谷子芽期耐盐碱综合鉴定及评价

doi:10.3724/SP.J.1006.2020.04064

Abstract

Abstract:

In the present study, the evaluation of 53 main foxtail millet cultivars was carried out under saline-alkaline mixed stress (100 mmol L^-1, NaCl : NaHCO₃ = 4 : 1). The results showed that germination potential, germination rate, root length, shoot length, fresh root weight and fresh shoot weight of the 53 cultivars were inhibited, among which with root length most affected by the salt and alkaline condition. Exposed to such a stress condition, significant or extremely significant positive correlations were observed for relative germination potential and relative germination rate, relative root length and relative shoot length, and relative fresh root weight and relative fresh shoot weight. 14 traits were integrated into four principal components with a cumulative contribution rate of 90.4% through principal component analysis (PCA). Composite scores for saline-alkaline tolerance were calculated from membership function with scores of the four principal components. The 53 cultivars were assigned to six different groups of saline-alkaline resistance by using cluster analysis, including 2 highly resistant, 16 moderately resistant, 17 lower resistant, 6 sensitive, 9 susceptible and 3 extremely intolerant foxtail millet cultivars. Meanwhile, a regression equation, D° = 0.298 + 0.037 X₂ + 0.144X₃ + 0.018X₆ + 0.209X₇ - 0.183X₉ + 0.115X₁₁ - 0.201X₁₂ + 0.112X₁₃ - 0.101X₁₄ + 0.284X₁₅, was established to estimate the tolerance of foxtail millet cultivars to saline-alkaline stress. Relative germination rate, salt injury rates for root length and shoot length, and root-shoot ratio could be regarded as the indicators of assessing the resistance of foxtail millet to saline-alkaline mixed stress.

Key words: foxtail millet, saline-alkaline stress, principal component analysis, membership function, regression analysis

CHEN Er-Ying, WANG Run-Feng, QIN Ling, YANG Yan-Bing, LI Fei-Fei, ZHANG Hua-Wen, WANG Hai-Lian, LIU Bin, KONG Qing-Hua, GUAN Yan-An. Comprehensive identification and evaluation of foxtail millet for saline-alkaline tolerance during germination[J].Acta Agronomica Sinica, 2020, 46(10): 1591-1604.

Figures/Tables 9

Table 1

Foxtail millet cultivars and breeding institutes"

编号 No.	品种 Cultivars	育成单位 Breeding institutes	编号 No.	品种 Cultivars	育成单位 Breeding institutes
1	鲁谷1号 Lugu 1	山东省农业科学院 SDAAS	28	豫谷13 Yugu 13	安阳市农业科学院 AYAAS
2	鲁谷10号 Lugu 10	山东省农业科学院 SDAAS	29	豫谷17 Yugu 17	河南省农业科学院 HNAAS
3	济谷13 Jigu 13	山东省农业科学院 SDAAS	30	豫谷18 Yugu 18	安阳市农业科学院 AYAAS
4	济谷16 Jigu 16	山东省农业科学院 SDAAS	31	豫谷31 Yugu 31	安阳市农业科学院 AYAAS
5	济谷17 Jigu 17	山东省农业科学院 SDAAS	32	豫谷32 Yugu 32	安阳市农业科学院 AYAAS
6	济谷18 Jigu 18	山东省农业科学院 SDAAS	33	安13-5079 An 13-5079	安阳市农业科学院 AYAAS
7	济谷19 Jigu 19	山东省农业科学院 SDAAS	34	郑谷607 Zhenggu 607	河南省农业科学院 HNAAS
8	济谷20 Jigu 20	山东省农业科学院 SDAAS	35	衡谷16 Henggu 16	衡水市农业科学研究院 HSAAS
9	济谷21 Jigu 21	山东省农业科学院 SDAAS	36	衡谷17 Henggu 17	衡水市农业科学研究院 HSAAS
10	济谷22 Jigu 22	山东省农业科学院 SDAAS	37	保谷18 Baogu 18	保定市农业科学研究院 BDAAS
11	中谷2号 Zhonggu 2	中国农业科学院 CAAS	38	保谷23 Baogu 23	保定市农业科学研究院 BDAAS
12	中谷6号 Zhonggu 6	中国农业科学院 CAAS	39	邯谷2号 Hangu 2	邯郸市农业科学研究院 HDAAS
13	中谷7号 Zhonggu 7	中国农业科学院 CAAS	40	沧谷9号 Canggu 9	沧州市农林科学院 CZAFS
14	冀谷19 Jigu 19	河北省农林科学院 HBAFS	41	沧15-298 Cang 15-298	沧州市农林科学院 CZAFS
15	冀谷20 Jigu 20	河北省农林科学院 HBAFS	42	延谷2号 Yangu 2	延安市农业科学研究所 YAIAS
16	冀谷26 Jigu 26	河北省农林科学院 HBAFS	43	秦谷3号 Qingu 3	延安市农业科学研究所 YAIAS
17	冀谷40 Jigu 40	河北省农林科学院 HBAFS	44	晋谷45号 Jingu 45	山西省农业科学院 SXAAS
18	冀谷41 Jigu 41	河北省农林科学院 HBAFS	45	长谷4号 Changgu 4	山西省农业科学院 SXAAS
19	冀谷42 Jigu 42	河北省农林科学院 HBAFS	46	晋谷46号 Jingu 46	山西省农业科学院 SXAAS
20	聊农1号 Liaonong 1	聊城市农业科学研究院 LCAAS	47	陇谷10 Longgu 10	甘肃省农业科学院 GAAAS
21	泰谷002 Taigu 002	泰安市农业科学研究院 TAAAS	48	龙谷34 Longu 34	黑龙江省农业科学院 HLJAAS
22	泰谷003 Taigu 003	聊城市农业科学研究院 LCAAS	49	公矮8号 Gongai 8	吉林省农业科学院 JLAAS
23	C17	河南省农业科学院 HNAAS	50	赤谷8号 Chigu 8	赤峰市农业科学研究院 CFAAS
24	14H481	邯郸市农业科学院 HDAAS	51	赤谷7号 Chigu 7	赤峰市农业科学研究院 CFAAS
25	豫谷7号 Yugu 7	安阳市农业科学院 AYAAS	52	公矮2号 Gongai 2	吉林省农业科学院 JLAAS
26	豫谷8号 Yugu 8	河南省农业科学院 HNAAS	53	龙谷31 Longgu 31	黑龙江省农业科学院 HLJAAS
27	豫谷9号 Yugu 9	安阳市农业科学院 AYAAS

Table 1

Table 2

Fig. 1

Fig. 2

Table 3

Table 4

Table 5

Value of each comprehensive index (Cl), index weight, μ(X), and comprehensive evaluation value (D)"

编号 No.	品种 Variety	Z₁	Z₂	Z₃	Z₄	μ(X₁)	μ(X₂)	μ(X₃)	μ(X₄)	综合得分值 Comprehensive assessment values (D)	排名 Rank
1	鲁谷1号Lugu 1	1.271	-1.367	1.084	0.551	1.000	0.175	0.703	0.596	0.742	6
2	鲁谷 lOLugu 10	1.233	-1.001	2.395	1.398	0.992	0.251	1.000	0.773	0.817	1
3	济谷 13 Jigu 13	0.177	0.247	0.224	0.434	0.760	0.511	0.509	0.572	0.651	23
4	济谷 16 Jigu 16	0.182	-0.281	2.202	-0.192	0.761	0.401	0.956	0.441	0.683	17
5	济谷 17 Jigu 17	0.516	-0.621	1.162	1.385	0.835	0.330	0.721	0.771	0.706	11
6	济谷 18 Jigu 18	0.400	-0.659	1.178	0.944	0.809	0.322	0.724	0.678	0.682	18
7	济谷 19 Jigu 19	0.805	1.282	0.446	-0.777	0.898	0.726	0.559	0.319	0.750	4
8	济谷 20 Jigu 20	-0.313	1.377	0.145	1.436	0.653	0.746	0.491	0.781	0.661	20
9	济谷 21 Jigu 21	1.198	-0.138	0.371	0.915	0.984	0.431	0.542	0.672	0.770	3
10	济谷 22 Jigu 22	0.906	0.933	0.795	0.885	0.920	0.653	0.638	0.666	0.795	2
11	中谷2号Zhonggu 2	1.204	-0.573	-0.411	-0.601	0.985	0.340	0.365	0.355	0.691	13
12	中谷6号Zhonggu 6	0.931	-0.062	-0.070	0.832	0.926	0.447	0.442	0.655	0.724	8
13	中谷7号Zhonggu 7	-0.425	-2.210	1.844	-2.302	0.629	0.000	0.875	0.000	0.471	42
14	冀谷 19 Jigu 19	1.075	-0.004	0.359	0.089	0.957	0.458	0.539	0.500	0.742	5
15	冀谷 20 Jigu 20	0.579	0.016	-0.018	-1.365	0.848	0.463	0.454	0.196	0.640	27
16	冀谷 26 Jigu 26	0.495	0.936	-0.612	-0.508	0.830	0.654	0.319	0.375	0.668	19
17	冀谷 40 Jigu 40	0.161	1.588	-0.992	0.239	0.757	0.789	0.233	0.531	0.660	21
18	冀谷 41 Jigu 41	-0.307	2.258	-0.669	-0.042	0.654	0.929	0.306	0.472	0.639	28
19	冀谷 42 Jigu 42	0.654	1.114	0.200	-0.432	0.865	0.691	0.503	0.391	0.724	9
20	聊农 1 号 Liaonong 1	0.336	-0.090	-2.022	-0.957	0.795	0.441	0.000	0.281	0.547	40
21	泰谷 0〇² Taigu 002	0.448	0.427	-0.952	-0.168	0.820	0.548	0.242	0.446	0.636	29
22	泰谷 003 Taigu 003	-1.615	-0.043	-1.647	1.923	0.368	0.450	0.085	0.883	0.396	49
23	C17	-0.675	-0.980	-1.039	-1.137	0.574	0.256	0.222	0.243	0.420	46
24	14H481	0.051	0.327	0.009	-1.227	0.733	0.527	0.460	0.225	0.595	34
25	豫谷7号Yugu 7	0.933	-0.178	-0.378	-0.234	0.926	0.422	0.372	0.432	0.686	15
26	豫谷8号Yugu 8	0.058	1.402	-0.242	-0.259	0.734	0.751	0.403	0.427	0.655	22
27	豫谷9号Yugu 9	0.710	0.040	-0.294	0.595	0.877	0.468	0.391	0.605	0.690	14
28	豫谷 13 Yugu 13	0.165	0.116	-0.521	0.952	0.758	0.483	0.340	0.680	0.629	30
29	豫谷 17 Yugu 17	0.260	-0.186	-1.092	-0.201	0.779	0.421	0.210	0.439	0.582	35
30	豫谷 18 Yugu 18	-1.141	-0.762	-0.809	-0.668	0.472	0.301	0.275	0.341	0.393	50
编号 No.	品种 Variety	Z₁	Z₂	Z₃	Z₄	μ(X₁)	μ(X₂)	μ(X₃)	μ(X₄)	综合得分值 Comprehensive assessment values (D)	排名 Rank
31	豫谷 31 Yugu31	-2.607	-0.433	0.321	0.217	0.151	0.369	0.530	0.526	0.293	52
32	豫谷 32 Yugu 32	-3.295	0.714	1.230	-0.520	0.000	0.608	0.736	0.372	0.277	53
33	安 13-5079 An 13-5079	0.829	-0.439	-1.288	-0.774	0.903	0.368	0.166	0.319	0.619	31
34	郑谷 607 Zhenggu 607	0.719	0.180	-0.841	-0.866	0.879	0.497	0.267	0.300	0.646	25
35	衡谷 16Henggu 16	-0.705	-2.002	-0.553	-0.798	0.567	0.043	0.333	0.314	0.397	48
36	衡谷 17Henggu 17	-1.589	-0.660	0.689	-0.319	0.374	0.322	0.614	0.414	0.404	47
37	保谷 18Baogu 18	-1.905	2.601	1.583	0.890	0.304	1.000	0.816	0.667	0.564	38
38	保谷 23 Baogu 23	-1.312	-1.750	-1.464	0.278	0.434	0.096	0.126	0.539	0.328	51
39	邯谷2号Hangu 2	0.404	-0.135	-0.704	-0.238	0.810	0.431	0.298	0.431	0.614	32
40	沧谷9号Canggu 9	-0.015	0.650	2.115	-0.730	0.718	0.594	0.937	0.329	0.685	16
41	沧 15-298 Cang 15-298	0.761	-1.101	0.349	2.314	0.888	0.231	0.537	0.965	0.707	10
42	延谷2号Yangu 2	-0.011	-1.133	-1.054	2.483	0.719	0.224	0.219	1.000	0.570	36
43	秦谷3号Qingu 3	0.325	-1.580	-0.037	-0.371	0.793	0.131	0.449	0.403	0.563	39
44	晋谷 45 Jingu 45	0.302	-0.101	0.572	-1.838	0.788	0.438	0.587	0.097	0.613	33
45	长谷4号Changgu 4	-1.177	-0.663	1.023	-0.315	0.464	0.322	0.689	0.415	0.464	43
46	晋谷 46 Jingu 46	-1.198	0.086	-0.009	-0.741	0.459	0.477	0.456	0.326	0.448	44
47	陇谷 10 Longgu 10	-0.565	0.158	-0.020	1.113	0.598	0.492	0.453	0.714	0.566	37
48	龙谷 34 Longgu 34	0.140	0.969	0.179	-0.756	0.752	0.661	0.498	0.323	0.650	24
49	公矮8号Gong’ai 8	-0.207	-0.069	-1.157	0.327	0.676	0.445	0.196	0.549	0.542	41
50	赤谷8号Chigu 8	0.829	0.527	0.207	-1.224	0.903	0.569	0.505	0.225	0.702	12
51	赤谷7号Chigu 7	0.685	1.563	-0.188	-0.478	0.872	0.784	0.415	0.381	0.732	7
52	公矮2号Gong’ai2	-1.256	-0.355	-0.858	1.068	0.447	0.386	0.264	0.704	0.433	45
53	龙谷 31 Longgu 31	0.573	0.064	-0.737	-0.231	0.847	0.473	0.291	0.433	0.641	26
		权重 Index weight (%)				0.536	0.206	0.153	0.105

Table 5

Fig. 3

Table 6

Accuracy analysis of regression equation"

编号 No.	品种 Cultivar	回归值 Regression value	原始值 Primary value	差值 Difference	估计精度 Evaluation accuracy (%)
1	鲁谷1号 Lugu 1	0.7420	0.7422	-0.00017	99.98
2	鲁谷10 Lugu 10	0.8172	0.8173	-0.00017	99.98
3	济谷13 Jigu 13	0.6504	0.6506	-0.00022	99.98
4	济谷16 Jigu 16	0.6831	0.6833	-0.00022	99.98
5	济谷17 Jigu 17	0.7062	0.7064	-0.00018	99.98
6	济谷18 Jigu 18	0.6821	0.6821	0.00004	100.00
7	济谷19 Jigu 19	0.7498	0.7499	-0.00004	100.00
8	济谷20 Jigu 20	0.6608	0.6607	0.00006	99.99
9	济谷21 Jigu 21	0.7695	0.7695	0.00003	100.00
10	济谷22 Jigu 22	0.7952	0.7952	-0.00002	100.00
11	中谷2号 Zhonggu 2	0.6912	0.6913	-0.00014	99.99
12	中谷6号 Zhonggu 6	0.7246	0.7244	0.00012	99.99
13	中谷7号 Zhonggu 7	0.4706	0.4708	-0.00017	99.98
14	冀谷19 Jigu 19	0.7422	0.7424	-0.00016	99.98
15	冀谷20 Jigu 20	0.6399	0.6401	-0.00022	99.98
16	冀谷26 Jigu 26	0.6680	0.6679	0.00006	99.99
17	冀谷40 Jigu 40	0.6600	0.6598	0.00021	99.98
编号 No.	品种 Cultivar	回归值 Regression value	原始值 Primary value	差值 Difference	估计精度 Evaluation accuracy (%)
18	冀谷41 Jigu 41	0.6388	0.6386	0.00016	99.98
19	冀谷42 Jigu 42	0.7239	0.7240	-0.00010	99.99
20	聊农1号 Liaonong 1	0.5469	0.5465	0.00032	99.97
21	泰谷002 Taigu 002	0.6362	0.6361	0.00004	100.00
22	泰谷003 Taigu 003	0.3958	0.3955	0.00022	99.98
23	C17	0.4201	0.4199	0.00024	99.98
24	14H481	0.5954	0.5955	-0.00001	100.00
25	豫谷7号 Yugu 7	0.6856	0.6857	-0.00003	100.00
26	豫谷8号 Yugu 8	0.6548	0.6548	-0.00005	100.00
27	豫谷9号 Yugu 9	0.6899	0.6899	0.00005	100.00
28	豫谷13 Yugu 13	0.6291	0.6290	0.00005	100.00
29	豫谷17 Yugu 17	0.5824	0.5823	0.00014	99.99
30	豫谷18 Yugu 18	0.3929	0.3927	0.00016	99.98
31	豫谷31 Yugu 31	0.2932	0.2932	0.00005	100.00
32	豫谷32 Yugu 32	0.2770	0.2770	0.00003	100.00
33	安13-5079 An 13-5079	0.6190	0.6189	0.00005	99.99
34	郑谷607 Zhenggu 607	0.6460	0.6460	0.00005	100.00
35	衡谷16 Henggu 16	0.3968	0.3968	0.00005	99.99
36	衡谷17 Henggu 17	0.4040	0.4040	0.00002	100.00
37	保谷18 Baogu 18	0.5640	0.5642	-0.00019	99.98
38	保谷23 Baogu 23	0.3284	0.3282	0.00014	99.99
39	邯谷2号 Hangu 2	0.6140	0.6140	-0.00002	100.00
40	沧谷9号 Canggu 9	0.6851	0.6853	-0.00023	99.98
41	沧15-298 Cang 15-298	0.7068	0.7068	-0.00001	100.00
42	延谷2号 Yangu 2	0.5700	0.5699	0.00002	100.00
43	秦谷3号 Qingu 3	0.5629	0.5630	-0.00003	100.00
44	晋谷45 Jingu 45	0.6126	0.6127	-0.00010	99.99
45	长谷4 Changgu 4	0.4639	0.4639	-0.00003	100.00
46	晋谷46 Jingu 46	0.4486	0.4485	0.00010	99.99
47	陇谷10 Longgu 10	0.5660	0.5660	0.00001	100.00
48	龙谷34 Longgu 34	0.6496	0.6496	0.00000	100.00
49	公矮8号 Gong’ai 8	0.5420	0.5418	0.00011	99.99
50	赤谷8号 Chigu 8	0.7022	0.7023	-0.00003	100.00
51	赤谷7号 Chigu 7	0.7324	0.7325	-0.00006	99.99
52	公矮2号 Gong’ai 2	0.4328	0.4329	-0.00011	99.99
53	龙谷31 Longgu 31	0.6411	0.6413	-0.00021	99.98

Table 6

References 34

[1]	Liang W X, Ma X L, Wang P, Liu L Y. Plant salt-tolerance mechanism: a review. Biochem Biophys Res Commun, 2018,495:286-291. doi: 10.1016/j.bbrc.2017.11.043 pmid: 29128358
[2]	Sun H, Meng M H, Yan Z H, Lin Z X, Nie X H, Yang X Y. Genome-wide association mapping of stress tolerance traits in cotton. Crop J, 2019,7:77-88. doi: 10.1016/j.cj.2018.11.002
[3]	Wu H H. Plant salt tolerance and Na⁺sensing and tranport. Crop J, 2018,6:215-225. doi: 10.1016/j.cj.2018.01.003
[4]	Shrivastava P, Kumar R. Soil salinity: a serious environmental issue and plant growth promoting bacteria as one of the tools for its alleviation. Saudi J Biol Sci, 2015,22:123-131. doi: 10.1016/j.sjbs.2014.12.001 pmid: 25737642
[5]	李丰先, 周宇飞, 王艺陶, 孙璐, 白薇, 闫彤, 许文娟, 黄瑞冬. 高粱品种萌发期耐碱性筛选与综合鉴定. 中国农业科学, 2013,46:25-34.
	Li F X, Zhou Y F, Wang Y T, Sun L, Bai W, Yan T, Xu W J, Huang R D. Screening and identification of sorghum cultivars for alkali tolerance during germination. Sci Agric Sin, 2013,46:25-34 (in Chinese with English abstract).
[6]	景宇鹏, 连海飞, 李焕春, 史培, 杜超, 刘梅, 常新娟. 玉米耐盐碱能力及评价指标筛选研究. 中国农业科技导报, 2018,20(11):94-104.
	Jing Y P, Lian H F, Li H C, Shi P, Du C, Liu M, Chang X J. Study on saline-alkaline tolerance ability and evaluation index selection for corn. J Agric Sci Technol China, 2018,20(11):94-104 (in Chinese with English abstract).
[7]	信彩云, 周学标, 刘奇华, 谢先芝, 赵庆雷, 王瑜, 朱其松, 陈博聪, 王佳, 马佳清. 黄河三角洲盐碱土条件下水稻苗期耐盐指标筛选. 山东农业科学, 2017,49(1):23-28.
	Xin C Y, Zhou X B, Liu Q H, Xie X Z, Zhao Q L, Wang Y, Zhu Q S, Chen B C, Wang J, Ma X Q. Screening of salt tolerant indexes for rice seedlings under salinity conditions of the Yellow River delta. Shandong Agric Sci, 2017,49(1):23-28 (in Chinese with English abstract).
[8]	于莹, 张树权, 郭永利, 姚玉波, 周菲, 赵东升, 刘继忠, 李文华. 31份玉米自交系萌发期耐盐碱性综合评价. 东北农业大学学报, 2018,49(9):9-19.
	Yu Y, Zhang S Q, Guo Y L, Yao Y B, Zhou F, Zhao D S, Liu J Z, Li W H. Comprehensive evaluation of saline-alkaline tolerance of 31 maize inbred lines at germination stage. J Northeast Agric Univ, 2018,49(9):9-19 (in Chinese with English abstract).
[9]	高春华, 朱金英, 张华文, 田艺心, 高凤菊. 38 个粒用高粱品种芽期耐盐性的综合鉴定及评价. 核农学报, 2019,33:1841-1855.
	Gao C H, Zhu J Y, Zhang H W, Tian Y X, Gao F J. Comprehensive identification and evaluation of 38 grain sorghum cultivars for tolerance during germination. J Nucl Agric Sci, 2019,33:1841-1855 (in Chinese with English abstract).
[10]	曹帅, 杜仲阳, 向殿军, 李志刚, 孙贺祥, 宫晓旭, 刘鹏. 18 份大豆品种耐盐碱性筛选与综合鉴定. 大豆科学, 2019,38:344-352.
	Cao S, Du Z Y, Xiang D J, Li Z G, Sun H X, Gong X Y, Liu P. Salt and alkaline tolerance screening and comprehensive identification of eighteen soybean varieties. Soybean Sci, 2019,38:44-52 (in Chinese with English abstract).
[11]	宁蕾, 王曙光, 琚鹏举, 柏星轩, 葛林豪, 齐欣, 姜奇彦, 孙现军, 陈明, 孙黛珍. 过表达谷子SiANT1对水稻耐盐性的影响. 中国农业科学, 2018,51:23-34.
	Ning L, Wang S G, Ju P J, Bai X X, Ge L H, Qi X, Jiang Q Y, Sun X J, Chen M, Sun D Z. Rice over expression of millet SiANT1 gene increases salt tolerance. Sci Agric Sin, 2013,51:23-34 (in Chinese with English abstract).
[12]	陈二影, 杨延兵, 程炳文, 秦岭, 张华文, 刘宾, 王海莲, 陈桂玲, 管延安. 不同夏谷品种的产量与氮肥利用效率. 中国土壤与肥料, 2015, (2):101-105.
	Chen E Y, Yang Y B, Cheng B W, Qin L, Zhang H W, Liu B, Wang H L, Chen G L, Guan Y A. Yield and nitrogen use efficiency in summer foxtail millet. China Soils Fert, 2015, (2):101-105 (in Chinese with English abstract).
[13]	陈二影, 秦岭, 程炳文, 杨延兵, 张华文, 刘宾, 王海莲, 陈桂玲, 管延安. 夏谷氮、磷、钾肥的效应研究. 山东农业科学, 2015,47(1):67-71.
	Chen E Y, Qin L, Cheng B W, Yang Y B, Zhang H W, Liu B, Wang H L, Chen G L, Guan Y A. Application effect of N, P, K fertilizers on summer foxtail millet. Shandong Agric Sci, 2017,47(1):67-71 (in Chinese with English abstract).
[14]	冯露, 钟理, 陈丹丹, 马有志, 徐兆师, 李连城, 周永斌, 陈明, 张小红. 过表达谷子液泡H⁺-ATPase E亚基基因在拟南芥中的耐盐性. 作物学报, 2015,41:66-75. doi: 10.3724/SP.J.1006.2015.00066
	Feng L, Zhong L, Chen D D, Ma Y Z, Xu Z S, Li L C, Zhou Y B, Chen M, Zhang X H. Over expression of vacuole H⁺-ATPase E subunit gene SiVHA-E from foxtail millet enhances salt resistance in transgenic Arabidopsis thaliana. Acta Agron Sin, 2015,41:66-75 (in Chinese with English abstract).
[15]	黄锁, 胡利芹, 徐东北, 李微微, 徐兆师, 李连城, 周永斌, 刁现民, 贾冠清, 马有志, 陈明. 谷子转录因子SiNF-YA5通过ABA非依赖途径提高转基因拟南芥耐盐性. 作物学报, 2016,42:1787-1797. doi: 10.3724/SP.J.1006.2016.01787
	Huang S, Hu L Q, Xu D B, Li W W, Xu Z S, Li L C, Zhou Y B, Diao X M, Jia G Q, Ma Y Z, Chen M. Transcription factor SiNF-YA5 from foxtail millet (Setaria italica) conferred tolerance to high-salt stress through ABA-independent pathway in transgenic Arabidopsis. Acta Agron Sin, 2016,42:1787-1797 (in Chinese with English abstract).
[16]	秦玉海, 张小红, 冯露, 李微微, 徐兆师, 李连城, 周永斌, 马有志, 刁现民, 贾冠清, 陈明, 闵东红. 谷子转录因子基因SibZIP42在拟南芥中对高盐和ABA的响应. 中国农业科学, 2016,49:3276-3286. doi: 10.3864/j.issn.0578-1752.2016.17.003
	Qin Y H, Zhang X H, Feng L, Li H H, Xu Z S, Li L C, Zhou Y B, Ma Y Z, Diao X M, Jia G Q, Chen M, Min D H. Response of millet transcription factor gene SibZIP42 to high salt and ABA treatment in transgenic Arabidopsis. Sci Agric Sin, 2016,49:3276-3286 (in Chinese with English abstract).
[17]	田伯红, 王素英, 李雅静, 王建广, 张立新, 梁凤芹, 翟玉柱, 刘金荣. 谷子地方品种发芽期和苗期对NaCl胁迫的反应和耐盐品种筛选. 作物学报, 2008,34:164-168.
	Tian B H, Wang S Y, Li Y J, Wang J G, Zhang L X, Liang F Q, Zhai G Z, Liu J R. Response to sodium chloride stress at germination and seedling and identification of salinity tolerant genotypes in foxtail millet landraces originated from China. Acta Agron Sin, 2008,34:164-168 (in Chinese with English abstract).
[18]	崔兴国, 时丽冉. 衡水地区14份夏谷品种种子萌发期耐盐性研究. 作物杂志, 2011, (4):117-119.
	Cui X G, Shi L R. Evaluation of salt tolerance of 14 foxtail millet summer varieties in Hengshui. Crops, 2011, (4):117-119 (in Chinese with English abstract).
[19]	崔兴国, 时丽冉. 盐胁迫对不同品种谷子萌发及幼苗生长的影响. 黑龙江农业科学, 2011, (6):14-16.
	Cui X G, Shi L R. Effect of salt stress on different seed germination and seedling growth of Setaria italica (L.). Heilongjiang Agric Sci, 2011, (6):14-16 (in Chinese with English abstract).
[20]	张永芳, 宋喜娥, 王润梅, 湛润生, 赵治海, 范光宇. Na₂CO₃胁迫对谷子种子萌发的影响. 种子, 2015,34(11):102-105.
	Zhang Y F, Song X E, Wang R M, Zhan R S, Zhao Z H, Fan G Y. Effect of Na₂CO₃ stress on different seed germination of millet. Seed, 2015,34(11):102-105 (in Chinese with English abstract).
[21]	韩飞, 诸葛玉平, 娄燕宏, 王会, 张乃丹, 何伟, 晁赢. 63份谷子种质的耐盐综合评价及耐盐品种筛选. 植物遗传资源学报, 2018,19:103-111.
	Han F, Zhu-Ge Y P, Lou Y H, Wang H, Zhang N D, He W, Chao Y. Evaluation of salt tolerance and screening for salt tolerant accessions of 63 foxtail millet germplasm. J Plant Genet Resour, 2018,19:103-111 (in Chinese with English abstract).
[22]	张鹏锐, 李旭霖, 崔德杰, 胡景田. 滨海重盐碱地不同土地利用方式的水盐特征. 水土保持学报, 2015,29(2):119-123.
	Zhang P R, Li X L, Cui D J, Hu J T. Characteristics of water and salt under different land use in heavy coastal saline-alkaline land. J Soil Water Conserv, 2015,29(2):119-123 (in Chinese with English abstract).
[23]	高彦花. 渤海湾盐碱地土壤水盐动态及耐盐植物改良盐渍土研究. 中国林业科学研究院博士学位论文, 北京, 2011. pp 18-20.
	Gao Y H. Study on the Dynamics of Water and Salt in Saline Soil and Ameliortion of Saline Soil by Salt-resistance Plants in Bohai Bay. PhD Dissertation of Graduate School of Chinese Academy of Forestry, Beijing, China, 2011. pp 18-20 (in Chinese with English abstract).
[24]	郭瑞锋, 张永福, 任月梅, 杨忠. 混合盐碱胁迫对谷子萌发、幼芽生长的影响及耐盐碱品种筛选. 作物杂志, 2017, (4):63-66.
	Guo R F, Zhang Y F, Ren Y M, Yang Z. Effects of saline-alkali stress on millet germination and shoots growth and saline-alkali tolerance variety screening. Crops, 2017, (4):63-66 (in Chinese with English abstract).
[25]	于菘, 郭潇潇, 梁海芸, 付鸾鸿, 史京京, 张翼飞, 闯磊. 不同基因型绿豆萌发期耐盐碱性分析及其鉴定指标的筛选. 植物生理学报, 2017,53:1629-1639.
	Yu S, Guo X X, Liang H Y, Fu L H, Shi J J, Zhang Y F, Chuang L. Analysis of saline-alkaline tolerance and screening of identification indicators at the germination stage among different mung bean genotypes. Acta Phytophysiol Sin, 2017,53:1629-1639 (in Chinese with English abstract).
[26]	段文学, 张海燕, 解备涛, 汪宝卿, 张立明. 甘薯苗期耐盐性鉴定及其指标筛选. 作物学报, 2018,44:137-147. doi: 10.3724/SP.J.1006.2018.00137
	Duan W X, Zhang H Y, Xie B T, Wang B Q, Zhang L M. Identification of salt tolerance and screening for its indicators in sweet potato varieties during seedling stage. Acta Agron Sin, 2018,44:137-147 (in Chinese with English abstract).
[27]	苑乂川, 陈小雨, 李明明, 李萍, 贾亚涛, 韩渊怀, 邢国芳. 谷子苗期耐低磷种质筛选及其根系保护酶系统对低磷胁迫的响应. 作物学报, 2019,45:121-132.
	Fan Y C, Chen X Y, Li M M, Li P, Jia Y T, Han Y H, Xing G F. Screening of germplasm tolerant to low phosphorus of seedling stage and response of root protective enzymes to low phosphorus in foxtail millet. Acta Agron Sin, 2019,45:121-132 (in Chinese with English abstract).
[28]	褚能明, 柯剑鸿, 袁亮. 不同鲜食甜糯玉米挥发性风味物质主成分分析. 核农学报, 2017,31:2175-2185.
	Chu N M, Ke J H, Yuan L. Principal components analysis for volatility of flavor compositions in different fresh sweet glutinous corn. J Nucl Agric Sci, 2017,31:2175-2185 (in Chinese with English abstract).
[29]	田茂成, 邓小华, 陆中山, 田峰, 陈治锋, 张明发, 张黎明. 基于灰色效果测度和主成分分析的湘西州烟叶物理特性综合评价. 核农学报, 2017,31:187-193.
	Tian M C, Deng X H, Lu Z S, Tian F, Chen Z F, Zhang M F, Zhang L M. Gray effect measure and principal component analysis-based comprehensive evaluation for physical properties of flue-cured tobacco leaves from Xiangxi area. J Nucl Agric Sci, 2017,31:187-193 (in Chinese with English abstract).
[30]	孙东雷, 卞能飞, 陈志德, 邢兴华, 徐泽俊, 齐玉军, 王晓军, 王幸. 花生萌发期耐盐性综合评价及耐盐种质筛选. 植物遗传资源学报, 2017,18:1079-1087.
	Sun D L, Bian N F, Chen Z D, Xing X H, Xu Z J, Qi Y J, Wang X J, Wang X. Comprehensive evaluation of salt tolerance and screening for salt tolerant accessions of peanut (Arachis hypogaea L.) at germination stage. J Plant Genet Resour, 2017,18:1079-1087 (in Chinese with English abstract).
[31]	戴海芳, 武辉, 阿曼古丽·买买提阿力, 王立红, 麦麦提·阿皮孜. 不同基因型棉花苗期耐盐性分析及其鉴定指标筛选. 中国农业科学, 2014,47:1290-1300. doi: 10.3864/j.issn.0578-1752.2014.07.005
	Dai H F, Wu H, Amanguli Maimaitiali, Wang L H, Maimaiti Apizi, Zhang J S. Analysis of salt-tolerance and determination of salt-tolerant evaluation indicators in cotton seedlings of different genotypes. Sci Agric Sin, 2014,47:1290-1300 (in Chinese with English abstract).
[32]	Radanielson A M, Angeles O, Li T, Ismail A M, Gaydon D S. Describing the physiological responses of different rice genotypes to salts tress using sigmoid and piecewise linear functions. Field Crops Res, 2018,220:46-56. doi: 10.1016/j.fcr.2017.05.001 pmid: 29725160
[33]	Burman D, Maji B, Singh S, Mandal S, Sarangi S K, Bandyopadhyay B K, Bal A R, Sharma D K, Krishnamurthy S L, Singh H N, Delosreyes A S, Villanueva D, Paris T, Singh U S, Haefele S M, Ismail A M. Participatory evaluation guides the development and selection of farmers’ preferred rice varieties for salt- and flood-affected coastal deltas of south and southeast Asia. Field Crops Res, 2018,220:67-77. doi: 10.1016/j.fcr.2017.03.009 pmid: 29725161
[34]	陈二影, 秦岭, 杨延兵, 黎飞飞, 王润丰, 张华文, 王海莲, 刘宾, 孔清华, 管延安. 生产条件下谷子品种盐碱耐性的差异及综合评价. 中国农业科学, 2019,52:4050-4065. doi: 10.3864/j.issn.0578-1752.2019.22.010
	Chen E Y, Qin L, Yang Y B, Li F F, Wang R F, Zhang H W, Wang H L, Liu B, Kong Q H, Guan Y A. Variation and comprehensive evaluation of salt and alkali tolerance of different foxtail millet cultivars under production conditions. Sci Agric Sin, 2019,52:4050-4065 (in Chinese with English abstract).

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

参数 Parameter	范围 Range (%)	均值 Mean (%)	均方 Mean square	变异系数 CV (%)
相对发芽势RGP (%)	53.30-97.90	85.71	109.91	12.23
相对发芽率RGR (%)	49.40-98.40	84.88	145.62	14.22
相对根长RRL (%)	8.70-56.40	22.37	104.70	45.75
相对芽长RSL (%)	38.00-99.70	73.37	162.88	17.39
相对根鲜重RRFW (%)	50.90-96.30	77.58	109.66	13.50
相对芽鲜重RSFW (%)	43.10-96.90	78.00	208.09	18.49
相对根冠比RRSR (%)	74.60-188.90	102.35	454.61	20.83
发芽势盐害率 SIRGP (%)	2.10-46.70	14.29	109.95	73.38
发芽率盐害率SIRGR (%)	1.60-50.60	15.12	145.67	79.81
根长盐害率SIRRL (%)	43.60-91.30	77.64	104.72	13.18
芽长盐害率SIRSL (%)	0.30-62.00	26.63	162.88	47.92
根鲜重盐害率SIRRFW (%)	3.70-49.10	22.42	109.65	46.71
芽鲜重盐害率SIRSFW (%)	3.10-56.90	22.00	208.09	65.57
根冠比盐害率SIRSR (%)	-88.90-25.40	-2.35	454.61	-908.39

性状 Trait	相对	相对	相对	相对	相对	相对	相对	发芽势	发芽率	根长	芽长	根鲜重	芽鲜重	根冠比
	发芽势	发芽率	根长	芽长	根鲜重	芽鲜重	根冠比	盐害率	盐害率	盐害率	盐害率	盐害率	盐害率	盐害率
	RGP	RGR	RRL	RSL	RRFW	RSFW	RRSR	SIRGP	SIRGR	SIRRL	SIRSL	SIRRFW	SIRRFW	SIRRS
相对发芽势RGP
相对发芽率RGR	0.736"
相对根长RRL	0.123	0.347*
相对芽长RSL	0.281*	0.409**	0.451"
相对根鲜重RRFW	0.287*	0.470**	0.160	0.269
相对芽鲜重RSFW	0.430**	0.590**	0.380**	0.593**	0.458**
相对根冠比RRSR	-0.320*	-0.361**	-0.290*	-0.475**	0.206	-0.744"
发芽势盐害率SIRGP	-1.000**	-0.736**	-0.123	-0.281*	-0.287*	-0.430**	0.319*
发芽率盐害率SIRGR	-0.735**	-1.000**	-0.347*	-0.409**	-0.470**	-0.590**	0.361"	0.736"
根长盐害率SIRRL	-0.123	-0.347*	-1.000**	-0.451**	-0.160	-0.380**	0.290*	0.123	0.347*
芽长盐害率SIRSL	-0.281*	-0.409**	-0.451**	-1.000**	-0.269	-0.593**	0.475**	0.281*	0.409**	0.45广
根鲜重盐害率SIRRFW	-0.287*	-0.470**	-0.160	-0.269	-1.000**	-0.458**	-0.206	0.287*	0.470**	0.160	0.269
芽鲜重盐害率SIRSFW	-0.430**	-0.590**	-0.380**	-0.593**	-0.458**	-1.000**	0.744**	0.430**	0.590**	0.380"	0.593**	0.458**
根冠比盐害率SIRRS	0.320*	0.361"	0.290*	0.475**	-0.206	0.744**	-1.000**	-0.319*	-0.361**	-0.290*	-0.475**	0.206	-0.744"

	主成分Principal component	I	II	III	IV
特征根Eigen value		6.78	2.61	1.94	1.32
贡献率Contribution (%)		48.43	18.64	13.82	9.45
累计贡献率Cumulative contribution (%)		48.43	67.07	80.89	90.35
载荷因子Load factor	相对发芽势RGP	0.671	0.318	-0.533	0.272
	相对发芽率RGR	0.821	0.326	-0.215	0.230
	相对根长RRL	0.544	-0.227	0.579	0.529
	相对芽长RSL	0.726	-0.224	0.317	-0.151
	相对根鲜重RRFW	0.473	0.740	0.347	-0.294
	相对芽鲜重RSFW	0.886	-0.128	0.013	-0.352
	相对根冠比RRSR	-0.659	0.657	0.284	0.148
	发芽势盐害率 SIRGP	0.671	0.319	-0.533	0.272
	发芽率盐害率SIRGR	0.821	0.326	-0.215	0.229
	根长盐害率SIRRL	0.543	-0.227	0.579	0.530
	芽长盐害率SIRSL	0.726	-0.224	0.317	-0.151
	根鲜重盐害率SIRRFW	0.473	0.740	0.347	-0.294
	芽鲜重盐害率SIRSFW	0.886	-0.128	0.013	-0.352
	根冠比盐害率SIRRS	-0.659	0.657	0.284	0.148

Comprehensive identification and evaluation of foxtail millet for saline-alkaline tolerance during germination

RichHTML373

PDF

Abstract

Cite this article

share this article

Figures/Tables 9

References 34

Related Articles 15

Metrics

Comments

Recommended 0

[1]	JIN Min-Shan, QU Rui-Fang, LI Hong-Ying, HAN Yan-Qing, MA Fang-Fang, HAN Yuan-Huai, XING Guo-Fang. Identification of sugar transporter gene family SiSTPs in foxtail millet and its participation in stress response [J]. Acta Agronomica Sinica, 2022, 48(4): 825-839.
[2]	DU Xiao-Fen, WANG Zhi-Lan, HAN Kang-Ni, LIAN Shi-Chao, LI Yu-Xin, ZHANG Lin-Yi, WANG Jun. Identification and analysis of RNA editing sites of chloroplast genes in foxtail millet [Setaria italica (L.) P. Beauv.] [J]. Acta Agronomica Sinica, 2022, 48(4): 873-885.
[3]	ZHAO Mei-Cheng, DIAO Xian-Min. Phylogeny of wild Setaria species and their utilization in foxtail millet breeding [J]. Acta Agronomica Sinica, 2022, 48(2): 267-279.
[4]	WANG Yang-Yang, HE Li, REN De-Chao, DUAN Jian-Zhao, HU Xin, LIU Wan-Dai, GU Tian-Cai, WANG Yong-Hua, FENG Wei. Evaluations of winter wheat late frost damage under different water based on principal component-cluster analysis [J]. Acta Agronomica Sinica, 2022, 48(2): 448-462.
[5]	GAO Zhen, LIANG Xiao-Gui, ZHANG Li, ZHAO Xue, DU Xiong, CUI Yan-Hong, ZHOU Shun-Li. Effects of irrigating at different growth stages on kernel number of spring maize in the North China Plain [J]. Acta Agronomica Sinica, 2021, 47(7): 1324-1331.
[6]	MA Gui-Fang, MAN Xia-Xia, ZHANG Yi-Juan, GAO Hao, SUN Zhao-Xia, LI Hong-Ying, HAN Yuan-Huai, HOU Si-Yu. Integrated analysis between folate metabolites profiles and transcriptome of panicle in foxtail millet [J]. Acta Agronomica Sinica, 2021, 47(5): 837-846.
[7]	JIA Xiao-Ping, LI Jian-Feng, ZHANG Bo, QUAN Jian-Zhang, WANG Yong-Fang, ZHAO Yuan, ZHANG Xiao-Mei, WANG Zhen-Shan, SANG Lu-Man, DONG Zhi-Ping. Responsive features of SiPRR37 to photoperiod and temperature, abiotic stress and identification of its favourable allelic variations in foxtail millet (Setaria italica L.) [J]. Acta Agronomica Sinica, 2021, 47(4): 638-649.
[8]	JIA Xiao-Ping,YUAN Xi-Lei,LI Jian-Feng,WANG Yong-Fang,ZHANG Xiao-Mei,ZHANG Bo,QUAN Jian-Zhang,DONG Zhi-Ping. Photo-thermal interaction model under different photoperiod-temperature conditions and expression analysis of SiCCT gene in foxtail millet (Setaria italica L.) [J]. Acta Agronomica Sinica, 2020, 46(7): 1052-1062.
[9]	Jin-Feng ZHAO,Yan-Wei DU,Gao-Hong WANG,Yan-Fang LI,Gen-You ZHAO,Zhen-Hua WANG,Yu-Wen WANG,Ai-Li YU. Identification of PEPC genes from foxtail millet and its response to abiotic stress [J]. Acta Agronomica Sinica, 2020, 46(5): 700-711.
[10]	Li-Lan ZHANG, Lie-Mei ZHANG, Huan-Ying NIU, Yi XU, Yu LI, Jian-Min QI, Ai-Fen TAO, Ping-Ping FANG, Li-Wu ZHANG. Correlation between SSR markers and fiber yield related traits in jute (Corchorus spp.) [J]. Acta Agronomica Sinica, 2020, 46(12): 1905-1913.
[11]	JI Long,SHEN Hong-Fang,XU Chun-Chun,CHEN Zhong-Du,FANG Fu-Ping. Comprehensive evaluation of green super rice varieties based on nonlinear principal component analysis [J]. Acta Agronomica Sinica, 2019, 45(7): 982-992.
[12]	JIA Xiao-Ping,QUAN Jian-Zhang,WANG Yong-Fang,DONG Zhi-Ping,YUAN Xi-Lei,ZHANG Bo,LI Jian-Feng. Effects of different photoperiod conditions on agronomic traits of foxtail millet [J]. Acta Agronomica Sinica, 2019, 45(7): 1119-1127.
[13]	YUAN Yi-Chuan, CHEN Xiao-Yu, LI Ming-Ming, LI Ping, JIA Ya-Tao, HAN Yuan-Huai, XING Guo-Fang. Screening of germplasm tolerant to low phosphorus of seedling stage and response of root protective enzymes to low phosphorus in foxtail millet [J]. Acta Agronomica Sinica, 2019, 45(4): 601-612.
[14]	Xue-Jiao CHEN,Xu-Dong ZHANG,Zhi-Zhong HAN,Peng ZHANG,Zhi-Kuan JIA,Yan-Hao LIAN,Qing-Fang HAN. Fertilizer Response and Its Contribution to Yield of Foxtail Millet under Ridge-furrow Rainfall Harvesting Planting Model in Semi-arid Areas [J]. Acta Agronomica Sinica, 2018, 44(7): 1055-1066.
[15]	Qian-Nan CHEN,Ke WANG,Sha TANG,Li-Pu DU,Hui ZHI,Guan-Qing JIA,Bao-Hua ZHAO,Xing-Guo YE,Xian-Min DIAO. Use of Bar Gene for the Stable Transformation of Herbicide-resistant Foxtail Millet Plants [J]. Acta Agronomica Sinica, 2018, 44(10): 1423-1432.