## 3 Results and Discussion
### iPLS and siPLS Models
The iPLS model for the parameter FV was developed after spectral processing based on the SNV plus second derivative algorithm and was characterized by R = 0.57, RMSECV = 270, and LV = 10 for the spectral region 5970-4396 cm\({}^{-1}\). Meanwhile, the siPLS model for FV was characterized by R = 0.64, RMSECV = 251, and 10 LVs for the spectral regions 7840-7520 cm\({}^{-1}\) and 4960-4320 cm\({}^{-1}\). FV is the most useful parameter to represent the quality of the sample, displaying the capacity of the material to produce a gelatinous gel after cooking and cooling. The siPLS model for the parameter FV showed a strong dependence on the species that absorb energy in the spectral regions 7515 cm\({}^{-1}\), 7591 cm\({}^{-1}\), 6385 cm\({}^{-1}\), and 6094 cm\({}^{-1}\), while the TR model was based on the bands characterized by peaks at 7515 cm\({}^{-1}\), 6530 cm\({}^{-1}\), 5947 cm\({}^{-1}\), 4909 cm\({}^{-1}\), and 4867 cm\({}^{-1}\). The quantity and quality of these factors may affect the gelatinization and retrogradation processes of rice flour. The protein content is one of the main factors affecting the gelatinization properties of starch [1]. The iPLS model for the parameter PV, characterized by R = 0.85, RMSECV = 332, and LV = 10, was developed after SNV plus second derivative processing for the spectral region 4784-4396 cm\({}^{-1}\). Meanwhile, the optimal siPLS model for PV was defined for the spectral region 5280-4320 cm\({}^{-1}\) and was characterized by R = 0.90, RMSECV = 275, and 10 LVs. The peaks registered at 7882 cm\({}^{-1}\), 5997 cm\({}^{-1}\), 4908 cm\({}^{-1}\), and 4867 cm\({}^{-1}\) presented a strong influence on the model. The correlation with amylose showed an opposite behavior due to the specific properties Finally, for both parameters ST and TR, the iPLS models defined after second derivative pre-processing were characterized by R = 0.85 and RMSECV = 332 (Table 1). Both iPLS models were defined for the spectral region 4784-4396 cm\({}^{-1}\). The bands at 6545 and 4762 cm\({}^{-1}\) are typically due to starch, the major component of rice, showing a significant correlation with pasting properties [7; 18]. The siPLS model for ST was characterized by R = 0.88, RMSECV = 297, and 9 LVs, defined by the spectral region 5280-4320 cm\({}^{-1}\), while, for the TR, the model was developed for a similar spectral region and characterized by R = 0.84, RMSECV = 154, and 10 LVs. The parameter ST showed a significative and positive correlation with amylose. Prior studies showed a correlation between pasting properties, such as PV and ST, and amylose fractions [7; 21]. Focusing on these parameters, the siPLS regression models presented significant accuracy compared with the iPLS models and can thus be considered a suitable tool for determining pasting properties in a huge variety of rice (Figure 3A,B). The pasting properties can explain the performance of rice flour and starch during processing (heating and/or cooling) once the rice pasting quality is defined on the basis of starch quality. In the models, selecting spectral intervals that include significant biochemical information allowed us to develop predictive models characterized by high correlation and low prediction error. The second overtone for the methyl group (-CH\({}_{3}\)), characterized by the interval 8941-8194 cm\({}^{-1}\), is close to the interval 8183-6850 cm\({}^{-1}\) (Figure 3B). The spectral region defined by the C-H second overtone corresponds to the amylose molecules [22]. The selected spectral range 5592-5054 cm\({}^{-1}\) is close to the interval 5875-5495 cm\({}^{-1}\), which can be related to amylose molecules [23; 24]. The appearance and eating quality of rice cultivars are directly correlated with their fat content [25]. Higher amounts of fat represent