2000
DOI: 10.1016/s0309-1740(00)00050-4
|View full text |Cite
|
Sign up to set email alerts
|

The use of principal component analysis (PCA) to characterize beef

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

14
70
3
3

Year Published

2006
2006
2022
2022

Publication Types

Select...
7
1
1

Relationship

0
9

Authors

Journals

citations
Cited by 147 publications
(90 citation statements)
references
References 6 publications
14
70
3
3
Order By: Relevance
“…The results indicate the negative correlation between overall liking and several attributes such as fibrousness, fat odour, rancid flavour, acid flavour or metallic flavour. Tenderness was positively related with juiciness, beef flavour and overall liking and placed on the positive side of the axis, coincidentally with other findings (Destefanis et al, 2000) where the eating quality characteristics are positively correlated among them and placed on the positive side of the plot. The samples from animals that were fed with linseed were placed on the positive side of the axis and the rest of the treatments were on the negative side of the axis.…”
Section: Resultssupporting
confidence: 83%
See 1 more Smart Citation
“…The results indicate the negative correlation between overall liking and several attributes such as fibrousness, fat odour, rancid flavour, acid flavour or metallic flavour. Tenderness was positively related with juiciness, beef flavour and overall liking and placed on the positive side of the axis, coincidentally with other findings (Destefanis et al, 2000) where the eating quality characteristics are positively correlated among them and placed on the positive side of the plot. The samples from animals that were fed with linseed were placed on the positive side of the axis and the rest of the treatments were on the negative side of the axis.…”
Section: Resultssupporting
confidence: 83%
“…When the interaction between effects was significant (P ⩽ 0.05), means were separated using the Duncan's multiple range tests with a significance of P ⩽ 0.05. To describe the relationships between meat sensory quality traits, a Principal Component Analysis, which makes possible to identify the most important directions of variability in a multivariate data matrix and to present the results in a graphical plot (Destefanis et al, 2000), was performed using SAS (8.3).…”
Section: Instrumental Analysismentioning
confidence: 99%
“…The first four PCs explained 72.04% of the total variation, which is in accordance with Destefanis et al (2000) and Cañeque et al (2004).…”
Section: Pcasupporting
confidence: 64%
“…Resultado semelhante foi encontrado por Destefanis et al (2000), que, trabalhando com componentes principais nas aná-lises químicas, físicas e sensoriais da carne de bovinos jovens, verificaram que os três primeiros componentes explicaram aproximadamente 63% da variação total. Esses autores concluíram que a técnica de componentes princiTabela 1 -Número de observações, médias e desvios-padrão das características de qualidade da carne Jolliffe (1972Jolliffe ( , 1973, visto que foram quatro os componentes com autovalores menores que 0,7.…”
Section: Resultsunclassified