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Title

Firmness prediction in Prunus persica ‘Calrico’ peaches by Visible/short wave near infrared spectroscopy and acoustic measurements using optimized linear and non-linear chemometric models (Article in press)

AuthorsLafuente Rosales, Victoria ; Herrera Maldonado, Luis Javier; Pérez, María del Mar; Val Falcón, Jesús ; Negueruela Suberviola, Ángel Ignacio
KeywordsNIR
Acoustic system
Firmness
Peaches
Issue Date2015
PublisherSociety of Chemical Industry
Wiley-Blackwell
CitationLafuente V, Herrera LJ, Pérez MD, Val J, Negueruela I. Firmness prediction in Prunus persica ‘Calrico’ peaches by Visible/short wave near infrared spectroscopy and acoustic measurements using optimized linear and non-linear chemometric models (Article in press). Journal of the Science of Food and Agriculture (Available online 15 September 2014) (DOI: 10.1002/jsfa.6916)
AbstractIn this work, near infrared spectroscopy (NIR) and an acoustic measure (AWETA) (two non-destructive methods) were applied in Prunus persica fruit ‘Calrico’ (n=260) to predict Magness-Taylor (MT) firmness. Separate and combined use of these measures was evaluated and compared using PLS and LS-SVM regression methods. Also, a Mutual Information (MI)-based variable selection method, seeking to find the most significant variables to produce optimal accuracy of the regression models, was applied to a joint set of variables (NIR wavelengths and AWETA measure). The newly proposed combined NIR-AWETA model gave good values of the determination coefficient (R2) for PLS and LS-SVM methods (0.77 and 0.78, respectively), improving the reliability of MT firmness prediction in comparison with separate NIR and AWETA predictions. The three variables selected by the variable selection method (AWETA measure plus NIR wavelengths 675 and 697 nm) achieved R2 values 0.76 and 0.77, PLS and LS-SVM. These results indicated that the proposed MI-based variable selection algorithm was a powerful tool for the selection of the most relevant variables.
Description16 p., 2 fig., 2 tab.
Publisher version (URL)http://dx.doi.org/10.1002/jsfa.6916
URIhttp://hdl.handle.net/10261/102347
DOI10.1002/jsfa.6916
ISSN0022-5142
E-ISSN1097-0010
Appears in Collections:(EEAD) Artículos
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