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Conference Proceedings This Community features the proceedings of conferences hosted by the KNUST or other bodies but had staff from KNUST attending and making presentationsJournal of Science and Technology (JUST) Research Articles from the members of KNUST submitted to the JUSTKumasi Center for Collaborative Research (KCCR) Research Articles Speeches A collection of speeches delivered by the Vice Chancellors and Official visitors to the KNUST
Recent Submissions
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Impact of climate change and land use/land cover change on soil fertility in the cotton Basins of Côte d’Ivoire
(KNUST, 2023-07) Kone, Ismail
The study assessed the impact of alterations in land use and land cover, as well as fluctuations in climate patterns, on soil fertility within the cotton-producing area of Côte d'Ivoire. The study entails evaluating how farmers perceive and cope with climate change, determining the current state of soil fertility, evaluating land suitability and management options for cotton production, and simulating the way the land in the region will be utilized and the vegetation that will cover it in the future. To evaluate smallholder farmers' perceptions of climate change adaptation options, a structured questionnaire with closed questions was used to collect data from 355 farmers located in the cotton basin of Côte d'Ivoire. The findings revealed that most respondents acknowledged the existence of climate change in the area and its detrimental impact on farmers' livelihoods, leading them to adopt coping mechanisms. To determine the status of soil fertility, the study analyzed 64 soil samples collected in 2013 and 2021 in the same fields where cotton was grown. Specifically, the analysis focused on the physical and chemical properties of the topsoil layer, ranging from 0 to 20 centimeters in depth. Between 2013 and 2021, the chemical properties of the soil (concentrations of Ca2+, Mg2+, K+, and Base Saturation (BS)) saw only a slight improvement, leaving soil fertility as a significant constraint on cotton production. Targeted, site-specific soil management is necessary to address this issue. The study evaluated soil suitability for cotton cultivation in eight villages in the Côte d'Ivoire cotton basin by characterizing two representative soil profiles (0-100 cm) per village which were described in terms of their soil chemical and physical properties. The soils were "moderately suitable" (S2) or "marginally suitable" (S3) due to poor chemical properties, such as the Sum of Basic Cations (SBC) and organic carbon (OC). The study also used Landsat images to track changes in land use and land cover (LULC) between 1998 and 2020 and predicted future LULC for 2035 and 2063 using the TerrSet software and the CA-Markov chain. From 1998 to 2020, there was a reduction in the share of forestland and Savannah with each zone decreased by -11.09 % and -21.56 % respectively at Korhogo, -14.09 % and -1.78 % respectively at Ferkessedougou, -0.33 %, and -14.8 % respectively at Boundiali, and -6.9 % and -31.33 % respectively at Mankono, while water body, cropland, and settlement/bare land increased. From 1998 to 2035, the results revealed that the share of cropland and, settlement/bare land within the department continue to increase in the study area by 4.54 % and 28.2 %, respectively at Korhogo, 5.34 %, and 10.45 % at Ferkessedougou, 14.95 %, and 0.01 % at Boundiali, and 1.12 %, and 37.04 % in the zone at Mankono. From 1998 to 2063, the results revealed that the share of cropland and, settlement/bear with the department's land could continue to increase. The findings of this study could aid in improving and optimizing soil management practices within the cotton-producing region of Côte d'Ivoire.
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Crops-Livestock Integration as a Resilience Strategy to Climate Change in Burkina Faso
(2023-07) Sanou, Charles Lamoussa
This study titled addressed a topical issue of climate change and its impacts on
farmers' livelihoods and the role that an integrated crop-livestock system can play in
building resilient farmers and agricultural systems. The research first of all analysed
historical climate (rainfall, minimum and maximum temperature) trends across three
climatic zones Sudan (Dano), Sudan-Sahel (Niou) and Sahel (Dori)) at annual,
seasonal and decadal scales. Climates indices computation was done using the
package ClimPACT2 GUI in R software. Annual and seasonal climate were
compared using the independent t-test. Decadal climate indices were subjected to a
Principal Component Analysis (PCA). The research also analysed the susceptibility
or sensibility of crop production and livestock health to climate change. Thirdly, the
research developed and/or updated measurement tool known as Crop-Livestock
Integration (CLI) indicators for a holistic characterisation of integrated croplivestock
system. These indicators were developed based on the information from
589 farmers’ households and secondary data. Above ground, data were collected
from 4,733 trees over a total land area of 243.2 ha (80.1 ha, 78.8 ha and 84.3 ha in
Sudan, Sudan-Sahel and Sahel zones, respectively). Due to the Sahel zone's
insecurity, soil data could be collected only within Sudan and Sudan-Sahel zones. In
total, 120 composite soil samples were collected for this purpose and 240 other
samples for soil bulk density determination. Results revealed changes in climate
conditions, more pronounced in temperature variations than in rainfall. In the
Sudan-Sahel and Sahel zones, a re-wetting trends was observed over the last decade
supporting the re-greening hypothesis of the Sahel. Despite some positive effects of
the climate indices, crop failure was the major impact of climate pejoration across
iv
zones. Similarly, livestock health was majorly negatively affected by climate
deterioration though the resurgence of diseases due to climate change. Climate
indices could explain 23.0 - 50.2 % of the variations in crop yield and an increased
cases of livestock diseases occurrence by 1-9.4 units due to the deterioration in
climate conditions across climatic zones. Changes in climatic conditions may also
induce microbial proliferation and host susceptibility to result in the emergence,
redistribution, and changes in the incidence and intensity of pest infestations. The
study concluded that crop-livestock integration is underperforming in Burkina Faso
and can be improved. Majority farmers (91.6 %) in the Sudan-Sahel zone are
practising full crop-livestock integration, unlike the Sahel (62.3%) and Sudan
(48.2%) zones. However, only 14.8%, 10.5% and 5.1 % showed the effectiveness of
integration in the Sudan-Sahel, Sahel and Sudan zones, respectively. CLI was
comparatively more effective in Sudan-Sahel (65.9±32.0 %) than Sahel (44.9±29.5
%) and Sudan zones (35.6±35.0 %). Integration indicators were significantly
associated with farm emissions, productivity, biodiversity and soils nutrients. CLI is
also a tree-based system with high sequestration potential that could significantly
counterbalance the whole system emissions. However, the coverage of fodder needs
is negatively associated with soils nutrients content indicating field nutrient mining if
an appropriate scheme of nutrient return to the soils as manure is not set. An
adequate combination of CLI components offers an opportunity to build resilient
farming systems in Burkina Faso to adapt to the changing climate.
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Adoption and Effects of Climate Change Adaptation, and Land Use Decision of Smallholders Farmers in the Saline Area of Sine-Saloum, Fimela Senegal
(2023-07) Thiam, Habibatou Ibrahima
Soil salinity expansion is one of the most severe land degradation issues confronting farmers in Senegal, particularly in coastal areas such as Fimela.
With sea level rise, temperature rise, and rainfall decrease, soil salinity is increasing significantly. It has a negative impact on crop yields and farmers' livelihoods. Farmers developed land use adaptation strategies to deal with soil salinity. Nonetheless, despite adaptations, some farmers continue to complain about the negative impact of soil salinity on their outcomes. Then, this study investigates farmers' adaptation, the different factors that influence it, its implications for smallholder farmers' livelihoods, and farmers' perception of soil salinity and its impact. Data from face-to-face interviews of 288 households using the Krejci and Morgan’s formula and GPS coordinates of households and each of their farms was collected. An agent-based model was used to understand land use adaptation to soil salinity expansion by considering farmers' perceptions of soil salinity expansion under climate change for simulation. A sub-model of household decisions, crop yield, and perception of soil salinity was developed and incorporated into the model. Three scenarios were considered to simulate the interaction between household agents and landscape agents over 25 years. Farmers' adoption is influenced by their assets and sociopsychological factors like threat assessment, coping assessment, and subjective norms. Farmers in Fimela do not have maladaptation thinking that may break their willingness to adopt strategies to cope with soil salinity. The ESR model shows that farmers' adoption of strategies to cope with soil salinity has a positive impact on groundnut yields and a negative influence on food security but has no significant effect on their millet yields. These findings have been validated by the simulation results, which show that the yield difference between farmers who perceive soil salinity expansion and those who do not is significant for groundnut but not millet over 25 years. As a result, it is critical to base policies in combating soil salinity effects on providing better methods of soil salinity adaptation strategies through scientific research. Policies should support a few pilot farmers in these precise and effective strategies to trigger other farmers to follow through the village and social influence by the farmer-to-farmer approach to enable farmers access and appropriation of these new methods.
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Zearalenone-contaminated cereals in African communities, probabilistic Exposures and adverse-health Outcomes: a meta-analysis
(Journal of Science and Technology, 2024) Quartey, N.K.A.; Ofosu, I. W.; Ankar-Brewoo, G. M.; Lutterodt, H. E.; Ellis, W. O.; 0000-0003-1671-5185
Zearalenone, a Fusarium spp. mycotoxin is an exposome with estrogenic properties that adversely impact global public health concerns, including African cereal-growing communities. In this study, we used the keywords; “adverse health”, “cereals”, “zearalenone”, and “Africa” to screen published articles from Google Scholar, CrossRef, PubMed and Scopus databases. The returned queries were filtered to obtain 36 relevant articles covering 53 studies. Data including the year of study, zearalenone concentration, number of total samples and total positive samples were extracted from the included papers. The zearalenone concentrations were meta-analyzed to characterize the following: data heterogeneity, weighted averages, effect sizes, and to visualize Forest plots and regression models. The exposures were determined using zearalenone concentrations, mass of cereals ingested, and WHO-recommended body weight according to the EFSA-recommended guidelines. Based on Palisade @Risk probabilistic approaches, the uncertainties of exposures and risks (hazard quotient) were obtained after simulation at 105 iterations and benchmarked against PMTDI (0.25 µg/kg). The meta-analysis results presented a zearalenone contamination occurrence of 16% and a high heterogeneity (I2 =97.9), which indicated high variability in the included articles. Zearalenone concentrations ranging from 0.90 to 1.03×103 µg/kg presented high occurrence in rice and rice-based products (75%), while the simulated modal exposures (μg/kg(bw)-d) ranged from 5.33×10-3 to 9.70×10-2, the 95th percentile ranged from 1.91 to 31.60. Although the modal exposures among the age-related consumers did not exceed the regulatory threshold (0.25 µg/kg), that for infants (0.10 μg/kg(bw)-d) and toddlers (0.04 μg/kg(bw)-d) were the highest. However, the 95th percentile exposures for all the age-related consumers exceeded the threshold at different intensities, while the infants (31.60 μg/kg(bw)-d) and toddlers (13.11 μg/kg(bw)-d) exposures were significantly (HQ>1) alarming. Control measures are urgently warranted to address this public health concern.
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Testing the pecking order theory of banks listed on the ghana stock exchange
(KNUST, 2021) SEY EUNICE
The research examined the pecking order theory practice of banks listed on the Ghana Stock Exchange. The link between leverage and firm specific characteristics such as profitability, loan quality, growth, age and size of firms was ascertained. The research used quantitative approaches and employed the descriptive designs. Secondary data from the annual financial statements of banks listed on the Ghana Stock Exchange from the year 2010 to 2019 were used for the studies. As at the end of the year 2019, eight (8) banks were listed consisting of Ecobank Ghana Ltd, Societe Generale, Standard Chartered Bank, Cal bank, Agricultural Development Bank, Access Bank, Republic Bank, and Ghana Commercial Bank. The data was analyzed using version 25 of Statistical Package for Service Solution. The Augmented Dickey Fuller, Tolerance, Durbin Watson and Variance Inflation Factor tests were used as estimation techniques to ensure accuracy of data. Panel data regression method was used to establish the presence of the pecking order theory. The study found that leverage was negatively related to profitability of listed banks but was statistically insignificant. Leverage was also negatively related to loan quality but statistically insignificant. Leverage showed positive correlation to the size and the age of the firm and was statistically significant, while leverage was positively correlated to growth but insignificant. The study recommends that management of the banks listed put in the necessary measures such as ensuring quality loans and using debt as financing strategies to enhance an increase in the growth levels of firms
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Agricultural Land Use Change in the Lowlands of Southern Mali under Climate Variability
(KNUST, 2023-07) Traore, Alou
This research investigated agricultural land use change in the lowlands of Southern Mali under climate variability. Four supervised classification techniques, Classification and Regression Tree (CART), Support Vector Machine (SVM), Random Forest (RF) and Gradient Tree Boosting (GTB) in Google Earth Engine (GEE), were used for the image classification. An integrated Cellular Automata-Artificial Neural-Network (CA-ANN) within the MOLUSCE plugin of QGIS was used for future Land Use and Land Cover prediction. The Mann-Kendall test, Sen’s slope, Pettit-test and change-point detection analyse were applied for climate variability assessment. Monthly rainfall and mean temperature extending over a period of 61 years (1960–2020) recorded at Sikasso District were analysed. Annual rainfall varied between 800 mm to 1600 mm and annual mean temperature ranged between 25 oC to 28 oC. Seasonal rainfall ranged between 37-387 mm, March-April-May (MAM), 400-1030 mm, June-July-August (JJA), 77-577 mm September-October-November (SON) and 0-45 mm for December-January-February (DJF). Mean seasonal temperature ranged from 29 oC to 32 oC (MAM), 26.5 oC to 28.5 (JJA) oC and 26 oC to 28 oC (SON). Annual and seasonal rainfall trends increased slightly. Temperature showed a significant increase in both annual and seasonal trends. Out of 395 respondents, 79 % were of the view that annual rainfall decreased while 83 % reported mean temperature increased. Again, respondents perceived late onset rainfall (97 %), early cessation of rainfall (96 %), increased in drought (83 %) and flooding (96 %). Also, 43 % of respondents adopted new varieties to cope with climate variability. The findings showed that physical and socioeconomic driving forces had impact on terrain patterns. Over the past three decades, the study revealed that apart from cropland area which increased from 43.81 % to 52.75 %, the size of the other land uses decreased, forest cover (19.93 % - 13.93 %) shrubs (16 % - 14 %), and streams (6 % - 4 %). However, the forecast for the 2020 to 2030 predicted an increasing trend in forest cover and decreasing trend in agricultural land in the study area due to the ongoing afforestation projects. The study demonstrates the need to reinforce regional land management policies and programmes.
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Development of Asphalt Pavement Temperature Prediction Models for the Climatic Conditions of Ghana
(2023-07) Ntramah, Simon
Asphalt pavement temperature finds application in several areas of pavement engineering including pavement structural evaluation and design, asphalt mixture design, asphalt material aging characterisation, and asphalt binder grade selection. Predictive models may be used in the estimation of asphalt pavement temperature when necessary, however, such models tend to have limited transferability and applicability to other regions where the environmental conditions are significantly different from those under which the models were developed. To avoid the risk of using foreign-developed models in estimating the temperature of asphalt pavements in Ghana using local data, this research set out to develop asphalt pavement temperature prediction models applicable to the climatic conditions of the country. Two locations in the country, one within the Savannah climatic zone and the other within the Forest climatic zone, were used for the study. Mid-depth and surface asphalt pavement temperatures, along with climatic data, were collected over a 12-month period (May 2022 to April 2023) at the two study locations. The dataset was then used to develop separate asphalt pavement temperature prediction models applicable to each climatic zones. Additional pavement temperature and climatic data were also collected on separate roads within the corresponding climatic zones for model validation. When tested against some high-rated foreign-developed models, using local environmental data inputs, the locally-developed models predicted asphalt pavement temperatures that were much superior in accuracy (R2 ≥ 0.919, RMSE < 2.8 ºC) to those predicted using the best-performing foreign-based model (R2 ≤ 0.905, RMSE ≥ 3.2 ºC). The local models are, therefore, recommended for predicting mid-depth asphalt pavement temperatures in the Forest and Savannah zones of Ghana for pavement engineering purposes.