土壤微生物和酶对大气CO2浓度与温度升高的响应

土壤微生物(Soil microbes)是生态系统的重要组成部分，它参与土壤中复杂有机物质的分解和再合成，也参与C、N、S、P等的循环。土壤酶(Soil enzyme)是土壤中具有生物活性的蛋白质，它与微生物一起推动着土壤的生物化学过程，并在树木营养物质的转化中起着重要的作用。鉴于土壤微生物和土壤酶对环境变化的敏感性，它们在CO2浓度和温度升高时的反应将在很大程度上影响森林生态系统的结构和功能。因此，要全面评价大气CO2浓度和温度升高对整个生态系统的影响，有必要对CO2浓度和温度升高条件下的土壤微生物的反应进行深入的研究与探讨。本文应用自控、封闭、独立的生长室系统，研究了川西亚高山岷江冷杉（Abies faxoniana）根际、非根际土壤微生物数量，红桦（Betula albosinensis）根际微生物数量以及根际、非根际土壤酶活性对大气CO2浓度(环境CO2浓度+350±25μmol·mol-1，EC)和温度(环境温度+2.0±0.5℃，ET)升高及两者同时升高(ECT)的响应。结果表明： 1) EC和ET显著增加岷江冷杉根际微生物数量，但不同微生物种类对EC和ET的反应有所差异。6、8和10月，岷江冷杉根际微生物数量与对照(CK)相比，EC处理的根际细菌数量分别增加了35%、164%和312%，ET处理增加了30%、115%和209%；EC和ET处理对根际放线菌和根际真菌数量影响不显著。ECT处理的根际放线菌数量分别增加了49%、50%和96%，根际真菌数量增加了151%、57%和48%；而ECT对根际细菌数量影响不显著。EC、ET和ECT处理对岷江冷杉土壤微生物总数的根际效应明显，其R/S值分别为1.93、1.37和1.46(CK的R/S值为0.81)。 2) 红桦根际微生物数量对EC、ET和ECT的响应不同。生长季节(5~10月)，高密度的红桦根际细菌数量与CK 相比，EC的根际细菌数量分别增加28%、33%、423%、65%、43%和79%，而低密度的红桦根际细菌数量增加不显著。ET能显著增加根际细菌数量(7~10月)，其中高密度的根际细菌数量分别增加了377%、107%、35%、22%，而低密度的根际细菌数量分别增加了27%、27%、64%、48%；ECT对两个密度水平下根际细菌数量均未产生有显著的影响。高、低密度的红桦根际放线菌和根际真菌数量与 CK 相比，EC显著增加了低密度的红桦根际放线菌数量，而对高密度的根际放线菌数量无显著影响；ET和ECT对高低密度的红桦根际放线菌数量均未产生显著影响。EC和ET对高低密度的根际真菌数量也无显著影响，而ECT却显著增加了高低密度的根际真菌数量。 3) EC、ET和ECT处理的低密度红桦根际微生物(细菌、放线菌和真菌)数量没有显著高于或低于高密度根际微生物数量，表明短期内密度对红桦根际微生物数量不产生影响。 4) 不同种类的氧化还原酶对EC、ET和ECT的响应不同。5~10月，EC的红桦根际过氧化氢酶活性是CK 的1.44、1.06、1.11、1.10、1.12和1.24倍，差异显著(6月除外)；ET和ECT处理根际过氧化氢酶活性无显著增加。EC的红桦根际多酚氧化酶活性比CK显著增加；ET的根际多酚氧化酶活性显著高于CK(8月除外)。ECT的根际多酚氧化酶活性高于CK，差异不显著。EC的根际脱氢酶活性分别增加了46%、40%、133%、48%、17%和26%，差异显著。5~7月，ET和ECT的根际脱氢酶活性高于CK的脱氢酶活性，而8~9月则相反，差异性均不显著。 5) EC、ET和ECT对不同种类的水解酶的影响不同。EC能显著增加红桦根际脲酶活性，5~10月分别增加了29%、42%，、70%、67%、59%和57%。ET和ECT 对根际脲酶活性未产生显著影响。EC显著提高根际转化酶活性，5、6和9月EC的根际转化酶活性分别比CK高51%、42%和40%。5和10月，ET的根际转化酶活性低于CK，而其余月份却高于CK，但均具有显著性差异。ECT的根际转化酶活性与CK的根际转化酶活性有显著性差异(9月除外)，5、6和7月的根际转化酶活性分别提高了94%、198%和67%。 6) 与CK相比，EC、ET和ECT的非根际土壤微生物数量以及非根际土壤酶活性均无显著提高。EC、ET和ECT的过氧化氢酶、脲酶的根际效应明显，而多酚氧化酶和脱氢酶根际效应不明显。EC和ECT的转化酶根际效应明显，而ET的转化酶根际效应不明显。 It is well known that atmospheric CO2 concentration and temperature are increasing as a consequence of human activities. In past decades, considerable efforts had been put into investigating the effects of climate change on processes of forest ecological system. In general, studies had been mainly focused on the effects of elevated atmospheric CO2 on plant physiology and development, litter quality, and soil microorganisms. Studies showed that there was variation in the responses of root development and below-ground processes to climate between different plant communities. Since the concentration of CO2 in soil was much higher (10~50 times) than in the atmosphere, increasing levels of atmospheric CO2 may not directly in fluence below ground processes. Betula albosinensis and Abies faxoniana, as the dominated tree species of subalpine dark coniferous forest in the western Sichuan province, which play an important role in the structure and function of this kind of forest ecosystem. In our study, effects of elevated atmospheric CO2 concentration (350±25μmol·mol-1), increased temperature (2.0±0.5℃) and both of the two on the number of rhizospheric microbe and rhizospheric enzyme activity were studied by the independent and enclosed-top chamber’ system under high-frigid conditions. Responses of rhizospheric bacteria, actinomycetes and fungi number of Betula albosinensis and Abies faxoniana under different densities(high density with 84 stems·m-2, low density with 28 stems·m-2 ), and rhizospheric enzyme activity of Betula albo-sinensis to elevated CO2 concentration and increased temperature were analyzed and discussed. The results are as the following, 1) In comparion with the control, the numbers of rhizospheric bacteria of Abies faxoniana were increased by 35%, 164% and 312% significantly in June, August and October respectively of EC, and were increased by 30%, 115% and 209% respectively of ET.However the effect of EC and ET on rhizospheric actinomycetes and fungi was not significant. The number of rhizospheric actinomycetes of ECT were increased significantly by 49%, 50% and 96% respectively, and the increment of rhizospheric fungi were 151%, 57% and 48% respectively .The effect of ECT on rhizospheric bacteria was not significant. Rhizospheric effect of soil microbe for all treatments was significant, with the R/S of 1.93, 1.27 and 1.46 for EC, ET and ECT, respectively. 2) Treatment EC improved the number of rhizospheric bacteria of Betula albosinensis under high density significantly in comparison with the control, over the growing season, the greatest increment of rhizospheric bacteria was from July. However, EC had no effect on the number of rhizospheric bacteria under low density. Except May and June, treatment ET improved the number of rhizospheric signifcantly. The effect of treatment ECT on the number of rhizospheric bacteria under different densities was not significant. Of treatment EC, the number of rhizospheric actinomycetes of Betula albosinensis under low density were increased significantly, however, treatment EC did not stimulate the number of rhizospheric actinomycetes under high density. Simultaneously, treatment ET and ECT did not stimulate the number of rhizospheric actinomycetes. Finally, in treatment ECT, the number of rhizospheric fungi under high density were increased significantly, however treatment EC and ET did not stimulate the number of rhizospheric fungi under different densities. 3) Of treatment EC, ET and ECT, the number of rhizospheric microbe of Betula albosinensis under low density were not more or fewer than that of microbe under hign density along the growing season, which showed that plant density had no effect on the nmber of microbe. 4) From May to October, 2004，rhizospheric catalase activity of Betula albosinensis of treatment EC was 1.44, 1.06, 1.11, 1.10, 1.12 and 1.24 times as treatment CK respectively, and the difference was statistically significant(except June). Treatment ET and ECT did not increase rhizospheric catalase activity significantly. In treatment EC, the rhizospheric pohyphenol oxidase activity was higher than treatment CK significantly. The rhizospheric pohyphenol oxidase activity of treatment ET was higher than CK significantly (except August). The rhizospheric pohyphenol oxidase activity of treatment ECT was higher than CK, but the difference was not statistically significant. Over the growing period, the rhizospheric dehydrogenase activity were increased 46%, 40%, 133%, 48%, 17% and 26% respectively by treatment EC, and the difference was statistically significant. From May to July, the rhizospheric dehydrogenase activity in treatment ET and ECT was higher than CK, but from August to October, the rhizospheric dehydrogenase activity was lower than CK, the difference was not significant. 5) Treatment EC increased rhizospheric urease activity significantly, from May to October, rhizospheric urease activity were increased 29%, 42%, 70%, 67%, 59% and 57% respectively by EC. Treatment ET and ECT had no effect on rhizospheric urease activity. Treatment EC improved rhizospheric invertase activity significantly, in May, June and September, the rhizospheric invertase activity of treatment EC were increased 51%, 42% and 40% in comparison with the control. Except May and October, the rhizospheric invertase activity of treatment ET was markly higher than CK. The rhizospheric invertase activity of treatment ECT was significantly different from CK (except September), in May, June and July treatment ECT increased rhizospheric invertase activity by 94%, 198% and 67% respectively. 6) In comparison with the control, treatment EC, ET, and ECT had no effect on the number of non-rhizospheric microbe and non-rhizospheric enzyme activity. Rhizospheric effect of catalase and urease for all treatments was significant, but rhizospheric effect of pohyphenol oxidase and dehydrogenase was not significant. Rhizospheric effect of invertase of EC and ECT was significant, but rhizospheric effect of invertase of ET was not significant.

小麦胚乳蛋白组分和Glu-B3位点基因核心编码区差异与小麦品质关系的研究

小麦加工品质改良已成为我国小麦育种的主要目标之一。特别是我国加入WTO以后，对小麦产品的质量提出了更高的要求，小麦品质改良的任务将更加艰巨和重要，小麦胚乳蛋白是影响小麦加工品质性状的重要因素。因此，深入了解小麦胚乳蛋白对加工品质性状的影响及其分子基础，为品质改良提供理论依据和科学指导，对加速我国小麦品质育种和优质小麦生产具有重要意义。本研究选用在麦谷蛋白5个基因位点(Glu-A1、Glu-B1、Glu-D1、Glu-B3和Glu-D3)上均含不同等位基因的小麦品种99G45和京771及Pm97034和京771杂交F9代共164个麦谷蛋白纯合系，及228个中国推广普通小麦品种和高代育成品系为试材，研究了麦谷蛋白Glu-1和Glu-3位点基因等位变异对籽粒蛋白、湿面筋含量、Zeleny沉降值和SDS沉降值间的关系；本研究还利用小麦A、B和D基因组中低分子量麦谷蛋白亚基（LMW-GS）基因特异引物，通过PCR方法克隆了1个Glu-A3位点和3个Glu-B3位点LMW-GS基因片段，在此基础上分析了不同等位基因对品质造成差异的分子基础；另外，本研究对中国近年推广的部分品种和育成的高代品系资源的多样性进行了分析。现将主要研究结果简述如下： 1. 对来自三个麦区的148份材料的醇溶蛋白组成进行了分析，结果表明，各麦区醇溶蛋白模式具有较大差异。在ω区,A7、B、E、F、G、J、P、Q、S和U仅存在于西南秋播麦区；A3、M、N、R、W和X仅存在于黄淮特种麦区；K仅存在于北方冬麦区；A6是北方冬麦区出现频率最高的带型模式，而西南秋播麦区中D出现的频率最高。ω-区的E、H和M几种模式是以前国内外未曾报道的。且初步确定，这些模式对品质性状具有正效应。至于γ区,A、B、D、E和F在各区均有出现，其中B和E在各区出现的频率都很高，在26.1-39.6％之间。相反，H 仅出现在黄淮特种麦区，J仅限于西南秋播麦区。对于β-区醇溶蛋白，B型模式在所有区中都相当高，而模式A仅存在于第三区.对于α-区，模式A在Ⅲ区而模式D在Ⅱ区出现的频率很高。1BL.1RS易位系在中国小麦品种中出现频率高达41.2％，在I, II和Ⅲ麦区的出现频率分别为 45.5、43.5和35.2%。各生态区模式的差异可能是品种适应不同生态条件和人为选择的结果，但这有待进一步证明。由于醇溶蛋白位点（Gli-1）与LMW-GS位点（Glu-3）紧密连锁，本结果可为下面确定普通小麦LMW-GS等位基因变异所用。 2. 利用Gli-1与Glu-3的紧密连锁，以228个小麦品种/系为材料，首次对中国小麦品种麦谷蛋白亚基的6个位点进行综合分析，研究小麦籽粒蛋白与品质性状间的关系，结果表明6个高分子量（HMW）和低分子量（LMW）麦谷蛋白位点对蛋白质含量的效应大小为，Glu-D1>Glu-B3>Glu-A1=Glu-B1> Glu-A3=Glu-D3；对GMP含量的效应大小为, Glu-A3>Glu-B3>Glu-D1> Glu-B1>Glu-A1>Glu-D3；对湿面筋含量的效应大小为, Glu-B1>Glu-B3= Glu-D3>Glu-A3>Glu-A1>Glu-D1；对Zeleny沉降值的效应大小为, Glu-A1> Glu-B3>Glu-D3>Glu-D1>Glu-B1>Glu-A3；对SDS沉降值的效应大小为, Glu-B3>Glu-A1=Glu-D1=Glu-A3>Glu-D3>Glu-B1。对蛋白含量而言，各位点的最佳组合方式为1、17+18、5+10、Glu-A3e、Glu-B3g、Glu-D3b；对湿面筋含量而言，各位点的最佳组合方式为1、6+8、5+10、Glu-A3d、Glu-B3c、Glu-D3b；对Zeleny沉降值而言，各位点的最佳组合方式为N、17+18、5+10、Glu-A3d、Glu-B3d、Glu-D3b；对SDS沉降值而言，各位点的最佳组合方式为1、7+8、2.2+12、Glu-A3b、Glu-B3g、Glu-D3b。另外，分析了稀有亚基对5+12与2.2+12与品质性状的关系，认为5+12对品质有负效应，2.2+12对品质有正效应。在品质育种时，应对优异组合或优异亚基加以利用。 3. 首次利用重组自交系（RILs）为材料，研究麦谷蛋白亚基表达量与品质性状的关系，通过对重组自交系中各HMW-GS表达量的分析，认为，就单个亚基的表达量而言，7亚基最高；其次为2亚基、5亚基、12亚基和10亚基；亚基9和1的表达量最小；N亚基不表达。对成对出现的亚基对而言，x型和y型亚基的总表达量2+12>5+10>7+9>17+18。就单个亚基与品质性状的关系而言，仅有10亚基的表达量与蛋白含量的相关性达5%的显著水平，2亚基的表达量与湿面筋含量呈负相关，显著水平也达5%，其余单个亚基对品质性状均无显著影响；就x型/y型亚基的比例来看，2/12和5/10对湿面筋含量都有显著的负效应；对某一位点等位基因控制的亚基表达总量来看，2+12对SDS沉降值有显著负效应。另外，本研究得出：2＋12的亚基对的负效应主要体现在2亚基上，且在同一位点上，x型亚基的表达量大于y型。所以推导稀有亚基组合2+10很可能也是劣质亚基。 4. 以 Glu-A1、Glu-B1、Glu-D1、Glu-B3和Glu-D3作为5个因素对99G45/京771和Pm97034/京771杂交后代的蛋白质含量和SDS沉降值进行多因素方差分析。结果表明，Glu-A1和Glu-D3对蛋白含量的加性效应达5％显著水平；Glu-D1 * Glu-D3对蛋白质含量的互作效应也达5%显著水平；其余位点的加性和互作效应对蛋白质含量的影响均不显著。对SDS 沉降值而言，Glu-D1的加性效应最大,贡献率为4.2 % ,达1 %显著水平,其次是Glu-B1位点,贡献率为3.3% ,达5%显著水平。其余位点对SDS 沉降值的加性和互作效应均未达5%显著水平。总体而言, 各位点对蛋白含量的效应大小为Glu-D3 > Glu-A1 > Glu-D1>Glu-B1>Glu-B3；对SDS沉降值的效应大小为Glu-D1>Glu-B1> Glu-D3>Glu-A1> Glu-B3。Glu-D1和Glu-D3位点上等位基因变异对蛋白含量有显著或极显著影响，含Glu-D1d和Glu-D3 GD、Glu-D3 JD基因的株系分别比含Glu-D1a和Glu-D3 PD基因的株系有较高的蛋白含量；在该遗传背景下，麦谷蛋白各基因位点对蛋白含量的效应大小依次排列为：Glu-A1位点1>N；Glu-B1位点7+9>17+18>14+15；Glu-D1位点5+10>2+12；Glu-B3位点GB>JB>PB；Glu-D3位点GB>JB>PB。对SDS沉降值的效应大小依次排列为：Glu-A1位点1>N；Glu-B1位点7+9=17+18>14+15；Glu-D1位点5+10>2+12；Glu-B3位点GB>JB>PB；Glu-D3位点GB>JB>PB。所以，对蛋白含量和SDS沉降值均较好的组合为1，7+9，5+10，GB，GD。 5. 因为GB和PB对品质的效应有显著差异，选取LMW-GS位点特异扩增引物对京771、99G45和Pm97034的Glu-B3位点进行扩增，结果得到三个不一样的扩增片段（Genebank号为DQ539657－DQ539659），得到的基因片段与Genebank中已报道的同类序列高度同源。通过克隆片段组成的分析，发现对Pm97034的序列较京771和99G45段少一个7氨基酸的重复单元，这可能是它较另外两个片段对面筋强度影响小的主要原因；另外，在99G45的序列中，124位处出现L（亮氨酸）代替P（脯氨酸），158位处出现了T（苏氨酸）代换M(蛋氨酸)，这可能是99G45Glu-B3位点序列对SDS沉降值的效应显著优于Pm97034的原因。 6．通过对RILs各位点同普通小麦品种（系）各位点与品质关系的比较，发现对SDS沉降值的效应，各位点在不同研究材料中是不同的，普通小麦中：Glu-B3>Glu-A1=Glu-D1=Glu-A3>Glu-D3>Glu-B1，RILs中：Glu-D1>Glu-B1> Glu-D3>Glu-A1> Glu-B3。利用重组自交系材料（完全排除了1BL/1RS易位干扰）所得到的结果与Gupta and MacRitchie (1994)所得结论一致。进一步证实了1BL/1RS易位对小麦品质的重要影响。对蛋白含量而言，普通小麦品种（系）中，Glu-D1>Glu-B3>Glu-A1=Glu-B1> Glu-A3=Glu-D3，RILs中，Glu-D3 > Glu-A1 > Glu-D1>Glu-B1>Glu-B3，和对SDS沉降值的效应一样，推断在非1BL/1RS易位的情况下，各位点对其效应应为Glu-D3 > Glu-A1 > Glu-D1>Glu-B1>Glu-B3。 对同一位点的等位基因而言，普通小麦和重组自交系中Glu-A1和Glu-D1上的等位基因对品质性状的贡献是一致的，但Glu-B1上的等位基因对SDS沉降值的贡献发生了变化，普通小麦中17+18>7+9，RILs中7+9>17+18，这可能也是1BL/1RS造成的。 Baking quality improved is one of the main object of wheat bread in China. The overall objective of the present studies was to increase the understanding about protein quality in wheat, i.e. to make it possible to improve the production of wheat with desired quality for different end-uses. With the analysis of gluten protein in RILs, 99G45/Jing 771 and Pm97034/Jing, and 228 wheat cultivars or lines in China, the correlations between glutenin compositions and protein content, glutenin macropolymer(GMP), wet gluten content, Zeleny sedimentation value and SDS sedimentation value contentand breadmaking quality were studied. Also a rapid and efficient detection method of geneticpolymorphism at Glu-B3 loci in wheat was established using polymerase chain reaction(PCR).The results obtained were as follows: 1. Cultivated Chinese wheat germplasm has been a valuable genetic resource in international plant breeding. Patterns of gliadin among cultivated Chinese accessions are unknown, despite the proven value and potential novelty. The objective of this work was to analyse the diversity within improved Chinese wheat germplasm. The electrophoretic banding patterns of gliadin in common wheat cultivars and advanced lines were determined by acid-polyacrylamide gel electrophoresis. For 148 leading commercial cultivars and promising advanced lines used in our study, 48 patterns were identified, 29 corresponding to ω-gliadin, 9 to γ-gliadin, 5 to β-gliadin and 5 to α-gliadin. The most frequent patterns were A6 in ω; B in γ; B in β and A in the region of α. 116 band types appeared in the148 samples: 94 accessions had unique gliadin types, and 22 gliadin types while not unique were found in 54 accessions. The gliadin patterns of Chinese wheat cultivars and lines greatly differed from the patterns of wheat lines from other countries. Three patterns, E, J, H, M, N and O in the ω-zone had not previously been reported. Three wheat zones，the Northern Winter Wheat Region, the Yellow and Huai Valley River valleys Winter Wheat Region and the Southwestern Winter Wheat Region，in China showed different frequencies in their gliadin patterns. This information can be used to monitor genetic diversity with Chinese wheat germplasm. 2. To analyse the relationship between the loci and characteristics quality, we utilized the 228 cultivars/lines. The results showed that : For protein content, Glu-D1 >Glu-B3>Glu-A1=Glu-B1>Glu-A3=Glu-D3. For GMP content, Glu-A3>Glu-B3 >Glu-D1>Glu-B1>Glu-A1>Glu-D3. For wet gluten content, Glu-B1>Glu-B3= Glu-D3>Glu-A3>Glu-A1>Glu-D1. For Zeleny sedimentation value, Glu-A1>Glu-B3> Glu-D3>Glu-D1>Glu-B1>Glu-A3, For SDS sedimentation value, Glu-B3>Glu-A1= Glu-D1= lu-A3>Glu-D3>Glu-B1。For protein content, the best combination of 6 loci is (1,17+18,5+10,Glu-A3e, Glu-B3g,Glu-D3b). For wet gluten content, the best combination of 6 loci is (1,6+8,5+10,Glu-A3d,Glu-B3c,Glu-D3b). For Zeleny sedimentation value, the best combination of 6 loci is (N,17+18,5+10,Glu-A3d, Glu-B3d, Glu-D3b). For SDS sedimentation value, the best combination of 6 loci is(7+8,2.2+12,Glu-A3b, Glu-B3g,Glu-D3b)。Additional, we analysed the relationship between the subunits 5+12 and 2.2+12, think that 5+12 was negative for quality, 2.2+12 is postive for quality. It should be effective utilized. 3. It’s the first time to utilize RILs to study the relationship between subunits expression quantity and characteristics quality. The results showed that: For single subunit, the expression quantity of 7 is the highest. Then the 2, 5, 12 and 10. The expression of subunit 9 and 1 is the lowest. Subunit N is not expressed. For subunits, the expression quantity of x type and y type are 2+12>5+10>7+9>17+18. The significant relation of 5% only showed between the expression quantity of subunit 10 and protein content. The relationship between expression quantity of others and characteristic quality was not significant. For x type/ytype, 2/12 and 5/10 is negative relation insignificant level. For the subunit(s) in a loci, Only 2+12 effect SDS sedimentation value negative in significant level. 4. With RILs 99G45/Jing 771 and Pm97034/Jing 771, we found that: The effective of Glu-A1, Glu-D3 and Glu-D1 * Glu-D3 for protein content is significant at 5% level. The effect of other loci for protein wre not significant. For SDS sedimentation value, the effect of Glu-D1is the highest, which contribution is 4.2 % .Then the Glu-B1, contribution is 3.3%. The effect of other loci for SDS sedimentationvalue were not significant. In total, for protein content: Glu-D3 > Glu-A1 > Glu-D1>Glu-B1>Glu-B3; for SDS sedimentationvalue: Glu-D1>Glu-B1> Glu-D3>Glu-A1>Glu-B3. The effect of alleles in Glu-D1 and Glu-D3 loci are significant at 1% or 5%. In Glu-A1, 1>N; Glu-B1, 7+9>17+18>14+15; Glu-D, 5+10>2+12; Glu-B3, GB>JB>PB; Glu-D3, GB>JB>PB. For SDS sedimentation, Glu-A1, 1>N; Glu-B1, 7+9=17+18>14+15; Glu-D1, 5+10>2+12; Glu-B3, GB>JB>PB; Glu-D3, GB>JB>PB. The best combinations for SDS sedimentation value is 1，7+9，5+10，GB，GD. 5. Because of the difference of GB and PB for SDS sedimentation value, we selected the specific primer for LMW-GS loci to amplified the Glu-B3 of Jing771, 99G45and Pm97034. We got 3 amplify fragment (Gene Bank accession number are DQ539657－DQ539659）. We found that the fragment of Pm97034 were deleted a repetitive 7 amino acid domain, which is perhaps the reason effect the gluten strength. Furthermore, in the position 124 of sequence 99G45, L has been replaced with P. Position 158, T replaced M, which may be the reason why the Glu-B3 locus of 99G45 is prefer to Pm97034 when refer to SDS sedimentation value. 6. Comparing the results of RILs and common wheat, we found that perhaps just the1BL/1RS made the difference of loci in different accession.

Studies of timing for a TOF counter at external target facility

Timing and amplitude properties of a prototype scintillator TOF counter at an external target facility are studied with a cosmic rays test. The dependence of signal pulse height and time resolution on the coordinate along the scintillator TOF counter is investigated with two different discriminators. A time resolution of 165 ps can be achieved at the center of the counter with a constant fraction discriminator. Time resolution better than 150 ps is obtained at the center with a leading edge discriminator af...

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