A researcher Phone: 234-8135296652 Address: University of Agriculture, Makurdi, Nigeria Department of Agricultural and Environmental Engineering P. M. B. 2373 Nigeria
Springer eBooks: Encyclopedia of Smart Agriculture Technologies, 2023
Definition 1. Silo: A tall, cylindrical storage structure designed to store grain or other agricu... more Definition 1. Silo: A tall, cylindrical storage structure designed to store grain or other agricultural products. 2. Monitoring system: A system that collects and processes data from the sensors and other sources to provide real-time information about the storage environment. 3. Control system: A system that uses the data from the monitoring system to adjust the ventilation, heating, and cooling systems within the silo to maintain optimal storage conditions for the grain. 4. Aeration system: A system that circulates air within the silo to control moisture levels and prevent the growth of mold and mildew. 5. Ventilation system: A system that allows for the controlled exchange of air within the silo to regulate temperature, humidity, and oxygen levels. 6. Grain quality: The condition of the grain in terms of its moisture content, temperature, and freedom from mold, pests, and other contaminants. 7. Grain spoilage: The deterioration of the quality of grain due to factors such as moisture, temperature, pests, or other contaminants.
Journal of Agricultural Engineering and Technology (JAET), 2022
The agriculture sector faces numerous challenges including disease and pest infestation, insuffic... more The agriculture sector faces numerous challenges including disease and pest infestation, insufficient available water, inadequate drainage, declining labour availability and knowledge gap between farmers and technology, leading to low outputs. More and more farmers are starting to adopt new techniques to boost productivity and increase revenue. This paper reviews the applications of artificial intelligence (AI) to agriculture and explores ways that the Nigerian farmers can benefit from this technology. AI-powered solutions have been applied in areas such as farm, crops and animal monitoring, diseases and pest detection, intelligent farm chemicals application, automatic weeding, aerial survey and mapping, smart irrigation, intelligent produce grading and sorting, among others. These will not only enable farmers to do more with less, but will also improve quality. Obstacles of inadequate technology infrastructure such as broadband internet access, and paucity of a workforce with the right skills exist in Nigeria, but with continuous efforts currently being made, they will be overcome. It is concluded that the application of AI holds great promise for improved productivity and better utilisation of resources.
Quality detection has been a major problem in the agriculture and food industries. This operation... more Quality detection has been a major problem in the agriculture and food industries. This operation is mostly done by a subjective sensory method which is prone to high error and food destruction. Therefore, there is a need to apply artificial intelligence using a machine learning approach. This study developed two intelligent acoustic yam quality detection and classification devices using two sound-generating techniques. The software (multi-wave frequency generator) sound-generating technique generated sound from a laptop to a speaker inside a detecting chamber. This sound passes through the yam and was received on the opposite side by a microphone, into another laptop for analysis using visual analyzer software. The impact sound-generating technique used sound generated from a gentle impact of the yam on a flat surface placed inside the detection chamber. The sound produced was picked up by a microphone into a laptop for analysis. Acoustic properties considered were amplitude, frequ...
Food security is the aspiration of every nation. To achieve this, particularly in Developing Coun... more Food security is the aspiration of every nation. To achieve this, particularly in Developing Countries, there is a need to reduce wastage by storing staple foods grains beyond their production seasons. Longer storage requires human presence, monitoring and control of the storage environment which may be laborious, demanding and sometimes outrightly unsafe. Therefore, the needs to employ automation and artificial intelligence become necessary to control this storage environment. This study developed an automated, intelligent silo bin that controls the storage environment of the system for the small-scale rural farmers, of which over 70% of their population still depend on agriculture, using Internet of Things (IoT). The developed system consists of three units interfaced together. These units are the pro-type 2-ton (2,000 kg) silo structure, the embedded system (made up of the microcontroller, sensors and relays). The system is integrated to an IoT system (made up of mobile application (BLYNK), Wi-Fi module and ultrasonic atomizer) and the air blowing system (consisting of blower fan and heater). The developed smart system was tested and the test run results showed that it successfully monitors and controls storage air temperature, humidity, air pressure, grain moisture, insect infestation and CO 2 levels, the key parameters for long term storability of grains. The coding process could be set to suit different grains and storage conditions required for their effective storage. Although the silo bin structure used for testing was for a particular prototype , it can be geometrically scaled for many silo structures.
Food security is the aspiration of every nation. To achieve this, particularly in Developing Coun... more Food security is the aspiration of every nation. To achieve this, particularly in Developing Countries, there is a need to reduce wastage by storing staple foods grains beyond their production seasons. Longer storage requires human presence, monitoring and control of the storage environment which may be laborious, demanding and sometimes outrightly unsafe. Therefore, the needs to employ automation and artificial intelligence become necessary to control this storage environment. This study developed an automated, intelligent silo bin that controls the storage environment of the system for the small-scale rural farmers, of which over 70% of their population still depend on agriculture, using Internet of Things (IoT). The developed system consists of three units interfaced together. These units are the pro-type 2-ton (2,000 kg) silo structure, the embedded system (made up of the microcontroller, sensors and relays). The system is integrated to an IoT system (made up of mobile application (BLYNK), Wi-Fi module and ultrasonic atomizer) and the air blowing system (consisting of blower fan and heater). The developed smart system was tested and the test run results showed that it successfully monitors and controls storage air temperature, humidity, air pressure, grain moisture, insect infestation and CO 2 levels, the key parameters for long term storability of grains. The coding process could be set to suit different grains and storage conditions required for their effective storage. Although the silo bin structure used for testing was for a particular prototype , it can be geometrically scaled for many silo structures.
Drying is essential to prolong storage life of crops. This study is carried out to provide design... more Drying is essential to prolong storage life of crops. This study is carried out to provide design information for developing a Bambara nut dryer. Bambara nuts samples were condition to 6%, 8%, 10% and 12% db. Pressure drops along depth of 0.2, 0.4, 0.6, 0.8 and 1 m were obtained using a constructed aerodynamic apparatus. Airflow resistances at these depths were calculated for airflow rates of 0.025, 0.035, 0.045, and 0.055 m s. I – Optimal response surface design was used to model and optimize the airflow resistance. Reduces quadratic model was selected among other models to be the best for modeling and optimizing airflow resistance of Bambara nuts. This study showed that airflow rate, bed depth, packing type and moisture content all influenced airflow resistance of Bambara nuts. Optimize airflow resistance values for drying Bambara nuts within and outside the experimental design space were obtained. Cube plots for dryer designers were established for Bambara nuts.
— Accurate scientific data are crucial to efficient design of machines for cleaning, separation, ... more — Accurate scientific data are crucial to efficient design of machines for cleaning, separation, drying and postharvest handling of agricultural materials such as Jatropha seeds. Therefore this study was undertaken to determine the terminal velocity and drag coefficient of native and improved accessions of Jatropha seeds at four moisture content levels (4%, 8%, 12% and 16% db). The aerodynamic properties were determined using theoretical and experimental methods. The experimental method involves the use of a vertical wind tunnel. The values of terminal velocity obtained from the theoretical methods ranged from 5.72 – 13.24m/s for native accession and 6.45 – 13.45m/s for improved accession. On the other hand, values of terminal velocity obtained from the experimental method ranged from 7.98 – 11.08 m/s for native accession and 7.42 – 11.36 m/s for the improved accession. The drag coefficient values obtained from the theoretical methods ranged from 0.27 – 1.67 and 0.292 – 1.474 for the native and improved accessions, respectively. The experimental values of drag coefficient ranged from 0.07 – 0.173 for the native accession and 0.07 – 0.164 for the improved accession. Moisture content was observed to have a significant effect (p < 0.05) on both terminal velocity and drag coefficient. Conversely, the accession had no effect on any of the aerodynamic properties. Means separation using Duncan's Multiple Range Test showed that the difference, for the experimental terminal velocity, lies between 8 to 12% for native accession and 8 to 16% for improved accession. These moisture contents are the points at which the seeds gain significant weight to alter its terminal velocity. Regression equations for determination of terminal velocity and drag coefficient of Jatropha seeds were obtained for different moisture content levels using the mass of the seeds. Keywords— Jatropha, terminal velocity, drag coefficients and moisture content.
The thermal properties of Jatropha seeds were investigated for two accessions and in the moisture... more The thermal properties of Jatropha seeds were investigated for two accessions and in the moisture range of 4 - 16% db. Specific heat was determined using the method of mixtures, bulk thermal diffusivity was determined using the transient method (Dickerson apparatus), while the bulk thermal conductivity was calculated. The results obtained for specific heat ranged from 739.5 – 1560.1J/kg oC for native and 667.4 – 1262.21J/kg oC for improve accessions in the above moisture range. Bulk thermal diffusivity ranged from1.1x10-6 - 1.71x10-6m2/s and 1.29x10-6 m2/s - 1.83X10-6 while bulk thermal conductivity ranged from 0.276 - 0.907 W/moC and 0.283 - 0.797 W/moC for native and improved accessions respectively. ANOVA and means separation (Duncan multiply range test) at 95% confidence level was carried out for specific heat, thermal diffusivity and thermal conductivity. ANOVA showed that moisture had a significant effect on specific heat and bulk thermal conductivity but not on bulk thermal d...
Abstract Automation and Artificial intelligence has been used to solve the world's most compl... more Abstract Automation and Artificial intelligence has been used to solve the world's most complex problems. The goal of this study is to develop, evaluate and optimize cowpea seeds quality detection and separating device to meet international export standards. The design of the device was divided into metering, automation, and conveyor belt outlet unit. An evaluation was done using samples made up of good and bad (impurity) portions. Response surface methodology was used to evaluate, model and optimize the device performance. The optimized results were validated using regression and prediction interval (PI) analysis test. The separating efficiency, throughput, maximum capacity, and actual utilization obtained; range from 68.966–94.118%, 0.5–3 kg/h, 6–36 kg/12 h, 0.083–0.083(8.3%) respectively. These evaluating parameters were significantly affected by the operational factors at P
Selection of agro-waste briquettes/binding agents for domestic and industrial cottage application... more Selection of agro-waste briquettes/binding agents for domestic and industrial cottage applications depends on the fuel properties. In this research work, investigations were carried out on the properties of briquettes produced from corncob, groundnut shells, sawdust and rice husk using three different binding agents namely; cassava starch, bombaxcostatum powdered calyxes and cissuspopulnea thickeners for each of the biodegradable materials, with a view of investigating which of the three binding agents and biodegradable materials examined can be used more efficiently and rationally as fuel. Proximate analyses were carried out to determine the average composition of their constituents. Cylindrical moulds were used to facilitate densification of these biodegradable materials into briquettes using those binding agents separately for each. Result of this work indicated that these briquettes/binding agents made good biomass fuels. However, findings from this research showed that briquettes with starch as binding agents have more positive attributes of biomass fuel than their cissuspopulnea and bombaxcostatum counterparts. For instance, corncob/starch briquette has the lowest mean moisture content of 14.57%, highest mean density of 759kg/m 3 , highest mean volatile matter of 87.73% and highest heating value of 20,258 kJ/kg compared with corncob/cissuspopulneaand corncob/bombaxcostatum briquettes. Rice husk /starch briquette has the lowest mean moisture content;13.06%, highest mean density;787kg/m 3 , highest mean volatile matter; 68.89% and highest heating value;13732kJ/kg compared to rice husk/cissuspopulnea briquette and rice husk/bombaxcostatum briquette. Groundnut shell/starch briquette has the lowest mean moisture content;9.48%, highest mean density; 761kg/m 3 ,highest average volatile matter;61.73% and highest mean heating value;17029 kJ/kg compared with groundnut shell/cissuspopulnea briquette and groundnut shell/bombaxcostatumbriquettev. Similarly, sawdust/starch briquette has the lowest mean moisture content; 8.33%, highest mean density; 765kg/m 3 , highest mean volatile matter; 76.32% ,and highest mean heating value; 17,952 kJ/kg compared with sawdust/cissuspopulnea briquette and sawdust/bombaxcostatum briquette.
Journal of Agricultural Engineering and Biotechnology, 2014
broadcasted while discharge efficiency increased with increase in the size of seeds broadcasted. ... more broadcasted while discharge efficiency increased with increase in the size of seeds broadcasted. Broken efficiency of the device was 2.7%, 8.3% and 10% for soya bean, paddy and guinea corn respectively while discharge efficiency was 91.7%, 92% and 97.5% for paddy, guinea corn and soya bean respectively. This device provides leverage in lifting the agricultural productivity in the area of quick broadcasting.
Springer eBooks: Encyclopedia of Smart Agriculture Technologies, 2023
Definition 1. Silo: A tall, cylindrical storage structure designed to store grain or other agricu... more Definition 1. Silo: A tall, cylindrical storage structure designed to store grain or other agricultural products. 2. Monitoring system: A system that collects and processes data from the sensors and other sources to provide real-time information about the storage environment. 3. Control system: A system that uses the data from the monitoring system to adjust the ventilation, heating, and cooling systems within the silo to maintain optimal storage conditions for the grain. 4. Aeration system: A system that circulates air within the silo to control moisture levels and prevent the growth of mold and mildew. 5. Ventilation system: A system that allows for the controlled exchange of air within the silo to regulate temperature, humidity, and oxygen levels. 6. Grain quality: The condition of the grain in terms of its moisture content, temperature, and freedom from mold, pests, and other contaminants. 7. Grain spoilage: The deterioration of the quality of grain due to factors such as moisture, temperature, pests, or other contaminants.
Journal of Agricultural Engineering and Technology (JAET), 2022
The agriculture sector faces numerous challenges including disease and pest infestation, insuffic... more The agriculture sector faces numerous challenges including disease and pest infestation, insufficient available water, inadequate drainage, declining labour availability and knowledge gap between farmers and technology, leading to low outputs. More and more farmers are starting to adopt new techniques to boost productivity and increase revenue. This paper reviews the applications of artificial intelligence (AI) to agriculture and explores ways that the Nigerian farmers can benefit from this technology. AI-powered solutions have been applied in areas such as farm, crops and animal monitoring, diseases and pest detection, intelligent farm chemicals application, automatic weeding, aerial survey and mapping, smart irrigation, intelligent produce grading and sorting, among others. These will not only enable farmers to do more with less, but will also improve quality. Obstacles of inadequate technology infrastructure such as broadband internet access, and paucity of a workforce with the right skills exist in Nigeria, but with continuous efforts currently being made, they will be overcome. It is concluded that the application of AI holds great promise for improved productivity and better utilisation of resources.
Quality detection has been a major problem in the agriculture and food industries. This operation... more Quality detection has been a major problem in the agriculture and food industries. This operation is mostly done by a subjective sensory method which is prone to high error and food destruction. Therefore, there is a need to apply artificial intelligence using a machine learning approach. This study developed two intelligent acoustic yam quality detection and classification devices using two sound-generating techniques. The software (multi-wave frequency generator) sound-generating technique generated sound from a laptop to a speaker inside a detecting chamber. This sound passes through the yam and was received on the opposite side by a microphone, into another laptop for analysis using visual analyzer software. The impact sound-generating technique used sound generated from a gentle impact of the yam on a flat surface placed inside the detection chamber. The sound produced was picked up by a microphone into a laptop for analysis. Acoustic properties considered were amplitude, frequ...
Food security is the aspiration of every nation. To achieve this, particularly in Developing Coun... more Food security is the aspiration of every nation. To achieve this, particularly in Developing Countries, there is a need to reduce wastage by storing staple foods grains beyond their production seasons. Longer storage requires human presence, monitoring and control of the storage environment which may be laborious, demanding and sometimes outrightly unsafe. Therefore, the needs to employ automation and artificial intelligence become necessary to control this storage environment. This study developed an automated, intelligent silo bin that controls the storage environment of the system for the small-scale rural farmers, of which over 70% of their population still depend on agriculture, using Internet of Things (IoT). The developed system consists of three units interfaced together. These units are the pro-type 2-ton (2,000 kg) silo structure, the embedded system (made up of the microcontroller, sensors and relays). The system is integrated to an IoT system (made up of mobile application (BLYNK), Wi-Fi module and ultrasonic atomizer) and the air blowing system (consisting of blower fan and heater). The developed smart system was tested and the test run results showed that it successfully monitors and controls storage air temperature, humidity, air pressure, grain moisture, insect infestation and CO 2 levels, the key parameters for long term storability of grains. The coding process could be set to suit different grains and storage conditions required for their effective storage. Although the silo bin structure used for testing was for a particular prototype , it can be geometrically scaled for many silo structures.
Food security is the aspiration of every nation. To achieve this, particularly in Developing Coun... more Food security is the aspiration of every nation. To achieve this, particularly in Developing Countries, there is a need to reduce wastage by storing staple foods grains beyond their production seasons. Longer storage requires human presence, monitoring and control of the storage environment which may be laborious, demanding and sometimes outrightly unsafe. Therefore, the needs to employ automation and artificial intelligence become necessary to control this storage environment. This study developed an automated, intelligent silo bin that controls the storage environment of the system for the small-scale rural farmers, of which over 70% of their population still depend on agriculture, using Internet of Things (IoT). The developed system consists of three units interfaced together. These units are the pro-type 2-ton (2,000 kg) silo structure, the embedded system (made up of the microcontroller, sensors and relays). The system is integrated to an IoT system (made up of mobile application (BLYNK), Wi-Fi module and ultrasonic atomizer) and the air blowing system (consisting of blower fan and heater). The developed smart system was tested and the test run results showed that it successfully monitors and controls storage air temperature, humidity, air pressure, grain moisture, insect infestation and CO 2 levels, the key parameters for long term storability of grains. The coding process could be set to suit different grains and storage conditions required for their effective storage. Although the silo bin structure used for testing was for a particular prototype , it can be geometrically scaled for many silo structures.
Drying is essential to prolong storage life of crops. This study is carried out to provide design... more Drying is essential to prolong storage life of crops. This study is carried out to provide design information for developing a Bambara nut dryer. Bambara nuts samples were condition to 6%, 8%, 10% and 12% db. Pressure drops along depth of 0.2, 0.4, 0.6, 0.8 and 1 m were obtained using a constructed aerodynamic apparatus. Airflow resistances at these depths were calculated for airflow rates of 0.025, 0.035, 0.045, and 0.055 m s. I – Optimal response surface design was used to model and optimize the airflow resistance. Reduces quadratic model was selected among other models to be the best for modeling and optimizing airflow resistance of Bambara nuts. This study showed that airflow rate, bed depth, packing type and moisture content all influenced airflow resistance of Bambara nuts. Optimize airflow resistance values for drying Bambara nuts within and outside the experimental design space were obtained. Cube plots for dryer designers were established for Bambara nuts.
— Accurate scientific data are crucial to efficient design of machines for cleaning, separation, ... more — Accurate scientific data are crucial to efficient design of machines for cleaning, separation, drying and postharvest handling of agricultural materials such as Jatropha seeds. Therefore this study was undertaken to determine the terminal velocity and drag coefficient of native and improved accessions of Jatropha seeds at four moisture content levels (4%, 8%, 12% and 16% db). The aerodynamic properties were determined using theoretical and experimental methods. The experimental method involves the use of a vertical wind tunnel. The values of terminal velocity obtained from the theoretical methods ranged from 5.72 – 13.24m/s for native accession and 6.45 – 13.45m/s for improved accession. On the other hand, values of terminal velocity obtained from the experimental method ranged from 7.98 – 11.08 m/s for native accession and 7.42 – 11.36 m/s for the improved accession. The drag coefficient values obtained from the theoretical methods ranged from 0.27 – 1.67 and 0.292 – 1.474 for the native and improved accessions, respectively. The experimental values of drag coefficient ranged from 0.07 – 0.173 for the native accession and 0.07 – 0.164 for the improved accession. Moisture content was observed to have a significant effect (p < 0.05) on both terminal velocity and drag coefficient. Conversely, the accession had no effect on any of the aerodynamic properties. Means separation using Duncan's Multiple Range Test showed that the difference, for the experimental terminal velocity, lies between 8 to 12% for native accession and 8 to 16% for improved accession. These moisture contents are the points at which the seeds gain significant weight to alter its terminal velocity. Regression equations for determination of terminal velocity and drag coefficient of Jatropha seeds were obtained for different moisture content levels using the mass of the seeds. Keywords— Jatropha, terminal velocity, drag coefficients and moisture content.
The thermal properties of Jatropha seeds were investigated for two accessions and in the moisture... more The thermal properties of Jatropha seeds were investigated for two accessions and in the moisture range of 4 - 16% db. Specific heat was determined using the method of mixtures, bulk thermal diffusivity was determined using the transient method (Dickerson apparatus), while the bulk thermal conductivity was calculated. The results obtained for specific heat ranged from 739.5 – 1560.1J/kg oC for native and 667.4 – 1262.21J/kg oC for improve accessions in the above moisture range. Bulk thermal diffusivity ranged from1.1x10-6 - 1.71x10-6m2/s and 1.29x10-6 m2/s - 1.83X10-6 while bulk thermal conductivity ranged from 0.276 - 0.907 W/moC and 0.283 - 0.797 W/moC for native and improved accessions respectively. ANOVA and means separation (Duncan multiply range test) at 95% confidence level was carried out for specific heat, thermal diffusivity and thermal conductivity. ANOVA showed that moisture had a significant effect on specific heat and bulk thermal conductivity but not on bulk thermal d...
Abstract Automation and Artificial intelligence has been used to solve the world's most compl... more Abstract Automation and Artificial intelligence has been used to solve the world's most complex problems. The goal of this study is to develop, evaluate and optimize cowpea seeds quality detection and separating device to meet international export standards. The design of the device was divided into metering, automation, and conveyor belt outlet unit. An evaluation was done using samples made up of good and bad (impurity) portions. Response surface methodology was used to evaluate, model and optimize the device performance. The optimized results were validated using regression and prediction interval (PI) analysis test. The separating efficiency, throughput, maximum capacity, and actual utilization obtained; range from 68.966–94.118%, 0.5–3 kg/h, 6–36 kg/12 h, 0.083–0.083(8.3%) respectively. These evaluating parameters were significantly affected by the operational factors at P
Selection of agro-waste briquettes/binding agents for domestic and industrial cottage application... more Selection of agro-waste briquettes/binding agents for domestic and industrial cottage applications depends on the fuel properties. In this research work, investigations were carried out on the properties of briquettes produced from corncob, groundnut shells, sawdust and rice husk using three different binding agents namely; cassava starch, bombaxcostatum powdered calyxes and cissuspopulnea thickeners for each of the biodegradable materials, with a view of investigating which of the three binding agents and biodegradable materials examined can be used more efficiently and rationally as fuel. Proximate analyses were carried out to determine the average composition of their constituents. Cylindrical moulds were used to facilitate densification of these biodegradable materials into briquettes using those binding agents separately for each. Result of this work indicated that these briquettes/binding agents made good biomass fuels. However, findings from this research showed that briquettes with starch as binding agents have more positive attributes of biomass fuel than their cissuspopulnea and bombaxcostatum counterparts. For instance, corncob/starch briquette has the lowest mean moisture content of 14.57%, highest mean density of 759kg/m 3 , highest mean volatile matter of 87.73% and highest heating value of 20,258 kJ/kg compared with corncob/cissuspopulneaand corncob/bombaxcostatum briquettes. Rice husk /starch briquette has the lowest mean moisture content;13.06%, highest mean density;787kg/m 3 , highest mean volatile matter; 68.89% and highest heating value;13732kJ/kg compared to rice husk/cissuspopulnea briquette and rice husk/bombaxcostatum briquette. Groundnut shell/starch briquette has the lowest mean moisture content;9.48%, highest mean density; 761kg/m 3 ,highest average volatile matter;61.73% and highest mean heating value;17029 kJ/kg compared with groundnut shell/cissuspopulnea briquette and groundnut shell/bombaxcostatumbriquettev. Similarly, sawdust/starch briquette has the lowest mean moisture content; 8.33%, highest mean density; 765kg/m 3 , highest mean volatile matter; 76.32% ,and highest mean heating value; 17,952 kJ/kg compared with sawdust/cissuspopulnea briquette and sawdust/bombaxcostatum briquette.
Journal of Agricultural Engineering and Biotechnology, 2014
broadcasted while discharge efficiency increased with increase in the size of seeds broadcasted. ... more broadcasted while discharge efficiency increased with increase in the size of seeds broadcasted. Broken efficiency of the device was 2.7%, 8.3% and 10% for soya bean, paddy and guinea corn respectively while discharge efficiency was 91.7%, 92% and 97.5% for paddy, guinea corn and soya bean respectively. This device provides leverage in lifting the agricultural productivity in the area of quick broadcasting.
1st International Engineering Conference: Engineering and Technology Approach for Sustainable National Development. FICE 2018 P043. Faculty of Engineering. Federal University of Oye-Ekiti, Nigeria, 2018
In the design of drying, cooling, or aeration systems, accurate data for pressure drop and air fl... more In the design of drying, cooling, or aeration systems, accurate data for pressure drop and air flow resistance are needed. Pressure drop and airflow resistance of Jatropha seeds were investigated for two accessions (native and improved) at four moisture content levels (4%, 8%, 12% and 16% db). They were measured using aerodynamic properties measuring apparatus designed, constructed and validated by the authors. During measurement the seeds were packed at three different densities (from loose fill to dense fill). Air was blown through the apparatus at airflow rate of 0.0456, 0.0638, 0.0817, 0.0997and 0.1178 m 3 /s.m 2 for each packing type with seeds at different depths of 0.2,0.4,0.6,0.8 and 1m. A significant difference was found to exist between the depth and the pressure drop at 95% confidence level. The mean separation shows that pressure drop at different depth along the bed at a particular flow rate are statistically different from each other in all the packing methods and at different moisture contents. The airflow resistance data were calculated only at 1m depth. The experimental data obtained were compared with Shedd model and Ergun model. The Ergun model was further divided into theoretically regression models generated using their physical properties and from the experimental data using regression equation respectively. The coefficients of determination (R 2) and the mean relative percentage error of the air flow resistance prediction (e) were used to evaluate the fit of the models to experimental data. The Ergun regression gave the best fit to experimental data because it has the lowest error values and the highest R 2 values. These orders were also observed in all the packing methods at different moisture content for both accessions. Moisture content was found to have a significant effect on airflow resistance of both accessions of the Jatropha seeds at different packing methods.
2ND International Conference on Green Engineering for Sustainable Development (IC-GESD 2017) Faculty of Engineering, Bayero University, Kano, Nigeria., 2017
Automation of Agricultural operations is one of the latest technological advances in agriculture.... more Automation of Agricultural operations is one of the latest technological advances in agriculture. This study aim is to optimize and generate mathematical models for some optical properties of tiger nuts used for harvest, processing and storage operations. Experimental values were obtained using Konica Minolta Chroma meter CR-410 for colour properties and Jenway 6850UV/Vis Spectrophotometer for absorbance and transmittance properties whereas reflectance property was calculated using Beer-Lambert equation. Experimental design used for colour properties was I-optimum response surface design while that for absorbance, transmittance and reflectance was central composite response surface design. Optical properties value ranges are L (37.16 - 41.88), a (5.18 - 8.18), b (13.04 - 19.04), (3.23 - 5.69%) for absorbance, (2.03x10-6 - 5.88x10-4 %) for reflectance and (0.02 - 0.13%) for transmittance. Linear, quadratic and quartic models were used to optimize L, a and b colour properties respectively while linear and quadratic models were used for absorbance, reflectance and transmittance properties. Optimal design value ranges for colour, absorbance, reflectance and transmittance properties were determined for selection of sensors for harvest, processing and storage equipment or machines. Conclusion of this study showed that colour is the best among all optical properties studied that could be considered for selecting sensors for separating, sorting and grading tiger nuts where as transmittance properties can be considered for bulk sensing. Also good predicting models were developed for predicting values outside the design space.
The proceedings 12th CIGR Section VI International Symposium 22 –25 October, 2018
Automation of sorghum production will increase world food production and improve the economy of p... more Automation of sorghum production will increase world food production and improve the economy of producing countries. Electrical properties of sorghum are used to select sensors and actuators used to automate their production operations like handling, separation and sorting. The objective of this study was to model and optimize some electrical properties of bulk sorghum grains for automation of harvesting, processing and storage operations of sorghum production. Electrical properties of three major varieties (NGB 01907: Red sorghum; NGB 01589: White sorghum; and NGB 01227: yellow sorghum) determined include resistance, conductance, resistivity, conductivity, capacitance, dielectric constant, inductance and capacitance reactance (impedance). The grains were conditioned to four moisture levels (10, 13, 16, 19 and 22% db). These properties were determined by forming different circuits with functional generator, oscilloscope, resistors, capacitors, connecting wires and grains sample holder by passing current frequencies of 1, 500,1000,1500 2000 kHz. Response surface central composite experimental design (CCD) was used for modeling and optimization. Reduced cubic, reduced linear and linear models were chosen, transformed and used to generate polynomial equations. All generated model equations were confirmed (validated) by the use of both mathematical and experimental methods. These generated polynomial equations were used to optimize the electrical properties. Optimized ranges for designing or selecting electrical sensors and actuators for automating harvesting, processing and storage operations, using these electrical properties for sensing was developed. Among the three farm operations studied only processing operation like handling, separation and sorting require values that fall at the middle of all optimized ranges of the electrical properties.
Encyclopedia of Smart Agriculture technology, 2023
Definition 1. Silo: A tall, cylindrical storage structure designed to store grain or other agricu... more Definition 1. Silo: A tall, cylindrical storage structure designed to store grain or other agricultural products. 2. Monitoring system: A system that collects and processes data from the sensors and other sources to provide real-time information about the storage environment. 3. Control system: A system that uses the data from the monitoring system to adjust the ventilation, heating, and cooling systems within the silo to maintain optimal storage conditions for the grain. 4. Aeration system: A system that circulates air within the silo to control moisture levels and prevent the growth of mold and mildew. 5. Ventilation system: A system that allows for the controlled exchange of air within the silo to regulate temperature, humidity, and oxygen levels. 6. Grain quality: The condition of the grain in terms of its moisture content, temperature, and freedom from mold, pests, and other contaminants. 7. Grain spoilage: The deterioration of the quality of grain due to factors such as moisture, temperature, pests, or other contaminants.
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Papers by John Audu