Functional Sustainability of a Flight Dynamics Control System for Stable Hovering Flight of an Unmanned Aerial Vehicle(UAV),such as in Agricultural Applications:Mathematical Modeling and Simulation

The simulation of a control system for the longitudinal axis of the rotary or fixed-wing unmanned aerial vehicles(UAVs)is demonstrated in this study.The control unit includes design considerations of two controllers to provide robust stability,tracking of the proposed linear dynamics,an adequate set of proportional-integral-derivative(PID)controller gains,and a minimal cost function.The PID control and linear quadratic regulator(LQR)with or without full-state-observer were evaluated.An optimal control system is assumed to provide fast rise and settling time,minimize overshoot,and eliminate the steady-state error.The effectiveness of this approach was verified by a linear model of the UAV aircraft in the semi-dynamic simulation platform of Matlab/Simulink,in which the open-loop system was assessed in terms of flight robustness and reference tracking.The experimental results show that the proposed controllers effectively improve the configuration of the control system of the plant,maintain the sustainability of the dynamic flight model stability,and diminish the flight controller errors.The LQR provides robust stability,but it is not optimal in the transient phase of particular plant output.The PID control system can adjust the controller’s gains for optimal hovering(or stable slow flight)and is especially useful for the tracking system.Finally,comparing aircraft stability using PID and LQR controllers shows that the latter has less overshoot and a shorter settling time;in addition,all proposed controllers can be practically deployed as one UAV’s system,which can be handled as an exemplary model of the UAV flight management system.

Quantification of the adulteration concentration of palm kernel oil in virgin coconut oil using near-infrared hyperspectral imaging

The adulteration concentration of palm kernel oil(PKO)in virgin coconut oil(VCO)was quantified using near-infrared(NIR)hyperspectral imaging.Nowadays,some VCO is adulterated with lower-priced PKO to reduce production costs,which diminishes the quality of the VCO.This study used NIR hyperspectral imaging in the wavelength region 900-1,650 nm to create a quantitative model for the detection of PKO contaminants(0-100%)in VCO and to develop predictive mapping.The prediction equation for the adulteration of VCO with PKO was constructed using the partial least squares regression method.The best predictive model was pre-processed using the standard normal variate method,and the coefficient of determination of prediction was 0.991,the root mean square error of prediction was 2.93%,and the residual prediction deviation was 10.37.The results showed that this model could be applied for quantifying the adulteration concentration of PKO in VCO.The prediction adulteration concentration mapping of VCO with PKO was created from a calibration model that showed the color level according to the adulteration concentration in the range of 0-100%.NIR hyperspectral imaging could be clearly used to quantify the adulteration of VCO with a color level map that provides a quick,accurate,and non-destructive detection method.

Joint Biomedical Entity and Relation Extraction Based on Multi-Granularity Convolutional Tokens Pairs of Labeling

Extracting valuable information frombiomedical texts is one of the current research hotspots of concern to a wide range of scholars.The biomedical corpus contains numerous complex long sentences and overlapping relational triples,making most generalized domain joint modeling methods difficult to apply effectively in this field.For a complex semantic environment in biomedical texts,in this paper,we propose a novel perspective to perform joint entity and relation extraction;existing studies divide the relation triples into several steps or modules.However,the three elements in the relation triples are interdependent and inseparable,so we regard joint extraction as a tripartite classification problem.At the same time,fromthe perspective of triple classification,we design amulti-granularity 2D convolution to refine the word pair table and better utilize the dependencies between biomedical word pairs.Finally,we use a biaffine predictor to assist in predicting the labels of word pairs for relation extraction.Our model(MCTPL)Multi-granularity Convolutional Tokens Pairs of Labeling better utilizes the elements of triples and improves the ability to extract overlapping triples compared to previous approaches.Finally,we evaluated our model on two publicly accessible datasets.The experimental results show that our model’s ability to extract relation triples on the CPI dataset improves the F1 score by 2.34%compared to the current optimal model.On the DDI dataset,the F1 value improves the F1 value by 1.68%compared to the current optimal model.Our model achieved state-of-the-art performance compared to other baseline models in biomedical text entity relation extraction.

Quantitative and Qualitative Responses of Hydroponic Tomato Production to Different Levels of Salinity

From economic and nutritional points of view,tomato is,historically,considered one of the most important crops.Without significant yield reduction,most commercial cultivars of tomato crops are sensitive to moderate levels of salinity.However,high levels of salt stress can negatively affect the yield and quality of tomato fruits.Therefore,this study was conducted to evaluate the yield and fruit quality of three tomato cultivars(Forester,Ghandowra-F1,and Feisty-Red)cultivated hydroponically,under three different levels of nutrient solution salinity.Evaluation of tomato fruits was performed based on quantity(number and weight of fruits,and total fruit yield),physical quality(color andfirmness),and chemical quality(refractometric index“Brix”,pH,EC,K^(+),Na^(+),and NO_(3)-).Experiments were conducted using three salinity levels of the nutrient solution with electrical conductivity values(dSm^(-1))of 2.5(control),6.0,and 9.5.Results showed that the studied tomato cultivars were significantly influenced by high salinity(9.5 dSm^(-1))in comparison to the low(2.5 dSm^(-1))and medium(6.0 dSm^(-1))levels of salinity.On average,the highest fruit weight per plant of 1944.84 g and total fruit yield of 4.42 kgm^(-2) were observed at the low salinity level;however,no significant differences were obtained in the two yield factors(single fruit weight and total fruit yield)for the low and medium salinity levels.On the other hand,a significant reduction in tomato yield(31%)was associated with the high salinity level compared to the yield at low and medium salinity levels.Results of physical quality parameters showed highly significant differences among all salinity levels.On average,the maximum value of color change(1.72)was associated with the medium salinity level,and the maximum value offirmness(9.61 Ncm^(-1))was recorded at the high salinity level.Salinity levels and tomato cultivars introduced significant differences in chemical quality parameters;however,no significant differences in these parameters were attributed to the low and medium salinity levels.The maximum value of pH was recorded for the combination of medium salinity and Forester cultivar.Moreover,the maximum values of Brix,EC,K^(+),Na^(+),and NO_(3)^(-) were recorded for the Ghandowra-F1 cultivar at the high salinity level.Unlike the Feisty-Red,the performance of the Forester and Ghandowra-F1 cultivars was found to be acceptable at the tested medium salinity level(6.0 dSm^(-1)).

Effect of Saline Water on Soil Acidity, Alkalinity and Nutrients Leaching in Sandy Loamy Soil in Rwamagana Bella Flower Farm, Rwanda

The necessity to saline and sodic waters is sometimes used for irrigating agricultural activities under certain circumstances, but it is important to note that the use of these waters comes with specific considerations and limitations. One way to decrease undesirable effects of sodic waters on the physical and chemical properties of soils is to apply organic and chemical amendments within the soil. This study aimed to assess the effectiveness of saline water on soil acidity, alkalinity and nutrients leaching in sandy loamy soil at Bella flower farm, in Rwamagana District, Rwanda. The water used was from the Muhazi Lake which is classified as Class I (Saline water quality). Column leaching experiments using treated soils were then conducted under saturated conditions. The soil under experimental was first analyzed for its textural classification, soil properties and is classified as sandy loamy soil. The t-test was taken at 1%, 5% and 10% levels of statistical significance compared to control soil. The results indicated that the application of saline water to soils caused an increase in some soil nutrients like increase of Phosphorus (P), Potassium (K+), Magnesium (Mg2+), Sulphur (S), CN ratio and Sodium (Na+) and decreased soil texture, physical and chemical properties and remained soil nutrients. Consequently, the intensive addition of saline water leachates to soil in PVC pipes led to decreased of soil EC through leaching and a raiser Soluble Sodium Percentage (SSP). The rate of saline water application affected the increase accumulation of SAR and Na% in the top soil layers. The study indicated that saline water is an inefficient amendment for sandy soil with saline water irrigation. The study recommends further studies with similar topic with saline water irrigation, as it accentuated the alkalinity levels.

Development of a Framework for Equipment Health Management in the Mining Industries in Zambia

The Zambian mining industry is crucial to the national economy but struggles with inconsistent equipment maintenance practices. This study developed an Equipment Maintenance Management Framework (EMMF) tailored to the industry’s needs. Using surveys, interviews, and on-site visits at eight major mining companies, we identified significant variations in maintenance strategies, CMMS usage, and reliability engineering. The EMMF prioritizes predictive maintenance, efficient CMMS implementation, ongoing training, and robust reliability engineering to shift from reactive to proactive maintenance. We recommend adopting continuous improvement practices and data-driven decision-making based on performance metrics, with a phased EMMF implementation aligning maintenance with strategic business objectives. This framework is poised to enhance operational efficiency, equipment reliability, and safety, fostering sustainable growth in the Zambian mining sector.

Design and Development of a Parabolic Trough Solar Air Heater for a Greenhouse Dryer

Design and Development of a Parabolic Trough Solar Air Heater (PTSAH) for a Greenhouse Dryer (GD) was done to improve the dryer’s performance. The materials used for the fabrication of the PTSAH included galvanized sheets covered with aluminium foil, an absorber tube made of GI pipe painted matt black to increase heat absorbance at the focal line, mild steel square tubes, shutter plywood, and an axial fan to push air through the absorber tube. Key geometrical parameters used for the design of the PTSAH were a rim angle of 98 degrees, focal length of 0.2608 m, height of 0.3451 m, length of 2 m, and an aperture width of 1.2 m. The PTSAH’s total aperture surface area was 2.4 m2, while its absorber tube surface area was 0.1587 m2. The PTSAH was experimentally tested to establish its thermal performance. It was found that the ambient air recorded an average value of 31.1˚C and that the air heater could increase the air temperature by 45.6˚C above ambient with a thermal efficiency of 5.3%. It can, therefore, be concluded that the PTSAH can significantly improve the performance of a GD by supplying the GD with air at a higher temperature than ambient.

Dynamics of Potable Well Water Quality in Key Mining Chiefdoms in Kono District, Eastern Sierra Leone

Groundwater is increasingly being used due to its universal availability and generally good quality. However, the risk of contamination of groundwater due to various human activities such as mining is equally increasing across the globe. In this study, the physical parameters of potable well waters in the key mining areas in Nimikoro and Tankoro Chiefdoms in Kono District were analyzed for compliance with drinking water quality standard. To do this, both unpurged and purged well water samples were collected once every month for a period of one year. Some of the well water properties like temperature, Total Dissolved Solids (TDS) and Electrical Conductivity (EC) were measured on site and others determined in the laboratory. The data collected from the laboratory analyses were statistically analyzed in MS Excel, SPSS and ArcGIS environments for quality trends in time-space fabric. The results showed that well water quality in the study area generally fell short of drinking water quality standards of Sierra Leone and WHO. There were high temperature and turbidity during the dry season and then high TDS and EC during the rainy season. Temperature and turbidity also significantly influenced well water quality in the study area, much more than TDS and EC. The implications for drinking water of lower quality than the standard could be huge for the local population and therefore needs the attention of stakeholders in the study area and decision makers in the country.

Assessing Mechanical Properties of Natural Fibre Reinforced Composites for Engineering Applications

Mechanical properties of ukam, banana, sisal, coconut, hemp and e-glass fibre reinforced laminates were evaluated to assess the possibility of using it as new material in engineering applications. Samples were fabricated by the hand lay-up process (30:70 fibre and matrix ratio by weight) and the properties evaluated using the INSTRON material testing system. The mechanical properties were tested and showed that glass laminate has the maximum tensile strength of 63 MPa, bending strength of 0.5 MPa, compressive strength of 37.75 MPa and the impact strength of 17.82 J/m2. The ukam plant fibre laminate has the maximum tensile strength of 16.25 MPa and the impact strength of 9.8J/m among the natural fibres;the sisal laminate has the maximum compressive strength of 42 MPa and maximum bending strength of 0.0036 MPa among the natural fibres. Results indicated that natural fibres are of interest for low-cost engineering applications and can compete with artificial glass fibres (E-glass fibre) when a high stiffness per unit weight is desirable. Results also indicated that future research towards significant improvements in tensile and impact strength of these types of composites should focus on the optimisation of fibre strength rather than interfacial bond strength.

Evaluation of the WEPP Model in a Belgian Agricultural Watershed

The physically based WEPP （Water Erosion Prediction Project） model was implemented in a small agricultural watershed located in central Belgium, called Ganspoel. The watershed, mainly agricultural and resulting in a smooth topography, covers about 115 ha in a landscape typical of large parts of central Europe. Seventeen runoff, peak flow and sediment yield events, collected during a 2-year monitoring period, were simulated by the model. Even though the runoff volume predictions were well correlated to the corresponding observations, WEPP prediction capability was generally unsatisfactory also when different set-up methods of the soil effective hydraulic conductivity were used. The poor performance achieved for runoff volume and peak flow simulations affected sediment yield predictions. The differences between observed and simulated values for runoff, peak flow and sediment yield events may depend on： i） the great number of small runoff and sediment yield events within the available database with which is associated large natural variation and which in many cases are not well reproduced by WEPP; ii） the lack of model calibration processes; iii） the scarceness of information about some important soil physical and hydrological parameters; iv） the land use heterogeneity and crop schedule complexity of the Ganspoel watershed.

Sentinel-2 Satellite Imagery Application to Monitor Soil Salinity and Calcium Carbonate Contents in Agricultural Fields

The estuary tides affect groundwater dynamics;these areas are susceptible to waterlogging and salinity issues.A study was conducted on two fields with a total area of 60 hectares under a center pivot irrigation system that works with solar energy and belong to a commercial farm located in Northern Sudan.To monitor soil salinity and calcium carbonate in the area and stop future degradation of soil resources,easy,non-intrusive,and practical procedures are required.The objective of this study was to use remote sensing-determined Sentinel-2 satellite imagery using various soil indices to develop prediction models for the estimation of soil electrical conductivity(EC)and soil calcium carbonate(CaCO_(3)).Geo-referenced soil samples were collected from 72 locations and analyzed in the laboratory for soil EC and CaCO_(3).The electrical conductivity of the soil saturation paste extract was represented by average values in soil dataset samples from two fields collected from the topsoil layer(0 to 15 cm)characteristic of the local salinity gradient.The various soil indices,used in this study,were calculated from the Sentinel-2 satellite imagery.The prediction was determined using the root mean square error(RMSE)and cross validation was done using coefficient of determination.The results of regression analysis showed linear relationships with significant correlation between the EC analyzed in laboratory and the salinity index-2“SI2”(Model-1:R^(2)=0.59,p=0.00019 and root mean square error(RMSE=1.32%)and the bare soil index“BSI”(Model-2:R^(2)=0.63,p=0.00012 and RMSE=6.42%).Model-1 demonstrated the best model for predicting soil EC,and validation R^(2)and RMSE values of 0.48%and 1.32%,respectively.The regression analysis results for soil CaCO_(3)determination showed linear relationships with data obtained in laboratory and the bare soil index“BSI”(Model-3:R^(2)=0.45,p=0.00021 and RMSE=1.29%)and the bare soil index“BSI”&Normalized difference salinity index“NDSI”(Model-4:R^(2)=0.53,p=0.00015 and RMSE=1.55%).The validation confirmed the Model-3 results for prediction of soil CaCO_(3)with R^(2)and RMSE values of 0.478%and 1.29%,respectively.Future soil monitoring programs might consider the use of remote sensing data for assessing soil salinity and CaCO_(3)using soil indices results generated from satellite image(i.e.,Sentinel-2).

Application of Zinc, Iron and Boron Enhances Productivity and Grain Biofortification of Mungbean

Deficiencies of essential vitamins,iron(Fe),and zinc(Zn)affect over one-half of the world’s population.A significant progress has been made to control micronutrient deficiencies through supplementation,but new approaches are needed,especially to reach the rural poor.Agronomic biofortification of pulses with Zn,Fe,and boron(B)offers a pragmatic solution to combat hidden hunger instead of food fortification and supplementation.Moreover,it also has positive effects on crop production as well.Therefore,we conducted three separate field experiments for two consecutive years to evaluate the impact of soil and foliar application of the aforementioned nutrients on the yield and seed biofortification of mungbean.Soil application of Zn at 0,4.125,8.25,Fe at 0,2.5,5.0 and B at 0,0.55,1.1 kg ha−1 was done in the first,second and third experiment,respectively.Foliar application in these experiments was done at 0.3%Zn,0.2%Fe and 0.1%B respectively one week after flowering initiation.Data revealed that soil-applied Zn,Fe and B at 8.25,5.0 and 1.1 kg ha−1,respectively,enhanced the grain yield of mungbean;however,this increase in yield was statistically similar to that recorded with Zn,Fe and B at 4.125,2.5 and 0.55 kg ha−1,respectively.Foliar application of these nutrients at flower initiation significantly enhanced the Zn contents by 28%and 31%,Fe contents by 80%and 78%,while B contents by 98%and 116%over control during 2019 and 2020,respectively.It was concluded from the results that soil application of Zn,Fe,and B enhanced the yield performance of mungbean;while significant improvements in seed Zn,Fe,and B contents were recorded with foliar application of these nutrients.

Improving Quantitative and Qualitative Characteristics of Wheat (Triticum aestivum L.) through Nitrogen Application under Semiarid Conditions

Nitrogen(N),the building block of plant proteins and enzymes,is an essential macronutrient for plant functions.A field experiment was conducted to investigate the impact of different N application rates(28,57,85,114,142,171,and 200 kg ha^(−1))on the performance of spring wheat(cv.Ujala-2016)during the 2017–2018 and 2018–2019 growing seasons.A control without N application was kept for comparison.Two years mean data showed optimum seed yield(5,461.3 kg ha^(−1))for N-application at 142 kg ha^(−1) whereas application of lower and higher rates of N did not result in significant and economically higher seed yield.A higher seed yield was obtained in the 2017–2018(5,595 kg ha^(−1))than in the 2018–2019(5,328 kg ha^(−1))growing seasons under an N application of 142 kg ha^(−1).It was attributed to the greater number of growing degree days in the first(1,942.35°C days)than in the second year(1,813.75°C).Higher rates of N(171 and 200 kg ha^(−1))than 142 kg ha^(−1) produced more number of tillers(i.e.,948,300 and 666,650 ha^(−1),respectively).However,this increase did not contribute in achieving higher yields.Application of 142,171,and 200 kg ha^(−1) resulted in 14.15%,15.0%and 15.35%grain protein concentrations in comparison to 13.15%with the application of 114 kg ha^(−1).It is concluded that the application of N at 142 kg ha^(−1) could be beneficial for attaining higher grain yields and protein concentrations of wheat cultivar Ujala-2016.

Evaluation of land suitability for Moringa oleifera tree cultivation by using Geospatial technology:The case of Dhidhessa Catchment,Abay Basin,Ethiopia

Land suitability analysis of Moringa oleifera tree cultivation is important to enhance its product,as the demand forthis tree for medicinal values and food sources is increasing worldwide.Therefore,this study aimed to assess suitableland for Moringa oleifera tree cultivation by using the integration of multi-criteria evaluation with geospatialtechnologies in the Dhidhessa catchment,western Ethiopia.Five parameters,namely:slope,land use and landcover(LULC),soil texture,land surface temperature,and rainfall data,were used in this study.The land suitabilityevaluation of Moringa oleifera is classified into three classes as highly suitable,moderately suitable,and notsuitable.The results revealed that,about 344.4 km2(12.2%)of the area is categorized into highly suitable,and2343.7 km2(83%)is moderately suitable for Moringa tree,whereas,137.2 km2(4.9%)is categorized as notsuitable for Moringa oleifera tree cultivation.Hence,based on the finding of the study,we suggested that farmers andother stakeholders can cultivate Moringa oleifera trees in the Dhidhessa catchment.

Estimation of Genetic Divergence and Character Association Studies in Local and Exotic Diversity Panels of Soybean(Glycine max L.)Genotypes

The availability of favorable genetic diversity is a thriving vitality for the success of a breeding program.It provides a firm basis of selecting superior breeding lines for the development of high yielding crop genotypes.In this context,present investigation aimed to generate information on genetic divergence and character association in a diversity panel of 123 local and exotic soybean genotypes.Analysis of variance revealed significant response of the evaluated genotypes based on studied attributes.It depicted the probability of selecting desirable soybean genotypes by focusing on character association studies and genetic diversity analysis.Correlation analysis revealed that seed yield per plant showed high positive correlation with 100-seed weight followed by pods per plant and plant height.Furthermore,path coefficient analysis exposed that pods per plant had maximum direct contribution in seed yield per plant followed by 100-seed weight,days to flowering and SPAD measurement.Genotype named“G-10”showed maximum yield per plant followed by 24607,G-52,24593,Arisoy,24566,17426,A-3127,24570 and 24567.Genetic diversity analysis grouped the evaluated germplasm into 17 clusters.All clusters showed zero intra-cluster variability;while inter-cluster divergence ranged from 9.00 to 91.11.Cluster V showed maximum inter-cluster distance with cluster XII followed by that of between V and VIII.Moreover,cluster IV with superior genotypes(G-10,24607,24593 and 24566),VI(17426 and 24567),XIII(24570)and X(Arisoy and G-52)showed above mean values for most of the studied characters.Overall,the results of hybridization between the superior genotypes of these cluster pairs might be useful for soybean breeding with improving agronomic traits and adaptability.

Physicochemical Characterization of Settling Particulate Matter and Sediments

The thrust of this research study was to ascertain the physicochemical characteristic in settling particulate matter and sediments of samples collected from the wellington industrial estate flood plains;the main of objectives are as follows: to determine the hydrogen ion index (pH) of the samples collected in the study area, to determine the electrical conductivity (EC) of the samples collected from the same location. Samples were collected from six locations (at varying depths of 0 - 5 cm and 5 - 10 cm) sample area 1 (Wellington Industrial Estate Area 1) WIEA1 WIEA 2, WIEA 3, WIEA 4, WIEA 5 and WIEA 6 and were given laboratory treatment. A laboratory thermometer was used to determine temperature of the samples when collected;(Dakton model) pH meter equipment and a Toledo electrical conductivity meter were used to determine the pH and EC respectively. The results indicated that the samples were acidic (low pH) and the conductivity of the samples was of medium and low range. This therefore expressed low levels of soluble metal ions in the environment that have effect on plants, animals and other organisms, agricultural and domestic activities in the environment under investigation. Hence bioconcentration and biomagnification are highly likely in these locations.

Evaluating the Impacts of Climate Variability on Cocoa Production in the Western Centre of Cote d’Ivoire during 1979-2010

Climate variability impacts on cocoa production are evaluated for the first time using 31 years (1979-2010) of data from SODEXAM (climate ground- based observations) and the ex-CAISTAB in three main cocoa production regions (Goh, Marahoué, and Haut-Sassandra) in the west-central part of Cote d’Ivoire. The work is a contribution to improving the quality of climate services dedicated to cocoa cultivation to ensure producers’ income and improve the yield of the production in the west-central part of Cote d’Ivoire. The results show that cocoa production is affected by the changes and variability in climate conditions (i.e. rainfall and temperature). In the Goh region, the increase in cocoa production seems to be mostly related to the augmentation of rainfall amount while in Marahoué, the increase in temperature is identified to have a more significant impact. Over the Haut-Sassandra region, both temperature and rainfall seem to have a considerable effect on the changes in cocoa production. The analysis based on linear regression by least-squares fit shows two characteristic modes (low and high-frequency variability) in the relationships between cocoa production and meteorological conditions suggesting a strong temporal signal impact related to the changes in the emblazoned surfaces. This leads to an important impact of the short-term variations of climate in cocoa production whereas, the influence of the long-term variability in climate on the cocoa yield seems marginal.

Climate Trends and Their Impact on Sorghum Production in Marigat, Baringo County: A Historical Analysis

Climate is subject to fluctuations in the majority of the world, mainly caused by rainfall as well as temperature variations. Climate fluctuations in Kenya have resulted in the spread of desert-like conditions in the ASALs region, such as Marigat in Baringo County. As a county, Baringo experiences great variations in climate annually, as well as uncertainty in expected rains, thereby negatively impacting the production of crops such as sorghum. This study applied the rainfall anomaly index (RAI), standardised precipitation evapotranspiration index (SPEI), standard precipitation index (SPI), and Mann-Kendall (MK) statistical test for trends on historical climatic data in analysing both temperature and precipitation data over the period 1990 to 2022 to determine their trend, patterns and how they affect the production of sorghum crops. The machine learning method (R studio) with inputs was used to calculate the SPI, SPEI, RAI and MK trend test. The rainfall varied from below average to above average during the study period with no clear pattern in the RAI, SPEI and SPI values. The years 2020 and 2000 stood out as they had higher and lower rainfall than usual, respectively. The Marigat area generally experienced more rainfall during the high/long rainfall season (AMJJ). The MK trend test on average monthly rainfall, SOND, AMJJ, and annual precipitation confirmed a positive trend in precipitation. However, the short rainy season (SOND) was found to be the most variable period for rainfall, and there was a slight increase in daily average temperatures during this season.

GIS-Based Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP) Techniques to Derive Flood Risks Management on Rice Productivity in Gishari Marshland

Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodologies by analyzing their temporal and spatial development. This study therefore attempts to employ the GIS-based multi-criteria decision analysis and analytical hierarchy process techniques to derive the flood risks management on rice productivity in the Gishari Agricultural Marshland in Rwamagana district, Rwanda. Here, six influencing potential factors to flooding, including river slope, soil texture, Land Use Land Cover through Land Sat 8, rainfall, river distance and Digital Elevation Model are considered for the delineation of flood risk zones. Data acquisition like Landsat 8 images, DEM, land use land cover, slope, and soil class in the study area were considered. Results showed that if the DEM is outdated or inaccurate due to changes in the terrain, such as construction, excavation, or erosion, the predicted flood patterns might not reflect the actual water flow. This could result unexpected flood extents and depths, potentially inundating rice fields that were not previously at risk and this, expectedly explained that the increase 1 m in elevation would reduce the rice productivity by 0.17% due to unplanned flood risks in marshland. It was found that the change in rainfall distribution in Gishari agricultural marshland would also decrease the rice productivity by 0.0018%, which is a sign that rainfall is a major factor of flooding in rice scheme. Rainfall distribution plays a crucial role in flooding analysis and can directly impact rice productivity. Oppositely, another causal factor was Land Use Land Cover (LULC), where the Multivariate Logistic Regression Model Analysis findings showed that the increase of one unit in Land Use Land Cover would increase rice productivity by 0.17% of the total rice productivity from the Gishari Agricultural Marshland. Based on findings from these techniques, the Gishari Agricultural Marshlands having steeped land with grassland is classified into five classes of flooding namely very low, low, moderate, high, and very high which include 430%, 361%, 292%, 223%, and 154%. Government of Rwanda and other implementing agencies and major key actors have to contribute on soil and water conservation strategies to reduce the runoff and soil erosion as major contributors of flooding.

Effects of Biomimetic Surface Designs on Furrow Opener Performance

The effects of biomimetic designs of tine furrow opener surface on equivalent pressure and pressure in the direction of motion on opener surface against soil were studied by finite element method (FEM) simulation and the effects of these designs on tool force and power requirements were examined experimentally.Geometrical structures of the cuticle surfaces of dung beetle (Copris ochus Motschulsky) were examined by stereoscopy.The structures of the cuticle surfaces and Ultra High Mo- lecular Weight Polyethylene (UHMWPE) material were modeled on surface of tine furrow opener as biomimetic designs.Seven furrow openers were analyzed in ANSYS program (a FEM simulation software).The biomimetic furrow opener surfaces with UHMWPE structures were found to have lower equivalent pressure and pressure in the direction of motion as compared to the conventional surface and to the biomimetic surfaces with textured steel-35 structures.It was found that the tool force and power were increased with the cutting depth and operating speed and the biomimetic furrow opener with UHMWPE tubular section ridges showed the lowest resistance and power requirement against soil..