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Abstract:

The increasing consumption worldwide of tortilla chips make it relevant to design and optimize their industrial quality analysis. Surface, structural, and total oil content during frying of tortilla chips fried at 160, 175, and 190°C for different times were analyzed. The aim was to obtain a relationship between oil content and features from their digital images. The results showed a high linear correlation (R > 0.90) between oil content with image features at each frying temperature, indicating that trustable models can be developed, allowing the prediction of oil content of tortilla chips by using selected features extracted from their digital images, without the necessity of measuring them. Cross-validation technique demonstrated the repeatability of each model and their good performance (>90%). © 2014 Copyright Taylor and Francis Group, LLC.

Registro:

Documento: Artículo
Título:Oil content fraction in tortilla chips during frying and their prediction by image analysis using computer vision
Autor:Matiacevich, S.B.; Henríquez, O.C.; Mery, D.; Pedreschi, F.
Filiación:Departamento de Ciencia y Tecnología de Los Alimentos, Facultad Tecnológica, Universidad de Santiago de Chile, Santiago, Chile
CONICET - Departamento de Industrias, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Int. Güiraldes s/n, Ciudad Autónoma de Buenos Aires, Argentina
Departamento de Ciencia de la Computación, Pontificia Universidad Católica de Chile, Santiago, Chile
Departamento de Ingeniería Química y Bioprocesos, Pontificia Universidad Católica de Chile, Santiago, Chile
Palabras clave:Computer vision; Image features; Oil content; Oil fraction; Tortilla chips; Cross-validation technique; Frying temperature; Image features; Industrial quality; Linear correlation; Oil contents; Oil fractions; Tortilla chips; Computer vision; Food technology; Image processing
Año:2014
Volumen:17
Número:2
Página de inicio:261
Página de fin:272
DOI: http://dx.doi.org/10.1080/10942912.2011.631245
Título revista:International Journal of Food Properties
Título revista abreviado:Int. J. Food Prop.
ISSN:10942912
CODEN:IJFPF
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_10942912_v17_n2_p261_Matiacevich

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Citas:

---------- APA ----------
Matiacevich, S.B., Henríquez, O.C., Mery, D. & Pedreschi, F. (2014) . Oil content fraction in tortilla chips during frying and their prediction by image analysis using computer vision. International Journal of Food Properties, 17(2), 261-272.
http://dx.doi.org/10.1080/10942912.2011.631245
---------- CHICAGO ----------
Matiacevich, S.B., Henríquez, O.C., Mery, D., Pedreschi, F. "Oil content fraction in tortilla chips during frying and their prediction by image analysis using computer vision" . International Journal of Food Properties 17, no. 2 (2014) : 261-272.
http://dx.doi.org/10.1080/10942912.2011.631245
---------- MLA ----------
Matiacevich, S.B., Henríquez, O.C., Mery, D., Pedreschi, F. "Oil content fraction in tortilla chips during frying and their prediction by image analysis using computer vision" . International Journal of Food Properties, vol. 17, no. 2, 2014, pp. 261-272.
http://dx.doi.org/10.1080/10942912.2011.631245
---------- VANCOUVER ----------
Matiacevich, S.B., Henríquez, O.C., Mery, D., Pedreschi, F. Oil content fraction in tortilla chips during frying and their prediction by image analysis using computer vision. Int. J. Food Prop. 2014;17(2):261-272.
http://dx.doi.org/10.1080/10942912.2011.631245