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Evaluation of Heat Tolerance in Wheat Germplasm Resources
WANG XiaoBo1, GUAN PanFeng1, XIN MingMing1, WANG YongFa1, CHEN XiYong2, ZHAO AiJu2, LIU ManShuang3, LI HongXia3, ZHANG MingYi4, LU LaHu4, WEI YiQin5, LIU WangQing5, ZHANG JinBo6, NI ZhongFu1, YAO YingYin1, HU ZhaoRong1, PENG HuiRu1, SUN QiXin,1通讯作者:
责任编辑: 李莉
收稿日期:2019-05-15接受日期:2019-08-3网络出版日期:2019-12-01
| 基金资助: |
Received:2019-05-15Accepted:2019-08-3Online:2019-12-01
作者简介 About authors
王小波,E-mail：xplayplus@hotmail.com
摘要
关键词：
Abstract
Keywords：
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王小波, 关攀锋, 辛明明, 汪永法, 陈希勇, 赵爱菊, 刘曼双, 李红霞, 张明义, 逯腊虎, 魏亦勤, 刘旺清, 张金波, 倪中福, 姚颖垠, 胡兆荣, 彭惠茹, 孙其信. 小麦种质资源耐热性评价[J]. 中国农业科学, 2019, 52(23): 4191-4200 doi:10.3864/j.issn.0578-1752.2019.23.001
WANG XiaoBo, GUAN PanFeng, XIN MingMing, WANG YongFa, CHEN XiYong, ZHAO AiJu, LIU ManShuang, LI HongXia, ZHANG MingYi, LU LaHu, WEI YiQin, LIU WangQing, ZHANG JinBo, NI ZhongFu, YAO YingYin, HU ZhaoRong, PENG HuiRu, SUN QiXin.
0 引言
【研究意义】随着温室效应的加剧,全球气温不断升高[1]。小麦属于喜凉作物,起源于温带,高温胁迫已成为小麦生产中的主要不利因素之一[2,3,4,5]。据估算,在小麦灌浆期内,温度每高于最适温度（24℃）1℃,产量将下降3%—4%[6]。在中国,黄淮及新疆等小麦主产区高温还常伴随干旱同时出现,形成干热风天气,其危害范围可达该区域小麦种植面积的三分之二左右,使小麦减产10%—20%[7];北方和长江中下游麦区小麦生产中也时常发生“高温逼熟”灾害,直接对小麦生产造成危害[8]。对于稳定粮食产量,提高小麦品种的耐热性是十分有必要的[9,10,11]。因此,鉴定和筛选耐热种质资源,培育耐热品种,以应对气候变化和保障小麦高产稳产具有十分重要的意义。【前人研究进展】小麦耐热性是多基因控制的复杂数量性状[12,13],受环境影响大,性状考察难度也较大。目前,小麦耐热性表型的选择多基于相关性状的间接选择[13]。人工模拟高温胁迫的鉴定方法在小麦种质耐热性研究中应用最为广泛,常用的评价指标有热感指数（heat susceptibility index,HSI）[14,15]、产量指数[16]、细胞膜的热稳定性[17]、冠层温度衰减[18]、灌浆速率[19]等。李世平等[20]利用分期播种的方法模拟大田生产条件下小麦籽粒灌浆后期的高温胁迫,根据千粒重热感指数对34份小麦材料进行耐热性研究,共鉴定出12份后期耐热性较好的材料。温辉芹等[21]利用同样的方法对26份山西省小麦材料进行了耐热性评价,共鉴定出17份耐热材料。李召锋等[16]利用塑料大棚对19份新疆春小麦品种在灌浆中后期进行高温处理,采用千粒重热感指数、产量指数及容重热感指数相结合的方法对供试材料的耐热性进行评价,共鉴定出6份耐热材料。陈冬梅等[22]利用大棚增温的方法对黄淮麦区的100份小麦品种进行耐热性鉴定,根据千粒重热感指数和产量热感指数的综合评定,筛选出26份耐热材料。此外,耿晓丽等[17]、傅晓艺等[23]、仪小梅等[24]还应用了细胞膜热稳定性、抗逆系数和抗逆指数等评价指标对小麦耐热性进行了研究。【本研究切入点】对小麦种质资源进行耐热性评价及筛选是耐热性育种的基础。虽然前人对小麦耐热性方面进行了大量的研究,但研究多集中在耐热鉴定方法评价和小麦对高温的生理生化反应等方面。另外,前人研究利用的材料数目通常较少,且材料来源多为单一生态区,对小麦耐热资源的分布情况也没有研究,亟需对小麦遗传资源进行大规模耐热性评价。【拟解决的关键问题】本研究对搜集的具有广泛代表性的1 325份国内外小麦种质资源（中国小麦核心种质、骨干亲本、来自不同生态区的小麦推广品种和高代品系及国外引进资源）进行耐热性鉴定和分析,基于千粒重热感指数,评价种质资源耐热性,并筛选优异耐热种质,为种质资源的进一步精准评价和耐热性遗传改良提供参考。1 材料与方法
1.1 供试材料
试验材料共1 325份,包括冬麦材料688份,春麦材料637份。其中,国内材料835份,包括了中国小麦核心种质和骨干亲本以及来自中国8大小麦生态区的推广品种和高代品系（北部冬麦区218份,东北春麦区7份,西北春麦区11份,黄淮冬麦区363份,新疆春冬麦区25份,长江中下游冬麦区88份,西南春麦区16份,青藏春冬麦区107份）。另外,还从美国、日本、法国、意大利、罗马尼亚等国家引进冬小麦品种59份,从国际玉米小麦改良中心（International Maize and Wheat improvement Centre,CIMMYT）引进的人工合成六倍体等春小麦种质资源194份,从国际干旱地区农业研究中心（International Center for Agricultural Research in the Dry Areas,ICARDA）引进耐热抗旱春小麦资源237份。春、冬麦材料在各麦区的具体份数和类型见表1。Table 1
表1
表1来自不同地理环境的小麦种质资源耐热性比较
Table 1
| 材料类型 Material type | 材料来源 Material source | 材料数 Number of genotype | 热感系数HSI | 极耐热 所占比率 Percent of extreme heat resistant (%) | 中等耐热 所占比率 Percent of medium heat resistant (%) | 中等热敏感 所占比率 Percent of medium heat sensitive (%) | 极热敏感 所占比率 Percent of extreme heat sensitive (%) | |
|---|---|---|---|---|---|---|---|---|
| 平均BLUP Mean BLUP | 标准差 SD | |||||||
| 冬小麦 | 北部冬麦区 NWWZ | 218 | 1.05 | 0.26 | 1.38 | 44.95 | 49.54 | 4.13 |
| Winter | 黄淮冬麦区 YHRVWWZ | 363 | 0.95 | 0.25 | 4.13 | 51.79 | 43.80 | 0.28 |
| wheat | 青藏春冬麦区 QTPSWWZ | 4 | 0.56 | 0.37 | 25.00 | 75.00 | 0 | 0 |
| 西南冬麦区 SCWWZ | 16 | 0.59 | 0.27 | 31.25 | 68.75 | 0 | 0 | |
| 国外引进品种 GRA | 59 | 1.18 | 0.33 | 1.69 | 25.42 | 57.63 | 15.25 | |
| 长江中下游冬麦区 MLYVWWZ | 28 | 0.74 | 0.30 | 21.43 | 64.29 | 14.29 | 0 | |
| 春小麦 | CIMMYT | 194 | 1.18 | 0.42 | 5.15 | 25.26 | 48.45 | 21.13 |
| Spring | ICARDA | 237 | 0.88 | 0.27 | 8.86 | 54.85 | 35.86 | 0.42 |
| wheat | 长江中下游冬麦区 MLYVWWZ | 60 | 1.07 | 0.39 | 5.00 | 25.00 | 51.67 | 18.33 |
| 东北春麦区 NSWZ | 7 | 0.83 | 0.50 | 28.57 | 28.57 | 42.86 | 0 | |
| 青藏春冬麦区 QTPSWWZ | 103 | 1.00 | 0.29 | 4.85 | 41.75 | 49.51 | 3.88 | |
| 西北春麦区 NSEZ | 11 | 1.16 | 0.27 | 0 | 36.36 | 54.55 | 9.09 | |
| 新疆春冬麦区 XSWWZ | 25 | 0.70 | 0.26 | 28.00 | 60.00 | 12.00 | 0 | |
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1.2 试验方法
冬小麦材料2014—2015年度、2015—2016年度和2016—2017年度分别种植在河北石家庄（114.83°E,38.03°N）、陕西咸阳（108.93°E,34.62°N）和山西临汾（111.52°E,36.08°N）,试验设对照组与高温处理组。对照组于10月1—8日适期播种;高温处理组推迟到2月10—15日左右播种,播种前浸种8 h,在种子胚露白时播种,使其顺利通过春化,在生长后期遭遇高温胁迫,均采用3次重复。春小麦材料试验于2015年、2016年和2017年分别种植在新疆吐鲁番（89.19°E,42.95°N）、银川（106.25°E,38.28°N）,以银川作为对照组,新疆吐鲁番为高温处理组,通过不同地理环境温度的差异实现高温胁迫的目的。两试验点均于3月10日左右适期播种,3次重复。春小麦在当年成熟后随机选取15个主穗,使用杭州万深检测科技有限公司开发的SC-G型自动种子考种分析及千粒重仪测定千粒重,以其最优线性无偏估计值（best linear unbiased prediction,BLUP）作为多年多点千粒重的估计值[25]。利用R的lme4包,基于REML的混合线性模型进行计算。1.3 耐热性评价方法
根据FISCHER与MAURER[26]的方法,利用千粒重的BLUP值计算热感指数（heat susceptibility index,HSI）。HSI=[(1-TGWheatstress/TGWcontrol)/D],其中TGWheatstress为某一小麦材料在热胁迫环境下的千粒重,TGWcontrol为对照环境下的千粒重。D表示胁迫强度,D=(1- Xheatstress/Xcontrol),Xheatstress为所有参试材料在热胁迫环境下千粒重的平均值,Xcontrol为所有参试材料在对照环境下千粒重的平均值。以HSI为耐热性评价指标,评价标准如下：HSI<0.5为极耐热材料,0.5≤HSI<1为中等耐热材料,1≤HSI<1.5为中等热敏感材料,HSI≥1.5为极敏感材料。2 结果
2.1 千粒重联合方差分析
通过对千粒重进行方差分析（表2）,结果表明,冬、春小麦基因型与环境（地点、年份、热处理）以及基因型与环境的交互作用均达到极显著水平。对于冬小麦种质,基因型的平方和占总变异的31.76%;环境中不同处理间的平方和占总变异的42.60%,是变异的主要来源。说明高温胁迫处理对千粒重有较大的影响,这表明通过推迟播种的方法,对冬麦材料耐热性研究是有效的。对于春小麦种质,基因型的平方和是变异的主要来源,占总变异的45.63%,环境中不同地点（即热胁迫处理）间的平方和占总变异的21.97%。说明通过不同地理环境间温度差异对春小麦进行热胁迫处理及评价不同种质材料耐热性是可行的。Table 2
表2
表2千粒重方差分析结果
Table 2
| 材料类型 Material type | 变异来源 Source of variation | 自由度 Degree of freedom | 平方和SS Sum of squares | 均方和MS Mean squares | F值 F value | 变异所占百分数 Total variation (%) | |
|---|---|---|---|---|---|---|---|
| 冬小麦 Winter wheat | 基因型Genotype(G) | 基因型Genotype(G) | 687 | 762885 | 1110 | 102.753*** | 31.76 |
| 环境Environment(E) | 地点Local(L) | 2 | 137384 | 68692 | 6356.252*** | 5.72 | |
| 年份Year(Y) | 2 | 21980 | 10990 | 1016.95*** | 0.92 | ||
| 处理Treatment(T) | 1 | 1023122 | 1023122 | 94672.04*** | 42.60 | ||
| 交互作用Interaction(G×E) | 基因型×地点(G×L) | 1374 | 47536 | 35 | 3.201*** | 1.98 | |
| 基因型×年份(G×Y) | 1374 | 39622 | 29 | 2.668*** | 1.65 | ||
| 基因型×处理(G×T) | 687 | 118705 | 173 | 15.988*** | 4.94 | ||
| 剩余方差 Residual | 23188 | 250593 | 11 | 10.43 | |||
| 春小麦 Spring wheat | 基因型Genotype(G) | 基因型Genotype(G) | 636 | 111558 | 175 | 19.58*** | 45.63 |
| 环境Environment(E) | 地点Local(L) | 1 | 53702 | 53702 | 5994.457*** | 21.97 | |
| 年份Year(Y) | 2 | 294 | 147 | 16.433*** | 0.12 | ||
| 交互作用Interaction(G×E) | 基因型×地点(G×L) | 636 | 14966 | 24 | 2.627*** | 6.12 | |
| 基因型×年份(G×Y) | 845 | 17975 | 21 | 2.375*** | 7.35 | ||
| 剩余方差 Residual | 5131 | 45966 | 9 | 18.80 | |||
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2.2 高温胁迫对千粒重的影响
由于后期高温胁迫主要影响籽粒灌浆,使千粒重下降,进而导致产量降低。为进一步评价高温胁迫的处理效果,比较了不同处理下灌浆期平均最高气温的差异（图1）,发现无论是冬小麦还是春小麦群体,处理组与对照组均存在明显差异。冬小麦热胁迫处理组在灌浆期的平均最高气温为29.71℃,比正常对照组平均高1.91℃;春小麦新疆试验点平均最高气温为37.14℃,比银川试验点高出7.09℃。进一步分析了高温胁迫条件对小麦千粒重的影响,结果（图2和表3）显示,热胁迫处理组千粒重与对照组相比均有显著降低,表明形成了热胁迫选择压力,即高温胁迫明显抑制了小麦籽粒干物质的积累,从而导致千粒重的降低。图1
新窗口打开|下载原图ZIP|生成PPT图1冬小麦（a）和春小麦（b）在灌浆期间正常环境与热胁迫环境的平均最高温度折线图
Fig. 1Line chart of the average maximum temperature of winter (a) and spring (b) wheat under normal and heat stress during grain filling
Table 3
表3
表3灌浆期热胁迫对小麦千粒重的影响
Table 3
| 材料类型 Material type | 试验处理 Test measures | 千粒重 Thousand grain weight (g) | ||
|---|---|---|---|---|
| 最高值Maximum | 最低值Minimum | 平均值Mean | ||
| 冬小麦 Winter wheat | 对照Control group | 57.37 | 23.93 | 44.89 |
| 热胁迫Heat stress group | 43.99 | 17.12 | 32.47 | |
| 春小麦 Spring wheat | 宁夏Ningxia | 55.65 | 31.61 | 44.88 |
| 新疆Xinjiang | 48.47 | 28.41 | 38.95 | |
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图2
新窗口打开|下载原图ZIP|生成PPT图2冬小麦（688份）和春小麦（637份）在正常环境与热胁迫环境条件下千粒重（BLUP）分布
Fig. 2Distribution of thousand grain weight (BLUP) in winter wheat (688 accessions) and spring wheat (637 accessions) under normal and heat stress environmental conditions
2.3 千粒重热感指数分析及耐热性评价
根据热感指数公式分别计算冬小麦材料和春小麦材料在不同环境下的千粒重热感指数（表4）。在688份冬小麦材料中,极耐热、中等耐热、中等热敏感、极热敏感的种质资源分别为31、333、305和19份,分别占4.51%、48.40%、44.33%和2.76%;在637份春麦材料中,极耐热、中等耐热、中等热敏感、极热敏感的种质资源分别为48、258、273和58份,分别占7.54%、40.50%、42.86%和9.11%。参试材料的耐热性存在明显差异,且多数属于中间型（中等耐热或中等热敏感）材料。Table 4
表4
表4供试冬小麦材料（688份）和春小麦材料（637份）耐热性分布
Table 4
| 评价 Evaluation | 热感指数 Heat susceptibility index | 材料数Number of genotype | 比率Percent (%) | ||
|---|---|---|---|---|---|
| 冬小麦Winter wheat | 春小麦Spring wheat | 冬小麦Winter wheat | 春小麦Spring wheat | ||
| 极耐热Extreme heat resistant | HSI<0.5 | 38 | 48 | 4.51 | 7.54 |
| 中等耐热Medium heat resistant | 0.5≤HSI<1 | 323 | 258 | 48.40 | 40.50 |
| 中等热敏感Medium heat sensitive | 1≤HSI<1.5 | 303 | 273 | 44.33 | 42.86 |
| 极敏感Extreme heat sensitive | HSI≥1.5 | 24 | 58 | 2.76 | 9.11 |
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2.4 不同生态区小麦种质耐热性差异
将耐热性鉴定结果按照材料的不同生态区来源进行分析（表1）。对于冬小麦材料,来自南方生态区域的西藏春冬麦区的耐热性最强,平均HSI值为0.56,且所有材料属于耐热（极耐热或中等耐热）材料;其次是来自西南冬小麦区的材料,平均HSI值为0.59,且所有材料属于耐热材料;再次是长江中下游冬麦区的材料,平均HSI值为0.74,且85.72%的材料属于耐热材料。来自黄淮冬麦区和北部冬麦区的材料,耐热性相对较差,HSI的平均值分别为0.95和1.05。来自美国、日本、法国、意大利等国外引进品种的耐热性最弱,平均HSI值为1.18,且72.88%属于热敏感（中等热敏感或极敏感）材料。从冬小麦生态区域的地理分布来看,来自南部麦区的材料相较于北方麦区具有较强的耐热性。对于春小麦,来自新疆春冬小麦区的材料耐热性最强,平均HSI值为0.70,且88.00%的材料属于耐热材料;引进的ICARDA的种质资源,平均HSI值为0.88,且63.71%的材料属于耐热材料。来自CIMMYT的人工合成六倍体材料耐热性最弱,平均HSI为1.18,其中69.58%的材料为热敏感材料。3 讨论
3.1 冬小麦与春小麦的耐热性
由于春小麦和冬小麦是截然不同的两种生态类型,前人在研究小麦耐热性时,通常对春小麦或冬小麦耐热性单独进行研究[16,24]。本研究对春、冬小麦采用不同热胁迫处理方法进行评价,所以无法根据千粒重热感指数比较两者的耐热性,但由于不同基因型间千粒重下降幅度的差异一定程度反映了该基因型对高温胁迫的适应性差异,可以根据对照条件下与热胁迫条件下千粒重的差值进行初步的比较。冬小麦在正常条件下与热胁迫条件下平均最高气温差值为1.94℃;而春小麦在正常条件下与热胁迫条件下平均最高气温差值为7.09℃,可以看出春小麦平均最高气温差值明显高于冬小麦,表明春小麦可能受到了更严重的热胁迫。但冬小麦在正常条件下与热胁迫条件下最高千粒重差值为13.38 g、最低千粒重差值为6.81 g、平均千粒重的差值为12.42 g;而春小麦在正常条件下与热胁迫条件下最高千粒重差值为7.18 g、最低千粒重差值为3.20 g、平均千粒重的差值为5.93 g（表3）,可以看出冬小麦最高、最低以及平均千粒重差值均明显高于春小麦,表明春小麦的耐热性可能要高于冬小麦,春小麦材料中可能存在较为丰富的耐热资源。另外,在实际生产过程中,春小麦的开花时间和成熟时间一般比冬小麦晚,这使得春小麦在灌浆后期比冬小麦更易遭遇选择压力。但由于本研究对春小麦和冬小麦热胁迫处理的方法和试验地点都存在差异,千粒重结果可能会受其他环境条件的影响,所以更加有效地比较春、冬小麦耐热性的方法有待进一步研究。本研究分别筛选出极端耐热的冬小麦（藏冬4号,洛麦23,恩麦4号,郑引4号,武农6等）和春小麦（皖麦19,ICARDA-154,鄂麦23,川麦43,新春16号等）材料,以及极端热敏感的冬小麦（BOGATKA,法国51,豫教5号,泰山4号,衡4399等）和春小麦（HC-131,HC-201,川麦47,贵农005,资麦1号等）材料,可作为小麦耐热性育种和遗传研究的亲本材料。3.2 耐热性与地理环境的关系
由于不同地区自然条件和生态环境的差异,在长期的自然进化和人工选择过程中,不同生态区域的小麦在应对高温胁迫的热敏感性会有明显的差异[27,28]。本研究结果也表明,中国南部生态区域的西南冬麦区和青藏春冬麦区的冬小麦耐热性显著高于其他地区,但青藏春冬麦区的冬小麦材料份数较少（4份）还有待进一步验证;长江中下游冬麦区等低纬度地区冬小麦的耐热性也强于黄淮冬麦区、北部冬麦区等高纬度地区的冬小麦材料。这表明,低纬度地区冬小麦材料整体耐热性强于高纬度地区的冬小麦材料,这可能是由于育种家在田间选种过程中,为适应当地气候环境,在选择高产品种的同时,不自觉地选育了具有一定耐热性的品种。中国的春小麦材料中,北部生态区域的新疆春冬麦区的材料具有很强的耐热性,这可能是在新疆干热风频发的气候条件下的选择结果。同时我们也发现来自ICARDA的春小麦材料也具有较强的耐热性,说明来自ICARDA的材料中挖掘耐热基因的潜力很大,可以在中国未来的小麦耐热育种中加以利用。3.3 耐热种质资源的利用
小麦在灌浆期间遭遇高温胁迫,会造成籽粒灌浆速率减慢、灌浆期缩短,使灌浆提前结束,从而导致千粒重降低,进而影响产量[29,30]。千粒重作为产量三要素之一,其高低会直接影响到品种的丰产性[31,32]。在品种选育和实际生产过程中,既要考虑品种的耐热性,同时也要求供试材料在未遭遇胁迫时具有较高的千粒重以保证品种的丰产性。因此,综合考虑正常条件下的产量潜力以及胁迫后产量的稳定性,结合本研究获得的千粒重及热感指数,对冬麦688份和春麦637份材料进行评价,从中筛选出适用于育种的耐热资源103份（表5）。这些材料具有较强的耐热性,同时具备较高的千粒重和产量潜力,在相应的生态区可以作为耐热性品种推广或作为亲本材料加以利用进行耐热高产的协同改良。Table 5
表5
表5筛选的具有高产潜力的耐热小麦种质资源
Table 5
| 材料类型 Material type | 材料来源 Material source | 材料名称 Material name |
|---|---|---|
| 冬小麦 Winter wheat | 北部冬麦区 NCPWWZ | 农大189 Nongda 189,农大3634 Nongda 3634,晋麦47 Jinmai 47,晋50 Jin 50,农大413 Nongda 413,京冬8号 Jingdong 8,农大212 Nongda 212,农大3659 Nongda 3659,农大3677 Nongda 3677,京冬6号 Jingdong 6,农大3097 Nongda 3097 |
| 黄淮冬麦区 YHRVWWZ | 济南8号 Jinan 8,04洛7671 04 luo 7671,中原麦 Zhongyuanmai,04洛7427 04 luo 7427,武农6 Wunong 6,泰山4606 Taishan 4606,洛麦23 Luomai 23,新麦208 Xinmai 208,新麦20 Xinmai 20,项麦969 Xiangmai 969,跃进5号 Yuejin 5,豫农9901 Yunong 9901,藳优1533-1 Gaoyou 1533-1,偃展4110 Yanzhan 4110,郑农17号 Zhengnong 17,中育8号 Zhongyu 8,新麦19 Xinmai 19,郑麦9962 Zhengmai 9962,新麦21 Xinmai 21,石麦12 Shimai 12,石麦22 Shimai 22,藳优9618 Gaoyou 9618,博农6号 Bonong 6,新麦2111 Xinmai 2111,中育5号 Zhongyu 5,04中36 04zhong 36,山农矮2号 Shannongai 2,新麦11 Xinmai 11,衡6632 Heng 6632,泰山24 Taishan 24,济麦19 Jimai 19,济麦23 Jimai 23,兰考926 Lankao 926,山农辐63 Shannongfu 63,新原9558 Xinyuan 9558,洛麦24 Luomai 24,烟农19 Yannong 19,衡观216 Hengguan 216,邯6628 Han 6628 | |
| 西南冬麦区 SCWWZ | 安麦1号 Anmai 1,安麦7号 Anmai 7 | |
| 国外引进品种 ERA | Haruminori,VICTO,TAM107 | |
| 春小麦 Spring wheat | CIMMYT | HC-18,HC-23,HC-100,HC-106,HC-107,HC-108,HC-114,HC-117,HC-126,HC-133,HC-136,HC-151,HC-176, |
| ICARDA | ICARDA244,ICARDA251,ICARDA263,ICARDA277,ICARDA283,ICARDA301,ICARDA302,ICARDA320,ICARDA330,ICARDA340,ICARDA345,ICARDA350,ICARDA376,ICARDA419 | |
| 长江中下游冬麦区 MLYVWWZ | 鄂恩4号 Een 4,皖麦54 Wanmai 54,华麦8 Huamai 8,荆麦66 Jingmai 66,襄专27 Xiangzhuan 27,扬麦15 Yangmai 15,鄂麦504060 Emai 504060 | |
| 青藏春冬麦区QTPSWWZ | 川麦45 Chuanmai 45,川育19 Chuanyu 19,西科麦1号 Xikemai 1,良麦2号 Liangmai 2,川麦55 Chuanmai 55 | |
| 西北春麦区 NSEZ | 宁春53号 Ningchun 53,宁2038 Ning 2038 | |
| 新疆春冬麦区 XSWWZ | 新春7号 Xinchun 7,新春8号 Xinchun 8,新春11号 Xinchun 11,新春16号 Xinchun 16,新春20号 Xinchun 20,新春24号 Xinchun 24,新春29号 Xinchun 29 |
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4 结论
采用延期播种或在具有高温的地理环境下种植能使小麦在灌浆期遭遇高温胁迫。以千粒重热感指数作为评价指标,对1 325份小麦种质资源进行高通量耐热性鉴定,综合考虑正常条件下的产量潜力和高温条件下的耐热性,筛选出优异耐热资源103份,可用于相应生态区小麦的耐热性遗传改良。参考文献 原文顺序
文献年度倒序
文中引用次数倒序
被引期刊影响因子
DOI:10.1073/pnas.1205276109URL [本文引用: 1]
"Climate dice," describing the chance of unusually warm or cool seasons, have become more and more "loaded" in the past 30 y, coincident with rapid global warming. The distribution of seasonal mean temperature anomalies has shifted toward higher temperatures and the range of anomalies has increased. An important change is the emergence of a category of summertime extremely hot outliers, more than three standard deviations (3 sigma) warmer than the climatology of the 1951-1980 base period. This hot extreme, which covered much less than 1% of Earth's surface during the base period, now typically covers about 10% of the land area. It follows that we can state, with a high degree of confidence, that extreme anomalies such as those in Texas and Oklahoma in 2011 and Moscow in 2010 were a consequence of global warming because their likelihood in the absence of global warming was exceedingly small. We discuss practical implications of this substantial, growing, climate change.
DOI:10.1016/j.scitotenv.2018.02.322URLPMID:29554771 [本文引用: 1]
Limited information exists on potential impacts of climate change on nitrous oxide (N2O) emissions by including N2-fixing legumes in crop rotations from rain-fed cropping systems. Data from two 3-yr crop rotations in northern NSW, Australia, viz. chickpea-wheat-barley (CpWB) and canola-wheat-barley (CaWB), were used to gain an insight on the role of legumes in mitigation of N2O emissions. High-frequency N2O fluxes measured with an automated system of static chambers were utilized to test the applicability of Denitrification and Decomposition model. The DNDC model was run using the on-site observed weather, soil and farming management conditions as well as the representative concentration pathways adopted by the Intergovernmental Panel on Climate Change in its Fifth Assessment Report. The DNDC model captured the cumulative N2O emissions with variations falling within the deviation ranges of observations (0.88±0.31kgNha-1rotation-1 for CpWB, 1.44±0.02kgNha-1rotation-1 for CaWB). The DNDC model can be used to predict between modeled and measured N2O flux values for CpWB (n=390, RSR=0.45) and CaWB (n=390, RSR=0.51). Long-term (80-yr) simulations were conducted with RCP 4.5 representing a global greenhouse gas stabilization scenario, as well RCP 8.5 representing a very high greenhouse gas emission scenario based on RCP scenarios. Compared with the baseline scenarios for CpWB and CaWB, the long-term simulation results under RCP scenarios showed that, (1) N2O emissions would increase by 35-44% for CpWB and 72-76% for CaWB under two climate scenarios; (2) grain yields would increase by 9% and 18% under RCP 4.5, and 2% and 14% under RCP 8.5 for CpWB and CaWB, respectively; and (3) yield-scaled N2O-N emission would increase by 24-42% for CpWB and 46-54% for CaWB under climate scenarios, respectively. Our results suggest that 25% of the yield-scaled N2O-N emission would be saved by switching to a legume rotation under climate change conditions.
DOI:10.1038/srep00066URLPMID:22355585 [本文引用: 1]
New crop cultivars will be required for a changing climate characterised by increased summer drought and heat stress in Europe. However, the uncertainty in climate predictions poses a challenge to crop scientists and breeders who have limited time and resources and must select the most appropriate traits for improvement. Modelling is a powerful tool to quantify future threats to crops and hence identify targets for improvement. We have used a wheat simulation model combined with local-scale climate scenarios to predict impacts of heat stress and drought on winter wheat in Europe. Despite the lower summer precipitation projected for 2050s across Europe, relative yield losses from drought is predicted to be smaller in the future, because wheat will mature earlier avoiding severe drought. By contrast, the risk of heat stress around flowering will increase, potentially resulting in substantial yield losses for heat sensitive cultivars commonly grown in northern Europe.
DOI:10.1016/j.eja.2012.01.009URL [本文引用: 1]
There is much evidence that increasing temperatures due to climate change are having negative effects on yields of key staple crops, including wheat. In France particularly, a link has been shown between the stagnating wheat yields and an increase in heat stress occurrence during grain filling. We studied the occurrence of heat stress during grain filling of wheat under climate change by coupling downscaled weather scenarios from the ARPEGE climate model with a modified version of the ARCWHEAT phenology model. We also explored the effects of different agronomic solutions: earlier sowing, use of earlier cultivars and improved genetic tolerance to heat stress. Results show that in the near future (2020-2049) a small to null increase in heat stress may occur. In the far future (2070-2099), the frequency of heat stress during grain filling should increase significantly. Adaptation through earlier sowing dates proves to be the least efficient. Use of earlier heading cultivars is somewhat efficient, and should be sufficient for the near future. Tolerance to heat stress appears to be the most promising adaptation strategy. We discuss the importance of placing earliness and heat tolerance high on the agenda of wheat research and breeding, and the potential use of modelling in evaluating such strategies. (C) 2012 Elsevier B.V.
DOI:10.1016/j.agrformet.2011.09.002URL [本文引用: 1]
DOI:10.1071/AR9890015URL [本文引用: 1]
URL [本文引用: 1]
Hot weather with dry wind(HDW),commonly termed as dry-hot-wind,is a particular injurious weather for the wheat plants in the stage ofgrain filling.The injurious effects of HDW have determined.HDWstress causes the following irreversible damages:chlorophyll contents ofwheat leaves and then photosynthe
URL [本文引用: 1]
Hot weather with dry wind(HDW),commonly termed as dry-hot-wind,is a particular injurious weather for the wheat plants in the stage ofgrain filling.The injurious effects of HDW have determined.HDWstress causes the following irreversible damages:chlorophyll contents ofwheat leaves and then photosynthe
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DOI:10.1016/j.cj.2017.09.005URL [本文引用: 1]
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DOI:10.1016/j.pbi.2006.01.003URLPMID:16458043 [本文引用: 1]
Homeostasis, a set-value for metabolism under optimal conditions, is rarely achieved by plants because of the cost exerted by external stress factors: climatic, biotic, and nutrient imbalances. Among these, stresses caused by abiotic conditions, such as temperature extremes (freezing, cold and heat), water availability (drought and ion excess) and ion toxicity (salinity and heavy metals), have been difficult to dissect because defense responses to abiotic factors require regulatory changes to the activation of multiple genes and pathways. Genomics technologies that have emerged during the past decade have been useful in addressing, in an integrated fashion, the multigenicity of the plant abiotic stress response through genome sequences; cell-, organ-, tissue- and stress-specific transcript collections; transcript, protein and metabolite profiles and their dynamic changes; protein interactions; and mutant screens.
DOI:10.1007/s13562-013-0229-3URL [本文引用: 2]
Global warming is causing changes in temperature rapidly for over two decades. The increased temperature during reproductive phase of plant growth has emerged as a serious problem all over the world. Constant or transitory high temperatures may affect the plant growth and development which may lead to diverse morphological, physiological and biochemical changes in plants ultimately decrease in yield. Genetic approaches leading to improved thermo-tolerance can mitigate the reduction in yield. In this backdrop, several indirect traits or parameters have been developed for identification of heat tolerant plants/lines. The traits like stay green/delayed senescence are reported to contribute toward capability of plants to tolerate heat stress. In addition, understanding of biochemical and molecular basis of thermo-tolerance in combination with genetic approaches like identification and mapping of heat tolerant QTLs will not only assist conventional breeders to develop heat tolerant cultivars but also help molecular biologists to clone and characterize genes associated with heat tolerance, which could be used in genetically modified heat tolerant plants. Therefore, overviews of different strategies for developing heat tolerant wheat are discussed in this review.
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DOI:10.1007/s00122-012-1853-3URL [本文引用: 1]
High temperature (> 30 A degrees C) at the time of grain filling is one of the major causes of yield reduction in wheat in many parts of the world, especially in tropical countries. To identify quantitative trait loci (QTL) for heat tolerance under terminal heat stress, a set of 148 recombinant inbred lines was developed by crossing a heat-tolerant hexaploid wheat (Triticum aestivum L.) cultivar (NW1014) and a heat-susceptible (HUW468) cultivar. The F-5, F-6, and F-7 generations were evaluated in two different sowing dates under field conditions for 2 years. Using the trait values from controlled and stressed trials, four different traits (1) heat susceptibility index (HSI) of thousand grain weight (HSITGW); (2) HSI of grain fill duration (HSIGFD); (3) HSI of grain yield (HSIYLD); and (4) canopy temperature depression (CTD) were used to determine heat tolerance. Days to maturity was also investigated. A linkage map comprising 160 simple sequence repeat markers was prepared covering the whole genome of wheat. Using composite interval mapping, significant genomic regions on 2B, 7B and 7D were found to be associated with heat tolerance. Of these, two (2B and 7B) were co-localized QTL and explained more than 15 % phenotypic variation for HSITGW, HSIGFD and CTD. In pooled analysis over three trials, QTL explained phenotypic variation ranging from 9.78 to 20.34 %. No QTL x trial interaction was detected for the identified QTL. The three major QTL obtained can be used in marker-assisted selection for heat stress in wheat.
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DOI:10.1016/S0378-4290(02)00138-7URL [本文引用: 1]
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The objective of this study was to estimate inheritance of the grain filling rate as indicator for heat tolerant genes. The minimum number of genes for the trait in bread wheat was also assessed by combining quantitative genetic estimates and SSR marker analyses. Two cultivars, Debra (heat-tolerant) and Yecora Rojo (heat-sensitive) crossed and F-1 and F-2 populations generated. The parents, F-1 and 162 F-2 plants were planted in winter season 2009 to evaluate heat tolerance during the grain-filling period. The sowing date in the present investigation represents the heat stress conditions in Saudi Arabia. The minimum number of genes or factors controlling heat tolerance was estimated (1.5) and the broad sense heritability was estimated as 47.7 %. The results revealed that three SSR markers; Xgwm132, Xgwm577 and Xgwm617 were linked to grain filling rate (GFR) by quantitative trait loci (QTL) analysis of the F-2 population. The results showed that regression analysis for the relationship between the three markers (Xgwm132, Xgwm577 and Xgwm617) and the phenotypes of F-2 plants were highly significant and the coefficients of determination (R-2) were 0.07, 0.25 and 0.03, respectively. This indicates that these three markers were associated with the grain filling rate as indicator for heat tolerant genes. The adjusted R-2 values suggested that the Xgwm132, Xgwm577 and Xgwm617 accounted for 7%, 25% and 3% of the total phenotypic variation of heat tolerance in the F-2 population, respectively. The results demonstrated that SSR markers, combined with bulked segregant analysis, could be used to identify molecular markers linked to the grain filling rate as indicator for heat tolerance in wheat.
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DOI:10.1038/ng.3636URLPMID:27526320 [本文引用: 1]
Maize production is threatened by drought stress worldwide. Identification of the genetic components underlying drought tolerance in maize is of great importance. Here we report a genome-wide association study (GWAS) of maize drought tolerance at the seedling stage that identified 83 genetic variants, which were resolved to 42 candidate genes. The peak GWAS signal showed that the natural variation in ZmVPP1, encoding a vacuolar-type H(+) pyrophosphatase, contributes most significantly to the trait. Further analysis showed that a 366-bp insertion in the promoter, containing three MYB cis elements, confers drought-inducible expression of ZmVPP1 in drought-tolerant genotypes. Transgenic maize with enhanced ZmVPP1 expression exhibits improved drought tolerance that is most likely due to enhanced photosynthetic efficiency and root development. Taken together, this information provides important genetic insights into the natural variation of maize drought tolerance. The identified loci or genes can serve as direct targets for both genetic engineering and selection for maize trait improvement.
DOI:10.1071/AR9780897URL [本文引用: 1]
DOI:10.3864/j.issn.0578-1752.2018.02.017URL [本文引用: 1]
【Objective】Global warming has been recognized as a key impact factor for wheat growth and development. However, the responses of wheat growth and development to warming are still remain unclear, and have not been systemically quantified in different climate regions of main wheat producing area in China. Therefore, there is a special need to systematically quantify the magnitude and mechanisms of field warming impacts on wheat yield and growing period at different periods in a day and the main climatic regions. 【Method】This study collected 21 published literatures between 1990-2017 from nationwide with the effects of field warming on wheat yield and development. In addition, the Meta-analysis was used to systemically quantify the magnitude of field warming during entire wheat growing season on wheat yield and growing period at different climate regions. 【Result】 The results indicated that: (1) Field warming (0-3 °C) significantly increased the wheat yield, thousand kernel weight, and grain number per spike under subtropical monsoon climate whose the average growth rates were 8.2%, 6.3%, and 4.7%, respectively, and significantly increased the wheat yield, spike numbers, and grain number per spike under temperate monsoon climate whose the average growth rates were 6.8%, 3.9% and 5.5%; By contrary, field warming (0-3 °C) reduced the wheat yield, thousand kernel weight and grain number per spike under temperate continental climate whose the average change rates were 10.2%, 5.9%, and 8.3%, respectively. Specifically, the wheat yield significantly were increased (8.5%) by 0-2 °C of field warming and were not significantly changed by 2-3 °C of field warming under subtropical monsoon climate; The increment of wheat yield by 2-3 °C of field warming was 14.5% under temperate monsoon climate; On the contrary, wheat yield were significantly reduced by 10.1% and 15.9% by 0-2 °C and 2-3 °C of field warming under temperate continental climate, respectively. (2) The entire duration of wheat growing period was shorten by 3.3% and 7.1% by field warming (0-3 °C) under subtropical monsoon climate and temperate monsoon climate, but was not changed apparently under temperate continental climate. At the same time, the duration of wheat reproductive period in temperate monsoon climate and temperate continental climate were not changed significantly, while the duration of reproductive growth in subtropical monsoon climate was increased significantly (8.7%). (3) On the whole, though the effects of warming period in a day on wheat yield and development were varied among different climatic regions, the wheat yield were significantly increased by 10.5% and 15.0% under 0-2 °C and 2-3 °C of night warming within all climatic regions. 【Conclusion】 The effect magnitude of field warming on wheat yield and growing period was varied under different climatic regions and the period in a day. The findings of this study could provide scientific base for rational optimization and arrangement of cropping system within the main producing areas in China under new climate change situations.
DOI:10.3864/j.issn.0578-1752.2018.02.017URL [本文引用: 1]
【Objective】Global warming has been recognized as a key impact factor for wheat growth and development. However, the responses of wheat growth and development to warming are still remain unclear, and have not been systemically quantified in different climate regions of main wheat producing area in China. Therefore, there is a special need to systematically quantify the magnitude and mechanisms of field warming impacts on wheat yield and growing period at different periods in a day and the main climatic regions. 【Method】This study collected 21 published literatures between 1990-2017 from nationwide with the effects of field warming on wheat yield and development. In addition, the Meta-analysis was used to systemically quantify the magnitude of field warming during entire wheat growing season on wheat yield and growing period at different climate regions. 【Result】 The results indicated that: (1) Field warming (0-3 °C) significantly increased the wheat yield, thousand kernel weight, and grain number per spike under subtropical monsoon climate whose the average growth rates were 8.2%, 6.3%, and 4.7%, respectively, and significantly increased the wheat yield, spike numbers, and grain number per spike under temperate monsoon climate whose the average growth rates were 6.8%, 3.9% and 5.5%; By contrary, field warming (0-3 °C) reduced the wheat yield, thousand kernel weight and grain number per spike under temperate continental climate whose the average change rates were 10.2%, 5.9%, and 8.3%, respectively. Specifically, the wheat yield significantly were increased (8.5%) by 0-2 °C of field warming and were not significantly changed by 2-3 °C of field warming under subtropical monsoon climate; The increment of wheat yield by 2-3 °C of field warming was 14.5% under temperate monsoon climate; On the contrary, wheat yield were significantly reduced by 10.1% and 15.9% by 0-2 °C and 2-3 °C of field warming under temperate continental climate, respectively. (2) The entire duration of wheat growing period was shorten by 3.3% and 7.1% by field warming (0-3 °C) under subtropical monsoon climate and temperate monsoon climate, but was not changed apparently under temperate continental climate. At the same time, the duration of wheat reproductive period in temperate monsoon climate and temperate continental climate were not changed significantly, while the duration of reproductive growth in subtropical monsoon climate was increased significantly (8.7%). (3) On the whole, though the effects of warming period in a day on wheat yield and development were varied among different climatic regions, the wheat yield were significantly increased by 10.5% and 15.0% under 0-2 °C and 2-3 °C of night warming within all climatic regions. 【Conclusion】 The effect magnitude of field warming on wheat yield and growing period was varied under different climatic regions and the period in a day. The findings of this study could provide scientific base for rational optimization and arrangement of cropping system within the main producing areas in China under new climate change situations.
DOI:10.1017/S0021859612000639URL [本文引用: 1]
Agricultural systems are challenged by global climatic change in a scenario of increasing food demand by a growing population. The increase in average temperature will be the main environmental factor affecting the crop development and productivity worldwide, although changes in carbon dioxide (CO2) concentration and rainfall are also expected. Global warming in the range of moderately high temperatures (15-32 degrees C) is projected for temperate environments such as that of central-southern Chile, where grain crops such as wheat are widely grown. The present study assessed the impact of moderately high temperatures on both yield and quality traits of wheat during key stages for grain number and grain weight determination. Two cultivars of spring wheat (Pandora INIA and Huayun INIA) were grown under field conditions during two cropping seasons (2006/07 and 2007/08) under different thermal regimes, consisting of a combination of three temperatures (a control at ambient temperature and two increased temperature treatments, ranging from 2.6 to 11.7 degrees C above the control) and two (3-15 and 20-32 days after anthesis) or three (booting to anthesis (Bo-At), 3-15 and 20-32 days after anthesis) timing regimes. The data recorded showed that the extent of yield reduction was strongly dependent on the timing of the heat treatments. Increased temperature at pre- (Bo-At) or early post-anthesis (3-15 days after anthesis) affected grain yield the most (reducing it by 8-30%). In light of these results, yield reductions of up to 18% can be expected when the crop undergoes average temperature increase of 2.8 degrees C at Bo-At. In this study, the negative effect of increasing temperature on grain yield was associated with both grain number and grain weight reductions; however, different sensitivities to higher temperatures were found between cultivars. Although protein concentration of grains was not affected by higher temperatures, other negative effects on industrial quality traits are important, considering the impact of thermal treatments on grain size of both cultivars.
URL [本文引用: 1]
植物超富集重金属机理主要涉及植物对金属离子高的吸收、运输能力, 区域化作用及螯合作用等方面,其中跨膜运载蛋白的表达、调控对重金属超富集这一特性起了关键作用.金属阳离子运载蛋白家族主要包括CDF家族、NRAMP家族和ZIP家族等,在超富集植物中已克隆出多个家族的金属运载蛋白基因,这些基因的过量表达对重金属在细胞中的运输、分布和富集及提高植物的抗性方面发挥了重要作用.综述了近年来研究重金属超富集植物吸收、转运和贮存Zn、Ni、Cd等重金属的生理和分子机制所取得的主要进展.
URL [本文引用: 1]
植物超富集重金属机理主要涉及植物对金属离子高的吸收、运输能力, 区域化作用及螯合作用等方面,其中跨膜运载蛋白的表达、调控对重金属超富集这一特性起了关键作用.金属阳离子运载蛋白家族主要包括CDF家族、NRAMP家族和ZIP家族等,在超富集植物中已克隆出多个家族的金属运载蛋白基因,这些基因的过量表达对重金属在细胞中的运输、分布和富集及提高植物的抗性方面发挥了重要作用.综述了近年来研究重金属超富集植物吸收、转运和贮存Zn、Ni、Cd等重金属的生理和分子机制所取得的主要进展.
DOI:10.1007/s00122-008-0901-5URL [本文引用: 1]
A set of 142 winter wheat recombinant inbred lines (RILs) deriving from the cross Heshangmai×Yu8679 were tried in four ecological environments during the seasons 2006 and 2007. Nine agronomic traits comprising mean grain filling rate (GFRmean), maximum grain filling rate (GFRmax), grain filling duration (GFD), grain number per ear (GNE), grain weight per ear (GWE), flowering time (FT), maturation time (MT), plant height (PHT) and thousand grain weight (TGW) were evaluated in Beijing (2006 and 2007), Chengdu (2007) and Hefei (2007). A genetic map comprising 173 SSR markers and two EST markers was generated. Based on the genetic map and phenotypic data, quantitative trait loci (QTL) were mapped for these agronomic traits. A total of 99 putative QTLs were identified for the nine traits over four environments except GFD, PHT and MT, measured in two environments (BJ07 and CD07), respectively. Of the QTL detected, 17 for GFRmean, 16 for GFRmax, 21 for TGW and 10 for GWE involving the chromosomes 1A, 1B, 2A, 2D, 3A, 3B, 3D, 4A, 4D, 5A, 5B, 6D and 7D were identified. Moreover, 13 genomic regions showing pleiotropic effects were detected in chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 4B, 4D, 5B, 6D and 7D; these QTL revealing pleiotropic effects may be informative for a better understanding of the genetic basis of grain filling rate and other yield-related traits, and represent potential targets for multi-trait marker aided selection in wheat.
DOI:10.1371/journal.pone.0031249URLPMID:22363596 [本文引用: 1]
Grain yield is a key economic driver of successful wheat production. Due to its complex nature, little is known regarding its genetic control. The goal of this study was to identify important quantitative trait loci (QTL) directly and indirectly affecting grain yield using doubled haploid lines derived from a cross between Hanxuan 10 and Lumai 14.
DOI:10.3389/fpls.2015.01099URLPMID:26734019 [本文引用: 1]
Identification of genes for yield components, plant height (PH), and yield-related physiological traits and tightly linked molecular markers is of great importance in marker-assisted selection (MAS) in wheat breeding. In the present study, 246 F8 RILs derived from the cross of Zhou 8425B/Chinese Spring were genotyped using the high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay. Field trials were conducted at Zhengzhou and Zhoukou of Henan Province, during the 2012-2013 and 2013-2014 cropping season under irrigated conditions, providing data for four environments. Analysis of variance (ANOVA) of agronomic and physiological traits revealed significant differences (P &lt; 0.01) among RILs, environments, and RILs × environments interactions. Broad-sense heritabilities of all traits including thousand kernel weight (TKW), PH, spike length (SL), kernel number per spike (KNS), spike number/m(2) (SN), normalized difference in vegetation index at anthesis (NDVI-A) and at 10 days post-anthesis (NDVI-10), SPAD value of chlorophyll content at anthesis (Chl-A) and at 10 days post-anthesis (Chl-10) ranged between 0.65 and 0.94. A linkage map spanning 3609.4 cM was constructed using 5636 polymorphic SNP markers, with an average chromosome length of 171.9 cM and marker density of 0.64 cM/marker. A total of 866 SNP markers were newly mapped to the hexaploid wheat linkage map. Eighty-six QTL for yield components, PH, and yield-related physiological traits were detected on 18 chromosomes except 1D, 5D, and 6D, explaining 2.3-33.2% of the phenotypic variance. Ten stable QTL were identified across four environments, viz. QTKW.caas-6A.1, QTKW.caas-7AL, QKNS.caas-4AL, QSN.caas-1AL.1, QPH.caas-4BS.2, QPH.caas-4DS.1, QSL.caas-4AS, QSL.caas-4AL.1, QChl-A.caas-5AL, and QChl-10.caas-5BL. Meanwhile, 10 QTL-rich regions were found on chromosome 1BS, 2AL (2), 3AL, 4AL (2), 4BS, 4DS, 5BL, and 7AL exhibiting pleiotropic effects. These QTL or QTL clusters are tightly linked to SNP markers, with genetic distances to the closest SNPs ranging from 0 to 1.5 cM, and could serve as target regions for fine mapping, candidate gene discovery, and MAS in wheat breeding.
