Validação de curvas de desaparecimento in situ utilizando modelos matemáticos para incubação de farinha de peixe e farelo de algodão
DOI:
https://doi.org/10.5433/1679-0359.2020v41n6Supl2p3391Palavras-chave:
Farinha de peixe, Farelo de algodão, Técnica in situ, Modelos matemáticos.Resumo
Quatro modelos matemáticos foram utilizados para descrever o desaparecimento ruminal da matéria seca (MS) e proteína bruta (PB) da farinha de peixe e farelo de algodão. Os resultados da particularidade da degradabilidade da MS mostraram que todos os modelos se ajustaram bem (R2> 0,95), no entanto, considerando que valores abaixo de 0 ou acima de 100 não são biologicamente justificados na degradabilidade ruminal, eles não são aceitáveis. Os modelos I e II foram aceitos para a degradabilidade ruminal da MS da farinha de peixe e e o farelo de algodão. Apenas os modelos I e II foram adaptados com sucesso à degradabilidade de PB da farinha de peixe (R2> 0,96), e os modelos I, II e III foram aceitáveis para a degradabilidade ruminal da PB do farelo de algodão (R2> 0,98). Em termos de degradabilidade efetiva (DE) da MS e da PB, o modelo II gerou valores mais altos que os demais. Para apreciar plenamente o papel da modelagem matemática nas ciências biológicas, é necessário considerar a natureza dos alimentos que foram avaliados e revisar os tipos de modelos que podem ser construídos.Downloads
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Referências
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Dhanoa, M. S., France, J., Siddons, R. C., Lopez, S., & Buchanan, S. J .G. (1995). A non-linear compartmental model to describe for age degradation kinetics during incubation in polyester bags in the rumen. British Journal of Nutrition, 73, 3-15. doi: 10.1079/BJN19950004
Dijkstra, J., Bannink, A., Bosma, P. M., Lantinga, E. A., & Reijs, J. W. (2018). Modeling the effect of nutritional strategies for dairy cows on the composition of excreta nitrogen. Frontiers in Sustainable Food Systems, 2, 63. doi: 10.3389/fsufs.2018.00063
France, J., Thornley, J. H. M., Lopez, S., Siddons, R. C., Dhanoa, M. S., Van Soest, P. J., & Gill, M. (1990). On the two-compartment model for estimating extent of feed degradation in the rumen. Journal of Theoretical Biology, 146, 269-287. doi: 10.1016/S0022-5193(05)80139-0
Gregorini, P., Provenza, F. D., Villalba, J. J., Beukes, P. C., & Forbes, M. J. (2018). Dynamics of forage ingestion, oral processing and digesta outflow from the rumen: a development in a mechanistic model of a grazing ruminant, MINDY. The Journal of Agricultural Science, 156(8), 980-995. doi: 10.1017/S00 21859618000886
Hanigan, M. D., & Daley, V. L. (2019). Use of mechanistic nutrition models to identify sustainable food animal production. Annual Review of Animal Biosciences, 8, 355-376. doi: 10.1146/annurev-animal-021 419-083913
Jin, L., Dunière, L., Lynch, J. P., Zaheer, R., Turkington, K., Blackshaw, R. E., & Baah, J. (2017). Impact of ferulic acid esterase producing lactobacilli and fibrolytic enzymes on ensiling and digestion kinetics of mixed small grain silage. Grass and Forage Science, 72(1), 80-92. doi: 10.1111/gfs.12217
Lapierre, H., Larsen, M., Sauvant, D., Van Amburgh, M. E., & Van Duinkerken, G. (2018). Converting nutritional knowledge into feeding practices: a case study comparing different protein feeding systems for dairy cows. Animal, 12(s2), s457-s466. doi: 10.1017/S1751731118001763
Lopes, F. C. F., Campos, M. M., Borges, A. L. D. C. C., Pancoti, C. G., Reis, R., & Moreira, T. S. (2018). Rumen parameters and passage rate in cattle fed diets based on sugarcane hydrolyzed with calcium oxide. Semina: Ciências Agrárias, 39(6), 2783-2794. doi: 10.5433/1679-0359.2018v39n6p2783
Milani, M. M. R. A., Çavdar, T., & Aghjehkand, V. F. (2012). Particle swarm optimization based determination of Ziegler-Nichols parameters for PID controller of brushless DC motors. International Symposium on Innovations in Intelligent Systems and Applications (pp. 1-5). IEEE. doi: 10.1109/ INISTA.2012.6246984
Oberson, J. L., Probst, S., & Schlegel, P. (2019). Magnesium absorption as influenced by the rumen passage kinetics in lactating dairy cows fed modified levels of fibre and protein. Animal, 13(7), 1412-1420. doi: 10.1017/S1751731118002963
Ørskov, E. R., Hovel, F. D. B., & Mould, F. L. (1980). The use of the nylon bag technique for evaluation of feedstuffs. Tropical Animal Production, 5, 195-213. Recovered from http://www.fao.org/WAICENT/ faoINFO/AGRICULT/AGA/AGAP/FRG/TAP53/53_1.pdf
Ørskov, E. R. I., & McDonald, I. M. (1979). The estimation of protein degradability in the rumen from incubation measurements weighted according to rate of passage. Journal of Agricultural Sciences, 92, 499-503. doi: 10.1017/S0021859600063048
Palangi, V., & Macit, M. (2019). In situ crude protein and dry matter ruminal degradability of heat-treated barley. Revue de Medecine Veterinaire, 170(7-9), 123-128. Recovered from https://www.revmedvet. com/2019/RMV170_123_128.pdf
Reed, K. F., Arhonditsis, G. B., France, J., & Kebreab, E. (2016). Bayesian calibration of dynamic ruminant nutrition models. Journal of Dairy Science, 99(8), 6362-6370. doi: 10.3168/jds.2015-10708
Rochen, N. M. R. Jr., Silva, M. C. da, Abreu, M. L. C., Oliveira, J. G. de, Glória, L. S., Tedeschi, L. O., & Vieira, R. A. M. (2020). The transit of external markers throughout the ruminant digestive tract: 1. The fitting quality of models to marker profiles in feces using an information-theoretic approach. Animal Feed Science and Technology, 261, 114407. doi: 10.1016/j.anifeedsci.2020.114407
Sauvant, D., & Noziere, P. (2016). Quantification of the main digestive processes in ruminants: the equations involved in the renewed energy and protein feed evaluation systems. Animal, 10(5), 755-770. doi: 10. 1017/S1751731115002670
Vaga, M., & Huhtanen, P. (2018). In vitro investigation of the ruminal digestion kinetics of different nitrogen fractions of 15n-labelled timothy forage. Plos One, 13(9), e0203385. doi: 10.1371/journal. pone.0203385
Van Soest, P. J. (2018). Nutritional ecology of the ruminant. Cornell University Press.
Yousefian, S., Teimouri Yansari, A., & Chashnidel, Y. (2019). The effects of Indigestible Neutral Detergent Fiber (iNDF) of alfalfa hay and corn silage on ruminal degradability of ration fiber in sheep. Iranian Journal of Applied Animal Science, 9(1), 73-78. Recovered from http://www.iaujournals.ir/article_6635 56.html
Çavdar, T., Mohammad, M., & Milani, R. A. (2013). A new heuristic approach for inverse kinematics of robot arms. Advanced Science Letters, 19(1), 329-333. doi: 10.1166/asl.2013.4700
Chanzanagh, E. G., Seifdavati, J., Gheshlagh, F. M. A., Abdibenemar, H., & Seyedsharifi, R. (2019). Comparison of two mathematical models to describe the rumen fermentation parameters of some sources of plant and animal protein using in vitro gas method. Asian Journal of Research in Animal and Veterinary Sciences, 3(1), 1-6. Recovered from http://www.sdiarticle3.com/review-history/47943
Dhanoa, M. S., France, J., Siddons, R. C., Lopez, S., & Buchanan, S. J .G. (1995). A non-linear compartmental model to describe for age degradation kinetics during incubation in polyester bags in the rumen. British Journal of Nutrition, 73, 3-15. doi: 10.1079/BJN19950004
Dijkstra, J., Bannink, A., Bosma, P. M., Lantinga, E. A., & Reijs, J. W. (2018). Modeling the effect of nutritional strategies for dairy cows on the composition of excreta nitrogen. Frontiers in Sustainable Food Systems, 2, 63. doi: 10.3389/fsufs.2018.00063
France, J., Thornley, J. H. M., Lopez, S., Siddons, R. C., Dhanoa, M. S., Van Soest, P. J., & Gill, M. (1990). On the two-compartment model for estimating extent of feed degradation in the rumen. Journal of Theoretical Biology, 146, 269-287. doi: 10.1016/S0022-5193(05)80139-0
Gregorini, P., Provenza, F. D., Villalba, J. J., Beukes, P. C., & Forbes, M. J. (2018). Dynamics of forage ingestion, oral processing and digesta outflow from the rumen: a development in a mechanistic model of a grazing ruminant, MINDY. The Journal of Agricultural Science, 156(8), 980-995. doi: 10.1017/S00 21859618000886
Hanigan, M. D., & Daley, V. L. (2019). Use of mechanistic nutrition models to identify sustainable food animal production. Annual Review of Animal Biosciences, 8, 355-376. doi: 10.1146/annurev-animal-021 419-083913
Jin, L., Dunière, L., Lynch, J. P., Zaheer, R., Turkington, K., Blackshaw, R. E., & Baah, J. (2017). Impact of ferulic acid esterase producing lactobacilli and fibrolytic enzymes on ensiling and digestion kinetics of mixed small grain silage. Grass and Forage Science, 72(1), 80-92. doi: 10.1111/gfs.12217
Lapierre, H., Larsen, M., Sauvant, D., Van Amburgh, M. E., & Van Duinkerken, G. (2018). Converting nutritional knowledge into feeding practices: a case study comparing different protein feeding systems for dairy cows. Animal, 12(s2), s457-s466. doi: 10.1017/S1751731118001763
Lopes, F. C. F., Campos, M. M., Borges, A. L. D. C. C., Pancoti, C. G., Reis, R., & Moreira, T. S. (2018). Rumen parameters and passage rate in cattle fed diets based on sugarcane hydrolyzed with calcium oxide. Semina: Ciências Agrárias, 39(6), 2783-2794. doi: 10.5433/1679-0359.2018v39n6p2783
Milani, M. M. R. A., Çavdar, T., & Aghjehkand, V. F. (2012). Particle swarm optimization based determination of Ziegler-Nichols parameters for PID controller of brushless DC motors. International Symposium on Innovations in Intelligent Systems and Applications (pp. 1-5). IEEE. doi: 10.1109/ INISTA.2012.6246984
Oberson, J. L., Probst, S., & Schlegel, P. (2019). Magnesium absorption as influenced by the rumen passage kinetics in lactating dairy cows fed modified levels of fibre and protein. Animal, 13(7), 1412-1420. doi: 10.1017/S1751731118002963
Ørskov, E. R., Hovel, F. D. B., & Mould, F. L. (1980). The use of the nylon bag technique for evaluation of feedstuffs. Tropical Animal Production, 5, 195-213. Recovered from http://www.fao.org/WAICENT/ faoINFO/AGRICULT/AGA/AGAP/FRG/TAP53/53_1.pdf
Ørskov, E. R. I., & McDonald, I. M. (1979). The estimation of protein degradability in the rumen from incubation measurements weighted according to rate of passage. Journal of Agricultural Sciences, 92, 499-503. doi: 10.1017/S0021859600063048
Palangi, V., & Macit, M. (2019). In situ crude protein and dry matter ruminal degradability of heat-treated barley. Revue de Medecine Veterinaire, 170(7-9), 123-128. Recovered from https://www.revmedvet. com/2019/RMV170_123_128.pdf
Reed, K. F., Arhonditsis, G. B., France, J., & Kebreab, E. (2016). Bayesian calibration of dynamic ruminant nutrition models. Journal of Dairy Science, 99(8), 6362-6370. doi: 10.3168/jds.2015-10708
Rochen, N. M. R. Jr., Silva, M. C. da, Abreu, M. L. C., Oliveira, J. G. de, Glória, L. S., Tedeschi, L. O., & Vieira, R. A. M. (2020). The transit of external markers throughout the ruminant digestive tract: 1. The fitting quality of models to marker profiles in feces using an information-theoretic approach. Animal Feed Science and Technology, 261, 114407. doi: 10.1016/j.anifeedsci.2020.114407
Sauvant, D., & Noziere, P. (2016). Quantification of the main digestive processes in ruminants: the equations involved in the renewed energy and protein feed evaluation systems. Animal, 10(5), 755-770. doi: 10. 1017/S1751731115002670
Vaga, M., & Huhtanen, P. (2018). In vitro investigation of the ruminal digestion kinetics of different nitrogen fractions of 15n-labelled timothy forage. Plos One, 13(9), e0203385. doi: 10.1371/journal. pone.0203385
Van Soest, P. J. (2018). Nutritional ecology of the ruminant. Cornell University Press.
Yousefian, S., Teimouri Yansari, A., & Chashnidel, Y. (2019). The effects of Indigestible Neutral Detergent Fiber (iNDF) of alfalfa hay and corn silage on ruminal degradability of ration fiber in sheep. Iranian Journal of Applied Animal Science, 9(1), 73-78. Recovered from http://www.iaujournals.ir/article_6635 56.html
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2020-11-06
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Palangi, V., & Besharati, M. (2020). Validação de curvas de desaparecimento in situ utilizando modelos matemáticos para incubação de farinha de peixe e farelo de algodão. Semina: Ciências Agrárias, 41(6Supl2), 3391–3396. https://doi.org/10.5433/1679-0359.2020v41n6Supl2p3391
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