Abstract
A study was conducted to examine spatial variability of soil properties related to fertility in maize fields across varying soil types in ward 10 of Hurungwe district, Zimbabwe; a smallholder farming area with sub-humid conditions and high yield potential. Purposively collected and geo-referenced soil samples were analyzed for texture, pH, soil organic carbon (OC), mineral N, bicarbonate P, and exchangeable K. Linear mixed model was used to analyze spatial variation of the data. The model allowed prediction of soil properties at unsampled sites by the empirical best linear unbiased predictor (EBLUP). Evidence for spatial dependence in the random component of the model was evaluated by calculating Akaike’s information criterion. Soil pH ranged from 4.0 to 6.9 and showed a strong spatial trend increasing from north to south, strong evidence for a difference between the home and outfields with homefields significantly higher and between soil textural classes with the sand clay loam fraction generally higher. Soil OC ranged from 0.2 to 2.02% and showed no spatial trend, but there was strong evidence for a difference between home and outfields, with mean soil OC in homefields significantly larger, and between soil textural classes, with soil OC largest in the sandy clay loams. Both soil pH and OC showed evidence for spatial dependence in the random effect, providing a basis for spatial prediction by the EBLUP, which was presented as a map. There were significant spatial trends in mineral N, available P and exchangeable K, all increasing from north to south; significant differences between homefields and outfields (larger concentrations in homefields), and differences between the soil textural classes with larger concentrations in the sandy clay loams. However, there was no evidence for spatial dependence in the random component, so no attempt was made to map these variables. These results show how management (home fields vs outfields), basic soil properties (texture) and other factors emerging as spatial trends influence key soil properties that determine soil fertility in these conditions. This implies that the best management practices may vary spatially, and that site-specific management is a desirable goal in conditions such as those which apply in Ward 10 of Hurungwe district in Zimbabwe.
Highlights
Sustainable agriculture is essential to ensure food security for the increasing population in sub-Saharan Africa (SSA) while reducing rural poverty and the degradation of natural resources [1]
Data for organic carbon, available P and exchangeable K were transformed to logarithms because octile skewness was larger than 0.2
A variable is considered weakly variable, moderately variable or strongly variable when the coefficient of variance (CV) % is less than 10%, between 10 and 100%, and above 100%, respectively
Summary
Sustainable agriculture is essential to ensure food security for the increasing population in sub-Saharan Africa (SSA) while reducing rural poverty and the degradation of natural resources [1]. The gradual decline of soil fertility in SSA soils induced by management, especially in intensively cropped areas, is a major cause of decreased yields and food production per capita [2]. This has led to undesirable mid- to long-term soil and environmental degradation [3]. It is important to understand this variation and how far it reflects the influence of long-range factors This might mean that recommendations for management should, in principle, differ between farms and between fields within farms, allowing more efficient, cost-effective, and less environmentally damaging use of agricultural inputs [9,10,11,12]. A better understanding of the variation of soil fertility could help farmers to achieve increased soil productivity and the objectives of sustainable agriculture [13,14,15]
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