Browsing by Author "Ngejane, Nompumelelo"

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    Soil spectral characteristics and their predictive value in relation to spatial and temporal variability in wheat yield and soil quality within a long-term field trial
    (Stellenbosch : Stellenbosch University, 2019-12) Ngejane, Nompumelelo; Rozanov, Andrei Borisovich; Clarke, Catherine E.; Stellenbosch University. Faculty of Agrisciences. Dept. of Soil Science.
    ENGLISH ABSTRACT: Soil is a heterogeneous growing medium, with complex processes and mechanisms that are not easy to be fully understood. Soil spatial variations may be encountered within short distances, and these variations, directly and indirectly, affect plant production and crop yields. The field of agriculture is facing an escalating demand of databases from a regional to a worldwide scale that will help agriculturists understand and be able to mitigate the impact of spatial variations in the field (soils and crops). However, to make such data available is expensive and involves tedious and labor-intensive methods. Rapid and cost-effective tools to measure variations in soil properties and crop yields for large areas are required. Soil spectroscopy appears to be a fast, nondestructive, cost-effective, environmental-friendly, reproducible, and repeatable analytical technique. The study aims at evaluating the use of soil spectroscopy in predicting common selected soil properties and wheat yield, as well as exploring its potential in explaining the spatial variations in the field, both in soil properties and in wheat yield. The experiment was conducted as a long-term ongoing trial at the Langgewens research farm, Western Cape Department of Agriculture. The trial was laid out in an incomplete block design structure, across a 12 ha area made up of three cropping systems with varying degrees of crop diversity and four replicates allocated in 120 plots. Archived soil samples (for the year 2015) from all the 120 plots were used for the analysis of selected common soil properties and scanned to acquire the near-infrared (NIR) spectral signatures using a spectrophotometer (Bruker Multi-Purpose Analyzer). The NIR spectral signatures were pre-processed following two procedures that are de-noising (removal of the fringe bands with large noise) and data transformation (first derivative and straight-line subtraction) before performing the multivariate data analyses. The partial least squares regression (PLSR) method was used to develop chemometric models to establish the relationship that the NIR spectral signatures have with wheat yield and soil properties. The prediction results of the PLSR models were fairly accurate and falling within the acceptable ranges. For the selected models, most correlation coefficients (R2) ranged between 0.80 and 0.60 with the ratios of performance to deviation (RPD) ranging between 2.38 to 1.6 for wheat yield and selected soil properties (CEC, SOC, pH, Ca). In 2019, the soil core samples at 0-5 cm depth (120 in total) were analyzed for some key soil parameters and were scanned to acquire the NIR spectral signatures. This was done to assess the temporal variations in wheat yield and changes in 5 cm soil spectral characteristics in the field trial area after four years (2015 to 2019). An overall significant difference was obtained between the averaged spectral absorbance for the years 2015 and 2019 (p<0.05), an increase in absorbance for the year 2019 was observed. When assessing the changes that have occurred in some selected soil properties, bulk density was observed to have significantly decreased across the field (p<0.05). A decrease in soil organic carbon (p<0.05) was observed as well as in soil organic carbon stocks (p<0.05) within a fixed depth. However, no significant change was observed in soil carbon stocks when the depth was adjusted. Results obtained in this study show that to a certain extent, the spectral characteristics in the NIR region might be a good indicator of not only soil properties but also plant responses to the changes in soil properties across the field.