Organic carbon prediction in soil cores using VNIR and MIR techniques in an alpine landscape

Abstract Diffuse reflectance spectroscopy (DRS), including visible and near-infrared (VNIR) and mid-infrared (MIR) radiation, is a rapid, accurate and cost-effective technique for estimating soil organic carbon (SOC). We examined 24 soil cores (0–100 cm) from the Sygera Mountains on the Qinghai–Tibe...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Xiaolin Jia, Songchao Chen, Yuanyuan Yang, Lianqing Zhou, Wu Yu, Zhou Shi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9d703bc8bff04b7d8579bbd69fd583bf
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:9d703bc8bff04b7d8579bbd69fd583bf
record_format	dspace
spelling	oai:doaj.org-article:9d703bc8bff04b7d8579bbd69fd583bf2021-12-02T11:53:13ZOrganic carbon prediction in soil cores using VNIR and MIR techniques in an alpine landscape10.1038/s41598-017-02061-z2045-2322https://doaj.org/article/9d703bc8bff04b7d8579bbd69fd583bf2017-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-02061-zhttps://doaj.org/toc/2045-2322Abstract Diffuse reflectance spectroscopy (DRS), including visible and near-infrared (VNIR) and mid-infrared (MIR) radiation, is a rapid, accurate and cost-effective technique for estimating soil organic carbon (SOC). We examined 24 soil cores (0–100 cm) from the Sygera Mountains on the Qinghai–Tibet Plateau, considering field-moist intact VNIR, air-dried ground VNIR and air-dried ground MIR spectra at 5-cm intervals. Preprocessed spectra were used to predict the SOC in the soil cores using partial least squares regression (PLSR) and a support vector machine (SVM). The SVM models performed better with three predictors, with the ratio of performance to inter-quartile distance (RPIQ) and R 2 values typically exceeding 1.74 and 0.73, respectively. The SVM using the DRS technique indicated accurate predictive results of SOC in each core. The RPIQ values of the shrub meadow, forest and total dataset prediction using air-dried ground VNIR were 1.97, 2.68 and 1.99, respectively; the values using field-moist intact VNIR were 1.95, 2.07 and 1.76 and those using air-dried ground MIR were 1.78, 1.96 and 1.74, respectively. We conclude that the DRS technique is an efficient and rapid method for SOC prediction and has the potential for dynamic monitoring of SOC stock density on the Qinghai–Tibet Plateau.Xiaolin JiaSongchao ChenYuanyuan YangLianqing ZhouWu YuZhou ShiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-9 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiaolin Jia Songchao Chen Yuanyuan Yang Lianqing Zhou Wu Yu Zhou Shi Organic carbon prediction in soil cores using VNIR and MIR techniques in an alpine landscape
description	Abstract Diffuse reflectance spectroscopy (DRS), including visible and near-infrared (VNIR) and mid-infrared (MIR) radiation, is a rapid, accurate and cost-effective technique for estimating soil organic carbon (SOC). We examined 24 soil cores (0–100 cm) from the Sygera Mountains on the Qinghai–Tibet Plateau, considering field-moist intact VNIR, air-dried ground VNIR and air-dried ground MIR spectra at 5-cm intervals. Preprocessed spectra were used to predict the SOC in the soil cores using partial least squares regression (PLSR) and a support vector machine (SVM). The SVM models performed better with three predictors, with the ratio of performance to inter-quartile distance (RPIQ) and R 2 values typically exceeding 1.74 and 0.73, respectively. The SVM using the DRS technique indicated accurate predictive results of SOC in each core. The RPIQ values of the shrub meadow, forest and total dataset prediction using air-dried ground VNIR were 1.97, 2.68 and 1.99, respectively; the values using field-moist intact VNIR were 1.95, 2.07 and 1.76 and those using air-dried ground MIR were 1.78, 1.96 and 1.74, respectively. We conclude that the DRS technique is an efficient and rapid method for SOC prediction and has the potential for dynamic monitoring of SOC stock density on the Qinghai–Tibet Plateau.
format	article
author	Xiaolin Jia Songchao Chen Yuanyuan Yang Lianqing Zhou Wu Yu Zhou Shi
author_facet	Xiaolin Jia Songchao Chen Yuanyuan Yang Lianqing Zhou Wu Yu Zhou Shi
author_sort	Xiaolin Jia
title	Organic carbon prediction in soil cores using VNIR and MIR techniques in an alpine landscape
title_short	Organic carbon prediction in soil cores using VNIR and MIR techniques in an alpine landscape
title_full	Organic carbon prediction in soil cores using VNIR and MIR techniques in an alpine landscape
title_fullStr	Organic carbon prediction in soil cores using VNIR and MIR techniques in an alpine landscape
title_full_unstemmed	Organic carbon prediction in soil cores using VNIR and MIR techniques in an alpine landscape
title_sort	organic carbon prediction in soil cores using vnir and mir techniques in an alpine landscape
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/9d703bc8bff04b7d8579bbd69fd583bf
work_keys_str_mv	AT xiaolinjia organiccarbonpredictioninsoilcoresusingvnirandmirtechniquesinanalpinelandscape AT songchaochen organiccarbonpredictioninsoilcoresusingvnirandmirtechniquesinanalpinelandscape AT yuanyuanyang organiccarbonpredictioninsoilcoresusingvnirandmirtechniquesinanalpinelandscape AT lianqingzhou organiccarbonpredictioninsoilcoresusingvnirandmirtechniquesinanalpinelandscape AT wuyu organiccarbonpredictioninsoilcoresusingvnirandmirtechniquesinanalpinelandscape AT zhoushi organiccarbonpredictioninsoilcoresusingvnirandmirtechniquesinanalpinelandscape
_version_	1718394882152726528

Organic carbon prediction in soil cores using VNIR and MIR techniques in an alpine landscape

Ejemplares similares