Performance and Inheritance of Rice Starch RVA Profile Characteristics

Abstract

Abstract: The classification and inheritance of rice starch RVA profiles were studied by testing RVA profiles of F₂ clonally propagated population and some varieties, including japonica, indica, and glutinous types. All the RVA profiles of accessions could be divided into six kinds based on the cluster analysis, that is A, B, C, D, E and F. Feature profile of sticky variety was type A. The profiles of indica varieties could be presented as B, C, D, E and F types and that of japonica varieties fell into D, E and F types. RVA profiles of the rice were mainly affected by apparent amylose content (AAC), but the difference of RVA profiles could also be detected in the varieties with similar AAC. The close relationship between RVA profile indices and sensory of low or middle AAC varieties suggested that the RVA profiles can be used as indirect index to evaluate eating and cooking quality. In four hybrid combinations, the component indices of RVA profiles of F₁were between those of its parents except peak viscosity and pasting temperature. Also, in F₂ clonally propagated population, all the components of the RVA profiles showed continuous segregation, suggesting that all of them were controlled by a series of minor genes, although Wx gene may play an important role in determining the RVA profiles. These results may provide some new information useful for rice quality breeding program.

Key words: rice, RVA profiles, apparent amylose content, eating quality, F2 clonally propagated population

YAN Chang-jie, LI Xin, ZHANG Rong, SUI Jiong-ming, LIANG Guo-hua, SHEN Xin-ping, GU Shi-liang, GU Ming-hong. Performance and Inheritance of Rice Starch RVA Profile Characteristics
[J]. RICE SCIENCE.

References

1 McKenzie K S, Rutger J N. Genetic analysis of amylose content, alkali spreading score, and grain dimensions in rice. Crop Sci, 1983, 23: 306–313.

2 He P, Li S G, Ma Y Q, Li J Z, Wang W M, Chen Y, Zhu L H. Genetic analysis of rice grain quality. Theor Appl Genet, 1999, 98: 502–508.

3 Gravois K A, Webb B D. Inheritance of long grain rice amylograph viscosity characteristics. Euphytica, 1997, 97: 25–29.

4 Bao J S, He P, Xia Y W, Chen Y, Zhu L H. RVA profile characteristics of rice mainly controlled by Wx gene. Chinese Sci Bull, 1999, 44(18): 1973–1976. (in Chinese with English abstract)

5 Wu D X, Shu Q Y, Xia Y W. Rapid identification of starch viscosity property of early indica rice varieties with different apparent amylose content by RVA profile. Chinese J Rice Sci, 2001, 15(1): 57–59. (in Chinese with English abstract)

6 Han X Z, Haymaker B R. Amylopectin fine structure and rice starch paste breakdown. J Cereal Sci, 2001, 34: 279–284.

7 Champagne E T, Bett K L, Vinyard B T, McClung A M, BartonⅡF E, Moldenhauer K, Linscombe S, McKenzie K. Correlation between cooked rice texture and Rapid Visco Analyser measurements. Cereal Chem, 1999, 76: 764–771.

8 Shu Q Y, Wu D X, Xia Y W, Gao M W, McClung A.

Studies on the apparent amylose content and starch viscosity of indica hybrid rice. J Zhejiang Agric Univ, 1998, 24(6): 621–626. (in Chinese with English abstract)

9 Wang C F, Yan C J, Dong X S, Liang G H, Gu M H. Construction and characteristic analysis of rice clonally propagated F₂ population. J Yangzhou Univ (Agric & Life Sci), 2002, 23(2): 41–45. (in Chinese with English abstract)

10 National Standards of the People’s Republic of China. GB/T17891- 1999. (in Chinese)

11 American Association of Cereal Chemistry (AACC). Methods 61-02 for RVA. 9th ed. St. Paul, MN: AACC, 1995.

12 Yan C J, Liang G H, Gu S L, Lu J F, Tang S Z, Gu M H. Characteristic and classification for sterility of hybrids from typical indica crossed with japonica (O. sativa). Acta Agron Sin, 2003, 29(4): 574–580. (in Chinese with English abstract)

13 Liu Q Q, Wang X W, Chen X H, Wang Z Y, Tang S Z, Hong M M, Gu M H. Effect of dominant waxy character on kernel weight of transgenic rice with antisense Wx gene. Sci Agric Sin, 2002, 35(2): 117–122. (in Chinese with English abstract)

14 Bao J S, Zheng X W, Xia Y W, He P, Shu Q Y, Lu X, Chen Y, Zhu L H. QTL mapping for the paste viscosity characteristics in rice (Oryza sativa L.). Theor Appl Genet, 2000, 100: 280–284.

15 Wu D X, Shu Q Y, Xia Y W. Assisted-selection for early indica rice with good eating quality by RVA profile. Acta Agron Sin, 2001, 27(2): 165–172. (in Chinese with English abstract)

[1]	Prathap V, Suresh KUMAR, Nand Lal MEENA, Chirag MAHESHWARI, Monika DALAL, Aruna TYAGI. Phosphorus Starvation Tolerance in Rice Through a Combined Physiological, Biochemical and Proteome Analysis [J]. Rice Science, 2023, 30(6): 8-.
[2]	Serena REGGI, Elisabetta ONELLI, Alessandra MOSCATELLI, Nadia STROPPA, Matteo Dell’ANNO, Kiril PERFANOV, Luciana ROSSI. Seed-Specific Expression of Apolipoprotein A-I_Milano Dimer in Rice Engineered Lines [J]. Rice Science, 2023, 30(6): 6-.
[3]	Sundus ZAFAR, XU Jianlong. Recent Advances to Enhance Nutritional Quality of Rice [J]. Rice Science, 2023, 30(6): 4-.
[4]	Kankunlanach KHAMPUANG, Nanthana CHAIWONG, Atilla YAZICI, Baris DEMIRER, Ismail CAKMAK, Chanakan PROM-U-THAI. Effect of Sulfur Fertilization on Productivity and Grain Zinc Yield of Rice Grown under Low and Adequate Soil Zinc Applications [J]. Rice Science, 2023, 30(6): 9-.
[5]	FAN Fengfeng, CAI Meng, LUO Xiong, LIU Manman, YUAN Huanran, CHENG Mingxing, Ayaz AHMAD, LI Nengwu, LI Shaoqing. Novel QTLs from Wild Rice Oryza longistaminata Confer Rice Strong Tolerance to High Temperature at Seedling Stage [J]. Rice Science, 2023, 30(6): 14-.
[6]	LIN Shaodan, YAO Yue, LI Jiayi, LI Xiaobin, MA Jie, WENG Haiyong, CHENG Zuxin, YE Dapeng. Application of UAV-Based Imaging and Deep Learning in Assessment of Rice Blast Resistance [J]. Rice Science, 2023, 30(6): 10-.
[7]	Md. Forshed DEWAN, Md. AHIDUZZAMAN, Md. Nahidul ISLAM, Habibul Bari SHOZIB. Potential Benefits of Bioactive Compounds of Traditional Rice Grown in South and South-East Asia: A Review [J]. Rice Science, 2023, 30(6): 5-.
[8]	Raja CHAKRABORTY, Pratap KALITA, Saikat SEN. Phenolic Profile, Antioxidant, Antihyperlipidemic and Cardiac Risk Preventive Effect of Chakhao Poireiton (A Pigmented Black Rice) in High-Fat High-Sugar induced Rats [J]. Rice Science, 2023, 30(6): 11-.
[9]	LI Qianlong, FENG Qi, WANG Heqin, KANG Yunhai, ZHANG Conghe, DU Ming, ZHANG Yunhu, WANG Hui, CHEN Jinjie, HAN Bin, FANG Yu, WANG Ahong. Genome-Wide Dissection of Quan 9311A Breeding Process and Application Advantages [J]. Rice Science, 2023, 30(6): 7-.
[10]	JI Dongling, XIAO Wenhui, SUN Zhiwei, LIU Lijun, GU Junfei, ZHANG Hao, Tom Matthew HARRISON, LIU Ke, WANG Zhiqin, WANG Weilu, YANG Jianchang. Translocation and Distribution of Carbon-Nitrogen in Relation to Rice Yield and Grain Quality as Affected by High Temperature at Early Panicle Initiation Stage [J]. Rice Science, 2023, 30(6): 12-.
[11]	Nazaratul Ashifa Abdullah Salim, Norlida Mat Daud, Julieta Griboff, Abdul Rahim Harun. Elemental Assessments in Paddy Soil for Geographical Traceability of Rice from Peninsular Malaysia [J]. Rice Science, 2023, 30(5): 486-498.
[12]	Monica Ruffini Castiglione, Stefania Bottega, Carlo Sorce, Carmelina SpanÒ. Effects of Zinc Oxide Particles with Different Sizes on Root Development in Oryza sativa [J]. Rice Science, 2023, 30(5): 449-458.
[13]	Tan Jingyi, Zhang Xiaobo, Shang Huihui, Li Panpan, Wang Zhonghao, Liao Xinwei, Xu Xia, Yang Shihua, Gong Junyi, Wu Jianli. ORYZA SATIVA SPOTTED-LEAF 41 (OsSPL41) Negatively Regulates Plant Immunity in Rice [J]. Rice Science, 2023, 30(5): 426-436.
[14]	Ammara Latif, Sun Ying, Pu Cuixia, Noman Ali. Rice Curled Its Leaves Either Adaxially or Abaxially to Combat Drought Stress [J]. Rice Science, 2023, 30(5): 405-416.
[15]	Liu Qiao, Qiu Linlin, Hua Yangguang, Li Jing, Pang Bo, Zhai Yufeng, Wang Dekai. LHD3 Encoding a J-Domain Protein Controls Heading Date in Rice [J]. Rice Science, 2023, 30(5): 437-448.