Comparison of visual and laboratory methods of soil quality assessment in Mubuku Irrigation Scheme, Kaseese, Uganda
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The knowledge on soil quality and its assessment is of great importance to farmers and other land users as it’s a way of identifying issues affecting the soil and those hindering it from performing its functions thereby reducing its productivity. Soil information obtained through soil quality assessment is prerequisite to understanding the soil quality of an area and it can also be used to understand the spatial variation of soil properties. Unfortunately, this spatial soil information is often missing and management decisions have to be based on guesswork since farmers cannot carry out routine laboratory analysis of their soils due to the high expenses and difficulties involved in addition to the time needed. There’s therefore need for more reliable, easier and cheaper alternative methods for obtaining soil information like the Visual Soil Assessment (VSA) method. However, there are limited studies that compare these two methods. The objectives of this study were (i) to assess the spatial variability of soil properties in division one of Mubuku irrigation scheme and (ii) to assess the soil quality of division one using the laboratory analysis and the visual soil quality assessment methods. Soil samples were collected at depths of 0-15 cm and 15-30 cm using the random sampling method from georefenced points where VSA was also done. Laboratory analyses for soil texture, soil pH, organic matter (OM), nitrogen (N), Av. Phosphorus (P), potassium (K) and sodium (Na) were done. Soil quality indices (SQI) for both the VSA and laboratory analysis were calculated and compared using a paired t-test and their spatial maps were generated. Spatial maps for soil pH, OM, N, P and K were also generated. The results revealed that there was spatial variability within OM, N, P, K and Na due to the high coefficients of variation (CV) that were calculated and there was no variability in pH with a CV of 3.1%. Low variability was seen in the percentages of sand, silt and clay. The results as well showed that there was a significant difference (p = 0.024) between the laboratory soil quality indices and a moderate positive correlation of 47.9%. The spatial maps also clearly showed the differences between the two soil quality indices. In conclusion, VSA cannot fully replace the laboratory analysis as depicted in the findings of the research. However, due to the small differences in the SQI means and close relationships reported in similar studies, the VSA provides a reliable and semi quantitative soil assessment. Therefore the two methods can be integrated where funds allow, but where they are limiting, VSA is a potential alternative.