Machine learning can help identify suitable distribution and storage conditions for delicate extra virgin olive oil

Nowadays, in the United States, and especially in California, different extra virgin olive oils are being produced. Nevertheless, many European countries have been and still are importing their extra virgin olive oils, mainly from Spain and Italy. Many recent studies performed in the US regarding the quality of these imported oils have revealed many low-quality products, even from prestigious brands, causing much discomfort in this sector overseas. Although initial blames were put on the producers, there is more and more evidence that, in fact, the distribution chain and storage plays a major role in the degradation of these delicate foods. Harsh conditions have been reported during transportation in ships, having olive oil containers sitting in the sun from days to even months at very high temperatures.

In the current age of information, where digitization is becoming indispensable (turning signals into digital format; i.e. “0s” and “1s”), photographs can be used as a great source of data. They can be transformed into mathematical databases, where each color of a single pixel can be seen as a set of three numbers representing the intensity of red, green, and blue channels. Therefore, the higher the number of pixels in a photo, which is directly related to its resolution, the greater the amount of information that can be used for different applications.

In this specific scenario, several photographs of olives, of different quality grades, were gathered, and their pixel maps were extracted through image processing. Afterwards, this information was used to train intelligent mathematical models to distinguish the olives in terms of quality grade. This intelligent modeling is also known as machine learning (computational artificial intelligence), which is becoming more and more popular within the scientific community. In many cases, its use is turning out to be a necessity, as it is the only way to process the immense databases that arise from fields such as food technology, biochemistry, or biomedicine.