Impact of measurement errors on alternative predictors of lean meat proportion of lamb carcasses

The objectives of this study were to evaluate the impact of measurement errors on alternative predictors of lean meat proportion (LMP) of lamb carcasses. Ninety eight lambs (72 males and 26 females) of Churra Galega Bragançana breed were slaughtered, and carcasses were weighed (HCW) approximately 30 min after exsanguination. During carcasses quartering a caliper was used to perform tissue depth measurements, over the maximum depth of longissimus muscle (LM), between the 12th and 13th ribs (C12 ), and between the 3rd and 4th lumbar vertebrae (C3). The C12 and C3 measurements were contaminated with simulated measurement errors, and three distributions for random error were simulated: 1} random error with mean 0 and variance of 0.25 mm (E ~ N(0,0.25mm), 2) random error with mean 0 and variance of 0.50 mm (E ~ N(0,0.50mm)), and 3) random error with mean 0 and variance of 0.75 mm (E ~ N(0,0.75mm)). Simple and multiple linear regression models were developed using as independent variables the measured (original) and the biased C12 and C3 measurements as predictors of LMP. The coefficient of determination and the residual standard deviation were computed. This work shows that measurement errors of subcutaneous fat can have a high impact on the stability of models to predict the carcasses LMP. The subcutaneous fat measurements of higher magnitude are less sensitive to measurement errors, and give rise to more stable prediction models

Prediction of lean meat proportion of lamb carcasses

The objectives of this study were to identify a reduced pertinent set of variables from an original set of 18 carcass measurements and the development of linear regression models to predict lean meat yield of lamb carcasses. Forty- six male lambs, 26 of Churro Galego Bragançano Portuguese local breed and 20 of Suffolk breed were used. Lambs were slaughtered and carcasses were weighed approximately 30 min after slaughter in order to obtain hot carcass weight (HCW). After cooling at 4°C for 24-h a set of 17 carcass measurements were recorded. The data interrelationships were analysed following the common factor analysis procedure. HCW was lowly correlated with leg length (r = 0.17) and moderately correlated with measurements that characterize carcass lengths and perimeters (r = -0.39 to 0.56). Four common factors (factor I = HCW; factor II = breast bone thickness; factor III = subcutaneous fat thickness; and factor IV = carcass conformation) were retained, accounting for 81.9% of the variation in the 18 original variables. This study shows that common factors analysis can be used to condense the information given by large sets of variables, by selecting a reduced number of variables, which avoids collinearity problems and simplifies the development of carcass composition estimation models

Tissue thickness measurements for objective classification of lamb carcasses based on lean meat percentage

The objectives of this study were to analyze the interrelationships among hot carcass weight (HCW), carcass dimension, and tissues thickness and area measurements, and to develop models to predict lean meat percentage of lamb carcasses. One hundred and twenty-five lambs, 83 males and 42 females, of Churra Galega Bragançana Portuguese local breed were slaughtered, and carcasses were weighed (HCW) approximately 30 min after exsanguination. After cooling at 4 C for 24- h a set of seventeen carcass measurements were recorded, and left side of carcasses was dissected and lean meat percentage (LMP) was calculated. Data interrelationships were analyzed following the common factor analysis procedure, and models to predict LMP were developed by regression procedures. All variables were highly and positively correlated with HCW (r > 0.46), being especially high in the carcass dimensions measurements (r > 0.75). Three common factors (factor I = carcass weight; factor II = subcutaneous fat thickness; factor III = breast bone tissues thickness) were retained, and accounted for 83.5% of the variation in the original variables. The best single predictor was C12 fat measurement, and accounted for 66.2% of the LMP variation with a sep of 2.39%. This study shows that prediction of LMP of lamb carcasses can be based on one single fat measurement (C12), If a large set variables is available, their orthogonal CF can be used as predictors avoiding collinearity, and given rise to more stable prediction models

Tourism and terrorism: protecting paradise

We tend to associate tourism with longed-for breaks, overseas adventures and the interruption of our daily routine by a couple of days’ rest and relaxation in ‘paradise’. Yet recent terrorist attacks at tourist destinations, from the beaches of Tunisia to the shrines of Bangkok and the city centre of Paris to hotels in Mali, are having a negative impact on the once widespread belief that vacations were not only an escape from the trials and tribulations of daily life but also an excursion from the political woes we witness at home on the news

The Use of Seemingly Unrelated Regression (SUR) to Predict the Carcass Composition of Lambs

The aim of this study was to develop and evaluate models for predicting the carcass composition of lambs. Forty male lambs of two different breeds were included in our analysis. The lambs were slaughtered and their hot carcass weight was obtained. After cooling for 24 hours, the subcutaneous fat thickness was measured between the 12th and 13th rib and the total breast bone tissue thickness was taken in the middle of the second sternebrae. The left side of all carcasses was dissected into five components and the proportions of lean meat, subcutaneous fat, intermuscular fat, kidney and knob channel fat, and bone plus remainder were otained. Our models for carcass composition were fitted using the SUR estimator which is novel in this area. The results were compared to OLS estimates and evaluated by several statistical measures. As the models are intended to predict carcass composition, we particularly focussed on the PRESS statistic, because it assesses the precision of the model in predicting carcass composition. Our results showed that the SUR estimator performed better in predicting LMP and IFP than the OLS estimator. Although objective carcass classification systems could be improved by using the SUR estimator, it has never been used before for predicting carcass composition.Carcass, Quality, Ordinary least squares, Seemingly unrelated regression

Tourism in Portugal at the beginning of the Second World War – an innocent oasis in Europe, or the achievements of disguised propaganda

This article discusses the importance of tourism-based representations as an effective vehicle of hidden propaganda for strengthening and validating the Estado Novo dictatorship in Portugal, particularly within the context of the outbreak of the Second World War. As more and more areas fell under the auspices of the official bu reau of propaganda, it proves worthwhile to acknowledge how tourism narratives became relevant tools for disseminating the features of the new politial regime. In fact, these seemed particularly effective devices for displaying the new “Nation” both to nationals and to foreign guests. The former group were to recognize the uniqueness and singularity of Portugal through the display of allegedly national icons, while the latter goup was invited to recognize and advocate the neutralty confirmed by Antonio de Oliveira Salazar, the ruling president, in September 1939

Predicting the carcass composition of lambs by a simultaneous equations model

The objective of this study was to develop models to predict lamb carcass composition by simultaneous equations model (SEM), and to compare t he efficiency of the ordinary least squares (OLS), weight least squares (WLS), and seemingly unrelated regressions (SUR) estimators. Forty male lambs, 22 of Churro Galego Bragançano Portuguese local breed and 18 of Suffolk breed were used. Lambs were slaughtered and carcasses were weighed approximately 30 min after slaughter in order to obtain hot carcass weight (HCW). After cooling at 4°C for 24-h, the subcutaneous fat thickness measurement (C3) was taken between the 12th and 13th ribs. The left side of al l carcasses was dissected into muscle, subcutaneous fat, intermuscular fat, bone, and remainder (major blood vessels, ligaments, tendons, and thick connective tissue sheets associated with muscles). The carcasses lean meat percentage (LMP), total fat percentage (FP), and bone percentage (BP) were calculated. A SEM model was fited by OLS, WLS and SUR estimators. Models fitting quality was evaluated by the coefficient of determination, the root mean square error, and Log-likelihood statistic. This study shows that SUR estimates are consistently better than the OLS and WLS estimates for modeling the carcass composition of lambs, and this trend was noticeably visible for the LMP

Subcutaneous fat depth magnitude influences its measurement errors: a simulation study

The objectives of this study were to evaluate the impact of proportional and absolute errors on subcutaneous fat depth (SFD) measurements, and the effects on the stability of models to predict the lean meat proportion (LMP) of lamb carcasses. Ninety eight lambs (72 males and 26 females) of Churra Galega Bragançana breed were slaughtered, and carcasses were weighed (HCW) approximately 30 min after exsanguination. During carcasses quartering a caliper was used to perform SFD measurements, over the maximum depth of longissimus muscle (LM), between the 12th and 13th ribs (C12), and between the 3rd and 4th lumbar vertebrae (C3). A computer program was written in order to simulate measurement errors for C12 and C3 measurements. Two scenarios were simulated, and C12 and C3 were contaminated with: 1) proportional errors of 5, 10, and 15%, and 2) absolute errors of 0.25, 0.50, and 0.75 mm. Simple and multiple linear models to predict LMP were developed using as independent variables: 1) the measured (original) SFD measurements, and 2) the biased SFD measurements. The coefficient of determination ( ) and the residual SD (RSD) were computed. Our study demonstrates that measurement errors can have a high impact on the SFD measurements, and on models stability. We conclude that SFD measurements of higher magnitude should be preferred as predictors of LMP since they are less influenced by measurement errors, thus contributing to more stable regression models

Utilização do software de geometria dinâmica GeoGebra por alunos do 3º Ciclo do Ensino Básico

As TIC estão em todos os ramos de atividade e em particular na educação. Tendo em conta as potencialidades das TIC, desenvolveu-se uma investigação no contexto de ensino formal da matemática. O principal objetivo da investigação foi estudar as perceções de alunos, do 3.º Ciclo do Ensino Básico, sobre a estratégia de ensino e aprendizagem suportada pela utilização do software de geometria dinâmica GeoGebra. O trabalho experimental decorreu nos meses de janeiro e fevereiro de 2012, com uma turma do 8.º ano de escolaridade de uma escola pública do Norte de Portugal. A investigação é de natureza mista, qualitativa e quantitativa. O instrumento de recolha de dados foi o questionário. Dos resultados destaca-se que os alunos reconhecem que com a utilização do Geogebra ficam mais motivados, melhoram o seu desempenho e o interesse pela disciplina, considerando que as aulas são mais dinâmicas, menos monótonas e as tarefas realizam-se mais facilmente