以优良玉米自交系许178×K12杂交衍生的包含150个家系的重组自交系群体为试验材料，在正常施氮和不施氮两种条件下，对玉米子粒品质性状（蛋白质、淀粉和油分）进行表型鉴定，利用最佳线性无偏预测法结合2年的表型数据，估计各家系各性状在不同氮水平下的育种值。利用QTL IciMapping V4.0软件的完备区间作图法（ICIM）对3个性状进行QTL检测，在两种氮水平下共检测到14个品质性状相关QTL位点，其中，正常施氮条件下检测到8个QTL，不施氮条件下检测到6个QTL。2个QTL可以同时在两种氮水平下被检测到，其受环境因素影响较小，可以在玉米子粒品质分子育种上应用。在不施氮条件下共发现4个特异表达的QTL，其可能应用于低氮条件下玉米品质改良研究。

One hundred and fifty recombinant inbred lines(RILs) as the experimental materials derived from a cross between maize inbred line Xu178×K12 were used to identify maize kernel quality traits(protein, starch and oil) under the high nitrogen(HN) and low nitrogen(LN) treatment in Yangling over two years(2014 and 2015). Using the best linear unbiased prediction(BLUP) combining with the phenotype data in two years estimated breeding value of each trait under different nitrogen levels. QTL mapping for 3 traits were detected by inclusive composite interval mapping(ICIM) in QTL IciMapping V4.0 software. Totally, fourteen QTL associated with 3 kernel quality traits at the two nitrogen levels were detected, including 8 QTL under HN and 6 QTL under LN treatment. The presently study found 2 consistency QTL across two nitrogen treatments might be stable QTL controlling kernel quality trait, which were less influenced by environments and might be used in molecular breeding for kernel quality traits in maize. The results showed that four specific QTL expressions under LN treatment were possibly applied in improving quality traits in maize in low nitrogen stress.

国家自然科学基金（31301830）、西北农林科技大学基本科研业务费专项资金（QN2012001）、陕西省自然科学基础研究计划项目（2014JQ3108）