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The evaluation of the relationship of lactose to production and reproduction traits in different breeding conditions of the Slovak Spotted dairy cows

2021· article· en· W3132480010 on OpenAlexaboutno aff
Jozef Bujko

Bibliographic record

VenueActa fytotechnica et zootechnica/Acta fytotechnica et zootechnica · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsnot available
Fundersnot available
KeywordsLactoseAnimal scienceHerdSireIce calvingBiologyCullingDairy cattleLactationFood sciencePregnancy

Abstract

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Article Details: Received: 2020-10-23 | Accepted: 2020-11-27 | Available online: 2021-01-31 https://doi.org/10.15414/afz.2021.24.mi-prap.140-144 The aim of this study was to evaluate lactose in relation to milk production and calving interval in dairy cows of Slovak Spotted cattle. A total of 92,730 lactations from 45,800 dairy cows evaluation from 2015 to 2019 were used for investigating lactose percentage (LP), milk yield (MY), lactose yield (LY), fat percentage (FP), proteins percentage (PP) and calving interval (CI). Data were analysed using the SAS version 9.4 and linear model with fixed effects: herd-years-season (HYS), sire (S), breeding type (BT), coding of milk (Cod-MY) and coding of calving interval (Cod-CI). In the dataset the average of LP was 4.77±0.20 %, while the one of MY, LY, FP, PP and CI were 6,778.53±2,014.18 kg, 325.27±100.45 kg, 3.96±0.47 %, 3.39±0.23 % and 406.66±91.09 days. The correlation of LP with MY, LY, FP, PP and CI was equal to r = 0.1712, r = 0.3157, r = 0.0546, r = 0.1852 and r = -0.0147. These correlation coefficients were statistically highly significant P <0.0001. Among all fixed effects in the analysis of variance of LP, the most relevant effect was observed for HYS (P<.0001). Keywords: cattle, milk components, lactose, calving interval, correlation References Alessio, D. R. M. et al. (2016). Multivariate analysis of lactose content in milk of Holstein and Jersey cows. Semina: Ciências Agrárias , 37(4), 2641–2652. http://dx.doi.org/10.5433/1679-0359.2016v37n4Supl1p2641 Bolacali, M. and Öztürk, Y. (2018). Effect of non-genetic factors on milk yields traits in Simmental cows raised subtropical climate condition. Arquivo Brasileiro de Medicina Veterinária e Zootecnia , 70(1), 297–305. https://doi.org/10.1590/1678-4162-9325 Boro, P. et al. (2016). Genetic and non-genetic factors affecting milk composition in dairy cows. International Journal of Advanced Biological Research , 6(2), 170–174. BRS (2020). Average milk production of Fleckvieh in Germany. Retrieved August 12. 2020. https://www.ggi-spermex.de/en/fleckvieh/about-fleckvieh-92.html Bujko, J. (2011). Optimalization Genetic Improvement Milk Production in Population Slovak Spotted Breed . Monograph. Nitra: SAU, 78 p. in Slovak. Bujko, J. et al. (2018). Evaluation relation between traits of milk production and calving interval in breeding herds of Slovak Simmental dairy cows. Albanian Journal of Agricultural Sciences , 17(1), 31–36. http://ajas .inovacion.al/volume-17-issue-i/ Bujko, J. et al. (2019). The Analysis of Reproduction in Population of the Slovak Spotted Dairy Cows. Acta Universitatis Agriculturae Silviculturae Mendelianae Brunensis , 67(6), 1419–1426. https://doi.org/10.11118/ actaun201967061419 Bujko, J. et al. (2020). Changes in production and reproduction traits in population of the Slovak Spotted Cattle. Acta fytotechnica et zootechnica online. ISSN 1336-9245, 23(3) http://www.acta. fapz.uniag.sk/docs/03-20/bujko-et-al-ref.pdf Costa, A. et al. (2019). Genetic associations of lactose and its ratios to other milk solids with health traits in Austrian Fleckvieh cows. Journal of Dairy Science , 102(5), 4238–4248. https://doi.org/10.3168/jds.2018-15883 Cziszter, L. T. et al. (2017). Comparative study on production. reproduction and functional traits between Fleckvieh and Braunvieh cattle. Asian-Australas. J. Anim. Sci ., 30(5), 666–671. https://doi.org/10.5713/ ajas.16.0588 Han, I. and Bobiş, O. (2019). Analysis of the Reproduction Traits and Milk Yield in Cows from Apuseni Mountains Farms. Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Animal Science and Biotechnologie s, 76(1), 7–13. http://dx.doi.org/10.15835/buasvmcn-asb:2019.0004 Hermiz, H. N. and Hadad, J. M. (2020). Factors affecting and estimates of repeatability for milk production and composition traits in several breeds of dairy cattle. Indian Journal of Animal Sciences , 90(3), 129–133. Chegini, A. et al (2019). Genetic and environmental relationships among milk yield, persistency of milk yield, somatic cell count and calving interval in Holstein cows. Revista Colombiana de Ciencias Pecuarias , 32(2), 81–89. http://dx.doi.org/10.17533/udea.rccp.v32n2a01 Juráček, M. et al. (2020). The effect of different feeding system on fatty acids composition of cowʼs milk. Acta fytotechnica et zootechnica , 23(1), 37–41. https://doi.org/10.15414/afz.2020.23.01.37-41 Karcol, J. et al. (2017). Effect of feeding of different sources of NPN on production performance of dairy cows. Acta fytotechnica et zootechnica , 19(4), 163–166. https://doi.org/10.15414/afz.2016.19.04.163-166 Kasarda, R. et al. (2020). Genetic diversity and production potential of animal food resources. Acta fytotechnica et zootechnica , 23(2), 102–108. https://doi.org/10.15414/afz.2020.23.02.102-108 . Miglior, F. et al. (2007). Genetic analysis of milk urea nitrogen and lactose and their relationships with other production traits in Canadian Holstein cattle. J. Dairy Sci ., 90, 2468–2479. DOI: 10.3168/jds.2006-487 Satoła, A. et al. (2017). Genetic parameters for lactose percentage and urea concentration in milk of Polish Holstein‑Friesian cows. Animal Science Papers and Reports , 35(2), 159–172. http://www.ighz.edu.pl/uploaded/FSiBundleContentBlockBundleEntityTranslatableBlockTranslatableFilesElement/filePath/872/str241-252.pdf SAS INSTITUTE Inc. (2016). Base SAS® 9.4 Procedures Guide. Cary. NC: SAS InstituteInc., Carry, USA. Slovak Simmental Breeders Association. (2020). The history of the breed. standard. breeding type of Slovak Spotted cattle. ZCHSSD. [Online]. Available at: http://www.simmental.sk/about-breed/breed-objective.html [Accessed: 2020.Jule 21]. Stadnik, L. et al. (2018). Effects of body condition score and daily milk yield on reproduction traits of Czech Fleckvieh cows. Animal Reproduction(AR) , 14(Supplement 1), 1264–1269. http://dx.doi. org/10.21451/1984-3143-AR944 The Breeding Service of the Slovak Republic, S.E. (2020). Results of dairy herd milk recording in Slovak Republic at control years 2015 to 2019. BSSR. Retrieved July 20. 2020. http://test.plis.sk/volne /rocenkamagazin/rocenka.aspx?id= mlhd2019 ZAR (2020). Fleckvieh/ Simmental. [Annual report 2019]. Vienna: ZAR. Retrieved October 5. 2020. http://en.zar.at/Cattle_breeding_in_Austria.html

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.004
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.311
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2021
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