Prediction of destructive properties using descriptive analysis of nd measurements

Herrero Langreo, Ana and Fernandez Ahumada, Elvira and Roger, Jean-Michel and Palagos, B. and Lleó García, Lourdes (2010). Prediction of destructive properties using descriptive analysis of nd measurements. In: "7º Colloquium Chemiometricum Mediterraneun (CCM VII 2010)", 21/06/2010 - 24/06/2010, Granada, España.

Description

Title: Prediction of destructive properties using descriptive analysis of nd measurements
Author/s:
  • Herrero Langreo, Ana
  • Fernandez Ahumada, Elvira
  • Roger, Jean-Michel
  • Palagos, B.
  • Lleó García, Lourdes
Item Type: Presentation at Congress or Conference (Article)
Event Title: 7º Colloquium Chemiometricum Mediterraneun (CCM VII 2010)
Event Dates: 21/06/2010 - 24/06/2010
Event Location: Granada, España
Title of Book: Proceedings of 7º Colloquium Chemiometricum Mediterraneun (CCM VII 2010)
Date: 2010
Subjects:
Freetext Keywords: Exploratory analysis, modelling, non destructive, multivariate, post-harvest, fruit handling
Faculty: E.U.I.T. Agrícolas (UPM)
Department: Ciencia y Tecnología Aplicadas a la Ingeniería Técnica Agrícola [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Three groups of measurements related to peach maturity were acquired through destructive (D) mechanical tests (Magness Taylor Firmness, MTF), mechanical non destructive (ND) tests, and ND optical spectroscopy (Optical indexes). The relationship between these groups of variables was studied in order to estimate D mechanical measurements (MTF, with higher instrumental and sampling variability, time consuming, generally used as a reference for the assessment of peach handling), from ND measurements (quick, applicable on line, dealing better with the high variability found in fruit products). Multivariate exploratory analysis was used to extract the structure of the data. The information about the data structure of ND measurements, the relationship of MTF with the space defined by ND variables, and the expert knowledge regarding to the dataset was then used for modelling MTF (R 2 =0.72 and standard error on validation 5.73 N)

More information

Item ID: 9202
DC Identifier: http://oa.upm.es/9202/
OAI Identifier: oai:oa.upm.es:9202
Official URL: http://www.ugr.es/~ecugr/es/welcome.html
Deposited by: Memoria Investigacion
Deposited on: 19 Oct 2011 08:54
Last Modified: 20 Apr 2016 17:42
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