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

Abstract

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

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.

0
/ / Recommend

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

URL: https://www.chinaagrisci.com/EN/10.3864/j.issn.0578-1752.2021.16.002

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

Figures/Tables 9

Fig. 1

Table 1

Table 2

Heat tolerance coefficient (HTC) of each single index of different wheat cultivars"

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

Table 2

Fig. 2

Table 3

Table 4

The value of each variety’s comprehensive index (CI), index weight, u(Xj), D value and comprehensive valuation"

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

Table 4

Fig. 3

Table 5

Table 6

Effects of high temperature on wheat yield of different varieties"

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

Table 6

References 35

[1]	DAVIDSON D. Gaps in agricultural climate adaptation research. Nature Climate Change, 2016, 6(5):433-435. doi: 10.1038/nclimate3007
[2]	Intergovernmental Panel on Climate Change. IPCC-SR15, Global Warming of 1.5℃. [2021-03-03]. http://www.ipcc.ch/report/sr15/.
[3]	CHALLINOR A J, WATSON J, LOBELL D B, HOWDEN S M, CHHETRI N B. A meta-analysis of crop yield under climate change and adaptation. Nature Climate Change, 2014, 4(4):287-291. doi: 10.1038/nclimate2153
[4]	HALL A, COX P, HUNTINGFORD C, KLEIN S. Progressing emergent constraints on future climate change. Nature Climate Change, 2019, 9(4):269-278. doi: 10.1038/s41558-019-0436-6
[5]	吴进东, 李金才, 魏凤珍, 王成雨, 张一, 武文明. 花后渍水高温交互效应对冬小麦旗叶光合特性及产量的影响. 作物学报, 2012, 38(6):1071-1079.
	WU J D, LI J C, WEI F Z, WANG C Y, ZHANG Y, WU W M. Effect of interaction of water logging and high temperature after anthesis on photosynthetic characteristics of flag leaf and yield in winter wheat. Acta Agronomica Sinica, 2012, 38(6):1071-1079. (in Chinese)
[6]	BERGKAMP B, IMPA S M, ASEBEDO A R, FRITZ A K, JAGADISH S V K. Prominent winter wheat varieties response to post-flowering heat stress under controlled chambers and field based heat tents. Field Crops Research, 2018, 222:143-152. doi: 10.1016/j.fcr.2018.03.009
[7]	刘萍, 郭文善, 浦汉春, 封超年, 朱新开, 彭永欣. 灌浆期高温对小麦剑叶抗氧化酶及膜脂过氧化的影响. 中国农业科学, 2005, 38(12):2403-2407.
	LIU P, GUO W S, PU H C, FENG C N, ZHU X K, PENG Y X. Effects of high temperature during grain filling period on antioxidant enzymes and lipid peroxidation in flag leaves of wheat. Scientia Agricultura Sinica, 2005, 38(12):2403-2407. (in Chinese)
[8]	卞晓波, 陈丹丹, 王强盛, 王绍华. 花后开放式增温对小麦产量及品质的影响. 中国农业科学, 2012, 45(8):1489-1498.
	BIAN X B, CHEN D D, WANG Q S, WANG S H. Effects of different day and night temperature enhancements on wheat grain yield and quality after anthesis under free air controlled condition. Scientia Agricultura Sinica, 2012, 45(8):1489-1498. (in Chinese)
[9]	郭天财, 王晨阳, 朱云集, 王化岑, 李九星, 周继泽. 后期高温对冬小麦根系及地上部衰老的影响. 作物学报, 1998, 24(6):957-962.
	GUO T C, WANG C Y, ZHU Y J, WANG H C, LI J X, ZHOU J Z. Effects of high temperature on the senescence of root and top-partial of wheat plant in the later stage. Acta Agronomica Sinica, 1998, 24(6):957-962. (in Chinese)
[10]	AYENEH A, GINKEL M V, REYNOLDS M P, AMMAR K. Comparison of leaf, spike, peduncle and canopy temperature depression in wheat under heat stress. Field Crops Research, 2002, 79(2/3):173-184. doi: 10.1016/S0378-4290(02)00138-7
[11]	BARAKAT M N, AL-DOSS A A, ELSHAFEI A A, MOUSTAFA K A. Identification of new microsatellite marker linked to the grain filling rate as indicator for heat tolerance genes in F₂ wheat population. Australian Journal of Crop Science, 2011, 5(2):104-110.
[12]	陈冬梅, 马永安, 刘保华, 苏玉环, 王雪香. 小麦耐热种质资源的鉴定与筛选. 河北农业科学, 2017, 21(4):64-69.
	CHEN D M, MA Y A, LIU B H, SU Y H, WANG X X. Appraisal and screening of heat resistant wheat germplasm resources. Journal of Hebei Agricultural Sciences, 2017, 21(4):64-69. (in Chinese)
[13]	王小波, 关攀锋, 辛明明, 汪永法, 陈希勇, 赵爱菊. 小麦种质资源耐热性评价. 中国农业科学, 2019, 52(23):4191-4200.
	WANG X B, GUAN P F, XIN M M, WANG Y F, CHEN X Y, ZHAO A J. Evaluation of heat tolerance in wheat germplasm resources. Scientia Agricultura Sinica, 2019, 52(23):4191-4200. (in Chinese)
[14]	张嵩午, 王长发, 冯佰利, 张宾, 郝彦宾. 冠层温度多态性小麦的性状特征. 生态学报, 2002, 22(9):1414-1419.
	ZHANG S W, WANG C F, FENG B L, ZHANG B, HAO Y B. The specific characteristics of wheat with polymorphic canopy temperature. Acta Ecologica Sinica, 2002, 22(9):1414-1419. (in Chinese)
[15]	张嵩午, 刘党校. 小麦冠温的多态性及其与品质变异的关联. 中国农业科学, 2007, 40(8):1630-1637.
	ZHANG S W, LIU D X. Polymorphism of wheat canopy temperature and its relationship with kernel quality differentiation. Scientia Agricultura Sinica, 2007, 40(8):1630-1637. (in Chinese)
[16]	王晶, 黄伟雄, 李敏, 许秀敏, 梁旭霞, 黄泓耀. 多元统计分析在小麦粉产地溯源中的应用. 中国食品卫生杂志, 2018, 30(1):68-73.
	WANG J, HUANG W X, LI M, XU X M, LIANG X X, HUANG H Y. The application of multivariate data analysis to determine the geographical origin of wheat flour. Chinese Journal of Food Hygiene, 2018, 30(1):68-73. (in Chinese)
[17]	汪明华, 李佳佳, 陆少奇, 邵文韬, 程安东, 张文明, 王晓波, 邱丽娟. 大豆品种耐高温特性的评价方法及耐高温种质筛选与鉴定. 植物遗传资源学报, 2019, 20(4):891-902.
	WANG M H, LI J J, LU S Q, SHAO W T, CHENG A D, ZHANG W M, WANG X B, QIU L J. Construction of evaluation standard for tolerance to high-temperature and screening of heat-tolerant germplasm resources in soybean. Journal of Plant Genetic Resources, 2019, 20(4):891-902. (in Chinese)
[18]	任茂, 张文英. 棉花品种耐热性分析及鉴定指标筛选. 核农学报, 2018, 32(4):788-794.
	REN M, ZHANG W Y. Evaluation of heat tolerance and screening the index for the assessment of heat tolerance in upland cotton. Journal of Nuclear Agricultural Sciences, 2018, 32(4):788-794. (in Chinese)
[19]	付丽军, 李聪晓, 苏胜宇, 李玉华, 周禹. 黄瓜苗期耐热种质筛选与耐热性评价体系构建. 植物生理学报, 2020, 56(7):1593-1604.
	FU L J, LI C X, SU S Y, LI Y H, ZHOU Y. Screening of cucumber germplasms in seedling stage and the construction of evaluation system for heat tolerance. Plant Physiology Journal, 2020, 56(7):1593-1604. (in Chinese)
[20]	李合生. 植物生理生化实验原理和技术. 北京: 高等教育出版社, 2015: 274-287.
	LI H S. Principles and Techniques for Plant Physiological Biochemical Experiment. Beijing: Higher Education Press, 2015: 274-287. (in Chinese)
[21]	ALMESELMANI M, DESHMUKH P S, SAIRAM R K. Protective role of antioxidant enzymes under high temperature stress. Plant Science, 2006, 171(3):382-388. doi: 10.1016/j.plantsci.2006.04.009
[22]	李春红, 姚兴东, 鞠宝韬, 朱明月, 王海英, 张惠君, 敖雪, 于翠梅, 谢甫绨, 宋书宏. 不同基因型大豆耐荫性分析及其鉴定指标的筛选. 中国农业科学, 2014, 47(15):2927-2939.
	LI C H, YAO X D, JU B T, ZHU M Y, WANG H Y, ZHANG H J, AO X, YU C M, XIE F T, SONG S H. Analysis of shade-tolerance and determination of shade-tolerance evaluation indicators in different soybean genotypes. Scientia Agricultura Sinica, 2014, 47(15):2927-2939. (in Chinese)
[23]	武晓玲, 梁海媛, 杨峰, 刘卫国, 佘跃辉, 杨文钰. 大豆苗期耐荫性综合评价及其鉴定指标的筛选. 中国农业科学, 2015, 48(13):2497-2507.
	WU X L, LIANG H Y, YANG F, LIU W G, SHE Y H, YANG W Y. Comprehensive evaluation and screening identification indexes of shade tolerance at seedling in soybean. Scientia Agricultura Sinica, 2015, 48(13):2497-2507. (in Chinese)
[24]	SALEM M A, KAKANI V G, KOTI S, REDDY K R. Pollen-based screening of soybean genotypes for high temperatures. Crop Science, 2007, 47(1):219-231 doi: 10.2135/cropsci2006.07.0443
[25]	于康珂, 刘源, 李亚明, 孙宁宁, 詹静, 尤东玲, 牛丽, 李潮海, 刘天学. 玉米花期耐高温品种的筛选与综合评价. 玉米科学, 2016, 24(2):62-71.
	YU K K, LIU Y, LI Y M, SUN N N, ZHAN J, YOU D L, NIU L, LI C H, LIU T X. Screening and comprehensive evaluation of heat tolerance of maize hybrids in flowering stage. Journal of Maize Sciences, 2016, 24(2):62-71. (in Chinese)
[26]	SONG G C, CHEN Q Z, TANG C M. The effects of high-temperature stress on the germination of pollen grains of upland cotton during square development. Euphytica, 2014, 200(2):175-186. doi: 10.1007/s10681-014-1141-1
[27]	徐如强, 孙其信, 张树榛. 春小麦耐热性的筛选方法与指标. 华北农学报, 1997, 12(3):22-29.
	XU R Q, SUN Q X, ZHANG S Z. Screening methods and indices of heat tolerance in spring wheat. Acta Agriculturae Boreali-Sinica, 1997, 12(3):22-29. (in Chinese)
[28]	陈希勇, 孙其信, 孙长征. 春小麦耐热性表现及其评价. 中国农业大学学报, 2000, 5(1):43-49.
	CHEN X Y, SUN Q X, SUN C Z. Performance and evaluation of spring wheat heat tolerance. Journal of China Agricultural University, 2000, 5(1):43-49. (in Chinese)
[29]	耿晓丽, 张月伶, 臧新山, 赵月, 张金波, 尤明山, 倪中福, 姚颖垠, 辛明明, 彭惠茹, 孙其信. 北方冬麦区与黄淮北片优良小麦品种(系)耐热性评价. 麦类作物学报, 2017, 36(2):172-181.
	GENG X L, ZHANG Y L, ZANG X S, ZHAO Y, ZHANG J B, YOU M S, NI Z F, YAO Y Y, XIN M M, PENG H R, SUN Q X. Evaluation the thermotolerance of the wheat (Triticum aestivum L.) cultivars and advanced lines collected from the northern china and north area of Huanghuai Winter Wheat regions. Journal of Triticeae Crops, 2016, 36(2):172-181. (in Chinese)
[30]	BHUSAL N, SHARMA P, SAREEN S, SARIAL A K. Mapping QTLs for chlorophyll content and chlorophyll fluorescence in wheat under heat stress. Biologia Plantarum, 2018, 62(7):721-731. doi: 10.1007/s10535-018-0811-6
[31]	DIAS A S, LIDON F C. Evolution of grain filling rate and duration in bread and durum wheat, under heat stress after an-thesis. Journal of Agronomy and Crop Science, 2009, 195(2):137-147. doi: 10.1111/jac.2009.195.issue-2
[32]	LV X K, HAN J, LIAO Y C, LIU Y. Effect of phosphorus and potassium foliage application post-anthesis on grain filling and hormonal changes of wheat. Field Crops Research, 2017, 214:83-93. doi: 10.1016/j.fcr.2017.09.001
[33]	KUMAR R R, GOSWAMI S, GUPTA R, VERMA P, SINGH K, SINGH J P, KUMAR M, SHARMA S K, PATHAK H, RAI R D. The Stress of Suicide: Temporal and spatial expression of putative heat shock protein 70 protect the cells from heat injury in wheat (Triticum aestivum L.). Journal of Plant Growth Regulation, 2015, 35(1):65-82. doi: 10.1007/s00344-015-9508-7
[34]	靳路真, 王洋, 张伟, 邱红梅, 陈健, 候云龙, 马晓萍, 王跃强, 谢甫绨. (大豆品种系)耐热性鉴定及分级评鉴. 中国油料作物学报, 2016, 38(1):77-87.
	JIN L Z, WANG Y, ZHANG W, QIU H M, CHEN J, HOU Y L, MA X P, WANG Y Q, XIE F T. Grading evaluation on heat-tolerance in soybean and identification of heat -tolerant cultivars. Chinese Journal of Oil Crop Sciences, 2016, 38(1):77-87. (in Chinese)
[35]	胡江龙, 郭林涛, 王友华, 周治国. 棉花渍害恢复的生理指示指标探讨[J]. 中国农业科学, 2013, 46(21):4446-4453.
	HU J L, GUO L T, WANG Y H, ZHOU Z G. Physiological indicator of cotton plant in recovery from waterlogging damage. Scientia Agricultura Sinica, 2013, 46(21):4446-4453. (in Chinese)

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

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

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

Analysis of Heat Tolerance of Wheat with Different Genotypes and Screening of Identification Indexes in Huang-Huai-Hai Region

RichHTML

PDF

Abstract

Cite this article

share this article

Figures/Tables 9

References 35

Related Articles 15

Metrics

Comments

Recommended 0

[1]	WANG YangYang,LIU WanDai,HE Li,REN DeChao,DUAN JianZhao,HU Xin,GUO TianCai,WANG YongHua,FENG Wei. Evaluation of Low Temperature Freezing Injury in Winter Wheat and Difference Analysis of Water Effect Based on Multivariate Statistical Analysis [J]. Scientia Agricultura Sinica, 2022, 55(7): 1301-1318.
[2]	WANG XiuXiu,XING AiShuang,YANG Ru,HE ShouPu,JIA YinHua,PAN ZhaoE,WANG LiRu,DU XiongMing,SONG XianLiang. Comprehensive Evaluation of Phenotypic Characters of Nature Population in Upland Cotton [J]. Scientia Agricultura Sinica, 2022, 55(6): 1082-1094.
[3]	BIAN NengFei, SUN DongLei, GONG JiaLi, WANG Xing, XING XingHua, JIN XiaHong, WANG XiaoJun. Evaluation of Edible Quality of Roasted Peanuts and Indexes Screening [J]. Scientia Agricultura Sinica, 2022, 55(4): 641-652.
[4]	LIU Jin,HU JiaXiao,MA XiaoDing,CHEN Wu,LE Si,JO Sumin,CUI Di,ZHOU HuiYing,ZHANG LiNa,SHIN Dongjin,LI MaoMao,HAN LongZhi,YU LiQin. Construction of High Density Genetic Map for RIL Population and QTL Analysis of Heat Tolerance at Seedling Stage in Rice (Oryza sativa L.) [J]. Scientia Agricultura Sinica, 2022, 55(22): 4327-4341.
[5]	SHEN Qian,ZHANG SiPing,LIU RuiHua,LIU ShaoDong,CHEN Jing,GE ChangWei,MA HuiJuan,ZHAO XinHua,YANG GuoZheng,SONG MeiZhen,PANG ChaoYou. Construction of A Comprehensive Evaluation System and Screening of Cold Tolerance Indicators for Cold Tolerance of Cotton at Seedling Emergence Stage [J]. Scientia Agricultura Sinica, 2022, 55(22): 4342-4355.
[6]	HU Xin, ZHANG ZhiLiang, ZHANG Fei, DENG Bo, FANG WeiMin. Comprehensive Evaluation and Selection of Hybrid Offsprings of Large-Flowered Tea Chrysanthemum [J]. Scientia Agricultura Sinica, 2022, 55(20): 4036-4051.
[7]	FANG TaoHong,ZHANG Min,MA ChunHua,ZHENG XiaoChen,TAN WenJing,TIAN Ran,YAN Qiong,ZHOU XinLi,LI Xin,YANG SuiZhuang,HUANG KeBing,WANG JianFeng,HAN DeJun,WANG XiaoJie,KANG ZhenSheng. Application of Yr52 Gene in Wheat Improvement for Stripe Rust Resistance [J]. Scientia Agricultura Sinica, 2022, 55(11): 2077-2091.
[8]	XU Xiao,REN GenZeng,ZHAO XinRui,CHANG JinHua,CUI JiangHui. Accurate Identification and Comprehensive Evaluation of Panicle Phenotypic Traits of Landraces and Cultivars of Sorghum bicolor (L.) Moench in China [J]. Scientia Agricultura Sinica, 2022, 55(11): 2092-2108.
[9]	FAN WenJing,LIU Ming,ZHAO Peng,ZHANG QiangQiang,WU DeXiang,GUO PengYu,ZHU XiaoYa,JIN Rong,ZHANG AiJun,TANG ZhongHou. Screening of Sweetpotato Varieties Tolerant to Low Nitrogen at Seedling Stage and Evaluation of Different Nitrogen Efficiencies [J]. Scientia Agricultura Sinica, 2022, 55(10): 1891-1902.
[10]	LIU QiuYuan,ZHOU Lei,TIAN JinYu,CHENG Shuang,TAO Yu,XING ZhiPeng,LIU GuoDong,WEI HaiYan,ZHANG HongCheng. Comprehensive Evaluation of Nitrogen Efficiency and Screening of Varieties with High Grain Yield and High Nitrogen Efficiency of Inbred Middle-Ripe Japonica Rice in the Middle and Lower Reaches of Yangtze River [J]. Scientia Agricultura Sinica, 2021, 54(7): 1397-1409.
[11]	ZHANG Yan,WANG JinSong,DONG ErWei,WU AiLian,WANG Yuan,JIAO XiaoYan. Comprehensive Evaluation of Low-Fertility Tolerance of Different Sorghum Cultivars in Middle-Late-Maturing Area [J]. Scientia Agricultura Sinica, 2021, 54(23): 4954-4968.
[12]	ZHAO Rui,ZHANG XuHui,ZHANG ChengYang,GUO JingLei,WANG Yu,LI HongXia. Evaluation and Screening of Nitrogen Efficiency of Wheat Germplasm Resources at Mature Stage [J]. Scientia Agricultura Sinica, 2021, 54(18): 3818-3833.
[13]	LIU Xing,CAO HongXia,LIAO Yang,ZHOU ChenGuang,LI HuangTao. Effects of Drip Irrigation Methods on Photosynthetic Characteristics, Yield and Irrigation Water Use of Apple [J]. Scientia Agricultura Sinica, 2021, 54(15): 3264-3278.
[14]	YANG Tao,HUANG YaJie,LI ShengMei,REN Dan,CUI JinXin,PANG Bo,YU Shuang,GAO WenWei. Genetic Diversity and Comprehensive Evaluation of Phenotypic Traits in Sea-Island Cotton Germplasm Resources [J]. Scientia Agricultura Sinica, 2021, 54(12): 2499-2509.
[15]	ZHANG LongYan,CHENG GongMin,WEI HengLing,WANG HanTao,LU JianHua,MA ZhiYing,YU ShuXun. Chilling Tolerance Identification and Response to Cold Stress of Gossypium hirsutum Varieties (Lines) During Germination Stage [J]. Scientia Agricultura Sinica, 2021, 54(1): 19-33.