Repository logo

Masters Degrees (Soil Science)

Permanent URI for this collectionhttps://hdl.handle.net/10413/6646

Browse

Browsing Masters Degrees (Soil Science) by Author "Dube, Nkosinomusa Nomfundo."

Filter results by typing the first few letters
Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Characterisation of potato waste biochars and effect on carbon dioxide emission, liming potential and availability of primary macro-nutrients of two amended contrasting soils.
    (2021) Vilakazi, Samukelisiwe Pinky.; Muchaonyerwa, Pardon.; Dube, Nkosinomusa Nomfundo.
    Abstract available in pdf.
  • Thumbnail Image
    Item
    Farm typology and spatial variability of selected soil fertility parameters on selected small-holder farms in KwaZulu-Natal province, South Africa.
    (2022) Manqana, Lonwabo.; Dube, Nkosinomusa Nomfundo.; Muchaonyerwa, Pardon.
    Diversity of resource endowment, soil and climatic conditions may affect the level of management and productivity and soil fertility in small-holder farms. The objectives of this study were to (i) develop farm typologies, (ii) assess fertility gradients, and (iii) map spatial variability of soil fertility in small-holder farms of uMbumbulu and Msinga regions in KwaZulu-Natal province, South Africa. To obtain data for the identification of farm typologies, a detailed open-ended questionnaire was used with topics including socio-economic attributes, local crops grown, soil amendments, management practices, labour, crop residue management, farmers perceptions and production constraints. The questionnaire was administered to fifty farmers per region. The data which had Kaiser-Meyer-Olkin (KMO) measure values of 0.67 and 0.51 for uMbumbulu and Msinga respectively, qualified for Principal component analysis (PCA). Three PCs which had significant eigenvalues of >1, provided key factors that determine the farm typologies, namely land size, livestock ownership, income from farming and external income. Multiple correspondence analysis (MCA) and cluster analysis were used to analyse quantitative and qualitative data, and variables and aggregate farms into clusters according to production, socioeconomics, and demographics. Three farm topologies were identified, namely (i) resource-endowed farms which have large land and profit from farming (type I), (ii) the middle-resourced group (type II), which is neither poor nor rich, and (iii) Poor resource groups (type III) with limited to no resources at all and have small land holdings and minimum profits from farming. For fertility gradients and mapping, soils were sampled from 0 – 20 cm depth, using a sampling interval of 5×5m and analysed for fertility parameters. There were no fertility gradients observed between homefields and outfields for both sites. Mapping was done only in uMbumbulu site with descriptive statistics (mean, standard deviation, covariance, skewness, and kurtosis) tested for normality to be used for kriging, and only the spherical model was tested in this study using R-Studio. For geo-statistics (Lag size, sill, and nugget) for semiviriograms produced was done using ArcMap-GIS as well as the maps. For type I farms the spatial dependency was strong (< 25%) for most variables tested (pH, total carbon, calcium, magnesium, potassium, and Clay %), while type III had a variety of spatial dependency from pH and clay % were weak (<75%), Ca and total carbon moderate (25-75%) to phosphorus, magnesium, potassium, and acid saturation strong (<25%). Overall implications of these maps can be very useful in targeting specific areas of poor or rich fertility and fertiliser recommendation, which is more economically viable to small-holder farmers to put in what is needed.
  • Thumbnail Image
    Item
    Quality parameters of organic amendments from Umbumbulu and Msinga farms and their effects on nitrogen and phosphorus mineralization.
    (2022) Hlatshwayo, Khethukuthula Pacia.; Dube, Nkosinomusa Nomfundo.; Muchaonyerwa, Pardon.
    Conventional agricultural management practices that farmers in Africa and South Africa have practiced have led to a decline in soil fertility. Organic amendments have shown to improve soil quality and fertility status when incorporated into the soil. Smallholder farmers manage their fields differently according to resource endowment, distance of fields from the homestead (i.e homefield and outfield), and labour. The use of organic inputs as fertilizers to remediate the soils from which the loss of nutrients occurred depends on their decomposition rates and nutrient release patterns. Factors such as soil type, climate and application rates of the amendments affect the decomposition and mineralization of these amendments in soils. The objective of this study was to determine (i) carbon and phosphorus pools from different fields from uMbumbulu and Msinga as affected by farmer typology and (ii) the characteristics of organic amendments and their decomposition and mineralization of nitrogen and phosphorus in soil. Three typologies (i.e. resource constrained, moderately resourced and resource endowed) were selected for both Msinga and Mbumbulu. Two fields per typology were used, namely homefield (<100m from homestead) and outfield (>150m from home) for Msinga while for uMbumbulu it was fields with mixed cropping and monocropping system. Three farms were selected per typology and field type with three replications. Soil samples were collected from the farms of different typologies at 0 – 20cm and analyzed for soil organic carbon (SOC) and phosphorus pools. Organic amendments including cattle manure, goat manure, accelerator and maize residues were sampled from different farms in Msinga and uMbumbulu and characterized. Composite samples of these amendments, separately and in combination, were then incorporated in soils and incubated for 84 days during which soil pH, P and mineral-N (ammonium-N and nitrate-N) were analyzed. Farmer typologies did not affect carbon and phosphorus pools of the soils on farms at Msinga and uMbumbulu. Carbon pools under different cropping systems and typologies for uMbumbulu showed significant difference with total carbon concentrations being the highest under monocropping system (40.3 g/kg) followed by c- POMC, f-POMC, MAOC and DOC and also under resource constrained typology, total carbon was the highest (44.6 g/kg). Carbon pools under Msinga did not follow the same trend both under cropping system and typology since there was no significant difference. More P was in a reductant P form in uMbumbulu soil both under different cropping systems and typology with concentration of 224-310 mg/kg under cropping system and 145-447 mg/kg within typology. Available P had lower concentrations in both cropping system (8.9-11.8 mg/kg) and typology (9.6-11.7 mg/kg) with Al-P and Fe-P showing no significant difference in uMbumbulu soil. Msinga soils followed the same trend of P pools showing no significant different in Al-P and Fe-P as uMbumbulu. Msinga soils showed more positive correlation between carbon and phosphorus pools than uMbumbulu soils. Msinga amendments appeared more beneficial than uMbumbulu with high pH levels and cattle manure having low C/N ratio content which allows rapid decomposition. More nutrients were available for plant uptake as Msinga amendments had higher concentrations of bases. The Accelerator had higher ammonium-N concentration (128 g/kg N on day 84) than other treatments showing higher decomposition rate in the uMbumbulu soil. When the manures were combined with maize residues, they had lower ammonium-N concentration due to C:N ratio of the maize residues. After day 7 of incubation, nitrate-N and mineral-N concentration increased in all treatment in both mg/kg soil and g/kg of N present. Like in the first incubation experiment (uMbumbulu soil), the control in the Msinga soil had higher nitrate-N than all treatment combinations containing maize residues between 14 to 56 days of incubation except for the accelerator+maize residues. Maize residues in both experiments (uMbumbulu and Msinga soils) showed lower mineralization of N and P and Msinga amendments had higher nutrient mineralisation than those from uMbumbulu. The findings of the study imply that carbon and phosphorus pools in the two study sites could be affected by environment factors more than management practices and that maize residues will require a longer period of time to allow maximum decomposition and mineralize nutrients compared to the accelerator, cattle, and goat manure. More studies need to be done on environmental factors such as climate, parent material, and topography, as they might be the primary drivers of carbon and phosphorus pools.