2.2.2 Soil Chemistry Analysis
The chemical attributes evaluated included pH determination, which was
measured by potentiometry (soil-water ratio 1:2.5), exchangeable acidity
(Al3+ + H+) and exchangeable
aluminium (Al3+) extracted with KCl 1N and titrated
with NaCl, and HCl respectively (McLean, 1965). Total organic carbon
(TOC) was measured using the Walkley and Black wet digestion method
(Nelson & Sommers, 1983). Available P
and extractable cations (K+, Ca2+and Mg2+) were removed using the Olsen extraction
solution. P was measured colorimetrically using the molybdenum blue
method, while K+, Ca2+ and
Mg2+ were determined using an atomic absorption
spectrophotometer (Okalebo et al., 2002).
Finally, the Leaf litter (LL) was calculated within the subplots of 10 x
10 m with the help of a 0.25 m2 quadrant; all of the
material corresponding to dead plant remains located within was
collected. The collected material was weighed and placed in bags for
drying at 105 °C for 24 hours, until a constant weight was obtained. Dry
matter in terms of kilograms of dry matter (DM) per hectare was
calculated (Mg DM ha-1).
Evaluation of the Soil Quality Index, Statistical Analysis and
Derivation of the Soil Quality Index
The evaluation of the SQI included three consecutive steps
(Masto et al., 2008;
Zhang et al., 2019): 1) the selection of
a minimum data sets (MDS); 2) scoring the MDS indicators; and 3)
calculation of integrated SQI values. To choose the best representative
indicator for MDS, principal component analysis (PCA) and Pearson’s
correlation coefficient were performed
(Doran & Parkin, 1997). In order to
select the minimum data sets (MDS), only principal components (PCs) that
had eigenvalues ≥1 and explained at least 5% of the total variance were
chosen (Andrews et al., 2003). Then in
each PC, only the factors with absolute loading values within 10 % of
the highest factor loading were selected as vital indicators
(Sharma et al., 2005;
Zhang et al., 2019). When more than one
indicator was retained in one PC, Pearson’s correlation analysis was
used to check whether other indicators should be removed
(Bastida et al., 2006). In this context,
if the indicators were adequately correlated (correlation coefficient
>0.6), with each other, only the highest weighted indicator
was selected in the PC (Andrews et al.,
2003). After selecting the indicators of MDS, a non-linear scoring
function was used to transform the soil indicators into scores that
ranged from 0 to 1. The sigmoidal function (Eq. 1) was used as follows
(Andrews et al., 2002):