A critical review on the use of artificial neural networks in olive oil production, characterization and authentication

Critical Reviews in Food Science and Nutrition 

doi.org/10.1080/10408398.2018.1433628

Artificial neural networks (ANN) are computationally based mathematical tools inspired by the fundamental cell of the nervous system, the neuron. ANN constitute a simplified artificial replica of the human brain consisting of parallel processing neural elements similar to neurons in living beings. ANN is able to store large amounts of experimental information to be used for generalization with the aid of an appropriate prediction model. ANN has proved useful for a variety of biological, medical, economic and meteorological purposes, and in agro-food science and technology.

The olive oil industry has a substantial weight in Mediterranean's economy. The different steps of the olive oil production process, which include olive tree and fruit care, fruit harvest, mechanical and chemical processing, and oil packaging have been examined in depth with a view to their optimization, and so have the authenticity, sensory properties and other quality-related properties of olive oil. This paper reviews existing literature on the use of bioinformatics predictive methods based on ANN in connection with the production, processing and characterization of olive oil. It examines the state of the art in bioinformatics tools for optimizing or predicting its quality with a view to identifying potential deficiencies or aspects for improvement.

Characterization of virgin olive oils produced with autochthonous Galician varieties

Food Chemistry 212 ( 2016) 162–171

http://dx.doi.org/10.1016/j.foodchem.2016.05.135

The interest of Galician oil producers (NW Spain) in recovering the ancient autochthonous olive varieties Brava and Mansa has increased substantially in recent years. Virgin olive oils produced by co-crushing both varieties in two different proportions, reflecting the usual and most common practice adopted in this region, have gradually emerged for the production of virgin olive oils. Herein, the sensory and chemical characteristics of such oils were characterized by quality and genuineness-related parameters. The results of chemical analysis are discussed in terms of their effective contribution to the sensory profile, which suggests useful recommendations for olive oil producers to improve the quality of oils. Antioxidant compounds, together with aromas and coloured pigments were determined, and their contribution in determining the functional value and the sensory properties of oils was investigated. In general, given the high levels of phenolic compounds (ranging between 254 and 375 mg/kg oil), tocopherols (about 165 mg/kg oil) and carotenoids (10–12 mg/kg oil); these are oils with long stability, especially under dark storage conditions, because stability is reinforced with the contribution of chlorophylls (15–22 mg/kg oil). A major content of phenolic compounds, as well as a predominance of trans-2-hexen-1-al within odor-active compounds (from 897 to 1645 μg/kg oil), responsible for bitter sensory notes. This characterization allows to developing new antioxidant-rich and flavour-rich VOOs, when co-crushing with a higher proportion of Brava olives, satisfying the consumers’ demand in having access to more healthy dishes and peculiar sensory attributes.