Response to Drought Stress of Wild Rice SSSLs at Booting Stage

doi:10.7668/hbnxb.20195230

Abstract

Abstract:

To reveal the mechanism of drought resistance rice in booting stage,six single chromosome segments substitution lines (SSSLs) constructed from Oryza meridionalis and O.glumaepatula and their recipient parent Huajingxian 74 (HJX74) were used as experimental materials for potted drought treatment.Six biochemical indexes during 0,5,10 days of drought treatment and 5 days of rewatering and 11 agronomic traits after setting stage were measured,and the drought tolerance of 7 materials was comprehensivly evaluated by correlation analysis and principal component analysis.The result showed that under drought stress,there were extremely significant difference in agronomic traits among the 7 materials.There were extremely significant difference between M78-1 and HJX74 in relative panicle length,relative empty grain number and relative grain number per panicle,and there was extremely significant difference between M148 and HJX74 in relative dented grain number,there were extremely significant differences between M107 and HJX74 in relative panicle length and relative number of secondary branches; six drought-tolerant QTLs were identified at booting stage,including qRPL1-1,qRPL2-1,qRNSB2-1,qRNDG11-1,qRNEG1-1,qRGNP1-1,which were distributed on chromosomes 1,2,and 11.The superoxide dismutase (SOD) activity and peroxidase(POD) activity increased by 3.76%—18.20% and 31.88%—100.00% after 5 days of drought,while malondialdehyde (MDA)concentration decreased by 41.07%—81.65%.After 10 days of drought,SOD activity and POD activity decreased by 9.20%—48.53% and 44.74%—79.79%,while malondialdehyde (MDA)concentration was extremely significantly higher than that on the 5th day of drought.Osmoregulatory substances such as proline,soluble sugar and soluble protein continued to increase at the 5 d and 10 d drought treatment stages,and the biochemical indexes basically returned to normal level after 5 days of rewater.The comprehensive analysis revealed that the eigenvector and contribution rates of relative seed setting rate,POD activity and proline were the largest,indicating that these three indexes could better represent the drought tolerance of rice at booting stage.In conclusion,drought stress can affect agronomic traits and biochemical indexes of rice at booting stage,and rice can regulate its metabolic process in response to drought stress.

Key words: Rice, Booting stage, Drought stress, Agronomic trait, Biochemical index, Comprehensive evaluation of drought tolerance

CHEN Ke, LIAO Bing, LIU Guoli, HUANG Xiuyan, HE Ping. Response to Drought Stress of Wild Rice SSSLs at Booting Stage[J]. Acta Agriculturae Boreali-Sinica, 2025, 40(2): 81-91. doi: 10.7668/hbnxb.20195230.

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Figures/Tables 9

References 33

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材料 Materials	供体名称 Donor name
HJX74	无
M148	南方野生稻
M135	南方野生稻
M78-1	南方野生稻
M77	南方野生稻
M107	南方野生稻
X24	展颖野生稻

材料 Materials	供体名称 Donor name
HJX74	无
M148	南方野生稻
M135	南方野生稻
M78-1	南方野生稻
M77	南方野生稻
M107	南方野生稻
X24	展颖野生稻

性状 Traits	HJX74	X24	M77	M78-1	M107	M135	M148
RPH	0.75±0.10A	0.77±0.08A	0.82±0.06A	0.83±0.07A	0.81±0.11A	0.67±0.23A	0.80±0.06A
RPL	0.80±0.21B	0.83±0.13B	0.92±0.10B	0.99±0.05A	1.01±0.10A	0.84±0.14B	0.88±0.09B
RNPB	0.92±0.09A	0.87±0.12A	0.92±0.22A	1.00±0.10A	1.07±0.13A	0.82±0.17A	0.90±0.11A
RNSB	0.62±0.37B	0.63±0.31B	0.49±0.18B	1.04±0.14B	1.59±0.67A	0.59±0.46B	0.67±0.25B
RNFG	0.11±0.11A	0.02±0.03A	0.118±0.17A	0.04±0.07A	0.03±0.05A	0.14±0.15A	0.12±0.06A
RNDG	0.58±0.77B	0.73±1.10B	0.73±0.71B	0.14±0.20B	0.06±0.13B	0.66±0.86B	4.84±4.06A
RNEG	0.91±0.49B	1.38±0.47B	1.23±0.53B	1.72±0.28A	1.15±0.48B	0.65±0.58B	0.62±0.42B
RGW	0.08±0.08A	0.01±0.02A	0.09±0.15A	0.02±0.03A	0.02±0.04A	0.13±0.13A	0.08±0.05A
RTGW	0.25±0.27A	0.27±0.33A	0.23±0.34A	0.26±0.20A	0.25±0.38A	0.57±0.35A	0.62±0.28A
RGNP	0.58±0.25B	0.70±0.22B	0.64±0.19B	0.95±0.16A	0.65±0.28B	0.43±0.28B	0.43±0.27B
RSSR	0.25±0.27A	0.04±0.06A	0.24±0.35A	0.03±0.06A	0.03±0.05A	0.40±0.35A	0.25±0.16A

性状 Traits	HJX74	X24	M77	M78-1	M107	M135	M148
RPH	0.75±0.10A	0.77±0.08A	0.82±0.06A	0.83±0.07A	0.81±0.11A	0.67±0.23A	0.80±0.06A
RPL	0.80±0.21B	0.83±0.13B	0.92±0.10B	0.99±0.05A	1.01±0.10A	0.84±0.14B	0.88±0.09B
RNPB	0.92±0.09A	0.87±0.12A	0.92±0.22A	1.00±0.10A	1.07±0.13A	0.82±0.17A	0.90±0.11A
RNSB	0.62±0.37B	0.63±0.31B	0.49±0.18B	1.04±0.14B	1.59±0.67A	0.59±0.46B	0.67±0.25B
RNFG	0.11±0.11A	0.02±0.03A	0.118±0.17A	0.04±0.07A	0.03±0.05A	0.14±0.15A	0.12±0.06A
RNDG	0.58±0.77B	0.73±1.10B	0.73±0.71B	0.14±0.20B	0.06±0.13B	0.66±0.86B	4.84±4.06A
RNEG	0.91±0.49B	1.38±0.47B	1.23±0.53B	1.72±0.28A	1.15±0.48B	0.65±0.58B	0.62±0.42B
RGW	0.08±0.08A	0.01±0.02A	0.09±0.15A	0.02±0.03A	0.02±0.04A	0.13±0.13A	0.08±0.05A
RTGW	0.25±0.27A	0.27±0.33A	0.23±0.34A	0.26±0.20A	0.25±0.38A	0.57±0.35A	0.62±0.28A
RGNP	0.58±0.25B	0.70±0.22B	0.64±0.19B	0.95±0.16A	0.65±0.28B	0.43±0.28B	0.43±0.27B
RSSR	0.25±0.27A	0.04±0.06A	0.24±0.35A	0.03±0.06A	0.03±0.05A	0.40±0.35A	0.25±0.16A

性状 Traits	最小值 Min	最大值 Max	均值 Mean	标准偏差 s	变异系数 CV
RPH	0.34	0.98	0.78	0.12	15.49
RPL	0.57	1.18	0.90	0.14	15.72
RNPB	0.56	1.31	0.93	0.16	16.76
RNSB	0.00	2.66	0.80	0.51	63.18
RNFG	0.00	0.53	0.08	0.11	133.19
RNDG	0.00	9.75	1.11	2.20	201.04
RNEG	0.17	2.04	1.10	0.58	53.36
RGW	0.00	0.53	0.08	0.11	133.19
RTGW	0.00	1.02	0.35	0.34	96.29
RGNP	0.00	1.13	0.63	0.28	45.00
RSSR	0.00	1.06	0.18	0.25	142.82

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