Predicción, usando imágenes hiperespectrales, del contenido de almidón en quesos frescos adulterados con harina de maíz

Descripción del Articulo

The aim of this study was to predict the cornmeal adulteration in cheese by hyperspectral imaging technique. Fresh cheese was prepared using milk with addition of cornmeal in concentrations of 0.0, 2.5, 7.5, 12.5, 17.5, 22.5 mg / ml of milk, obtaining final concentrations of starch 0,055, 2,656, 6,0...

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Detalles Bibliográficos
Autor: Barreto Alcántara, Abel Andree
Formato: tesis de grado
Fecha de Publicación:2015
Institución:Universidad Nacional de Trujillo
Repositorio:UNITRU-Tesis
Lenguaje:español
OAI Identifier:oai:dspace.unitru.edu.pe:20.500.14414/4434
Enlace del recurso:https://hdl.handle.net/20.500.14414/4434
Nivel de acceso:acceso abierto
Materia:Adulteración en queso, Plsr, Almidón, Imágenes hiperespectrales, Harina de maíz
Descripción
Sumario:The aim of this study was to predict the cornmeal adulteration in cheese by hyperspectral imaging technique. Fresh cheese was prepared using milk with addition of cornmeal in concentrations of 0.0, 2.5, 7.5, 12.5, 17.5, 22.5 mg / ml of milk, obtaining final concentrations of starch 0,055, 2,656, 6,007, 7,946, 9,884 and 12,705 mg / g cheese; subsequently hyperspectral imaging in the range of 0 to 1200 nm, distributed in 150 bands were acquired. In order to perform the pre-processing of the images, they were developed and implemented in Matlab v. 2010ª script functions. Modeling starch content was performed by the method of partial least squares regression (PLSR), with 14 latent variables a correlation coefficient of cross validation (r2) of 0.992 was obtained. With wavelengths of 24, 272, 296, 312, 376, 392, 424, 496, 728, 840, 936, 928, 968, 984 and 1000 nm was obtained reduced model with a correlation coefficient (r2) of 0.917.
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