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Original Articles

An original approach for the quantitative characterization of saffron aroma strength using electronic nose

, , &
Pages S673-S683 | Received 21 Nov 2016, Accepted 11 Mar 2017, Published online: 10 Jul 2017

References

  • Maggi, L.; Carmona, M.; Zalacain, A.; Kanakis, C.; Anastasaki, E.; Tarantilis, P.A.; Polissiou, M.G.; Alonso, G.L. Changes in Saffron Volatile Profile according to Its Storage Time. Food Research International 2010, 43(5), 1329–1334.
  • ISO 3632-2. Saffron (Crocus sativus L.): Test Methods (2003 Revised 2011); International Standards Organization: Switzerland: Geneva, 2011.
  • Roedel, W.; Petrzika, M. Analysis of the Volatile Components of Saffron. Journal High Researcher Chromatographic 1991, 14, 771–774.
  • Tarantilis, P.A.; Polissiou, M.G. Isolation and Identification of the Aroma Components from Saffron (Crocus sativus). Journal Agricultural Food Chemical 1997, 45, 459–462.
  • Maggi, L.; Carmona, M.; Del Campo, C.P.; Kanakis, C.D.; Anastasaki, E.; Tarantilis, P.A.; et al. Worldwide Market Screening of Saffron Volatile Composition. Journal of the Science of Food and Agriculture 2009, 89, 1950–1954.
  • Kiani, S.; Minaei, S.; Ghasemi-Varnamkhasti, M. Application of Electronic Nose Systems for Assessing Quality of Medicinal and Aromatic Plant Products: A Review. Journal of Applied Research on Medicinal and Aromatic Plants 2016a, 3(1), 1–9.
  • Banerjee (Roy), R.; Chattopadhyay, P.; Tudu, B.; Bhattacharyya, N.; Bandyopadhyay, R. Artificial flavor Perception of Black Tea Using Fusion of Electronic Nose and Tongue Response: A Bayesian Statistical Approach. Journal of Food Engineering 2014, 142, 87–93.
  • Yang, S.; Xie, S.; Xu, M.; Zhang, C.; Wu, N.; Yang, J.; Zhang, L.; Zhang, D.; Jiang, Y.; Wu, C. A Novel Method for Rapid Discrimination of Bulbus of Fritillaria by Using Electronic Nose and Electronic Tongue Technology. Analytical Methods 2015, 7(3), 943–952.
  • Xu, M.; Yang, S.L.; Peng, W.; Liu, Y.J.; Xie, D.S.; Li, X.Y.; Wu, C.J. A Novel Method for the Discrimination of Semen Arecae and Its Processed Products by Using Computer Vision, Electronic Nose and Electronic Tongue; Evidence-Based Complementary and Alternative Medicine, 2015(2015), 1–10. http://www.hindawi.com/journals/ecam/aip/753942/
  • Chen, Q.; Zhang, Z.; Pan, W.; Ouyang, Q.; Li, H.; Urmila, K.; Zhao, J. Recent Developments of Green Analytical Techniques in Analysis of Tea’s Quality and Nutrition. Trends in Food Science & Technology 2015, 43, 63–82.
  • Kiani, S.; Minaei, S.; Ghasemi-Varnamkhasti, M. A Portable Electronic Nose as an Expert System for Aroma-Based Classification of Saffron. Chemometrics and Intelligent Laboratory Systems 2016b, 156(15), 148–156.
  • Ghasemi-Varnamkhasti, M.; Mohtasebi, S.S.; Siadat, M.; Ahmadi, H.; Razavi, S.H. From Simple Classification Methods to Machine Learning for the Binary Discrimination of Beers Using Electronic Nose Data. Engineering in Agriculture, Environment and Food 2015, 8(1), 44–51.
  • Dutta, R.; Hines, E.L.; Gardner, J.W.; Kashwan, K.R.; Bhuyan, A. Tea Quality Prediction Using a Tin Oxide-Based Electronic Nose: An Artificial Intelligence Approach. Sensors and Actuators B: Chemical 2003, 94, 228–237.
  • Carmona, M.; Martínez, J.; Zalacain, A.; Rodríguez-Méndez, M.L.; De Saja, J.A.; Alonso, G.L. Analysis of Saffron Volatile Fraction by TD-GC-MS and E-Nose. European Food Research and Technology 2005, 223, 96–101.
  • Sanaeifar, A.; Mohtasebi, S.S.; Ghasemi-Varnamkhasti, M.; Ahmadi, H. Application of MOS Based Electronic Nose for the Prediction of Banana Quality Properties. Measurement 2016, 82, 105–114.
  • Li, S.; Li, X.; Wang, G.; Nie, L.; Yang, Y.; Wu, H.; Wei, F.; Zhang, J.; Tian, J.; Lin, R. Rapid Discrimination of Chinese Red Ginseng and Korean Ginseng Using an Electronic Nose Coupled with Chemometrics. Journal of Pharmaceutical and Biomedical Analysis 2012, 70, 605–608.
  • Shafiee, S.; Minaei, S.; Moghaddam-Charkari, N.; Barzegar, M. Honey Characterization Using Computer Vision System and Artificial Neural Networks. Food Chemistry 2014, 159, 143–150.
  • Scott, S.M.; James, D.; Ali, Z. Data Analysis for Electronic Nose Systems. Microchimica Acta 2007, 156, 183–207.
  • Gutierrez-Osuna, R.;. Pattern Analysis for Machine Olfaction: A Review. IEEE Sensors Journal 2002, 2(3), 189–202.
  • Patel, H.K.;. The Electronic Nose: Artificial Olfaction Technology; Biological and Medical Physics, Biomedical Engineering, Springer India, DOI:10.1007/978-81-322-1548-6.
  • Zou, H.-Q.; Li, S.; Huang, Y.-H.; Liu, Y.; Bauer, R.; Peng, L.; Tao, Q.; Yan, S.-R.; Yan, Y.-H. Rapid Identification of Asteraceae Plants Improved RBF-ANN Classification Models MOS Sensor E-Nose; Evidence-Based Complementary and Alternative Medicine, 2014, 2014, 1–6. DOI:10.1155/2014/425341
  • Ghasemi-Varnamkhasti, M.; Mohtasebi, S.S.; Siadat, M.; Razavi, S.H.; Ahmadi, H.; Dicko, A. Discriminatory Power Assessment of the Sensor Array of an Electronic Nose System for the Detection of Nonalcoholic Beer Aging. Czech Journal Food Sciences 2012, 30(3), 230–236.

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