The Different Pollination Combinations in Castean henryi Determined by Auto Discrete Analyzers and Atomic Absorption Spectrometry
ZOU Feng, ZHANG Xu-hui, YUAN De-yi*, ZHU Zhou-jun, TAN Lu-man, LIU Dong-ming
Key Laboratory of Cultivation and Protection for Non-Wood Forest Trees of Ministry of Education, Key Laboratory of Non-Wood Forest Product of State Forestry Administration, Central South University of Forestry and Technology, Changsha 410004，China
Abstract：To elucidate the xenia effects of mineral elements on different pollination combinations in Castanea henryi, using the chinquapin cultivars “Huali No.1”, “Huali No.2”, “Huali No.3” and “Huangzhen” as materials, we investigated the xenia effects of mineral elements in C. henryi by auto dicsrete analyzers and atomic absorption spectrometry. Twenty combinations of self-, cross-, and natural pollination were undertaken. The results revealed that eight mineral elements of Castanea henryi seeds were significant differences. Xenia obviously has its mineral elements, especially iron and znic. The fruit of “Huali No.2”דHuangzhen” showed the highest iron and zinc content, which were 162.13 and 41.79 μg·g-1, respectively. The fruit of “Huangzhen”דHuali No.1” showed an increased manganese content of 165.67 μg·g-1, which provides a reference for the utilization of this variety as a manganese fertilizer.Through principal component analysis, the best combination was “Huali No.2”דHuangzhen” in the 19 combinations. The results can give a basis for planting design of varieties and improving fruit quality in C. henryi.
Key words：Auto discrete analyzers; Atomic absorption spectrometry; Castean henryi; Xenia; Mineral elements; Principal component analysis
邹 锋，张旭辉，袁德义，朱周俊，谭露曼，刘冬明. 自动化学间断分析仪和原子吸收光谱法测定锥栗不同授粉组合果实的元素含量[J]. 光谱学与光谱分析, 2019, 39(01): 286-291.
ZOU Feng, ZHANG Xu-hui, YUAN De-yi, ZHU Zhou-jun, TAN Lu-man, LIU Dong-ming. The Different Pollination Combinations in Castean henryi Determined by Auto Discrete Analyzers and Atomic Absorption Spectrometry. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(01): 286-291.
