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                <text>Iron deficiency is commonly referred to as anaemia which is a general public health problem that normally occurs as a result of a reduction in red blood cells which is common in developing countries such as Africa. In this study, machine learning algorithms such as CNN, k-NN, Naïve Bayes, Decision Tree and SVM were utilized for the study to detect anaemia in children using conjunctiva images. The images were segmented into their various CIELAB colour space components and the ROI from each image was retrieved. The dataset was split randomly into 70:10:20, which were then used to train, validate, and test the models, as appropriate. The CNN achieved the highest accuracy (98.45 %). The findings of this study demonstrate that non-invasive techniques are essential for detecting anaemia in children. This study deploys a cost-effective mechanism, and result-orientated, to detect anaemia in developing …</text>
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                <text>Iron deficiency is commonly referred to as anaemia which is a general public health problem that normally occurs as a result of a reduction in red blood cells which is common in developing countries such as Africa. In this study, machine learning algorithms such as CNN, k-NN, Naïve Bayes, Decision Tree and SVM were utilized for the study to detect anaemia in children using conjunctiva images. The images were segmented into their various CIELAB colour space components and the ROI from each image was retrieved. The dataset was split randomly into 70:10:20, which were then used to train, validate, and test the models, as appropriate. The CNN achieved the highest accuracy (98.45 %). The findings of this study demonstrate that non-invasive techniques are essential for detecting anaemia in children. This study deploys a cost-effective mechanism, and result-orientated, to detect anaemia in developing …</text>
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                <text>The aim of this study was to assess the macrobenthic fauna structure and use its indices as a tool for characterizing the ecological state of the Laloi lagoon. Thus, a field assessment of the benthos in the Laloi lagoon was carried in January 2012. Four replicate samples were taken at each station contained in three zones and analysed for their structure and composition. Twenty-one (21) species of macrobenthos belonging to 19 genera were identified. The highest number of species belonged to Polychaetes (15 species) followed by Bivalves (6 species) and 1 species of Gastropod. The grain size of sediments and total organic matter as essential factors in distribution and population diversity of macrobenthos communities were also analysed. The results showed that all of the stations were characterized by medium sand to very fine sand. Shannon-Wiener index (H'), species richness (S) and Pielou’s evenness were calculated and they revealed a high species diversity with variability in abundance within stations. The ecological indices, such as (AMBI, M-AMBI, BENTIX and H’) were also applied to the available benthic species data to determine the ecological status of the lagoon. AMBI, M-AMBI, H'and BENTIX gave different results regarding the boundaries for High, Good and Moderate and it was worse when applying H'and BENTIX. However, the index AMBI provided a more suitable evaluation of EcoQS corresponding to ‘slightly polluted’lagoons in compliance with univariate community indices.</text>
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                <text>Investigations were conducted employing a three-component constrained mixture design to formulate milk blends from soy milk, peanut milk and cow milk. Variations in chemical composition and physico-chemical properties of 10-soy-peanut-cow milk (SPCM) formulations were studied. Variations in soy-peanut-cow milk (SPCM) concentrations influenced to varying levels the chemical composition and physico-chemical properties of blends. SPCM formulations containing significant amounts of all three ingredients used (60-70% soy milk, 20-27% peanut milk and 7-20% cow milk) had high crude protein and fat values ranging from 2.20-2.51% and 5.00-6.35% respectively. Increasing soy concentrations caused relative increases in protein content while fat content increased with increasing peanut concentrations. SPCM formulations were high in the minerals Fe and Mn relative to cow milk which was high in Ca and Zn content. Trends in pH were contrary to titratable acidity and increased with increasing soy milk content but decreasing cow milk content. SPCM formulations demonstrated acceptable non-Newtonian behaviour and consistency indices.</text>
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                <text>Response surface methodology and central composite design for K = 3 was used to study the combined effect of blanching time (0-12 min), soaking time (0-24 h) and sodium hexametaphosphate [(NaPO3)(6)] salt concentration (0-1%) on moisture, ash, leached solids, phytates, tannins and hardness (texture) of cowpeas during canning. Regression models were developed to predict the effects of variables on the studied indices. Blanching, soaking and salt concentration all had significant positive effects on moisture content, ash content. leached solids, phytates, tannins and hardness of the canned cowpeas with significant interaction between all the factors with high regression coefficients (72.0-91.4%). The use of blanching and soaking prior to canning led to increasing moisture content and leached solids while significant decreases were observed for phytates, tannins and hardness of the canned cowpeas …</text>
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                <text>Bambara groundnut (Voandzei subterranea) seeds were canned with the objective of investigating the optimal pre-processing conditions that would yield the best quality canned product from it. Pre-canning procedures such as blanching time, soaking time and sodium hexametaphosphate [(NaPO3) 6] salt concentration were used as the independent variables for a Central Composite Rotatable Design (CCRD). The pre-processing parameters obtained from the CCRD for k= 3 were used for the canning of the bambara groundnuts and the quality characteristics (moisture content, pH of the drained liquid, drained weight, splitting of the seeds, leached solids and seed hardness) of the canned products were studied using response surface methodology. Regression models were generated using regression analysis and used for the plotting of response surface curves. Adequacy of the model equation for predicting the …</text>
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                <text>Application of response surface methodology for studying the influence of soaking, blanching and sodium hexametaphosphate salt concentration on some biochemical and physical characteristics of cowpeas (Vigna unguiculata) during canning</text>
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                <text>Response surface methodology and central composite design for K=3 was used to study the combined effect of blanching time (0–12 min), soaking time (0–24 h) and sodium hexametaphosphate [(NaPO3)6] salt concentration (0–1%) on moisture, ash, leached solids, phytates, tannins and hardness (texture) of cowpeas during canning. Regression models were developed to predict the effects of variables on the studied indices. Blanching, soaking and salt concentration all had significant positive effects on moisture content, ash content, leached solids, phytates, tannins and hardness of the canned cowpeas with significant interaction between all the factors with high regression coefficients (72.0–91.4%). The use of blanching and soaking prior to canning led to increasing moisture content and leached solids while significant decreases were observed for phytates, tannins and hardness of the canned cowpeas …</text>
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                <text>Response surface methodology (with central composite rotatable design for k0/3) was used to investigate the product properties of extruded riceÁ/cowpeaÁ/groundnut blends in a single screw extruder. The combined effect of cowpea (0Á/20%), groundnut (0Á/10%), and feed moisture (14Á/48%) levels were used for formulation of the products. The product moisture, expansion ratio, bulk density and total colour change were studied using standard analytical methods. Well-expanded riceÁ/legume blend extrudates of less bulk density and lower moisture content were produced at low feed moisture. Increasing legume addition affected the various shades of colour in the product. Models developed for the indices gave R2 values ranging from 52.8%(for the b-value) to 86.5%(for bulk density). The models developed suggested that the optimal process variables for the production of a puffed snack with an enhanced nutrition and spongy structure from a riceÁ/cowpeaÁ/groundnut blend are low feed moisture of 14Á/20% and maximum additions of 20% cowpea and 10% groundnut. A lack-of-fit test showed no significance, indicating that the models adequately fitted the data.</text>
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                <text>Application of response surface methodology for studying the product characteristics of extruded rice–cowpea–groundnut blends</text>
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                <text>Response surface methodology (with central composite rotatable design for k=3) was used to investigate the product properties of extruded rice–cowpea–groundnut blends in a single screw extruder. The combined effect of cowpea (0–20%), groundnut (0–10%), and feed moisture (14–48%) levels were used for formulation of the products. The product moisture, expansion ratio, bulk density and total colour change were studied using standard analytical methods. Well-expanded rice–legume blend extrudates of less bulk density and lower moisture content were produced at low feed moisture. Increasing legume addition affected the various shades of colour in the product. Models developed for the indices gave R2 values ranging from 52.8% (for the b-value) to 86.5% (for bulk density). The models developed suggested that the optimal process variables for the production of a puffed snack with an enhanced nutrition …</text>
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