Effect of different tumbling marination methods and time on the quality characteristics of prepared pork chops

AbstractThe combined effects of tumbling marination methods (Vacuum continuous tumbling marination, CT; Vacuum intermittent tumbling marination, IT) and effective tumbling time (4, 6, 8 and 10 h) on quality characteristics of prepared boneless pork chops were investigated. The results showed that regardless of tumbling time, CT method significantly increased the pH, product yield, cohesiveness, resilience, sensory tenderness and overall flavor (p<0.05) compared with IT method, and CT method also significantly decreased the pressing loss, cooking loss, shear force value (SFV), hardness and chewiness (p<0.05) compared with IT method. With the effective tumbling time increasing from 4 h to 10 h, the product yield and sensory attributes of prepared pork chops increased at first and then decreased, whereas the pressing loss, cooking loss, SFV, hardness and chewiness decreased at first and then increased. Additionally, an interaction between CT method and effective tumbling time was also observed. These results suggested that CT method of 8 h obtained the best quality characteristics of prepared pork chops, which should be adopted.

Titulação potenciométrica aplicada na determinação de ácidos graxos livres de óleos e gorduras comestíveis

Free fatty acids are a measure of evaluating fats and oils, submitted to abusive conditions, besides being a quality characteristic of edible vegetable oils. The official method of determination (AOCS Ca 5a-40, 2004) is based on titration, using phenolphthalein as an indicator. For crude and degummed oils, the titration end point is difficult to be observed due to the high level of pigments, resulting in dark solutions. In this case and others, such as self-life studies, in which sample quantities are limited, potentiometric titration may be a very good alternative.

Control charts for individual observations of a bivariate Poisson process

In this paper, three single-control charts are proposed to monitor individual observations of a bivariate Poisson process. The specified false-alarm risk, their control limits, and ARLs were determined to compare their performances for different types and sizes of shifts. In most of the cases, the single charts presented better performance rather than two separate control charts ( one for each quality characteristic). A numerical example illustrates the proposed control charts.

Economic design of an X chart for short-run production

The aim of this paper is to present an economical design of an X chart for a short-run production. The process mean starts equal to mu(0) (in-control, State I) and in a random time it shifts to mu(1) > mu(0) (out-of-control, State II). The monitoring procedure consists of inspecting a single item at every m produced ones. If the measurement of the quality characteristic does not meet the control limits, the process is stopped, adjusted, and additional (r - 1) items are inspected retrospectively. The probabilistic model was developed considering only shifts in the process mean. A direct search technique is applied to find the optimum parameters which minimizes the expected cost function. Numerical examples illustrate the proposed procedure. (C) 2009 Elsevier B.V. All rights reserved.

Controle estatístico de processo aplicado no monitoramento da absorção de água por carcaças de frango durante a etapa de pré-resfriamento

A absorção de água por carcaças de frango na etapa de pré-resfriamento da linha abate representa uma característica de qualidade importante relacionada ao rendimento do produto final. Uma forma de manter o padrão de qualidade de um produto é garantir que as etapas do processo sejam estáveis e replicáveis. Ao empregar o Controle Estatístico de Processo (CEP) é possível obter estabilidade e melhorias nos processos, por meio da redução da variabilidade. Neste contexto, o objetivo deste trabalho foi a aplicação de gráficos de controle, análise de correlação, estatística descritiva, testes de hipóteses e regressão linear múltipla na linha de abate de um abatedouro-frigorífico de aves para monitorar a variabilidade da absorção de água pelas carcaças de frango após a etapa de pré-resfriamento. Como resultado, verificou-se que o teor de absorção de água das carcaças de frango apresentou elevada variabilidade, sendo que 10% (8/80) das carcaças apresentaram absorção de água superior ao limite de 8% definido pela legislação brasileira. Do total de 16 variáveis de entrada analisadas, as mais impactantes no teor de absorção de água foram o “tempo de retenção da carcaça no pré-chiller” e o “tempo de espera da carcaça após a etapa de gotejamento”. Entretanto, o modelo de regressão obtido apresentou baixa correlação (R²=0,16) que foi associada à elevada variabilidade da variável-resposta. Os resultados da estatística descritiva demonstraram que as variáveis de entrada também apresentaram elevada variabilidade, com coeficiente de variação entre 7,95 e 63,5%. Verificou-se, pela análise dos gráficos de controle de medida individual e da amplitude móvel, que 15 das 16 variáveis de entrada se apresentaram fora de controle estatístico assim como a variável-resposta. Baseado no fluxograma e na descrição das etapas da linha de abate, previamente realizados, atribuiu-se à falta de padronização na condução das etapas e de procedimentos para o controle de qualidade das operações na linha de abate como fatores relevantes que poderiam estar associados à presença de causas especiais no processo. Concluiu-se que para reduzir a elevada variabilidade das variáveis e eliminar as causas especiais presentes são necessários ajustes operacionais para, dessa forma, obter um processo mais estável e mais uniforme garantindo o padrão de qualidade das carcaças de frango em relação ao teor de absorção de água.

Recommended Practice for Accepting New Concrete Pavement Surfaces for Tire/Pavement Noise, March 2, 2011

This practice provides guidance and example specification language intended for use by Owner-Agencies in development of specific contract language when requiring the evaluation of tire/pavement noise for new concrete pavement surfaces. The overall sound intensity level is designated as the quality characteristic used for pay adjustment.

Titulação potenciométrica aplicada na determinação de ácidos graxos livres de óleos e gorduras comestíveis

Free fatty acids are a measure of evaluating fats and oils, submitted to abusive conditions, besides being a quality characteristic of edible vegetable oils. The official method of determination (AOCS Ca 5a-40, 2004) is based on titration, using phenolphthalein as an indicator. For crude and degummed oils, the titration end point is difficult to be observed due to the high level of pigments, resulting in dark solutions. In this case and others, such as self-life studies, in which sample quantities are limited, potentiometric titration may be a very good alternative.

Effect of measurement error and autocorrelation on the (X)over-bar chart

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Control charts for individual observations of a bivariate Poisson process

In this paper, three single-control charts are proposed to monitor individual observations of a bivariate Poisson process. The specified false-alarm risk, their control limits, and ARLs were determined to compare their performances for different types and sizes of shifts. In most of the cases, the single charts presented better performance rather than two separate control charts ( one for each quality characteristic). A numerical example illustrates the proposed control charts.

Economic design of (X)over-bar and R charts under Weibull shock models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Joint conomic design of (x)over-bar and R charts under Weibull shock models

This paper deals with the joint economic design of (x) over bar and R charts when the occurrence times of assignable causes follow Weibull distributions with increasing failure rates. The variable quality characteristic is assumed to be normally distributed and the process is subject to two independent assignable causes (such as tool wear-out, overheating, or vibration). One cause changes the process mean and the other changes the process variance. However, the occurrence of one kind of assignable cause does not preclude the occurrence of the other. A cost model is developed and a non-uniform sampling interval scheme is adopted. A two-step search procedure is employed to determine the optimum design parameters. Finally, a sensitivity analysis of the model is conducted, and the cost savings associated with the use of non-uniform sampling intervals instead of constant sampling intervals are evaluated.

Joint (X)over-bar and R charts with two-stage samplings

When joint (X) over bar and R charts are in use, samples of fixed size are regularly taken from the process, and their means and ranges are plotted on the (X) over bar and R charts, respectively. In this article, joint (X) over bar and R charts have been used for monitoring continuous production processes. The sampling is performed, in two stages. During the first stage, one item of the sample is inspected and, depending on the result, the sampling is interrupted if the process is found to be in control; otherwise, it goes on to the second stage, where the remaining sample items are inspected. The two-stage sampling procedure speeds up the detection of process disturbances. The proposed joint (X) over bar and R charts are easier to administer and are more efficient than the joint (X) over bar and R charts with variable sample size where the quality characteristic of interest can be evaluated either by attribute or variable. Copyright (C) 2004 John Wiley Sons, Ltd.

Adaptive control charts: A Markovian approach for processes subject to independent disturbances

Recent studies have shown that adaptive X control charts are quicker than traditional X charts in detecting small to moderate shifts in a process. In this article, we propose a joint statistical design of adaptive X and R charts having all design parameters varying adaptively. The process is subjected to two independent assignable causes. One cause changes the process mean and the other changes the process variance. However, the occurrence of one kind of assignable cause does not preclude the occurrence of the other. It is assumed that the quality characteristic is normally distributed and the time that the process remains in control has exponential distribution. Performance measures of these adaptive control charts are obtained through a Markov chain approach. (c) 2005 Elsevier B.V. All rights reserved.

Joint conomic design of x̄ and R charts under Weibull shock models

This paper deals with the joint economic design of x̄ and R charts when the occurrence times of assignable causes follow Weibull distributions with increasing failure rates. The variable quality characteristic is assumed to be normally distributed and the process is subject to two independent assignable causes (such as tool wear-out, overheating, or vibration). One cause changes the process mean and the other changes the process variance. However, the occurrence of one kind of assignable cause does not preclude the occurrence of the other. A cost model is developed and a non-uniform sampling interval scheme is adopted. A two-step search procedure is employed to determine the optimum design parameters. Finally, a sensitivity analysis of the model is conducted, and the cost savings associated with the use of non-uniform sampling intervals instead of constant sampling intervals are evaluated.

The no-central chi-square chart with two-stage samplings

Throughout this article, it is assumed that the no-central chi-square chart with two stage samplings (TSS Chisquare chart) is employed to monitor a process where the observations from the quality characteristic of interest X are independent and identically normally distributed with mean μ and variance σ2. The process is considered to start with the mean and the variance on target (μ = μ0; σ2 = σ0 2), but at some random time in the future an assignable cause shifts the mean from μ0 to μ1 = μ0 ± δσ0, δ >0 and/or increases the variance from σ0 2 to σ1 2 = γ2σ0 2, γ > 1. Before the assignable cause occurrence, the process is considered to be in a state of statistical control (defined by the in-control state). Similar to the Shewhart charts, samples of size n 0+ 1 are taken from the process at regular time intervals. The samplings are performed in two stages. At the first stage, the first item of the i-th sample is inspected. If its X value, say Xil, is close to the target value (|Xil-μ0|< w0σ 0, w0>0), then the sampling is interrupted. Otherwise, at the second stage, the remaining n0 items are inspected and the following statistic is computed. Wt = Σj=2n 0+1(Xij - μ0 + ξiσ 0)2 i = 1,2 Let d be a positive constant then ξ, =d if Xil > 0 ; otherwise ξi =-d. A signal is given at sample i if |Xil-μ0| > w0σ 0 and W1 > knia:tl, where kChi is the factor used in determining the upper control limit for the non-central chi-square chart. If devices such as go and no-go gauges can be considered, then measurements are not required except when the sampling goes to the second stage. Let P be the probability of deciding that the process is in control and P 1, i=1,2, be the probability of deciding that the process is in control at stage / of the sampling procedure. Thus P = P1 + P 2 - P1P2, P1 = Pr[μ0 - w0σ0 ≤ X ≤ μ0+ w 0σ0] P2=Pr[W ≤ kChi σ0 2], (3) During the in-control period, W / σ0 2 is distributed as a non-central chi-square distribution with n0 degrees of freedom and a non-centrality parameter λ0 = n0d2, i.e. W / σ0 2 - xn0 22 (λ0) During the out-of-control period, W / σ1 2 is distributed as a non-central chi-square distribution with n0 degrees of freedom and a non-centrality parameter λ1 = n0(δ + ξ)2 / γ2 The effectiveness of a control chart in detecting a process change can be measured by the average run length (ARL), which is the speed with which a control chart detects process shifts. The ARL for the proposed chart is easily determined because in this case, the number of samples before a signal is a geometrically distributed random variable with parameter 1-P, that is, ARL = I /(1-P). It is shown that the performance of the proposed chart is better than the joint X̄ and R charts, Furthermore, if the TSS Chi-square chart is used for monitoring diameters, volumes, weights, etc., then appropriate devices, such as go-no-go gauges can be used to decide if the sampling should go to the second stage or not. When the process is stable, and the joint X̄ and R charts are in use, the monitoring becomes monotonous because rarely an X̄ or R value fall outside the control limits. The natural consequence is the user to pay less and less attention to the steps required to obtain the X̄ and R value. In some cases, this lack of attention can result in serious mistakes. The TSS Chi-square chart has the advantage that most of the samplings are interrupted, consequently, most of the time the user will be working with attributes. Our experience shows that the inspection of one item by attribute is much less monotonous than measuring four or five items at each sampling.