Proposal of a non-linear model to adjust in vitro gas production at different incubation times

Authors

DOI:

https://doi.org/10.14393/BJ-v39n0a2023-63017

Keywords:

Alternative foods, Degradation kinetics, Non-linear models, Silage, Suggested model.

Abstract

This work aims to propose a new model named Gompertz-Von Bertalanffy bicompartmental (GVB), a combination of the models Gompertz and Von Bertalanffy. The GVB models is applied to fit the kinetic curve of cumulative gas production (CGP) of four foods (SS – sunflower silage; CS – corn silage; and the mixtures 340SS – 660 gkg-1 of corn silage and 340 gkg-1 of sunflower silage; and 660SS – 340 gkg-1 of corn silage and 660 gkg-1 of sunflower silage). The GVB fit is compared to models Logistic-Von Bertalanffy bicompartmental (LVB) and bicompartmental logistic (BL). All the process studied employed the semi-automatic “in vitro” technique of producing gases used in ruminant nutrition. The gas production readout was performed at times 2, 4, 6, 8, 10, 12, 15, 19, 24, 30, 48, 72, and 96 h. The data generated were used to estimate the models’ parameters by the least squared method with the iterative Gauss-Newton process. The data fit quality of the models was verified using the adjusted coefficient of determination criterion (), mean residual square (MRS), Akaike information criterion (AIC), and mean absolute deviation (MAD). Among the analyzed models, the LVB model presented the best quality of fit evaluators for CS. In contrast, the GVB model showed better quality of fit to describe CGP over time for 340SS, 660SS, and SS, presenting the highest values of () and the lowest values of MSR, AIC, and MAD.

Downloads

Download data is not yet available.

References

ARAGADVAY-YUNGÁN, R.G., et al. Evaluación in vitro del ensilaje de girasol (Helianthus annuus L.) solo y combinado con ensilaje de maíz. Revista Mexicana de Ciencias Pecuarias. 2015, 6(3), 315-327.

BREUSCH, T.S. and PAGAN, A.R. A simple test for heteroscedasticity and random coefficient variation. Econometrica. 1979, 47, 1287-1294. https://doi.org/10.2307/1911963

DURBIN, J. and WATSON, G.S. Testing for serial correlation in least squares regression I. Biometrika. 1950, 37, 409-428. https://doi.org/10.1093/biomet

FRANCE, J., et al. A model to interpret gas accumulation profiles associated with in vitro degradation of ruminant feeds. Journal of theoretical biology. 1993, 163(1), 99-111. https://doi.org/10.1006/jtbi.1993.1109

FRANCE, J., et al. Estimating the extent of degradation of ruminant feeds from a description of their gas production profiles observed in vitro: derivation of models and other mathematical considerations. British Journal of Nutrition. 2000, 83(2), 143-150. https://doi.org/10.1017/S0007114500000180

FRANCE, J., et al. A general compartmental model for interpreting gas production profiles. Animal Feed Science and Technology. 2005, 123, 473-485. https://doi.org/10.1016/j.anifeedsci.2005.04.038

FERNANDES, T.J., et al. Selection of nonlinear models for the description of the growth curves of coffee fruit. Coffee Science. 2014, 9(2), 207-215. http://www.sbicafe.ufv.br:80/handle/123456789/8029

GROOT, J.C.J., et al. Multiphasic analysis of gas production kinetics for in vitro fermentation of ruminant feeds. Animal Feed Science and Technology. 1996, 64(1), 77-89. https://doi.org/10.1016/S0377-8401(96)01012-7

KOOPS, W.J., 1986. Multiphasic growth curve analysis. Growth 50, Bar Harbor, pp.169-177.

KRUEGER, N.A., et al. Evaluation of feeding glycerol on free-fatty acid production and fermentation kinetics of mixed ruminal microbes in vitro. Bioresource Technology. 2010, 101(21), 8469-8472. https://doi.org/10.1016/j.biortech.2010.06.010

LEITE, L.A., et al. Sunflower and corn silages in lactating cow diets: intake and digestibility. Arquivo Brasileiro de Medicina Veterinária e Zootecnia. 2006, 58(6), 1192-1198. https://doi.org/10.1590/S0102-09352006000600031

LEITE, L.A., et al. Performance of lactating dairy cows fed sunflower or corn silages and concentrate based on citrus pulp or ground corn. Revista Brasileira de Zootecnia. 2017, 46, 56-64. http://dx.doi.org/10.1590/s1806-92902017000100009

MAIDANA, E., et al. Características agronómicas del maíz inoculado con diferentes dosis de Azospirillum brasiliense. Revista de la Sociedad Científica del Paraguay. 2020, 25(1), 49-57. https://doi.org/10.32480/rscp.2020-25-1.49-57

MARTINS, S.C.D.S.G., et al. Consumo, digestibilidade, produção de leite e análise econômica de dietas com diferentes volumosos. Revista Brasileira de Saúde e Produção Animal. 2011, 12(3), 691-708.

MARTINS, A.D.S., et al. Glycerol inclusion levels in corn and sunflower silages. Ciência e Agrotecnologia. 2014, 38, 497-505. https://doi.org/10.1590/S1413-70542014000500009

MELLO, R., et al. Models for fit of gas production in sunflower and corn silages. Pesquisa Agropecuária Brasileira. 2008, 43(2), 261–269. http://dx.doi.org/10.1590/S0100-204X2008000200016

OLIVEIRA, J.G., 2016. Avaliação de modelos matemáticos de cinética de degradação ruminal. 2016. Dissertação de Mestrado. Universidade Tecnológica Federal do Paraná.

OLIVEIRA, V.S., et al. Estratégias para mitigar a produção de metano entérico. Veterinária Notícias. 2017, 23(1), 39-70. http://dx.doi.org/10.14393/VTV-v23n1-2017.4

PASTERNAK, H. and SHALEV, B.A. The effect of a feature of regression disturbance on the efficiency of fitting growth curves. Growth, Development and Aging: GDA. 1994, 58(1), 33-39.

PEREIRA, D.R., et al. Uso do girassol (Helianthus annuus) na alimentação animal: aspectos produtivos e nutricionais. Veterinária e Zootecnia. 2016, 23, 174-183.

R DEVELOPMENT CORE TEAM. A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing, 2018. Available in: http://www.r-project.org.

SÁ, J. F. D., et al. In vitro ruminal fermentation kinetics of Marandu grass at different harvest ages. Acta Scientiarum. Animal Sciences. 2011, 33(3), 225-232.

SANTOS, A.L.P., et al. Generation of models from existing models composition: An application to agrarian sciences. PloS one. 2019, 14(12), e0214778. https://doi.org/10.1371/journal.pone.0214778

SANTOS, A.L.P., et al. New model of evaluation of sunflower and corn silages by the in vitro gas production technique. Semina: Ciências Agrárias. 2020, 41(4), 1373-1384. http://biblioteca.incaper.es.gov.br/digital/handle/123456789/4019

SANTOS, A.L.P., e al. Proposals of non-linear models to adjust in vitro gas production at different incubation times in cassava genotypes. Ciência e Natura. 2021, 43, e22. https://doi.org/10.5902/

X39962

SCHOFIELD, P., PITT, R.E. and PELL, A.N. Kinetics of fiber digestión from in vitro gas production. Journal of animal science. 1994, 72(11), 2980-2991.

SHAPIRO, S.S. and WILK, M.B. An analysis of variance test for normality. Biometrika. 1965, 52(3), 591–611

SOUZA, G.S., 1998. Introdução aos modelos de regressão linear e não linear, 1 ed. Brasília: EmbrapaSPI/Embrapa-SEA.

THORNLEY, J.H.M. and FRANCE, J. An open-ended logistic-based growth function. Ecological Modelling. 2005, 184(2-4), 257-261. https://doi.org/10.1016/j.ecolmodel.2004.10.007

ÜÇKARDEŞ, F. and EFE, E. Investigation on the usability of some mathematical models in in vitro gas production techniques. Slovak Journal of Animal Science. 2014, 47(3), 172-179.

WANDERLEY, W.L., et al. Consumo, digestibilidade e parâmetros ruminais em ovinos recebendo silagens e fenos em associação à palma forrageira. Revista Brasileira de Saúde e Produção Animal. 2012, 13(2), 444-456. https://doi.org/10.1590/S1519-99402012000200013

Downloads

Published

2023-03-31

How to Cite

SANTOS, A.L.P. dos, FERREIRA, T.A.E., BRITO, C.C.R. de, MOREIRA, G.R., GOMES-SILVA, F., JALE, J.S., REIS, R.B., LEITE, L.A. and PIMENTEL, P.G., 2023. Proposal of a non-linear model to adjust in vitro gas production at different incubation times. Bioscience Journal [online], vol. 39, pp. e39046. [Accessed22 November 2024]. DOI 10.14393/BJ-v39n0a2023-63017. Available from: https://seer.ufu.br/index.php/biosciencejournal/article/view/63017.

Issue

Section

Agricultural Sciences