The world population is expected to reach over 9 billion by 2050, which will require an increase in agricultural and food production by 70% to fit the need, a serious challenge for the agri-food industry. Such requirement, in a context of resources scarcity, climate change, COVID-19 pandemic, and very harsh socioeconomic conjecture, is difficult to fulfill without the intervention of computational tools and forecasting strategy. Hereby, we report the importance of artificial intelligence and machine learning as a predictive multidisciplinary approach integration to improve the food and agriculture sector, yet with some limitations that should be considered by stakeholders.

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Adulteration of virgin olive oil with less expensive oils is a serious problem for the public and quality control evaluators of olive oil. That is why olive oil authenticity has become a major issue for producers, consumers, and policy makers. In order to avoid fraud to consumers, it is crucial to study the traceability of olive oil. This review covers 2 important techniques, analytical, and molecular methods, used to characterize olive oil and detect possible adulteration. Several analytical techniques are discussed for the detection of olive oil adulteration by analyzing minor and major compounds of olive oil. However, the chemical composition of olive oil can dramatically change due to the environmental and processing conditions. For this reason, the DNA-based technologies are gaining greater attention now because they are not influenced by environmental conditions and provide an opportunity for direct comparison of different genetic materials. In this review, we emphasize the great potential of different authenticity methods and discuss their practical implementation in olive oil traceability.

Strawberry trees (Arbutus unedoL.) are naturally grown in particular Black Sea and Mediterranean regions of Turkey with great diversity due to continuous seed propagation for centuries. The trees differ in terms of most of the horticultural characteristics. We investigated the phenolic compounds and the biochemical and pomological characteristics of the fruits of eight strawberry tree selections naturally grown in the western part of Turkey. Significant differences were found among the genotypes in terms of their phenolic compounds and their biochemical and pomological characteristics. Among soluble sugars, fructose (11.63 g 100 g−1) was the dominant sugar, followed by glucose (6.10 g 100 g−1) and sucrose (1.44 g 100 g−1) for all the genotypes. Positive correlation was found between fruit weight and soluble sugar content. Malic acid was the major organic acid (0.67-2.33 g 100 g−1), and the second major organic acid in strawberry tree fruits was citric acid (0.25-0.87 g 100 g−1). Vitamin C content was an average of 56.22 g 100 g−1for the eight genotypes. Among phenolic compounds, gallic acid was dominant (1.62-7.29 mg 100 g−1), followed by chlorogenic acid (1.23-3.14 mg 100 g−1), on an average basis.