Statistical analysis alternatives to validate hematic parameters in dairy under tropical conditions

Authors

DOI:

https://doi.org/10.22267/rcia.202239E.193

Keywords:

dairy catlle, hematology, metabolites, statistical models, transition period, tropical conditions

Abstract

The hematic parameters of cows selected for milk production in grazing under tropic conditions were analyzed based on six experimental studies. The major objective was to determine statistical analysis alternatives that could be used in the study of physiological, environmental or genetic variations. The parameters analyzed were hematocrit, hemoglobin concentrations and counts of polymorphonuclear cells (i.e., eosinophils, basophils, neutrophils and lymphocytes). Initially 972 data from adult cows with productions considered medium-high in the context of local dairy production were analyzed. After the information decanting process, 415 records were used. These data corresponded to a sampling period from 30 days before calving to day 105 postpartum, with determinations made fortnightly.  Blood collection was made every two weeks and each moment was defined as a period. Different analytical techniques were applied in searching to extract the best information from the data and that could be reused in the future. The best type of analysis corresponded to the Random Forest (RF) technique, clustering, and analysis of variance.The effect of an indicator of energy metabolism (non-esterified fatty acids - NEFA), an indicator of protein metabolism (total protein - TP) of 10 collection periods, three breed groups and three types of nutritional management given to the animals on the blood variables were analyzed. Multivariate correlation and machine learning methods were used to extract information from the data. Results indicated that hematological behavior change throughout close up dry cow, transition period and first phase of lactation. No high direct or inverse correlation were found among variables. Hematocrit and hemoglobin levels can be estimated from variables associated with metabolic indicators and blood components. Further studies are required to elucidate the hematic behavior of dairy cows during the transition period.

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References

Aleri, J.W.; Hine, B.C.; Pyman, M.F.; Mansell, P.D.; Wales, W.J.; Mallard, B.; Fisher, A.D. (2016). Periparturient immunosuppression and strategies to improve dairy cow health during the periparturient period. Research in veterinary science. 108: 8-17. http://dx.doi.org/10.1016/j.rvsc.2016.07.007

Campos, R.; de Almeida Lacerda, L.; Terra, S.R.; González, F.H.D. (2008). Parâmetros hematológicos e níveis de cortisol plasmático em vacas leiteiras de alta produção no Sul do Brasil. Brazilian Journal of Veterinary Research and Animal Science. 45(5): 354-361..10.11606/issn.1678-4456.bjvras.2008.26676

Cozzi, G.; Ravarotto, L.; Gottardo, F.; Stefani, A.L.; Contiero, B.; Moro, L.; Brscic, M.; Dalvit, P. (2011). Short communication: reference values for blood parameters in Holstein dairy cows: effects of parity, stage of lactation, and season of production. Journal of Dairy Science. 94(8): 3895-3901. 10.3168/jds.2010-3687

De Vasconcelos, A.M.; de Albuquerque, C.C.; de Carvalho, J.F.; Façanha, D.A.E.; Lima, F.R.G.; Silveira, R.M.F.; Ferreira, J. (2020). Adaptive profile of dairy cows in a tropical region. International Journal of Biometeorology. 64: 105-113. 10.1007/s00484-019-01797-9

Di Rienzo, J.A.; Casanoves, F.; Balzarini, M.G.; Gonzalez, L.A.; Tablada, E.M. (2017). InfoStat, versión 2017. Universidad Nacional de Córdoba, Argentina._http://www.infostat.com.ar/index.php?mod=page&id=34

Florio-Luis, J.; Tamasaukas, R.; Rivera, S. (2012). Diagnóstico participativo de hemotrópicos en bovinos a nivel de pequeños productores y productoras de ganadería doble propósito en el sur del estado Aragua en la República Bolivariana de Venezuela. Actas Iberoamericanas de Conservación Animal. 2(2): 163-170.

Grünwaldt, E.G.; Guevara, J.C.; Estévez, O.R.; Vicente, A.; Rousselle, H.; Alcuten, N.; Aguerregaray, D.; Stasi, C.R. (2005). Biochemical and haematological measurements in beef cattle in Mendoza plain rangelands (Argentina). Tropical animal health and production. 37: 527-540. https://doi.org/10.1007/s11250-005-2474-5

Holdridge, L.R. (1967). Life zone ecology. San Jose, Costa Rica: Tropical Science Center.

Kim, S.; Jung, S.H.; Do, Y.J.; Jung, Y.H.; Choe, C.; Ha, S.; Jeong, H.Y.; Cho, A.; Oh, S.I.; Kim, E.; Yoo, J.G.; Kim, S. (2020). Haemato-chemical and immune variations in Holstein cows at different stages of lactation, parity, and age. Veterinární medicína. 65(3): 95-103. https://doi.org/10.17221/110/2019-VETMED

Krupa, J.R.; Pathan, M.M.; Madhira, S.P.; Pande, A.M.; Dhusa, D.D. (2018). Study of haematological parameters of crossbred cows during peripartum period. International Journal of Current Microbiology and Applied Sciences. 7(12): 461-467. 10.20546/ijcmas.2018.712.057

Martens, H. (2020). Transition period of the dairy cow revisited: I. Homeorhesis and its changes by selection and management. Journal of Agricultural Science. 12(3): 1–24. https://doi.org/10.5539/jas.v12n3p1

McGuffey, R.K. (2017). A 100-Year Review: Metabolic modifiers in dairy cattle nutrition. Journal of Dairy Science. 100(12): 10113-10142. 10.3168/jds.2017-12987

Moretti, P.; Paltrinieri, S.; Trevisi, E.; Probo, M.; Ferrari, A.; Minuti, A.; Giordano, A. (2017). Reference intervals for hematological and biochemical parameters, acute phase proteins and markers of oxidation in Holstein dairy cows around 3 and 30 days after calving. Research in Veterinary Science. 114: 322-331. 10.1016/j.rvsc.2017.06.012

Nguyen, T.; Fouchereau, R.; Frenod, E.; Gerard, C.; Sincholle, V. (2020). Comparison of forecast models of production of dairy cows combining animal and diet parameters. Computers and Electronics in Agriculture. 170: 105258..10.1016/j.compag.2020.105258

Oppong, F.B.; Agbedra, S.Y. (2016). Assessing univariate and multivariate normality, a guide for non-statisticians. Mathematical theory and modeling. 6(2): 26-33.

Radkowska, I.; Herbut, E. (2014). Hematological and biochemical blood parameters in dairy cows depending on the management system. Animal Science Papers & Reports. 32(4): 317–325.

RStudio Team. (2020). RStudio: Integrated development for R. RStudio, PBC, Boston, MA. http://www.rstudio.com/

Sejian, V.; Bhatta, R.; Gaughan, J.B.; Dunshea, F.R.; Lacetera, N. (2018). Adaptation of animals to heat stress. Animal. 12(s2): s431-s444. 10.1017/S1751731118001945

Tremblay, M.; Kammer, M.; Lange, H.; Plattner, S.; Baumgartner, C.; Stegeman, J.A.; Duda, J.; Mansfeld, R.; Döpfer, D. (2018). Identifying poor metabolic adaptation during early lactation in dairy cows using cluster analysis. Journal of Dairy Science. 101(8): 7311-7321. 10.3168/jds.2017-13582

Trevisi, E.; Minuti, A. (2018). Assessment of the innate immune response in the periparturient cow. Research in Veterinary Science. 116: pp. 47-54. 10.1016/j.rvsc.2017.12.001

Van der Heide, E.M.M.; Veerkamp, R.F.; van Pelt, M.L.; Kamphuis, C.; Athanasiadis, I.; Ducro, B.J. (2019). Comparing regression, naive Bayes, and random forest methods in the prediction of individual survival to second lactation in Holstein cattle. Journal of Dairy Science. 102(10): 9409–9421. https://doi.org/10.3168/jds.2019-16295

Zecconi, A.; Albonico, F.; Gelain, M.E.; Piccinini, R.; Cipolla, M.; Mortarino, M. (2018). Effects of herd and physiological status on variation of 16 immunological and inflammatory parameters in dairy cows during drying off and the transition period. Journal of Dairy Research. 85(2): 167-173 p. 10.1017/S0022029918000316

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Published

2022-12-20

How to Cite

Campos, R., Vélez , M. ., García, K. ., Correa, A. . ., & Ordoñez, A. L. . (2022). Statistical analysis alternatives to validate hematic parameters in dairy under tropical conditions. Revista De Ciencias Agrícolas, 39(E), 21–34. https://doi.org/10.22267/rcia.202239E.193