Sustainable control of infestations using image processing and modelling

A sustainable pest control system integrates automated pest detection and recognition to evaluate the pest density using image samples taken from habitats. Novel predator/prey modelling algorithms assess control requirements for the UAV system, which is designed to deliver measured quantities of naturally beneficial predators to combat pest infestations within economically acceptable timeframes. The integrated system will reduce the damaging effect of pests in an infested habitat to an economically acceptable level without the use of chemical pesticides. Plant pest recognition and detection is vital for food security, quality of life and a stable agricultural economy. The research utilises a combination of the k-means clustering algorithm and the correspondence filter to achieve pest detection and recognition. The detection is achieved by partitioning the data space into Voronoi cells, which tends to find clusters of comparable spatial extents, thereby separating the objects (pests) from the background (pest habitat). The detection is established by extracting the variant and distinctive attributes between the pest and its habitat (leaf, stem) and using the correspondence filter to identify the plant pests to obtain correlation peak values for the different datasets. The correspondence filter can achieve rotationally invariant recognition of pests for a full 360 degrees, which proves the effectiveness of the algorithm and provides a count of the number of pests in the image. A series of models has been produced that will permit an assessment of common pest infestation problems and estimate the number of predators that are required to control the problem within a time schedule. A UAV predator deployment system has been designed. The system is offered as a replacement for chemical pesticides to improve peoples’ health opportunities and the quality of food products

Automatic plant pest detection and recognition using k-means clustering algorithm and correspondence filters

Plant pest recognition and detection is vital for food security, quality of life and a stable agricultural economy. This research demonstrates the combination of the k-means clustering algorithm and the correspondence filter to achieve pest detection and recognition. The detection of the dataset is achieved by partitioning the data space into Voronoi cells, which tends to find clusters of comparable spatial extents, thereby separating the objects (pests) from the background (pest habitat). The detection is established by extracting the variant distinctive attributes between the pest and its habitat (leaf, stem) and using the correspondence filter to identify the plant pests to obtain correlation peak values for different datasets. This work further establishes that the recognition probability from the pest image is directly proportional to the height of the output signal and inversely proportional to the viewing angles, which further confirmed that the recognition of plant pests is a function of their position and viewing angle. It is encouraging to note that the correspondence filter can achieve rotational invariance of pests up to angles of 360 degrees, which proves the effectiveness of the algorithm for the detection and recognition of plant pests

Biological control of taro scarab beetle (Papuanauninodis Coleoptera: Scarabaeidae) instars via Scoliid and Voria Tachinidae parasitoid wasps

Scoliid and Voria Tachinidae parasitoid wasps are shown to be able to control the population of the Taro Scarab beetle (Papuanauninodis, Coleoptera: Scarabaeidae) larvae using a newly created continuous-time simulation model based on non-linear ordinary differential equations that track the populations of the beetle’s life cycle stages: egg, larva, pupa, adult and the populations of the two parasitoid wasps. Due to the fact that the scarab beetles are, relatively speaking, long lived it is challenging to drive down the adult population below the environmental carrying capacity. Mortality and predator/prey capture rates are modelled using the Weibull and Pascal probability distribution functions, respectively. We suggest the use of a virus or fungi to drive down the population of the adult beetles, the ambition being to avoid the use of pesticides so as to produce higher quality food that doesn’t damage human health via chemical residues

Eco control of agro pests using imaging, modelling & natural predators

Caterpillars in their various forms: size, shape, and colour cause significant harm to crops and humans. This paper offers a solution for the detection and control of caterpillars through the use of a sustainable pest control system that does not require the application of chemical pesticides, which damage human health and destroy the naturally beneficial insects within the environment. The proposed system is capable of controlling 80% of the population of caterpillars in less than 65 days by deploying a controlled number of larval parasitoid wasps (Cotesia Flavipes, Cameron) into the crop environment. This is made possible by using a continuous time model of the interaction between the caterpillar and the Cotesia Flavipes (Cameron) wasps using a set of simultaneous, non-linear, ordinary differential equations incorporating natural death rates based on the Weibull probability distribution function. A negative binomial distribution is used to model the efficiency and the probability that the wasp will find and parasitize a host larva. The caterpillar is presented in all its life-cycle stages of: egg, larva, pupa and adult and the Cotesia Flavipes (Cameron) wasp is present as an adult larval parasitoid. Biological control modelling is used to estimate the quantity of the Cotesia Flavipes (Cameron) wasps that should be introduced into the caterpillar infested environment to suppress its population density to an economically acceptable level within a prescribed number of days. Keywords

Sustainable control of Anopheles mosquito population

Despite the widespread use of insecticides, community engagement programmes and preventive measures mosquito borne diseases are growing and new tools to prevent the spread of disease are urgently needed. An alternative control measure for the eradication of Anopheles mosquitoes is suggested by the use of a Sustainable Control Model, which demonstrates the capability of Odonata, a natural beneficial predator, to exercise control over Anopheles mosquitoes in less than 140 days

Experimental design and construction of an enhanced solar battery charger

A Solar Battery Charger circuit is designed, built and tested. It acts as a control circuit to monitor and regulate the process of charging several batteries ranging from 4 volts to 12 volts, using a photovoltaic (PV) solar panel as the input source for the battery charging process. The circuit is economical and can be easily constructed from discrete electronic components. The circuit operation is based on matching the solar panel terminal load voltage to the input terminal of the charging circuit and the appropriate number of battery cell units to be charged to the output circuit through the use of a current limited voltage regulator, allowing fast charging while limiting heat build-up and gassing and a rotary switch for easy selection of the appropriate voltage depending on the solar light intensity. Experimental results indicate that there is an increase of the overall charging current when fully charging an empty: mobile phone battery and a 6v rechargeable lamp for 4 hours using direct charging between 10.00am to 4.00pm. The success of this device will bridge the gap of power failure that often occur within the hours of the day between 10.00am to 4.00pm, especially in rural communities

Zonal evaluation for siting a solar power plant in Cross River State, Nigeria

An experimental survey was embarked upon to establish the effect of solar radiation intensity, the panel power output, current density and the efficiency of solar panels in three major geographical zones in Cross River State, Nigeria. The zones are Mangrove, University of Calabar, Tropical Rainforest, Nko - Yakurr and Guinea Savanna, Abakpa - Ogoja. The result from the investigation shows that the Guinea Savanna produced the highest current density of 8.20 A/cm2, power output of 152.3W, 36.5% efficiency and a solar radiation magnitude of 991.9 W/m2 from a monocrystalline panel. However, polycrystalline panel generated better output for all the measured parameters thus: current density of 8.80 A/cm2, power output of 170.72 W, 39.9% efficiency range for the same solar radiation magnitude of 991.9W/m2. From the analysis of the survey performed across the three geographical zones. The Mangrove zone has shown greater potential to accommodate solar farms, hence generate good energy to bridge the vacuum created in the power generating sector.Keywords: Epileptic supply, mangrove zone, solar farm, output power, panels efficienc

Modelling the control of African armyworm (Spodoptera exempta) infestations in cereal crops by deploying naturally beneficial insects

A solution was sought for control of Spodoptera exempta in cereal crops. The proposed solution enhanced a previous scheme since it provided control of the pest eggs and larvae and improved the quality of crop products by replacing pesticides. The scheme consists of a surveillance and monitoring system to activate a measured response to pest invasion. In the control phase naturally beneficial insects (NBIs) were deployed via an unmanned aerial vehicle (UAV) system to control the pest population; parasite egg wasps (Trichogramma) were combined with a larval parasite Diptera (Tachinidae) to achieve greater control of the life cycle stages of the African Armyworm e Spodoptera exempta