Rice Proteins Bring Good Relationship between Eating Quality of Cooked Rice and Brewing Suitability of Sake

Abstract Background Rice is one of the few cereals consumed as a whole grain, and therefore the appearance of the final milled product, both before and after cooking, strongly influences the consumer’s perception of product quality. Matching consumer preference for rice grain quality is a key component of rice variety development programs, as the quality drives demand, which in turn drives variety adoption, market price, and profitability. The quality of cooked rice is normally evaluated indirectly, through measurement of key elements driving quality as well as more directly by sensory evaluation, but remains a complex trait conditioned by the genetic complexity of factors driving quality, changes wrought by environment, and the complexity of consumer preferences. Result In this study, we evaluated 17 traits, including the taste value obtained by glossiness of cooked rice (TV), to explain rice eating quality by statistical methods and identified QTLs associated with TV. To explain the correlation among traits, exploratory factor analysis was performed for 2 years. The overall eating quality (OE) was correlated with TV and protein content loading at the same factor (PA1) in 2017, and there was a relationship between the OE (PA1) and the TV (PA2) in 2018 (PA1:PA2, r = 0.3). In QTL analysis using 174 RILs, three QTLs for TV derived from Wandoaengmi6 were detected on chromosomes 4, 6, and 9. The QTL qTV9 delimited within Id9007180 and 9,851,330 on chromosome 9 was detected in both years, explaining approximately 17% of the variation, on average. Through the use of fine mapping, qTV9 was delimited to an approximately 34-Kbp segment flanked by the DNA markers CTV9_9 and CTV9_13, and nine ORFs were listed in the target region as candidate genes associated with TV. In the evaluation of qTV9’s effect on OE, the lines with qTV9 showed a significant increase in correlation coefficiency compared to the negative lines. These data will apply to functional analysis on the glossiness and the MAS breeding program to improve the eating quality of japonica as a donor line. Conclusion In this paper we report a number of QTL associated with changes in glossiness of cooked rice, and these may have utility in the development of MAS in breeding programs with a specific focus on cooked grain quality.

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Dissecting the genetic basis for the effect of rice chalkiness, amylose content, protein content, and rapid viscosity analyzer profile characteristics on the eating quality of cooked rice using the chromosome segment substitution line population across eight environments

Genome ◽

10.1139/g10-070 ◽

2011 ◽

Vol 54 (1) ◽

pp. 64-80 ◽

Cited By ~ 35

Author(s):

Xiaolu Liu ◽

Xiangyuan Wan ◽

Xiaodong Ma ◽

Jianmin Wan

Keyword(s):

Amylose Content ◽

Chromosome 8 ◽

Eating Quality ◽

Quality Traits ◽

Cooked Rice ◽

Qtl Cluster ◽

Profile Characteristics ◽

Segment Substitution ◽

Paste Viscosity

Quantitative trait locus (QTL) mapping and stability analysis were carried out for 16 rice ( Oryza sativa L.) quality traits across eight environments, by using a set of chromosome segment substitution lines with ‘Asominori’ as genetic background. The 16 quality traits include percentage of grain with chalkiness (PGWC), area of chalky endosperm (ACE), amylose content (AC), protein content (PC), peak viscosity, hot paste viscosity, cool paste viscosity, breakdown viscosity (BDV), setback viscosity (SBV), consistency viscosity, cooked-rice luster (LT), scent, tenderness (TD), viscosity, elasticity, and the integrated values of organleptic evaluation (IVOE). A total of 132 additive effect QTLs are detected for the 16 quality straits in the eight environments. Among these QTLs, 56 loci were detected repeatedly in at least three environments. Interestingly, several QTL clusters were observed for multiple quality traits. Especially, one QTL cluster near the G1149 marker on chromosome 8 includes nine QTLs: qPGWC-8, qACE-8, qAC-8, qPC-8a, qBDV-8a, qSBV-8b, qLT-8a, qTD-8a, and qIVOE-8a, which control PGWC, ACE, AC, PC, BDV, SBV, LT, TD, and IVOE, respectively. Moreover, this QTL cluster shows high stability and repeatability in all eight environments. In addition, one QTL cluster was located near the C2340 marker on chromosome 1 and another was detected near the XNpb67 marker on chromosome 2; each cluster contained five loci. Near the C563 marker on chromosome 3, one QTL cluster with four loci was found. Also, there were nine QTL clusters that each had two or three loci; however, their repeatability in different environments was relatively lower, and the genetic contribution rate was relatively smaller. Considering the correlations among all of the 16 quality traits with QTL cluster distributions, we can conclude that the stable and major QTL cluster on chromosome 8 is the main genetic basis for the effect of rice chalkiness, AC, PC, and rapid viscosity analyzer profile characteristics on the eating quality of cooked rice. Consequently, this QTL cluster is a novel gene resource for controlling rice high-quality traits and should be of great significance for research on formation mechanism and molecule improvement of rice quality.

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US Consumers’ Perceptions of Raw and Cooked Broken Rice

Foods ◽

10.3390/foods10122899 ◽

2021 ◽

Vol 10 (12) ◽

pp. 2899

Author(s):

Matthew G. Richardson ◽

Philip Glen Crandall ◽

Han-Seok Seo ◽

Corliss A. O’Bryan

Keyword(s):

Milling Process ◽

Eating Quality ◽

Human Consumption ◽

Price Discounts ◽

Cooked Rice ◽

Broken Rice ◽

Rice Samples ◽

Willingness To Purchase ◽

Different Levels

Rice supplies about 20% of the calories to the world’s consumers. Milling removes the outer husk and bran, breaking about 20% of the rice kernels during the milling process that equates to almost 100,000,000 tons of rice annually. Broken rice is discounted in price by almost half or relegated to non-human consumption. This study seeks to understand why this large percentage of rice production is discounted for human consumption. Consumers who routinely consume rice evaluated raw and cooked rice with 5%, 10%, 20%, 30% and 40% levels of brokens. Sensory analysis indicated the appearance of raw rice with high levels of brokens affected the price consumers were willing to pay. Panelists were not able to discern sensory differences amongst cooked rice samples with different brokens percentages despite an eight-fold difference in brokens (p < 0.01). From this, we concluded that the price discounts imposed on broken rice are not because of perceived differences in the eating quality of cooked rice. Overall impression and overall texture were the two most significant determinants in willingness to purchase rice. The five cooked-rice samples with different levels of broken rice inclusion did not differ in terms of willingness to purchase.

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Eating quality of cooked rice determination using Fourier transform near infrared spectroscopy

Journal of Innovative Optical Health Sciences ◽

10.1142/s1793545814500035 ◽

2014 ◽

Vol 07 (06) ◽

pp. 1450003 ◽

Cited By ~ 1

Author(s):

Ravipat Lapcharoensuk ◽

Panmanas Sirisomboon

Keyword(s):

Fourier Transform ◽

Near Infrared ◽

Nir Spectroscopy ◽

Eating Quality ◽

Least Squares Regression ◽

Prediction Ability ◽

Cooked Rice ◽

Near Infrared Spectra ◽

Jasmine Rice

The goal of this research was to study the relationship between the eating quality of cooked rice and near infrared spectra measured by a Fourier Transform near infrared (FT–NIR) Spectrometer. Samples of milled: parboiled rice, white rice, new Jasmine rice (harvested in 2012) and aged Jasmine rice (harvested in 2006 or during the period 2007–2011) were used in this study. The eating quality of the cooked rice, i.e., adhesiveness, hardness, dryness, whiteness and aroma, were evaluated by trained sensory panelists. FT–NIR spectroscopy models for predicting the eating quality of cooked rice were established using the partial least squares regression. Among the eating quality, the stickiness model indicated its highest prediction ability (i.e., [Formula: see text]; RMSEP = 0.65; Bias = 0.00; RPD = 1.87) and SEP/SD of 2. In addition, it was clear that the water content did not affect the eating quality of cooked rice, rather the main chemical component implicated was starch.

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