Statistical procedure for the composition of a sensory panel of blends of coffee with different qualities using the distribution of the extremes of the highest scores
Document title: Statistical procedure for the composition of a sensory panel of blends of coffee with different qualities using the distribution of the extremes of the highest scores
Journal: Acta scientiarum. Agronomy
Database: PERIÓDICA
System number: 000460087
ISSN: 1679-9275
Authors: 1
1
2
2
2
3
Institutions: 1Universidade Federal de Lavras, Departamento de Estatistica, Lavras, Minas Gerais. Brasil
2Universidade Federal de Lavras, Departamento de Engenharia, Lavras, Minas Gerais. Brasil
3Universidade Federal de Lavras, Departamento de Fisica, Lavras, Minas Gerais. Brasil
Year:
Volumen: 41
Country: Brasil
Language: Inglés
Document type: Artículo
Approach: Experimental, analítico
English abstract The identification and interpretation of discrepant observations in sensory experiments are difficult to implement since the external effects are associated with the individual consumer. This fact becomes more relevant in experiments that involve blends, which scrutinize coffees with different qualities, varieties, origins, and forms of processing and preparation. This work proposes a statistical procedure that facilitates the identification of outliers while also evaluating the discriminatory powers of a sensory panel concerning the differentiation of pure blends and coffees. For this purpose, four experiments were performed that tested coffees with different qualities and varieties. The results suggest that the statistical procedure proposed in this work was effective for discriminating the blends relative to the pure coffees and that the effects of the concentrations and types of processing did not interfere with the statistical evaluations
Disciplines: Agrociencias,
Ingeniería
Keyword: Plantas para uso industrial,
Equipo y maquinaria,
Café,
Calidad,
Mezclas,
Modelos biológicos,
Variedades
Keyword: Plants for industrial use,
Equipment and machinery,
Coffee,
Quality,
Mixtures,
Varieties,
Biological models
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