Xiang Wei, Li Kailong, Dong Fang, Zhang Ya, Zeng Qiang, Jiang Ling, Zhang Daowei, Huang Yanlan, Xiao Liang, Zhang Zhuo, Zhang Chaofan
Crop Research Institute, Hunan Academy of Agricultural Sciences, Changsha 410125, Hunan, PR China.
Plant Protection Institute, Hunan Academy of Agricultural Sciences, Changsha 410125, Hunan, PR China.
Breed Sci. 2023 Jun;73(3):246-260. doi: 10.1270/jsbbs.22096. Epub 2023 Jun 27.
Sweetpotato variety breeding is always a long process. Screening of hybrid offspring is dominated by empirical judgment in this process. Data analysis and decision fatigue have been troubling breeders. In recent years, the low-efficiency screening mode has been unable to meet the requirements of sweetpotato germplasm innovation. Therefore, it is necessary to construct a high-efficiency method that can screen germplasms for different usages, for mining elite genotypes, and to create dedicated sweetpotato varieties. In this article, the multicriteria decision-making (MCDM) model was constructed based on six agronomic traits, including fresh root yield, vine length, vine diameter, branch number, root number and the spatial distribution of storage roots, and five quality traits, including dry matter content, marketable root yield, uniformity of roots, starch content and the edible quality score. Among these, the edible quality score was calculated by using fuzzy comprehensive evaluation to integrate the sensory scores of color, odor, sweetness, stickiness and fibrous taste. The MCDM model was compared with the traditional screening method via an evaluation in 25 sweetpotato materials. The interference of subjective factors on the evaluation results was significantly reduced. The MCDM model is more overall, more accurate and faster than the traditional screening method in the selection of elite sweetpotato materials. It could be programmed to serve the breeders in combination with the traditional screening method.
甘薯品种选育一直是一个漫长的过程。在此过程中,杂交后代的筛选主要依靠经验判断。数据分析和决策疲劳一直困扰着育种者。近年来,低效率的筛选模式已无法满足甘薯种质创新的需求。因此,有必要构建一种高效的方法,用于筛选不同用途的种质,挖掘优良基因型,培育专用甘薯品种。本文基于鲜薯产量、蔓长、蔓粗、分枝数、根数和贮藏根空间分布这6个农艺性状以及干物质含量、商品薯产量、根的均匀度、淀粉含量和食用品质评分这5个品质性状构建了多准则决策(MCDM)模型。其中,食用品质评分通过模糊综合评价法计算得出,该方法综合了颜色、气味、甜度、粘性和纤维口感的感官评分。通过对25份甘薯材料的评价,将MCDM模型与传统筛选方法进行了比较。主观因素对评价结果的干扰显著降低。在优良甘薯材料的选择上,MCDM模型比传统筛选方法更全面、更准确、速度更快。它可以进行编程,与传统筛选方法相结合为育种者服务。