Correlation among Quality Characteristics in Medium-Grain Rice

Rice ( Oryza sativa L.) grain attributes, such as grain length and shape, milling quality, and physicochemical quality, are crucial for varietal development and subsequent farm adoption. Thus, it is crucial to comprehend the phenotypic range of these grain attributes and how they relate to one another. Therefore, this study analyzed the main grain quality traits in medium-grain rice, namely the amylose content (AC), gelatinization temperature (GT), gel consistency (GC), ratio of head rice (HR), and percentage of chalkiness (PC). Correlations among the major quality characteristics were then calculated through Pearson correlation matrix analysis. The results showed that AC was highly connected with GC, and PC and HR (GC) showed a strong correlation. The correlation between GT and GC was average. The other quality traits did not correlate significantly. The phenotypes of the grain quality traits provide a basis for improving the quality of medium-grain rice populations.


Introduction
Medium-grain rice with good quality has become a high-value product in the market and it is forecasted that both demand from consumers and the price of this rice will remain stable or even increase (Wailes & Chavez, 2015). Rice grain quality includes physical and chemical characteristics related to grain shape, milling quality, cooking qualities, and nutritional value (Juliano, 1985;Wang et al., 2007;Wang et al., 2011;Guo et al., 2011;Bao, 2014). In particular, the milling (head rice and chalkiness) and physicochemical (amylose content, gelatinization temperature, gel consistency, and aroma) qualities are the two groups of characteristics that are of interest to researchers, producers, and consumers (Raju et al., 1991;Demont et al., 2017;Custodio et al., 2019;Misra et al., 2019).
The ratio of head rice (HR) is the first milling quality in rice. It refers to the percentage of intact grains that remain after milling (Cnossen et al., 2003). HR is one of the most crucial economic characteristics of rice. Lower HR ratios are linked to decreases in the market value of milled rice (Siebenmorgen et al., 2006;Cuevas et al., 2016;Demont et al., 2017). Many factors can affect HR, such as (i) post-harvest procedures including the drying of grains, (ii) harvest grain moisture content (Cnossen et al., 2003), (iii) the detrimental influence of high nighttime temperatures during the filling of seeds, and (iv) genetic components (Sreenivasulu et al., 2015). Another important milling quality trait is chalkiness, which is commonly defined as an opaque white discoloration in the translucent endosperm brought on by the formation of air gaps between unevenly formed starch granules (Butardo and . Grain chalkiness or the percentage of chalkiness (PC) is an undesirable trait because it is related to high levels of damage to the grain during milling, and hence, to a decrease in the recovery of head rice (Del Rosario et al., 1968). Chalkiness significantly affects other milling quality traits (the ratio of brown, white, and head rice) but does not significantly affect the flexibility of the rice grains (amylose content) or the taste of cooked rice (IRRI, 2006). Among the grain quality traits, HR and PC are significantly affected by the environment (Zhao & Fitzgerald, 2013).
The most significant characteristic for classifying rice varieties is amylose content (AC) (Juliano, 1985), which affects the texture and retrogradation potential of cooked rice grains (Champagne et al., 2004). In the rice grain, amylose content comprises about 20-30% of the total starch (Vandeputte & Delcour, 2004;Regina et al., 2006). However, AC alone does not explain all of the variations in the eating and cooking quality, as cultivars with similar AC values possess different eating and cooking qualities (Pang et al., 2016). Gelatinization temperature (GT) and gel consistency (GC) are two of the physicochemical traits in rice that are also closely related to the eating and cooking quality of rice and are correlated with AC (Hossaina et al., 2009;Ritika et al., 2010;Pang et al., 2016;Zhang et al., 2020). GT is calculated as the alkali spreading value, which is determined by how whole-milled rice grains disperse in a weak alkali solution (1.7% potassium hydroxide). Low, intermediate, and high GT rice grains disintegrate completely, partially, and non-affectedly in a diluted alkali solution, respectively (IRRI, 1996). GC is a secondary indicator to further define the quality classes of varieties within the classifications of waxy and high-AC (Custodio et al., 2019). GC measures the cold paste viscosity of cooked rice flour and varies from soft to hard. The connection of starch polymers in the aqueous phase determines the soft and hard gels. Rice with a soft GC is more popular with customers (Wang et al., 2007). Many significant studies on improving rice quality have been conducted (Qian et al., 2016;Lang et al., 2017;Ferdous et al., 2018). However, these results have not particularly affirmed the quality of medium-grain rice. Therefore, studying the quality characteristics and their correlations would allow breeders to comprehend and breed medium-grain rice with good quality more effectively.
This study examined the relationships among the key quality attributes in medium-grain rice varieties.

Materials
A total of 342 varieties of the rice diversity panel (RDP) were provided by the Genetic Resources Center, International Rice Research Institute (IRRI) ( Table 1).

Experimental site and time
The experiments were conducted at the experimental station of the Institute of Food and Biotechnology, Can Tho University, Can Tho city, Vietnam from January to June 2021. Analysis methods of grain quality characteristics (grain size, AC, GT, GC, HR, and PC) in the medium-grain rice are shown in Figure 1.

Identifying the medium-grain rice
Rice samples were randomly selected with 100 grains/variety, husks were removed, and brown rice grains were photographed and measured using the SmartGRAIN software (Tanabata et al., 2012). The grain size classification was referenced from the methods of Jenning et al. (1979) and IRRI (2014), who reported that medium-grain rice has a grain length from 5.51 to 6.60mm and a ratio of grain length to grain width from 2.1 to 3.0.

Analysis of amylose content
The AC of the milled rice samples was assessed using the methods of Juliano (1971) and Graham (2002). In a 50-mL glass test tube, 100 mg of milled rice flour was soaked in 1 mL of 95% ethanol and 9.0mL of 1 N NaOH, and the mixture was left undisturbed for 16 hours. Then, to bring the solution to a volume of 100mL, 90mL of distilled water was added, and 0.5mL of the solution was put into a 20-mL test tube containing 5 mL of distilled water. Following the addition of 0.1mL of 1 M CH3COOH, 0.2mL of iodine solution (0.15% I2 in 1.5% KI) was added and the mixture was well stirred using a vortex mixer. The solution was then diluted to 10mL using 4.2mL of distilled water. To develop the calibration curves for the determination of amylose content in a rice sample, 40mg of Avebe potato amylose (standard amylose) was put in a 50mL test tube and the procedure described above was followed. Then, 0.1, 0.2, 0.3, 0.4, and 0.5mL of the standard amylose sample solution were transferred into 20mL test tubes and the same procedure used for the test samples was followed. Construction of the calibration curve was carried out by converting the spectral reading to the percentage of amylose content according to the formula: y = ax + b, where y is the absorbance OD, and x is the amount of amylose in the measured sample (mg L -1 ) (Graham, 2002).

Analysis of gelatinization temperature
Six whole-milled, unbroken duplicate kernels were chosen and put in a petri dish (8.0cm in diameter). Ten mL of 1.7% KOH solution was added. The samples were set up so that there was sufficient room between the kernels to permit spreading. The plates were covered and kept at 30°C for 23 hours of incubation. As part of the standard evaluation system for rice, the starchy endosperm was rated visually using a seven-point numerical spreading scale: high (1-2), high or intermediate (3), intermediate (4)(5), and low (6-7) (IRRI, 2014).

Analysis of gel consistency
Analysis of gel consistency was conducted according to the methods of Tang et al. (1991). Milled rice flour (100mg) was put into a glass test tube (13 x 100mm). Then, 0.2mL of 95% ethanol ..  containing 0.03% green thymol was placed into the test tube followed by the addition of 2mL of 0.2N KOH and the mixture was shaken thoroughly on a vortex machine. The test tube was covered and placed in a pot of boiling water (100 o C) for 8min. Test tubes were cooled to room temperature for 5min and placed in an ice bath for 20min. Test tubes were removed and placed horizontally for 1h. The gel consistency was the length the gel moved as measured from the bottom of the test tube to the end of the gel. The classification of gel consistency was according to the standard evaluation system for rice of IRRI (2014): soft (61-80mm), medium (41-60mm), and hard (< 40mm).

Analysis of the ratio of head rice
Evaluation of HR was performed according to the methods of IRRI (1996). Rice samples (200g) with a moisture content of 14% were peeled and milled, and the broken grains left out. The ratio of head rice was calculated by the formula: HR (%) = (Weight of head rice grains/Weight of paddy samples) x 100.

Analysis of the percentage of chalkiness
The PC was visually assessed based on the Standards Evaluation System for Rice (SES) of IRRI. The PC in rice was classified into four scales: scale 0 (non-chalky), scale 1 (chalkiness area less than 10%), scale 5 (chalkiness area from 11 to 20%), and scale 9 (chalkiness area more than 20%) (IRRI, 1996).
For each seed sample, 100g of rice grains were milled and each grain of rice was classified for PC. The percentage of chalkiness was determined by the formula: PC (%) = (Weight of chalkiness grains in scale 9/Weight of milled rice) * 100.
Statistical analysis of quality characteristics R-studio software version 3.2.2 (R Core Team, 2015) was used for Box-plot charting and Pearson's correlation coefficients (r) for AC, GT, GC, HR, and PC.

Results and Discussion
The medium-grain rice group The Rice Diversity Panel (RDP) consists of long-grain, medium-grain, and short-grain rice varieties classified according to the grain size of the brown rice. Among the examined 342 RDP rice varieties, there were 122 long-grain, 106 short-grained, and 114 medium-grained types, making up 35.7%, 31.0%, and 33.3% of the total, respectively. Thus, the RDP had similar numbers of long, medium, and short grain varieties or, in other words, the medium-grain varieties accounted for about one-third. The group of medium-grain rice included many rice subpopulations, in which, the indica (IND) was the biggest subpopulation (accounting for 36.0%), followed by the aus (AUS) and tropical japonica (TRJ) subpopulations, accounting for 22.8% and 14.9%, respectively, and the rest were other subpopulations.

Grain quality of medium-grain rice
The characteristics of grain quality (AC, GT, GC, HR, and PC) in the medium-grain rice varieties are shown in Table 2.
AC had significant differences among the rice varieties, ranging from 10.83 to 30.12%. This result is similar to many previous studies on AC in rice (Manners, 1979;Juliano, 1992;Patindol et al., 2015). The results showed that there were no glutinous rice varieties (AC ≤ 2%), the very low amylose group accounted for 3.5%, the low amylose group accounted for 18.4%, the medium amylose group had the biggest rate of 42.1%, and the remaining 36.0% had high amylose content. The varieties having a low amylose content of less than 20% make a potential group that needs attention for breeding new rice varieties with high quality.
The experiment recorded GT values ranging from a scale of 3 to 7. The high GT (from scale 3 and lower) accounted for about 4.4%, the middle GT (from scale 4 to 5) accounted for 23.7%, and the low GT (from scale 6 to 7) made up the majority, about 71.9%. According to Juliano and Villareal (1993) and Pang et al. (2016), rice varieties with low or intermediate GT are preferred because these varieties require less water and cooking time than those possessing high GT. The results of this study showed that many medium-grain varieties have low GT and can be considered potential materials for breeding high-quality rice varieties.
The GC test lengths of the medium-grain rice varieties were recorded as ranging from 31 to 96mm with the average value being 57.26mm. In which, most varieties had a medium gel consistency (GC = 41-60mm), accounting for 51.8%. The group of soft GC made up 34.2% and the rest of the varieties, about 14.0%, were classified as having hard GC. Chemutai et al. (2016) asserted that rice with a soft GC had a higher preference among consumers. Furthermore, hard GC is closely related to high AC, identifying the varieties as hard rice, and vice versa. Similar to the AC, rice varieties with better GC (softer) are preferred (Hirano & Sano, 1998;Nguyen Ngoc De, 2008).
The PC of medium-grain rice had a large range among the varieties. Many rice varieties were non-chalky (PC = 0%), while other varieties had very high chalkiness, with the highest rate of  (Sreenivasulu et al., 2015;Misra et al., 2019). These varieties are potential materials for breeding rice with low chalkiness. The HR of the medium-grain rice varieties ranged from 42.2% to 66.0%, showing a range of about 23.8% among the varieties. The mediumgrain rice had a high percentage of head rice, with an average of 53.6%. This result is consistent with the conclusions of previous studies. IRRI (2010) stated that the average HR of Asian rice varieties was in the range of 35-50% and an optimal 55-60% HR could be reached (FAO, 1998;Nguyen Ngoc De, 2008;Lapis et al., 2019). Therefore, the HR values of the medium-grain rice examined in this study were good.

Correlation analysis of quality characteristics
The correlations among the quality indicators are shown in Figure 2.
AC was strongly associated with GC and their correlation was inversely correlated. The correlation coefficient recorded between these two indicators was -0.85. This meant that the lower the AC, the greater the GC, the more flexible the rice, and vice versa. This result was similarly recorded in previous studies (Lapitan et al., 2009;Ritika et al., 2010;Zhang et al., 2020). Therefore, when determining AC or GC, researchers can predict the range of the remaining indicator. Moreover, within the same AC group, the rice varieties with a softer GC are preferred (Morgante & Olivieri, 1993;Hirano et al., 1998;Nguyen Ngoc De, 2008  GT was positively correlated on average with GC, and the correlation coefficient between the two indicators was +0.46. The results showed that many varieties with a high scale of GT (low GT) corresponded with a long GC, however, there were still many exceptions. Many studies on the correlation between GT and GC have given different conclusions. Lapitan et al. (2009) said that the correlation between these two indicators was low but significant (+0.18), while, Yang et al. (2020) concluded that the correlation was average (+0.42).
PC was strongly related to HR and their correlation was inverse, with a correlation coefficient of -0.75. This meant that the higher the PC of a rice variety, the lower the HR or recovery rate. This correlation has also been recognized across many studies (Nguyen Ngoc De, 2008;Liu et al., 2015;Sreenivasulu et al., 2015;Zhou et al., 2015;Yue et al., 2020). The cause of this phenomenon can be explained by the disjointed arrangement of starch granules in the chalkiness area. Starch granules have a less tight structure and create air-filled gaps between the starch particles. As a result, this phenomenon contributes to the cracking of rice grains during milling (Nagato, 1962;Nguyen Ngoc De, 2008;Lin et al., 2017).
PC and AC had a low correlation, with the correlation coefficient being +0.31. This low correlation was also confirmed in the studies of Nkori Kibanda & Luzi-Kihupi (2007), Zhu et al. (2020), and Yue et al. (2020).
In addition, PC was weakly correlated with GT and GC, and HR was weakly related to AC, GT, and GC.

Conclusions
In the medium-grain rice, AC was strongly correlated with GC, and PC was significantly related to HR. GT and GC had an average correlation. The correlations of the other quality indicators were not significant. The range of quality traits and their correlations in the medium-grain rice varieties did not have remarkable differences compared to the results of the ranges and correlations of the quality traits in earlier studies. This study provides basic information on the quality indicators of mediumgrain rice and can serve as a reference to help breeders comprehend medium-grain rice for breeding and selection.