Bioscience Methods 2026, Vol.17, No.1, 23-31 http://bioscipublisher.com/index.php/bm 27 4.3 Correlation between moisture content and flavor quality indicators When evaluating the quality of rice, the content of amylose and gelatinization degree are often mentioned. However, these two indicators are more influenced by the variety itself rather than the timing of harvest. Even if the harvest time is slightly earlier or later, the changes will not be too significant as long as it is within the normal range (Zhou et al., 2025). Some studies have already pointed out that for most varieties, the content of amylose remains relatively stable under different harvest periods. In this experiment, a similar situation was observed. Regardless of whether it is amylose or gelatinization degree, the differences between different treatments were not prominent (Teng et al., 2024). Overall, compared to processing performance or flavor changes, the impact of harvest time on the starch-related qualities within the rice is not significant. 5 Comprehensive Relationship Analysis of Moisture Content, Whole-Grain Rice Rate and Flavor Quality 5.1 Correlation analysis of different quality indicators Based on the test results, the various qualities of rice are not necessarily better when the numerical value is higher. In many cases, they actually interfere with each other. For instance, some varieties with high amylose content and hard rice texture may have an improved whole-milled rice rate, but the taste score when eaten actually decreases (Tao et al., 2019). The processing effect and flavor do not simultaneously improve. Looking at it from another perspective, the moisture content also plays a key role: within an appropriate range, the whole-milled rice rate and flavor tend to be stable; however, if the moisture content is too high or too low, both aspects will be affected (Zhou et al., 2025). These situations remind us that improving the quality of rice cannot focus solely on a single indicator. Instead, it is necessary to repeatedly weigh different quality performances and find a relatively appropriate balance point (Figure 4) (Brinkhof et al., 2025). Figure 4 a Correlation coefficient between moisture and normalized difference spectral indices ND (B1,B2); b the relationship between NDVI=ND (NIR,R) and grain moisture content (GMC); c the relationship between most correlated index ND (SWIR1,RE3) and GMC (Adopted from Brinkhof et al., 2025)
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