In order to enjoy Iberico ham to its maximum capacity and enjoy all its refined flavor. It is necessary to know everything related to its care, handling, type of cut, but also know how to differentiate the various types of hams, their degrees of quality and other very important aspects of our prestigious gourmet product.

Tasting hams, just like any other culinary delicacy, is an art form that is only mastered be a select group of experts. For most of us, a ham tasting consists of trying a good Iberian ham, cut into thin slices. However, none of this would be possible without the work of a ham master, who previously evaluates and tastes the ham in order to then sell a good product in different stores. 

What is the problem associated with the traditional methods of tasting ham?

When it comes to tasting ham, the main difficulty is the need for the ham master to puncture it with an instrument made of bone; this material absorbs the ham's aromas, allowing the ham master to know whether the ham has reached the right amount of curing, or if it should be left in this stage for more time or if, on the other hand, the product has spent too much time in the cellar.

Puncturing the ham interrupts the curing process and the piece risks being damaged if it's not ready. For this reason, the ham master needs to trust their other senses in order to evaluate and decide what condition the ham is in. Clearly, the ability to determine whether the leg of ham is sufficiently cured by just observing and sniffing it, is an art that only a few are able to master perfectly and that leaves a great deal up to chance. 

Which characteristics of a ham can be evaluated technically?

The quality assessment of meat products has been the subject of many studies for decades. In most cases, techniques have been developed to evaluate the physico-chemical characteristics of both fresh and cured meat products, including their colour, moisture content, amount of fats, proteins or salt. However, these techniques are destructive and involve the use of organic solvents, in addition to requiring a lot of time and effort.

What modern methods have emerged?

MRIs and other imaging techniques have emerged as alternative methods for the physico-chemical analysis of ham, due to their non-destructive, non-invasive, non-intrusive, non-ionising and harmless nature. There have been many studies published that have tried to determine a meat product's characteristics in terms of its quality, most of which have focused on loins and legs.

In Spain, a team of scientists from the University Research Institute of Meat and Meat Products (IProCar), a meat studies institute at the University of Extremadura, has described an ingenious method for tasting ham, without the need to puncture or open it up. To do so, they used an MRI scanner, the same non-invasive imaging technique used in modern medicine that makes it possible to see organs and structures inside the human body. This imaging method is now used for a very different purpose: to find out the characteristics of Iberian hams and loins without the need to handle them in any way. 

Once the images have been captured, the scientists analyse them with computerised vision algorithms and extract numerical values to which statistical methods are applied. Thus, it is possible to predict the characteristics of meat products in terms of quality. These techniques allow us to know parameters such as the amount of fat, moisture and colour, as well as some of the product's sensory attributes. When it comes to ham, this method also enables us to monitor salt diffusion during the different stages of the ageing process, practically in real time. 

What does the future hold for MRIs in the ham market? 

The procedure described was recently published in the Journal of Food Engineering. The researchers commented that their technique can easily be applied to the ham industry because it uses devices and algorithms that are very simple to implement. In addition, they pointed out that it is only a matter of time before these methods are implemented in the meat industry as a whole.

Spectral Images

It is common knowledge that when a product has an elevated cost in the market, as in the case of Iberian ham, competitors then offer another product that they claim has similar characteristics and components, but at a better price. These cheaper products are often not what they seem, something that is well-known reality in the meat sector, and can be seen, for example, in products that are marked with confusing labels, masking the fact that we're consuming something other than what we were offered. This improper and fraudulent practice seems to have its days numbered.

A group of researchers from the University of Seville (Spain) has developed a novel technique that allows us to determine the presence of microorganisms in real time, along with the meat's quality, the type of feed that the animal received or, in the case of plants like the olive, the appropriate point of maturation in order to obtain the best oil; all this information is obtained from hyperspectral images, which collect up to 170 bands of the electromagnetic spectrum (both visible and non-visible) of any product, with the subsequent application of artificial intelligence for its analysis and interpretation. 
 
Doctors from the research group Electronic Technology and Industrial Informatics (TIC-150), at the University of Seville, are working on the application of artificial intelligence in the field, a key issue in agricultural and livestock production in this technological era in which we live. This team has developed a prototype along with the ProDTI foundation, a non-profit entity belonging to the university, whose mission is to generate research projects and to transfer their results to a business reality, along with the companies Soltel and Ctaex (Agrifood Technology Centre of Extremadura). 

The developed prototype uses cameras that collect information obtained from all the spectrums of a product (up to 170 bands, in comparison with the three bands from conventional imaging) for its subsequent analysis by artificial intelligence, with which the machine is able to detect any property of the evaluated object. The researchers have pointed out that, in approximately seven seconds, between 400 megabytes and two gigabytes of information are analysed, which allows us to know, for example, if a meat is contaminated with Salmonella (a bacterium that generates a gastrointestinal infection), its percentage of oleic acid and other nutrients that make it possible to determine how the animal was fed, and even the presence of defects or foreigns objects in the product. 

To reach a high degree of efficiency (95%), the researchers have also developed algorithms that make it possible to distinguish the images obtained by the cameras within the framework of the Hyqum project, a system for the detection of microbial contamination in beef and pork, the presence of foreign bodies and a system that determines the characteristics of the pig's diet via remote sensing using hyperspectral technology. 

With the use of these technologies, the industry obtains a clear benefit, as with a camera that can cost up to €12,000 and the right computer system, each product can be analysed prior to its processing for consumption, all of which is occurring in real time. In contrast, right now samples are obtained that have to be analysed in laboratories so that a food can remain in the production chain, which requires more time and different laborious techniques. As an additional benefit, the analysis of spectral images provides information that guarantees the level of quality that is offered to the market. 

For the consumer, the benefit is equally significant. The record of the image analyses certifies not only that the meat is in perfect condition, but it also provides information regarding its composition, including the animal's diet before being slaughtered, and it's pathogen-free status. 

It's worth mentioning that these technologies can be applied outside of the meat sector. For example, this technique and its parameters of artificial intelligence are being used to determine the quality of olives, thus ensuring they are harvested at the ideal time in order to prepare the best possible oil. Beyond that, with the image of an olive tree, it is possible to determine the amount of olives in a farm, the caliber or degree of ripeness of the fruit, all of which is information that is essential for managing the harvest and taking it to the mills at the right time. 

Finally, the researchers of the described project have stated that, at the end of the year, the technology could be ready to be applied by the industry, and they have highlighted the existence of other fields of research in which the implementation of this technology may be useful, including everything from medicine, where it is already applied as a non-invasive diagnostic method in the specific areas of oncology, cardiology and ophthalmology, to the restoration of cultural heritage.