http://hdl.handle.net/123456789/972 2026-04-14T23:26:46Z http://hdl.handle.net/123456789/12136 Enriching Roasted Maize Porridge to Enhance Intake of Protein and Vitamin a Using Locally Available Staple Foods Otoo, Gifty Serwaa(Mrs) Protein deficiency, particularly among youngsters, is widespread in most developing nations. An effective approach to address this insufficiency is to integrate regionally abundant staple foods, such as Bambara groundnut and soybean, into current and widely consumed meals, like porridge made from roasted maize flour. For addressing issue related to vitamin A deficiency among expectant mothers and infants, the use of staple foods such as ripe plantain and orange-fleshed sweet potatoes, which abound in Vitamin A, can be explored. Thus, in this study, the properties of composite flours made from roasted maize, Bambara groundnut, and ripe plantain (MBP), roasted maize, Bambara groundnut, and orange-fleshed sweet potatoes (MBO), and roasted maize, soybean, and ripe plantain (MSP) were investigated. Additionally, the study assessed the consumer preference for porridge made from the ingredients. Increasing the quantities of Bambara groundnut, soybean, orange-fleshed sweet potatoes, and ripe plantain resulted in an augmentation in protein and β-carotene levels, respectively, while having no impact on the physicochemical quality. The iron content was enhanced by increasing the amount of ripe plantain, while the zinc content was enhanced by increasing the amount of orange flesh sweet potatoes. Nevertheless, elevated concentrations of the Bambara groundnut and soybean resulted in an augmentation of the tannin content. Hedonic sensory scores indicated no significant changes in acceptability in terms of aroma, appearance, texture, and taste. Therefore, the porridges from the composite flours from this study could easily be accepted by consumers because their attributes were similar to those of roasted maize porridge that they are familiar with. xv, 199p:, ill. 2024-07-01T00:00:00Z http://hdl.handle.net/123456789/12133 Evaluation of a Self-Regulating Low Energy Clay-Based Irrigation (Sleci) System Using Bell Pepper (Capsicum Annuum) as aTest Crop Osei, Gilbert The study evaluated the SLECI system's effectiveness, using bell pepper (Capsicum annuum) as a test crop. Five specific objectives were set to accomplish the aim of the study. Objective one aimed at assessing how irrigation water quality and soil properties influence the performance indicators of (SLECI) system. This objective was accomplished by undertaking a laboratory experiment, with soil type (clay, sand, and loam) and source of irrigation water (river, well, and tap water) as treatments. Performance parameters of the SLECI system, such as seepage rate, hydraulic conductivity, and drainage porosity, were recorded. Pearson correlation tests conducted at a 5% probability level indicated that eight (8) correlations (Zinc, Copper, Calcium, Magnesium, Sodium, Iron, Potassium, and SAR) were statistically significant to the performance of the SLECI system. In contrast, soil properties (bulk density, porosity (%), particle density, infiltration rate, soil salinity, and soil sodicity) were significant to the performance of the SLECI system. Objective two aimed to assess the response of bell peppers to different irrigation systems (watering, drip irrigation, and SLECI system) and fertilizer application methods (basal application and fertigation), under greenhouse conditions. Analysis of variance (p < 0.05) revealed that bell peppers grown under the SLECI system had significantly higher growth, yield, productivity, and quality parameters. Fertigation resulted in significantly superior growth, yield, productivity, and quality parameters. The interaction of the SLECI system and fertigation outperformed all the remaining interactions of the irrigation system and fertilizer application method for data collection. Objective three aimed at investigating the effects of SLECI system burying depth (5 cm, 10cm, and 15 cm) and fertilizer recommended application dosage (100% RAD, 80% RAD, and 60 RAD) on bell peppers under open field conditions. Analysis of variance (p < 0.05) showed significantly higher growth, yield, productivity, and parameters from a burying depth of 10cm. Among fertilizer application dosage treatments, 80% of RAD produced bell pepper plants exhibited significantly higher growth, yield, and productivity parameters. The best-performing treatment interaction was the SLECI system burying depth of 10cm and 80% RAD. Objective four aimed to assess bell peppers' response to saline irrigation water (0.54 dS/m (control), 2.0 dS/m, 4.0 dS/m, 6.0 dS/m, and 8.0 dS/m) using the SLECI system. Compared to the control (0.55 dS/m) increasing water salinity levels to 2.0 dS/m, 4.0 dS/m, 6.0 dS/m, and 8.0 dS/m resulted in decreased growth, yield, and productivity parameters of bell pepper. Objective five aimed at simulating moisture and salinity levels using MATLAB. A coefficient determination of 0.99413, 0.98613, and 0.96689 was observed between experimental and simulated results indicating the robustness of MATLAB in simulating water and soil dynamics in the soil. Overall, the research highlights the potential of the SLECI system to enhance agricultural land and water productivity. xxiii, 326p:, ill. 2025-02-01T00:00:00Z http://hdl.handle.net/123456789/12082 Innovative Applications of Handheld Near-Infrared Spectroscopic Technology for Quality Assessment of Fruits and Fruit Products in Ghana Lamptey, Francis Padi Handheld near-infrared spectroscopy (NIRS) is emerging as a key technology for food analysis in Africa. This study explores its effectiveness, combined with chemometric techniques, for rapid and non-destructive evaluation of mango fruits and products. It focuses on developing predictive models for variety differentiation, classification of organic and inorganic samples, and assessing quality attributes such as total soluble solids (TSS) and pH. Additionally, it identifies ethephon residues and categorizes organic and inorganic pineapple juice. The study also examines the physicochemical and microbial changes in expired and unexpired commercial fruit juices using conventional laboratory methods. For mango variety identification, NIRS combined with multivariate algorithms achieved 97.44% accuracy. The synergy partial least squares model yielded r² values of 0.63 and 0.81 for TSS and pH predictions, with RMSEP values of 1.83 and 0.49, respectively. In detecting ethephon residues, the neural network model with multiplicative scatter correction reached 100% classification accuracy, while the partial least squares model demonstrated strong predictive performance (r² = 0.996, RMSEP = 0.068). The random forest algorithm classified organic and inorganic mango products with varying accuracy levels. When preprocessed using the second derivative, it achieved 88.76% accuracy for fresh fruit, 77.98% for chips, and 87.53% for juice without preprocessing. The combination of dual NIR spectrometers effectively distinguished organic and inorganic pineapple juice with 100% accuracy. Furthermore, a comparative assessment of expired and unexpired commercial fruit juices showed notable declines in titratable acidity (apple juice decreased from 0.60% to 0.12%) and vitamin C (a 57.6% reduction in pineapple juice), alongside an increase in microbial load. These findings highlight the potential of handheld NIRS as a reliable tool for quality control, product authentication, and food safety assurance. Its application could improve postharvest monitoring, mitigate food fraud, and enhance regulatory compliance within the fruit industry. xx, 283p:, ill. 2024-10-01T00:00:00Z http://hdl.handle.net/123456789/11920 Developing A Novel Onsite Detection Technology By Using Chemometrical Analysis Of Hand-Held Near-Infrared Sensor Technique For Assessing Coffee Quality Boadu, Vida Gyimah This study aims to apply handheld infrared spectral technique to develop a predictive model for the identification of adulterants and rapid estimation of the quality of coffee products. For the classification of coffee varieties, the novel potable NIR spectrometer combined with multivariant qualitative algorithms gave 98.8%, 99.72% and 99.22% identification for raw, roasted and roasted powdered coffee, respectively. Also, in the classification of Africa coffee types, it gave 99.76%, 99.78% and 99.88% identification for raw, roasted and roasted powdered coffee, respectively. Qualitatively, FD-LDA performed better with 97.78% and 100% in both calibration and prediction sets in the determination of coffee husk in roasted coffee powder. Quantitatively, in the detection of coffee adulteration, SPAPLS model had the best results with R=0.9711 and 0.9897 in both calibration and prediction sets respectively. The novel handheld spectroscopy could be employed for the discrimination of coffee varieties and African robusta coffee in three forms (raw, roasted and powder) and quantification of coffee husk in coffee. With 10% occurrence frequencies, two fungi, Aspergillus niger and flavus were found in commercially sold powder coffee in some of the major markets in Ghana with acrylamide levels below the benchmark threshold (400ug/kg) set by the European Commission. The proximate analysis conducted on the commercially sold coffee powder revealed high moisture and ash attributed to a substantial amount of impurities in the coffee samples. Furthermore, minerals namely nitrogen, phosphorus, potassium and magnesium were found in the coffee powders. xxiii, 240p; , ill. 2024-06-01T00:00:00Z