## 3 Results and Discussion
### Comparison of Spectra Sampling Zone: Fat vs. Lean Meat
MicroNIR also shows this behavior, i.e., a lower number of predicted constituents from the fat spectrum (10) with respect to the lean zone (14) and only one equation with an RSQ > 0.7 in each recording zone. It should be noted that this equipment is the one that presented the highest number of equations with an RSQcv > 0.5 with respect to the rest of the portable equipment. Finally, the SCiO presented the opposite tendency, so that the number of equations obtained from the fat spectra was greater than in the meat zone with the prediction of12 fatty acids, among which are all the summative and the majority C16:0, C18:2 n6, and C18:3 n3 versus 9 fatty acids predicted in the lean meat zone and 50% of the equations with RSQ values > 0.7 but no RSQcv > 0.5. In order to assess the suitability of the equations developed, the SEC and SECV values must also be taken into consideration. Specifically, the RSQcv and SEC are relevant because a higher value of the RSQcv and a lower value of the SEC are indicative of a better predictive fit and less error in the calibrated value, thus obtaining a more accurate and reliable model. On the other hand, SEC and SECv values provide information on how the model fits the calibration data and how it behaves with data that are not part of the calibration training. Comparison between the two data may result in detecting poor predictive reliability due to overfitting when the SEC is significantly lower than the SECv. To determine a correct fit, the SEC and SECv values must be very close to confirm a tight and reliable model for the prediction of samples external to the calibration set. The SEC in all equations took very low values in general, with slightly higher values in the fat recording zone for the NIRFlex N-500, microPHAZIR, and Enterprise Sensor devices. On the contrary, for the SCIO Sensor equipment, the SEC values were slightly higher in most of the equations for the spectra taken in the lean meat zone, while for the MicroNIR equipment, the behavior of the errors was similar in both zones. Finally, the cross-validation errors (SECv) presented different behaviors with respect to the SEC; in some of the cases, the behavior of both was maintained, and in other cases, it was much higher. These errors are comparable with those reported in the literature for the fatty acids C18:0, C18:2, and C18:3 [28]. The analysis of the results obtained seems to show that the number of equations obtained for the calibration of fatty acids is always higher when the recording is carried out on lean meat. This fact is especially significant in the microPHAZIR equipment that records in the longer wavelength zone (1596-2395 nm). On the other hand, only the spectral zone of 740-1070 nm (SCIO equipment) offers a greater number of calibration equations in samples when the recording is performed on fat. This appears to indicate that higher wavelengths are more suitable for lean and lower wavelengths for fat. It should be noted that fatty acids are muscle components that are strongly influenced by animal nutrition and to a lesser extent by genotype. In turn, they are associated with many sensory attributes of meat and meat products [63]. Specifically, in Iberian ham, a high content of infiltrated fat directly related to a higher oleic acid content and lower PUFA content is pursued, which is reflected in the product through the properties of smoothness and shine. In addition, a high oleic and palmitoleic acid content is associated with less hardness, dryness, and fibrousness in the cured product [57]. Therefore, the determination of the lipid profile can be interesting to look at for correlations with sensory parameters of interest in this type of cured product.