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미국 벼 품종의 입형과 호화점도 및 식감 관련 형질 특성 분석

박재령, 이창민, 백만기, 안주현, 서정환, 홍하철, 정오영, 박현수*

Characterization of Grain-Related Traits and Pasting and Texture Properties of United State Rice Varieties in Korea

Korean Journal of Breeding Science 2022;54(2):81-97.
Published online: June 1, 2022

농촌진흥청 국립식량과학원

National Institute of Crop Science, RDA, Wanju 55365, Republic of Korea

*Corresponding Author (E-mail: mayoe@korea.kr, Tel: +82-63-238-5214, Fax: +82-63-238-5205)

First authors equally contributed to this study.

• Received: February 14, 2022   • Revised: March 6, 2022   • Accepted: April 26, 2022

Copyright © 2022 by the Korean Society of Breeding Science

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Characterization of Grain-Related Traits and Pasting and Texture Properties of United State Rice Varieties in Korea
Korean. J. Breed. Sci.. 2022;54(2):81-97.   Published online June 1, 2022
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Characterization of Grain-Related Traits and Pasting and Texture Properties of United State Rice Varieties in Korea
Korean. J. Breed. Sci.. 2022;54(2):81-97.   Published online June 1, 2022
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Characterization of Grain-Related Traits and Pasting and Texture Properties of United State Rice Varieties in Korea
Image Image Image Image Image Image
Fig. 1 Phenotype (A) and genotype (B) of grains of U.S. rice varieties. The number of grains in the petridish is 100. PCR analysis was conducted to confirm the allele types of nine grain-related genes, GW2, GS3, qGL3, qLGY3, qSW5, GS5, TGW6, GW7, and GW8. M: DNA size marker, 1: Boramchan (BRC), 2: Rico1 (RC1), 3: Pecos (PCS), 4: Saturn (ST), 5: Mars (MS), 6: Saber (SB), 7: Shortlabelle (SLBL), 8: A008, 9: Bluebelle (BLBL), 10: Rajbonnet (RJBN), 11: Cypress (CPRS), 12: Cocodrie (CCDR), 13: Lacassine (LCS), 14: Jefferson (JFS), 15: A020.
Fig. 2 Distribution of U.S. rice varieties using grain-related traits. Principal component analysis (A) and K-means clustering analysis (B). PC1: principal component 1, PC2: principal component 2, GL: grain length, GW: grain width, GT: grain thickness, RLW: ratio of length to width, TGW: 1,000-grain weight. Dim1: dimension 1, Dim2: dimension 2.
Fig. 3 The effects of various allele combinations of U.S. rice varieties. Black rectangles indicate the means of grain-related traits. GL: grain length, GW: grain width, GT: grain thickness, RLW: ratio of length to width, TGW: 1,000-grain weight. CU1: GW2-GS3_C-qGL3-qLGY3- qsw5_N-gs5-TGW6-GW7-GW8 (Boramchan), CU2: GW2-GS3_C-qGL3-qLGY3-qSW5-gs5-TGW6-GW7-GW8 (Rico1, Pecos), CU3: GW2-GS3_ C-qGL3-qlgy3-qSW5-gs5-TGW6-GW7-GW8 (Saturn, Mars), CU4: GW2-GS3_B-qgl3-qlgy3-qSW5-gs5-TGW6-GW7-GW8 (Saber), CU5: GW2-gs3- qGL3-qlgy3-qSW5-gs5-TGW6-GW7-GW8 (Shortlabelle, A008, Bluebelle, Rajbonnet, Cypress, Cocordire, Lacassine, Jefferson), CU6: GW2-gs3- qGL3-qlgy3-qSW5-gs5-TGW6-GW7-gw8 (A020). Means with same letters in a column are not significantly different at p<0.05 (ANOVA followed by DMRT).
Fig. 4 Distribution of U.S. rice varieties using pasting properties-related traits. Principal component analysis (A) and K-means clustering analysis (B). PC1: principal component 1, PC2: principal component 2, PaT: pasting temperature, PV: peak viscosity, TV: trough viscosity, FV: final viscosity, BD: breakdown, SB: setback. Dim1: dimension 1, Dim2: dimension 2.
Fig. 5 Distribution of U.S. rice varieties using texture properties-related traits. Principal component analysis (A) and K-means clustering analysis (B). PC1: principal component 1, PC2: principal component 2, HN: hardness, AN: adhesiveness, TN: toughness, SN: stickiness. Dim1: dimension 1, Dim2: dimension 2.
Fig. 6 Relationship among grain-, pasting-, and texture-related traits. Principal component analysis (A) and correlation analysis (B). PC1: principal component 1, PC2: principal component 2. G_UV1-4 mean clusters by K-means clustering using grain-related traits (Fig. 2B). GL: grain length, GW: grain width, GT: grain thickness, RLW: ratio of length to width, TGW: 1,000-grain weight, PaT: pasting temperature, PV: peak viscosity, TV: trough viscosity, FV: final viscosity, BD: breakdown, SB: setback, HN: hardness, AN: adhesiveness, TN: toughness, SN: stickiness.
Characterization of Grain-Related Traits and Pasting and Texture Properties of United State Rice Varieties in Korea

Yield-related traits of U.S. rice varieties

Variety HDz (DAS) CL
(cm)
PL
(cm)
PN NS RRG
(%)
Yield
(g)
Boramchan 109ay 65c 20efgh 11a 114fg 94.1abc 583a
Rico1 102cd 72bc 22cdefg 10ab 144abcd 91.0cd 595a
Pecos 97f 73bc 18h 9c 99g 94.4abc 408cd
Saturn 98ef 83a 22cd 8c 131cde 90.2d 333f
Mars 102cd 79ab 22defg 8c 158a 90.0d 409cd
Saber 105b 71bc 24c 8c 147abc 95.8a 395cdef
Shortlabelle 100cd 71bc 20gh 9abc 121ef 91.5bcd 390cdef
A008 106b 86a 28a 8c 158a 91.4bcd 393cdef
Bluebelle 105b 84a 26b 9c 142abcd 94.0abc 420bcd
Rajbonnet 106b 80ab 23cd 9bc 139bcd 93.3abcd 476b
Cypress 106b 65c 22cde 9c 117ef 92.4abcd 404cde
Cocodrie 102c 72bc 23cd 8c 153ab 91.5bcd 477b
Lacassine 109a 70bc 22cdef 8c 130def 94.1abc 444bc
Jefferson 101cd 67c 20fgh 8c 100g 94.3abc 370def
A020 100de 67c 19h 9bc 78h 95.1ab 342ef
Totalx 103 74 22 9 130 92.8 418
Range 97-109 65-86 18-28 8-10 99-158 90.0-95.8 333-595

Morphological characteristics of spikelet and grain of U.S. rice varieties

Variety Lemma and palea Apiculus
color
Stigma
color
Sterile lemma
color
Awning
pubesence color
Boramchan short hair straw straw white straw absent
Rico1 glabrous straw brown white straw absent
Pecos glabrous gold purple purple straw absent
Saturn glabrous straw straw white straw absent
Mars glabrous straw straw white straw absent
Saber glabrous straw brown white straw absent
Shortlabelle glabrous straw brown white straw absent
A008 glabrous straw straw white straw absent
Bluebelle glabrous gold brown purple straw absent
Rajbonnet glabrous straw brown white straw absent
Cypress glabrous straw brown white straw absent
Cocodrie glabrous straw brown white straw absent
Lacassine glabrous straw brown white straw absent
Jefferson glabrous straw straw white straw absent
A020 glabrous straw brown white straw absent

Grain-related traits of U.S. rice varieties

Variety GLz (mm) GW
(mm)
GT
(mm)
RLW TGW Clustery Allele combinationx
Boramchan 5.04hw 3.08a 2.05a 1.64h 22.9c G_UV1 CU1
Rico1 5.69g 2.70b 1.84b 2.11g 20.9d G_UV2 CU2
Pecos 5.71g 2.73b 1.81b 2.09g 20.4de G_UV2 CU2
Saturn 5.93fg 2.67b 1.86b 2.22g 20.7d G_UV2 CU3
Mars 6.08f 2.65b 1.82b 2.30g 19.6ef G_UV2 CU3
Saber 6.59e 2.09ef 1.66d 3.15ef 16.6i G_UV3 CU4
Shortlabelle 6.71de 2.16def 1.72c 3.12f 18.1gh G_UV3 CU5
A008 7.04cd 2.08f 1.64d 3.38bcde 17.6h G_UV3 CU5
Bluebelle 7.35bc 2.14def 1.73c 3.43bcd 18.8fg G_UV3 CU5
Rajbonnet 7.37bc 2.05f 1.65d 3.59ab 17.6h G_UV3 CU5
Cypress 7.26bc 2.20de 1.74c 3.31cdef 19.4f G_UV3 CU5
Cocodrie 7.40bc 2.20d 1.75c 3.37bcde 20.5de G_UV3 CU5
Lacassine 7.57b 2.14def 1.74c 3.55abc 20.8d G_UV3 CU5
Jefferson 7.56b 2.34c 1.81b 3.25def 23.9b G_UV4 CU5
A020 8.12a 2.22d 1.85b 3.68a 24.9a G_UV4 CU6
Totalu 6.88 2.31 1.76 3.04 20.0
Range 5.69-8.12 2.05-2.73 1.64-1.86 2.09-3.68 16.6-24.9

Characterization of grain-related traits of U.S. rice varieties classified by K-means clustering analysis

Cluster n Varietyz Brown rice
GLy GW GT RLW TGW
G_UV1 1 BRC 5.04cx 3.08a 2.05a 1.64c 22.9ab
G_UV2 4 RC1, PCS, ST, MS 5.85b 2.69b 1.83b 2.18b 20.4bc
G_UV3 8 SB, SLBL, A008, BLBL, RJBN, CPRS, CCDR, LCS, 7.16a 2.13d 1.70c 3.36a 18.7c
G_UV4 2 JFS, A020 7.84a 2.28c 1.83b 3.46a 24.4a
Total 15 6.76 2.36 1.78 2.95 20.19
C.V. (%) 4.70 2.20 2.20 5.80 6.10

Pasting properties of U.S. rice varieties

Variety Pasting temperature
(℃)
Peak viscosity
(RVU)
Trough viscosity
(RVU)
Final viscosity
(RVU)
Breakdown
(RVU)
Setback
(RVU)
Cluster
Boramchan 72.8gz 269de 206a 297a 62i 28bc R_UV1
Rico1 75.6f 270d 162bc 270bc 108fg -1e R_UV1
Pecos 76.5e 303c 171b 264bcd 132cd -40g R_UV2
Saturn 76.4e 336a 171b 256cd 165b -80h R_UV2
Mars 76.5e 322b 142d 228ef 180a -94i R_UV2
Saber 80.0cd 261ef 166bc 297a 95h 36ab R_UV1
Shortlabelle 80.7c 242h 116g 237e 126d -5ef R_UV4
A008 76.5e 296c 157c 267bc 139c -29g R_UV2
Bluebelle 79.8d 250gh 121fg 250d 129cd 0e R_UV4
Rajbonnet 79.9d 250gh 127efg 271b 123de 20cd R_UV4
Cypress 79.7d 250gh 136de 269bc 114ef 20cd R_UV4
Cocodrie 81.5b 173i 99h 216f a73i 44a R_UV3
Lacassine 79.7d 252g 138de 264bcd 114ef 12d R_UV4
Jefferson 80.3cd 266de 132def 251d 135cd -15f R_UV4
A020 82.7a 257fg 156c 290a 101gh 33ab R_UV4
Totaly 79.0 266 143 259 124 -7
Range 75.6-82.7 173-336 99-171 216-298 73-180 -94-44

Characterization of of pasting properties-related traits U.S. rice varieties classified by K-means clustering analysis

Cluster n Varietyz Pasting temperature
(℃)
Peak viscosity
(RVU)
Trough viscosity
(RVU)
Final viscosity
(RVU)
Breakdown
(RVU)
Setback
(RVU)
R_UV1 3 BRC, RC1, SB 76.2by 267b 178a 288a 88bc 22a
R_UV2 4 PCS, ST, MS, A008 76.5b 314a 160ab 254a 154a -60b
R_UV3 1 CCDR 81.5a 173c 099c 216b 73c 44a
R_UV4 7 SLBL, BLBL, RJBN, CPRS, LCS, JFS, A020 80.4a 253b 132b 262a 120ab 9a
Total 15 78.6 266 147 262 120 -5
C.V. 2.2 4.2 10.9 6.6 14.7 -11.1

Texture properties of cooked rice of U.S. rice varieties

Variety Hardness Adhesiveness Toughness Stickiness Cluster
Boramchan 50.2fz 53.8a 37.4e 60.8a T_UV1
Rico1 65.4def 44.4a 54.9c 45.6d T_UV2
Pecos 51.4f 52.7a 41.9de 58.7ab T_UV1
Saturn 86.4bc 23.5bc 79.1a 24.2ef T_UV4
Mars 59.6f 53.2a 44.7de 50.9cd T_UV2
Saber 82.6bc 16.1cd 79.7a 19.5f T_UV4
Shortlabelle 63.1ef 52.9a 43.3de 53.1bc T_UV2
A008 54.2f 46.7a 48.8cd 45.4d T_UV2
Bluebelle 77.2cde 15.9cd 79.8a 19.9f T_UV4
Rajbonnet 78.1cde 20.1cd 77.8a 22.6f T_UV4
Cypress 81.3bcd 25.4bc 77.9a 27.1ef T_UV4
Cocodrie 110.5a 13.6d 83.2a 19.2f T_UV3
Lacassine 86.4bc 18.9cd 80.2a 24.6ef T_UV4
Jefferson 80.6bcd 25.2bc 69.7b 26.2ef T_UV4
A020 95.1b 29.7b 69.3b 31.4e T_UV4
Totaly 76.6 31.3 66.5 33.4
Range 51.4-110.5 13.6-53.2 41.9-83.2 19.1-58.7

Characterization of of texture properties-related traits U.S. rice varieties classified by K-means clustering analysis

Cluster n Varietyz Hardness Adhesiveness Toughness Stickiness
T_UV1 2 BRC, PCS 50.8cy 53.3a 39.7b 59.7a
T_UV2 4 RC1, MS, SLBL, A008 60.6c 49.3a 47.9b 48.7b
T_UV3 1 CCDR 110.5a 13.6b 83.2a 19.2c
T_UV4 8 ST, SB, BLBL, RJBN, CPRS, LCS, JFS, A020 83.5b 21.9b 76.7a 24.4c
Total 15 74.8 32.8 64.5 35.3
C.V. 7.1 13.9 7.1 10.7
Table 1 Yield-related traits of U.S. rice varieties

zHD: heading date, DAS: days after seeding, CL: culm length, PL: panicle length, PN: number of panicles per hill, NS: number of spikelets per panicle, RRG: ratio of ripened grain

yMeans with same letters in a column are not significantly different at p<0.05 (ANOVA followed by DMRT)

xThe value of total is calculated for U.S. rice varieties (n=14)

Table 2 Morphological characteristics of spikelet and grain of U.S. rice varieties
Table 3 Grain-related traits of U.S. rice varieties

zGL: grain length, GW: grain width, GT: grain thickness, RLW: ratio of length to width, TGW: 1,000-grain weight

yG_UV1-4: clusters classified by K-means clustering

xCU1: GW2-GS3_C-qGL3-qLGY3-qsw5_N-gs5-TGW6-GW7-GW8CU2: GW2-GS3_C-qGL3-qLGY3-qSW5-gs5-TGW6-GW7-GW8CU3: GW2-GS3_C-qGL3-qlgy3-qSW5-gs5-TGW6-GW7-GW8CU4: GW2-GS3_B-qgl3-qlgy3-qSW5-gs5-TGW6-GW7-GW8CU5: GW2-gs3-qGL3-qlgy3-qSW5-gs5-TGW6-GW7-GW8CU6: GW2-gs3-qGL3-qlgy3-qSW5-gs5-TGW6-GW7-gw8

wMeans with same letters in a column are not significantly different at p<0.05 (ANOVA followed by DMRT)

uThe value of total is calculated for U.S. rice varieties (n=14)

Table 4 Characterization of grain-related traits of U.S. rice varieties classified by K-means clustering analysis

zBRC: Boramchan, RC1: Rico1, PCS: Pecos, ST: Saturn, MS: Mars, SB: Saber, SLBL: Shortlabelle, BLBL: Bluebelle, RJBN: Rajbonnet, CPRS: Cypress, CCDR: Cocodrie, LCS: Lacassine, JFS: Jefferson

yGL: grain length, GW: grain width, GT: grain thickness, RLW: ratio of length to width, TGW: 1,000-grain weight

xMeans with same letters in a column are not significantly different at p<0.05 (ANOVA followed by DMRT)

Table 5 Pasting properties of U.S. rice varieties

zMeans with same letters in a column are not significantly different at p<0.05 (ANOVA followed by DMRT)

yThe value of total is calculated for U.S. rice varieties (n=14)

Table 6 Characterization of of pasting properties-related traits U.S. rice varieties classified by K-means clustering analysis

zBRC: Boramchan, RC1: Rico1, PCS: Pecos, ST: Saturn, MS: Mars, SB: Saber, SLBL: Shortlabelle, BLBL: Bluebelle, RJBN: Rajbonnet, CPRS: Cypress, CCDR: Cocodrie, LCS: Lacassine, JFS: Jefferson

yMeans with same letters in a column are not significantly different at p<0.05 (ANOVA followed by DMRT)

Table 7 Texture properties of cooked rice of U.S. rice varieties

zMeans with same letters in a column are not significantly different at p<0.05 (ANOVA followed by DMRT)

yThe value of total is calculated for U.S. rice varieties (n=14)

Table 8 Characterization of of texture properties-related traits U.S. rice varieties classified by K-means clustering analysis

zBRC: Boramchan, RC1: Rico1, PCS: Pecos, ST: Saturn, MS: Mars, SB: Saber, SLBL: Shortlabelle, BLBL: Bluebelle, RJBN: Rajbonnet, CPRS: Cypress, CCDR: Cocodrie, LCS: Lacassine, JFS: Jefferson

yMeans with same letters in a column are not significantly different at p<0.05 (ANOVA followed by DMRT)