Accumulation and concentration of nitrogen, phosphorus and potassium in Jerusalem artichoke in a semi-arid region
Jerusalem artichoke (Helianthus tuberosus L.) has been recognized as being a biomass crop for energy and livestock forage production. In this study, 26 Jerusalem artichoke clones previously collected from 24 provinces of China were grown under semiarid conditions in 2008 and 2011. At harvest, nitrogen (N), phosphorus (P) and potassium (K) concentrations and accumulations were measured for all clones and levels of both were higher overall for 2008 than 2011, with statistically reasonable results for both years. Notably, N and K concentrations in aboveground parts were higher than in tubers for most clones, yet the tuber P concentration was consistently higher than in aboveground parts. Comparing with other forage and energy plants, it demonstrates that under optimal conditions, diverse Jerusalem artichoke clones could meet the requirements of either energy production or livestock forage feed. Based on N, P and K accumulation and concentration profiles, the 26 Jerusalem artichoke clones clustered into six groups. Three clones of one cluster, CQ-1, GZ-1 and HUN-3, are recommended for use as biomass energy materials due to the lower N concentration level in aboveground parts and higher N concentration level in tubers, while 16 clones are recommended for use as forage due to the higher N concentration level in aboveground parts. The phenotypic traits described in this work should facilitate quantitative trait locus mapping and the subsequent use of clone germplasms for development of improved varieties suited to specific growth conditions and applications.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2018 Tongcheng Fu, Zuxin Liu, Yang Yang, Guang Hui Xie
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.