Hanuš, F. Buňka, J. Pozdíšek, V. Mrkvička, S. Kráčmar rera-Saldava et al., (1990) and Owens et al., (1997) interpret this discrepancy by the diff erent digestive speed of grains. Small grains as maize, feterite, or millet are faster fermented in rumen. Wheat is considered as the one of the fastest degradable species between small grains. Amino acids One of the aims of this study was determination of amino acid content in milk obtained from cows fed diff erent diet (as can be seen in Table I). At fi rst, content of amino acids in hard fodder (maize, wheat and triticale) of the feeding ration was analysed. The results in Table II show that in comparison to maize, wheat contained signifi - cantly higher amount (P ≤ 0.05) of almost all detected amino acids with the exception of leucine, methionine and alanine (P ≤ 0.05). The comparison of amino acids amount detected in maize and triticale demonstrated lower content of leucine and alanine in triticale (P ≤ 0.05). Higher amount of methionine and cysteine (P ≤ 0.05) was measured in triticale compared to wheat, whereas lysine showed the same content in all the tested grains. In the second step, eff ects of maize replacing on amino acid content in milk were studied. In Table III content of amino acids in milk obtained from tested groups is presented. Amount of all detected amino acids in milk from group fed wheat is same or lower (P ≤ 0.05) in comparison to milk from group fed maize. On the other hand, all detected amino acids, which are contained in milk from group fed triticale are reaching, beside group fed maize, the same or higher amount (P ≤ 0.05) with exception of proline, the content of which was signifi cantly lower (P ≤ 0.05). The comparison of milk from group fed wheat and milk from group fed triticale showed that triticale’s milk contains higher amount of almost all detected amino acids (P ≤ 0.05) with exception of histidine, arginine and cysteine, which are detected with no statistically signifi cant diff erence in milk from all tested groups. Amino acids detected in grain and milk samples are shown in Table II and Table III, respectively. Values in Tables II and III were used for calculation of the amino acid amount in the CP. The conversion data (g/16gN) were used to Pearson’ s correlation and are summarized in Figure 1 and Figure 2 as content of nonessential and essential amino acids in feedstuff s and milk. III: Amino acids composition and crude protein (CP) of milk obtained from experimental groups (g/1000 g); mean ± SE Amino acid Milk obtained from experimental group 1 (maize) 2 (wheat) 3 (triticale) Thr 1.28 ± 0.014a1.19 ± 0.014b1.27 ± 0.016a Val 1.74 ± 0.017a1.63 ± 0.015b1.78 ± 0.018a Ile 1.39 ± 0.012a1.31 ± 0.010b1.45 ± 0.014c Leu 2.50 ± 0.022a2.37 ± 0.018b2.63 ± 0.025c Phe 1.27 ± 0.010a1.20 ± 0.009b1.34 ± 0.014c His 0.71 ± 0.007a0.70 ± 0.007a0.73 ± 0.008a Lys 2.12 ± 0.018a2.02 ± 0.016b2.23 ± 0.021c Arg 1.04 ± 0.010a1.03 ± 0.018a1.07 ± 0.015a Met 0.88 ± 0.011a0.82 ± 0.015b0.89 ± 0.009a ∑EAA 12.93 ± 0.195a12.27 ± 0.183b13.39 ± 0.208c Asp 2.11 ± 0.021a1.96 ± 0.019b2.14 ± 0.022a Ser 1.37 ± 0.015a1.31 ± 0.013b1.44 ± 0.018c Glu 6.18 ± 0.067a5.87 ± 0.071b6.28 ± 0.081c Pro 3.09 ± 0.037a2.63 ± 0.029b2.82 ± 0.034c Gly 0.51 ± 0.005a0.48 ± 0.004b0.53 ± 0.006a Ala 0.81 ± 0.008a0.82 ± 0.008a0.87 ± 0.006b Tyr 1.22 ± 0.010a, b 1.17 ± 0.010a1.27 ± 0.013b Cys 0.31 ± 0.005a0.30 ± 0.005a0.33 ± 0.004a ∑NEAA 15.60 ± 0.683a14.54 ± 0.639b15.68 ± 0.682a ∑AA 28.53 ± 0.332a26.81 ± 0.310b29.07 ± 0.333a CP 30.8 ± 0.67a30.5 ± 0.55a32.3 ± 0.72b ∑EAA … sum of essential and semi-essential amino acids ∑NEAA … sum of nonessential amino acids ∑AA … sum of all detected amino acids SE … standard error of the mean Means within a row (line) with the same superscript letter do not diff er signifi cantly (P ≥ 0.05) The eff ect of selected cereals contained in feed ration on the amino acid composition of cows’ milk 373 Pearson’s correlation The fi rst Pearson’s correlation analysis pointed to the question, whether the relative content (g/16gN) of amino acids in milk will rise (fall) with the rising of amino acid content in maize (shows in Table IV, column 1). For detected amino acids with the exception of isoleucine, proline and tyrosine (P ≤ 0.05), no statistically signifi cant correlation was found (as can be seen in Table IV, the fi rst column). The positive correlation observed for proline and isoleucine expresses that their amount in milk will increase with the high probability (r = 0.8202 and r = 0.7794) when their amount will rise in maize. On the contrary, the negative correlation for tyrosine (r = – 0.7587) shows the high probability of its decreasing amount in milk, while its amount in maize is growing. The Pearson’s correlation analysis presented column two of Table IV pointed to the question, whether the relative content (g/16gN) of amino acids in milk will grow (decline) with the growing relative content of amino acid in wheat. As can be seen in Table IV, serine and histidine showed the statistically signifi cant positive correlation. Conseguently, the high possibility of increasing histidine content in milk with increasing content of this amino acid in wheat exists (r = 0.8514, P ≤ 0.05). Correspondingly, the statistically signifi cant (P ≤ 0.01) positive correlation for serine showed its high possible increase in milk when it will increase in wheat. However, the statistically signifi cant (P ≤ 0.05) negative high correlation was determined for proline (r = – 0.7507). The last performed Pearson’s correlation analy sis (Table IV, column 3) pointed to the question, whether the relative content (g/16gN) of amino acids in milk will increase (decrease) with the increasing relative content of amino acid in triticale. The statistically signifi cant positive correlation was found for tyrosine and phenylalanine. Thereby, the high 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 16.00 18.00 20.00 22.00 Glu Pro A s p Se r Ty r A la Gly Cy s nonessential amino acids g/16 g N Maize Wheat Triticale Maize Wheat Triticale Feedstuff Milk 1: Content of nonessential amino acids in feedstuffs and in milk 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 Leu Lys Val Ile Thr Phe Arg Met His essential amino acids g/16 g N Maize Wheat Triticale Maize Wheat Triticale Feddstuff Milk 2: Content of essential amino acids in feedstuffs and in milk 374 M. Šípalová, O. Hanuš, F. Buňka, J. Pozdíšek, V. Mrkvička, S. Kráčmar possibility of tyrosine’s and phenylalanine’s increasing in milk with their growth in triticale exists (r = 0.8910, P ≤ 0.01; r = 0.7332, P ≤ 0.05, resp.). On the other hand, the statistically signifi cant (P ≤ 0.05) negative high correlation was detected for arginine (r = – 0.8173). IV: Statistically signifi cant Pearson’s correlation coeffi cients (r) obtained from the correlation between amino acids content determined in feedstuff (maize, wheat, triticale) and corresponding milk samples Amino acid maize vs. milk wheat vs. milk triticale vs. maize His 0.3501 0.8514* 0.2538 Phe 0.6627 0.2243 0.7332* Ile 0.7794* 0.2789 0.5123 Arg 0.2471 -0.3873 −0.8173* Ser −0.6888 0.9417** 0.3610 Pro 0.8202* -0.7507* 0.4805 Tyr −0.7587* -0.2135 0.8910* * … P < 0.05 ** … P < 0.01 CONCLUSION Amino acids determined in feedstuff used for feeding of tested cows were subsequently presented in milk obtained from all the three tested groups. On the other hand, the expected abundance of wheat CP was not confi rmed in corresponding milk samples. With a view to amino acid content in milk samples, none of the tested grains can be recommended as a full-value maize replacement. Wheat is, according to Pearson’s correlation coeffi cient, abundant source of histidine and serine in milk, however it cannot serve as a source of proline. According Pearson’s correlation coeffi cient, triticale is reliable source of phenylalanine and tyrosine in milk, nevertheless it is unsuitable as a source of arginine. The supply of amino acids for absorption in the small intestine of ruminants is a mixture of undegraded dietary protein and microbial protein produced in rumen. With the view to amino acid composition in milk, it will be the best choice to make the mixture of all tested feedstuff s. Each feedstuff (maize, wheat, triticale) is an abundant and unique source of typical amino acids in milk. According to (Boisen et al., 2000) it is infl uenced not only by dietary proteins but also by variations in the microbial population in rumen. As a summary it is possible to conclude that triticale (cultivar Kitaro) seems to be more suitable replacement of maize because of its better CP effi ciency and total milk quality. SOUHRN Účinek vybraných obilnin obsažených v krmné dávce na obsah aminokyselin v mléce Cílem této práce bylo zhodnocení možného účinku náhrady kukuřice v krmné dávce na obsah aminokyselin v kravském mléce. Dojnice byly krmeny směsnou krmnou dávkou složenou z kukuřice, jetelové siláže a sena. Rozdílnost v krmné dávce byla v jadrném krmivu. První skupina (krmena kukuřicí) byla skupinou kontrolní, ostatní dvě skupiny byly experimentální, jedna byla krmena pšenicí a druhá obilninou tritikale. V průběhu šesti týdnů bylo odebráno celkem 26 vzorků mléka od dojnic plemene České strakaté. Krmné skupiny byly vyváženy v dojivosti, laktačních dnech a v pořadí laktace. Vzorky krmiv a stejně tak i mléka byly upraveny pro analýzu pomocí kyselé a oxidativně-kyselé hydrolýzy. Analýza aminokyselin v hydrolysátech byla provedena pomocí kapalinové chromatografi e (AAA 400 analyzátor) za použití sodno-citrátových pufrů a ninhydrinové detekce. Celkové množství dusíku bylo stanoveno dle Kjehldahla a hrubý protein daných vzorků byl stanoven pomocí vynásobení hodnoty celkového dusíku vhodným faktorem 6,38. Vysoká hodnota hrubého proteinu v pšenici neovlivnila složení mléka získaného od experimentální skupiny krmené touto obilninou. Z pohledu obsahu aminokyselin ve vzorcích mléka nemůže být žádná z testovaných obilnin doporučena jako plnohodnotná náhrada kukuřice. Každé krmivo je bohatým zdrojem mnohých a typických aminokyselin v mléce. Avšak tritikale (kultivar Kitaro) se může zdát jako vhodnou náhradou kukuřice vzhledem k lepší využitelnosti hrubého proteinu, celkovému složení mléka a zdravotním ukazatelům mléčné kvality. dojnice, kukuřice, pšenice, tritikale, aminokyseliny The eff ect of selected cereals contained in feed ration on the amino acid composition of cows’ milk 375 Acknowledge This study was supported by the Ministry of Agriculture of the Czech Republic (Grant No. QF 3133) and by the Ministry of Education Youth and Sports of the Czech Republic (Grant No. MSM 7088352101 and Grant No. MSM 2678846201). REFERENCES ADIN, G., SOLOMON, R., SHOSHANI, E., FLAMENBAUM, I., NIKBACHAT, M., YOSEF, E., ZENOU, A., HALACHMI, I., SHAMAY, A., BROSH, A., MABJEESH, S. J., MIRON, J., 2008: Heat production, eating behaviour and milk yield of lactating cows fed two rations diff ering in roughage content and digestibility under heat load conditions. Livestock Science, 119, 145–153. ISSN 1871-1413. BOISEN, S., HVELPLUND, T., WEISBJERG, M. R., 2000: Ideal amino acid profi les as a basis for feed protein evaluation. Livestock Production Science, 64, 239–251. ISSN 0301-6226. BUŇKA, F., KŘÍŽ, O., VELIČKOVÁ, A., BUŇKOVÁ, L., KRÁČMAR, S., 2009: Eff ect of acid hydrolysis time on amino acid determination in casein and processed cheeses with diff erent fat content. Journal of Food Composition and Analysis, 22, 224–232. ISSN 1096-0481. COHEN, D. C., STOCKDALE, C. R., DOYLE, P. T., 2006: Feeding an energy supplement with white clover silage improves rumen fermentation, metabolisable protein utilisation, and milk production in dairy cows. Australian Journal of Agricultural Research, 57, 367–375. ISSN 0004-9409. Commission Regulation (EC) No 152/2009 of 27 January 2009 laying down the methods of sampling and analysis for the offi cial control of feed. Offi cial Journal. L 54, 1–130. DEPETERS, E. J. and CANT, J. P., 1992: Nutritional factors infl uencing the nitrogen composition of bovine milk: a review. Journal of Dairy Science, 75, 2043–2070. ISSN 1525-3198. DHIMAN, T. R., MACQUEEN, I. S., LUCHINI, N. D., 2001: Milk yield response of dairy cows fed fat along protein. Animal Feed Science and Technology, 90, 169–184. ISSN 0377-8401. HANUŠ, O., FICNAR, J., JEDELSKÁ, R., KOPECKÝ, J., BERANOVÁ, A., GABRIEL, B., 1995: Methodical problems of nitrogen matters determination in cow’s milk. Veterinary medicine – Czech, 40, 387–396. ISSN 0375-8427. HERRERA-SALDANA, R. E., HUBER, J. T., POORE, M. H., 1990: Dry matter, crude protein, and starch degradibility of fi ve cereal grains. Journal of Dairy Science, 47, 2386–2393. ISSN 1525-3198. KRÁČMAR, S., GAJDŮŠEK, S., JELÍNEK, P., ZEMAN, L., KOZEL, V., KOZLOVÁ, M., KRÁČMAROVÁ, E., 1998: Changes in amino acid composition of goat’s colostrum during the fi rst 72 hours a er birth. Czech Journal of Animal Science. 44, 541– 545. ISSN 1212-1819. KRÁČMAR, S., LIŠKA, I., MINAŘÍK, B., ZBÍRAL, J., 2000: Amino acid determination in standard solution and feed mixture: an intralaboratory study. Acta Universitatis Agriculturae et Silviculturae Men de lianae Brunensis, 48, 69–79. ISSN 1211-8516. KUHN, M. T., HUTCHINSON, J. L., NORMAN, H. D., 2006: Eff ects of lenght of dry period on yields of milk fat and protein, fertility and milk somatic cell score in the subsequent lactation of dairy cows. Journal of Dairy Research, 73, 154–162. ISSN 14697629. LEIBER, F., NIGG, D., KUNZ, C., SCHEEDER, M. R. L., WETTSTEIN, H. R., KREUZER, M., 2005: Protein composition, plasmin acitivity and cheesemaking properties of cows´milk produced at two altitudes from hay of lowland and high-alpine origins. Journal of Dairy Research, 72, 65–74. ISSN 14697629. MASOERO, F., MOSCHINI, M., ROSSI, F., PIVA, G., 1998: Eff ect of bovine somatotropin on milk production, milk quality and the cheese-making properties of Grana Padano cheese. Livestock Production Science, 54, 107–114. ISSN 0301-6226. OWENS, F. N., SECRIST, D. S., HILL, W. J., GILL, D. R., 1997: The eff ect of braun source and braun processing on performance of feedlot cattle: A review. Journal of Animal Science, 75, 868–879. ISSN 1525-3163. PALMQUIST, D. L., WEISBJERG, M. R., HVELPLUND, T., 1993: Ruminal, intestinal, and total digestabilities of nutrients in cows fed diets high in fat and undegradable protein. Journal of Dairy Science, 76, 1353–1364. ISSN 1525-3198. POZDÍŠEK, J. and VACULOVÁ, K., 2008: Study of wheat (Triticum aestivum L.) quality for feeding ruminants using in vitro and in vivo methods. Czech Journal of Animal Science, 53, 253–264. ISSN 12121819. POZDÍŠEK, J., HANUŠ, O., VACULOVÁ, K., MIKYSKA, F., KOPECKÝ, J., JEDELSKÁ, R., 2008: Some compositional and health indicators of milk quality of dairy cows with higher milk yield at including of selected corn species into feeding ration. Acta Universitatis Agriculturae et Silviculturae Mendeleianae Brunensis, LVI, 171–180. ISSN 12118516. SÁNCHEZ, N. R. and LEDIN, I., 2006: Eff ect of fedding diff erent levels of foliage from Cratylia argentea to creole dairy cows on intake, digestibility, milk production and milk composition. Tropical Animal Health and Production, 38, 343–351. ISSN 1573-7438. SEHESTED, J., KRISTENSEN, T., SOEGAARD, K., 2003: Eff ect of concentrate supplementation level on production, health and effi ciency in an organic dairy herd. Livestock Production Science, 80, 153–165. ISSN 0301-6226. 376 M. Šípalová, O. Hanuš, F. Buňka, J. Pozdíšek, V. Mrkvička, S. Kráčmar SINCLAIR, L. A., WILKINSON, R. G., FERGUSON, D. M. R., 2003: Eff ects of crop maturity and cutting height on the nutritive value of fermented whole crop wheat and milk production in dairy cows. Livestock Production Science, 81, 257–269. ISSN 03016226. STEINSHAMN, H. and THUEN, E., 2008. WHITE OR RED CLOVER-GRASS SILAGE IN ORGANIC DAIRY MILK PRODUCTION: Grassland productivity and milk production responses with diff erent levels of concentrate. Livestock Science, 119, 202–215. ISSN 1871-1413. STRUSIŃSKA, D., MINAKOWSKI, D., PYSERA, B., KALINIEWICZ, J., 2006: Eff ects of fat-protein supplementation of diets for cows in early lactation on milk yield and composition. Czech Journal of Animal Science, 51, 196–204. ISSN 1212-1819. WU, Z. and HUBER, J. T., 1994: Relatioship between dietary fat supplementation and milk protein concentration in lactating cows: a review. Livestock Production Science, 39, 141–155. ISSN 0301-6226. Address Ing. Markéta Šípalová, prof. Ing. Stanislav Kráčmar, DrSc., doc. Ing. František Buňka, Ph.D., doc. Dr. Ing. Oto Hanuš, Ing. Jan Pozdíšek, CSc., Ing. Vladimír Mrkvička, Ph.D., Ústav biochemie a analýzy potravin, Fakulta technologická, Univerzita Tomáše Bati ve Zlíně, nám. T. G. Masaryka 275, 762 72 Zlín, Česká republika, e-mail: sipalova@ .utb.cz, kracmar@ .utb.cz