Development of a Wireless Sensor Network for Monitoring Environmental Condition on a Farmland

In recent time, the wireless sensor network technology has found its implementation in precision agriculture as a result of the need for high productivity. This paper focuses on the development of a wireless sensor network on agricultural environment to monitor environmental conditions and deduce the appropriate environmental parameters required for the high yield of crop production on a given farmland. The developed wireless sensor network is built around sensor nodes and a master microcontroller (PI16F648A) that takes in the data sent from the nodes for upload into a personal computer (PC). Each node has sensors to monitor environmental conditions such as temperature, relative humidity and light intensity which are important environmental factors in an agricultural set-up. The DHT11 sensor is used to sense and provide calibrated digital outputs for the measured temperature and relative humidity while a calibrated light dependent resistor (LDR) is configured to the light intensity sensor unit. The outputs from these sensors are processed by the microcontroller and sent wirelessly, using low-power radio frequency transceivers, to a remote master controller for storage. The deployment of the developed wireless sensor network on a named farmland shows that the aforementioned could be efficiently utilized to provide an up-to-date and accurate measurement of agriculture data, which include light-intensity, relative-humidity and temperature. Thus, the developed framework replaces the traditional method of predicting environmental parameters required on a given farmland

ANTIMICROBIAL EFFICACY OF THYMOL IN THE MANAGEMENT OF BACTERIAL WILT OF TOMATO

Bacterial wilt (BW), caused by Ralstonia solanacearum, is a devastating disease of tomato world-wide. The disease is responsible for more than 60% reduction of tomato yield in Nigeria. Volatile plant essential oil, thymol, was evaluated against BW in artificially-inoculated potted plants.  Twenty milliliter of 108 cfu/ml suspension of Ralstonia solanacearum was introduced into 5 kg pot of sterilized soil and 20 ml each of three concentrations of thymol (0.2, 0.4, 0.6 g/L) applied as pre-plant soil drench 2 hours after bacterial inoculation.  Eight tomato genotypes were transplanted into the pots five days after thymol application.    The experiment was laid in a completely randomized design (CRD) with three replicates.  At 0.2 g/L thymol application, disease severity index was 1.50-4.00 at 5 Weeks After Transplanting (WAT).  Disease severity index was reduced significantly (p<0.05) by 77.78% in tomato variety Delila upon 0.4 g/L application of thymol. At 0.6 g/L thymol application, tomato varieties Delila, Perfect Pee and Kerewa each had 0 (zero) disease severity index, while tomato lines NG/AA/MAY/09/030, NG/TB/AUG/09/006 and NG/AA/SEP/09/037 had disease severity index of 1 (one) each.  These results indicated that application of thymol (0.6 g/L concentration, 1:250, thymol:soil, v:w) in potted experiment was effective in reducing the severity index of bacteria wilt of tomato caused by Ralstonia solanacearum, and is therefore recommended for management of the disease

TUBE GRAFTING REDUCES INCIDENCE AND SEVERITY OF BACTERIAL WILT IN TWO TOMATO CULTIVARS IN ABEOKUTA, NIGERIA

Bacterial wilt, Ralstonia solanacearum, causes severe loss of tomato (Solanum lycopersicum L.) pro-duction in Nigeria. Tube grafting of two tomato cultivars (Beske and UC82-B) on bacterial wilt-resistant tomato landrace rootstock (Tomachiva) was conducted to reduce incidence of bacterial wilt and in-crease the yield in the two cultivars. The experiments were laid in Randomized Complete Block De-sign (RCBD). Percentage incidence and Percentage Severity Index (PSI) of grafted tomato were 0.00% each in the early planting season. Incidence (1.70%) and PSI (1.50%) of grafted tomato were observed in late planting season. Non-grafted tomato had higher significant values of 42.50% and 38.80% in incidence and percentage severity index in late planting season. Grafting on Tomachiva effectively reduced the incidence and severity of bacterial wilt in two cultivars of tomato in southwest Nigeri

AN mAGRICULTURE FRAMEWORK FOR AGRICULTURE INFORMATION SERVICES DELIVERY

Agriculture is an information intensive industry that is spatial in nature. For farmers to thrive, they must be generalists who are well versed in the latest farming technologies. Thus, farmers need to be well informed on the best agricultural practices, prime farming operation techniques, optimum methods of management, prevailing post harvest operations and transactions and so on. However, Nigerian and African agriculture in general is disadvantaged owing to factors that include: poor access to agriculture-related information, deficits in physical infrastructure, high transactional costs, digital divides, low literacy level, problems with availability of agricultural inputs to mention but a few. In this paper, we present an mAgriculture framework for agricultural information services delivery using the communication channels available on a feature phone. Features phones are easy to use and are increasingly able to bypass the barriers of illiteracy and affordability, and they provide access to a wide range of very useful services, such as transferring money, checking market prices, gathering weather information, obtaining personal agricultural extension and other professional advice. The three basic communication channels of feature phones employed by the developed framework are: voice, short message service (SMS) and Unstructured Supplementary Service Data (USSD) with the intent of providing a platform where farmers’ need of agriculture information could be met

DEVELOPMENT OF AN IMPACT ASSESSMENT ALGORITHM FOR THE ADOPTION OF INFORMATION AND COMMUNICATION TECHNOLOGY IN BASIC EDUCATION USING CROSS-IMPACT METHOD

In many countries, the adoption of Information and Communication Technology (ICT) in basic education has been continuously linked to higher efficiency, productivity, and educational outcomes, including quality of cognitive, creative and innovative thinking. This paper focuses on the development of an impact assessment algorithm for evaluating the adoption of ICT in basic education using Cross-impact method. A questionnaire on adoption of ICT in basic education was designed based on Government Policy (GP), Teacher Competency (TC), Availability of ICT infrastructure (IF), Integration of ICT in school curriculum by Ministry of Education (MC), Student preparedness in adopting ICT in learning process (SC) and Perception of schools’ management in adoption of ICT in schools (MI), which are the six major events considered. The questionnaire was administered to experts in basic education within the selected South-Western states of Nigeria (Oyo, Lagos and Ekiti). Experts’ opinions from the administered questionnaires were quantitatively analysed using descriptive statistic in Statistical Package for Social Sciences. The results obtained from the analysis of questionnaires were used to derive the Initial Probability (InitProb) and generate the Conditional Probability Matrices (CondProbMatrices) for occurrence and non-occurrence of the six events under consideration. The impact assessment algorithm was developed such that its starting instructions would determine the consistence of the InitProb and the CondProbMatrices using the three fundamental laws of probability calculus (Normalization, Product and Addition rules). These are followed by sequential instructions which would determine the occurrence of each event in the CondProbMatrices. Then, through repetitive instructions, each event would be selected at random and its occurrence and non-occurrence would be determined using a random number generator. The last group of instructions would successively determine the impact of each event on other alternative events. Thus, the developed impact assessment algorithm could replace the existing user perspective method of evaluating the adoption of ICT in basic education

MODELLING OF A PRE-HOSPITAL EMERGENCY CARE FLOW PROCESS USING TIMED COLOURED PETRI NETS

Pre-hospital emergency care service is a major gateway to the Accident and Emergency Department that determines the rate of quality emergency service in hospitals. In this paper, Timed Coloured Petri Nets (TCPN) formalism is employed to model a pre-hospital emergency care flow process which is characterized by ambulance localization and emergency call responses using Osun State Emergency Management Ambulance Service (O’ambulance) as a case study. The developed TCPN model consists of Next Arrival Call (NAC) and Process Emergency Call (PEC) modules. The NAC module abstracted the emergency calls that were received by one (1) call receiver agent being utilized while the PEC module abstracts the operation (services) carried out in the units. The developed TCPN model was simulated using Coloured Petri Nets (CPN) tools while its validation was explored by comparing the simulated and actual rescue team average response time and turn-around times of the rescue teams in operation at the considered case study. The simulation results of the developed TCPN model yielded maximum Average Waiting Times (AWT) of 1.65 and 0.35 minutes using one and two emergency call receiver agents, respectively. Also, the simulation results showed that 7.05, 26.17 and 35.13 minutes were recorded as minimum values for Rescue team Average Response Time (RART), Rescue team Turn-around Time in case of non-critical (RTTNC) and Rescue team Turn-around Time Critical (RTTC), respectively. Similarly, the simulation results showed that RART, RTTNC and RTTC yielded maximum values of 15, 34 and 41.62 minutes, respectively. Statistically, there were no significant differences between the simulated and the real number of patients entering the health centre at 5% level. This gave a confirmation that the developed TCPN model accurately described the pre-hospital emergency care flow process under study. The developed TCPN model could serve as a referential model for studying and improving pre-hospital emergency care flow process in a named ambulance centre

Effect of dietary supplementation of Padauk (Pterocarpus soyauxii) leaf on high fat diet/streptozotocin induced diabetes in rats’ brain and platelets

Background This study investigated the effects of Padauk leaf on brain malondialdehyde (MDA) content, acetylcholinesterase (AChE) activities, ectonucleotidases and adenosine deaminase (ADA) activities in the platelet of high fat diet and streptozotocin (STZ)-induced diabetic rats. Methods The animals were divided into six groups (n = 7): normal control rats; diabetic rats + high fat diet (HFD); diabetic rats + HFD + Metformin; diabetic rats + HFD + acarbose; diabetic rats + HFD + 10% Padauk leaf; normal rats + basal diet + 10% Padauk leaf. After 30 days of experiment comprising of acclimatization, dietary manipulation, pre-treatment with STZ and supplementation with Padauk leaf, the animals were sacrificed and the rats’ brain and blood were collected for subsequent analysis. Results The results demonstrated that the elevated MDA content and AChE activity in the diabetic rats were significantly reduced when compared with the control rats. Furthermore, the increased NTPDases, 5′-nucleotidase and ADA activities in the diabetic rats were significantly reduced when compared with the control rats. Conclusion This study demonstrated that Padauk leaf exhibited modulatory effects on purinergic and cholinergic enzymes involved in the prevention of platelet abnormality and consequent vascular complications in diabetic state

Data-independent acquisition mass spectrometry in severe rheumatic heart disease (RHD) identifies a proteomic signature showing ongoing inflammation and effectively classifying RHD cases

Background Rheumatic heart disease (RHD) remains a major source of morbidity and mortality in developing countries. A deeper insight into the pathogenetic mechanisms underlying RHD could provide opportunities for drug repurposing, guide recommendations for secondary penicillin prophylaxis, and/or inform development of near-patient diagnostics. Methods We performed quantitative proteomics using Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectrometry (SWATH-MS) to screen protein expression in 215 African patients with severe RHD, and 230 controls. We applied a machine learning (ML) approach to feature selection among the 366 proteins quantifiable in at least 40% of samples, using the Boruta wrapper algorithm. The case–control differences and contribution to Area Under the Receiver Operating Curve (AUC) for each of the 56 proteins identified by the Boruta algorithm were calculated by Logistic Regression adjusted for age, sex and BMI. Biological pathways and functions enriched for proteins were identified using ClueGo pathway analyses. Results Adiponectin, complement component C7 and fibulin-1, a component of heart valve matrix, were significantly higher in cases when compared with controls. Ficolin-3, a protein with calcium-independent lectin activity that activates the complement pathway, was lower in cases than controls. The top six biomarkers from the Boruta analyses conferred an AUC of 0.90 indicating excellent discriminatory capacity between RHD cases and controls. Conclusions These results support the presence of an ongoing inflammatory response in RHD, at a time when severe valve disease has developed, and distant from previous episodes of acute rheumatic fever. This biomarker signature could have potential utility in recognizing different degrees of ongoing inflammation in RHD patients, which may, in turn, be related to prognostic severity