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玉米籽粒脱水速率测定方法优化及遗传研究
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摘要
玉米是粮、经、饲三元作物。作为我国三大粮食作物之一,自新中国成立以来的近60年间,在解决温饱问题、保证粮食和饲料安全、发展国民经济以及缓解能源危机等方面发挥了重要作用。2009年,我国玉米种植面积已经超过水稻成为种植面积最大的作物,但是随着畜牧业和玉米深加工的发展,玉米作为粮经饲兼用作物的需求量日趋增加,玉米育种的任务仍然艰巨,而玉米改良的重点在可预见的将来仍集中在产量和品质的改良。粒用玉米的品质,除本身的蛋白质,赖氨酸、淀粉和脂肪含量外,另一个重要方面就是籽粒外观色泽。要保持籽粒外观色泽鲜美、洁净,就要求籽粒能迅速脱水和干燥。在一些高纬度高海拔地区,由于秋后气温迅速下降、雨水偏多、日照不足以及有效活动积温低,部分品种在收获时或遇到早霜时甚至不能正常成熟,或者引起籽粒霉烂;与此同时,玉米生产的全程机械化是世界和我国玉米生产的不可逆转趋势,玉米果穗脱水快和收获时籽粒含水量低,利用机械化收获可大大减少破碎率,减少产量损失;还可大大减少籽粒烘干的时间,节约能源和低碳,保护环境。鉴于此,玉米籽粒脱水慢、收获时籽粒含水量过高已成为世界玉米生产特别是高纬度或高海拔玉米生产区的主要问题。因此,籽粒快速脱水成为了玉米育种的一个重要的目标性状。本研究以5个自交系为材料,利用一种改良后的探针水分测定仪对全穗、苞叶、籽粒以及穗轴四部分的水分进行测定,并采用传统的烘箱法对这四部分的水分进行测定并与水分测定仪的测定值进行比较,优化了利用水分测定仪进行籽粒含水量测定的方法,并建立真实水分读数的标准曲线;以6个玉米自交系及8个F1为供试材料,对其抽丝后不同时间段进行水分测定,评价环境因子包括玉米热单位(CHU,Corn Heat Unit)及降雨量对籽粒脱水速率的影响,并提出利用水分测定仪进行快速脱水玉米选择的最佳时间;以上述研究结果为基础,通过对262份自交系进行鉴定,筛选出快速脱水自交系,供快速脱水育种用;以6个玉米自交系为材料,配制8个F1组合,对亲本及组合进行脱水性状的遗传分析,为组配快速脱水杂交种提供理论依据;对籽粒脱水速率与穗粒腐病抗性及农艺性状进行相关分析,探讨籽粒脱水速率与其它性状的相关性;搜集已发表的控制水分含量及抗穗粒腐病的QTL研究,通过元分析得出两个性状相关的真实QTL位点,并综合元分析结果,分析两个性状的一致性QTL区域。主要研究结果如下:
     1.利用水分测定仪(读数法)和烘干法测定的各部分含水量均具有显著相关性。其中全穗含水量和籽粒+穗轴含水量的相关系数最高,达到了0.98(2006年)和0.99(2007年)。用读数法进行含水量测定时,苞叶对全穗水分读数的影响不大。当籽粒含水量大于60%或者低于20%时,穗轴对籽粒含水量的影响较小;而当籽粒含水量位于20%至60%之间时,穗轴对籽粒含水量的影响相对偏大。当利用烘干法进行含水量测定时,穗轴对籽粒含水量影响较小。对全穗水分读数及籽粒含水量进行相关性分析,发现全穗水分读数可以利用线性模型(y=1.11x,R2=0.79)来预测籽粒含水量。
     2.2007、2008及2009年间,降雨量及CHU均与籽粒含水量具有显著相关性。抽丝后的累积CHU可以利用模型y=c+dx2预测收获时的籽粒含水量。对不同的材料而言,籽粒含水量在抽丝后第4周开始出现差异,第5周开始出现显著差异。试验筛选出20个材料在抽丝后第5至6周(35-42天)具有较低的籽粒含水量,而其中的16个在收获时也具有较低的籽粒含水量。因此,使用水分测定仪MT808进行脱水速率测定时,最佳测定时间是从抽丝后的第5周至第8周。
     3.抽丝期对脱水速率具有显著影响,可使用分值进行籽粒快速脱水自交系筛选。具体的评分标准为:得分值=第5周含水量差异值+第8周含水量差异值-抽丝期差异值。其中,差异值=(总体平均值-该基因型平均值)/总体标准差。根据以上评定标准,对评价分数大于1的自交系作为快速脱水自交系进行选择。2008年筛选出22份自交系,2010年筛选出24份自交系。综合两年的研究结果,共筛选出5份在两年的脱水速率得分值均大于1的自交系,分别为:A679,B73-10,C0308、C0314和C0328。
     4.玉米籽粒脱水速率性状主要受加性遗传效应(87.48%)影响,也受少量非加性效应(12.52%)影响;籽粒脱水速率的广义遗传力(hB%)为79.16,狭义遗传力(hN%)为69.25,说明脱水速率是高度遗传的,实践中对籽粒快速脱水育种可进行早代选择;通过对不同组合的配合力效应值分析,发现C0431和C0441均表现出较高的GCA效应值,表明这两个自交系具有良好的育种应用价值,在籽粒快速脱水育种中可利用C0431和C0441组配组合。
     5.籽粒脱水速率与镰刀穗腐(籽粒接种)和水处理在0.1的水平上具有显著相关性。镰刀穗腐(籽粒接种)和串珠穗粒腐(籽粒接种),镰刀穗腐(籽粒接种)和水处理间均具有极显著相关性,相关系数分别为0.760和0.821。株高、穗位高和粒长与籽粒脱水速率均表现出显著负相关。其中,穗位高和脱水速率的相关系数最大(r=-0.607),株高与脱水速率的相关系数其次(r=-0.577),粒长与籽粒脱水速率的相关系数为-0.535。秃尖长在0.1的水平上也与脱水速率具有显著相关性(r=0.521)。
     6.研究发现44个控制籽粒含水量的“一致性”QTL,并筛选出6个热点区域(bins 1.03,2.09,8.03,8.05,8.06和10.04)。控制穗粒腐抗性的“一致性”QTL有29个,主要分布的热点区域为bin 2.08和bin 3.04。在第2、第3、第6和第7条染色体上,共存在14个玉米籽粒含水量及穗粒腐病抗性“一致性”QTL的重叠区域,这些重叠区域主要集中在5个区段。在这些区段内共发现13个已知基因,可将这些基因归纳为5类:压力相关基因(htl,和abal),光合系统相关基因(lhcal、psbsl和ij1形态相关基因(eif5α和lg2),动力学相关基因rop6和sarl)以及生殖相关基因(dfr1和zmm7)。
Maize (Zea mays L.) is the important food, industrial materials, feed and economic crop in China. As one of the three most important crops, it played an important role to solve many problems, such as food safety, energy sources, and so on. Maize became the biggest plant area in 2009 in China. However, becaust of the use develop of economic, the maize breeding is much more important than before. The mainly breeding goal included yield and quality. High kernel dry down rate is important to keep high quality. In mid-to short-season environments, the available seasonal thermal-time may be insufficient for grain maize to nature, there is a risk of insufficient time for kernel filling and drydown before the cooler fall weather slows development or an early frost occurs if these intermediate to late maturing hybrids do not flower until August. Based on this, high ear moisture (EM) at harvest became the main problem in all over the world, especially in short season region. So kernel dry down rate is the important goal in maize breeding. In this study, five inbred lines were used to measure the moisture reading in ear, husk, kernel and cob using modified moisture meter MT808, and compared the data with moisture content which measured by oven method, to develop a tool that could be used to non-destructively measure kernel moisture in the field, thereby allowing the selection of genotypes with faster kernel drydown rates; six inbred and eight hybrid lines were used to do the different period water measurements. We analysis the influence of environment factors included core heat units (CHU) and rainfall to kernel dry down rate, and measure the best time to select the fast dry down rate using MT808; identification the kernel dry down rate of 262 inbred lines, and select the inbred lines with fast dry down rate for breeding; six inbred and eight hybrid lines were used to do genetic analysis; the correlation between kernel dry down rate and ear rot resistance, the kernel dry down rate and the agronomic traits; all the published QTL results of ER reactions and GM in maize were collected, a meta-analysis was carried out to get the overlap domain of both traits to investigate the relationship between ER resistance and GM. The main results were summarized as followed:
     1. An Electrophysics moisture meter model MT808 was modified with two steel pins, it can be used for measuring maize ear moisture. Meter readings and relative kernel moisture, measured after destructive sampling and oven drying, were highly correlated. Total ear moisture readings (readings taken by inserting the pins thru the husk and into the kernels) could be used to predict kernel moisture, using the calibration curve y= 1.11x (R=0.79). Genotypic differences in kernel moisture were measurable using this meter. Husks influenced moisture measurements more in the early stages of ear development. The use of a modified hand-held moisture meter will improve the selection for kernel drydown in short-season corn hybrids.
     2. In 2007,2008 and 2009, ear moisture of six inbred lines and eight hybrid lines of corn (Zea Mays L.) were measured weekly using a modified Electrophics Moisture Meter model MT808 during the period from a week after silking date to harvest. Daily rainfall impacting on ear moisture dry down rate. During the filling time, CHU played an important role in ear moisture drydown. Calibration curve y= c+dx2 could be used to measure the moisture content in harvest using accumulation CHU after silking. During the first four weeks after silking, the ear drydown rates for all the test lines were not significant. However, at the time of 5 and 6 weeks after silking, ear drydown rate were different among lines. Most of lines which had lower ear moisture at 5 and 6 weeks after silking had lower kernel moisture at 8 weeks after silking where it was about harvesting time. The study shows that the suitable time for measuring ear moisture was between 5 and 6 weeks after silking date.
     3. A formula was used to measure the kernel dry down rate:Difference= (All average-genotype average)/all STDEV, and selection using scores. The score calculate as followed: score= difference in 5 week+difference in 8 week-difference in silk date. Based on above standard, we selected the fast dry down rate inbred lines with scores more than 1. There were 22 inbred lines were selected in 2008, while 24 inbred lines were selected in 2010. In total, there were five inbred lines had good performance in both two years, included:A679, B73-10, CO308、CO314 and CO328.
     4. The studies on six maize inbred lines and its eight F1 which derived from 4×2 incomplete diallel crosses demonstrate that:The kernel dry down rate mainly influenced by the additive genetic effect (87.48%), low influence by non-additive effect (12.52%) also exist; The broad sense heritability (79.16%) and narrow sense heritability (69.25%) also existed in kernel dry down rate, it showed that fast dry down rate was highly heritable, so selection of early generation should be carried out in fast dry down breeding; The results showed that CO431and CO441 had high generally combining ability, it can be used as good potential parents in fast dry down breeding.
     5. The disease severity in FGK and water check were significant correlated with kernel dry down rate in probability 0.1. FGK and FVK, FGK and water check had significant correlation, the correlation coefficient were 0.760 and 0.821, respectively. The plant height, ear height and kernel length were negatively correlated to kernel dry down rate. Among them, the correlation coefficient of ear height and kernel dry down rate was the most high one (r=-0.607), the correlation coefficient of plant height and kernel dry down rate was-0.577.
     6. Our purpose was to identify the genomic regions of maize in the control of ER resistance and GM, and the correlations between two traits. A meta-analysis was carried out using 241 quantitative trait loci (QTL) from 29 studies to propose meta-QTL (MQTL) on a high-density genetic linkage map (IBM 2 neighbors 2008). Twenty-nine MQTL were found for ER resistance, mainly located on chromosomes 3,6 and 7. The ER MQTL were clustered on two chromosome regions, bins 3.04 and 2.08. For GM content,44 MQTL were identified on all chromosomes except for chromosome 9. The GM MQTL were clustered on six active chromosome regions, including bins 1.03,2.09,8.03,8.05,8.06 and 10.04. Moreover,14 overlapping domains for ER MQTL and GM MQTL were observed on chromosomes 2,3,6 and 7, mainly focused on five active regions (bins 2.08-2.09,3.04,3.06,6.04-6.06 and 7.03-7.03). There were 13 genes in the overlapping domain between MQTL for GM and ER. These genes were divided into five classed:stress-related gene(htl and aba 1), photosystem-related gene (lhcal, psbsl and ijl), architecture-related gene (eif5a and lg2), dynamic-related gene (pdi8, tua5, rop6 and sar1) and seminal-related gene(dfrl and zmm7).
引文
1. Ali ML, Taylor JH, Jie L, Sun G, William M, Kasha KJ, Reid LM, Pauls KP. Molecular mapping of QTLs for resistance to Gibberella ear rot, in corn, caused by Fusarium graminearum. Genome. 2005,48:521-533
    2. Alwala S. Identification of molecular markers associated with resistance to Aspergillus flavus in maize. Master Thesis, Louisiana State University, Baton Rouge, Louisiana State, United States. 2007
    3. Andrew, RH, Ferwerda FP, Strommen AM. Maturation and yield as influenced by climate and production technique. Agronomy Journal.1956,48:231-236.
    4. Arcade A, Labourdette A, Falque M, Mangin B, Chardon F, Charcosset A, Joets J. Biomercator: Integrating genetic maps and QTL towards discovery of candidate genes. Bioinformatics.2004, 20:2324-2326.
    5. Austin DF, Lee M, Veldboom LR, Hallauer AR. Genetic mapping in maize with hybrid progeny across testers and generations:grain yield and grain moisture. Crop Sci.2000,40:30-39.
    6. Ballini E, Morel J, Droc G, Price A, Courtois B, Notteghem J, Tharreau D. A genome-wide meta-analysis of rice blast resistance genes and quantitative trait loci provided new insights into partial and complete resistance. Mol Plant Microbe Interact.2008,21:859-868
    7. Baute T, Hayes A, McDonald I, Reid K. Agronomy guide for field crops. Publication 811. The Ontario Ministry of Agriculture, Food and Rural Affairs.2002.
    8. Beavis WD, Smith OS, Grant D, Fincher R. Identification of quantitative trait loci using a small sample of topcrossed and F4 progeny from maize. Crop Sci.1994,34:882-896.
    9. Boling MB, Grogan CO. Gene action affecting host resistance to Fusarium ear rot of maize. Crop Sci.1965,5:305-307.
    10. Brooking IR. Maize ear moisure during grain-filling, and its relation to physipcogical maturity and grain-drying. Field crop research.1990,23(1):55-67.
    11. Brown DM, Bootsma A. Crop heat units for corn and other warm-season crops in Ontario. Ontario Ministry of Agriculture and Food. Factsheet 1993, p93-119, Agdex 111/31,4pp. Available on-line: http://www.omafra.gov.on.ca/english/crops/facts/93-119.htm.
    12. Brown, DM. Heat units for corn in southern Ontario. Ontario Ministry of Agriculture and Food. Order No.1978,78-063, Agdex 111/31,4pp.
    13. Busboom KN, White DG. Inheritance of resistance to aflatoxin production and Aspergillus ear rot of corn from the cross of inbreds B73 and Oh516. Phytopathology.2004,94:1107-1115.
    14. Bush BJ, Carson ML, Cubeta MA, Hagler WM, Payne GA. Infection and fumonisin production by Fusarium verticillioides in developing maize kernels. Phytopathology.2004,94:88-93.
    15. Capelle V, Remoue C, Moreau L, Reyss A, Mahe A, Massonneau A, Falque M, Charcosset A, Thevenot C, Rogowsky P, Coursol S, Prioul j1. QTLs and candidate genes for desiccation and abscisic acid content in maize kernels. BMC Plant Biology.2010,10:2
    16. Castegnaro M, McGregor D. Carcinogenic risk assessment of mycotoxins. Rev Med Vet.1998, 149:671-678.
    17. Cavalieri AJ, Smith OS. Grain filling and field drying of a set of maize hybrids released from 1930 to 1982. Crop Sci.1985,25:856-860.
    18. Chardon F, Virlon B, Moreau L, Falque M, Joets J, Decousset L, Murigneux A, Charcosset A. Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome. Genetics.2004,168:2169-2185.
    19. Chungu C, Mather DE, Reid LM, Hamilton RI. Comparison of techniques for inoculating maize silk, kernel and cob tissues with Fusarium graminearum. Plant Dis,1996,80:81-84.
    20. Chungu C, Mather DE, Reid LM, Hamilton RI. Inheritance of kernel resistance to Fusarium graminearum in maize. J Heredity.1996,87:382-385.
    21. Crane PL, Miles SR, Newman JE. Factors associated with varietal differences in rate of field drying in corn. Agron J.1959,51:318-320.
    22. Cross HZ, Chyle JR, Hammond JJ. Divergent selection for ear moisture in early maize. Crop Sci. 1987,27:914-918.
    23. Cross HZ, Kabir KM. Evaluation of field dry-down rates in early maize. Crop Sci.1989,29:54-58
    24. Cross HZ, Zuber MS. Predictin of flowering dates in maize based on different methods of estimating thermal units. Agronomy Journal.1972,64:351-355.
    25. Cross HZ. A selection procedure for ear drying-rates in maize. Euphytica.1985,34:409-418.
    26. Cross HZ. Leaf expansion rate effects on yield and yield components in early-maturing mazie. Crop Sci.1991,31(3):579-583.
    27. Curtis PE, Leng ER, Hageman RH. Developmental changes in oil and fatty acid content of maize strains varying in oil content. Crop Sci.1968,8:689-693.
    28. D 2462-90, Standard testmethod formoisture inwoolby distillation with toluene.ASTM Standards,USA.2001.
    29. Darvasi A, Soller M. A simple method to calculate resolving power and confidence interval of QTL map location. Behav Genet.1997,27:125-132
    30. Daynard TB, Kannenberg LW. Relationships between length of the actual, and effective grain filling periods and the grain yield of corn. Can J Plant Sci.1976,56:237-242.
    31. Derieux M, Bonhomme R. Heat unit requirements for maize hybrids in Europe. Results of the European FAO sub-network:Ⅱ. Period from silking to maturity. Maydica.1982,27:79-96.
    32. Desjardins AE, Busman M, Manandhar G, Jarosz AM, Manandhar HK, Proctor RH. Gibberella ear rot of maize (zea mays) in Nepal:distribution of the mycotoxins nivalenol and deoxynicalenol in naturally and experimentally infected maize. J Agric Food Chem.2008,56:5428-5436.
    33. Ding JQ, Wang XM, Chander S, Yan JB, Li JS. QTL mapping of resistance to Fusarium ear rot using a RIL population in maize. Mol Breeding.2008,22:395-403.
    34. Dwyer, L.M. D.W. Stewart, L. Carrigan, B.L. Ma, and P. Neave. Guidelines for comparisons among different corn maturity rating systems. Agron J.1999,91:946-949.
    35. Eckert DJ. Growing drier corn for the conservation of energy. Cooperative Extension Service, The Ohio State University, Bul.1978, p645.
    36. Eta-Ndu JT, Openshaw SJ. Selection criteria for grain yield and moisture in maize yield trials. Crop Sci.1992,32:332-335
    37. Eyherabide GH, Hallauer AR. Reciprocal full-sib recurrent selection in maize; I. Direct and indirect responses. Crop Sci,1991,31(4):952-959.
    38. Frary A, Nesbitt TC, Grandillo S, can de Knaap E, Cong B, Liu J, Meller J, Elber R, Alpert K, Tanksley S. Cloning and transgenic expression of fw-2:A quantitative traits locus key to the evolution of tomato. Fruit Sci.2000,89:85-87.
    39. Frascaroli E, Cane MA, Landi P, Pea G, Gianfranceschi L, Villa M, Morgante M, Pe ME. Classical genetic and QTL analyses of heterosis in a maize hybrid between two elite inbred Lines. Genetics. 2007,176:625-644.
    40. Freppon JT, St. Martin SK, Pratt RC, Henderlong PR. Selection for low ear moisture in corn, using a hand-held meter. Crop Sci.1992,32:1062-1064.
    41. GB 2772-1999,林木种子检测规程[S].国家质量技术监督局,2000
    42. Gelderblom WCA, Jaskiewicz K, Marasas WFO, Thiel PG, Horak RM, Vleggaar R, Kriek NPJ. Fumonisins-novel mycotoxins with cancer-promoting activity produced by Fusarium moniliforme. Appl. Environ Microbiol.1988,54:1806-1811
    43. Gilmore, ECJr, Rogers JS. Heat units as a method of measuring maturity on corn. Agronomy Journal.1958,50:611-615.
    44. Glass GV. Primary, secondary, and meta-analysis of research. Educ Res.1976,5:3-8
    45. Goffinet B, Gerber S. Quantitative trait loci:A meta-analysis. Genetics.2000,155:463-473
    46. Groos C, Robert N, Bervas E, Charmet G. Genetic analysis of grain protein-content, grain yield and thousand-kernel weight in bread wheat. Theor Appl Genet.2003,106:1032-1040.
    47. Guo B, Sleper DA, Lu P, Shannon JG, Nguyen HT, Arelli PR. QTLs associated with resistance to soybean cyst nematode in soybean:meta-analysis of QTL locations. Crop Sci.2006,46:595-602.
    48. Hallauer AR. Estimates of maturity and its inheritance in maize. Crop Sci.1962,2:289-295
    49. Hallauer, AR, Miranda JB. Quantitative genetics in maize breeding.2nd Edition. Iowa State Univ. Press, Ames, IA.1988.
    50. Hanocq E, Laperche A, Jaminon O, Laine AL, Le Gouis J. Most significant genome regions involved in the control of earliness traits in bread wheat, as revealed by QTL meta-analysis. Theor Appl Genet.2007,114:569-584.
    51. Hao Z, Li X, Liu X, Xie C, Li M, Zhang D, Zhang S. Meta-analysis of constitutive and adaptive QTL for drought tolerance in maize. Euphytica.2010,174:163-177
    52. Hart LP, Gendloff E, Rossman EC. Effect of corn genetypes on ear rot infection by Gibberella zeae. Plant Dis.1984,68:296-298
    53. Hellevang K. Post-harvest tips for late maturing Corn. NDSU Extension Service, North Dakota State University.2004. http://www.ext.nodak.edu/county/griggs/agriculture/2004agalerts/08-18-04.htm.
    54. Hellevang KJ, Reff T. Calculating grain drying cost. AE-923. NDSU Extension Service, North Dakota State University.1987. http://www.ag.ndsu.nodak.edu/abeng/pdffiles/ae923.pdf.
    55. Henry WB, Williams WP, Windham GL, Hawkins LK. Evaluation of maize inbred lines for resistance to Aspergillus and Fusarium ear rot and mycotoxin accumulation. Agron J.2009,101: 1219-1226.
    56. Herrera M, Conchello P, Juan T, Estopanan G, Herrera A, Arino A. Fumonisins concentrations in maize as affected by physico-chemical, enviromental and agronomical conditions. Maydica.2010, 55:121-126.
    57. Hesseltine CW, Bothast RJ. Mold development in ears of corn from tasseling to harvest. Mycologia. 1977,69:328-340.
    58. Hicks DR, Geadelmann JL, Peterson RH. Drying rates of frosted maturing maize. Agron J,1976, 68:452-455.
    59. Hillson MF, Penny LH. Dry matter accumulation and moisture loss during maturation of corn grain. Agron J.1965,57:150-153.
    60. Ho JC, McCouch SR, Smith ME. Improvement of hybrid yield by advanced backcross QTL analysis in elite maize. Theor Appl Genet.2002,105:440-448.
    61. Hunter RB, Mortimore G, Gerrish EE, Kannenberg LW. Field drying of flint and dent endosperm maize. Crop Sci.1979,19:401-402.
    62. Kandala CVK, Nelson SO, Lawrence KC. Moisture deternimation in single of corn-a nondestructive method. Trans ASAE.1988,31:1890-1895.
    63. Kang MS, Colbert TR, Zuber MS, Horrocks RD. Grain moisture loss as related to dry down rates in corn. Am Soc Agron Abstr.1975, p57.
    64. Kang MS, Zuber MS, Colbert TR, Horrocks RD. Effect of certain agronomic traits on and relationship between rates of grain moisture reduction and grain fill during the filling perion in maize. Field crops research.1986,14(4):339-346
    65. Kang MS, Zuber MS, Horrocks RD. An electronic probe for estimating ear moisture content of maize. Crop Sci.1978,18:1083-1084.
    66. Kang MS, Zuber MS. Combining ability for grain moisture, husk moisture, and maturity in maize with yellow and white endosperms. Crop Sci.1989,29:689-692.
    67. Kang MS, Zuber MS. Grain dry-down studies in corn. In D. Wilison (ed.) Proc. Of the Forty-Second Annu. Corn and Sorghum Industry Res. Conf., Chicago, IL.7-9 Dec.1987. American Seed Trade Association, Washington, DC.1987, p220-226.
    68. Kang MS. Comparative effect of Y vs y gene on several agronomic characters in Maize. Ph.D. diss. Uni of missouri columbia (Diss. Abstr,27-1734):1977.
    69. Kiesselbach TA, Walker ER. Structure of certain specialized tissue in the kernel of corn. Am J Bot. 1952,39:561-569.
    70. Kondapi N, Kang MS, Zhang Y, Deng X. Genetics of grain dry down rate in corn. In Agronomy Abstracts. ASA, Madison, WI,1993, p91-92.
    71. Kumar LS. DNA markers in plant improvement:an overview. Biotechnol Adv.1999,17:143-182.
    72. Lackey R. Corn energy value-a comparison of harvesting corn as shelled dried corn, high moisture corn, high moisture cob corn (cob meal) and corn silage. Ministry of Agriculture Food & Rural Affairs.2008. http://www.omafra.gov.on.ca/english/livestock/beef/news/vbn1108a2.htm.
    73. Lanaud C, Fouet O, Clement D, Boccara M, Risterucci AM, Surujdeo-Maharaj S, Legavre T, Argout X. A meta-QTL analysis of disease resistance traits of Theobroma cacao L.. Mol Breed, 2009,24:361-374.
    74. Lauer J. Guidelines for handling corn damaged by frost prior to grain maturity. Wisconsin Crop Manager.2004,11(23):148-149.
    75. Leslie JF, Summerell BA. The Fusarium Laboratory Manual. Ames:Blackwell Professional.2006.
    76. Li J. Inheritance of resistance to Fusarium moniliforme ear rot in maize by near isogenic lines. Master thesis, Henan Agricultural University, Zhengzhou, Henan, China.2008.
    77. Liu S, Dall MD, Griffey CA, McKendry AL. Meta-analysis of QTL associated with Fusarium head blight resistance in wheat. Crop Sci.2009,49:1955-1968.
    78. Loffler M, Schon C, Miedaner T. Revealing the genetic architecture of FHB resistance in hexaploid wheat(Triticum aestivum L.) by QTL meta-analysis. Mol Breed.2009,23:473-488.
    79. Logrieco A, Mule G, Moretti A, Bottalico A. Toxigenic Fusarium species and mycotoxins associated with maize ear rot in Europe. Eur J of Plant Patho.2002,108:597-609.
    80. Magari R, Kang MS, Zhang Y. Sample size for evaluating field ear moisture loss rate in maize. Maydica,1996,41:19-24.
    81. Mao SL, Wei YM, Cao WG, Lan XJ, Yu M, Chen ZM, Chen GY, Zheng YL. Confirmation of the relationship between plant height and Fusarium head blight resistance in wheat(Triticum aestivum L.) by QTL meta-analysis. Euphytica.2010,174:343-356.
    82. Marasas WFO, van Rensburg SJ, Mirocha CJ. Incidence of Fusarium species and the mycotoxins, deoxynivalenol and zearalenone, in corn produced in esophageal caner areas in Transkei. J Agri Food Chem.1979,27:1108-1112.
    83. Martin RA, Johnston HW. Effects and control of Fusarium diseases of cereal grains in the Atlantic province. Can J Plant Pathol.1982,4:210-216.
    84. Marza F, Bai GH, Carver BF, Zhou WC. Quantitative trait loci for yield and related traits in the wheat population Ning7840×Clark. Theor Appl Genet.2005,21:1-11.
    85. Mathre DE, Johnston RH, Martin JM. Sources of resistance to Cephalosporium gramineum in Triticum and Agropyron species. Euphytica.1985,34(2):409.
    86. Melchinger AE, Utz HF, Schon CC. Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects. Genetics.1998,149:383-403.
    87. Miller MF, Hughes HD. Cooperative variety tests of corn:variety tests of corn at Columbia, MO. Missouri Agric. Exp Stn Bull.1910,87.
    88. Misevic D, Alexander DE. Twenty four cycles of phenotypic recurrent selection for percent oil in miaze:1. per se and test-cross performance. Crop sci.1989,29(2):320-324.
    89. Misevic D, Alexander DE. Recurrent selection for percent oil in cron. Genetica (Iemun Yugosl). 1985,17:97-106.
    90. Misevic D. Grain moisture loss rate of high-oil and standard-oil maize hybrid. Agron J.1988, 80(5):841-846.
    91. Moreau L, Charcosset A, Gallais A. Use of trial clustering to study QTL × environment effects for grain yield and related traits in maize. Theor Appl Genet.2004,110:92-105.
    92. Nankam C, Pataky JM. Resistance to kernel infection by Fusaruim moniliforme in the sweet corn inbred IL125b. Plant Dis.1996,80:593-598.
    93. Nass HG, Crane PL. Effect of endosperm mutants on drying rate in corn. Crop Sci,1970, 10:141-144.
    94. Nelson SO, Lawrence KC, Kandala CVK. Comparison of RF impedance and DC conductance sensing for single-kernel moisture measurement in corn. Trans. ASAE.1990,33:637-641.
    95. Nelson SO, Lawrence KC. Kernel moisture variation on the ear in yellow-dent field corn. Trans. ASAE.1991,34:513-516.
    96. Neuffer MG, Jone LS, Zuber MS. The mutants of maize, Crop Sci. Soc. of America, Madison, Wis, USA,1968.
    97. Nijenstein H, Don R, Nydam J. Comparison of oven moisture test at130℃vs.103℃. Seed science and technology,2002,30(3):102-106.
    98. Owen CR. Corn varieties in Mississippi. Mississippi Agric Exp Stn Bull.1940, p339.
    99. Payne GA. Aflatoxin in maize. Crit Rev Plant Sci.1992,10:423-440.
    100. Perez-Brito D, Jeffers D, Gonzalez-de-Leon D, Khairallah M, Cortes-Cruz M, Velazquez-Cardelas G, Azpiroz-Rivero S, Srinivasan G. QTL mapping of Fusarium moniliforme ear rot resistance in highland maize, Mexico. Agrociencia.2001,35:181-196.
    101. Pestka JJ. Deoxynivalenol:toxicity, mechanisms and animal heath risk. Anim Feed Sci Tech.2007, 137:283-298.
    102. Purdy JD, Crane PL. Inheritance of drying rate immature corn. Crop Sci.1967,7:294-297.
    103. Qu S, Liu G, Zhou B, Bellizzi M, Zeng L, Dai LY, Han B, Wang GL. The broad-spectrum blast resistance gene pi9 encodes a nucleotide-binding site-leucine-rich repeat protein and is a member of a multigene family in rice.Genetics.2006,172(3):1901-1914.
    104. Quarrie SA, Quarrie SP, Radosevic R, Rancic D, Kaminska A, Barnes JD, Leverington M, Ceoloni C, Dodig D. Dissecting a wheat QTL for yield present in a range of environments:from the QTL to candidate genes. J Exp Bot.2006,57:2627-2637.
    105. Ragai H., W.E. Loomis. Respiration of maize grain. Plant Physiology.1954,29:49-55.
    106. Ragot M, Sisco PH, Hoisington DA, Stuber CW. Molecular-Marker-Mediated characterization of favorable exotic alleles at quantitative trait loci in maize. Crop Sci.1995,35:1306-1315.
    107. Reid LM, Bolton AT, Hamilton RI, Woldemariam T, Mather DE. Effect of silk age on resistance of maize to Fusarium gramiuearum. Can J Plant Pathol.1992,14:293-298.
    108. Reid LM, Hamilton RI, Mather DE. Screening Maize for Resistance to Gibberella Ear Rot. Agriculture and Agri-Food Canada Technical Bulletin. Publication.1996,196-201.
    109. Reid LM, Stewart DW, Hamilton RI. A 4-year study of the association between Gibberella ear rot severity and deoxynivalenol concentration. J Phytopathol.1996,144:43-436.
    110. Reid LM, Zhu X, Parker A, Yan W. Increased resistance to Ustilago zeae and Fusarium verticilliodes in maize inbred lines bred for Fusarium graminearum resistance. Euphytica.2009, 165:567-578.
    111. Reid LM, Zhu XY, Morrison MJ, Woldemariam T, Voloaca C, Wu J. A non-destructive method for measuring maize kernel moisture in a breeding program. Maydica.2010,55:163-171.
    112. Reid, LM, Woldemariam T, Zhu X, Stewart DW, and Schaafsma AW. Effect of inoculation time and point of entry on disease severity in Fusarium graminearum, Fusarium verticillioides, or Fusarium subglutinans inoculated maize ears. Can J Plant Pathol.2002,24:162-167.
    113. Ren JP. Preliminary study in maize ear rot. Maize Sci.1993,1:75-79.
    114. Robertson-Hoyt LA, Betran J, Payne GA, White DG, Isakeit T, Maragos CM, Molnar TL, Holland JB. Relationships among resistances to Fusarium and Aspergillus ear rots and contamination by fumonisin and aflatoxin in maize. Phytopathology.2007a,97:311-317.
    115. Robertson-Hoyt LA, Jines MP, Balint-Kurti PJ, Kleinschmidt CE, White DG, Payne GA, Maragos CM, Molnar TL, Holland JB. QTL mapping for Fusarium ear rot and fumonisin contamination resistance in two maize populations. Crop Sci.2006,46:1734-1743.
    116. Robertson-Hoyt LA, Kleinschmidt CE, White DG, Payne GA, Maragos CM, Holland JB. Relationships of resistance to Fusarium ear rot and Fumonisin contamination with agronomic performance of maize. Crop Sci.2007b,47:1770-1778.
    117. Rodrigo GS, Fernando HA, Elsa LC, Julio CC. Quantitative trait loci for grain moisture at harvest and field grain drying rate in maize (Zea mays L.). Theor Appl Genet.2006,112:462-471.
    118. Rong J, Feltus FA, Waghmare VN, Pierce GJ, Chee PW, Draye X, Saranga Y, Wright RJ, Wilkins TA, May OL, Smith CW, Gannaway JR, Wendel JF, Paterson AH. Meta-analysis of polyploidy cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development. Genetics.2007,176:2577-2588.
    119. Rosenberg MS, Garrett KA, Su Z, Bowden RL. Meta-analysis in plant pathology:Synthesizing research results. Phytopathology.2004,94:1013-1017.
    120. Sala RG, Andrade FH, Camadro EL, Cerono JC. Quantitative trait loci for grain moisture at harvest and field grain drying rate in maize(Zea mays, L.) Theor Appl Genet.2006,112:462-471.
    121. SAS Institute Inc. SAS/STAT user's guide. Version 9.1. SAS Institute Inc., Cary, NC.2003.
    122. Schmidt JL, Hallauer AR. Estimating harvest date of corn in the field. Crop Sci.1966,6:227-231.
    123. Stuber CW, Lincoln SE, Wolff DW, Helentjaris T, Lander ES. Identification of genetic factors contributing to heterosis in a hybrid from two elite maize inbred lines using molecular markers. Genetics.1992,132:823-839.
    124. Sutton JC. Epidemiology of wheat head blight and maize ear rot caused by Fusarium graminearum. Can J Plant Pathol.1982,4:195-209.
    125. Sweeney PM, St Martin SK, Clucas CP. Indirect inbred selection to reduce grain moisture in maize hybrids. Crop Sci.1994,34:391-396.
    126. Troyer AF, Ambrose WB. Plant characteristics affecting field drying rate of ear corn. Crop Sci. 1971,11:529-531.
    127. Troyer AF. Background of U.S.hybrid corn Ⅱ:breeding climate and food. Crop Sci.2004, 44:370-380.
    128. Troyer AF. Selection for early flowering in corn:three adapted synthetics. Crop Sci.1990,30: 896-900.
    129. Vigier B, Reid LM, Dwyer LM, Stewart DW, Sinha RC, Arnason JT, Butler G. Maize resistance to gibberella ear rot:symptoms, deoxynivalenol, and yield. Can J Plant Pathol.2001,23:99-105.
    130. Voss KA, Smith GW, Haschek WM. Fumonisins:toxicikinetics, mechanism of action and toxicity. Anim Feed Sci Tech.2007,137:299-325.
    131. Wang R. QTL mapping for resistance to Fusarium moniliforme ear rot using recombinant inbred lines in maize. Master thesis, Henan Agricultural University, Zhengzhou, Henan, China.2009.
    132. Warburton ML, Brooks TD, Windham GL, Williams WP. Identification of novel QTL contributing resistance to aflatoxin accumulation in maize. Mol Breed.2010, (in press) DOI: 10.1007/s11032-010-9446-9
    133. Wilcoxson RD, Busch RH, Ozmon EA. Fusarium head blight resistance in spring wheat cultivars. Plant Dis.1992,76:658-661.
    134. Wisser, RJ, Qi S, Hulbert, SH, Kresovich S, Nelson RJ. Identification and characterization of regions of the rice genome associated with broad-spectrum, quantitative disease resistance. Genetics.2005,167:2277-2293.
    135. Yan J B, Tang H, Huang YQ, Zheng YL, Li JS. Comparative analyses of QTL for important agronomic traits between maize and rice.Acta Genet Sin.2004,31(12):1401-1407.
    136. Zabalia O, Claurey J, Carvajal T. Resistencia a pudricion de mazorca (Fusarium moniliforme) en la poblacion Pairumani Aychasara 101. XVI Reunion de la Zona Andina y III Reunion Latinoamericana de Investigaciones de Maiz. Santa Cruz 20 a 24 noviembre:10.1995.
    137. Zhang F, Wan XQ, Pan GT. Molecular mapping of QTL for resistance to maize ear rot caused by Fusarium moniliforme. Acta Agron Sin.2007,33:491-496.
    138. Zhang Y, Kang MS, Magari R. A diallel analysis of ear moisture loss rate in maize. Crop Sci,1996, 36:1140-1144.
    139.Zuber MS, Calvert OH, Kwolek WF, Lillehoj EB, Kang MS. Aflatoxin B1 production in an eight-line diallele of Zea mays infected with Aspergillus flavus. Phytopathology.1978, 68:1346-1349.
    140. Zuber MS, Gundy LJ, Aslin WE. yield trials with corn hybrids in Missouri. Missouri Agric Exp Stn Bull.1949,533.
    141. Zuber MS. Effect of the Y-y factor pair on yield and orther agronomic characters in corn. PhD diss, lows state college ames,50-(01-0245),1950.
    142.鲍继友,孙月轩,姜先梅.夏玉米灌浆与温度、籽粒含水率的关系.耕作与栽培,1994,5:31-33.
    143.胡晋,李永平,苏菊萍等.种子水分测定的原理和方法.北京:中国农业出版社,2008.
    144.胡晋.种子生物学.北京:高等教育出版社,2006.
    145.胡延吉.植物育种学.北京:高等教育出版社,2003:21-23.
    146.黄操军,田芳明.粮食水分检测技术及发展趋势.农机化研究,2006(6):44-47.
    147.霍仕平,晏庆九.玉米生理成熟后籽粒快速脱水的意义及其研究进展.四川农业大学学报,1993,11(4):626-629.
    148.霍仕平.玉米灌浆期籽粒、脱水速率的研究进展综述.玉米科学,1993,4:39-44.
    149.金益,王振华,张永林等.玉米灌浆后期百粒重变化的品种间差异分析.东北农业大学学报,1998,29(1):7-10.
    150.金益,王振华,张永林等.玉米杂交种蜡熟后籽粒自然脱水速率差异分析.东北农业大学学报,1997,28(1):29-32.
    151.李明,李文雄.玉米产量形成与源库关系.玉米科学,2006,14(2):67-70.
    152.李淑娴,高莹莹,李运红,田树霞.种子含水量的测定方法及展望.种子,2010,29(10):57-59.
    153.李艳杰,史纪明,鞠成梅等.玉米籽粒水分与品种性状相关性研究初报.玉米科学,2000,8(4):37-38.
    154.梁文科.热带温带玉米群体育种价值评估及光周期反应敏感性指标研究.华中农业大学.2008.
    155.刘玲译.成熟期籽粒迅速失水的玉米选育问题[J].作物育种攻关参考资料,1988,4:18-20.
    156.刘显君,王振华,王霞等.玉米籽粒胜利成熟后自然脱水速率QTL的初步定位.作物学报,2010,36(1):47-52.
    157.吕新,胡昌浩,董树亭等.紧凑型玉米掖单22与SC704籽粒灌浆特性对比分析研究.山东农业大学学报(自然科学版),2005,36(1):70-74.
    158.庞增译.玉米成熟表型特征和收获期籽粒含水量的可见标志-苞叶干燥期.国外作物育种,1992,2:25-27.
    159.申琳.夏玉米籽粒灌浆与籽粒含水率的关系及籽粒发育过程的分期.北京农业科学,1998,16(5):6-9.
    160.王振华,姜艳喜,鄂文弟等.降低玉米收获期子粒含水量的育种策略.全国作物遗传育种学术研讨会论文集,2003:251-254.
    161.王振华,张忠臣,常华章等.黑龙江省38个玉米自交系生理成熟期及籽粒自然脱水速率的分析.玉米科学,2001,9(2):53-55.
    162.王忠孝,高学曾,许金芳等.关于玉米籽粒败育的研究.中国农业科学,1986(6):36-40.
    163.魏蒙关.玉米两个相关F2:3群体秸秆产量和品质性状QTL分析及遗传相关研究,河南农业大学,2009.
    164.闫淑琴,李德新.玉米籽粒脱水速度的遗传及相关分析和技术措施对脱水的影响.黑龙江农业科 学,1994(6):9-11.
    165.杨村,邹庆道,田云等.玉米籽粒水分含量的遗传研究.国外农学-杂粮作物,1998,18(2):11-14.
    166.张立国,张林,管春云等.玉米生理成熟后籽粒脱水速率与品质性状的相关分析.2007,38(5):582-585.
    167.张林,王振华,金益等.玉米收获期含水量的配合力分析.西南农业学报,2005,18(5):534-537.

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