Quantitative Determination of Hydrolytic Nitrogen Content in Soil by Near Infrared Spectroscopy Combined with Competitive Adaptive Reweighted Sampling Variable Selection Algorithm
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Quantitative Determination of Hydrolytic Nitrogen Content in Soil by Near Infrared Spectroscopy Combined with Competitive Adaptive Reweighted Sampling Variable Selection Algorithm
Vol. 39, Issue 10, Pages: 1305-1310(2020)
作者机构:
1. 四川威斯派克科技有限公司
2. 云南省烟草公司昆明市公司
3. 中国烟草总公司云南省公司
4. 昆明市烟草公司嵩明分公司
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Quantitative Determination of Hydrolytic Nitrogen Content in Soil by Near Infrared Spectroscopy Combined with Competitive Adaptive Reweighted Sampling Variable Selection Algorithm. [J]. 39(10):1305-1310(2020)
DOI:
Quantitative Determination of Hydrolytic Nitrogen Content in Soil by Near Infrared Spectroscopy Combined with Competitive Adaptive Reweighted Sampling Variable Selection Algorithm. [J]. 39(10):1305-1310(2020)DOI:
Quantitative Determination of Hydrolytic Nitrogen Content in Soil by Near Infrared Spectroscopy Combined with Competitive Adaptive Reweighted Sampling Variable Selection Algorithm
为了能够快速准确地掌握整个昆明地区土壤水解性氮含量的情况,收集963个不同类型的土壤样品,采用竞争自适应重加权采样(Competitive adaptive reweighted sampling,CARS)变量选择方法筛选波长变量,并建立水解性氮的偏最小二乘法(Partial least squares,PLS)分析模型。结果表明,采用CARS方法优选波长变量后,模型参数有所改善,交互验证标准偏差(Root mean square error of cross validation,RMSECV)由31.63降至25.55,交互验证相关系数(Correlation coefficientof cross validation,Rcv)由078提升至0.84,且模型外部验证结果与内部交叉验证结果基本一致。研究结果表明近红外光谱技术结合CARS分法,在大量代表性样品建模下,能够有效建立昆明地区不同土壤类型的水解性氮含量的近红外数学模型,方法可推广应用于土壤其他组分的近红外检测,具有重要的指导意义。
Abstract
In order to quickly and accurately grasp the hydrolytic nitrogen content of soil in the whole Kunming area,963 soil samples of different types were collected.Partial least squares(PLS) combined with competitive adaptive reweighted sampling(CARS) method used to screen the spectral wavelength variables was adopted to establish an analysis model for hydrolytic nitrogen.Results showed that the parameters for the model were improved after the optimization of wavelength variables by CARS,and the root mean square error of cross validation(RMSECV) was reduced from 31.63 to 25.55,the correlation coefficient of cross validation(Rcv) was increased from 0.78 to 0.84,and the external verification results of the model were basically consistent with the internal cross verification results.Meanwhile,near infrared spectroscopy combined with CARS method could be used to effectively establish a near infrared(NIR) mathematical model for hydrolytic nitrogen content in different soil types in Kunming area under the modeling of a large number of representative samples,which is suitable for the NIR detection of other components in soil and has an important guiding significance.
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