Bioecology of a major pest of Arabica coffee in Eastern Africa highlands, the african coffee white stem borer, Monochamus leuconotus (Coleoptera: Cerambycidae)

For the last 50 years, coffee production has been in constant decline for major producing countries of Eastern Africa, like Kenya and Tanzania. Factors explaining this decline include high production costs, especially costs for fertilizers and pesticides, which led many smallholders to phase out of coffee farming. The African coffee white stem borer (CWSB), Monochamus leuconotus (Pascoe) (Coleoptera: Cerambycidae) appears to be a growing threat in those countries and a significant cause of coffee farming abandonment. CWSB damages coffee trees, mainly by ring barking and wood boring, leading to low yields and dieback under high infestation. Insecticides that have proven to be effective for CWSB control in the past are banned today, and coffee smallholders are poorly equipped to resolve the threat. An urgent need for action has been recognized in different countries of the region to provide scientifically-sound and practical strategies for the management of CWSB. However, available knowledge of the pest bioecology still suffers gaps that need to be filled to achieve this objective. For 4 years now, the coffee pest project at International Centre of Insect Physiology and Ecology (icipe) in Kenya has undertaken research dedicated to CWSB bioecology. The present communication reviews this research and gives some basic unpublished life history traits. A rearing method with an artificial diet has been developed that allowed the description of CWSB life cycle and feeding and reproductive behaviours, and the assessment of the pest demographic parameters. Field surveys in smallholder coffee farms located on elevation gradients on Kilimanjaro, Tanzania allowed the characterization of the pest population dynamics and showed impact of agro-ecological factors such as elevation, shade and microclimate. Recommendations for a more efficient and sustainable management of this major pest are proposed based on existing knowledge along with results obtained at icipe. (Résumé d'auteur

Predicting the impact of temperature increase on the distribution of the variegated coffee bug, Antestiopsis thunbergii over an elevation gradient

The antestia bug Antestiopsis thunbergii (Gmelin 1790) is one of most damaging pests of Arabica coffee in eastern and southern Africa. It feeds on coffee vegetative parts and fruits, leading to yield and quality reduction. The present study aims to predict the impact of temperature increase on the distribution and abundance of A. thunbergii over an elevation gradient, ranging from 1000 to 1700 m asl, located on Mt. Kilimanjaro, Tanzania. Temperature-dependent phenology models were developed using a complete life table study at 7 constant temperatures. Three indices assessing infestation risk were computed and mapped over the elevation gradient using the phenology models and temperature data for year 2013 and predictions for 2055 (AFRICLIM database): 1) the establishment risk index (ERI), which characterizes the suitability of a geographical area for the insect establishment, 2) the generation index (GI), which estimates the mean number of generations per year, and 3) the activity index (AI), which indicates the population growth rate. Under 2055 temperature predictions, the ERI will decrease by 0.13 at elevations between 1000 and 1100 m asl, and increase by 0.24 between 1500 and 1700 m asl, indicating that high elevations will be more suitable for antestia bug establishment in the future. The number of generations per year will remain constant at elevations between 1000-1100 m asl, but will increase by one generation between 1500-1700 m asl. By 2055, the AI will increase by 1.71 at high elevations leading to higher population growth as a result of temperature rising. These results globally indicate a risk of increasing antestia bug infestation in the highest coffee producing areas of East Africa highlands in the coming decades. These areas are renowned for the high quality of their coffee and mitigation strategies against climate change are therefore needed to minimize the antestia bug risk. (Résumé d'auteur

Prediction of insect pest distribution as influenced by elevation: Combining field observations and temperature-dependent development models for the coffee stink bug, Antestiopsis thunbergii (Gmelin)

The antestia bug, Antestiopsis thunbergii (Gmelin 1790) is a major pest of Arabica coffee in Africa. The bug prefers coffee at the highest elevations, contrary to other major pests. The objectives of this study were to describe the relationship between A. thunbergii populations and elevation, to elucidate this relationship using our knowledge of the pest thermal biology and to predict the pest distribution under climate warming. Antestiopsis thunbergii population density was assessed in 24 coffee farms located along a transect delimited across an elevation gradient in the range 1000–1700 m asl, on Mt. Kilimanjaro, Tanzania. Density was assessed for three different climatic seasons, the cool dry season in June 2014 and 2015, the short rainy season in October 2014 and the warm dry season in January 2015. The pest distribution was predicted over the same transect using three risk indices: the establishment risk index (ERI), the generation index (GI) and the activity index (AI). These indices were computed using simulated life table parameters obtained from temperature-dependent development models and temperature data from 1) field records using data loggers deployed over the transect and 2) predictions for year 2055 extracted from AFRICLIM database. The observed population density was the highest during the cool dry season and increased significantly with increasing elevation. For current temperature, the ERI increased with an increase in elevation and was therefore distributed similarly to observed populations, contrary to the other indices. This result suggests that immature stage susceptibility to extreme temperatures was a key factor of population distribution as impacted by elevation. In the future, distribution of the risk indices globally indicated a decrease of the risk at low elevation and an increase of the risk at the highest elevations. Based on these results, we concluded with recommendations to mitigate the risk of A. thunbergii infestation

Comparison of the temporal efficacy of Aquatain surface films for the control ofAnopheles arabiensisandOchlerotatus caspiuslarvae from Sudan

Aquatain mosquito formulation (AMF) is a surfactant that spreads across the surface of water bodies to produce a monomolecular film. This study experimentally evaluates the temporal efficacy of AMF against aquatic stages of Anopheles arabiensis and Ochlerotatus caspius under laboratory conditions. Using the recommended application dose of 1 ml m−2, a large species-specific difference in the median lethal time for L3–L4 larvae was observed. The median lethal time to 50% mortality (LT50) and 90% mortality (LT90) was 1.3 h, 95% CI [1.2, 1.4] and 3.8 h, 95% CI [3.6, 4.0], respectively, for Oc. caspius. The corresponding values for An. arabiensis were 8.1 h, 95% CI [7.3, 9.0] and 59.6 h, 95% CI [48.5, 76.2]. Based on data from published laboratory studies for a total of seven mosquito species, drawn from four genera, results in the following three groups, [LT50 = 1–2 h, Culex quinquefasciatus, Ochlerotatus caspius] [LT50 = 8–24, hours, Anopheles minimus, Anopheles arabiensis, Anopheles gambiae s.s.] and [LT50 = 72–143 h, Anopheles stephensi, Aedes aegypti]. In all experiments, 100% mortality was achieved given sufficient time. The potential relevance of mortality rate estimates, in the context of other studies, on the use of monomolecular films for the control of malaria and arbovirus diseases is discussed

Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model

The development of a large-scale metabolic model of Escherichia coli (E. coli) is very crucial to identify the potential solution of industrially viable productions. However, the large-scale kinetic parameters estimation using optimization algorithms is still not applied to the main metabolic pathway of the E. coli model, and they’re a lack of accuracy result been reported for current parameters estimation using this approach. Thus, this research aimed to estimate large-scale kinetic parameters of the main metabolic pathway of the E. coli model. In this regard, a Local Sensitivity Analysis, Segment Particle Swarm Optimization (Se-PSO) algorithm, and the Enhanced Segment Particle Swarm Optimization (ESe-PSO) algorithm was adapted and proposed to estimate the parameters. Initially, PSO algorithm was adapted to find the globally optimal result based on unorganized particle movement in the search space toward the optimal solution. This development then introduces the Se-PSO algorithm in which the particles are segmented to find a local optimal solution at the beginning and later sought by the PSO algorithm. Additionally, the study proposed an Enhance Se-PSO algorithm to improve the linear value of inertia weigh

Review: machine and deep learning methods in Malaysia for COVID-19

The global pandemic of the coronavirus disease COVID-19 has impacted a variety of operations. This dilemma is also attributable to the lockdown measures taken by the afflicted nations. The entire or partial shutdown enacted by nations across the globe affected the majority of hospitals and clinics until the pandemic was contained. The judgements made by the authorities of each impacted nation vary based on a number of variables, including the nation's severity of reported cases, the availability of vaccines, beds in intensive care unit (ICU), staff number, patient number, and medicines. Consequently, this work offers a thorough analysis of the most recent machine learning (ML) and deep learning (DL) approaches for COVID-19 that can assist the medical field in offering quick and exact COVID-19 diagnosis in Malaysia. This research aims to review the machine learning and deep learning methods that were used to help diagnose COVID-19 in Malaysia

A Comparison of Particle Swarm optimization and Global African Buffalo Optimization

The performance of Particle Swarm Optimization (PSO) brings attention to the field of algorithms when deals with different optimization problems. Due to her simple implementation, small consumption, and very effective in finding a solution in many problems, (PSO) becomes well known to the field of algorithms. In addition, the late proposed algorithms mostly are compared to the well-known algorithm such as PSO. Thus, the Global African Buffalo Optimization (GABO) was proposed lately and yet not been compared to the old well-known algorithms in terms of accuracy and time consumption. However, in this paper, a comparison between Particle Swarm Optimization (PSO) and Global African Buffalo Optimization (GABO) algorithms was performed. Five different nonlinear equations with their upper and lower boundaries values were selected as the test optimization functions problem in addition to PSO was applied to real case study. The experimental results illustrated the differences in the performances of both algorithms toward the optimum solution. At the end of the experiments, the PSO algorithm quickly convergence towards the optimum solution using a few particles and iterations rather than GABO. However, the experimental result showed that PSO achieved good results in all the test cases within a short time. In many cases, PSO and GABO are promising optimization methods

Predicting the habitat suitability and distribution of two species of mound-building termites in Nigeria using bioclimatic and vegetation variables

Temperature is an important factor determining the abundance, distribution and diversity of termite species. Thus, termites are affected by changing climate and have to adopt different means of surviving in order to avoid extinction. Using termite occurrence data, bioclimatic variables and vegetation cover, we modelled and predicted the current and future habitat suitability for mound-building termites in Nigeria. Of the 19 bioclimatic variables and the vegetation index (NDVI) tested, only six were significant and eligible as predictors of habitat suitability for the mound-building termites Macrotermes subhyalinus and M. bellicosus. Under current climatic conditions (2022), the northwest, northeast and central regions are highly suitable for M. subhyalinus, while the distribution of M. bellicosus decreased in the North West, North East and in the Central region. However, regarding habitat suitability for the future (2050), there was a predicted range expansion into suitable areas for the two termite species. The increase in temperature due to global warming has an effect which can either result in migration or sometimes extinction of termite species within an ecosystem. Here, we have predicted habitat suitability for the two mound-building termite species under current and future climatic scenarios, and how the change in climatic variables would lead to an expansion in their range across Nigeria.The University of Pretoria, The South African National Research Foundation (NRF) Incentive Funding for Rated Researchers (IFRR), Y-Rated Research Grant, PI grant from South African Research Chair in Mathematical Methods in Bioengineering and Biosciences (M2B3), Alexander von Humboldt’s Georg Foster HERMES Experienced Research Fellowship, a University of Pretoria Postgraduate Bursary and the Nigerian Tertiary Education Trust Fund (TETFund).https://www.mdpi.com/journal/diversityhj2023Zoology and Entomolog

Influence of implant-abutment angulations and crown material on stress distribution on central incisor: a 3D FEA

Aim: To investigate the effect of implant-abutment angulation and crown material on stress distribution of central incisors. Finite element method was used to simulate the clinical situation of a maxillary right central incisor restored by two different implant-abutment angulations, 15° and 25°, using two different crown materials (IPS E-Max CAD and zirconia). Methods: Two 3D finite element models were specially prepared for this research simulating the abutment angulations. Commercial engineering CAD/CAM package was used to model crown, implant abutment complex and bone (cortical and spongy) in 3D. Linear static analysis was performed by applying a 178 N oblique load. The obtained results were compared with former experimental results. Results: Implant Von Mises stress level was negligibly changed with increasing abutment angulation. The abutment with higher angulation is mechanically weaker and expected to fail at lower loading in comparison with the steeper one. Similarly, screw used with abutment angulation of 25° will fail at lower (about one-third) load value the failure load of similar screw used with abutment angulated by 15°. Conclusions: Bone (cortical and spongy) is insensitive to crown material. Increasing abutment angulation from 15° to 25°, increases stress on cortical bone by about 20% and reduces it by about 12% on spongy bone. Crown fracture resistance is dramatically reduced by increasing abutment angulation. Zirconia crown showed better performance than E-Max one