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ACTA AGRICULTURAE UNIVERSITATIS JIANGXIENSIS, Volume 41 , Issue 6 : 1227-1234(2019) https://doi.org/10.13836/j.jjau.2019143

Evaluation of Accuracy of Bootstrap-PLSR Model based on Vis-NIR Spectra in Predicting Soil Organic Matter

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  • ReceivedMay 29, 2019

Abstract


Funded by

国家自然科学基金项目(41361049)

江西省教育厅科学技术研究项目(GJJ181150)

the National Nature Science Foundation(41361049)

the Science and Technology Research Project of Jiangxi Provincial Department of Education(GJJ181150)


References

[1] 杨梅花,王芳东,赵小敏,等. 基于综合指数的吉安县耕地质量监测[J]. 江西农业大学学报,2014,36(4):911-917.. Google Scholar

[2] Vohland M,Besold J,Hill J,et al. Comparing different multivariate calibration methods for the determination of soil organic carbon pools with visible to near infrared spectroscopy[J]. Geoderma,2011,166(1):198-205.. Google Scholar

[3] Morra M J,Hall M H,Freeborn L L. Carbon and nitrogen analysis of soil fractions using near-infrared reflectance spectroscopy[J]. Soil Science Society of America Journal,1991,55:288-291.. Google Scholar

[4] Stenberg B,Viscarra Rossel R A,Mouazen A M,et al. Chapter five-visible and near infrared spectroscopy in soil science [M]. SPARKS D L. Adv Agron. Academic Press,2010:163-215.. Google Scholar

[5] Word S,Sjösröm M,Eriksson L. PLS-regression:a basic tool of chemometrics[J]. Chemometrics and Intelligent Laboratory Systems,2001,58(2):109-130.. Google Scholar

[6] Wold S. Cross-validatory estimation of the number of components in factor and principal components models[J]. Technometrics,1978,20(4):397-405.. Google Scholar

[7] Hastie T,Tibshirani R,Friedman J. The elements of statistical learning:data mining,inference,and prediction[J]. The Mathematical Intelligencer,2005,27(2),83-85.. Google Scholar

[8] Hancock T,Put R,Coomans D,et al. A performance comparison of modern statistical techniques for molecular descriptor selection and retention prediction in chromatographic QSRR studies[J]. Chemometrics and Intelligent Laboratory Systems,2005,76(2):185-196.. Google Scholar

[9] Mevik B H,Segtnan V H,Næs T. Ensemble methods and partial least squares regression[J]. Journal of Chemometrics,2004,18(11):498-507.. Google Scholar

[10] Rossel R a V. Robust modelling of soil diffuse reflectance spectra by bagging-partial least squares regression[J]. Journal of Near Infrared Spectroscopy,2007,15(1):39-47.. Google Scholar

[11] Stoner E R,Baumgardner M F. Characteristic variations in reflectance of surface soils[J]. Soil Science Society of America Journal,1981,45:1161-1165.. Google Scholar

[12] Clark R N,Roush T L. Reflectance spectroscopy:quantitative analysis techniques for remote sensing applications[J]. Journal of Geophysical Research:Solid Earth,1984,89(B7):6329-6340.. Google Scholar

[13] 杨梅花,赵小敏,王芳东,等. 基于主成分分析的最小数据集的肥力指数构建[J]. 江西农业大学学报,2016,38(6):1188-1195.. Google Scholar

[14] 李曦. 基于高光谱遥感的土壤有机质预测建模研究[D]. 杭州:浙江大学,2013.. Google Scholar

[15] Viscarra Rossel R A. ParLeS:software for chemometric analysis of spectroscopic data[J]. Chemometr IntellLab,2008,90(1):72-83.. Google Scholar

[16] 杨梅花,赵小敏,方倩,等. 基于可见-近红外光谱变量选择的土壤全氮含量估测研究[J]. 中国农业科学,2014,47(12):2374-2383.. Google Scholar

[17] Yang M,Xu D,Chen S,et al. Evaluation of machine learning approaches to predict soil organic matter and pH using vis-NIR spectra[J]. Sensors,2019,19(2):263.. Google Scholar

[18] Bellon-Maurel V,Fernandez-Ahumada E,Palagos B,et al. Critical review of chemometric indicators commonly used for assessing the quality of the prediction of soil attributes by NIR spectroscopy[J]. TRAC Trends in Analytical Chemistry,2010,29(9):1073-1081.. Google Scholar

[19] Wilding L P. Spatial variability:its documentation,accommodation and implication to soil surveys[J]. Soil Spatial Variability,1985:166-194.. Google Scholar

[20] Abdi D,Tremblay G F,Ziadi N,et al. Predicting soil phosphorous and other properties using near infrared spectroscopy[J]. 2012,76:2318-2326.. Google Scholar

[21] Leardi R,Seasholtz M B,Pell R J. Variable selection for multivariate calibration using a genetic algorithm:prediction of additive concentrations in polymer films from Fourier transform-infrared spectral data[J]. Analytica Chimica Acta,2002,461(2):189-200.. Google Scholar

[22] Almeida M R,Fidelis C H,Barata L E,et al. Classification of amazonian rosewood essential oil by Raman spectroscopy and PLS-DA with reliability estimation[J]. Talanta,2013,117:305-311.. Google Scholar