| Autor: |
Sadiq FK; Department of Soil Science, Faculty of Agriculture, Institute for Agricultural Research, Ahmadu Bello University, P. M. B. 1044, Samaru, Zaria, Nigeria., Maniyunda LM; Department of Soil Science, Faculty of Agriculture, Institute for Agricultural Research, Ahmadu Bello University, P. M. B. 1044, Samaru, Zaria, Nigeria. lemuelmusa@gmail.com., Adegoke KA; Department of Chemical Sciences, University of Johannesburg, Doornfontein Campus, Johannesburg, South Africa. kwharyourday@gmail.com., Anumah AO; Faculty of Science and Technology, University of the Baque Country, Baque, Spain.; College STEE (Science and Technology for Energy and the Environment), University of Pau and Pays de L'Adour, Pau, France.; ICBAS - Instituto de Ciências Biomédicas Abel Salazar, University of Porto, Porto, Portugal. |
| Abstrakt: |
A few investigations have been done regarding the soil quality index (SQI) for various locations, soil types, and states. Still, little has been reported regarding SQI for both surface and control sections, especially for the Northern Guinea Savanna of Nigeria. Due to the subsurface property pedogenic influence on soil function, it is crucial to assess SQI using surface and subsurface properties as both properties influence soil productivity. We investigated the potentials of choosing a minimum data set for soil quality indicators and assess soil quality (SQ), using both surface and entire soil pedon data for the soils on the basement complexes. Both additive and weighted soil quality indices and different scoring methods (linear and non-linear) were used in evaluating SQ. Out of the twenty-three soil properties subjected to PCA, eight indicators (TEB, clay, silt, K, EA, EC, BD, and Fe) were selected as the minimum data set (MDS). There was not much difference in the calculated soil quality using the non-linear additive (SQI-NLA), linear additive (SQI-LA), linear weighted (SQI-LW), and non-linear weighted (SQI-NLW) for the soils as they were all rated low (SQI < 0.55). The estimated SQI for the control section had relatively higher values than the surface soil, thus suggesting the need to incorporate both surface and entire soil profile properties in assessing SQ as both are important in integrating the relationship between soil properties and management goals which eventually provides complete information that affects the production of crops. |
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