| Title: | Soil Quality Index |
|---|---|
| Description: | The overall performance of soil ecosystem services and productivity greatly relies on soil health, making it a crucial indicator. The evaluation of soil physical, chemical, and biological parameters is necessary to determine the overall soil quality index. In our package, three commonly used methods, including linear scoring, regression-based, and principal component-based soil quality indexing, are employed to calculate the soil quality index. This package has been developed using concept of Bastida et al. (2008) and Doran and Parkin (1994) <doi:10.1016/j.geoderma.2008.08.007> <doi:10.2136/sssaspecpub35.c1>. |
| Authors: | Dr. Owais Ali Wani [aut, cre], Dr. Faaique Nazir [aut], Dr. Syed Sheraz Mahdi [aut], Dr. Shabir Bangroo [aut], Dr. A Raouf Malik [aut], Dr. Shahnawaz Rasool Dar [aut], Dr. Md Yeasin [aut] |
| Maintainer: | Dr. Owais Ali Wani <[email protected]> |
| License: | GPL-3 |
| Version: | 0.1.0 |
| Built: | 2025-02-09 04:00:38 UTC |
| Source: | https://github.com/cran/SQI |
This is data to be included in my package
data(Data)data(Data)
A data frame with 60 rows and 12 column
Soil Quality Index Based on Regression
PCAIndex(DataFrame, OptimumValue)PCAIndex(DataFrame, OptimumValue)
DataFrame |
Data set with first column as factors |
OptimumValue |
Optimum value of each variable; Minimum and maximum coded as "1111" and "9999" respectively. |
PCAIndex: Final index
Bastida, F., Zsolnay, A., Hernández, T., & García, C. (2008). Past, present and future of soil quality indices: a biological perspective. Geoderma, 147(3-4), 159-171.
Doran, J. W., & Parkin, T. B. (1994). Defining and assessing soil quality. Defining soil quality for a sustainable environment, 35, 1-21.
Mukherjee, A., & Lal, R. (2014). Comparison of soil quality index using three methods. PloS one, 9(8), e105981.
library("SQI") OP<-c(7,1111,9999,9999,9999,9999,9999,9999,9999,9999,1111) PIndex<-PCAIndex(DataFrame = Data,OptimumValue = OP)library("SQI") OP<-c(7,1111,9999,9999,9999,9999,9999,9999,9999,9999,1111) PIndex<-PCAIndex(DataFrame = Data,OptimumValue = OP)
Soil Quality Index Based on Regression
RegIndex(DataFrame, Dep_col, OptimumValue)RegIndex(DataFrame, Dep_col, OptimumValue)
DataFrame |
Data set with first column as factors |
Dep_col |
Dependent variable column number |
OptimumValue |
Optimum value of each variable; Minimum and maximum coded as "1111" and "9999" respectively. |
RegIndex: Final index
Bastida, F., Zsolnay, A., Hernández, T., & García, C. (2008). Past, present and future of soil quality indices: a biological perspective. Geoderma, 147(3-4), 159-171.
Doran, J. W., & Parkin, T. B. (1994). Defining and assessing soil quality. Defining soil quality for a sustainable environment, 35, 1-21.
Mukherjee, A., & Lal, R. (2014). Comparison of soil quality index using three methods. PloS one, 9(8), e105981.
library("SQI") OP<-c(7,1111,9999,9999,9999,9999,9999,9999,9999,9999,1111) RIndex<-RegIndex(DataFrame = Data,Dep_col=7,OptimumValue = OP)library("SQI") OP<-c(7,1111,9999,9999,9999,9999,9999,9999,9999,9999,1111) RIndex<-RegIndex(DataFrame = Data,Dep_col=7,OptimumValue = OP)
Soil Quality Index Based on Linear Scoring
ScoingIndex(DataFrame, OptimumValue)ScoingIndex(DataFrame, OptimumValue)
DataFrame |
Data set with first column as factors |
OptimumValue |
Optimum value of each variable; Minimum and maximum coded as "1111" and "9999" respectively. |
Raw_mean: Raw score
Index: Final index
Bastida, F., Zsolnay, A., Hernández, T., & García, C. (2008). Past, present and future of soil quality indices: a biological perspective. Geoderma, 147(3-4), 159-171.
Doran, J. W., & Parkin, T. B. (1994). Defining and assessing soil quality. Defining soil quality for a sustainable environment, 35, 1-21.
Mukherjee, A., & Lal, R. (2014). Comparison of soil quality index using three methods. PloS one, 9(8), e105981.
library("SQI") OP<-c(7,1111,9999,9999,9999,9999,9999,9999,9999,9999,1111) ScoreIndex<-ScoingIndex(DataFrame = Data,OptimumValue = OP)library("SQI") OP<-c(7,1111,9999,9999,9999,9999,9999,9999,9999,9999,1111) ScoreIndex<-ScoingIndex(DataFrame = Data,OptimumValue = OP)