Spectrometric techniques for elemental profile analysis associated with bitter pit in apples

Zuniga, Carlos Espinoza; Jarolmasjed, Sanaz; Sinha, Rajeev; Zhang, Chongyuan; Kalcsits, Lee; Dhingra, Amit; Sankaran, Sindhuja


Bitter pit and healthy 'Honeycrisp', 'Golden Delicious', and 'Granny Smith' apples were collected from three commercial orchards. Apples were scanned using Fourier transform infrared (FTIR) and X-ray fluorescence (XRF) spectrometers to associate the elemental profile with bitter pit occurrence in apples. The FTIR spectra were acquired from apple peel and flesh; while XRF spectra were acquired from the apple surface (peel). Destructive elemental analysis was also performed to estimate calcium, magnesium, and potassium concentrations in the apples. There were significant differences between healthy and bitter pit affected apples in calcium, magnesium, and potassium concentrations, in addition to magnesium/calcium and potassium/calcium ratios (5% level of significance). Peak analysis of FTIR spectra of prepared standards indicated the possible spectral regions associated with calcium content as 11501450 cm (1). Two different classification models (support vector machine, SVM and soft independent modeling of class analogy, SIMCA) were used to classify healthy and bitter pit affected apples using FTIR spectral signatures. FTIR spectra were able to predict bitter pit incidence in apples with higher classification accuracy using peel tissue (92%) than using flesh tissue with SVM model. The XRF technique could determine bitter pit incidence in apples and semi-quantitative analysis using XRF data was in agreement with the elemental analysis. FTIR and XRF spectrometric techniques are rapid methods that can be used for elemental profile analysis in apples. These techniques can serve as potential prediction tools for elemental profile analysis to detect bitter pit in apples. (C) 2017 Elsevier B.V. All rights reserved.

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Título según WOS: ID WOS:000396831800014 Not found in local WOS DB
Volumen: 128
Editorial: Elsevier
Fecha de publicación: 2017
Página de inicio: 121
Página final: 129


Notas: ISI