Determination of milk fatty acids and some phenotypic characters affecting total milk fat in dairy cows with multiple linear regression
Abstract
This study aimed to determine the effect of milk fatty acid composition, breed, and pregnancy status on total milk fat in dairy cows. The study was conducted with a total of 400 milk samples collected form healthy Holstein and Simmental cows. Milk samples were collected for total milk fat and fatty acid analysis. To investigate the effects of milk fatty acids, breed and pregnancy status on total milk fat, multiple linear regression analysis was performed. As a result of the analysis, breed, pregnancy status, C11:0, C14:0, C18:0, C18:1 ω9 and C18:3 ω6 were found to be statistically significant (p<0.05), while the C18:3 ω3 was nearly significant (p=0.069). Also, Holstein cows, C11:0 and C18:0 were found to have a positive effect, while pregnant cows, C14:0, C18:1 ω9, C18:3 ω3, and C18:3 ω6 had a negative effect. The multiple explanatory coefficient of the regression model (R2) was 0.238. In the light of all these findings, it was thought that milk fat could be increased with different breeding protocols. Moreover, it is suggested that the regression model can be improved further by adding different variables in future studies.
Supporting Institution
Scientific Research Project Fund of HATAY MUSTAFA KEMAL ÜNİVERSİTESİ
Project Number
21.GAP.004
Thanks
We would like to thank Saray Agriculture and Livestock Inc. for their kindly help.
References
- 1. TÜİK. Animal production data [serial online]. 2022 Nov 10 [cited 2022 Nov 15]; Available from: URL:http://www.tuik.gov.tr/Start.do.
- 2. Akçapınar H, Özbeyaz C. Hayvan yetiştiriciliği temel bilgileri. Ankara: Kariyer Matbaacılık Ltd Şti; 1999.
- 3. Korkmaz M, Akyüz B. Simental ırkı sığırlarda GH ve PIT-I gen polimorfizmleri ile süt verimleri arasındaki ilişkinin araştırılması. KSÜ Tarım ve Doğa Derg 2020;23(6):1678-1686.
- 4. Koç A. Simmental yetiştiriciliğinin değerlendirilmesi: 1. Dünyada ve Türkiye'deki yetiştiriciliği. ADÜ Ziraat Derg 2016;13(2):97-102.
- 5. Fleming A, Schenkel FS, Chen J, Malchiodi F, Bonfatti V, Ali RA et al. Prediction of milk fatty acid content w ith mid-infrared spectroscopy in Canadian dairy cattle using differently distributed model development sets. J Dairy Sci 2017;100(6):5073-5081.
- 6. Teng F, Wang P, Yang L, Ma Y, Day L. Quantification of fatty acids in human, cow, buffalo, goat, yak, and camel milk using an improved one-step GC-FID method. Food Anal Methods 2017;10(8):2881-2891.
- 7. Pilarczyk R, Wójcik J, Sablik P, Czerniak P. Fatty acid profile and health lipid indices in the raw milk of Simmental and Holstein-Friesian cows from an organic farm. S Afr J Anim Sci 2015;45(1):30-38.
- 8. Akçay A, Yakan A, Ünal N. Bafra (Sakız x Karayaka G1) kuzularında et kalitesinin değerlendirilmesinde alternatif bir yaklaşım: Temel bileşenler analizi. Erciyes Üniv Vet Fak Derg 2014;11(2):105-110.
- 9. Alpar R. Uygulamalı çok değişkenli istatistiksel yöntemler. Ankara: Detay Yayıncılık; 2013.
- 10. Özkan H, Yakan A, Çamdeviren B, Karaaslan İ. Milk traits of damascus goats at different lactation stages: 1. Somatic cell counts and milk quality parameters. Erciyes Üniv Vet Fak Derg 2020;17:318-324.
- 11. Özkan H, Karaaslan İ, Kaya U, Dalkıran S, Yüksel M, Yakan A. The levels of milk fatty acids and alterations of correlations between them in weaning process in damascus goats. Large Anim Rev 2022;28:241-248.
- 12. Rebechi SR, Vélez MA, Vaira S, Perotti MC. Adulteration of Argentinean milk fats with animal fats: Detection by fatty acids analysis and multivariate regression techniques. Food Chem 2016;192:1025-1032.
- 13. Rodriguez MAP, Petrini J, Ferreira EM, Mourao LRMB, Salvian M, Cassoli LD et al. Concordance analysis between estimation methods of milk fatty acid content. Food Chem 2014;156:170-175.
- 14. Pralle RS, Weigel KW, White HM. Predicting blood β-hydroxybutyrate using milk Fourier transform infrared spectrum, milk composition, and producer-reported variables with multiple linear regression, partial least squares regression, and artificial neural network. J Dairy Sci 2018;101(5):4378-4387.
- 15. Ungerfeld EM, Urrutia NL, Vásconez-Montúfar C, Morales R. Factors associated with the content of mammary-synthesized fatty acids in milk fat: A meta-analysis. J Dairy Sci 2019;102(5):4105-4117.
- 16. Gross JJ, Bruckmaier RM. Metabolic challenges in lactating dairy cows and their assessment via established and novel indicators in milk. Animal 2019;13:75-81.
- 17. Bendelja D, Prpić Z, Mikulec N, Ivkic Z, Havranek J, Antunac N. Milk urea concentration in Holstein and Simmental cows. Mljekarstvo 2011;61(1):45-55.
- 18. Mauric M, Masek T, Ljoljic DB, Grbavac J, Starcevic K. Effects of different variants of the FASN gene on production performance and milk fatty acid composition in Holstein× Simmental dairy cows. Vet Med 2019;64(3):101-108.
- 19. Penasa M, De Marchi M, Cassandro M. Effects of pregnancy on milk yield, composition traits, and coagulation properties of Holstein cows. J Dairy Sci 2016;99(6):4864-4869.
- 20. Laine A, Bastin C, Grelet C, Hammami H, Colinet FG, Dale LM et al. Assessing the effect of pregnancy stage on milk composition of dairy cows using mid-infrared spectra. J Dairy Sci 2017;100(4):2863-2876.
- 21. Olori VE, Brotherstone S, Hill WG, McGuirk BJ. Effect of gestation stage on milk yield and composition in Holstein Friesian dairy cattle. Livest Prod Sci 1997;52(2):167-176.
- 22. Moate PJ, Chalupa W, Boston RC, Lean IJ. Milk fatty acids. I. Variation in the concentration of individual fatty acids in bovine milk. J Dairy Sci 2007;90(10):4730-4739.
- 23. Wiking L, Stagsted J, Björck L, Nielsen JH. Milk fat globule size is affected by fat production in dairy cows. Int Dairy J 2004;14(10):909-913.
- 24. Dan N, Zhang H, Ao C, Khas-Erdene. Transcriptional regulation of milk lipid synthesis by exogenous C16: 0 and C18 fatty acids in bovine mammary epithelial cells. Can J Anim Sci 2018;98:260-270.
- 25. Li Y, Xu C, Xia C, Zhang H, Sun L, Gao Y. Plasma metabolic profiling of dairy cows affected with clinical ketosis using LC/MS technology. Vet Q 2014;34(3):152-158.
- 26. Čítek J, Brzáková M, Hanusová L, Hanus O, Vecerek L, Samkova E et al. Gene polymorphisms influencing yield, composition and technological properties of milk from Czech Simmental and Holstein cows. Anim Biosci 2021;34(1):2-11.
- 27. Samková E, Čítek J, Brzáková M, Hanus O, Vecerek L, Jozova E et al. Associations among Farm, Breed, Lactation Stage and Parity, Gene Polymorphisms and the Fatty Acid Profile of Milk from Holstein, Simmental and Their Crosses. Animals 2021;11(11):3284.
Sütçü ineklerde toplam süt yağı üzerine etkisi olan yağ asitleri ve bazı fenotipik karakterlerin çoklu doğrusal regresyon ile belirlenmesi
Abstract
Bu çalışma, süt ineklerinde süt yağ asitleri, ırk ve gebelik durumunun toplam süt yağına etkisini incelemeyi amaçlamıştır. Çalışma sağlıklı Holştayn ve Simental ineklerden toplanan toplam 400 adet süt örneği ile yürütülmüştür. Süt örnekleri, toplam süt yağı ve yağ asidi analizi için toplanmıştır. Süt yağ asitlerinin, ırkın ve gebelik durumunun toplam süt yağı üzerindeki etkilerini araştırmak için çoklu doğrusal regresyon analizi yapıldı. Analiz sonucunda ırk, gebelik durumu, C11:0, C14:0, C18:0, C18:1 ω9 ve C18:3 ω6 istatistiksel olarak anlamlı bulunurken (p<0,05), C18:3 ω3 neredeyse anlamlıydı (p=0,069). Ayrıca, Holştayn inekler C11:0 ve C18:0 pozitif bir etkiye sahip bulunmuşken, gebe inekler, C14:0, C18:1 ω9, C18:3 ω3 ve C18:3 ω6 negatif bir etkiye sahipti. Regresyon modelinin çoklu açıklayıcılık katsayısı (R2) 0,238'dir. Tüm bu bulgular ışığında farklı yetiştiricilik protokolleri ile süt yağının artırılabileceği düşünülmüştür. Ayrıca ileriki çalışmalarda farklı değişkenler eklenerek regresyon modelinin daha da geliştirilebileceği önerilmektedir.
Keywords
Project Number
21.GAP.004
References
- 1. TÜİK. Animal production data [serial online]. 2022 Nov 10 [cited 2022 Nov 15]; Available from: URL:http://www.tuik.gov.tr/Start.do.
- 2. Akçapınar H, Özbeyaz C. Hayvan yetiştiriciliği temel bilgileri. Ankara: Kariyer Matbaacılık Ltd Şti; 1999.
- 3. Korkmaz M, Akyüz B. Simental ırkı sığırlarda GH ve PIT-I gen polimorfizmleri ile süt verimleri arasındaki ilişkinin araştırılması. KSÜ Tarım ve Doğa Derg 2020;23(6):1678-1686.
- 4. Koç A. Simmental yetiştiriciliğinin değerlendirilmesi: 1. Dünyada ve Türkiye'deki yetiştiriciliği. ADÜ Ziraat Derg 2016;13(2):97-102.
- 5. Fleming A, Schenkel FS, Chen J, Malchiodi F, Bonfatti V, Ali RA et al. Prediction of milk fatty acid content w ith mid-infrared spectroscopy in Canadian dairy cattle using differently distributed model development sets. J Dairy Sci 2017;100(6):5073-5081.
- 6. Teng F, Wang P, Yang L, Ma Y, Day L. Quantification of fatty acids in human, cow, buffalo, goat, yak, and camel milk using an improved one-step GC-FID method. Food Anal Methods 2017;10(8):2881-2891.
- 7. Pilarczyk R, Wójcik J, Sablik P, Czerniak P. Fatty acid profile and health lipid indices in the raw milk of Simmental and Holstein-Friesian cows from an organic farm. S Afr J Anim Sci 2015;45(1):30-38.
- 8. Akçay A, Yakan A, Ünal N. Bafra (Sakız x Karayaka G1) kuzularında et kalitesinin değerlendirilmesinde alternatif bir yaklaşım: Temel bileşenler analizi. Erciyes Üniv Vet Fak Derg 2014;11(2):105-110.
- 9. Alpar R. Uygulamalı çok değişkenli istatistiksel yöntemler. Ankara: Detay Yayıncılık; 2013.
- 10. Özkan H, Yakan A, Çamdeviren B, Karaaslan İ. Milk traits of damascus goats at different lactation stages: 1. Somatic cell counts and milk quality parameters. Erciyes Üniv Vet Fak Derg 2020;17:318-324.
- 11. Özkan H, Karaaslan İ, Kaya U, Dalkıran S, Yüksel M, Yakan A. The levels of milk fatty acids and alterations of correlations between them in weaning process in damascus goats. Large Anim Rev 2022;28:241-248.
- 12. Rebechi SR, Vélez MA, Vaira S, Perotti MC. Adulteration of Argentinean milk fats with animal fats: Detection by fatty acids analysis and multivariate regression techniques. Food Chem 2016;192:1025-1032.
- 13. Rodriguez MAP, Petrini J, Ferreira EM, Mourao LRMB, Salvian M, Cassoli LD et al. Concordance analysis between estimation methods of milk fatty acid content. Food Chem 2014;156:170-175.
- 14. Pralle RS, Weigel KW, White HM. Predicting blood β-hydroxybutyrate using milk Fourier transform infrared spectrum, milk composition, and producer-reported variables with multiple linear regression, partial least squares regression, and artificial neural network. J Dairy Sci 2018;101(5):4378-4387.
- 15. Ungerfeld EM, Urrutia NL, Vásconez-Montúfar C, Morales R. Factors associated with the content of mammary-synthesized fatty acids in milk fat: A meta-analysis. J Dairy Sci 2019;102(5):4105-4117.
- 16. Gross JJ, Bruckmaier RM. Metabolic challenges in lactating dairy cows and their assessment via established and novel indicators in milk. Animal 2019;13:75-81.
- 17. Bendelja D, Prpić Z, Mikulec N, Ivkic Z, Havranek J, Antunac N. Milk urea concentration in Holstein and Simmental cows. Mljekarstvo 2011;61(1):45-55.
- 18. Mauric M, Masek T, Ljoljic DB, Grbavac J, Starcevic K. Effects of different variants of the FASN gene on production performance and milk fatty acid composition in Holstein× Simmental dairy cows. Vet Med 2019;64(3):101-108.
- 19. Penasa M, De Marchi M, Cassandro M. Effects of pregnancy on milk yield, composition traits, and coagulation properties of Holstein cows. J Dairy Sci 2016;99(6):4864-4869.
- 20. Laine A, Bastin C, Grelet C, Hammami H, Colinet FG, Dale LM et al. Assessing the effect of pregnancy stage on milk composition of dairy cows using mid-infrared spectra. J Dairy Sci 2017;100(4):2863-2876.
- 21. Olori VE, Brotherstone S, Hill WG, McGuirk BJ. Effect of gestation stage on milk yield and composition in Holstein Friesian dairy cattle. Livest Prod Sci 1997;52(2):167-176.
- 22. Moate PJ, Chalupa W, Boston RC, Lean IJ. Milk fatty acids. I. Variation in the concentration of individual fatty acids in bovine milk. J Dairy Sci 2007;90(10):4730-4739.
- 23. Wiking L, Stagsted J, Björck L, Nielsen JH. Milk fat globule size is affected by fat production in dairy cows. Int Dairy J 2004;14(10):909-913.
- 24. Dan N, Zhang H, Ao C, Khas-Erdene. Transcriptional regulation of milk lipid synthesis by exogenous C16: 0 and C18 fatty acids in bovine mammary epithelial cells. Can J Anim Sci 2018;98:260-270.
- 25. Li Y, Xu C, Xia C, Zhang H, Sun L, Gao Y. Plasma metabolic profiling of dairy cows affected with clinical ketosis using LC/MS technology. Vet Q 2014;34(3):152-158.
- 26. Čítek J, Brzáková M, Hanusová L, Hanus O, Vecerek L, Samkova E et al. Gene polymorphisms influencing yield, composition and technological properties of milk from Czech Simmental and Holstein cows. Anim Biosci 2021;34(1):2-11.
- 27. Samková E, Čítek J, Brzáková M, Hanus O, Vecerek L, Jozova E et al. Associations among Farm, Breed, Lactation Stage and Parity, Gene Polymorphisms and the Fatty Acid Profile of Milk from Holstein, Simmental and Their Crosses. Animals 2021;11(11):3284.
Details
| Primary Language | English |
|---|---|
| Subjects | Veterinary Surgery, Animal Science, Genetics and Biostatistics |
| Journal Section | RESEARCH ARTICLE |
| Authors | |
| Project Number | 21.GAP.004 |
| Early Pub Date | June 14, 2023 |
| Publication Date | June 15, 2023 |
| Submission Date | November 18, 2022 |
| Acceptance Date | March 28, 2023 |
| Published in Issue | Year 2023 Volume: 94 Issue: 2 |
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