Relationships between soil colour and composition
pH KCl
mod <- lm(my_dat$ph_kcl ~ my_dat$hue + my_dat$value + my_dat$chroma)
summary(mod)
##
## Call:
## lm(formula = my_dat$ph_kcl ~ my_dat$hue + my_dat$value + my_dat$chroma)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.2390 -1.0536 -0.0992 0.9776 3.3364
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.1004 1.3313 -0.075 0.9400
## my_dat$hue5YR -0.9747 0.8105 -1.203 0.2311
## my_dat$hue7.5YR -1.1993 0.2637 -4.547 1.14e-05 ***
## my_dat$value 0.9245 0.1734 5.332 3.64e-07 ***
## my_dat$chroma 0.2790 0.1209 2.308 0.0224 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.339 on 145 degrees of freedom
## Multiple R-squared: 0.3536, Adjusted R-squared: 0.3358
## F-statistic: 19.83 on 4 and 145 DF, p-value: 4.857e-13
Conductivity
mod <- lm(my_dat$conductivity_ms ~ my_dat$hue + my_dat$value + my_dat$chroma)
summary(mod)
##
## Call:
## lm(formula = my_dat$conductivity_ms ~ my_dat$hue + my_dat$value +
## my_dat$chroma)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.804 -1.465 -0.181 1.418 7.215
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.38581 2.16573 0.178 0.859
## my_dat$hue5YR 0.27678 1.31851 0.210 0.834
## my_dat$hue7.5YR -0.09282 0.42907 -0.216 0.829
## my_dat$value 0.37531 0.28206 1.331 0.185
## my_dat$chroma 0.20767 0.19667 1.056 0.293
##
## Residual standard error: 2.178 on 145 degrees of freedom
## Multiple R-squared: 0.02147, Adjusted R-squared: -0.005528
## F-statistic: 0.7952 on 4 and 145 DF, p-value: 0.5301
Acidity
mod <- lm(my_dat$acidity ~ my_dat$hue + my_dat$value + my_dat$chroma)
summary(mod)
##
## Call:
## lm(formula = my_dat$acidity ~ my_dat$hue + my_dat$value + my_dat$chroma)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.4230 -0.5124 -0.1625 0.3168 3.7603
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.34133 0.84787 5.120 9.55e-07 ***
## my_dat$hue5YR -0.11929 0.51619 -0.231 0.8176
## my_dat$hue7.5YR 0.36467 0.16798 2.171 0.0316 *
## my_dat$value -0.54358 0.11042 -4.923 2.29e-06 ***
## my_dat$chroma -0.13877 0.07699 -1.802 0.0736 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8527 on 145 degrees of freedom
## Multiple R-squared: 0.2244, Adjusted R-squared: 0.203
## F-statistic: 10.49 on 4 and 145 DF, p-value: 1.721e-07
Ca
mod <- lm(my_dat$Ca ~ my_dat$hue + my_dat$value + my_dat$chroma)
summary(mod)
##
## Call:
## lm(formula = my_dat$Ca ~ my_dat$hue + my_dat$value + my_dat$chroma)
##
## Residuals:
## Min 1Q Median 3Q Max
## -10.638 -3.554 -1.517 0.430 44.971
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -20.8830 8.1333 -2.568 0.011253 *
## my_dat$hue5YR -5.6761 4.9516 -1.146 0.253555
## my_dat$hue7.5YR -3.1958 1.6114 -1.983 0.049224 *
## my_dat$value 3.6586 1.0593 3.454 0.000724 ***
## my_dat$chroma 1.6500 0.7386 2.234 0.027010 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.18 on 145 degrees of freedom
## Multiple R-squared: 0.1662, Adjusted R-squared: 0.1432
## F-statistic: 7.226 on 4 and 145 DF, p-value: 2.466e-05
Mg
mod <- lm(my_dat$Mg ~ my_dat$hue + my_dat$value + my_dat$chroma)
summary(mod)
##
## Call:
## lm(formula = my_dat$Mg ~ my_dat$hue + my_dat$value + my_dat$chroma)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8.4489 -3.4204 -0.6576 2.8560 12.5374
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.2896 4.4459 -1.190 0.236073
## my_dat$hue5YR -3.4307 2.7067 -1.268 0.207002
## my_dat$hue7.5YR -2.6931 0.8808 -3.058 0.002658 **
## my_dat$value 1.4786 0.5790 2.554 0.011690 *
## my_dat$chroma 1.3720 0.4037 3.398 0.000875 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4.471 on 145 degrees of freedom
## Multiple R-squared: 0.2303, Adjusted R-squared: 0.2091
## F-statistic: 10.85 on 4 and 145 DF, p-value: 1.01e-07
Na
mod <- lm(my_dat$Na ~ my_dat$hue + my_dat$value + my_dat$chroma)
summary(mod)
##
## Call:
## lm(formula = my_dat$Na ~ my_dat$hue + my_dat$value + my_dat$chroma)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2402.0 -968.8 -154.5 964.6 4419.3
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1175.83 1332.47 -0.882 0.3790
## my_dat$hue5YR 451.03 811.21 0.556 0.5791
## my_dat$hue7.5YR -38.96 263.99 -0.148 0.8829
## my_dat$value 442.06 173.54 2.547 0.0119 *
## my_dat$chroma 210.37 121.00 1.739 0.0842 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1340 on 145 degrees of freedom
## Multiple R-squared: 0.06299, Adjusted R-squared: 0.03714
## F-statistic: 2.437 on 4 and 145 DF, p-value: 0.04978
K
mod <- lm(my_dat$K ~ my_dat$hue + my_dat$value + my_dat$chroma)
summary(mod)
##
## Call:
## lm(formula = my_dat$K ~ my_dat$hue + my_dat$value + my_dat$chroma)
##
## Residuals:
## Min 1Q Median 3Q Max
## -316.31 -87.11 -34.34 68.21 770.63
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -55.87 138.22 -0.404 0.6867
## my_dat$hue5YR -140.41 84.15 -1.669 0.0974 .
## my_dat$hue7.5YR -97.52 27.38 -3.561 0.0005 ***
## my_dat$value 39.07 18.00 2.170 0.0316 *
## my_dat$chroma 22.97 12.55 1.830 0.0693 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 139 on 145 degrees of freedom
## Multiple R-squared: 0.1903, Adjusted R-squared: 0.1679
## F-statistic: 8.518 on 4 and 145 DF, p-value: 3.346e-06
P
mod <- lm(my_dat$P ~ my_dat$hue + my_dat$value + my_dat$chroma)
summary(mod)
##
## Call:
## lm(formula = my_dat$P ~ my_dat$hue + my_dat$value + my_dat$chroma)
##
## Residuals:
## Min 1Q Median 3Q Max
## -39.116 -16.080 -8.644 -0.148 207.313
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 24.594 34.862 0.705 0.482
## my_dat$hue5YR -26.968 21.224 -1.271 0.206
## my_dat$hue7.5YR -11.296 6.907 -1.635 0.104
## my_dat$value 2.043 4.540 0.450 0.653
## my_dat$chroma 1.283 3.166 0.405 0.686
##
## Residual standard error: 35.06 on 145 degrees of freedom
## Multiple R-squared: 0.03712, Adjusted R-squared: 0.01056
## F-statistic: 1.397 on 4 and 145 DF, p-value: 0.2378
Olsen
mod <- lm(my_dat$Olsen ~ my_dat$hue + my_dat$value + my_dat$chroma)
summary(mod)
##
## Call:
## lm(formula = my_dat$Olsen ~ my_dat$hue + my_dat$value + my_dat$chroma)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.8743 -1.8308 -0.4051 1.4803 10.1257
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 21.1955 2.5966 8.163 1.45e-13 ***
## my_dat$hue5YR -4.9161 1.5808 -3.110 0.002254 **
## my_dat$hue7.5YR -1.8480 0.5144 -3.592 0.000448 ***
## my_dat$value -2.0217 0.3382 -5.978 1.67e-08 ***
## my_dat$chroma -0.7057 0.2358 -2.993 0.003250 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.611 on 145 degrees of freedom
## Multiple R-squared: 0.2383, Adjusted R-squared: 0.2173
## F-statistic: 11.34 on 4 and 145 DF, p-value: 4.925e-08