The effect of paternal bull on milk fat composition of dairy cows of different breeds

Intake of milk fat in human nutrition is important because of unsaturated and especially essential fatty acids (FAs), linoleic and α-linolenic acid, and conjugated linoleic acid (CLA), which is found only in meat and milk of ruminants. The objective of our study was to investigate the effect of paternal bulls on fatty acids composition in milk fat of dairy cows of different breeds. The milk samples were taken in total from 299 dairy cows from 11 dairy farms. In experiment Holstein (H, n = 105), Red Holstein (R, n = 120) and Pinzgau (P, n = 74) breeds originated from different bulls were used. Individual milk samples were analyzed for fatty acids in milk fat using gas chromatography (apparatus GC Varian 3800, Techtron, USA), using FID detector in capillary column Omegawax 530; 30 m. In the chromatography records there were identified 54 fatty acids inclusive of particular isomers. Their relative proportions were expressed in percent's (%). Among the studied breeds, the highest content of conjugated linoleic acid (CLA) - 0.67%, essential FAs (EFA) - 2.98%, monounsaturated FAs (MUFA) - 25.84% and the lowest atherogenic index (AI) - 3.10 was at breed P. Within this breed there was high variability and daughters of bull COS1 achieved significant above-average values of CLA content 1.07%, EFA 3.71%, MUFA 29.93% and under breed average AI = 2.40. The group of daughters of NOB3 was significant lower in CLA, 0.50% as compared with an average of P breed. . From the breed H bull MTY2 showed significantly higher value of 0.62% CLA, EFA 3.42%, 34.29% MUFA and lower value of AI, 1.9 as compared to H breed average. Statistically significantly lower levels of CLA 0.29% and 21.46% MUFA and higher AI 3.72 in milk fat of his daughters, bull STY3 may be considered as potential worser of these properties. At the breed R bull MOR506 showed in compar to the breed average significantly higher value of the EFA 3.80% and also the higher content of CLA 0.50% and MUFA 25.09%, resulting in statistically significant lower AI = 2.91. Bull MOR506 could be considered as potential improver of milk fat composition. The above described variability in the composition of milk fat of dairy cows and the subsequent relationships between these values suggest that the selection of the bull according to the fatty acid composition of milk fat may be considered

Pojavnost uzročnika mastitisa u razdoblju suhostaja i nakon teljenja

The aim of the work was to study the occurrence of mastitis pathogens before and after calving in the same dairy cows. The Holstein cows suspicious on subclinical mastitis (positive California Mastitis Test) were sampled at quarter level under practical farm with high level of milk yield (11,278 kg). The cows were treated with antibiotics (Cefquinomum) before drying. In total 84 samples before drying and 107 samples after calving from the same dairy cows were collected. The samples were cultured on blood agar (MkB Test as, Rosina, SR). MALDI-TOF MS (Bruker Daltonics, Germany) was used to identify mastitis pathogens. Bacteriologically positive (BP) samples from dairy cows before drying were found in 35% of the milk samples. The most frequent pathogens in BP milk samples were coagulase-negative staphylococci (CNS) (77.38%). The most common CNS was Staphylococcus (S.) xylosus (32.14%). S. aureus was detected in 5.95% of BP samples. After calving, we found BP samples in 14.02% of dairy cows. The most common pathogens in milk samples were CNS (10.39%). S. aureus was detected in 0.94% of BP samples. Antibiotic treatment during the drying period clearly reduced the occurrence of CNS and S. aureus in dairy cows at the beginning of lactation.Cilj rada bio je utvrditi pojavu uzročnika mastitisa u vrijeme suhostaja i nakon teljenja. Krave Holštajn pasmine visoke razine proizvodnje mlijeka (11.278 kg) sa sumnjom na prisutnost uzročnika mastitisa (pozitivni Kalifornija mastitis test) u barem jednoj četvrti uključene su u istraživanje. Krave su prije zasušenja tretirane antibiotikom (Cefquinomum). Ukupno je prikupljeno 84 uzoraka mlijeka krava prije zasušenja i 107 uzoraka krava nakon teljenja. Uzorci su kultivirani na krvnom agaru (MkB Test kao Rosina, SR). MALDI-TOF MS (Bruker Daltonics, Germany) je korišten za identifikaciju uzročnika mastitisa. Bakteriološki pozitivni uzorci utvrđeni su kod 35 krava prije zasušenja. Najčešći uzročnik mastitisa utvrđen u bakteriološki pozitivnim uzorcima mlijeka krava prije zasušenja je bio koagulaza negativnio stafilokok (CNS) (77,38 %). Najčešće utvrđeni CNS je bio Staphylococcus (S,) xylosus (32,14 %) dok je Staphylococcus aureus izoliran iz 5,95 bakteriološki pozitivnih uzoraka. Nakon teljenja, utvrđeno je 14,02 % bakteriološki pozitivnih uzoraka mlijeka krava. Najčešći patogeni u uzorcima mlijeka bili su CNS (10,39 %). S. aureus je otkriven u 0,94 % bakterioloških uzoraka. Liječenje antibioticima tijekom razdoblja zasušenja jasno je smanjilo pojavu CNS -a i S. aureus kod mliječnih krava na početku laktacije

Pojavnost uzročnika mastitisa u razdoblju suhostaja i nakon teljenja

The aim of the work was to study the occurrence of mastitis pathogens before and after calving in the same dairy cows. The Holstein cows suspicious on subclinical mastitis (positive California Mastitis Test) were sampled at quarter level under practical farm with high level of milk yield (11,278 kg). The cows were treated with antibiotics (Cefquinomum) before drying. In total 84 samples before drying and 107 samples after calving from the same dairy cows were collected. The samples were cultured on blood agar (MkB Test as, Rosina, SR). MALDI-TOF MS (Bruker Daltonics, Germany) was used to identify mastitis pathogens. Bacteriologically positive (BP) samples from dairy cows before drying were found in 35% of the milk samples. The most frequent pathogens in BP milk samples were coagulase-negative staphylococci (CNS) (77.38%). The most common CNS was Staphylococcus (S.) xylosus (32.14%). S. aureus was detected in 5.95% of BP samples. After calving, we found BP samples in 14.02% of dairy cows. The most common pathogens in milk samples were CNS (10.39%). S. aureus was detected in 0.94% of BP samples. Antibiotic treatment during the drying period clearly reduced the occurrence of CNS and S. aureus in dairy cows at the beginning of lactation.Cilj rada bio je utvrditi pojavu uzročnika mastitisa u vrijeme suhostaja i nakon teljenja. Krave Holštajn pasmine visoke razine proizvodnje mlijeka (11.278 kg) sa sumnjom na prisutnost uzročnika mastitisa (pozitivni Kalifornija mastitis test) u barem jednoj četvrti uključene su u istraživanje. Krave su prije zasušenja tretirane antibiotikom (Cefquinomum). Ukupno je prikupljeno 84 uzoraka mlijeka krava prije zasušenja i 107 uzoraka krava nakon teljenja. Uzorci su kultivirani na krvnom agaru (MkB Test kao Rosina, SR). MALDI-TOF MS (Bruker Daltonics, Germany) je korišten za identifikaciju uzročnika mastitisa. Bakteriološki pozitivni uzorci utvrđeni su kod 35 krava prije zasušenja. Najčešći uzročnik mastitisa utvrđen u bakteriološki pozitivnim uzorcima mlijeka krava prije zasušenja je bio koagulaza negativnio stafilokok (CNS) (77,38 %). Najčešće utvrđeni CNS je bio Staphylococcus (S,) xylosus (32,14 %) dok je Staphylococcus aureus izoliran iz 5,95 bakteriološki pozitivnih uzoraka. Nakon teljenja, utvrđeno je 14,02 % bakteriološki pozitivnih uzoraka mlijeka krava. Najčešći patogeni u uzorcima mlijeka bili su CNS (10,39 %). S. aureus je otkriven u 0,94 % bakterioloških uzoraka. Liječenje antibioticima tijekom razdoblja zasušenja jasno je smanjilo pojavu CNS -a i S. aureus kod mliječnih krava na početku laktacije

The impact of calving season, dams’ parity on milk yield and gestation length of dairy cows

Article Details: Received: 2020-10-06 | Accepted: 2020-11-27 | Available online: 2021-01-31https://doi.org/10.15414/afz.2021.24.mi-prap.41-44The purpose of the study was to asses the effect of calving season and dams’ parity on milk yield and gestation length of dairy cows. We examined 93 animals of Slovak spotted breed from the farm located in western Slovakia (Lower Váh region), in years 2014-2017. The herds’ average 305-d milk yield was 8133±1380 kg. The calving season was divided into four categories: spring (March to May), summer (June to August), autumn (September to November) and winter (December to February). The factor of dams parity was divided into 4 groups: 1st parity cows, 2nd-3rd parity cows, 4th and higher parity cows. Calving season affected significantly milk yield of dairy cows (P 0.32). Dams’ parity was not significantly affected by 305-d milk yield (P > 0.22). Nevertheless, the animals on the 4th and higher lactation were numerically more productive (8481±259 kg) compared to the dairy cows on their 1st,2nd-3rd lactation (8123±264 kg; 7884±223 kg; resp.). The dams’ parity significantly affected gestation length (P < 0.02), with the shortest gestation length in 1st parity dams (278±2 days) and the longest gestation in 2nd-3rd parity dams (284±1 days).To sum up, our results suggest significant role of calving season in relation to milk yield and significant effect of dams’ parity on gestation length.Keywords:milk yield, gestation, calving season, parity, dairy cows ReferencesBARASH, H., SILANIKOVE, N. and WELLER, J. (1996). Effect of Season of Birth on Milk, Fat, and Protein Production of Israeli Holsteins. Journal of Dairy Science, 79(6), 1016–1020.DOI: https://doi.org/10.3168/jds.S0022-0302(96)76453-6Ceyhan, A., Cinar, M. and Serbester, U. (2015). Milk yield, somatic cell count, and udder measurements in holstein cows at different lactation number and months. Media Peternakan, 38(2), 118–122. DOI: https://doi.org/10.5398/medpet.2015.38.2.118DAHL, G. E. and PETITCLERC, D. (2003). Management of photoperiod in the dairy herd for improved production and health. Journal of Animal Science, 81(3), 11-17. DOI: https://doi.org/10.2527/2003.81suppl_311xDAHL, G. E., TAO, S. and MONTEIRO, A. P. A. (2016). Effects of late-gestation heat stress on immunity and performance of calves. Journal of Dairy Science, 99(4), 3193–3198. DOI: https://doi.org/10.3168/jds.2015-9990FROIDMONT, E. et al. (2013). Association between age at first calving, year and season of first calving and milk production in Holstein cows. Animal, 7(4), 665–672. DOI: https://doi.org/10.1017/S1751731112001577MACIUC, V. 2009. Influence of the calving season on the milk yield given by a friesian population, imported from the Netherlands. Lucrări Ştiinţifice - Seria Zootehnie, 52(1), 340–344.Mellado, M. et al. (2011). Effect of lactation number, year, and season of initiation of lactation on milk yield of cows hormonally induced into lactation and treated with recombinant bovine somatotropin. Journal of Dairy Science, 94(9), 4524–4530. DOI: https://doi.org/10.3168/jds.2011-4152Mikláš, Š. et al. (2019a). Association of chosen environmental and animal factorswith gestation length and lactation of dairy cows in two Slovak herds. In Cerkal R. et al. (eds.) MendelNet 2019. Brno : Mendel University in Brno (pp. 153–157). ISBN 978-80-7509-688-3.Mikláš, Š. et al. (2019b). Effect of calving season and temperature at calving on the gestation length. In Tóthová, M. et al. (eds.) Scientific conference of PhD. students of FAFR and FBFS with international participation. Nitra: Slovak University of Agriculture (p. 20). ISBN 978-80-552-2083-3.Mikláš, Š. et al. (2020). The effect of dams‘ parity on milk yield, birth and weaning weight of their daughters. In Chrenek P. (ed.) Animal biotechnology 2020. Nitra: Slovak Agricultural University (p. 54). ISBN 978-80-552-2145-8NORMAN, H. D. et al. (2009). Genetic and environmental factors that affect gestation length 72 in dairy cattle. Journal of Dairy Science, 92(2), 2259-2269. DOI: https://doi.org/10.3168/jds.2007-0982RAY, D. E., HALBACH, T. J. and ARMSTRONG, D. V. (1992). Season and Lactation Number Effects on Milk Production and Reproduction of Dairy Cattle In Arizona. Journal of Dairy Science, 75(11), 2976-2983.RIUS, A. G. and DAHL, G. E. (2006). Exposure to long-day photoperiod prepubertally may increase milk yield in first-lactation cows. Journal of Dairy Science, 89(6), 2080-2083. DOI: https://doi.org/10.3168/jds.S0022-0302(06)72277-9Storli, K. S., Heringstad B. and Salte R. (2014). Effect of dams' parity and age on daughters' milk yield in Norwegian Red cows. Journal of Dairy Science, 97(10), 6242-6249. DOI: https://doi.org/10.3168/jds.2014-8072Tančin, V., Mikláš, Š. and Mačuhová, L. (2018). Possible physiological and environmental factors affecting milk production and udder health of dairy cows: a review. Slovak journal of animal science. 51(1), 32-40.Tao, S. et al. (2019). PHYSIOLOGY SYMPOSIUM: Effects of heat stress during late gestation on the dam and its calf. Journal of Animal Science, 97(5), 2245–2257. DOI: https://doi.org/10.1093/jas/skz061TOMASEK, R., REZAC, P. and HAVLICEK, Z. (2017). Environmental and animal factors associated with gestation length in Holstein cows and heifers in two herds in the Czech Republic. Theriogenology, 87(1), 100-107. DOI: https://doi.org/10.1016/j.theriogenology.2016.08.009WRIGHT, E.C. et al. (2014). Effect of elevated ambient temperature at parturition on duration of gestation, ruminal temperature, and endocrine function of fall-calving beef cows. Journal of Animal Science, 92(10), 4449-4456. DOI: https://doi.org/10.2527/jas.2014-805

Effect of season and temperature before and after calving on the future milk production of born heifers

Article Details: Received: 2020-06-30 | Accepted: 2020-10-15 | Available online: 2020-12-31https://doi.org/10.15414/afz.2020.23.04.224-229The aim of the study was to evaluate the effect of birth season, average maximum temperatures 6 weeks before and after birth of heifers on their first lactation milk yield. In chosen herd, the effect of birth weight, weight gain until weaning on first lactation milk yield was also investigated. Additionally, the effect of the average maximum temperatures before birth, effect of birth season on birth weight were evaluated. The data were collected from the herd “A” in Orava region consisting of Slovak spotted breed (127 records), the herd “B” in Lower Nitra (150 records) and herd “C” in Upper Nitra (116 records) both consisting of black Holstein Friesian cows. Birth season tended to influence the heifers first lactation milk yield in the herd “C” (P 0.66, herd “A”; P >0.59, herd “B”; P >0.38, herd “C”). In the herd “B” there was insignificant effect of prenatal temperatures, birth season on birth weight of heifers (P >0.97; P >0.74). However, the heifers with the highest weight gains until weaning had numerically higher first lactation milk yield (P >0.20).Keywords: dairy calves, temperature, season, milk yield, gestation lengthReferencesCALLINAN P.A. and FEINBERG A. P. (2006). The emerging science of epigenomics. Human Molecular Genetics, 15(1), R95-R101. https://doi.org/10.1093/hmg/ddl095COLLIER, R. J. et al. (2006). Use of gene expression microarrays for evaluating environmental stress tolerance at the cellular level in cattle. Journal of Animal Science, 84(13), 1–13. https://doi.org/10.2527/2006.8413_supplE1xDAHL, G. E., TAO, S. and MONTEIRO, A. P. A. (2016). Effects of late-gestation heat stress on immunity and performance of calves. Journal of Dairy Science, 99(4), 3193–3198. DOI: https://doi.org/10.3168/jds.2015-9990DAHL, G. E., TAO, S. and THOMPSON, I. M. (2012). LACTATION BIOLOGY SYMPOSIUM: Effects of photoperiod on mammary gland development and lactation. Journal of Animal Science, 90(3), 755–760. https://doi.org/10.2527/jas.2011-4630HEINRICHS, A. J. and HEINRICHS, B. S. (2011). A prospective study of calf factors affecting first-lactation and lifetime milk production and age of cows when removed from the herd. Journal of Dairy Science, 94(1), 336–341. https://doi.org/10.3168/jds.2010-3170KASARDA, R. et al. (2018). Estimation of heritability for claw traits in Holstein cattle using Bayesian and REML approaches. Journal of Central European Agriculture, 19(4), 784–790. https://doi.org/10.5513/JCEA01/19.4.2338LAPORTA, J. et al. (2017). In utero exposure to heat stress during late gestation has prolonged effects on the activity patterns and growth of dairy calves. Journal of Dairy Science, 100(4), 1–9. https://doi.org/10.3168/jds.2016-11993MIGLIOR, F. et al. (2017). Identification and genetic selection of economically important traits in dairy cattle. Journal of Dairy Science, 100(12), 10251–10271. DOI: https://doi.org/10.3168/jds.2017-12968MOALLEM, U. et al. (2010). Long-term effects of ad libitum whole milk prior to weaning and prepubertal protein supplementation on skeletal growth rate and first-lactation milk production. Journal of Dairy Science, 93(6), 2639–2650. DOI: https://doi.org/10.3168/jds.2009-3007MONTEIRO, A. P. A. et al. (2013). Effect of heat stress in utero on calf performance and health through the first lactation. Journal of Animal Science, 91, 184. https://doi.org/10.3168/jds.2015-9990MONTEIRO, A. P. A. et al. (2014). Effect of heat stress during late gestation on immune function and growth performance of calves: Isolation of altered colostral and calf factors. Journal of Dairy Science, 97(10), 6426–6439. https://doi.org/10.3168/jds.2013-7891MONTEIRO, A. P. A. et al. (2016a). Effect of maternal heat stress during the dry period on growth and metabolism of calves. Journal of Dairy Science, 99(5), 3896–3907. https://doi.org/10.3168/jds.2015-10699MONTEIRO, A. P. A. et al. (2016b). In utero heat stress decreases calf survival and performance through the first lactation. Journal of Dairy Science, 99(10), 8443–8450. https://doi.org/10.3168/jds.2016-11072OSBORNE, V. R. et al. (2007). Effects of photoperiod and glucose-supplemented drinking water on the performance of  dairy calves. Journal of Dairy Science, 90(11), 5199–5207. https://doi.org/10.3168/jds.2007-0402RIUS, G. and DAHL, G. E. (2006). Exposure to Long-Day Photoperiod Prepubertally May Increase Milk Yield in FirstLactation Cows. Journal of Dairy Science, 89(6), 2080–2083. https://doi.org/10.3168/jds.S0022-0302(06)72277-9SCHAEFFER, L. R. (2006). Strategy for applying genome-wide selection in dairy cattle. Journal of Animal Breeding and Genetics, 123, 218–223. https://doi.org/10.1111/j.1439-0388.2006.00595.xSOBERON, F. et al. (2012). Preweaning milk replacer intake and effects on long-term productivity of dairy calves. Journal of Dairy Science, 95(2), 783–793. https://doi.org/10.3168/jds.2011-4391SOBERON, F. and VAN AMBURGH, M. E. (2013). Lactation Biology Symposium: The effect of nutrient intake from milk or milk replacer of preweaned dairy calves on lactation milk yield as adults: A meta-analysis of current data. Journal of Animal Science, 91(2), 706–712. https://doi.org/10.2527/jas.2012-5834STRAPÁK, P., JUHÁS, P. and BUJKO, J. (2013). The influence of health status in calves with subsequent growth of heifers and milk production in dairy cows. Journal of Central European Agriculture, 14(3), 347–356. https://doi.org/10.5513/JCEA01/14.3.1326TANČIN, V. et al. (1994). Different nutrition of calves in relation to the levels of thyroid-hormones and some biochemical indexes. Živočíšna výroba, 39(11), 961–971.TANČIN, V., MIKLÁŠ, Š. and MAČUHOVÁ, L. (2018). Possible physiological and environmental factors affecting milk production and udder health of dairy cows: A  review. Slovak Journal of Animal Science, 51(1), pp. 32–40.TAO, S. et al. (2012). Effect of late gestation maternal heat stress on growth and immune function of dairy calves. Journal of Dairy Science, 95(12), 7128–7136. https://doi.org/10.3168/jds.2012-5697TAO, S. et al. (2018). Symposium review: The influences of heat stress on bovine mammary gland function. Journal of Dairy Science, 101(6), 5642–5654. https://doi.org/10.3168/jds.2017-13727TAO, S. et al. (2019). Effects of heat stress during late gestation on the dam and its calf. Journal of Animal Science, 97(5), 2245–2257. https://doi.org/10.1093/jas/skz061UHRINČAŤ, M. et al. (2007). The effect of growth intensity of heifers till 15 months of age on their milk production during first lactation. Slovak Journal of Animal Science, 40(2), 83–88.VACULIKOVA, M. and CHLADEK, G. (2015). Air temperature impacts on the behaviour of holstein calves in individual outdoor calf hutches according to age of observed calves. In O.  Polák, R. Cerkal and N. Březinová-Belcredi (Eds.), The Conference MendelNet 2015 (pp. 169–173). Brno: Mendel University in Brno.VAN EETVELDE, M. et al. (2017). Season of birth is associated with first-lactation milk yield in Holstein Friesian cattle. Animal, 11(12), 2252–2259. https://doi.org/10.1017/S1751731117001021VAN EETVELDE, M. and OPSOMER, G. (2017). Innovative look at dairy heifer rearing: Effect of prenatal and postnatal environment on later performance. Reproduction in Domestic Animals, 52(3), 30–36. https://doi.org/10.1111/rda.13019WIGGANS, G. R. et al. (2017). Genomic Selection in Dairy Cattle: The USDA Experience. Annual Review of Animal Biosciences, 5, 309–327. https://doi.org/10.1146/annurev-animal-021815-111422WU, G. F. et al. (2006). Board-Invited Review: Intrauterine growth retardation: Implications for the animal sciences. Journal of Animal Science, 84(9), 2316–2337. https://doi.org/10.2527/jas.2006-156YATES, D., GREEN, A. and LIMESAND, S. (2011). Catecholamines mediate multiple fetal adaptations during placental insufficiency that contribute to intrauterine growth restriction: Lessons from hyperthermic sheep. Journal of Pregnancy, Article ID 740408, pp. 1–9. https://doi. org/10.1155/2011/74040

Broj somatskih stanica u sirovom ovčjem mlijeku u mljekarskoj praksi: učestalost distribucije i mogući učinak na količinu i sastav mlijeka

The aim of the work was to analyse the somatic cell counts (SCC) of the individual sheep milk samples under practical conditions. Totally 2159 samples were collected from four farms in April, May, June and July. Ewes were divided into five SCC groups on the basis of individual SCC: Low = 1000000 cells.mL-1). The percentage of distribution of individual milk samples in SCC groups was as followed: 71.79 %, 10.24 %, 5.05 %, 4.03 % and 8.89 % respectively. Thus 82.03 % of samples of whole data set were below 400000 cells.mL-1 and only 8.89 % over 1000000 cells.mL-1. Lacaune had a higher percentage of milk samples in the group Mastitis as compared to the other breeds or crossbreds. Factor SCC group reduced the milk yield, while a significant difference was observed in ewes of Mastitis SCC group as compared with ewes in Low SCC group (419±13 mL, 503±6 mL, resp.). The high percentage of ewes in the first two SCC groups significantly contributes to the possible development of limits for sheep milk quality.Cilj rada bio je analizirati broj somatskih stanica (SCC) individualnih uzoraka ovčjeg mlijeka ovaca na farmama. Prikupljeno je ukupno 2159 uzoraka s četiri farme tijekom travnja, svibnja, lipnja i srpnja. Ovce su bile podijeljene u pet SCC skupina na temelju pojedinačnih SCC vrijednosti: niska = 1.000.000 stanica.mL-1). Postotak distribucije pojedinačnih uzoraka mlijeka u SCC skupinama bio je kako slijedi: 71,79 %, 10,24 %, 5,05 %, 4,03 % i 8,89 %. Tako je 82,03 % svih ispitivanih uzoraka sadržavalo manje od 400.000 stanica mL-1, a samo je 8,89 % sadržavalo više od 1.000.000 stanica mL-1. Pasmina Lacaune imala je veći postotak uzoraka mlijeka u skupini “Mastitis” u usporedbi s ostalim pasminama ili križancima. Faktor SCC utjecao je na smanjenje prinosa mlijeka u skupini, dok je značajna razlika zabilježena kod ovaca svrstanih u “Mastitis SCC“ skupinu (419 ±13 mL-1) u usporedbi s ovcama u “Niska SCC“ skupini (503 ± 6 mL). Visok postotak ovaca u prve dvije “SCC skupine” značajno pridonosi mogućem razvoju graničnih vrijednosti broja somatskih stanica za definiranje kvalitete ovčjeg mlijeka

Evaluation of milk yield in tsigaiewes by somatic cell count

The objective of our research was to study daily milk production which was affected by somatic cell count (SCC). The study was performed on a selected flock of purebred Tsigai ewes (326 animals). Regular milk yield recording was performed during the evening milking in around the middle of April, May and June. Milk samples were analyzed for basic milk composition (fat, protein and lactose) and somatic cells count. SCC were evaluated using decadic logarithm (logSCC).According to animals, the dairy ewes were divided into the four groups on the basis of individual SCC (G1 = SCC &lt;100 × 103 cells.mL-1, G2 = SCC between 100 – 300 × 103 cells.mL-1, G3 = SCC between 300 – 600 × 103 cells.mL-1, G4 = SCC &gt;600 × 103 cells.mL-1 to study the frequency of distribution of animals in selected group of ewes throughout experimental period. The average daily milk production in selected flock of Tsigai was 421.02 mL. We reached the highest daily milk production in April 476.40 ml and the highest content of fat and protein in June, while milk production was the lowest. From this flock of purebred Tsigai 76% of eweswere belowSCC 300 × 103 cells.mL-1. This SCC indicated a good health status of experimental ewes, at which 61% sheep were at the first lactation. We found a tendency to lower milk production by a higher SCC. With the increasing SCC decreased lactose content from 4.78% (G1) to 4.32% (G4). Reduced lactose content refers to the occurrence of mastitis and there is a need for performing bacteriological examination in milk

Somatic cell count in milk of individual lacaune ewes under practical conditions in slovakia: possible effect on milk yield and its composition

The aim of this study was to describe the health status of udder through analysis of somati cell count (SCC) in milk of Lacaune breed. The study was conducted at five Slovak farms. Milk yield recordings and milk samples were taken from March till August by certificated organisation for milk recording, where also milk analysis on SCC was processed. In total 1192 samples were analysed. Milk samples were divided into the five categories on the basis of SCC: SCC &lt;0.2 &times; 106, between 0.2 - 0.4 &times; 106, 0.4 - 0.6 &times; 106, 0.6 - 1 &times; 106 and &gt;106 cells.mL-1. Animals were divided into seven stages of lactation (first: 30-60 days of lactation and then each following 30 days a further group of lactation stage was considered). The Mixed model with Scheffe's analysis as a post hoc test was used. SCC on farm 3 was highest (5.80 &plusmn;0.04 log SCC mL-1) as compared with others farms (p &lt;0.05). Significant effect of farms on milk yield demonstrates different level of farm management. Between farm 1 and 3 the differences in milk yield per milking is more than double. Frequency of distribution of milk samples was 53.36%, 13.93%, 6.29%, 7.21% and 19.21% for different categories respectively. In category &gt;106 cells.mL-1 the highest percentage was on farm 4 (33.57%) and lowest on farm 2 (8.06%) though more representative percentage was on farm 5 (12.05%) due to larger number of animals. The negative effect of high SCC on milk yield was observed in all farms. Data also revealed that main part of individual milk samples had SCC below 0.6&nbsp;&times;&nbsp;106 cells.mL-1 which could be an important argument for future legislative establishment of limits for SCC in ewe's milk.&nbsp; Normal 0 21 false false false EN-GB X-NONE X-NONE <!--[endif] --

Relationship between mastitis causative pathogens and somatic cell counts in milk of dairy cows

Milk somatic cell count is a key component of national and international regulation for milk quality and an indicator of udder health and of the prevalence of clinical and subclinical mastitis in dairy herds. The objective of this study was to evaluate the presence of mastitis pathogens in milk samples differed by somatic cell count (SCC) in microbiologically positive samples. Also frequency of distribution of samples differed by SCC were studied in non infected samples as well. The milk samples were collected from individual quarters from the dairy farms located in Nitra region with problematic udder health of herd for SCC and bacteriological analysis. Totally, 390 milk samples were examined, and 288 (73.85%) positive milk samples were detected. Four SCC groups of samples (400×103 /ml) were used to identify presence of microorganisms in positive samples. The most frequently isolated pathogens in samples with high SCC >400×103 /ml according to year were Coagulase-negative Staphylococci (29.11 %) in 2012, followed by Staphylococcus aureus (28.0%) in 2010, yeasts (24.05%) in 2012, Escherichia coli (22.78%) in 2012, Bacillus sp. (20%) in 2010 and Pseudomonas aerugenosa (11.88%) in 2011. Coagulase-negative Staphylococci (66.67%) were the predominantly identified in the samples with low SCC <100×103 cells/ml, followed by Bacillus spp (50%), Entrococcus spp. (33.33%) and Staphylococcus aureus (16.67%) and E. coli (16.67%). The results of this study indicated that the SCC of individual milk samples corresponded with the health status of the udder of dairy cows represented by presence of mastitis microorganisms in milk. However, the contamination of milk samples could be also connected with low SCC. On the ohter side the samples with high SCC were found out without presence of microorganism. The further study is needed to identify the reason of high SCC in milk from negative samples