# Rapid Assessment of Rice Quality Traits Using Low-Cost Digital Technologies
## 3 Results and Discussion  
Figure 3a shows the significant correlations (\(p<0.05\)) between e-nose outputs and volatile aromatic compounds found in raw rice samples. Among all e-nose sensors, MQ3 had the highest incidence of significant correlations with other variables. There were significant positive correlations between MQ3 and MQ7 (r = 0.58), MQ8 (r = 0.56), MQ135 (r = 0.71), MQ137 (r = 0.88), MQ138 (r = 0.78), MG118 (r = 0.51), and volatile aromatic compounds such as hexanoic acid (C5, r = 0.57), valeric anhydride (C8, r = 0.62), nonanal (C10, r = 0.49), octanoic acid (C16, r = 0.62), and benzene, 1,4-diethoxy (C23, r = 0.51). Additionally, it can be observed that MQ137 was positively correlated with valeric anhydride (C8, nonanal (C10, r = 0.49), and octanoic acid (C16, r = 0.62). Both nonanal and octanoic acid are associated with a waxy and fatty aroma [68]. Interestingly, positive correlations that have been reported between gas sensors and volatile aromatic compounds related to rice aging and yellowing processes, such as hexanoic acid, octanoic acid, and nonanal [69; 70; 18; 67; 68], were identified in the present study. This shows that the outputs obtained from the e-nose used in this study have great potential as a low-cost alternative tool for rice quality traits assessment and monitoring applications. Figure 2: Regression models developed using the (**a**) first derivative of NIR absorbance values to estimate the aromas (Models 3 and 4) and (**b**) physicochemical quality (Model 5) of rice, and (**c**) electronic nose sensors’ data as inputs to estimate rice aromas (Models 6 and 7). A description of the electronic nose sensors can be found in Table 2.  
Figure 3: Significant correlations (\(p<0.05\)) between the (**a**) electronic nose sensors’ outputs obtained from raw rice samples with volatile aromatic compounds detected in the raw rice and (**b**) electronic nose sensors’ outputs obtained from cooked rice samples with volatile aromatic compounds, color, texture, and pH of the cooked rice. Figure 3b shows the significant correlations (\(p<0.05\)) between the e-nose outputs obtained from cooked rice samples with the volatile aromatic compounds, color, texture, and pH of the cooked rice samples. It was observed that the volatile compounds that belong to the esters group had a significant positive correlation with some of the e-nose sensors' outputs. Dodecanoic acid, ethyl ester (C38) was positively correlated with MQ3 (r = 0.93), MQ4 (r = 0.87), MQ7 (r = 0.94), MQ8 (r = 0.74), MQ136 (r = 0.73), and MG811 (r = 0.87). Meanwhile, hexadecanoic acid, methyl ester (C39) was positively correlated with MQ135 (r = 0.83), MQ137 (r = 0.69), and MQ138 (r = 0.65). Dodecanoic acid, ethyl ester, is associated with sweet, waxy, floral, soapy, and clean aromas, whereas waxy and creamy are used to describe the aromas of hexadecanoic acid and methyl ester [68]. Additionally, it was observed that the lightness (L) of the cooked rice was negatively correlated with benzaldehyde (C2, r = \(-\)0.66), furan, 2-pentyl- (C4, r = \(-\)0.50), and 2,4-decadienal,(E,E) (C37, r = \(-\)0.95). This could be associated with the high abundance of the aforementioned volatile aromatic compounds detected in pigmented rice samples, such as the wild rice (WRO), which had lower L values than the other types of rice [16; 72]. Even though some significant correlations were observed between e-nose outputs of cooked rice and volatile compounds detected in cooked rice samples, it will be convenient to develop a method to assess cooked rice quality traits using the raw rice samples to avoid tedious sample preparation and destructive analysis. Additionally, previous studies showed promising potential through emerging trends of using sensor technology combined with the chemometrics technique to indirectly assess cooked rice quality traits using raw rice samples [73; 74; 75].