QTL underlying field grain drying rate after physiological maturity in maize (Zea Mays L.)

Wang, Zhenhua; Wang, Xia; Lin, Zhang; Liu, Xianjun; Di, Hong; Li, Tingfeng; Xiao-chun, Jin

doi:10.1007/s10681-012-0676-2

Cited by 27 publications

(20 citation statements)

References 22 publications

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“…According to the comparative analysis with our study results, preliminary mapping results of qFkdr2b and qFkdr2d detected in our study were consistent with QTLs found by both Stuber et al (1992) and Sala et al (2006). The mapping results of qFkdr3a and qFkdr3c detected in our study also agreed with the QTLs found in previous studies (Ho et al, 2002;Capelle et al, 2010;Wang et al, 2012;Xiang et al, 2012).…”

Section: Introductionsupporting

confidence: 93%

Detection of QTLs controlling fast kernel dehydration in maize (Zea mays L.)

et al. 2016

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ABSTRACT. In order to understand the effect of grain moisture of inbred lines at the silking and physiological maturity stages on kernel 2 Y.L. Qian et al. Genetics and Molecular Research 15 (3): gmr.15038151 dehydration rate, 59 maize inbred lines from six subgroups were selected. Grain moisture was measured and QTLs associated with kernel dehydration were mapped. A rapid dehydration evaluation and association analysis revealed eight inbred lines with faster dehydration rate, including Yuanwu 02, K36, Zhonger/O2, Lo1125, Han 49, Qi 319, Hua 160, and PH4CV. A single sequence repeat analysis using 85 pairs detected five QTLs with phenotypic variation contribution ≥10% in the permanent F2 generation populations Zheng 58 x S1776 and Chang 7-2 x K1131, which had LOD threshold values ≥ 3 in both 2013 and 2014. The chromosome region of qFkdr7b had not previously been reported and is preliminarily identified as a new major QTL. A false positive field verification of grain dehydration rate of 53 inbred lines indicated that the screening result of the rapid dehydration inbred lines by specific amplification with marker Phi114 was most similar to the field assessment result, followed by markers Phi127 and Phi029. The rapid dehydration lines selected based on primer Phi114 amplification were also similar to the field dehydration rate and can thus be used for molecular marker-assisted selection. A significant effort is needed to improve stress resistance and shorten the growth period via fast kernel dehydration in intermediate materials of the inbred lines K36, Zhonger/ O2, Lo1125, Han 49, Hua 160, and PH4CV, and further using the selected lines for new combinations.

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Section: Introductionsupporting

confidence: 93%

Detection of QTLs controlling fast kernel dehydration in maize (Zea mays L.)

et al. 2016

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“…All these methods are effective, but require precise calibration. The classical oven-drying method, although laborious and time-consuming, is the most reliable way to obtain accurate GWC value [8,26,42,45,57,58]. Considering that the mapping of a small-effect QTL requires extremely accurate GWC values, we finally chose an improved ovendrying method.…”

Section: Discussionmentioning

confidence: 99%

“…In a similar work with 280 RILs, 14 GDR QTL were identified after PM, and each could explain 5.05-16.28% of the total GDR variation. Two of them, qKdr-2-1 and qKdr-3-6, were consistently detected across both locations [45]. With 330 F 2:3 families, 10 GWC at 45 DAP QTL, 10 GWC at harvest QTL and 10 AUDDC (area under the dry down curve) QTL were detected.…”

Section: Introductionmentioning

confidence: 88%

“…Histogram of the frequency distribution and probability density curve of GWC values for the RILs in the three field trials. A-B, GWC values for the first and second samplings at 45 The GDR values on the x axis denote the boundary values for defining the GDR groups. The y axis on the left denotes the numbers of RILs related to the GDR groups.…”

Section: Supplementary Informationmentioning

confidence: 99%

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Genetic dissection of grain water content and dehydration rate related to mechanical harvest in maize

Liu

et al. 2020

BMC Plant Biol

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Background: The low grain water content (GWC) at harvest is a prerequisite to mechanical harvesting in maize, or otherwise would cause massive broken kernels and increase drying costs. The GWC at harvest in turn depends on GWC at the physiological maturity (PM) stage and grain dehydration rate (GDR). Both GWC and GDR are very complex traits, governed by multiple quantitative trait loci (QTL) and easily influenced by environmental conditions. So far, a number of experiments have been conducted to reveal numbers of GWC and GDR QTL, however, very few QTL have been confirmed, and no QTL has been fine-mapped or even been cloned. Results: We demonstrated that GWCs after PM were positively correlated with GWC at PM, whereas negatively with GDRs after PM. With a recombinant inbred line (RIL) population, we identified totally 31 QTL related to GWC and 17 QTL related to GDR in three field trials. Seven GWC QTL were consistently detected in at least two of the three field trials, each of which could explain 6.92-24.78% of the total GWC variation. Similarly, one GDR QTL was consistently detected, accounting for 9.44-14.46% of the total GDR variation. Three major GWC QTL were found to overlap with three GDR QTL in bins 1.05/06, 2.06/07, and 3.05, respectively. One of the consistent GWC QTL, namely qGwc1.1, was fine-mapped from a 27.22 Mb to a 2.05 Mb region by using recombinant-derived progeny test. The qGwc1.1 acted in a semi-dominant manner to reduce GWC by 1.49-3.31%. Conclusions: A number of consistent GWC and GDR QTL have been identified, and one of them, QTL-qGwc1.1, was successfully refined into a 2.05 Mb region. Hence, it is realistic to clone the genes underlying the GWC and GDR QTL and to make use of them in breeding of maize varieties with low GWC at harvest.

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“…It is commonly determined only in pre commercial and commercial hybrids, aimed at guiding technicians along with producers. This phenotypic attribute is dependent on the genetic constitution of the genotypes, both during and after physiological maturity, revealing the importance of genetic factors (Wang et al, 2012). However, the selection of elite lines for earliness and yield in breeding hybrids for tropical regions is hampered by the complexity of these traits and negative correlation (Hallauer et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Genetic diversity of maize lines for traits related to maturity and yield components

Friske¹,

Schuelter²,

Schuster³

et al. 2018

Aust J Crop Sci

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Grain yield and maturity class are among the commercial traits that most often direct maize breeding that aims to meet the requirements of the seed market. Thus, the aim of this study was to evaluate genetic diversity in maize inbred lines for grain maturity and yield components. The phenotypic attributes of 81 maize inbred lines were assessed in a field experiment in a square lattice design with three replications. Analysis of variance and multivariate analysis were performed considering complete randomized blocks due to the equivalence to the estimation for lattice efficiency. The results of analysis of variance indicated genetic diversity in the germplasm for all the traits, showing high variability for number of days to male flowering (DMF) and female flowering (DFF). Genetic diversity was also detected for grain water loss, which was determined by the area under the water loss curve (AUWLC), an index representing the dynamic progress of field water loss, based on area under the disease progress curve (AUDPC). The high magnitude of genetic correlation between the AUWLC and the moisture content of grain (0.98) collected at different moments in the R6 stage suggests the possibility of its substitution by the moisture content evaluation in only one collection. Weak genetic correlations (0.07 to 0.45) between yield and maturity components indicated the possibility of selection for earliness without compromising yield. In addition, the results of the Tocher method and the UPGMA were compatible, enabling classification of the germplasm and suggestion of hybrid combinations among inbreds that might have a higher heterotic effect on yield associated with earliness.

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QTL underlying field grain drying rate after physiological maturity in maize (Zea Mays L.)

Cited by 27 publications

References 22 publications

Detection of QTLs controlling fast kernel dehydration in maize (Zea mays L.)

Detection of QTLs controlling fast kernel dehydration in maize (Zea mays L.)

Genetic dissection of grain water content and dehydration rate related to mechanical harvest in maize

Genetic diversity of maize lines for traits related to maturity and yield components

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