Silagens de milho inoculadas microbiologicamente em diferentes estádios de maturidade: perdas fermentativas, composição bromatológica e digestibilidade in vitro

Objetivou-se com este estudo avaliar as perdas fermentativas, composição bromatológica e digestibilidade in vitro da matéria orgânica de silagens de milho produzidas em diferentes estádios de maturidade, inoculadas microbiologicamente. Aplicaram-se dois inoculantes comerciais nas silagens produzidas nos estádios SLL, 1/3 LL, 1/2 LL, 2/3 LL e CN, permanecendo ainda um tratamento sem inoculação (silagem controle), configurando um esquema fatorial 3x5. A inoculação com BAL resultou em menores perdas fermentativas (P=0,0348), ao passo que silagens produzidas com plantas mais secas também apresentam menores perdas de MS (P<0,01). A inoculação das silagens resultou em maiores concentrações de PB nas silagens produzidas nos estádios SLL, 2/3 LL e CN (P=0,0033). O uso do inoculante Maize All® resultou em menor concentração de FDN (P=0,0140) no estádio CN e acréscimo dos coeficientes de DIVMO quando as plantas foram colhidas com 2/3 LL e CN (P=0,0006). As perdas fermentativas diminuem devido à utilização dos inoculantes bacterianos e também em silagens produzidas com plantas mais secas. A aplicação de bactérias ácido-láticas (inoculante Maize All®) em silagens de milho produzidas com plantas em estádio de maturidade mais avançado melhora a composição química e digestibilidade in vitro.The aim of this study was to evaluate the fermentative losses, chemical composition and in vitro organic matter digestibility of corn silages produced in different maturity stages microbiologically inoculated. Two commercial inoculants were applied in the silages produced in stages SLL, 1/3 LL, 1/2 LL, 2/3 LL and CN, remaining an uninoculated treatment (control silage), illustrating a factorial scheme 3 x 5. The lactic acid bacteria (LAB) inoculation resulted in lower fermentative losses (P=0.0348), whereas silages produced with dried plants present lower DM losses (P<0.01). Because of inoculant application, there was higher concentrations of CP in the silages produced in stages SLL, 2/3 LL and CN (P=0.0033) and concentration lower of NDF (P=0.0140) in CN stage because of the Maize All® inoculant. This inoculant provided increase in the IVOMD coefficients when the plants were harvested with 2/3 LL and CN (P= 0.0006). Fermentative losses decreased because of the use of microbial inoculants, and this fact it is also observed in silages produced with dried plants. Application of lactic acid bacteria (Maize All® inoculant) in corn silages produced with plants harvested in more advanced stages of maturity improve the chemical composition and in vitro digestibility.Universidade Estadual Paulista (UNESP)Universidade José do Rosário Vellano (UNIFENAS)Escola Superior de Agricultura “Luiz de Queiroz” (ESALQ)Universidade Federal de Alfenas (UNIFAL)Universidade Estadual Paulista (UNESP

A meta-analysis of dry matter intake in Nellore and Zebu-crosses cattle

The study was carried out to develop and to evaluate new equations to predict dry matter intake (DMI) of Nellore and Zebu-crosses cattle using meta-analysis procedure. The data used to estimate the parameters were collected from independent performance experiments using growing and fattening Nellore and Zebu-crosses cattle, and they were compiled from 561 experimental units. Before proposing an equation to predict DMI, it was observed that the genetic group was a source of statisticaly significant variation. Therefore, equations to predict dry matter intake in the Zebu-Crosses and Nellore cattle were independently developed. The regression equations for Zebu-crosses cattle were: DMI = -2.6098 + 0.08844BW0.75 + 4.4672ADG - 1.3579ADG2 and DMI = -1.0094 + 0.01608BW + 4.4363ADG -1.2548ADG2. The regression equations for Nellore cattle were: DMI = -2.7878 + 0.08789BW0.75 + 5.0487ADG - 1.6835ADG2 and DMI = -1.3559 + 0.0159BW + 5.6397ADG - 1.8494ADG2. In order to evaluate fitted equations, it was utilized data from independent experiments published from 2005 to 2008 in the Revista Brasileira de Zootecnia. The equations (DMI) for Nellore overpredicted dry matter intake for estimates lower than 7 and higher than 10 kg·d-1. For Zebu-crosses cattle, dispersions of 3 kg d-1 were observed when extreme intakes were evaluated, however, when the equation included BW 0.75, the intercept did not differ from zero and the slope did not differ from 1. It is not possible to fit only one equation for preditcting DMI for beef cattle in tropical conditions, because there are differences between Zebu and Zebu-crosses. Fitted equations that include ADG and BW 0.75 should be used as an alternative method to predict dry matter intake of Zebu-crosses and Nellore beef cattle in tropical conditions.Objetivou-se desenvolver e avaliar novas equações para predição do consumo de matéria seca (CMS) em bovinos Nelore e mestiço, utilizando-se meta-análise. Os dados utilizados para estimar os parâmetros foram coletados em experimentos de desempenho independentes com bovinos Nelore e mestiço nas fases de recria e engorda, compilados a partir de 561 unidades experimentais. Antes de propor uma equação para predizer o CMS, observou-se que o grupo genético foi uma fonte de variação estatisticamente significativa. Neste sentido, equações para predizer o CMS em bovinos Nelores e mestiços foram desenvolvidas de forma independente. As equações de regressão para bovinos mestiços foram: CMS = -2,6098 + 0,08844PV0,75 + 4,4672GMD - 1,3579GMD2 e CMS = -1,0094 + 0,01608PV + 4,4363GMD -1.2548GMD2. As equações de regressão para bovinos Nelore foram: CMS = -2,7878 + 0,08789PV0,75 + 5,0487GMD - 1,6835GMD2 e CMS = -1,3559 +,0159PV + 5,6397GMD - 1,8494GMD2. Para avaliar as equações ajustadas, utilizaram-se dados de experimentos independentes publicados entre 2005 e 2008 na Revista Brasileira de Zootecnia. As equações (CMS) para Nelore superestimaram o CMS para estimativas menores que 7 e maiores que 10 kg d-1. Para bovinos mestiços, as dispersões de 3 kg·d-1 foram observadas quando pontos extremos foram avaliados, no entanto, quando a equação incluiu PV0,75, o intercepto não diferiu de zero e a inclinação não diferiu de 1. Não é possível ajustar uma única equação para predizer o CMS para bovinos de corte em condições tropicais, porque há diferenças entre Nelores e mestiços. Equações ajustadas que incluem GMD e PV0,75 devem ser usadas como um método alternativo para predizer o CMS em bovinos Nelores e mestiços em condições tropicais

Comparison of model predictions with measurements: A novel model-assessment method

AbstractFrequently, scientific findings are aggregated using mathematical models. Because models are simplifications of the complex reality, it is necessary to assess whether they capture the relevant features of reality for a given application. An ideal assessment method should (1) account for the stochastic nature of observations and model predictions, (2) set a correct null hypothesis, (3) treat model predictions and observations interchangeably, and (4) provide quantitatively interpretable statistics relative to precision and accuracy. Current assessment methods show deficiencies in regards to at least one of these characteristics. The method being proposed is based on linear structural relationships. Unlike ordinary least-squares, where the projections from the observations to the regression line are parallel to the y-axis and inverse regression where they are parallel to the x-axis, the generalized projection regression method (GePReM) projects the observations on a regression line in a direction determined by the ratio of the precision of the observations to that of the mathematical model predictions. Estimation and testing issues arise when the model is expressed in the common slope-intercept format. A polar transformation circumvents these issues. The parameter for the angle between the regression line and the horizontal axis has symmetrical confidence intervals and is equivariant to the exchange of X and Y. The null hypothesis for the equivalence test is that the model predictions are not equivalent to the observations. Information size is calculated as the simple ratio of the variance of the true values of the observations and of the computer model predictions divided by their respective precision. This information size plays a critical role in determining the number of observations required and the size of the zone of practical tolerance for the equivalence tests. The terminology used in the comparison of measurement methods is adapted to that of model assessment based on the equivalence tests on the relative precision, regression slope, and mean bias. Two examples are presented, with complete details of the calculations required for parameter estimation, equivalence tests, and confidence intervals. The assessment method proposed is an alternative to other assessment methods available. Further research is required to establish the relative benefits and performance of this proposed method compared with others available in the literature