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

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.

Chemical Composition, Antimicrobial Activity, and Mode of Action of Essential Oils against Paenibacillus larvae, Etiological Agent of American Foulbrood on Apis mellifera.

This study aimed to characterize the chemical composition of Aloysia polystachia, Acantholippia seriphioides, Schinus molle, Solidago chilensis, Lippia turbinata, Minthostachys mollis, Buddleja globosa, and Baccharis latifolia essential oils (EOs), and to evaluate their antibacterial activities and their capacity to provoke membrane disruption in Paenibacillus larvae, the bacteria that causes the American Foulbrood (AFB) disease on honey bee larvae. The relationship between the composition of the EOs and these activities on P. larvae was also analyzed. Monoterpenes were the most abundant compounds in all EOs. All EOs showed antimicrobial activity against P. larvae and disrupted the cell wall and cytoplasmic membrane of P. larvae provoking the leakage of cytoplasmic constituents (with the exception of B. latifolia EO). While, the EOs' antimicrobial activity was correlated most strongly to the content of pulegone, carvone, (Z)-ß-ocimene, δ-cadinene, camphene, terpinen-4-ol, elemol, ß-pinene, ß-elemene, γ-cadinene, α-terpineol, and bornyl acetate; the volatiles that better explained the membrane disruption were carvone, limonene, cis-carvone oxide, pentadecane, trans-carvyl acetate, trans-carvone oxide, trans-limonene oxide, artemisia ketone, trans-carveol, thymol, and γ-terpinene (positively correlated) and biciclogermacrene, δ-2-carene, verbenol, α-pinene, and α-thujene (negatively correlated). The studied EOs are proposed as natural alternative means of control for the AFB disease.