Farmers’ Notion of Climate Change and Response to Rainfall Variability in a Nigerian Coastal Settlement of Oron

The study investigated farmers’ notion of climate change and their response to rainfall variability in Oron, a Coastal settlement in Akwa Ibom State of Nigeria. The specific objectives of the study is to determine farmer’s notion of climate and their response to climate variability. The farmers’ perception of climate change  is necessary for preparedness and planning purposes in an agrarian community in order to boost farm productivity. Through the use of structured questionnaires, data for the study was obtained from 400 farmers’ in 17 randomly sampled villages in Oron. The data was complemented by information obtained through focus group discussion, participatory rural appraisal, direct field observations and in-depth interviews of key informants. To aid the analysis, data on some climatic variables from 2003 to 2013 were obtained from the study area and analysed to show the behavior of annual precipitation, wet  and dry seasons precipitation and to compare results with the farmers’ notion of climate change. In the same vein, the number of drought years occurring in the study area was calculated using Shewale and Kumar (2005) method. The study reveals that (i)  most of the farmers’ were unaware of the concept of climate change, even though they have considerable knowledge of major changes taking place in their environment (ii)  The farmers have general feeling of uncertainty about the best time to plant crops due to the unpredictability of rainfall and the difficulties in planning farming activities  (iii) the number of extreme rain event per year in the study area does not appear to be increasing, indicating that farming has not become more vulnerable to such phenomena. All the farmers indicated the need for  planting early maturing seed and changing the timing of planting, as a response strategies to mitigate the effect of climate variability in the study area. The study, thus concludes that unless urgent steps are taken to educate the farmers’ about their notion of climate variability and the possible pathways to adaptation, the coastal settlement  is vulnerable to food insecurity. Keywords: Climate change; Farmers notion; Rainfall variability; Coastal settlement

Modelling of Moisture Loss and Oil Uptake During Deep-Fat Frying of Plantain (Dodo)

In this study, model was developed to predict moisture loss and oil uptake during deep-fat frying of plantain (dodo). Plantain samples were sliced and fried at different frying temperatures (150, 160, 170, 180 and 190 °C) in a deep fryer for periods varying from 2 to 4 min. Moisture and fat analyses were determined based on the AOAC standard method. Mathematical model was developed from fundamental law of mass diffusion with the aim of predicting moisture loss and oil uptake rate during DFF of dodo. The model was solved numerically using explicit Finite Difference Technique (FDT). Computer codes were written in MATLAB environment for moisture loss and oil uptake in the slices at different frying conditions. The predicted results were compared with experimental data and good agreement was obtained. The correlation coefficients between the predicted and experimental values of moisture and oil transfer models ranged from 0.988 to 0.994 and 0.958 to 0.978, respectively. The results show that the model is consistent and it may be used to predict moisture loss and oil uptake during deep-fat fried of dodo

Optimization of Deep-Fat Frying of Plantain Chips (Ipekere) using Response Surface Methodology

Deep-fat frying of plantain chips (ipekere) was investigated with the aim of predicting optimum operating conditions for plantain chips to minimize oil content in order to produce healthy products. The effect of frying temperature and time on moisture content, oil content, breaking force and colour difference of plantain chips was evaluated. Response surface methodology was used to analyze the results of the central composite design of the frying processes for the responses as a result of variation in the levels of frying temperature (150 – 190oC) and frying time (2 – 4 min). Response surface regression analysis shows that responses were significantly (p<0.05) correlated with frying temperature and time. Regression model was developed for the investigation of the effect of frying temperature and time on the responses. The polynomial regression models were validated with statistical tool whose values of coefficients of determination (R2) were 0.995, 0.982, 0.971 and 0.996 for moisture content, oil content, breaking force and colour difference, respectively. The optimum values of moisture content, oil content, breaking force and colour difference were 3.73%, 1.18%, 17.66 N and 65.53, respectively, at frying temperature of 183oC and frying time of 3 min. Therefore, frying conditions had a significant effect on the quality attributes of chips produced from plantain. Keywords: plantain chips, deep-fat frying, regression models, texture and colou

Characterization of Thiosulphate: Cyanide sulphur transferase from the gut and body segments of Earthworm (Hyperiodrilus africanus)

Cyanide compounds that are by products of industrial activities are known to pose serious environmental pollution. The use of these cyanide compounds by the mining industry, along with limitations in the analysis and monitoring of these compounds, raises serious concerns regarding environmental protection and public safety. Hyperiodrilus africanus (earthworm) is directly employed within bioremediation strategies to promote biodegradation of organic contaminants and thus could be employed to rejuvenate cyanide contaminated soils. Cyanides detoxification could also prevent the risk of cyanide poisoning in poultry animals by converting cyanides in forages to a less toxic compound. This work is designed to extract and characterize rhodanese (thiosulphate: cyanide sulphur transferase, (EC 2.8.1.1) from the gut and body segments of H. africanus collected from the swampy area along Uren bank river in Ikenne community of Ogun State, Nigeria. Our results show total rhodanese activities of 1434.50 RU and 2274.28 RU and specific activities of 108.01 RUmg-1 and 83.1901 RUmg-1 in the gut and body segments of H. africanus respectively. The optimum temperature of 25 °C and optimum pH of 10.5 were obtained for both the gut and body segments enzymes. The enzyme obeyed Michaelis-Menten kinetics and the kinetic constants, Km and Vmax in the gut segment were 33.33 mM and 62.50 RU/ml for KCN substrate and 22.22 mM and 41.67 RU/ml for Na2S2O3 substrates. In the body segment, the Km and Vmax were 33.33 mM and 83.33 RU/ml; 15.38 mM and 4.00 RU/ml for the KCN and Na2S2O3 substrates respectively. Hence, we conclude that the enzyme is more specific for  Na2S2O3 than KCN as substrates, though maximum activity was observed in the body segment for KCN substrate. Ca2+, Mg2+, Ba2+, K+, Na+, Cu2+ and Zn2+ metal ion salts activated the body segment rhodanese at 1 mM and 5 mM concentrations while they have no effect on the gut segment rhodanese from earthworm. On the basis of these findings we conclude that earthworm could detoxify cyanide-containing wastes/forages and therefore promote biodegradation.Keywords: Rhodanese, earthworm, environmental protection, cyanide detoxification, bioremediatio

Activities of a Cellulase of the Termite, Ametermes Eveuncifer (Silverstri) Soldier: Clue to Termites Salt Intolerance

Table salt which contains predominantly NaCl is both toxic and lethal to termites and is therefore used to control the insect traditionally. In an attempt to find out a scientific explanation for this treatment and possibly design a pesticide for the destructive insect, we carried out some tests on the effects of NaCl (table salt), some other chloride and sodium salts on some important enzymes produced by termites. At 0.1mM concentration, all the chloride salts inhibited all the enzymes. Acid phosphatase and arginase were however mildly inhibited. Interestingly, some chloride salts were more potent than NaCl the conventional pesticide.  The greatest inhibition was by the chlorides of mercury (81%), manganese (78%), and sodium (76%). The inhibitory effect was more on cellulolytic enzymes; β-glucosidase and cellulase than on detoxifying enzymes; 3-MST and rhodanese. Again, all the sodium salts tested inhibited cellulase drastically with most of them more potent than NaCl. Thus both the sodium and chloride ions contributed immensely to the inhibition. Form these discoveries, one of the chloride salts of mercury, manganese and sodium or a combination of at least two can be used as a pesticide for termites. Almost all the sodium salts tested or a combination of at least two can also be used. Keywords: cellulase, cellulose, termites, salts, insects, enzyme

Sorghum Brown Midrib19 (Bmr19) Gene Links Lignin Biosynthesis to Folate Metabolism

Genetic analysis of brown midrib sorghum (Sorghum bicolor) mutant lines assembled in our program has previously shown that the mutations fall into four allelic groups, bmr2, bmr6, bmr12 or bmr19. Causal genes for allelic groups bmr2, bmr6 and bmr12, have since been identified. In this report, we provide evidence for the nature of the bmr19 mutation. This was accomplished by introgressing each of the four bmr alleles into nine different genetic backgrounds. Polymorphisms from four resequenced bulks of sorghum introgression lines containing either mutation, relative to those of a resequenced bulk of the nine normal midrib recurrent parent lines, were used to locate their respective causal mutations. The analysis confirmed the previously reported causal mutations for bmr2 and bmr6 but failed in the case of bmr12-bulk due to a mixture of mutant alleles at the locus among members of that mutant bulk. In the bmr19-bulk, a common G → A mutation was found among all members in Sobic.001G535500. This gene encodes a putative folylpolyglutamate synthase with high homology to maize Bm4. The brown midrib phenotype co-segregated with this point mutation in two separate F2 populations. Furthermore, an additional variant allele at this locus obtained from a TILLING population also showed a brown midrib phenotype, confirming this locus as Bmr19

APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS AND GENETIC ALGORITHMS IN DRYING OF FRUITS AND VEGETABLES : A REVIEW

oai:ojs2.laujet.com:article/1Fruits and vegetables play an important role in the diet of human beings and economic development of a country. They are cheapest and most available sources of important proteins, vitamins, minerals and essential amino acids. Considering the perishable nature of fruits and vegetables it is necessary to preserve them and drying is one such method to do it. The drying of fruits and vegetables is a complex operation that demands much energy and time. Due to this complexity, the use of drying mathematical models in estimating the drying kinetics, the behaviour and the energy needed in the drying of fruits and vegetables becomes indispensable. Numerous mathematical models, empirical and semi-empirical, have been proposed to estimate the drying characteristics of fruits and vegetables. But these models are generally solutions of simultaneous heat and mass transfer differential equations and the final result may be very complicated and difficult to use in actual drying systems. This article present a comprehensive review on the applications of artificial neural networks and genetic algorithms in drying of fruits and vegetables. The paper starts with the drying of fruits and vegetables, the introduction of basic theoretical knowledge of ANN and GA. Then summarize their application on modeling, predicting, and optimization of heat and mass transfer, thermodynamic performance parameters, and quality indicators as well as physicochemical properties of dried fruits and vegetables. Conclusively, opportunities and limitations of ANN and GA technique in are outlined to provide more ideas for research and development in this field

ASSESSMENT OF CHEMICAL AND ANTINUTRITIONAL PROPERTIES OF BREAKFAST MEAL PREPARED FROM BLENDS OF BANANA AND AFRICAN YAM BEAN

Banana (Musa sapientus) and African yam bean (Sphenostylis stenocarpa) are nutritional food sources that are valuable industrially even in consideration for a balanced nutrition. This research work evaluates the production of breakfast meal from blends of Banana and African yam bean (AYB). Banana and AYB were mixed in the ratio 90:10, 80:20, 70:30 and 100:0 (control) for the production of breakfast meal. Crude protein, ash, crude fiber, fat and carbohydrate content of mixtures were determined using the AOAC methods. Vitamins, minerals and anti-nutrient composition of the breakfast meal were determined using standard methods and data were analyzed using Analysis of Variance (ANOVA). Sensory attributes were determined using 9-point hedonic scale by forty panelists. The results of the proximate analysis showed that protein ranged from 5.41-11.26%, fat content (1.97-4.56%), carbohydrate (72.71-79.89%), fiber (0.39-0.57%), ash (3.23-3.97%) and moisture content (7.86-8.20%). Oxalate (8.73-4.38%) decreased with increase in AYB inclusion. Tannin values ranged from 17.09-26.73% and phytate ranged from 11.59-46.77%. The sensory evaluation by the panelists shows that the product was widely accepted. Samples 100:0 and 90:10 were mostly preferred in terms of colour, texture, taste, crispiness, sweetness, flavour, appearance and general acceptability. Hence, the fortification of banana flakes with AYB can be encouraged as a breakfast meal

Deformation Monitoring Using A Terrestrial Laser Scanner: A Case Study Of Alausa Shopping Mall, Ikeja, Lagos, Nigeria

Deformation refers to the continuous transformation of a structure from a reference configuration to a current configuration. The passage of time causes significant damage to buildings, so it is necessary to carry out monitoring procedures. Hence, the objective of this paper is to monitor the deformation of Alausa Shopping Mall, Ikeja, Lagos, Nigeria using a Polaris Terrestrial Laser Scanner to ascertain the structure's stability. The Polaris Terrestrial Scanner was used to acquire the point cloud of the structure; which represents the as-is geometries of the structure, and when imported into a BIM software environment, a 3D point cloud model, which represents the current state of the structure is created. The dimension of the building was acquired from the Lagos state vector, and when combined with height data, a 3D model representing the As-built building was developed. Then a comparison between the 3D point cloud and the As-built model was performed by comparing building segments in the 3D point cloud model with their corresponding segments in the As-built model which resulted in the determination of the horizontal and vertical displacements. The horizontal displacement rate was calculated to be 0.593mm per year, and the vertical displacement rate recorded was 3.845mm per year. Predictions of the displacement rates over 50 years at 10 years intervals were made, with the maximum (after 50 years) as 29.65mm and 192.25mm at the horizontal and vertical, respectively. Therefore, monitoring of structure should be a continuous process in the build environment