VIS-NIR光谱法在克罗地亚红地中海土壤有机碳预测中的应用

Q3 Agricultural and Biological Sciences Eurasian Journal of Soil Science Pub Date : 2017-09-25 DOI:10.18393/EJSS.319208
B. Miloš, A. Bensa
{"title":"VIS-NIR光谱法在克罗地亚红地中海土壤有机碳预测中的应用","authors":"B. Miloš, A. Bensa","doi":"10.18393/EJSS.319208","DOIUrl":null,"url":null,"abstract":"Received : 09.03.2017 Accepted : 24.05.2017 The objectives of this research were: (i) to assess the accuracy of diffuse reflectance spectroscopy (DRS) in predicting the soil organic carbon (SOC) content, and (ii) determine the importance of wavelength ranges and specific wavelengths in the SOC prediction model. The reflectance spectra of a total of 424 topsoils (0-25 cm) samples were measured in a laboratory using a portable Terra Spec 4 Hi-Res Mineral Spectrometer with a wavelength range 350-2500 nm. Partial least squares regression (PLSR) with leave-one-out cross validation was used to develop calibration models for SOC prediction. The accuracy of the estimate determined by the coefficient of determination (R2), the concordance correlation coefficient (ρc), the ratio of performance to deviation (RPD), the range error ratio (RER) and the root mean square error (RMSE) values of 0.83, 0.90, 2.22, 14.2 and 2.47 g C kg-1 respectively, indicated good model for SOC prediction. The near infrared (NIR) and the short-wave infrared (SWIR) spectrums were more accurate than those in the visible (VIS) and short-wave near-infrared (SWNIR) spectral regions. The wavelengths contributing most to the prediction of SOC were at: 1925, 1915, 2170, 2315, 1875, 2260, 1910, 2380, 435, 1960, 2200, 1050, 1420, 1425 and 500 nm. This study has shown that VIS-NIR reflectance spectroscopy can be used as a rapid method for determining organic carbon content in the Red Mediterranean soils that can be sufficient for a rough screening.","PeriodicalId":36945,"journal":{"name":"Eurasian Journal of Soil Science","volume":"6 1","pages":"365-373"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Prediction of soil organic carbon using VIS-NIR spectroscopy: Application to Red Mediterranean soils from Croatia\",\"authors\":\"B. Miloš, A. Bensa\",\"doi\":\"10.18393/EJSS.319208\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Received : 09.03.2017 Accepted : 24.05.2017 The objectives of this research were: (i) to assess the accuracy of diffuse reflectance spectroscopy (DRS) in predicting the soil organic carbon (SOC) content, and (ii) determine the importance of wavelength ranges and specific wavelengths in the SOC prediction model. The reflectance spectra of a total of 424 topsoils (0-25 cm) samples were measured in a laboratory using a portable Terra Spec 4 Hi-Res Mineral Spectrometer with a wavelength range 350-2500 nm. Partial least squares regression (PLSR) with leave-one-out cross validation was used to develop calibration models for SOC prediction. The accuracy of the estimate determined by the coefficient of determination (R2), the concordance correlation coefficient (ρc), the ratio of performance to deviation (RPD), the range error ratio (RER) and the root mean square error (RMSE) values of 0.83, 0.90, 2.22, 14.2 and 2.47 g C kg-1 respectively, indicated good model for SOC prediction. The near infrared (NIR) and the short-wave infrared (SWIR) spectrums were more accurate than those in the visible (VIS) and short-wave near-infrared (SWNIR) spectral regions. The wavelengths contributing most to the prediction of SOC were at: 1925, 1915, 2170, 2315, 1875, 2260, 1910, 2380, 435, 1960, 2200, 1050, 1420, 1425 and 500 nm. This study has shown that VIS-NIR reflectance spectroscopy can be used as a rapid method for determining organic carbon content in the Red Mediterranean soils that can be sufficient for a rough screening.\",\"PeriodicalId\":36945,\"journal\":{\"name\":\"Eurasian Journal of Soil Science\",\"volume\":\"6 1\",\"pages\":\"365-373\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Eurasian Journal of Soil Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18393/EJSS.319208\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eurasian Journal of Soil Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18393/EJSS.319208","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 17

摘要

本研究的目的是:(i)评估漫反射光谱(DRS)预测土壤有机碳(SOC)含量的准确性,(ii)确定波长范围和特定波长在SOC预测模型中的重要性。利用便携式Terra Spec 4高分辨率矿物光谱仪在实验室测量了424个表层土壤(0 ~ 25 cm)样品的反射光谱,波长范围为350 ~ 2500 nm。采用偏最小二乘回归(PLSR)和留一交叉验证建立了SOC预测的校准模型。决定系数(R2)、一致性相关系数(ρc)、性能与偏差比(RPD)、极差误差率(RER)和均方根误差(RMSE)分别为0.83、0.90、2.22、14.2和2.47 g C kg-1,表明该模型具有良好的SOC预测效果。近红外(NIR)和短波红外(SWIR)光谱比可见光(VIS)和短波近红外(SWNIR)光谱更精确。对SOC预测贡献最大的波长为:1925、1915、2170、2315、1875、2260、1910、2380、435、1960、2200、1050、1420、1425和500 nm。该研究表明,VIS-NIR反射光谱可以作为一种快速测定地中海红色土壤中有机碳含量的方法,足以进行粗略筛选。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Prediction of soil organic carbon using VIS-NIR spectroscopy: Application to Red Mediterranean soils from Croatia
Received : 09.03.2017 Accepted : 24.05.2017 The objectives of this research were: (i) to assess the accuracy of diffuse reflectance spectroscopy (DRS) in predicting the soil organic carbon (SOC) content, and (ii) determine the importance of wavelength ranges and specific wavelengths in the SOC prediction model. The reflectance spectra of a total of 424 topsoils (0-25 cm) samples were measured in a laboratory using a portable Terra Spec 4 Hi-Res Mineral Spectrometer with a wavelength range 350-2500 nm. Partial least squares regression (PLSR) with leave-one-out cross validation was used to develop calibration models for SOC prediction. The accuracy of the estimate determined by the coefficient of determination (R2), the concordance correlation coefficient (ρc), the ratio of performance to deviation (RPD), the range error ratio (RER) and the root mean square error (RMSE) values of 0.83, 0.90, 2.22, 14.2 and 2.47 g C kg-1 respectively, indicated good model for SOC prediction. The near infrared (NIR) and the short-wave infrared (SWIR) spectrums were more accurate than those in the visible (VIS) and short-wave near-infrared (SWNIR) spectral regions. The wavelengths contributing most to the prediction of SOC were at: 1925, 1915, 2170, 2315, 1875, 2260, 1910, 2380, 435, 1960, 2200, 1050, 1420, 1425 and 500 nm. This study has shown that VIS-NIR reflectance spectroscopy can be used as a rapid method for determining organic carbon content in the Red Mediterranean soils that can be sufficient for a rough screening.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Eurasian Journal of Soil Science
Eurasian Journal of Soil Science Environmental Science-Environmental Science (miscellaneous)
CiteScore
2.00
自引率
0.00%
发文量
40
审稿时长
16 weeks
期刊最新文献
Impact of varied NPK fertilizer application rates and seed quantities on barley yield and soil nutrient availability in chestnut soil of Azerbaijan Comprehensive assessment and information database on saline and waterlogged soils in Kazakhstan: Insights from Remote Sensing Technology Prediction of some selected soil properties using the Hungarian Mid-infrared spectral library Assessment of ecological state of Rostov zoo soil Carbon sequestration potential of community forests: A comparative analysis of soil organic carbon stock in community managed forests of Far-Western Nepal
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1