Welcome to Chinese Agricultural Science Bulletin,

Chinese Agricultural Science Bulletin ›› 2022, Vol. 38 ›› Issue (24): 28-37.doi: 10.11924/j.issn.1000-6850.casb2021-0850

Special Issue: 生物技术 资源与环境 马铃薯 园艺

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Potted Conservation Substrates of Sweet Potato Germplasms: Screening and Evaluation

YAO Xiaojian(), ZHANG Xiongjian, YAO Zhufang, LUO Zhongxia, WANG Zhangying, HUANG Lifei, FANG Boping, YANG Yiling()   

  1. Crops Research Institute, Guangdong Academy of Agricultural Sciences/Guangdong Provincial Key Laboratory of Crop Genetic Improvement, Guangzhou 510640
  • Received:2021-09-02 Revised:2021-12-05 Online:2022-08-25 Published:2022-08-22
  • Contact: YANG Yiling E-mail:yaoxiaojian@gdaas.cn;yangyiling@gdaas.cn

Abstract:

To screen and optimize soil substrate for potted conservation of sweet potato germplasm resources in the National Germplasm Guangzhou Sweet Potato Nursery, field soil, sand and peat substrate were selected as materials for seven different soil substrates preparation in this study. The soil substrates were evaluated and screened by measuring the growth indexes of different sweet potato varieties. The growth indexes, including fresh weight of the aboveground parts, the yield of sweet potato tubers and so on, were analyzed by subordinate function, variation coefficient and principal component analysis methods. The results showed that under substrate 5 (composed of 50% field soil, 20% sand and 30% peat soil), the subordinate function value of variation coefficient and the principal component comprehensive evaluation value of the growth indexes of different sweet potato resources were the highest, which were 8.1639 and 0.8725 respectively. It indicated that substrate 5 could keep the vitality and reflect the characteristics of different sweet potato germplasm resources most. Taken together, substrate 5 is recommended to be an appropriate soil substrate for potted conservation of sweet potato germplasm resources.

Key words: sweetpotato, germplasm, potted conservation, substrate composition, subordinate function analysis, variation coefficient analysis, principal component analysis.

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