Kondou Youichi, Manickavelu Alagu, Komatsu Kenji, Arifi Mujiburahman, Kawashima Mika, Ishii Takayoshi, Hattori Tomohiro, Iwata Hiroyoshi, Tsujimoto Hisashi, Ban Tomohiro, Matsui Minami
Department of Biosciences, Kanto Gakuin University College of Science and Engineering, 1-50-1 Mutsura-Higashi, Kanazawa-ku, Yokohama, Kanagawa 236-8501, Japan; Center for Sustainable Resource Science, RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.
Kihara Institute for Biological Research, Yokohama City University , 641-12 Maioka-cho, Totsuka-ku, Yokohama, Kanagawa 244-0813 , Japan.
Breed Sci. 2016 Dec;66(5):676-682. doi: 10.1270/jsbbs.16041. Epub 2016 Aug 23.
This study was carried out with the aim of developing the methodology to determine elemental composition in wheat and identify the best germplasm for further research. Orphan and genetically diverse Afghan wheat landraces were chosen and EDXRF was used to measure the content of some of the elements to establish elemental composition in grains of 266 landraces using 10 reference lines. Four elements, K, Mg, P, and Fe, were measured by standardizing sample preparation. The results of hierarchical cluster analysis using elemental composition data sets indicated that the Fe content has an opposite pattern to the other elements, especially that of K. By systematic analysis the best wheat germplasms for P content and Fe content were identified. In order to compare the sensitivity of EDXRF, the ICP method was also used and the similar results obtained confirmed the EDXRF methodology. The sampling method for measurement using EDXRF was optimized resulting in high-throughput profiling of elemental composition in wheat grains at low cost. Using this method, we have characterized the Afghan wheat landraces and isolated the best genotypes that have high-elemental content and have the potential to be used in crop improvement.
本研究旨在开发测定小麦元素组成的方法，并确定用于进一步研究的最佳种质。选择了珍稀且遗传多样的阿富汗小麦地方品种，使用能量色散X射线荧光光谱法（EDXRF）测量部分元素的含量，以利用10条参考线确定266个地方品种籽粒中的元素组成。通过标准化样品制备来测量钾（K）、镁（Mg）、磷（P）和铁（Fe）这四种元素。使用元素组成数据集进行的层次聚类分析结果表明，铁含量与其他元素呈现相反的模式，尤其是与钾元素。通过系统分析，确定了磷含量和铁含量方面最佳的小麦种质。为了比较EDXRF的灵敏度，还使用了电感耦合等离子体方法（ICP），获得的相似结果证实了EDXRF方法。对使用EDXRF进行测量的采样方法进行了优化，从而以低成本实现了小麦籽粒元素组成的高通量分析。利用该方法，我们对阿富汗小麦地方品种进行了表征，并分离出了具有高元素含量且有潜力用于作物改良的最佳基因型。
