Dispersive Raman Spectroscopy for the Nondestructive and Rapid Assessment of the Quality of Southern Italian Honey Types
作者： Anna Grazia Mignani , Leonardo Ciaccheri , Andrea Azelio Mencaglia , Rosa Di Sanzo , Sonia Carabetta
关键词: Electronic tongue 、 Food quality 、 Raman scattering 、 Raman spectroscopy 、 Near-infrared spectroscopy 、 Materials science 、 Honey samples 、 Mineralogy 、 Spectroscopy 、 Rapid assessment
摘要: Raman spectroscopy performed using optical fibers, with excitation at 1064 nm and a dispersive detection scheme, was utilized to measure selection of unifloral honeys produced in the Italian region Calabria. The honey samples had three different botanical origins: chestnut, citrus, acacia. A multivariate processing spectroscopic data enabled us distinguish their origin, build predictive models for quantifying important nutraceutic indicators, such as main sugars potassium. Furthermore, spectra chestnut were compared taste profile measured by an electronic tongue: good correlation bitter-savory obtained. This experiment indicates excellent potential modern analytical tool nondestructive rapid multi-component analysis food quality indicators.
osapublishing.org
harvard.edu参考文章(46)
A. G. Mignani, L. Ciaccheri, A. A. Mencaglia, R. Di Sanzo, S. Carabetta, M. T. Russo, Dispersive Raman spectroscopy excited at 1064nm to classify the botanic origin of honeys from Calabria and quantify the sugar profile Proceedings of SPIE. ,vol. 9486, ,(2015) , 10.1117/12.2179699
Janet Riedl, Susanne Esslinger, Carsten Fauhl-Hassek, Review of validation and reporting of non-targeted fingerprinting approaches for food authentication Analytica Chimica Acta. ,vol. 885, pp. 17- 32 ,(2015) , 10.1016/J.ACA.2015.06.003
Jessie Bong, Kerry M Loomes, Ralf C Schlothauer, Jonathan M Stephens, Fluorescence markers in some New Zealand honeys. Food Chemistry. ,vol. 192, pp. 1006- 1014 ,(2016) , 10.1016/J.FOODCHEM.2015.07.118
Priscila Missio da Silva, Cony Gauche, Luciano Valdemiro Gonzaga, Ana Carolina Oliveira Costa, Roseane Fett, Honey: Chemical composition, stability and authenticity. Food Chemistry. ,vol. 196, pp. 309- 323 ,(2016) , 10.1016/J.FOODCHEM.2015.09.051
Qin Ouyang, Quansheng Chen, Jiewen Zhao, Intelligent sensing sensory quality of Chinese rice wine using near infrared spectroscopy and nonlinear tools Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. ,vol. 154, pp. 42- 46 ,(2016) , 10.1016/J.SAA.2015.10.011
Livia Persano Oddo, Roberto Piro, Étienne Bruneau, Christine Guyot-Declerck, Tzeko Ivanov, Jirina Piskulová, Christian Flamini, Joel Lheritier, Monique Morlot, Harald Russmann, Werner Von der Ohe, Katharine Von der Ohe, Panagiota Gotsiou, Sophia Karabournioti, Panagiotis Kefalas, Maria Passaloglou-Katrali, Andreas Thrasyvoulou, Angeliki Tsigouri, Gian Luigi Marcazzan, Maria Lucia Piana, Maria Gioia Piazza, Anna Gloria Sabatini, Jacob Kerkvliet, Joana Godinho, Antonio Bentabol, Alberto Ortiz Valbuena, Stefan Bogdanov, Kaspar Ruoff, Main European unifloral honeys: descriptive sheets Apidologie. ,vol. 35, pp. S38- S81 ,(2004) , 10.1051/APIDO:2004049
Beril Özbalci, İsmail Hakkı Boyaci, Ali Topcu, Cem Kadılar, Uğur Tamer, Rapid analysis of sugars in honey by processing Raman spectrum using chemometric methods and artificial neural networks. Food Chemistry. ,vol. 136, pp. 1444- 1452 ,(2013) , 10.1016/J.FOODCHEM.2012.09.064
Kaspar Ruoff, Romdhane Karoui, Eric Dufour, Werner Luginbühl, Jacques-Olivier Bosset, Stefan Bogdanov, Renato Amadò, Authentication of the Botanical Origin of Honey by Front-Face Fluorescence Spectroscopy. A Preliminary Study Journal of Agricultural and Food Chemistry. ,vol. 53, pp. 1343- 1347 ,(2005) , 10.1021/JF048384Q
Jun-Hu Cheng, Da-Wen Sun, Data fusion and hyperspectral imaging in tandem with least squares-support vector machine for prediction of sensory quality index scores of fish fillet Lwt - Food Science and Technology. ,vol. 63, pp. 892- 898 ,(2015) , 10.1016/J.LWT.2015.04.039
Javier Moros, Salvador Garrigues, Miguel de la Guardia, Vibrational spectroscopy provides a green tool for multi-component analysis Trends in Analytical Chemistry. ,vol. 29, pp. 578- 591 ,(2010) , 10.1016/J.TRAC.2009.12.012