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基于激光衍射的土壤粒径测定法的评价与校正
引用本文:王伟鹏,刘建立,张佳宝,李晓鹏.基于激光衍射的土壤粒径测定法的评价与校正[J].农业工程学报,2014,30(22):163-169.
作者姓名:王伟鹏  刘建立  张佳宝  李晓鹏
作者单位:1. 中国科学院南京土壤研究所,南京 210008; 中国科学院大学,北京 100049
2. 中国科学院南京土壤研究所,南京,210008
基金项目:国家自然科学基金项目(40871105);中国科学院知识创新工程重大项目(KSCX1-YW-09-05)
摘    要:为比较与评价激光法与吸管法测定土壤粒径分布的准确性,该文采用激光法与吸管法测定了23组来自中国13个不同省份或自治区土壤样本的粒径分布,将激光法与传统吸管法的测定结果进行比较,并在此基础上对激光法测定参数进行了修正。结果表明:1)与吸管法相比,激光衍射法低估土壤样品中的黏粒含量,其相对误差为36.33%;高估粉粒含量,其相对误差为36.51%;2)对吸管法与激光衍射法的实测结果进行线性关系分析表明,其中黏粒与粉粒的线性关系较好,决定系数分别为0.91,0.90;3)经过模型转换后,基于激光衍射法的土壤粒径分布结果的相对误差明显降低:黏、粉的相对误差分别降低至16.25%、12.83%,说明激光衍射法可以用于大规模不同类型的土壤粒径分析。该研究可为土壤系统化和规范化的对比研究以及建立基于激光衍射技术的土壤质地划分标准提供依据。

关 键 词:土壤  粒径  激光  激光衍射法  吸管法  土壤吸收系数  土壤折射系数  土壤粒径分布
收稿时间:2014/4/16 0:00:00
修稿时间:2014/11/3 0:00:00

Evaluation and correction of measurement using diffraction method for soil particle size distribution
Wang Weipeng,Liu Jianli,Zhang Jiabao and Li Xiaopeng.Evaluation and correction of measurement using diffraction method for soil particle size distribution[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(22):163-169.
Authors:Wang Weipeng  Liu Jianli  Zhang Jiabao and Li Xiaopeng
Institution:1. Institute of Soil Science, Chinese Academy of Science, Nanjing 210008, China; 2. University of Chinese Academy of Sciences, Beijing 100049, China;;1. Institute of Soil Science, Chinese Academy of Science, Nanjing 210008, China;;1. Institute of Soil Science, Chinese Academy of Science, Nanjing 210008, China;;1. Institute of Soil Science, Chinese Academy of Science, Nanjing 210008, China;
Abstract:Abstract: Particle size distribution (PSD) is one of the most fundamental physical properties of the soil, which provides researchers the key basics for the spatial variability of digital soil mapping. Earlier, the soil PSD was mostly derived from the classical sieve-pipette method (SPM). However, the process of SPM analysis is tedious and time-consuming especially for the fine-textured soils. Based on the laser diffraction technique, laser diffraction method (LDM) provides an effective method to determine soil PSD, and its popularity increases for soil researches involving a large number of samples. However, results from the LDM and traditional SPM are different. The present study is aimed to assess the suitability of LDM as a routine method for determining soil PSD, and establish a simplified protocol for transforming the LDM results into traditional SPM ones. The soil samples (a total number of 23) from 13 Chinese provinces or autonomous region were analyzed and the results indicated that: 1) Compared to the SPM in the condition of limited sample numbers and large between-sample variation, LDM underestimate of clay content in soil samples, and overestimate of silt content in soil samples, the relative errors for clay and silt fractions were 36.33% and 36.51% respectively; 2) a linear relationship was established for the measured results of SPM and LDM, the detemination coefficients were 0.91, 0.90 and 0.79; through model transformation, the relative error of the LDM measured results decreased to 16.25% (for clay content), 12.83% (for silt content); 3) upon using the Mie theory to determine the soil PSD, the results of the present study also indicated that the precision could be improved and the discrepancies between the PSD obtained from the SPM and LDM could be decreased with slight modifications in SRI values; A soil particle refractive index (SRI) of 1.50 and soil particle absorption index (SAI) of 0.01 were found to be optimal for the Mie theory model. With relatively limited sample numbers and apparent textural difference between the samples, the distinct incompatibilities were observed in the present work between the PSD obtained by the LDM and SPM. However, depending on the specific research purpose, the deviations between the LDM and SPM may be considerably reduced with the increase of sample capacity or decrease of the spatial scale. This study has contributed to the development of the systematization and standardization for soil comparison. Also, it can help to establish the criteria of soil texture classification based on LDM results.
Keywords:soils  particle size  lasers  laser diffraction method (LDM)  sieve-pipette method (SPM)  soil particles' refractive index (SRI)  soil particles' absorption index (SAI)  particle size distribution (PSD)
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