scholarly journals New model of evaluation of sunflower and corn silages by the in vitro gas production technique

2020 ◽  
Vol 41 (4) ◽  
pp. 1373
Author(s):  
André Luiz Pinto dos Santos ◽  
Cícero Carlos Ramos de Brito ◽  
Guilherme Rocha Moreira ◽  
Frank Gomes-Silva ◽  
Moacyr Cunha Filho ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Least Squares Method ◽  
Kinetic Curve ◽  
Information Criterion ◽  
Gas Production ◽  
Corn Silage ◽  
Coefficient Of Determination ◽  
Von Bertalanffy ◽  
Production Technique

This study aimed to propose a model called Two-compartment Logistic-von Bertalanffy (LVB) and to identify among the proposed and Two-compartment Logistic (TL) models the one that has the best goodness of fit to the kinetic curve of cumulative gas production (CGP) of sunflower and corn silages alone and combined using the in vitro semi-automated gas production technique. A random block split-plot experimental design was employed in which the inoculums were the blocks, the incubation times were the split-plots, and the experimental diets were: CS - corn silage, SS - sunflower silage (as single roughage), and their mixtures, i.e., 340SS (660 g kg-1 corn silage and 340 g kg-1 sunflower silage) and 660SS (340 g kg-1 corn silage and 660 g kg-1 sunflower silage). The parameters were estimated by the least squares method using the iterative Gauss-Newton process in the software R version 3.4.1. The criteria adopted were: adjusted coefficient of determination (R2adj.), residual mean squares (RMS), mean absolute deviation (MAD), Akaike information criterion (AIC), Bayesian information criterion (BIC), and relative efficiency (RE). The TL model had higher R2adj. values compared to LVB, however, such difference may be considered negligible. The LVB model had RE above one, which indicates it is superior to the TL model, in addition to the lowest RMS, MAD, AIC, and BIC values, The Two-compartment Logistic-von Bertalanffy model had the best fit to describe the CGP over time according to the methodology and conditions of the present study.

scholarly journals Method to generate growth and degrowth models obtained from combinations of existing models applied to agrarian sciences

2019 ◽  
Author(s):  
André Luiz Pinto dos Santos ◽  
Guilherme Rocha Moreira ◽  
Frank Gomes-Silva ◽  
Cícero Carlos Ramos de Brito ◽  
Maria Lindomárcia Leonardo da Costa ◽  
...  
Keyword(s):  
Least Squares Method ◽  
Kinetic Curve ◽  
Information Criterion ◽  
Compartment Model ◽  
Gas Production ◽  
Coefficient Of Determination ◽  
Von Bertalanffy ◽  
Absolute Deviation ◽  
Two Compartment Model

AbstractMathematical models that describe gas production are widely used to estimate the rumen degradation digestibility and kinetics. The present study presents a method to generate models by combining existing models and to propose the von Bertalanffy-Gompertz two-compartment model based on this method. The proposed model was compared with the logistic two-compartment one to indicate which best describes the kinetic curve of gas production through the semi-automatedin vitrotechnique from different pinto peanut cultivars. The data came from an experiment grown and harvested at the Far South Animal Sciences station (Essul) in Itabela, BA, Brazil and gas production was read at 2, 4, 6, 8, 10, 12, 14, 17, 20, 24, 28, 32, 48, 72, and 96 h after the start of thein vitrofermentation process. The parameters were estimated by the least squares method using the iterative Gauss-Newton process in the software R version 3.4.1. The best model to describe gas accumulation was based on the adjusted coefficient of determination, residual mean squares, mean absolute deviation, Akaike information criterion, and Bayesian information criterion. The von Bertalanffy-Gompertz two-compartment model had the best fit to describe the cumulative gas production over time according to the methodology and conditions of the present study.

scholarly journals Proposals of non-linear models to adjust in vitro gas production at different incubation times in cassava genotypes

2021 ◽  
Vol 43 ◽  
pp. e22
Author(s):  
André Luiz Pinto dos Santos ◽  
Frank Sinatra Gomes da Silva ◽  
Guilherme Rocha Moreira ◽  
Cícero Carlos Ramos de Brito ◽  
Maria Lindomárcia Leonardo da Costa ◽  
...  
Keyword(s):  
Linear Models ◽  
Least Squares Method ◽  
Logistic Models ◽  
Information Criterion ◽  
Gas Production ◽  
Coefficient Of Determination ◽  
Absolute Deviation ◽  
In Vitro Gas Production ◽  
The One

The present study aimed to propose new two-compartment models from the combination of the Gompertz, Logistic and Von Bertalanffy models and to identify between Gompertz and Logistic models, in their uni and two-compartiment versions, the one that presents the highest quality of fit to cumulative gas production curves of five cassava genotypes: Brasília, Engana Ladrão, Dourada, Gema de Ovo e Amansa Burro. The gas production readings were 2, 4, 6, 8, 10, 12, 14, 17, 20, 24, 28, 32, 48, 72, and 96 hours after the start of the in vitro fermentation process. The estimation of the parameters for the models was made by the least squares method through the Gauss-Newton iterative process. The selection of the best model to describe the gas accumulation was based on the adjusted coefficient of determination, residual mean squares, mean absolute deviation, Akaike information criterion and Bayesian information criterion. Among the adjusted models, the proposed models were the best to describe the accumulation of gases over time according to the methodology and conditions under which this study was developed.

scholarly journals Method to generate growth and degrowth models obtained from differential equations applied to agrarian sciences

2018 ◽  
Vol 39 (6) ◽  
pp. 2659 ◽  
Author(s):  
André Luiz Pinto dos Santos ◽  
Guilherme Rocha Moreira ◽  
Cicero Carlos Ramos de Brito ◽  
Frank Gomes-Silva ◽  
Maria Lindomárcia Leonardo da Costa ◽  
...  
Keyword(s):  
Differential Equations ◽  
Goodness Of Fit ◽  
Least Squares Method ◽  
Growth Curves ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Absolute Deviation ◽  
Marquardt Algorithm ◽  
Maturation Rate ◽  
Biological Interpretation

This study aims to propose a method to generate growth and degrowth models using differential equations as well as to present a model based on the method proposed, compare it with the classic linear mathematical models Logistic, Von Bertalanffy, Brody, Gompertz, and Richards, and identify the one that best represents the mean growth curve. To that end, data on Undefined Breed (UB) goats and Santa Inês sheep from the works of Cavalcante et al. (2013) and Sarmento et al. (2006a), respectively, were used. Goodness-of-fit was measured using residual mean squares (RMS), Akaike information criterion (AIC), Bayesian information criterion (BIC), mean absolute deviation (MAD), and adjusted coefficient of determination . The models’ parameters (?, weight at adulthood; ?, an integration constant; ?, shape parameter with no biological interpretation; k, maturation rate; and m, inflection point) were estimated by the least squares method using Levenberg-Marquardt algorithm on the software IBM SPSS Statistics 1.0. It was observed that the proposed model was superior to the others to study the growth curves of goats and sheep according to the methodology and conditions under which the present study was carried out.

scholarly journals In vitro ruminal fermentation kinetics of diets with crambe cake protein replacing soybean meal protein by gas production technique

2021 ◽  
Vol 42 (6) ◽  
pp. 3399-3414
Author(s):  
Angela Rocio Poveda-Parra ◽  
Odimári Pricila Prado-Calixto ◽  
Elzânia Sales Pereira ◽  
Fernando Luiz Massaro Junior ◽  
Larissa Nóbrega de Carvalho ◽  
...  
Keyword(s):  
Soybean Meal ◽  
Dry Matter ◽  
Gas Production ◽  
Corn Silage ◽  
Ruminal Fermentation ◽  
Production Technique ◽  
Meal Protein ◽  
Feedlot Lambs ◽  
Gas Volume

The objective of this study was to evaluate ingredients and diets containing increasing levels of crambe cake protein replacing soybean meal protein, with in vitro ruminal fermentation parameters using a gas production technique. Diets were formulated for feedlot lambs and contained different levels of crambe cake protein (0, 250, 500, 750, and 1000 g kg-1) replacing soybean meal protein. Corn silage was used as roughage. Carbohydrate digestion rates were estimated using the in vitro gas production technique and the cumulative gas production kinetics were analyzed using the bicompartmental logistic model. The parameters values of ruminal degradation kinetics were generated using the R statistical program with the Gauss-Newton algorithm and then subjected to analysis of variance and regression (when necessary) according to a completely randomized experimental design with five treatments and five replications. Upon carbohydrate fractionation of ingredients and experimental diets, it was observed that corn grain and corn silage presented the highest levels of total carbohydrates (TC), with values of 128.3 and 464.8 g kg-1 dry matter (DM) in fraction B2, respectively. Lower TC content was found for soybean meal and crambe cake (CC). There was a predominance of fractions A + B1 in the ingredients and experimental diets. The B2 fraction decreased in the diets with the inclusion of the CC protein, and CC presented the highest C fraction. Protein fractionation (g kg-1 DM and g kg-1 crude protein - CP), the ingredients and diets showed a higher proportion of fractions A and B1 + B2. In in vitro degradation, the diet without CC (0 g kg-1 DM) showed the highest final cumulative gas production (365.04 mL g-1 of incubated DM), while the CC presented the lowest volume (166.68 mL g-1 of incubated DM). The gas volume of non-fibrous carbohydrate fermentation and fibrous carbohydrate degradation rate exhibited a quadratic effect according increasing levels of CC (Pmax = 265.8 g kg-1 DM and Pmin = 376.3 g kg-1 DM, respectively). The lag time and final gas volume showed a decreasing linear effect with increasing levels of CC protein. The degradation rate of non-fibrous carbohydrates and the final volume of fibrous carbohydrates did not differ. Replacing soybean meal protein with CC protein at the level of 250 g kg-1 of dry matter in diets formulated for feedlot lambs leads to good profiles of ruminal fermentation kinetics with respect to the degradation of fibrous and non-fibrous carbohydrates.

scholarly journals Kinetics of In Vitro Gas Production and Fitting Mathematical Models of Corn Silage

Fermentation ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. 298
Author(s):  
Camila da Silva Zornitta ◽  
Luis Carlos Vinhas Ítavo ◽  
Camila Celeste Brandão Ferreira Ítavo ◽  
Geraldo Tadeu dos Santos ◽  
Alexandre Menezes Dias ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Gas Production ◽  
Feed Additives ◽  
Corn Silage ◽  
Feed Additive ◽  
Coefficient Of Determination ◽  
Production Data ◽  
In Vitro Gas Production ◽  
Kinetics Of

This study aimed at examining the effects of rumen inoculum of steers receiving different combinations of ionophore and probiotics in their diets on in vitro gas production of corn silage. The fitting of gas production was performed with five mathematical models and its kinetics was evaluated. Four crossbred steers (403.0 ± 75.5 kg body weight) with ruminal cannula were assigned to a 4 × 4 Latin square design. The additives used were Monensin sodium (Rumensin® 100, 3 g/day), Bacillus toyonensis (Micro-Cell Platinum® 109, 1 g/day) and Saccharomyces cerevisiae boulardii (ProTernative®20, 0.5 g/day). Additives were arranged into the following treatments, supplied daily into total mixed diet: (1) Monensin; (2) Monensin + B. toyonensis; (3) Monensin + S. boulardii; and (4) B. toyonensis + S. boulardii. The gas production data were fitted into the models of Gompertz, Groot, Ørskov, Brody, Richards, and Dual-pool Logistic. A perfect agreement between observed and predicted values in curves of accumulated in vitro gas production was observed in the Groot and Richards models, with higher coefficient of determination (R2 = 0.770 and 0.771, respectively), concordance correlation coefficient (CCC = 0.871 and 0.870, respectively), and root mean square error of prediction (RMSEP = 1.14 and 1.15, respectively). Evaluating the feed additives throughout the Groot model, the B. toyonensis + S. boulardii treatment presented higher VF (12.08 mL/100 mg of DM; p = 0.0022) than Monensin and Monensin + S. boulardii (9.16 and 9.22 mL/100 mg of DM, respectively). In addition, the fractional rate of gas production (k) was higher (p = 0.0193) in B. toyonensis + S. boulardii than in Monensin, not presenting a statistical difference (p > 0.05) from the other two treatments. Additionally, with the time of beginning to gas production, the lag time (λ), was greater (p < 0.001) with Monensin and Monensin + B. toyonensis than with Monensin + S. boulardii and B. toyonensis + S. boulardii. The combination of Monensin and probiotics (B. toyonensis + S. boulardii) resulted in better kinetics of degradation of corn silage, being that the Groot and Richards models had the best fit for estimates of the in vitro gas production data of corn silage tested with different feed additive combinations.

Estimation of fermentable energy by the automatic in vitro gas production technique for a selection of feedstuffs incubated alone and in combination

1998 ◽  
Vol 1998 ◽  
pp. 69-69
Author(s):  
S. Fakhri ◽  
A. R. Moss ◽  
D.I. Givens ◽  
E. Owen
Keyword(s):  
Organic Matter ◽  
Incubation Period ◽  
Gas Production ◽  
Production Technique ◽  
In Vitro Gas Production ◽  
Fe Content ◽  
The Individual ◽  
Gas Volume ◽  
Selection Of

The gas production (GP) technique has previously been used to estimate the gas volume (fermentable energy (FE)) of compound feed ingredients for ruminants (Newbold et al., 1996). It was shown that the FE content of feed mixtures was represented by the combination of the total gas from the incubation of the individual feeds. However this additivity might not be consistent throughout the incubation period. The objectives were to test whether 1. other GP parameters give better estimates of FE for simple mixtures and are they additive; 2. whether organic matter apparently degraded in the rumen (OMADR) explain differences in GP; and 3. to find out if there are any other better measures than OMADR for estimating FE.

scholarly journals The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar

2017 ◽  
Vol 48 (1) ◽  
Author(s):  
Thais Destefani Ribeiro ◽  
Taciana Villela Savian ◽  
Tales Jesus Fernandes ◽  
Joel Augusto Muniz
Keyword(s):  
Logistic Model ◽  
Least Squares Method ◽  
Nonlinear Models ◽  
Logistic Models ◽  
Information Criterion ◽  
Fruit Weight ◽  
Coefficient Of Determination ◽  
Pear Fruit ◽  
Asian Pear ◽  
Residual Correlations

ABSTRACT: The goal of this study was to elucidate the growth and development of the Asian pear fruit, on the grounds of length, diameter and fresh weight determined over time, using the non-linear Gompertz and Logistic models. The specifications of the models were assessed utilizing the R statistical software, via the least squares method and iterative Gauss-Newton process (DRAPER & SMITH, 2014). The residual standard deviation, adjusted coefficient of determination and the Akaike information criterion were used to compare the models. The residual correlations, observed in the data for length and diameter, were modeled using the second-order regression process to render the residuals independent. The logistic model was highly suitable in demonstrating the data, revealing the Asian pear fruit growth to be sigmoid in shape, showing remarkable development for three variables. It showed an average of up to 125 days for length and diameter and 140 days for fresh fruit weight, with values of 72mm length, 80mm diameter and 224g heavy fat.

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