黄淮海麦区小麦耐热性分析及其鉴定指标的筛选

doi:10.3864/j.issn.0578-1752.2021.16.002

摘要/Abstract

摘要：

【目的】分析不同基因型小麦的耐热性,筛选耐热鉴定指标,建立可靠的耐热评价模型,为耐热小麦品种的选育提供理论支撑。【方法】以黄淮海麦区大面积推广的20个小麦品种为试验材料,采用田间试验,设置高温（花后第14—20天,连续7 d高温处理）和自然条件2种处理,在灌浆后期测定小麦穗部冠层温度、旗叶叶绿素相对含量（SPAD）、丙二醛（MDA）含量以及超氧化物歧化酶（SOD）、过氧化物酶（POD）和过氧化氢酶（CAT）活性;收获晾干后测定单穗粒重、千粒重和产量。根据高温处理和自然条件生长下各项指标的耐热系数,采用主成分分析、隶属函数法、聚类分析和逐步回归分析方法对小麦耐热性进行综合评价。【结果】高温处理下各性状变异幅度为-14.89%—15.09%。通过对9个性状指标的相关分析,发现各指标之间存在显著或极显著相关性。通过主成分分析将9个单项指标转换为3个相互独立的综合指标,其贡献率分别为55.970%、15.530%和12.171%,代表了全部数据83.670%的信息量。利用隶属函数法计算综合耐热评价值（D）,并对其进行聚类分析,按照耐热性强弱将20个小麦品种划分为3类,第一类耐热型8个品种;第二类中等耐热型7个品种;第三类高温敏感型5个品种。通过逐步回归方程建立了小麦耐热性的评价数学模型：D=-4.801+0.834X₄+2.913X₇+0.303X₆+2.937X₈- 1.409X₁-0.524X₃+0.876X₉（R²=0.986）,利用建立的最优回归方程预测供试材料的耐热性,预测值（VP）与D值基本一致,表明SOD活性（X₄）、单穗粒重（X₇）、CAT活性（X₆）、千粒重（X₈）、冠层温度（X₁）、MDA含量（X₃）和产量（X₉）这7个指标可用于小麦耐热性品种的鉴定。【结论】采用多元统计分析方法对小麦耐热性评价是可行的;20个小麦品种被分为3类（耐热型、中等耐热型和高温敏感型）;高温处理下,SOD活性、单穗粒重、CAT活性、千粒重、冠层温度、MDA含量和产量可以作为小麦耐热性的鉴定指标。

关键词: 冬小麦, 花后耐热性, 主成分分析, 综合评价

Abstract:

【Objective】 The main objectives of this study were to (i) explore the methods of evaluating heat tolerance, (ii) screen suitable identification indexes of heat tolerance, and (iii) establish an evaluation model of heat tolerance, for screening of heat-tolerance resources and variety breeding of wheat.【Method】 20 wheat cultivars from Huang-Huai-Hai area were used in this study. High temperature treatment was applied by covering a plastic tunnel and the plants were subjected to heat from 14 to 20 days after flowering, during the heat treatment, normal field growth as the control. Canopy temperature, chlorophyll content (SPAD), malondialdehyde content (MDA) superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) activity were measured at the filling stage; single spike weight, thousand-grain weight and yield of wheat were measured after harvesting, heat tolerance was analyzed and evaluated by using principal component analysis, membership function method, hierarchical cluster analysis and stepwise regression analysis.【Result】After high temperature treatment, the variation range of heat tolerance of each single index was between -14.89% and 15.09%. Correlation analysis of the heat tolerance coefficients about 20 varieties indicated that there existed significant (P<0.05 and 0.01) correlations between nine traits. Three independent comprehensive components were obtained from nine single traits by a principal component analysis, and their contribution rates respectively were 55.970%, 15.530% and 12.171%, which reflected 83.67% information of all traits information. The comprehensive heat tolerance values were calculated from the membership function methods, and 20 wheat materials were divided into three heat-tolerance types by the cluster analysis. The first category is heat tolerance, and the second category is medium heat tolerance, followed by the third category belonging to high temperature sensitive type. A mathematical evaluation model from heat tolerance of wheat was established using the stepwise regression equation: D=-4.801+0.834X₄+2.913X₇+0.303X₆+2.937X₈-1.409X₁-0.524X₃+0.876X₉(R²=0.986). The predictive values (VP) were basically consistent with the comprehensive heat tolerance value, the results showed that SOD activity (X₄), single spike weight (X₇), CAT activity (X₆), Thousand-grain weight (X₈), canopy temperature (X₁), MDA content (X₃) and yield (X₉) could be used to identify wheat heat-resistant varieties. 【Conclusion】 A comprehensive evaluation system established by multivariate statistics was used to identify heat tolerance of wheat is feasible. Twenty wheat varieties were divided into three heat tolerance types, i.e., heat tolerance type, medium heat tolerance type and heat sensitive type, and SOD activity, single spike weight, CAT activity, Thousand-grain weight, canopy temperature, MDA content and grain yield can be used for identification of heat tolerance of wheat.

Key words: Triticum aestivum L., heat tolerance, membership function method, comprehensive evaluation

李敏, 苏慧, 李阳阳, 李金鹏, 李金才, 朱玉磊, 宋有洪. 黄淮海麦区小麦耐热性分析及其鉴定指标的筛选[J]. 中国农业科学, 2021, 54(16): 3381-3392.

LI Min, SU Hui, LI YangYang, LI JinPeng, LI JinCai, ZHU YuLei, SONG YouHong. Analysis of Heat Tolerance of Wheat with Different Genotypes and Screening of Identification Indexes in Huang-Huai-Hai Region[J]. Scientia Agricultura Sinica, 2021, 54(16): 3381-3392.

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链接本文: https://www.chinaagrisci.com/CN/10.3864/j.issn.0578-1752.2021.16.002

https://www.chinaagrisci.com/CN/Y2021/V54/I16/3381

图/表 9

图1

表1

表2

图2

表3

表4

各参试材料综合指标值、权重、u(Xj)、D值及综合评价"

材料名称 Material name	CI₁	CI₂	CI₃	u(X₁)	u(X₂)	u(X₃)	D值 D value	VP值 VP value	综合评价 Comprehensive valuation
中麦895 Zhongmai 895	2.620	0.530	0.740	0.993	0.625	0.644	0.874	0.885	耐热型Heat tolerance type
新科169 Xinkemai 169	-2.100	-0.320	-0.490	0.287	0.478	0.352	0.332	0.354	高温敏感型 Heat sensitive type
中麦175 Zhongmai 175	2.610	0.190	0.400	0.991	0.566	0.563	0.850	0.863	耐热型 Heat tolerance type
郑麦136 Zhengmai 136	2.670	0.160	0.520	1.000	0.561	0.591	0.859	0.865	耐热型Heat tolerance type
良星99 Liangxing 99	-2.110	-0.460	1.660	0.286	0.454	0.862	0.401	0.388	中等耐热型Medium heat tolerance type
淮麦33 Huaimai 33	1.960	-0.650	-0.330	0.894	0.421	0.390	0.733	0.732	耐热型 Heat tolerance type
安农0711 Annong 0711	0.620	-3.090	-1.420	0.694	0.000	0.131	0.483	0.475	中等耐热型Medium heat tolerance type
华成3366 Huacheng 3366	-4.020	-1.170	0.330	0.000	0.332	0.546	0.141	0.144	高温敏感型 Heat sensitive type
周麦27 Zhoumai 27	-2.150	-0.980	0.060	0.280	0.364	0.482	0.325	0.294	高温敏感型 Heat sensitive type
洛旱22 Luohan 22	1.590	-0.030	0.060	0.839	0.528	0.482	0.729	0.744	耐热型 Heat tolerance type
洛旱19 Luohan 19	2.030	0.610	-0.320	0.904	0.639	0.392	0.781	0.755	耐热型 Heat tolerance type
百农207 Bainong 207	-0.070	0.570	-0.880	0.590	0.632	0.259	0.550	0.541	中等耐热型Medium heat tolerance type
洛麦26 Luomai 26	0.300	0.300	-1.750	0.646	0.585	0.052	0.548	0.527	中等耐热型Medium heat tolerance type
新麦36 Xinmai 36	-2.710	-1.120	0.080	0.196	0.340	0.487	0.265	0.300	高温敏感型 Heat sensitive type
丰德存麦5号 Fengdecunmai 5	2.240	0.280	0.110	0.936	0.582	0.494	0.806	0.808	耐热型 Heat tolerance type
丰德存麦21号 Fengdecunmai 21	2.480	0.130	0.270	0.972	0.556	0.532	0.831	0.821	耐热型 Heat tolerance type
丰德存麦1号 Fengdecunmai 1	-3.250	2.700	-1.970	0.115	1.000	0.000	0.263	0.273	高温敏感型 Heat sensitive type
郑麦369 Zhengmai 369	-0.340	1.190	-0.490	0.550	0.739	0.352	0.556	0.550	中等耐热型Medium heat tolerance type
周麦36 Zhoumai 36	-2.260	1.610	2.240	0.263	0.812	1.000	0.472	0.466	中等耐热型Medium heat tolerance type
郑麦366 Zhengmai 366	-0.100	-0.460	1.190	0.586	0.454	0.751	0.585	0.593	中等耐热型Medium heat tolerance type
权重Index weight				0.669	0.186	0.145

表4

图3

表5

表6

高温处理对不同品种小麦产量的影响"

材料名称 Material name	对照产量 Control yield (kg·hm^-2)			高温产量 High temperature yield (kg·hm^-2)			产量下降比例 Relative grain yield reduction (%)
材料名称 Material name	2019	2020	平均值Mean	2019	2020	平均值Mean	2019	2020	平均值Mean
中麦895 Zhongmai 895	9500.40	8004.30	8752.35	9338.74	7592.14	8465.44	1.70	5.15	3.43
新科麦169 Xinkemai 169	9548.16	8067.18	8807.67	8754.46	7349.12	8051.79	8.31	8.90	8.61
中麦175 Zhongmai 175	8611.46	4707.63	6659.54	8359.98	4513.02	6436.50	2.92	4.13	3.53
郑麦136 Zhengmai 136	9262.52	9014.63	9138.57	9220.45	8726.40	8973.43	0.45	3.20	1.83
良星99 Liangxing 99	9013.11	8108.28	8560.69	7990.59	7126.55	7558.57	11.34	12.11	11.73
淮麦33 Huaimai 33	9761.52	7498.83	8630.17	9267.07	7031.30	8149.18	5.07	6.23	5.65
安农0711 Annong 0711	8934.77	7338.49	8136.63	8394.50	6941.92	7668.21	6.05	5.40	5.73
华成3366 Huacheng 3366	9412.04	7193.99	8303.01	7874.91	6553.64	7214.27	16.33	8.90	12.62
周麦27 Zhoumai 27	9311.52	8014.61	8663.06	8168.85	6931.15	7550.00	12.27	13.52	12.90
洛旱22 Luohan 22	8272.62	8235.92	8254.27	7879.23	7299.77	7589.50	4.76	11.37	8.06
洛旱19 Luohan 19	9833.82	8351.24	9092.53	9587.08	7922.40	8754.74	2.51	5.14	3.82
百农207 Bainong 207	8389.31	7102.16	7745.73	7876.61	6807.27	7341.94	6.11	4.15	5.13
洛麦26 Luomai 26	10750.55	8034.18	9392.36	10386.07	7172.79	8779.43	3.39	10.72	7.06
新麦36 Xinmai 36	9684.89	8172.29	8928.59	8689.86	7325.29	8007.58	10.27	10.36	10.32
丰德存麦5号 Fengdecunmai 5	8194.86	7755.06	7974.96	7931.76	7124.55	7528.15	3.21	8.13	5.67
丰德存麦21号 Fengdecunmai 21	9328.23	8963.82	9146.03	9174.25	8635.60	8904.92	1.65	3.66	2.66
丰德存麦1号 Fengdecunmai 1	9656.01	7700.74	8678.38	9083.05	7264.86	8173.95	5.93	5.66	5.80
郑麦369 Zhengmai 369	9121.54	8148.73	8635.14	8591.11	7607.83	8099.47	5.82	6.64	6.23
周麦36 Zhoumai 36	10200.53	8243.04	9221.78	9727.32	7252.42	8489.87	4.64	12.02	8.33
郑麦366 Zhengmai 366	9844.97	7540.83	8692.90	9389.41	7135.29	8262.35	4.63	5.38	5.00
平均值Mean	9331.64	7809.80	8570.72	8784.26	7215.67	7999.96	5.87	7.54	6.70

表6

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性状 Trait	对照均值±标准差 Control mean±SD	高温处理后的平均值±标准差 Mean±SD after HT stress	变幅 Range (%)
冠层温度Canopy temperature (℃)	29.08±0.65b	29.98±1.26a	3.09
叶绿素相对含量SPAD	24.37±9.56a	21.80±7.68b	-10.55
丙二醛含量MDA content (μmol·g^-1)	37.21±8.59b	42.82±9.89a	15.09
超氧化物歧化酶活性SOD activity (U·g^-1·FW)	166.89±8.23a	142.09±13.68b	-14.86
过氧化物酶活性POD activity (μ·g^-1·min^-1)	147.63±18.94a	135.53±16.24b	-8.19
过氧化氢酶活性CAT activity (μ·g^-1·min^-1)	26.53±9.05a	22.58±7.37b	-14.89
单穗粒重Seed weight per plant (g)	1.75±0.16a	1.70±0.16b	-2.83
千粒重Thousand-grain weight (g)	50.88±3.28a	48.45±2.97b	-4.76
产量Yield (kg·hm^-2)	9331.64±645.20a	8784.26±726.29b	-5.87

品种名称Variety	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈	X₉
中麦895 Zhongmai 895	1.005	0.957	1.120	0.954	0.938	0.942	0.988	0.975	0.986
新科麦169 Xinkemai 169	1.054	0.803	1.183	0.744	0.907	0.889	0.960	0.943	0.918
中麦175 Zhongmai 175	1.005	0.957	1.091	0.937	0.948	0.958	0.985	0.972	0.977
郑麦136 Zhengmai 136	1.002	0.957	1.091	0.920	0.932	0.972	0.982	0.972	0.997
良星99 Liangxing 99	1.073	0.916	1.204	0.747	0.879	0.854	0.976	0.963	0.888
淮麦33 Huaimai 33	1.009	0.963	1.066	0.909	0.950	0.935	0.968	0.959	0.953
安农0711 Annong 0711	1.016	0.943	1.071	0.908	0.916	0.964	0.903	0.940	0.943
华成3366 Huacheng 3366	1.066	0.866	1.207	0.743	0.854	0.705	0.950	0.934	0.839
周麦27 Zhoumai 27	1.062	0.888	1.208	0.754	0.922	0.856	0.950	0.953	0.877
洛旱22 Luohan 22	1.007	0.966	1.108	0.885	0.922	0.962	0.990	0.952	0.953
洛旱19 Luohan 19	1.009	0.966	1.116	0.890	0.966	0.900	0.987	0.959	0.978
百农207 Bainong 207	1.024	0.921	1.247	0.846	0.945	0.949	0.985	0.936	0.942
洛麦26 Luomai 26	1.027	0.936	1.137	0.847	0.954	0.860	0.978	0.921	0.971
新麦36 Xinmai 36	1.064	0.824	1.219	0.799	0.866	0.889	0.947	0.939	0.898
丰德存麦5号 Fengdecunmai 5	1.005	0.960	1.074	0.906	0.946	0.905	0.987	0.964	0.971
丰德存麦21号 Fengdecunmai 21	1.002	0.959	1.088	0.894	0.949	0.942	0.978	0.973	0.989
丰德存麦1号 Fengdecunmai 1	1.027	0.667	1.269	0.740	0.939	0.573	0.974	0.931	0.942
郑麦369 Zhengmai 369	1.045	0.889	1.173	0.902	0.945	0.727	0.987	0.941	0.945
周麦36 Zhoumai 36	1.062	0.857	1.295	0.834	0.845	0.654	0.984	0.968	0.957
郑麦366 Zhengmai 366	1.048	0.944	1.084	0.872	0.869	0.783	0.971	0.956	0.956
平均值Average	1.031	0.907	1.153	0.852	0.920	0.861	0.971	0.953	0.941
标准差STDEV	0.026	0.075	0.072	0.072	0.037	0.114	0.021	0.016	0.040
变异系数CV(%)	2.489	8.274	6.249	8.464	4.021	13.270	2.153	1.693	4.281

主成分 Principle factor		CI₁	CI₂	CI₃
特征值 Eigen value		5.037	1.398	1.095
贡献率 Contribution ratio (%)		55.970	15.530	12.171
累计贡献率 Cumulative contribution ratio (%)		55.970	71.500	83.670
特征向量 Eigen vector	X₁	-0.397	-0.115	0.293
	X₂	0.351	-0.305	0.265
	X₃	-0.364	0.335	0.057
	X₄	0.405	-0.004	0.054
	X₅	0.303	0.220	-0.553
	X₆	0.318	-0.421	-0.029
	X₇	0.170	0.663	0.263
	X₈	0.256	0.070	0.678
	X₉	0.368	0.333	-0.052

类型 Type	对照 CK
类型 Type	冠层温度 Canopy temperature (℃)	MDA	SOD		CAT		单穗粒重 Seed weight per plant (g)	千粒重 Thousand-grain weight (g)		产量 Yield (kg·hm^-2)
耐热型 Heat tolerance type	28.51±0.39c	35.61±7.95c	166.14±9.81b		23.86±7.99c		1.76±0.16b	50.61±2.29a		9095.68±649.98c
中等耐热型 Medium heat tolerance type	29.25±0.37b	37.18±9.63b	168.07±3.33a		28.03±10.78b		1.71±0.19c	51.02±4.81a		9464.97±826.48a
高温敏感型 Heat sensitive type	29.77±0.50a	39.81±9.34a	166.45±11.52b		28.68±8.91a		1.80±0.12a	51.09±2.67a		9329.20±159.35b
类型 Type	高温 HT
类型 Type	冠层温度 Canopy temperature (℃)	MDA	SOD	CAT		单穗粒重 Seed weight per plant (g)			千粒重 Thousand-grain weight (g)		产量 Yield (kg·hm^-2)
耐热型 Heat tolerance type	28.67±0.43c	38.92±8.43c	151.49±9.68a	22.29±6.96b		1.73±0.16a			48.90±2.49a		8844.82±678.65b
中等耐热型 Medium heat tolerance type	30.48±0.60b	43.34±10.19b	142.92±8.62b	23.30±9.34a		1.66±0.21b			48.25±4.03ab		8907.94±944.92a
高温敏感型 Heat sensitive type	31.39±0.60a	48.34±10.75a	125.89±10.35c	22.02±6.37c		1.72±0.10a			48.02±2.44b		8792.64±484.80c