Resistance Level and Mechanism of Descurainia sophia to Florasulam in Wheat Field of Shandong Province
GAO XingXiang, ZHANG YueLi, LI Mei,, LI Jian, FANG FengInstitute of Plant Protection, Shandong Academy of Agricultural Sciences, Ji’nan 250100通讯作者:
责任编辑: 岳梅
收稿日期:2019-12-30接受日期:2020-03-2网络出版日期:2020-06-16
基金资助: |
Received:2019-12-30Accepted:2020-03-2Online:2020-06-16
作者简介 About authors
高兴祥,E-mail:xingxiang02@163.com。
张悦丽,E-mail:yueligaoxing@163.com。
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高兴祥, 张悦丽, 李美, 李健, 房锋. 山东省小麦田播娘蒿对双氟磺草胺抗性水平及靶标抗性机理[J]. 中国农业科学, 2020, 53(12): 2399-2409 doi:10.3864/j.issn.0578-1752.2020.12.008
GAO XingXiang, ZHANG YueLi, LI Mei, LI Jian, FANG Feng.
0 引言
【研究意义】随着双氟磺草胺(florasulam)在我国冬小麦田的大面积应用,部分区域已发现小麦田主要阔叶杂草播娘蒿(Descurainia sophia)对双氟磺草胺的敏感性降低,在田间造成防治效果下降的现象,研究播娘蒿对双氟磺草胺的抗性水平和抗性机理,对制定抗性杂草区域性治理技术具有重要意义。【前人研究进展】播娘蒿是我国小麦田常见的一种恶性阔叶杂草,在华东、华北、东北、西北等地区均有分布,是黄淮海冬小麦田最主要的越年生阔叶杂草,在河南[1]、山东[2]和河北[3]等省发生优势度均居于前三位。播娘蒿因其茎叶伸展侵占面积大,与禾本科作物小麦竞争有效资源占尽优势,严重影响小麦产量和品质[4,5],对播娘蒿的抗性研究主要集中于其对苯磺隆(tribenuron-methyl)的抗性,据报道播娘蒿抗苯磺隆主要是基因位点突变,第197、376和574位发生突变,且以197位点发生突变为主,约占90%[6]。双氟磺草胺是美国陶氏益农公司在20世纪90年代中期开发成功的第5个三唑嘧啶磺酰胺类除草剂新品种[7],对小麦田几乎所有的阔叶杂草包括播娘蒿、荠菜、猪殃殃等均有很好的防除效果[8],是继苯磺隆之后在小麦田用量最大的除草剂[9],并可与植物生长调节剂、杀菌剂、其他除草剂等混用,现在黄淮海冬小麦田防除阔叶杂草的配方中几乎都有双氟磺草胺这一成分[10],但该药剂在我国应用多年后,对部分区域播娘蒿等阔叶杂草防治效果已明显下降。关于小麦田阔叶杂草对双氟磺草胺抗性报道不多,马鹏生[11]报道了部分猪殃殃种群对双氟磺草胺产生一定抗性,也有抗苯磺隆的荠菜种群对双氟磺草胺产生交互抗性的报道[12],但均无抗性机理报道,而另一种重要阔叶杂草播娘蒿未见抗双氟磺草胺报道。【本研究切入点】笔者在田间调查时发现,因为双氟磺草胺具有杀草谱广、用量少等优点,近几年在小麦田推广面积很大,部分区域已发现用量在提高,防治效果下降现象,这很可能与播娘蒿对双氟磺草胺产生抗性有关。【拟解决的关键问题】在山东省冬小麦田主产区采集播娘蒿种子40份,采用整株生物测定法,研究播娘蒿种群对双氟磺草胺和对比药剂苯磺隆、2甲4氯(MCPA)3种除草剂的抗性水平,并对高抗双氟磺草胺播娘蒿种群进行靶标抗性位点测定,为小麦田杂草抗药性精准治理提供理论依据。1 材料与方法
1.1 供试材料
播娘蒿种子:2017年5月于山东省17地(市)小麦田采集自然成熟的播娘蒿种子,装入牛皮纸袋,种子自然晾干后储藏柜低温储藏。种群名称以采集点所在地级市的首字母缩写命名(表1)。Table 1
表1
表140个播娘蒿种群采集地点
Table 1
序号 Number | 采集地点 Collection site | 序号 Number | 采集地点 Collection site | |
---|---|---|---|---|
BZ-1 | 滨州市邹平县台子镇 Taizi Town, Zouping County, Binzhou City | LY-2 | 临沂市郯城县胜利镇 Shengli Town, Tancheng County, Linyi City | |
BZ-2 | 滨州市惠民县胡集镇 Huji Town, Huimin County, Binzhou City | LY-3 | 临沂市费县探义镇 Tanyi Town, Fei County, Linyi City | |
DY-1 | 东营市利津县北宋镇 Beisong Town, Lijin County, Dongying City | LY-4 | 临沂市沂南县青驼镇 Qingtuo Town, Yi’nan County, Linyi City | |
DZ-1 | 德州市庆云县常家镇 Changjia Town, Qingyun County, Dezhou City | QD-1 | 青岛市莱西区河头店镇 Hetoudian Town, Laixi District, Qingdao City | |
DZ-2 | 德州市平原县恩城镇 Encheng Town, Pingyuan County, Dezhou City | QD-2 | 青岛市平度市云山镇 Yunshan Town, Pingdu County, Qingdao City | |
DZ-3 | 德州市武城县武城镇 Wucheng Town, Wucheng County, Dezhou City | RZ-1 | 日照市莒县小店镇 Xiaodian Town, Ju County, Rizhao City | |
HZ-1 | 菏泽市成武县张楼镇 Zhanglou Town, Chengwu County, Heze City | RZ-2 | 日照市五莲县西湖镇 Xihu Town, Wulian County, Rizhao City | |
HZ-2 | 菏泽市巨野县田桥镇 Tianqiao Town, Juye County, Heze City | TA-1 | 泰安市东平县大洋镇 Dayang Town, Dongping County, Taian City | |
JN-1 | 济南市长清区张夏镇 Zhangxia Town, Changqing District, Ji’nan City | TA-2 | 泰安市肥城县老城街道 Laocheng Street, Feicheng County, Taian City | |
JN-2 | 济南市历城区王舍人镇 Wangsheren Town, Licheng District, Ji’nan City | TA-3 | 泰安市宁阳县磁窑镇 Ciyao Town, Ningyang County, Taian City | |
JN-3 | 济南市章丘区刁镇 Diao Town, Zhangqiu District, Ji’nan City | WF-1 | 潍坊市潍城区于河街道 Yuhe Street, Weicheng District, Weifang City | |
JNI-1 | 济宁市汶上县郭仓镇 Guocang Town, Wenshang County, Jining City | WF-2 | 潍坊市昌邑市卜庄镇 Bozhuang Town, Changyi County, Weifang City | |
JNI-2 | 济宁市梁山县韩岗镇 Hangang Town, Liangshan County, Jining City | WF-3 | 潍坊市临朐县沂山镇 Yishan Town, Linqu County, Weifang City | |
JNI-3 | 济宁市嘉祥县疃里镇 Tuanli Town, Jiaxiang County, Jining City | WH-1 | 威海市乳山市夏村镇 Xiacun Town, Rushan County, Weihai City | |
JNI-4 | 济宁市任城区南张镇 Nanzhuang Town, Rencheng District, Jining City | YT-1 | 烟台市莱州市沙河镇 Shahe Town, Laizhou County, Yantai City | |
LC-1 | 聊城市莘县古城镇 Gucheng Town, Shen County, Liaocheng City | YT-2 | 烟台市莱阳市河头店镇 Hetoudian Town, Laiyang County, Yantai City | |
LC-2 | 聊城市阳谷县西湖镇 Xihu Town, Yanggu County, Liaocheng City | ZB-1 | 淄博市周村区南郊镇 Nanjiao Town, Zhoucun District, Zibo City | |
LC-3 | 聊城市东昌府区侯营镇 Houying Town, Dongchangfu District, Liaocheng City | ZB-2 | 淄博市临淄区齐陵街道 Qiling Street, Linzi District, Zibo City | |
LW-1 | 莱芜市莱城区口镇 Kou Town, Laicheng District, Laiwu City | ZZ-1 | 枣庄市滕州市鲍沟镇 Baogou Town, Tengzhou County, Zaozhuang City | |
LY-1 | 临沂市兰陵县卢柞镇 Luzuo Town, Lanling County, Linyi City | ZZ-2 | 枣庄市薛城区周营镇 Zhouying Town, Xuecheng District, Zaozhuang City |
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除草剂:98%双氟磺草胺原药,沈阳科创化学品有限公司;95%苯磺隆原药,江苏省激素研究所股份有限公司;95% 2甲4氯原药,江苏辉丰生物农业股份有限公司。
1.2 试验方法
1.2.1 抗性水平测定 试验于2018年2—4月进行,在玻璃温室中进行播娘蒿试材的培养,光照为自然光,温度靠暖气调整,试验期间温室温度为14—28℃。每个采集样点的播娘蒿为一个种群,在直径为9 cm的塑料盆中单独种植,覆土1—2 mm,每个种群种植64盒,将塑料盒放入装有水的搪瓷盘中,以盆钵底部渗灌方式浇水,每隔3 d浇水一次,保持土壤湿度。抗性测定采用盆栽整株剂量-反应测定法[4]。根据预试验,每种除草剂设置5个剂量,其中双氟磺草胺剂量为0.37、1.11、3.33、10.0、30.0 g·hm-2;苯磺隆剂量为5、20、80、320、1 280 g·hm-2;2甲4氯剂量为22.2、66.7、200、600、1 800 g·hm-2,每个种群均设置单独空白对照,每处理4次重复,于播娘蒿3—6叶期,采用ASS-4型自动控制喷洒系统进行药剂喷雾,喷头为扇形喷头,喷雾压力为0.35 MPa,用水量按照每公顷450 L计算。
施药后,观察同一种药剂下,40个播娘蒿种群的敏感差异,详细记录播娘蒿表现症状、表现时期以及不同种群的敏感差异。施药后30 d,用剪刀剪取各种群各处理播娘蒿地上部分,称量鲜重,每个种群根据相应的空白对照鲜重,计算鲜重抑制率。鲜重抑制率(%)=100×(空白对照鲜草重-处理区鲜草重)/空白对照鲜草重。
1.2.2 ALS基因突变分析 根据播娘蒿ALS基因序列(GenBank:FJ715633),设计引物(DS-F 5′ GGTA TCAAATCCCGTGCTCT 3′和DS-R 5′ CATATGCA TACAATCACCGGTT 3′),扩增片段包含目前已报道所有抗性相关位点。参照1.2.1的方法进行播娘蒿高抗种群植株的种植,待播娘蒿长到3—4叶时,采集药剂处理后存活植株的单株叶片,采用植物基因组提取试剂盒(TaKaRa)提取基因组DNA,具体提取方法参照试剂盒相关流程;PCR克隆(25 μL反应体系,参数为94℃ 3 min;95℃ 30 s,53℃ 45 s,72℃ 2min,30个循环;72℃ 10 min)其ALS基因序列,使用UNlQ-10 DNA纯化试剂盒(上海生工生物工程有限公司)回收PCR产物并送上海生工生物工程有限公司测序。将测序后获得序列与拟南芥敏感型ALS基因和氨基酸序列进行比对,查找相关突变位点。每个种群检测10株。
1.3 数据分析
用DPS 7.05软件对药剂剂量的对数值与鲜重抑制率的概率值进行回归分析,得到剂量-反应曲线、相关系数、抑制杂草生长50%的除草剂剂量(GR50)及95%置信区间。由于不同种群本身种子活力、生长势等有差异,所以相对抗性指数(resistance index,RI)<5.00的均认定为敏感种群,RI=GR50(R)/ GR50(S),其中GR50(R)为抗性种群的GR50值,GR50(S)为敏感种群的GR50值。抗性判断参考高兴祥等[4]:1.00≤RI<5.00为敏感种群,5.00≤RI<10.00为低抗性种群,10.00≤RI<50.00为中抗性种群,RI≥50.00为高抗性种群。2 结果
2.1 播娘蒿对双氟磺草胺抗性水平测定
双氟磺草胺药效表现较慢,施药后7 d播娘蒿开始出现黄化,而后生长被抑制,至药后15 d后开始死亡。40个播娘蒿种群中大部分种群对双氟磺草胺敏感,但BZ-1、DZ-3、LC-3、LY-4、YT-1 5个种群敏感性明显低于其他种群。施药后30 d调查结果统计(表2)可见,双氟磺草胺对大部分播娘蒿种群效果很好,最敏感种群是DY-1和JNI-4,GR50均为0.11 g·hm-2,敏感种群有32个,占80.00%,抗性种群有8个,占总种群数的20.00%,部分种群抗性已很明显。其中低抗、中抗和高抗种群数量分别为3、3和2个,各自占总种群数的7.50%、7.50%和5.00%。从山东省不同区域来看,对双氟磺草胺产生抗性的播娘蒿种群分布无明显规律,8个抗性种群分布于7个地(市),最高抗性种群为DZ-3,RI为194.00。
Table 2
表2
表2播娘蒿种群对双氟磺草胺抗性水平测定
Table 2
序号 Number | 回归方程 Regression equation (y=) | 相关系数 Correlation coefficient | GR50 (g·hm-2) (95% CL) | 相对抗性指数 RI |
---|---|---|---|---|
BZ-1 | 3.0871+2.5252x | 0.9220 | 5.72 (3.89-10.98) | 52.00 |
BZ-2 | 6.7548+2.0988x | 0.8926 | 0.15 (0.01-0.39) | 1.36 |
DY-1 | 6.1746+1.2088x | 0.9405 | 0.11 (0.02-0.26) | 1.00 |
DZ-1 | 6.1210+1.8228x | 0.8825 | 0.24 (0.08-0.45) | 2.18 |
DZ-2 | 6.1178+1.5045x | 0.8717 | 0.18 (0.001-0.62) | 1.64 |
DZ-3 | 3.7060+0.9736x | 0.8519 | 21.34 (13.81-39.62) | 194.00 |
HZ-1 | 5.6433+1.2505x | 0.9203 | 0.31 (0.14-0.51) | 2.82 |
HZ-2 | 6.2837+2.3134x | 0.8914 | 0.28 (0.10-0.50) | 2.55 |
JN-1 | 5.4469+1.6999x | 0.9475 | 0.55 (0.33-0.78) | 5.00 |
JN-2 | 5.5627+1.0454x | 0.8902 | 0.29 (0.002-0.97) | 2.64 |
JN-3 | 6.1607+1.3459x | 0.9459 | 0.14 (0.03-0.31) | 1.27 |
JNI-1 | 5.6161+2.1229x | 0.9679 | 0.51 (0.30-0.74) | 4.64 |
JNI-2 | 5.3038+1.5719x | 0.9333 | 0.64 (0.18-1.20) | 5.82 |
JNI-3 | 6.4349+1.5358x | 0.8804 | 0.12 (0.01-0.30) | 1.09 |
JNI-4 | 6.5989+1.6727x | 0.9630 | 0.11 (0.01-0.31) | 1.00 |
LC-1 | 6.6323+1.9998x | 0.8911 | 0.15 (0.02-0.38) | 1.36 |
LC-2 | 6.2404+1.7165x | 0.9655 | 0.19 (0.05-0.39) | 1.73 |
LC-3 | 3.3624+2.2387x | 0.9631 | 5.39 (3.89-8.22) | 49.00 |
LW-1 | 5.6180+1.4674x | 0.9352 | 0.38 (0.19-0.59) | 3.45 |
LY-1 | 6.4307+2.3490x | 0.8925 | 0.25 (0.07-0.48) | 2.27 |
LY-2 | 5.3477+1.7628x | 0.9479 | 0.64 (0.41-0.87) | 5.82 |
LY-3 | 6.0852+1.7614x | 0.9592 | 0.24 (0.08-0.45) | 2.18 |
LY-4 | 4.0274+2.0848x | 0.9589 | 2.93 (2.48-3.44) | 26.64 |
QD-1 | 5.9423+1.3467x | 0.9401 | 0.20 (0.07-0.38) | 1.82 |
QD-2 | 6.0594+1.2737x | 0.9363 | 0.15 (0.04-0.32) | 1.27 |
RZ-1 | 5.4556+1.6946x | 0.9474 | 0.54 (0.15-1.01) | 4.91 |
RZ-2 | 6.0120+1.6168x | 0.8734 | 0.24 (0.004-0.70) | 2.18 |
TA-1 | 5.9847+1.6603x | 0.8744 | 0.26 (0.01-0.72) | 2.36 |
TA-2 | 6.0133+1.9703x | 0.8839 | 0.31 (0.13-0.52) | 2.82 |
TA-3 | 6.1886+1.3238x | 0.9432 | 0.13 (0.03-0.29) | 1.18 |
WF-1 | 6.4373+1.8136x | 0.8868 | 0.16 (0.03-0.37) | 1.45 |
WF-2 | 6.4515+2.7972x | 0.8939 | 0.30 (0.10-0.54) | 2.73 |
WF-3 | 6.1546+2.1186x | 0.8883 | 0.29 (0.11-0.50) | 2.64 |
WH-1 | 5.7762+1.1081x | 0.9022 | 0.20 (0.07-0.38) | 1.82 |
YT-1 | 4.5119+1.3342x | 0.8726 | 2.32 (1.26-3.85) | 21.09 |
YT-2 | 6.2982+1.7011x | 0.9642 | 0.17 (0.04-0.37) | 1.55 |
ZB-1 | 5.4225+1.4153x | 0.9245 | 0.50 (0.13-0.98) | 4.55 |
ZB-2 | 6.2430+1.5091x | 0.8754 | 0.15 (0.03-0.33) | 1.36 |
ZZ-1 | 6.5223+2.1754x | 0.8918 | 0.20 (0.04-0.43) | 1.82 |
ZZ-2 | 6.0763+1.4651x | 0.9454 | 0.18 (0.05-0.37) | 1.64 |
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2.2 播娘蒿对对比药剂苯磺隆和2甲4氯的抗性水平测定
苯磺隆药效表现与双氟磺草胺差别不大,施药后7 d播娘蒿开始出现黄化,而后生长被抑制,至药后15 d后开始死亡。表3为苯磺隆施药后30 d调查结果。40个播娘蒿种群敏感性差异明显,对苯磺隆最敏感的播娘蒿种群是HZ-1,GR50为0.56 g·hm-2,另外,DY-1、DZ-1、JN-2、WH-1等20个种群也比较敏感,RI<5.00,敏感种群占52.50%;抗性种群有19个,占总种群数的47.50%,而且在抗性种群中,低抗、中抗、高抗种群分别为11、6、2个,分别占总种群数的27.50%、15.00%、5.00%。最高抗性种群是DZ-3,RI为244.75。Table 3
表3
表3播娘蒿种群对苯磺隆抗性水平测定
Table 3
序号 Number | 回归方程 Regression equation (y=) | 相关系数 Correlation coefficient | GR50 (g·hm-2) (95% CL) | 相对抗性指数 RI |
---|---|---|---|---|
BZ-1 | 4.4592+0.4070x | 0.9305 | 21.31 (7.80-41.91) | 38.05 |
BZ-2 | 3.4995+2.1764x | 0.8938 | 4.89 (1.73-9.05) | 8.73 |
DY-1 | 4.5408+1.5010x | 0.8883 | 2.02 (0.27-5.44) | 3.61 |
DZ-1 | 4.5400+1.3410x | 0.8811 | 2.20 (0.42-5.40) | 3.93 |
DZ-2 | 3.7377+1.7915x | 0.8886 | 5.07 (1.96-9.11) | 9.05 |
DZ-3 | 2.7435+1.0560x | 0.9480 | 137.06 (58.29-448.11) | 244.75 |
HZ-1 | 4.0109+1.4039x | 0.9423 | 0.56 (0.03-11.73) | 1.00 |
HZ-2 | 4.0697+1.2949x | 0.9481 | 5.23 (2.24-9.17) | 9.34 |
JN-1 | 4.1869+0.9237x | 0.9913 | 7.59 (3.73-12.60) | 13.55 |
JN-2 | 4.7999+0.9194x | 0.9239 | 1.65 (0.34-4.16) | 2.95 |
JN-3 | 4.2133+1.3990x | 0.9533 | 3.65 (1.18-7.25) | 6.52 |
JNI-1 | 4.5819+1.1696x | 0.9575 | 2.28 (0.53-5.29) | 4.07 |
JNI-2 | 3.4317+1.9362x | 0.8894 | 6.46 (2.96-10.70) | 11.54 |
JNI-3 | 4.4136+1.5958x | 0.8898 | 2.33 (0.37-5.92) | 4.16 |
JNI-4 | 4.1771+1.2621x | 0.9501 | 4.49 (1.76-8.23) | 8.02 |
LC-1 | 3.7939+1.5722x | 0.9610 | 5.85 (2.59-9.96) | 10.45 |
LC-2 | 4.4694+1.8515x | 0.8941 | 1.93 (0.12-6.05) | 3.45 |
LC-3 | 4.2146+0.9707x | 0.9104 | 6.44 (3.02-10.96) | 11.50 |
LW-1 | 4.8448+0.7822x | 0.8931 | 1.58 (0.33-4.02) | 2.82 |
LY-1 | 4.3215+1.7573x | 0.8925 | 2.43 (0.35-6.26) | 4.34 |
LY-2 | 4.7095+1.5411x | 0.8909 | 1.54 (0.10-5.04) | 2.75 |
LY-3 | 4.4512+1.5314x | 0.8883 | 2.28 (0.37-5.77) | 4.07 |
LY-4 | 3.3832+1.0208x | 0.8737 | 38.36 (18.32-67.62) | 68.50 |
QD-1 | 4.0803+1.2919x | 0.9503 | 5.15 (2.19-9.07) | 9.20 |
QD-2 | 3.7652+1.5620x | 0.9589 | 6.17 (2.83-10.34) | 11.02 |
RZ-1 | 4.3648+1.5478x | 0.8879 | 2.57 (0.50-6.12) | 4.59 |
RZ-2 | 4.5092+1.3450x | 0.8808 | 2.32 (0.47-5.55) | 4.14 |
TA-1 | 3.9601+1.6906x | 0.8879 | 4.12 (1.35-8.00) | 7.36 |
TA-2 | 3.2026+2.4882x | 0.8944 | 5.28 (1.95-9.52) | 9.43 |
TA-3 | 4.2321+1.4666x | 0.9509 | 3.34 (0.96-6.92) | 5.96 |
WF-1 | 4.8405+1.4052x | 0.8883 | 1.30 (0.07-4.49) | 2.32 |
WF-2 | 4.7478+1.2172x | 0.8773 | 1.61 (0.23-4.46) | 2.88 |
WF-3 | 4.4687+1.5162x | 0.9677 | 2.24 (0.36-5.70) | 4.00 |
WH-1 | 4.7373+1.4737x | 0.8894 | 1.51 (0.10-4.85) | 2.70 |
YT-1 | 4.3582+0.9489x | 0.9037 | 4.75 (1.94-8.67) | 8.48 |
YT-2 | 4.6091+1.5464x | 0.8902 | 1.79 (0.17-5.28) | 3.20 |
ZB-1 | 4.4016+1.2996x | 0.8750 | 2.89 (0.03-10.85) | 5.16 |
ZB-2 | 4.3259+1.8489x | 0.8936 | 2.32 (0.26-6.31) | 4.14 |
ZZ-1 | 4.8315+1.4640x | 0.8900 | 1.30 (0.06-4.64) | 2.32 |
ZZ-2 | 4.3491+1.7430x | 0.8924 | 2.36 (0.32-6.18) | 4.21 |
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2甲4氯施药后观察,播娘蒿表现速度快,施药后3 d时播娘蒿即开始出现扭曲,叶片不伸展,药后7 d时茎叶开始黄化,而后逐渐死亡。40个播娘蒿种群对2甲4氯均敏感,效果无明显差异。表4为2甲4氯施药后30 d调查结果。2甲4氯对40个播娘蒿种群效果均很好,无明显抗性产生,RI在1.00—5.00,且大部分在3.00以下。
Table 4
表4
表4播娘蒿种群对2甲4氯抗性水平
Table 4
序号 Number | 回归方程 Regression equation (y=) | 相关系数 Correlation coefficient | GR50 (g·hm-2) (95% CL) | 相对抗性指数 RI |
---|---|---|---|---|
BZ-1 | 2.0945+2.5738x | 0.8928 | 13.45 (2.43-29.10) | 3.61 |
BZ-2 | 3.3409+1.6892x | 0.8819 | 9.60 (1.80-21.89) | 2.57 |
DY-1 | 3.9377+1.3693x | 0.8715 | 5.97 (0.69-16.27) | 1.60 |
DZ-1 | 4.3261+1.0307x | 0.9189 | 4.51 (0.60-12.56) | 1.21 |
DZ-2 | 3.7099+1.5489x | 0.8802 | 6.91 (0.73-18.38) | 1.85 |
DZ-3 | 3.4617+1.7590x | 0.8866 | 7.49 (0.66-20.53) | 2.01 |
HZ-1 | 4.2287+0.9926x | 0.9061 | 5.98 (1.17-14.62) | 1.60 |
HZ-2 | 4.9736+0.7651x | 0.8886 | 3.88 (0.40-12.68) | 1.04 |
JN-1 | 3.2623+1.7257x | 0.8826 | 10.16 (2.04-22.62) | 2.72 |
JN-2 | 3.7622+1.4396x | 0.9516 | 7.24 (1.10-18.09) | 1.94 |
JN-3 | 3.4954+1.7896x | 0.8880 | 6.93 (0.41-20.41) | 1.86 |
JNI-2 | 3.3834+1.6609x | 0.8811 | 9.40 (1.75-21.55) | 2.52 |
JNI-2 | 3.6806+1.4785x | 0.9582 | 7.81 (1.29-18.91) | 2.09 |
JNI-3 | 3.4141+1.6799x | 0.8826 | 8.79 (1.39-21.08) | 2.36 |
JNI-4 | 4.3825+1.0806x | 0.9246 | 3.73 (0.32-11.68) | 1.00 |
LC-2 | 3.7705+1.5307x | 0.8802 | 6.36 (0.59-17.83) | 1.71 |
LC-2 | 3.5698+1.4654x | 0.8705 | 9.46 (0.03-34.75) | 2.54 |
LC-3 | 3.2963+1.5965x | 0.8749 | 11.67 (3.24-23.58) | 3.13 |
LW-1 | 3.0031+2.1808x | 0.8924 | 8.24 (0.33-24.44) | 2.21 |
LY-1 | 3.4446+1.8365x | 0.8889 | 7.03 (0.38-20.88) | 1.88 |
LY-2 | 3.4498+1.6801x | 0.8831 | 8.37 (1.18-20.70) | 2.24 |
LY-3 | 4.0256+1.3975x | 0.8761 | 4.98 (0.33-15.47) | 1.34 |
LY-4 | 3.0374+1.8191x | 0.8837 | 11.99 (2.97-24.79) | 3.21 |
QD-1 | 3.1072+1.9785x | 0.8897 | 9.05 (0.95-23.20) | 2.43 |
QD-2 | 3.1567+1.9338x | 0.8890 | 8.98 (1.00-22.84) | 2.41 |
RZ-1 | 3.5592+1.7137x | 0.8860 | 6.93 (0.52-19.76) | 1.86 |
RZ-2 | 4.1233+1.4701x | 0.8825 | 3.95 (0.07-15.40) | 1.06 |
TA-1 | 3.2322+1.6788x | 0.8794 | 11.30 (2.83-23.52) | 3.03 |
TA-2 | 3.7666+1.4893x | 0.8774 | 6.73 (0.80-17.88) | 1.80 |
TA-3 | 3.0389+2.0898x | 0.8914 | 8.68 (0.61-23.81) | 2.33 |
WF-1 | 4.2364+1.2589x | 0.9485 | 4.04 (0.24-13.34) | 1.08 |
WF-2 | 3.5311+1.8064x | 0.8888 | 6.50 (0.27-20.34) | 1.74 |
WF-3 | 3.5460+1.6892x | 0.8849 | 7.26 (0.68-19.82) | 1.95 |
WH-1 | 3.2738+1.8467x | 0.8876 | 8.60 (0.98-21.99) | 2.31 |
YT-1 | 3.4549+1.8182x | 0.8884 | 7.08 (0.42-20.75) | 1.90 |
YT-2 | 3.7438+1.3591x | 0.9397 | 8.40 (1.82-18.96) | 2.25 |
ZB-1 | 3.0505+1.6576x | 0.9504 | 15.00 (5.39-27.35) | 4.02 |
ZB-2 | 3.6460+1.7483x | 0.8881 | 5.95 (0.20-19.50) | 1.60 |
ZZ-1 | 3.3559+1.8120x | 0.8873 | 8.08 (0.81-21.35) | 2.17 |
ZZ-2 | 4.2640+1.1111x | 0.9285 | 4.60 (0.55-13.04) | 1.23 |
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2.3 双氟磺草胺高抗种群ALS基因突变分析
对双氟磺草胺产生高抗种群BZ-1和DZ-3进行了ALS基因测序,测序分析结果显示两个高抗播娘蒿植株均发生了ALS基因功能位点的突变,但是突变位点或突变方向存在差异。BZ-1 ALS基因第197位氨基酸发生CCT(Pro)到TCT(Ser)或CTT(Leu)的突变,DZ-3 ALS基因第574位氨基酸发生了TGG(Trp)到TTG(Leu)的突变(表5)。Table 5
表5
表5高抗种群ALS基因突变分析
Table 5
序号Number | 相对抗性指数RI | ALS基因突变ALS gene mutation | 检出比例Detection rate |
---|---|---|---|
BZ-1 | 52.00 | Pro-197-Leu;Pro-197-Ser | Pro-197-Leu,40%;Pro-197-Ser,60% |
DZ-3 | 194.00 | Trp-574-Leu | 100% |
DY-1 | 1.00 | Wild type | — |
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3 讨论
3.1 播娘蒿对双氟磺草胺及对比药剂苯磺隆、2甲4氯的抗性水平
1988年美国杜邦公司的苯磺隆在我国正式登记,我国小麦田除草剂进入一个飞速发展期,但苯磺隆连续多年使用后,小麦田播娘蒿[13,14,15,16]、荠菜[17,18,19,20]、猪殃殃[21,22,23]、麦家公[24,25]等阔叶杂草的抗性逐年加重,苯磺隆单剂逐渐退出市场,仅作为复配制剂的成分之一。本研究中,播娘蒿对苯磺隆的抗性仍然很普遍,抗性种群占47.50%,最高相对抗性指数为244.75。双氟磺草胺是继苯磺隆之后在小麦田应用最广的防除阔叶杂草的除草剂,该药剂与苯磺隆一样,均属于ALS抑制剂类除草剂,目前市场上防除小麦田阔叶杂草的除草配方中,双氟磺草胺已成为一种必不可少的成分,该药剂由于用量低、活性高,且对小麦安全性高,已大面积应用,国内****对双氟磺草胺以及复配制剂的应用进行了大量报道[8,10],但随着用药时间延长,效果逐渐下降,用药量逐渐加大,已是最初登记用量的3倍甚至更高,已有报道小麦田猪殃殃对双氟磺草胺产生一定程度的抗性[11],但未有小麦田主要杂草播娘蒿对双氟磺草胺的抗性报道,对双氟磺草胺产生抗性也没有引起足够的重视。从本试验结果可见,虽然仅有20.00%的播娘蒿种群对双氟磺草胺产生抗性,但两个高抗种群BZ-1和DZ-3的相对抗性指数分别达到了52.00和194.00。
本试验中播娘蒿种群未对对比药剂2甲4氯产生抗药性,2甲4氯在小麦田也主要应用于防除播娘蒿、荠菜,因此以播娘蒿、荠菜为主的地块,可以使用2甲4氯等不易产生抗药性的激素类药剂进行防除,多种阔叶杂草混生地块,可采用多种作用机制的除草剂混合使用或者交替使用[26,27,28,29],减少双氟磺草胺单一药剂的使用。
综合山东省播娘蒿40个种群对双氟磺草胺和对比药剂苯磺隆、2甲4氯的抗性水平测定结果,2甲4氯为激素类除草剂,40个播娘蒿种群未发现抗性产生,这也进一步印证了激素类除草剂不易产生抗药性。双氟磺草胺和苯磺隆为ALS抑制剂类除草剂,也是容易产生抗性的除草剂类型,从结果可以看出,抗双氟磺草胺和抗苯磺隆的播娘蒿种群存在着一定程度的一致性,但又不是完全一致。抗双氟磺草胺种群有8个,抗苯磺隆种群有19个,其中抗双氟磺草胺的8个种群中有7个也是抗苯磺隆种群,如高抗双氟磺草胺的播娘蒿种群BZ-1和DZ-3同时也是中抗和高抗苯磺隆种群;中抗双氟磺草胺种群LC-3、LY-4、YT-1同时分别为中抗、高抗和低抗苯磺隆种群;低抗双氟磺草胺的种群JN-1、JNI-2同时也是中抗苯磺隆种群,只有低抗双氟磺草胺的种群LY-2对苯磺隆没有抗性。其他抗苯磺隆的12个种群未见对双氟磺草胺的抗性。
3.2 播娘蒿对双氟磺草胺的抗性机理
靶标抗性机理和非靶标抗性机理是杂草对ALS类除草剂产生抗性的两大原因[6,30-31]。靶标ALS基因突变或代谢作用增强是报道最多的ALS类除草剂抗性机理,国内外大量研究证实ALS存在8个抗性突变位点,分别为第122位丙氨酸、第197位脯氨酸、第205位丙氨酸、第376位天冬氨酸、第377位精氨酸、第574位色氨酸、第653位丝氨酸和第654位甘氨酸[32,33,34],任一位点发生氨基酸替代均可导致杂草抗药性的产生。本试验结果表明,靶标突变是播娘蒿种群BZ-1、DZ-3对双氟磺草胺产生高水平抗性的重要原因之一,种群BZ-1和DZ-3均发生ALS关键位点突变,但突变方式存在差异,这进一步证实了ALS突变的多样性[6]。BZ-1的ALS基因第197位氨基酸发生了CCT(Pro)到TCT(Ser)或CTT(Leu)的突变,而DZ-3的ALS基因则是第574位氨基酸发生了TGG(Trp)到TTG(Leu)的突变,这一结果与邓维[6]报道的关于播娘蒿对苯磺隆靶标抗性突变的3个位点(197、376和574位)研究结果具有一定的一致性,但突变方式不一样。至于二者抗性机理的关联性,有待进一步研究。非靶标抗性机理比靶标抗性复杂[28,35],这方面的研究报道较少。非靶标抗性机制是尽量减少除草剂到达目标部位的数量,从而减少除草剂对杂草的损伤,目前有关非靶标抗性机理报道最多的是植物代谢能力的增强。播娘蒿对双氟磺草胺抗性机理除了主要的靶标抗性外,是否还有非靶标抗性是下一步研究的重点内容之一。4 结论
山东省40个播娘蒿种群中已有20.00%的种群对双氟磺草胺产生明显抗性,其中高抗种群的BZ-1和DZ-3相对抗性指数已高达52.00和194.00,且主要为靶标抗性。另外,播娘蒿种群对对比除草剂苯磺隆的抗性仍很普遍,对另一种激素类除草剂2甲4氯未产生抗性。因此,针对冬小麦田播娘蒿发生区域,不能单一使用双氟磺草胺,应推广多种作用机理的除草剂交替、混和使用,从而延缓和控制杂草产生抗药性,同时扩大杀草谱、降低除草剂使用量。参考文献 原文顺序
文献年度倒序
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被引期刊影响因子
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[本文引用: 1]
[本文引用: 1]
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DOI:10.11686/cyxb20140510URL [本文引用: 1]
A weed survey was conducted using inverted W-pattern sampling methods to determine the species composition and structure of weed communities in wheat fields in Shandong Province. The taxa found included 69 weed species belonging to 21 families and 54 genera. Among these, 10 species were considered dominant weeds, including Descurainia sophia, Capsella bursa-pastoris, Galium aparine, Bromus japonicus, Silene conoidea, Erysimum cheiranthoides, Lithospermum arvense, Alopecurus aequalis, Aegilops squarrosa, and Calystegin hederacea; 15 species were regional dominant weeds and 44 were normal weed species. Fields in the plain regions of southwest Shandong possessed highest species richness, Shannon-wiener index and Evenness index,while the highest Simpson’s index was found in the plain regions of northwest Shandong and coastal regions of north Shandong. Hierarchical cluster analysis revealed that weeds in Shandong Province fall into 4 regional groups: hill regions of east Shandong with plain and mountain regions of mid Shandong; mountain regions of south Shandong and plain regions of southwest Shandong; plain regions of northwest Shandong ; and coastal regions of north Shandong.
DOI:10.11686/cyxb20140510URL [本文引用: 1]
A weed survey was conducted using inverted W-pattern sampling methods to determine the species composition and structure of weed communities in wheat fields in Shandong Province. The taxa found included 69 weed species belonging to 21 families and 54 genera. Among these, 10 species were considered dominant weeds, including Descurainia sophia, Capsella bursa-pastoris, Galium aparine, Bromus japonicus, Silene conoidea, Erysimum cheiranthoides, Lithospermum arvense, Alopecurus aequalis, Aegilops squarrosa, and Calystegin hederacea; 15 species were regional dominant weeds and 44 were normal weed species. Fields in the plain regions of southwest Shandong possessed highest species richness, Shannon-wiener index and Evenness index,while the highest Simpson’s index was found in the plain regions of northwest Shandong and coastal regions of north Shandong. Hierarchical cluster analysis revealed that weeds in Shandong Province fall into 4 regional groups: hill regions of east Shandong with plain and mountain regions of mid Shandong; mountain regions of south Shandong and plain regions of southwest Shandong; plain regions of northwest Shandong ; and coastal regions of north Shandong.
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URL [本文引用: 1]
In order to understand the weed composition and characterization in winter wheat in Hebei Province, the weeds of 146 winter wheat fields was investigated using the method of inverted W-pattern with 9 sampling points. The results showed that 61 weed species belonged to 53 genera of 21 families, with Descurainia sophia (L.) Schur, Calystegia hederacea Wall.Ex Roxb, Capsella bursa-pastoris (L.) Medic, Silene conoidea L. and Lithospermum arvense L. as dominate species in Hebei Province. Weeds in Baoding wheat fields possessed highest species richness and Gleason index, while highest Shannon-Wiener index and Pielou index appeared in Cangzhou wheat fields. Weeds in Langfang wheat fields had lowest species richness, Shannon-Wiener index and Pielou index, but highest Simpson index. Q cluster analysis and principal component analysis (PCA) revealed that weeds in Hebei Province were in 3 groups: abundant drought tolerant weed species in Shijiazhuang, Baoding, Xingtai and Langfang, Cangzhou and Hengshui with more saline tolerant or hygrophilous species, and Handan with more hygrophilous species. These results indicated that salinity and moisture of soil were the main ecological factors to affect the characterization of weed communities in winter wheat fields in Hebei Province.
URL [本文引用: 1]
In order to understand the weed composition and characterization in winter wheat in Hebei Province, the weeds of 146 winter wheat fields was investigated using the method of inverted W-pattern with 9 sampling points. The results showed that 61 weed species belonged to 53 genera of 21 families, with Descurainia sophia (L.) Schur, Calystegia hederacea Wall.Ex Roxb, Capsella bursa-pastoris (L.) Medic, Silene conoidea L. and Lithospermum arvense L. as dominate species in Hebei Province. Weeds in Baoding wheat fields possessed highest species richness and Gleason index, while highest Shannon-Wiener index and Pielou index appeared in Cangzhou wheat fields. Weeds in Langfang wheat fields had lowest species richness, Shannon-Wiener index and Pielou index, but highest Simpson index. Q cluster analysis and principal component analysis (PCA) revealed that weeds in Hebei Province were in 3 groups: abundant drought tolerant weed species in Shijiazhuang, Baoding, Xingtai and Langfang, Cangzhou and Hengshui with more saline tolerant or hygrophilous species, and Handan with more hygrophilous species. These results indicated that salinity and moisture of soil were the main ecological factors to affect the characterization of weed communities in winter wheat fields in Hebei Province.
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URL [本文引用: 3]
In order to examine the resistance level and distribution of flixweed to tribenuron-methyl in Shandong Province, 37 biotypes of the flixweed were collected from winter wheat fields. Whole-plant dose response experiments were conducted to determine the responses of different flixweed biotypes to tribenuron-methyl in glasshouses. The results showed that the resistant flixweed occurrence in Shandong Province has become a serious problem. From a total of 37 biotypes, 29 were resistant and 8 were susceptible, and the rate was 78.38% and 21.62%, respectively. There were 9 low-level, 15 mid-level and 5 high-level resistant biotypes, accounting for 31.03%, 51.72% and 17.24% of the resistant biotypes, respectively. The results showed that the resistance level of flixweed biotypes was high in the plain regions in southwestern and northwestern Shandong, and the levels in mountain regions in southern Shandong and coastal regions in northern Shandong were much lower.
URL [本文引用: 3]
In order to examine the resistance level and distribution of flixweed to tribenuron-methyl in Shandong Province, 37 biotypes of the flixweed were collected from winter wheat fields. Whole-plant dose response experiments were conducted to determine the responses of different flixweed biotypes to tribenuron-methyl in glasshouses. The results showed that the resistant flixweed occurrence in Shandong Province has become a serious problem. From a total of 37 biotypes, 29 were resistant and 8 were susceptible, and the rate was 78.38% and 21.62%, respectively. There were 9 low-level, 15 mid-level and 5 high-level resistant biotypes, accounting for 31.03%, 51.72% and 17.24% of the resistant biotypes, respectively. The results showed that the resistance level of flixweed biotypes was high in the plain regions in southwestern and northwestern Shandong, and the levels in mountain regions in southern Shandong and coastal regions in northern Shandong were much lower.
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DOI:10.3864/j.issn.0578-1752.2015.13.008URL [本文引用: 1]
【Objective】Flixweed (Descurainia sophia) is the most serious broad-leaved weed in main areas of winter wheat production in China, and it seriously threatens winter wheat production. The objective of this study is to determine the D. sophia dynamics of emergence, plant height, fresh weight and its competitive effect on yield components of wheat. 【Method】 The dynamics of emergence, plant height and fresh weight of D. sophia were surveyed by fixed quadrat sampling and random sampling in wheat field with severe D. sophia infestation in Ji’nan from 2013 to 2014. Shallow rotary tillage was implemented in experimental plot with maize straw giving back before wheat sowing. In order to compare the effect of different D. sophia densities on wheat yield, three wheat planting densities were set as 67.5, 135.0, and 202.5 kg·hm-2, each wheat planting densities set with different D. sophia densities as 0, 10, 20, 40, 60, 80, 160, 320, 640, and 1 280 plants/m2. D. sophia densities were based on artificial inoculation, and three final thinning of seedlings were made before winter, early spring, and revival stage. Excel graphing was conducted to analyze the cause of yield loss caused by D. sophia.【Result】The peak of D. sophia seedling emergence appeared after wheat seeding one week to mid-November, the weekly average temperature at 13.5-14.8℃. The amount of seedling emergence before winter accounted for 96.7% of the total annual emergence. In late March, the weekly average temperature raised above 8.0℃, D. sophia seedling began to grow rapidly. Plant height of D. sophia was higher than wheat after early April. In mid-May, D. sophia plant height reached maximum 115.6 cm, and 43.4 cm higher than wheat. The fresh weight of D. sophia and wheat changed slowly at overwintering stage. Fresh weight of D. sophia increased rapidly after April, achieved the maximum 50.2 g in early May, which was four folds of wheat. The effect of D. sophia on wheat yield was primarily through inhibiting the effective ears and grain number per ear of wheat. It had no significant effect on 1 000-seed weight. Wheat spikes were from 4.29 to 0.28 million/hm2, reduced by 93.5%, when the D. sophia plant rose from 0 to 640 plants/m2 in the plot with 67.5 kg·hm-2 wheat sowing amount. Wheat spikes were from 5.49 to 1.88 million/hm2, reduced by 65.8%, when the D. sophia plant rose from 0 to 640 plants/m2 in the plot with 135.0 kg·hm-2 wheat sowing amount. Wheat spikes were from 6.69 to 3.22 million/hm2, reduced by 52.0%, when the D. sophia plant rose from 0 to 320 plants/m2 in the plot with 202.5 kg·hm-2 wheat sowing amount. The loss rate of wheat was 84.7%, 71.9%, and 64.9% when the D. sophia density was at 320 plants/m2 in the three wheat planting densities. The wheat yield was 2 396.3 and 1 680.2 kg·hm-2, the loss rate was as high as 97.5% and 87.9% in the plots with wheat sowing amount at 67.5 and 135.0 kg·hm-2, on the verge of failure. 【Conclusion】The dynamics of emergence, plant height and fresh weight of D. sophia were closely related with phenology. The damages of D. sophia can be effectively controlled and the impact of D. sophia on wheat production can be reduced by timely control and rational close planting.
DOI:10.3864/j.issn.0578-1752.2015.13.008URL [本文引用: 1]
【Objective】Flixweed (Descurainia sophia) is the most serious broad-leaved weed in main areas of winter wheat production in China, and it seriously threatens winter wheat production. The objective of this study is to determine the D. sophia dynamics of emergence, plant height, fresh weight and its competitive effect on yield components of wheat. 【Method】 The dynamics of emergence, plant height and fresh weight of D. sophia were surveyed by fixed quadrat sampling and random sampling in wheat field with severe D. sophia infestation in Ji’nan from 2013 to 2014. Shallow rotary tillage was implemented in experimental plot with maize straw giving back before wheat sowing. In order to compare the effect of different D. sophia densities on wheat yield, three wheat planting densities were set as 67.5, 135.0, and 202.5 kg·hm-2, each wheat planting densities set with different D. sophia densities as 0, 10, 20, 40, 60, 80, 160, 320, 640, and 1 280 plants/m2. D. sophia densities were based on artificial inoculation, and three final thinning of seedlings were made before winter, early spring, and revival stage. Excel graphing was conducted to analyze the cause of yield loss caused by D. sophia.【Result】The peak of D. sophia seedling emergence appeared after wheat seeding one week to mid-November, the weekly average temperature at 13.5-14.8℃. The amount of seedling emergence before winter accounted for 96.7% of the total annual emergence. In late March, the weekly average temperature raised above 8.0℃, D. sophia seedling began to grow rapidly. Plant height of D. sophia was higher than wheat after early April. In mid-May, D. sophia plant height reached maximum 115.6 cm, and 43.4 cm higher than wheat. The fresh weight of D. sophia and wheat changed slowly at overwintering stage. Fresh weight of D. sophia increased rapidly after April, achieved the maximum 50.2 g in early May, which was four folds of wheat. The effect of D. sophia on wheat yield was primarily through inhibiting the effective ears and grain number per ear of wheat. It had no significant effect on 1 000-seed weight. Wheat spikes were from 4.29 to 0.28 million/hm2, reduced by 93.5%, when the D. sophia plant rose from 0 to 640 plants/m2 in the plot with 67.5 kg·hm-2 wheat sowing amount. Wheat spikes were from 5.49 to 1.88 million/hm2, reduced by 65.8%, when the D. sophia plant rose from 0 to 640 plants/m2 in the plot with 135.0 kg·hm-2 wheat sowing amount. Wheat spikes were from 6.69 to 3.22 million/hm2, reduced by 52.0%, when the D. sophia plant rose from 0 to 320 plants/m2 in the plot with 202.5 kg·hm-2 wheat sowing amount. The loss rate of wheat was 84.7%, 71.9%, and 64.9% when the D. sophia density was at 320 plants/m2 in the three wheat planting densities. The wheat yield was 2 396.3 and 1 680.2 kg·hm-2, the loss rate was as high as 97.5% and 87.9% in the plots with wheat sowing amount at 67.5 and 135.0 kg·hm-2, on the verge of failure. 【Conclusion】The dynamics of emergence, plant height and fresh weight of D. sophia were closely related with phenology. The damages of D. sophia can be effectively controlled and the impact of D. sophia on wheat production can be reduced by timely control and rational close planting.
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Dose-response experiments were conducted to determine the combination type of florasulam+MCPA by calculating the co-toxicity coefficients in greenhouse. Weed control effect, response of winter wheat and rotational crops to different dosages of 43% florasulam+MCPA SE were also investigated in fields in Jinan, Shandong Province. The results showed that the ratio of 1:100-120 was the best that exhibited a synergistic effect on control of the grasses, Descurainia sophia and Galium aparine. The 43% florasulam+MCPA SE achieved high weed control when applied at 387, 516, 645 and 1 032 g/hm2 during spring and autumn in winter wheat. Fresh weights were reduced by more than 99% when applied in autumn, and more than 95% in spring. The 43% florasulam+MCPA SE didn't cause injury to wheat and rotational crops, including maize, soybean, peanut and cotton.
URL [本文引用: 2]
Dose-response experiments were conducted to determine the combination type of florasulam+MCPA by calculating the co-toxicity coefficients in greenhouse. Weed control effect, response of winter wheat and rotational crops to different dosages of 43% florasulam+MCPA SE were also investigated in fields in Jinan, Shandong Province. The results showed that the ratio of 1:100-120 was the best that exhibited a synergistic effect on control of the grasses, Descurainia sophia and Galium aparine. The 43% florasulam+MCPA SE achieved high weed control when applied at 387, 516, 645 and 1 032 g/hm2 during spring and autumn in winter wheat. Fresh weights were reduced by more than 99% when applied in autumn, and more than 95% in spring. The 43% florasulam+MCPA SE didn't cause injury to wheat and rotational crops, including maize, soybean, peanut and cotton.
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URL [本文引用: 1]
In order to demonstrate the application value of florasulam in wheat field in northern China, the spectrum of weed control, herbicidal activity and the safety to common various wheat varieties of florasulam which belonged to triazolo [1,5-c] pyrimidine-2-sulfonanilide herbicides were studied in the laboratory. The results indicated that florasulam had a wonderful herbicidal activity to common broadleaf weeds in wheat field, and there was higher biological activity against Descurainia sophia, Silene conoidea, Lithospermum arvense, Galium aparine and Capsella bursa-pastoris than tribenuron-methyl with the activity ratio of 1.56, 6.26, 1.65, 18.27 and 22.75. The tolerance of Jinan 17 and Shanyou 2 to florasulam were 2.57 and 11.66 times more than tribenuron-methyl respectively. There was better selectivity to florasulam between wheat and weed (selectivity index 11.16-49.32) than tribenuron-methyl. In seedling stage, plant length and fresh weight were inhibited when wheat was treated with florasulam and the inhibition to various wheat varieties was significantly different, the inhibition ratio to Linmai 2, Jining 13 and Jinan 17 was relatively higher and the lower was Weimai 8, Shannong 6 and Taishan 9818. In conclusion, florasulam has an excellent application prospect.
URL [本文引用: 1]
In order to demonstrate the application value of florasulam in wheat field in northern China, the spectrum of weed control, herbicidal activity and the safety to common various wheat varieties of florasulam which belonged to triazolo [1,5-c] pyrimidine-2-sulfonanilide herbicides were studied in the laboratory. The results indicated that florasulam had a wonderful herbicidal activity to common broadleaf weeds in wheat field, and there was higher biological activity against Descurainia sophia, Silene conoidea, Lithospermum arvense, Galium aparine and Capsella bursa-pastoris than tribenuron-methyl with the activity ratio of 1.56, 6.26, 1.65, 18.27 and 22.75. The tolerance of Jinan 17 and Shanyou 2 to florasulam were 2.57 and 11.66 times more than tribenuron-methyl respectively. There was better selectivity to florasulam between wheat and weed (selectivity index 11.16-49.32) than tribenuron-methyl. In seedling stage, plant length and fresh weight were inhibited when wheat was treated with florasulam and the inhibition to various wheat varieties was significantly different, the inhibition ratio to Linmai 2, Jining 13 and Jinan 17 was relatively higher and the lower was Weimai 8, Shannong 6 and Taishan 9818. In conclusion, florasulam has an excellent application prospect.
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DOI:10.1126/science.1067226URLPMID:11809972 [本文引用: 1]
A survey of China's plant biotechnologists shows that China is developing the largest plant biotechnology capacity outside of North America. The list of genetically modified plant technologies in trials, including rice, wheat, potatoes, and peanuts, is impressive and differs from those being worked on in other countries. Poor farmers in China are cultivating more area of genetically modified plants than are small farmers in any other developing country. A survey of agricultural producers in China demonstrates that Bacillus thuringiensis cotton adoption increases production efficiency and improves farmer health.
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DOI:10.1016/j.pestbp.2014.10.012URLPMID:25619914 [本文引用: 1]
Flixweed (Descurainia Sophia L.) is a problematic weed in winter wheat fields in China, which causes great loss of wheat yield. A total of 46 flixweed accessions from winter wheat-planting areas were collected and used for the survey of resistance to tribenuron-methyl and Pro197 mutation diversity. According to the
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DOI:10.1614/WS-D-10-00099.1URL [本文引用: 1]
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DOI:10.1614/WS-08-058.1URL [本文引用: 1]
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DOI:10.1016/j.pestbp.2017.05.007URLPMID:29183598 [本文引用: 1]
Shepherd's purse is a troublesome dicot weed that occurs in the major wheat-producing areas in China. Twenty-eight shepherd's purse populations were collected from winter wheat-planting areas in Henan Province and used to evaluate tribenuron-methyl resistance and acetohydroxyacid synthase (AHAS) gene-mutation diversity. The results indicate that all 28 shepherd's purse populations were resistant to tribenuron-methyl at different levels compared with the susceptible population. Mutation of the 197 codon (CCT) changed proline (Pro) into tyrosine (Tyr), histidine (His), leucine (Leu), serine (Ser), arginine (Arg), alanine (Ala) and threonine (Thr), whereas mutation of the 574 codon (TGG) changed tryptophan (Trp) into leucine (Leu). Among these amino acid changes, a co-concurrence of Pro197Leu and Trp574Leu substitutions was identified for the first time in resistant weed species. Furthermore, Pro197Tyr, Pro197Arg and Pro197Ala substitutions have not been previously reported in shepherd's purse. The results of the in vitro AHAS assay suggest that an insensitive AHAS is likely involved in the resistance to tribenuron-methyl in the R populations with AHAS gene mutations, and the non-target-site based resistance might exist in some populations.
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URL [本文引用: 1]
In order to evaluate the resistance of Galium aparine to tribenuron-methyl, 14 potential resistant biotypes were collected from winter wheat fields of 14 counties or cities in Shandong, Shanxi, Henan, Hebei, Jiangsu, Shaanxi, and Anhui Provinces, and 14 susceptible biotypes were correspondingly collected from the nearby non-farming lands never applied herbicides. Greenhouse pot tests and the quick-test in Petri dish were conducted to detect the resistance level. The results of greenhouse pot tests showed that except for the potential resistant biotypes from the collecting sites of Shijiazhuang, Hebei Province, Taiyuan, Shanxi Province, Zhouzhi, Shaanxi Province, and Tai’an, Shandong Province, all the other potential resistant biotypes evolved resistance to tribenuron-methyl, with a resistance factor ranging from 1.6 to 4.3, with the highest 4.3 in the collecting site of Xuchang, Henan Province and the lowest 1.6 in the collecting sites of Taihe, Anhui Province and Huaxian, Shaanxi Province. The resistance in the collecting site of Xuchang, Henan Province is relatively higher than those in the collecting sites of Taihe, Anhui Province and Huaxian, Shaanxi Province, with a resistance factor 2.2, 1.9, 1.7 respectively. The results of the quick-test in Petri dish are in accordance with those of greenhouse pot tests on the whole.
URL [本文引用: 1]
In order to evaluate the resistance of Galium aparine to tribenuron-methyl, 14 potential resistant biotypes were collected from winter wheat fields of 14 counties or cities in Shandong, Shanxi, Henan, Hebei, Jiangsu, Shaanxi, and Anhui Provinces, and 14 susceptible biotypes were correspondingly collected from the nearby non-farming lands never applied herbicides. Greenhouse pot tests and the quick-test in Petri dish were conducted to detect the resistance level. The results of greenhouse pot tests showed that except for the potential resistant biotypes from the collecting sites of Shijiazhuang, Hebei Province, Taiyuan, Shanxi Province, Zhouzhi, Shaanxi Province, and Tai’an, Shandong Province, all the other potential resistant biotypes evolved resistance to tribenuron-methyl, with a resistance factor ranging from 1.6 to 4.3, with the highest 4.3 in the collecting site of Xuchang, Henan Province and the lowest 1.6 in the collecting sites of Taihe, Anhui Province and Huaxian, Shaanxi Province. The resistance in the collecting site of Xuchang, Henan Province is relatively higher than those in the collecting sites of Taihe, Anhui Province and Huaxian, Shaanxi Province, with a resistance factor 2.2, 1.9, 1.7 respectively. The results of the quick-test in Petri dish are in accordance with those of greenhouse pot tests on the whole.
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URL [本文引用: 1]
【Objective】 In recent years, Galium aparine L. in most winter wheat fields in China could not be controlled by tribenuron-methyl. The objective of this study is to understand the molecular basis of the resistance mechanism to tribenuron-methyl in G. aparine and to find the specific mutation sites in amino acid sequence of acetolactate synthase (ALS) in the resistant biotype of G. aparine. 【Method】 Fragments encoding the ALS were amplified and cloned from G. aparine, susceptible (S) and resistant (R) biotypes to tribenuron-methyl, respectively, and sequenced subsequently. 【Result】 The result showed that the nucleotide sequence of R-biotype of G. aparine differed from that of the S biotype with three amino acid substitutions, of which, the amino acid substitution of Trp574 (TGG) to Gly (GGG) located in the highly conserved region Domain B. 【Conclusion】 The substitution of Trp574 might be responsible for the resistance to tribenuron-methyl in the R-biotype of G. aparine.
URL [本文引用: 1]
【Objective】 In recent years, Galium aparine L. in most winter wheat fields in China could not be controlled by tribenuron-methyl. The objective of this study is to understand the molecular basis of the resistance mechanism to tribenuron-methyl in G. aparine and to find the specific mutation sites in amino acid sequence of acetolactate synthase (ALS) in the resistant biotype of G. aparine. 【Method】 Fragments encoding the ALS were amplified and cloned from G. aparine, susceptible (S) and resistant (R) biotypes to tribenuron-methyl, respectively, and sequenced subsequently. 【Result】 The result showed that the nucleotide sequence of R-biotype of G. aparine differed from that of the S biotype with three amino acid substitutions, of which, the amino acid substitution of Trp574 (TGG) to Gly (GGG) located in the highly conserved region Domain B. 【Conclusion】 The substitution of Trp574 might be responsible for the resistance to tribenuron-methyl in the R-biotype of G. aparine.
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DOI:10.3864/j.issn.0578-1752.2019.03.002URL [本文引用: 1]
【Objective】 To investigate the effect of residual tribenuron-methyl in soil on seed germination, genome-wide association analysis (GWAS) of 52157 SNPs with genome-wide coverage was used to identify the candidate genes for the germinating traits of rapeseed under tribenuron-methyl stress. The results of this study may provide a theoretical basis for tribenuron-methyl tolerance in oilseed rape.【Method】 In the germination experiment, 241 rape varieties (lines) were treated with tribenuron-methyl solution of 25 mg·L -1, and distilled water was added to the control. At the 7th day of germination, the phenotypic data including relative germination rate, relative root length and relative fresh weight were measured and calculated. Using the TASSEL software, tribenuron-methyl tolerance related traits were explored in B. napus under germination with a 60K Brassica Illumina ? Infinium SNP array. Then, the structure of the population was analyzed by the software STRUCTURE, and the genetic relationship and LD attenuation were analyzed by the software TASSEL, respectively. In order to determine the optimal model for GWAS analysis of each trait, 6 models involved the general linear model and mixed linear model were used to analyze and compare the effects of group structure and relationship. The software TASSEL was employed to analyze the relative values of the 3 traits under the optimal model. Meanwhile, the candidate genes were predicted based on the LD interval sequence of the associated SNP locus. 【Result】 The population structure analysis showed the population could be divided into two subgroups, P1 with 94 materials and P2 with 147 materials. Meanwhile, the result of genetic relationship analysis showed that about 56.28% of the materials had no kinship relationship. In the optimal GWAS model (K+PCA), we found that 16 SNP loci significantly associated with 3 traits including relative root length, relative fresh weight and relative germination rate, and each locus explained phenotypic variations ranging from 9.42% to 13.14%. By analyzing the LD interval of the significant SNP locus and the corresponding interval sequence of Brassica napus, twenty-five candidate genes related to tribenuron-methyl tolerance were screened out in the LD interval of these significant SNP loci, in which nine of them belonged to cytochrome P450 gene families, five were involved in glutathione synthesis or metabolic processes, and two were multidrug-tolerance associated protein. At the same time, it was revealed that the gene ATGSTU19 significantly related to germination rate encodes glutathione transferase, which participates in the process of toxin decomposition and plays an important role in various stress responses. In addition, BnaC02g27690D was identified at relative root length and relative fresh weight. However, its function was not clear. 【Conclusion】 In this study, 16 SNP loci were detected to be significantly associated with tribenuron-methyl tolerance, and 25 candidate genes were screened out.
DOI:10.3864/j.issn.0578-1752.2019.03.002URL [本文引用: 1]
【Objective】 To investigate the effect of residual tribenuron-methyl in soil on seed germination, genome-wide association analysis (GWAS) of 52157 SNPs with genome-wide coverage was used to identify the candidate genes for the germinating traits of rapeseed under tribenuron-methyl stress. The results of this study may provide a theoretical basis for tribenuron-methyl tolerance in oilseed rape.【Method】 In the germination experiment, 241 rape varieties (lines) were treated with tribenuron-methyl solution of 25 mg·L -1, and distilled water was added to the control. At the 7th day of germination, the phenotypic data including relative germination rate, relative root length and relative fresh weight were measured and calculated. Using the TASSEL software, tribenuron-methyl tolerance related traits were explored in B. napus under germination with a 60K Brassica Illumina ? Infinium SNP array. Then, the structure of the population was analyzed by the software STRUCTURE, and the genetic relationship and LD attenuation were analyzed by the software TASSEL, respectively. In order to determine the optimal model for GWAS analysis of each trait, 6 models involved the general linear model and mixed linear model were used to analyze and compare the effects of group structure and relationship. The software TASSEL was employed to analyze the relative values of the 3 traits under the optimal model. Meanwhile, the candidate genes were predicted based on the LD interval sequence of the associated SNP locus. 【Result】 The population structure analysis showed the population could be divided into two subgroups, P1 with 94 materials and P2 with 147 materials. Meanwhile, the result of genetic relationship analysis showed that about 56.28% of the materials had no kinship relationship. In the optimal GWAS model (K+PCA), we found that 16 SNP loci significantly associated with 3 traits including relative root length, relative fresh weight and relative germination rate, and each locus explained phenotypic variations ranging from 9.42% to 13.14%. By analyzing the LD interval of the significant SNP locus and the corresponding interval sequence of Brassica napus, twenty-five candidate genes related to tribenuron-methyl tolerance were screened out in the LD interval of these significant SNP loci, in which nine of them belonged to cytochrome P450 gene families, five were involved in glutathione synthesis or metabolic processes, and two were multidrug-tolerance associated protein. At the same time, it was revealed that the gene ATGSTU19 significantly related to germination rate encodes glutathione transferase, which participates in the process of toxin decomposition and plays an important role in various stress responses. In addition, BnaC02g27690D was identified at relative root length and relative fresh weight. However, its function was not clear. 【Conclusion】 In this study, 16 SNP loci were detected to be significantly associated with tribenuron-methyl tolerance, and 25 candidate genes were screened out.
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DOI:10.1104/pp.114.242750URL [本文引用: 1]
Weedy plant species that have evolved resistance to herbicides due to enhanced metabolic capacity to detoxify herbicides (metabolic resistance) are a major issue. Metabolic herbicide resistance in weedy plant species first became evident in the 1980s in Australia (in Lolium rigidum) and the United Kingdom (in Alopecurus myosuroides) and is now increasingly recognized in several crop-weed species as a looming threat to herbicide sustainability and thus world crop production. Metabolic resistance often confers resistance to herbicides of different chemical groups and sites of action and can extend to new herbicide(s). Cytochrome P450 monooxygenase, glycosyl transferase, and glutathione S-transferase are often implicated in herbicide metabolic resistance. However, precise biochemical and molecular genetic elucidation of metabolic resistance had been stalled until recently. Complex cytochrome P450 superfamilies, high genetic diversity in metabolic resistant weedy plant species (especially cross-pollinated species), and the complexity of genetic control of metabolic resistance have all been barriers to advances in understanding metabolic herbicide resistance. However, next-generation sequencing technologies and transcriptome-wide gene expression profiling are now revealing the genes endowing metabolic herbicide resistance in plants. This Update presents an historical review to current understanding of metabolic herbicide resistance evolution in weedy plant species.
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DOI:10.1002/ps.3710URL [本文引用: 1]
Acetohydroxyacid synthase (AHAS) inhibitor herbicides currently comprise the largest site-of-action group (with 54 active ingredients across five chemical groups) and have been widely used in world agriculture since they were first introduced in 1982. Resistance evolution in weeds to AHAS inhibitors has been rapid and identified in populations of many weed species. Often, evolved resistance is associated with point mutations in the target AHAS gene; however non-target-site enhanced herbicide metabolism occurs as well. Many AHAS gene resistance mutations can occur and be rapidly enriched owing to a high initial resistance gene frequency, simple and dominant genetic inheritance and lack of major fitness cost of the resistance alleles. Major advances in the elucidation of the crystal structure of the AHAS (Arabidopsis thaliana) catalytic subunit in complex with various AHAS inhibitor herbicides have greatly improved current understanding of the detailed molecular interactions between AHAS, cofactors and herbicides. Compared with target-site resistance, non-target-site resistance to AHAS inhibitor herbicides is less studied and hence less understood. In a few well-studied cases, non-target-site resistance is due to enhanced rates of herbicide metabolism (metabolic resistance), mimicking that occurring in tolerant crop species and often involving cytochrome P450 monooxygenases. However, the specific herbicide-metabolising, resistance-endowing genes are yet to be identified in resistant weed species. The current state of mechanistic understanding of AHAS inhibitor herbicide resistance is reviewed, and outstanding research issues are outlined. (C) 2013 Society of Chemical Industry
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DOI:10.1614/WS-D-14-00184.1URL [本文引用: 1]
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DOI:10.1104/pp.113.223156URL [本文引用: 1]
Previous research reported the first case of resistance to mesotrione and other 4-hydroxyphenylpyruvate dioxygenase (HPPD) herbicides in a waterhemp (Amaranthus tuberculatus) population designated MCR (for McLean County mesotrione- and atrazine-resistant). Herein, experiments were conducted to determine if target site or nontarget site mechanisms confer mesotrione resistance in MCR. Additionally, the basis for atrazine resistance was investigated in MCR and an atrazine-resistant but mesotrione-sensitive population (ACR for Adams County mesotrione-sensitive but atrazine-resistant). A standard sensitive population (WCS for Wayne County herbicide-sensitive) was also used for comparison. Mesotrione resistance was not due to an alteration in HPPD sequence, HPPD expression, or reduced herbicide absorption. Metabolism studies using whole plants and excised leaves revealed that the time for 50% of absorbed mesotrione to degrade in MCR was significantly shorter than in ACR and WCS, which correlated with previous phenotypic responses to mesotrione and the quantity of the metabolite 4-hydroxy-mesotrione in excised leaves. The cytochrome P450 monooxygenase inhibitors malathion and tetcyclacis significantly reduced mesotrione metabolism in MCR and corn (Zea mays) excised leaves but not in ACR. Furthermore, malathion increased mesotrione activity in MCR seedlings in greenhouse studies. These results indicate that enhanced oxidative metabolism contributes significantly to mesotrione resistance in MCR. Sequence analysis of atrazine-resistant (MCR and ACR) and atrazine-sensitive (WCS) waterhemp populations detected no differences in the psbA gene. The times for 50% of absorbed atrazine to degrade in corn, MCR, and ACR leaves were shorter than in WCS, and a polar metabolite of atrazine was detected in corn, MCR, and ACR that cochromatographed with a synthetic atrazine-glutathione conjugate. Thus, elevated rates of metabolism via distinct detoxification mechanisms contribute to mesotrione and atrazine resistance within the MCR population.