Vibrational Spectroscopy Coupled to a Multivariate Analysis Tiered Approach for Argentinean Honey Provenance Confirmation

Abstract

In the present work, the provenance discrimination of Argentinian honeys was used as case study to compare the capabilities of three spectroscopic techniques as fast screening platforms for honey authentication purposes. Multifloral honeys were collected among three main honey-producing regions of Argentina over four harvesting seasons. Each sample was fingerprinted by FT-MIR, NIR and FT-Raman spectroscopy. The spectroscopic platforms were compared on the basis of the classification performance achieved under a supervised chemometric approach. Furthermore, low- mid- and high-level data fusion were attempted in order to enhance the classification results. Finally, the best-performing solution underwent to SIMCA modelling with the purpose of reproducing a food authentication scenario. All the developed classification models underwent to a “year-by-year” validation strategy, enabling a sound assessment of their long-term robustness and excluding any issue of model overfitting. Excellent classification scores were achieved by all the technologies and nearly perfect classification was provided by FT-MIR. All the data fusion strategies provided satisfying outcomes, with the mid- and high-level approaches outperforming the low-level data fusion. However, no significant advantage over the FT-MIR alone was obtained. SIMCA modelling of FT-MIR data produced highly sensitive and specific models and an overall prediction ability improvement was achieved when more harvesting seasons were used for the model calibration (86.7% sensitivity and 91.1% specificity). The results obtained in the present work suggested the major potential of FT-MIR for fingerprinting-based honey authentication and demonstrated that accuracy levels that may be commercially useful can be reached. On the other hand, the combination of multiple vibrational spectroscopic fingerprints represents a choice that should be carefully evaluated from a cost/benefit standpoint within the industrial context.

Identification and Authentication of Honey Using Chemometric Analysis Based on Atr-Ftir and Raman Spectroscopy

“…The peaks observed at a wavelength of 1640-1760 cm -1 may be because of the C=O stretching mainly from carbohydrates and H-O-H stretching [10]. The peak observed at 2800-3000 cm -1, which strongly shows at 2937 cm -1 could be associated with the presence of C-H stretching from carboxylic acids and NH3 stretching from free amino acids [19].…”

“…The advantages of Raman spectroscopy are usable for samples in the form of solids or liquids, no sample preparation, the chemical fingerprint obtained is specific for material, and spectra can be generated quickly in just seconds [8]. The use of chemometrics, especially discriminant analysis techniques is because each compound has different and distinctive FTIR or Raman vibration spectra, so the resulting spectrum may represent the characteristics of a honey sample [9,10].…”

Innovative Vibrational Spectroscopy Research for Forensic Application

“…They proved that SERDS, in combination with PCA-LDA, can differentiate tree pollen types according to their growth habits with a high of 95.5% accuracy. Finally, Damiani et al utilized vibrational spectroscopy techniques like FT-MIR, NIR, and FT-Raman spectroscopy with multivariate data analysis for Argentinean honey provenance confirmation . The spectroscopic techniques were compared based on the classification performance achieved using the chemometric methods, resulting in excellent classification with all the techniques and perfect classification by FT-MIR.…”

Current Trends of Food Analysis, Safety, and Packaging

“…FT-MIR potential for fingerprinting-based honey authentication is demonstrated which can achieve accuracy levels that could be commercially useful. The combination of multiple vibrational spectroscopic fingerprints in honey authentication is carefully considered in terms of cost/benefit in the industrial context [ 136 ]. Electrochemical biosensors have made substantial advances in quantitative detection and screening, and they have enormous potential for overcoming conventional limitations.…”