| Type: | Package |
| Title: | Soil Quality Index |
| Version: | 0.1.0 |
| Author: | 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 <owaisaliwani@skuastkashmir.ac.in> |
| 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>. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.2.1 |
| Imports: | readxl, dplyr, stats, matrixStats, olsrr, FactoMineR |
| LazyData: | true |
| Depends: | R (≥ 3.5.0) |
| NeedsCompilation: | no |
| Packaged: | 2023-04-07 17:49:07 UTC; YEASIN |
| Repository: | CRAN |
| Date/Publication: | 2023-04-10 14:20:03 UTC |
This is data to be included in my package
Description
This is data to be included in my package
Usage
data(Data)
Format
A data frame with 60 rows and 12 column
Soil Quality Index Based on Regression
Description
Soil Quality Index Based on Regression
Usage
PCAIndex(DataFrame, OptimumValue)
Arguments
DataFrame |
Data set with first column as factors |
OptimumValue |
Optimum value of each variable; Minimum and maximum coded as "1111" and "9999" respectively. |
Value
PCAIndex: Final index
References
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.
Examples
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
Description
Soil Quality Index Based on Regression
Usage
RegIndex(DataFrame, Dep_col, OptimumValue)
Arguments
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. |
Value
RegIndex: Final index
References
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.
Examples
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
Description
Soil Quality Index Based on Linear Scoring
Usage
ScoingIndex(DataFrame, OptimumValue)
Arguments
DataFrame |
Data set with first column as factors |
OptimumValue |
Optimum value of each variable; Minimum and maximum coded as "1111" and "9999" respectively. |
Value
Raw_mean: Raw score
Index: Final index
References
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.
Examples
library("SQI")
OP<-c(7,1111,9999,9999,9999,9999,9999,9999,9999,9999,1111)
ScoreIndex<-ScoingIndex(DataFrame = Data,OptimumValue = OP)