干旱区生态环境知识资源中心(Arid): Prediction of soil organic matter using an inexpensive colour sensor in arid and semiarid areas of Iran

Arid

DOI	10.1071/SR18323
	Prediction of soil organic matter using an inexpensive colour sensor in arid and semiarid areas of Iran
	Raeesi, Maryam 1; Zolfaghari, Ali Asghar 1; Yazdani, Mohammad Reza 1; Gorji, Manouchehr 2; Sabetizade, Marmar 2
通讯作者	Zolfaghari, Ali Asghar
来源期刊	SOIL RESEARCH
ISSN	1838-675X
EISSN	1838-6768
出版年	2019
卷号	57 期号:3 页码:276-286
英文摘要	Soil organic matter (SOM) plays a major role in agricultural and ecological processes. For this reason, accurate quantification of SOM is important for precision agriculture and environmental management. Inexpensive sensor technology could be a potential approach to achieving the accurate prediction of SOM. The objective of this study was to evaluate inexpensive colour sensor (Nix Pro) data for prediction of SOM in arid and semiarid areas of Iran. A total number of 85 and 152 soil samples from the soil surface (0-20 cm) were collected from the Semnan (arid area) and Qazvin (semiarid area) regions respectively. The nonlinear random forest (RF) method and linear regression were conducted to predict SOM using Nix(TM) pro colour sensor data. The partial least-squares approach was also utilised to reduce the dimensions of the dataset, decrease the number of input variables and avoid multi-collinearity. Soil colour was measured in moist and dry conditions. Root mean square error (RMSE), correlation coefficient (r), r-square (R-2), mean square prediction error (MSPE) and ratio of performance to interquartile distance (RPIQ) were used to assess the RF and the linear regression models for prediction of SOM. Moist sample data was used for estimation of the SOM because of the larger correlation between SOM and colour sensor data in moist than dry samples. In estimation of SOM, the RF model represented lower dispersion between the estimated and the actual values of SOM (RMSE = 0.42, 0.43, RPIQ = 2.2, 2.06 and MSPE = 0.19, 0.19 in semiarid and arid regions respectively). In contrast, more dispersion was obtained by applying the linear regression model (RMSE = 0.61 and 0.51, RPIQ = 1.47 and 1.76, and MSPE = 0.39 and 0.26 in semiarid and arid regions respectively). The RPIQ values for linear regression in arid and semiarid areas were 1.76 and 1.47 respectively. Hence, the use of a linear regression model for prediction of SOM in arid areas would result in acceptable reliability; however, its utilisation should be avoided in semiarid areas due to less reliable results.
英文关键词	Inexpensive colour sensor nonlinear models soil organic matter
类型	Article
语种	英语
国家	Iran
收录类别	SCI-E
WOS记录号	WOS:000463909500008
WOS关键词	CARBON ; NITROGEN ; INFILTRATION ; VARIABILITY ; ATTRIBUTES ; PHOSPHORUS ; PARAMETERS ; VARIABLES ; FIELD
WOS类目	Soil Science
WOS研究方向	Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/218880
作者单位	1.Semnan Univ, Fac Desert Sci, Semnan, Iran; 2.Univ Tehran, Soil Sci Dept, Tehran, Iran
推荐引用方式 GB/T 7714	Raeesi, Maryam,Zolfaghari, Ali Asghar,Yazdani, Mohammad Reza,et al. Prediction of soil organic matter using an inexpensive colour sensor in arid and semiarid areas of Iran[J],2019,57(3):276-286.
APA	Raeesi, Maryam,Zolfaghari, Ali Asghar,Yazdani, Mohammad Reza,Gorji, Manouchehr,&Sabetizade, Marmar.(2019).Prediction of soil organic matter using an inexpensive colour sensor in arid and semiarid areas of Iran.SOIL RESEARCH,57(3),276-286.
MLA	Raeesi, Maryam,et al."Prediction of soil organic matter using an inexpensive colour sensor in arid and semiarid areas of Iran".SOIL RESEARCH 57.3(2019):276-286.