Lactation curve, milk composition and metabolic status of goats from different genetic groups under tropical conditions

Document Type : Research Article (Regular Paper)

Authors

1 School of Veterinary Medicine and Animal Science/Federal University of Bahia, Salvador City, Bahia State, 40.170-110, Brazil

2 Department of Agricultural and Environmental Sciences of the State University of Santa Cruz, Ilhéus City, 45.662-900, Brazil

3 Department of Animal Science, Federal University of Ceara, Fortaleza City, Ceara State, Brazil

4 Department of Animal Science, Federal University of Ceará, Fortaleza City, Ceará State, 60356-001, Brazil

Abstract

The objectives of this study were 1) to compare models to describe the lactation curve of the Saanen, Moxotó, and Anglo-Nubian 2) to evaluate the effect of genetic groups on production and composition milk and efficiency of mobilization of body reserves during lactation. Twenty-three multiparous goats, newly calved, were divided into three treatments (genetic groups: 9 Saanen, 8 Moxotó, and 6 Anglo-Nubian). The goats were randomly distributed in collective pens, under the same feeding conditions. Five mathematical models were used to adjust the lactation curves: Wood (WD); Papajcsik and Bodero (PB); Adapted from Papajcsik and Bodero (APB); Nelder (ND) and Wilmink (WM). To indicate the best fit, the model evaluation system software was used, performing additional analyzes with the observed and predicted values ​​for each fitted equation. There were differences (P<0.05) in the parameters a, b and c between the genetic groups in each mathematical model. The APB model is recommended for use in all genetic groups to evaluate milk yield (Y), following the parameters: Y = 1.196+0.0545×t×e (-0.038×t) for Saanen, Y = 0.297+0.031×t×e(-0.0462×t) for Moxotó and Y = 0.757+0.0554×t×e(-0.0417×t) for Anglo-Nubian. The results for average milk production during 27 weeks of lactation were 1.37; 0.37 and 0.9 kg d-1 for Saanen, Moxotó and Anglo-Nubian, respectively. Except for lactose, there was a difference (P<0.05) between the genetic groups for milk composition and plasma beta-hydroxybutyrate (BHB) levels. Considering milk composition, the Saanen, Moxoto and Anglo Nubiana presented the averages (%) for fat of 3.66, 6.75, and 5.10, protein 3.32, 4.97, and 4.18 and lactose 4.28, 4.46, and 4.39%, respectively. There was no effect (P>0.05) on B-HBO in response to days of lactation, but Saanen and Anglo Nubian goats had higher plasma levels of this metabolite compared to Moxotó goats. Saanen had a greater weight loss of 12.83 kg, which was verified at 35 days of lactation. Saanen and Anglo-Nubian animals have a greater ability to mobilize body reserves compared to Moxotó. APB model is adequate to describe milk production of goats in tropical areas.

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References
Aliloo, H., Pryce, J.E., González-Recio, O., Cocks, B.G., Goddard, M.E., Hayes, B.J., 2017.    Including nonadditive genetic effects in mating programs to maximize dairy farm profitability. Journal of Dairy Science 100, 1203-1222. doi.org/10.3168/jds.2016-11261.
Amayi, A.A., Okeno, T.O., Gicheha, M.G., Kahi, A.K., 2016. Breeding systems for genetic improvement of dairy goats in smallholder production systems in Kenya. Small Ruminant Research 144,176-183. doi.org/10.1016/j.smallrumres.2016.09.017.
AOAC, 2005. Official Methods of Anaysis. 18th ed., Association of Official Analytical Chemists, Washington, DC. USA.
Araújo, M.J.D., Medeiros, A.N.D., Teixeira, I.A.M.D.A., Costa, R.G., Marques, C.A.T., Resende, K.T.D., Melo, G.M.P.D., 2017. Trace mineral requirements for growth of Moxotó goats grazing in the semiarid region of Brazil. Revista Brasileira de Zootecnia 46, 231-239.  doi.org/10.1590/S1806-92902017000300008.
Bermejo, J.V.D., Limón, Pérez, F.A., Navas, G.F.J., León, J.M, Álvarez, F.J, Gama, L.T., 2020. Conditioning factors of linearized Wood's function lactation curve shape parameters, milk yield, fat and protein content in Murciano-Granadina primiparous does. Animals 10, 1-16. doi: 10.3390/ani10112115.
Bouallegue, M., M’Hamdi, N., 2020. Mathematical modeling of lactation curves: A review of parametric models. In: Lactation in Farm Animals: Biology, Physiological Basis, Nutritional Requirements, and Modelization. Ed. IntechOpen Limited. doi: 10.5772/intechopen.90253.
Brzáková M., Rychtářová J., Čítek J., Sztankóová Z.A., 2021. Candidate gene association study for economically important traits in Czech dairy goat breeds. Animals 11, 1-15. doi: 10.3390/ani11061796.
Chávari, A.C.T., Marques, R.O., Cañizares, G.I.L., Brito, E.P., Gomes, H.F.B., Lourençon, R. V., Gonçalves, H.C., 2020. Yield, composition, and fatty acid profile of milk from Anglo-Nubian goats fed a diet supplemented with vegetable oils. Revista Brasileira de Zootecnia 49, 1-15. doi.org/10.37496/rbz4920200071.
Felisberto Perdigão, N.D.O., Oliveira, L., Cordeiro, A., 2016. Sistemas de produção de caprinos leiteiros. Proceedings of the 13 Workshop sobre produção de caprinos na região da Mata Atlântica, Embrapa Caprinos e Ovinos, Brasil.
Fonseca, W.L., Azevêdo, D.M.M.R., Campelo, J.E.G., Fonseca, W.L., Luz, C.S.M., Oliveira, M.R.A., Júnior, S.S., 2016. Effect of heat stress on milk production of goats from Alpine and Saanen breeds in Brazil. Archivos de Zootecnia 65, 615-621.
Hall, M.B., 2000. Neutral Detergent-Soluble Carbohydrates: Nutritional Relevance and Analysis. Gainesville: University of Florida, P. 76.
Ledinek, M., Gruber, L., Steininger, F., Fuerst-Waltl, B., Zottl, K., Royer, M., Egger-Danner, C., 2019. Analysis of lactating cows in commercial Austrian dairy farms: Interrelationships between different efficiency and production traits, body condition score and energy balance. Italian Journal of Animal Science 18, 723-733. https://doi.org/10.1080/1828051X.2019.1569485.
Licitra, G., Hernandez, T.M.,Van Soest, P.J., 1996. Standardization of procedures for nitrogen fractionation of ruminant feeds. Animal Feed Science and Technology 57, 347-358.
Lira, T.B.F., Bezerra, V.S., Silva, F.D.O., Dias, G.M.P., Lima, Filho, J.L.D., Porto, T.S., Porto, A.L.F., 2010. Evaluation of the variables that influence the enzymatic hydrolysis of Moxotó goat's milk casein. Pesquisa Agropecuária Brasileira 45,1036-1043.
Macciotta, N.P., Dimauro, C., Rassu, S.P., Steri, R., Pulina, G., 2011. The mathematical description of lactation curves in dairy cattle. Italian Journal of Animal Science 10,4. doi.org/10.4081/ijas. 2011.e51.
Mertens, D.R., 2002. Gravimetric determination of amylase-treated neutral detergent fiber in feeds with refluxing in beaker or crucibles: collaborative study. Journal of AOAC International 85, 1217-1240.
Miglior, F., Fleming, A., Malchiodi, F., Brito, L.F., Martin, P., Baes, C.F., 2017. A 100-Year Review: Identification and genetic selection of economically important traits in dairy cattle. Journal of Dairy Science 100, 10251-10271. doi: 10.3168/jds.2017-12968.
Nelder J.A., 1966. Inverse polynomials a useful group of multi-factor response functions. In: Internacional Biometric Society, pp. 128-141. doi.org/10.2307/2528220.
NRC, 2001. Nutrient Requirements of Dairy Cattle.  7th revised Edn. National Research Council. National Academy Press, Washington, DC, USA.
NRC, 2007. Nutrient Requirements of Small Ruminants: Sheep, Goats, Cervids, and New World Camelids. National Research Council. National Academy Press, Washington, DC, USA.
Nudda, A., Atzori, A.S., Boe, R., Francesconi, A.H.D., Battacone, G., Pulina, G., 2019. Seasonal variation in the fatty acid profile in meat of Sarda suckling lambs. Italian Journal of Animal Science 18, 488-497. doi: 10.1080/1828051X.2018.1542978.
Oliveira, J.G.D., Sant'Anna, D.F.D., Lourenço, M.C., Tavares, D.S.T., Rodrigues, M.T., Tedeschi, L.O., Vieira, R.A.M., 2020. The geometry of the lactation curve based on Wood's equation: a two-step prediction. Revista Brasileira de Zootecnia, 49, 1-21. doi: 10.37496/rbz4920200023.
Papajcsik, I.A., Bodero, J. 1988 Modeling lactation curves of Friesian cow in a subtropical climate. Animal Science 47, 201-207.
Prasad, H., Tewari, H.A., Sengar, O.P.S., 2005. Milk yield and composition of the Beetal breed and their crosses with Jamunapari, Barbari and Black Bengal breeds of goat. Small Ruminant Research 58, 195-199.
Queiroga, R.D.C.R.D., Costa, R.G., Biscontini, T.M.B., Medeiros, A.N.D., Madruga, M.S., Schuler, A.R.P., 2007. Effects of flock management, milking sanitary conditions and lactation stage on milk composition of Saanen goats. Revista Brasileira de Zootecnia 36, 430-437.
Ramos, J.P.D.F., Sousa, W.H., Santos, E.M., Medeiros, A.N., Moura, J.F., Junior, A.C.L., Silva, M.A., 2017. Dietary sources of diet for lactating Anglo-Nubian goats: intake, digestibility and ingestive behavior. Revista Electrónica de Veterinária 18, 1-20.
Regazzi, A.J., 1999. Teste para verificar a identidade de modelos de regressão e a igualdade de parâmetros no caso de dados de delineamentos experimentais. Revista Ceres 46, 383-410.
Rocha, R.R.C., Costa, A.P.R., Azevedo, M.M.R., Nascimento, H.T.S., Cardoso, F.S., Muratori, M.C.S., Lopes, J.B., 2009. Climatic adaptability of Saanen and Azul goats in Brazilian Middle-North. Arquivo Brasileiro de Medicina Veterinária e Zootecnia 61, 1165-1172.
Santos, S.A., Valadares Filho, S.C., Detmann, E., Valadares, R.F.D., Ruas, J.R.M., Prados, L.F.,  Vega, D.D.S.M., 2012. Voluntary intake and milk production in F1 Holstein × Zebu cows in confinement. Tropical Animal Health and Production 44, 1303-1310.
SAS, 2009. SAS/STAT User’s Guide: Statistical Analysis. Version 9.2. System SAS Institute, Cary, North Carolina. USA.
Sousa, N.M., Oliveira, J.S., Silva, D.S., Santos, E.M., Medeiros, A.N., Ramos, J.P.F., Brito, E.A., 2018. Levels of neutral detergent fiber in diets with forage palm for dairy goats. Arquivo Brasileiro de Medicina Veterinária e Zootecnia 70,1595-1604.
Tamime, A.Y., Wszolek, M., Božanić, R., Özer, B., 2011. Popular ovine and caprine fermented milks. Small Ruminant Research 101, 2-16. https://doi.org/10.1016/j.smallrumres.2011.09.021.
Tedeschi, L.O., 2006 Assessment of the adequacy of mathematical models. Agricultural Systems 89, 225-247
Tedeschi, L.O., Fox, D.G., Guiroy, P.J., 2004. A decision support system to improve individual cattle management. 1.A mechanistic, dynamic model for animal growth. Agricultural Systems 79, 171-204.
Tovar-Luna, I., Puchala, R., Sahlu, T., Freetly, H.C., Goetsch, A.L., 2010. Effects of stage of lactation and level of feed intake on energy utilization by Alpine dairy goats. Journal of Dairy Science 93, 4829-4837. doi: 10.3168/jds.2010-3316
Veerkamp, R.F., Emmans, G.C., 1995. Sources of genetic variation in energetic efficiency of dairy cows. Livestock Production Science 44, 87-97.
Verruck, S., Dantas, A., Prudencio, E.S., 2019. Functionality of the components from goat’s milk, recent advances for functional dairy products development and its implications on human health. Journal of Functional Foods 52, 243-257. https://doi.org/10.1016/j.jff.2018.11.017.
Wilmink J.B.M., 1987. Adjustment of test-day milk, fat and protein yields for age, season and stage of lactation. Livestock Production Science 16, 335-348.
Wood, P.D.P., 1967. Algebraic model of the lactation curve in cattle. Nature 216,164-165.
Yan, T., Mayne, C.S., Keady, T.W.J., Agnew, R.E., 2006. Effects of dairy cow genotype with two planes of nutrition on energy partitioning between milk and body tissue. Journal of Dairy Science, 89, 1031-1042. doi.org/10.3168/jds.S0022-0302(06)72170-1.
Journal of Livestock Science and Technologies
Volume 11, Issue 2
December 2023
Pages 1-12

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