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考虑到高地做为整个亚洲季风带新垦区的不断增长的重要地位,迫切需要评价高地土壤性能不同状况的方法。这些方法并且应该是数量评价和实用的。用于本系列研究的样品征集自种植农作和牧草的旱地。包括火山源土壤(主要为暗色土)和非火山源土壤(岩成土、假潜育土、酸性棕壤、红壤和黄壤等)。本文中土壤有效水持水量(AWC)是根据常规试验室资料和田间观测特性来预示的。首先,研究了全部样品的AWC在容重(BD)、腐殖质、CEC、质地(CS、FS、TS、粉粒、粘粒)这一类常规实验室资料上的多重回归。BD对AWC显示了非常之高的贡献。腐殖质、CEC和总砂量(TS)的贡献是轻微的,但它们的偏回归系数达显著水准。因此最终回归方程为: AWC=103.74-0.61~**BD-0.09~**TS-0.31~*CEC+0.57~*腐殖质其复回归系数(R)=0.91。以田间特征预测AWC时使用了林氏(Hayashi)数量化理论。这些被测定的变量是田间腐殖质等级(FOM)、田间质地(FTEXT)、结构发育(STRD)、湿结持度(MCON)、干结持度(DCON)、紧实性(CMPT)等。除此之外,容重也包括在内,这是因为其重要性和在田间很容易测定。最后证明AWC可由BD(4个等级)、FOM(3个等级)和CMPT(三个等级)来预测。为了校验上述结果的重现性,对分层次的样品做了同样的分析。回归分析和林氏数量化理论方法Ⅰ二者都给出了令人满意的结果。
Given the growing importance of the Highlands as a reclamation site for the entire Asian monsoon belt, there is an urgent need to evaluate ways of differentiating the performance of soils in the highlands. These methods should and should be quantitatively evaluated and useful. The samples used in this series of studies are collected from dry land for farming and pasture. Including volcanic source soil (mainly dark soil) and non-volcanic source soil (rock soil, pseudo-subsoil soil, acid brown earth, red soil and yellow soil, etc.). The soil available water capacity (AWC) in this paper is based on conventional laboratory data and field observations. First, the multiple regression of AWC for all samples on conventional laboratory data of bulk density (BD), humus, CEC, texture (CS, FS, TS, silt, and cosmid) was studied. BD showed a very high contribution to the AWC. The contribution of humus, CEC and total sand (TS) is minor, but their partial regression coefficients reach significant levels. Therefore, the final regression equation is as follows: AWC = 103.74-0.61 ~ ** BD-0.09 ~ ** TS-0.31 ~ * CEC + 0.57 ~ * The regression coefficient (R) of humus is 0.91. Hayashi’s quantitative theory was used to predict AWC with field characteristics. The variables tested were FOM, FTEXT, STRD, MCON, DCON, and Compactness (CMPT). In addition, bulk density is also included because of its importance and ease of determination in the field. Finally, AWC can be predicted by BD (4 levels), FOM (3 levels) and CMPT (3 levels). In order to verify the reproducibility of the above results, the same analysis was performed on the stratified samples. Regression analysis and Lin’s quantitative theory method I both give satisfactory results.