| 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).
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