中国农业科学2009，Vol.42Issue(11)：4100-4105,6.DOI:10.3864/j.issn.0578-1752.2009.11.043
玉米果穗DUS性状测试的图像处理应用研究
Study on Application of Image Process in Ear Traits for DUS Testing in Maize
摘要
Abstract
[Objective] The objective of this study is to assess the suitability of image process techniques for measuring and quantifying ear traits in maize DUS tests. [Method] The 7 ear traits, namely ear length and width, kernel top and ear axis color, ear shape, ear row number, kernel arrangement, as ruled in The National Guidelines for Maize, were measured by image processes from 50 ears each of four cultivars or 93 up to 107 ear axes each of eight cultivars. Measurements obtained were subjected to different statistical procedures in order to determine adequate data analysis requirements, in the context that the variety evaluation of distinctness. [Result] Relative measurement errors were 6.2%, 1.6% and 0.66% respectively for ear length, ear width and ear row number by image process. Individual ear edge angles, as a trait depicting ear shape, ranged from 0 to 2.22 degrees, and mean kernel row angles, as a trait depicting kernel arrangement, varied from 89.4-90.7 degrees among cultivars. Colors and shapes of ears, which, as usual, are quality traits or pseudo-quality traits, were quantified as quantitative traits so that information gain increased. Variations in kernel top color among both ears and sides within ears were tiny, and variations in other traits among sides within ears were smaller than or comparative to among ears. The increased number of traits based on same bulk samples may lead to higher risk of false between-varieties distinctness. Nevertheless, the risk of this kind can substantially be reduced by the mean separation for individual traits with multiple traits adjustment. [Conclusion] Image process is a useful tool for gathering and quantifying maize ear DUS and other more waits with advantages of objectivity, efficiency and low cost, when integrated with adequate statistical analysis tools such as the mean separation for individual traits with multiple waits adjustment, and will play more and more important roles in the new maize variety DUS testing in the whole country.关键词
玉米/果穗性状/图像处理/DUS测试/统计分析Key words
maize/ear trait/image process/DUS testing/statistical analysis分类
农业科技引用本文复制引用
赵春明,韩仲志,杨锦忠,李娜娜,梁改梅..玉米果穗DUS性状测试的图像处理应用研究[J].中国农业科学,2009,42(11):4100-4105,6.基金项目
山东省农业重大应用技术创新项目(6207a7)、山西省归圉留学人员项目(2003049) （6207a7）
