Phenolic Profile as a Powerful Machine Learning Tool for Identification, Traceability, and Quality Control of Olive Cultivars.

This study investigates the phenolic and fatty acid profiles of olives from four cultivars (Arbequina, Arbosana, Frantene, and Koroneiki), widely grown in the Mediterranean region and collected at different ripening stages in Italy. The aim was to assess the potential of olive chemical profiles as markers for cultivar classification using machine learning algorithms, including Linear Discriminant Analysis (LDA), K-Nearest Neighbors (KNN), Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM). Results showed that phenolic profiling achieved significantly higher classification accuracy than fatty acids across all models.

Does the Harvest Type Affect Olive Health? Influence of the Harvesting System and Storage Time on the Chemical, Volatile and Sensory Qualities of Extra Virgin Olive Oils.

With the aim of investigating the effect of bruising and its development during the postharvest time, olive fruits (Frantoio and Moraiolo), manually and mechanically harvested, were stored in climatic chambers at two different temperatures (5 °C and 18 °C) for five days. Visual observations highlighted changes in the olive peel with discoloration in the damaged areas and tissue bruising. Olive fruit polyphenols, volatile organic compounds (VOCs) and other oil quality parameters (phenolic content, free acidity and peroxide index) and sensory assessment were evaluated.

Metabolic Responses in Leaves of 15 Italian Olive Cultivars in Correspondence to Variable Climatic Elements.

This study aims to evaluate the metabolic changes that occurred in olive leaves as responses over time to variations in climatic elements. Rainfall, temperature, and solar radiation data were collected over 4 months (August-November) to assess the impact of different climatic trends on the metabolism of the leaves of 15 Italian olive cultivars, cultivated at the experimental farm of the University of Florence. The net photosynthetic rate (A) and stomatal conductance (g), measured as main indicators of primary metabolism, were mainly influenced by the "cultivar" effect compared to the "climate" effect.

Nutrigenomic Effects of Long-Term Grape Pomace Supplementation in Dairy Cows.

The increasing demand for more animal products put pressure on improving livestock production efficiency and sustainability. In this context, advanced animal nutrition studies appear indispensable. Here, the effect of grape pomace (GP), the polyphenol-rich agricultural by-product, was evaluated on Holstein-Friesian cows' whole-blood transcriptome, milk production and composition.

Tuberomics: a molecular profiling for the adaption of edible fungi (Tuber magnatum Pico) to different natural environments.

Background: Truffles are symbiotic fungi that develop underground in association with plant roots, forming ectomycorrhizae. They are primarily known for the organoleptic qualities of their hypogeous fruiting bodies. Primarily, Tuber magnatum Pico is a greatly appreciated truffle species mainly distributed in Italy and Balkans.

Dietary Supplementation of Dried Grape Pomace Increases the Amount of Linoleic Acid in Beef, Reduces the Lipid Oxidation and Modifies the Volatile Profile.

The aim of this study was to evaluate the effect of dietary supplementation with dried grape pomace on beef quality. Ten Friesian calves were divided into two groups, a control group that received a standard diet, and an experimental group that was administered the dietary supplementation. At the end of the 75 days of the trial, animals were slaughtered, and meat samples analyzed for physical and chemical properties, fatty acids composition, lipid oxidation, volatile compounds, and biogenic amines.

Covering the different steps of the coffee processing: Can headspace VOC emissions be exploited to successfully distinguish between Arabica and Robusta?

This work was performed to evaluate the possible application of PTR-ToF-MS technique in distinguishing between Coffea arabica (Arabica) and Coffea canephora var. robusta (Robusta) commercial stocks in each step of the processing chain (green beans, roasted beans, ground coffee, brews). volatile organic compounds (VOC) spectra from coffee samples of 7 Arabica and 6 Robusta commercial stocks were recorded and submitted to multivariate statistical analysis.