Search

Origin authentication methods are pivotal in counteracting frauds and provide evidence for certification systems. For these reasons, geographical origin authentication methods are used to ensure product origin. This study focused on the origin authentication (i.e. at the producer level) of a typical mountain cheese origin using various approaches, including shotgun metagenomics, volatilome, near infrared spectroscopy, stable isotopes, and elemental analyses. DNA-based analysis revealed that viral communities achieved a higher classification accuracy rate (97.4 ± 2.6 %) than bacterial communities (96.1 ± 4.0 %). Non-starter lactic acid bacteria and phages specific to each origin were identified. Volatile organic compounds exhibited potential clusters according to cheese origin, with a classification accuracy rate of 90.0 ± 11.1 %. Near-infrared spectroscopy showed lower discriminative power for cheese authentication, yielding only a 76.0 ± 31.6 % classification accuracy rate. Model performances were influenced by specific regions of the infrared spectrum, possibly associated with fat content, lipid profile and protein characteristics. Furthermore, we analyzed the elemental composition of mountain Caciotta cheese and identified significant differences in elements related to dairy equipment, macronutrients, and rare earth elements among different origins. The combination of elements and isotopes showed a decrease in authentication performance (97.0 ± 3.1 %) compared to the original element models, which were found to achieve the best classification accuracy rate (99.0 ± 0.01 %). Overall, our findings emphasize the potential of multi-omics techniques in cheese origin authentication and highlight the complexity of factors influencing cheese composition and hence typicity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Despite their importance as a reservoir of biodiversity, the factors shaping soil microbial communities and the extent by which these are impacted by cultivation are still poorly understood. Using 16S rRNA gene and ITS sequencing, we characterized the soil microbiota of vineyards and of neighboring permanent grassland soils in the Italian province of Trentino, and correlated their structure and composition to location, chemical properties of the soil, and land management., Results: Bacterial communities had a core of conserved taxa accounting for more than 60% of the reads of each sample, that was influenced both by geography and cultivation. The core fungal microbiota was much smaller and dominated by geography alone. Cultivation altered the structure and composition of the soil microbiota both for bacteria and fungi, with site-specific effects on their diversity. The diversity of bacterial and fungal communities was generally inversely correlated across locations. We identified several taxa that were impacted by the chemical properties and texture of the soil., Conclusions: Our results highlight the different responses of bacterial and fungal communities to environmental factors and highlight the need to characterize both components of the soil microbiota to fully understand the factors that drive their variability.

Mozzarella di Bufala Campana (MBC) is a PDO cheese produced from whole buffalo milk in specific regions of southern Italy. Due to the high price and the limited amount of buffalo milk, MBC is potentially subject to mislabelling. Stable isotope ratio analysis combined with elemental analysis is one powerful technique for detecting the authenticity of PDO cheeses. Here, the elemental and isotopic profiles of authentic samples of buffalo milk and the corresponding MBC samples collected in the reference area in winter and summer are presented in an initial exploratory study. By merging MBC-PDO samples with non-PDO samples of buffalo mozzarella produced both inside and outside the reference area, a model was developed to classify product categories for this cheese. Despite the differences occurring during processing, along with differences in the season and production area, the model was effective in distinguishing PDO and non-PDO mozzarella, particularly when non-PDO cheeses were made outside the MBC reference area., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

This work characterises and distinguishes Italian and Asian goji berries, combining three analytical approaches to determine 5 light stable isotope ratios, 57 mineral elements and 14 carotenoids. The study analyses stable isotope ratios and provides full HPLC-DAD-MS characterisation of the carotenoid fraction in goji berries for the first time. The isotopic composition of Italian berries was characterised by δ 13 C values ranging between -28.2‰ and -25.7‰, δ 15 N between 2.3 and 7.3‰, δ 34 S between 2.6 and 7.9‰, and D/H between -112 and -49‰. Italian goji berries were shown to have a particular composition and interesting nutritional characteristics, specifically a higher total carotenoid content (355 mg/100 g dw mean content vs 198 mg/100 g dw) and higher content of some micronutrients: K, B, Cu, Mo, Se, and Zn. On the basis of δ 34 S, Y, U, Cu, Rb, zeaxanthin palmitate and total carotenoid content, discriminant analysis correctly classified all samples according to their geographical origin., (Copyright © 2018 Elsevier Ltd. All rights reserved.)