Study on Soil and Pine-Seedling Zn and Mn and Predicting-Model Design

作     者：ZHANGJI－ZHEN J.G.JYER ZHANG JI-ZHEN and J. G.JYERA nhui Agricultural College, Hefei 230036 (China)Department of Soil Science, University of Wisconsin-Madison, 55706(U. S.A.)

作者机构：AnhuiAgriculturalCollegeHefei230036（China） DepartmentofScienceUniversityofWisconsin－Madison53706（U 

出 版 物：《Pedosphere》 (土壤圈（英文版）)

年 卷 期：1992年第2卷第2期

页      面：153-160页

核心收录：

学科分类：09[农学] 0903[农学-农业资源与环境] 090301[农学-土壤学] 

主　　题：manganese predicting model red-pine seedling zinc 

摘      要：Soils were collected from 2-year (2-y) and 3-year (3-y) old red-pine seedling plots in two tree nurseries, Hayward in the north and Wilson in the southwestern part of Wisconsin State respectively, and equilibrated with 0.01 M Ca(NO3)2 for soil solution Zn and Mn (solu-Zn and Mn), and with 0.01 M Ca(NO3)2+0.005 M EDTA for soil adsorbed Zn and Mn (ad-Zn and Mn). Buffering capacity of soil Zn and Mn (b-Zn and Mn) was obtained from the ratio of ad-Zn and Mn to the solu-Zn and Mn. The concerned traces in pine seedling needles (ndls), stems(sts) and roots (rts) were simultaneously measured. The results obtained show that:About 60% of solu- and ad- Zn ranged from 0.2 to 0.4 and from 1 to 2μ/g soil respectively. About 70% of b-Zn was within) *** highest content of solu-Zn compared with the lowest showed a discrepancy of more than 10-fold. The two forms of soil Zn were commonly higher in Wilson than in Hayward *** 80% of solu-, ad- and b-Mn were within 3-10, 5-5.8 μg/ g soil and 1-2 respectively. Influence of low buffering capacity on solu-Zn and Mn was about 20 times stronger than that of the *** E-value, a ratio of accumulated Zn and Mn in needles to those in the soil solution, is proved to be: E-Zn E-Mn;E-sts E-ndls or E-rts; and E-2y *** and/ or linear correlations between soil solu-, ad- and b-Zn and Mn and ndls-, sts-, rts-Zn and Mn were at very significant or significant *** predicting ndls-Zn and Mn, two realizable and simple models from two regression equations were established through the selection of related parameters and dependent variables. Binary regression analysis basically eliminated the influence of soil pH on the prediction of Zn and Mn in needles. Soil pH was thus thought to be excluded from the model.