Search results for: crop modelling

Authors: Madelaine Venzon, Dany S. S. L. Amaral, André L. Perez, Natália S. Diaz, Juliana A. Martinez Chiguachi, Maira C. M. Fonseca, James D. Harwood, Angelo Pallini

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Integrating strategies of sustainable crop production and promoting the provisioning of ecological services on farms and within rural landscapes is a challenge for today’s agriculture. Habitat management, through increasing vegetational diversity, enhances heterogeneity in agroecosystems and has the potential to improve the recruitment of natural enemies of pests, which promotes biological control services. In tropical agroecosystems, however, there is a paucity of information pertaining to the resources provided by associated plants and their interactions with natural enemies. The maintenance of non-crop plants integrated into and/or surrounding crop fields provides the farmer with a low-investment option to enhance biological control. We carried out field experiments in chili pepper agroecosystems with small stakeholders located in the Zona da Mata, State of Minas Gerais, Brazil, from 2011 to 2015 where we assessed: (a) whether non-crop plants within and around chili pepper fields affect the diversity and abundance of aphidophagous species; (b) whether there are direct interactions between non-crop plants and aphidophagous arthropods; and (c) the importance of non-crop plant resources for survival of Coccinellidae and Chrysopidae species. Aphidophagous arthropods were dominated by Coccinellidae, Neuroptera, Syrphidae, Anthocoridae and Araneae. These natural enemies were readily observed preying on aphids, feeding on flowers or extrafloral nectaries and using plant structures for oviposition and/or protection. Aphid populations were lower on chili pepper fields associated with non-crop plants that on chili pepper monocultures. Survival of larvae and adults of different species of Coccinellidae and Chrysopidae on non-crop resources varied according to the plant species. This research provides evidence that non-crop plants in chili pepper agroecosystems can affect aphid abundance and their natural enemy abundance and survival. It is also highlighting the need for further research to fully characterize the structure and function of plant resources in these and other tropical agroecosystems. Financial support: CNPq, FAPEMIG and CAPES (Brazil).

Keywords: Conservation biological control, aphididae, Coccinellidae, Chrysopidae, plant diversification

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Authors: Joseph Sello Kau, Elias Mashayamombe, Brian Washington Madinkana, Cynthia Ngwane

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This paper presents the results for the statistical (stepwise linear regression and multiple regression) analyses, carried out on a number of crops in order to evaluate how the decision for crop choice affect the level of farm income generated by the farmers participating in the High Value Crop production (referred to as the HVC). The goal of the HVC is to encourage farmers cultivate fruit crops. The farmers received planting material from different extension agencies, together with other complementary packages such as fertilizer, garden tools, water tanks etc. During the surveys, it was discovered that a significant number of farmers were cultivating traditional crops even when their plot sizes were small. Traditional crops are competing for resources with high value crops. The results of the analyses show that farmers cultivating fruit crops, maize and potatoes were generating high income than those cultivating spinach and cabbage. High farm income is associated with plot size, access to social grants and gender. Choice for a crop is influenced by the availability of planting material and the market potential for the crop. Extension agencies providing the planting materials stand a good chance of having farmers follow their directives. As a recommendation, for the farmers to cultivate more of the HVCs, the ARC must intensify provision of fruit trees.

Keywords: farm income, nature of extension services, type of crops cultivated, fruit crops, cabbage, maize, potato and spinach

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Authors: Arega Shumetie Ademe, Belay Kassa, Degye Goshu, Majaliwa Mwanjalolo

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Currently the world economy is suffering from one critical problem, climate change. Some studies done before identified that impact of the problem is region specific means in some part of the world (temperate zone) there is improvement in agricultural performance but in some others like in the tropics there is drastic reduction in crop production and crop income. Climate variability is becoming dominant cause of short-term fluctuation in rain-fed agricultural production and income of developing countries. The purely rain-fed Ethiopian agriculture is the most vulnerable sector to the risks and impacts of climate variability. Thus, this study tried to identify impact of climate variability on crop income of smallholders in Ethiopia. The research used eight rounded unbalanced panel data from 1994- 2014 collected from six villages in the study area. After having all diagnostic tests the research used fixed effect method of regression. Based on the regression result rainfall and temperature deviation from their respective long term averages have negative and significant effect on crop income. Other extreme devastating shocks like flood, storm and frost, which are sourced from climate variability, have significant and negative effect on crop income of households’. Parameters that notify rainfall inconsistency like late start, variation in availability at growing season, and early cessation are critical problems for crop income of smallholder households as to the model result. Given this, impact of climate variability is not consistent in different agro-ecologies of the country. Rainfall variability has similar impact on crop income in different agro-ecology, but variation in temperature affects cold agro-ecology villages negatively and significantly, while it has positive effect in warm villages. Parameters that represent rainfall inconsistency have similar impact in both agro-ecologies and the aggregate model regression. This implies climate variability sourced from rainfall inconsistency is the main problem of Ethiopian agriculture especially the crop production sub-sector of smallholder households.

Keywords: climate variability, crop income, household, rainfall, temperature

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Authors: Zeenat Rupawalla, Nicole Robinson, Susanne Schmidt, Sijie Li, Selina Carruthers, Elodie Buisset, John Roles, Ben Hankamer, Juliane Wolf

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Agriculture has radically changed the global biogeochemical cycle of nitrogen (N). Fossil fuel-enabled synthetic N-fertiliser is a foundation of modern agriculture but applied to soil crops only use about half of it. To address N-pollution from cropping and the large carbon and energy footprint of N-fertiliser synthesis, new technologies delivering enhanced energy efficiency, decarbonisation, and a circular nutrient economy are needed. We characterised algae fertiliser (AF) as an alternative to synthetic N-fertiliser (SF) using empirical and modelling approaches. We cultivated microalgae in nutrient solution and modelled up-scaled production in nutrient-rich wastewater. Over four weeks, AF released 63.5% of N as ammonium and nitrate, and 25% of phosphorous (P) as phosphate to the growth substrate, while SF released 100% N and 20% P. To maximise crop N-use and minimise N-leaching, we explored AF and SF dose-response-curves with spinach in glasshouse conditions. AF-grown spinach produced 36% less biomass than SF-grown plants due to AF’s slower and linear N-release, while SF resulted in 5-times higher N-leaching loss than AF. Optimised blends of AF and SF boosted crop yield and minimised N-loss due to greater synchrony of N-release and crop uptake. Additional benefits of AF included greener leaves, lower leaf nitrate concentration, and higher microbial diversity and water holding capacity in the growth substrate. Life-cycle-analysis showed that replacing the most effective SF dosage with AF lowered the carbon footprint of fertiliser production from 2.02 g CO₂ (C-producing) to -4.62 g CO₂ (C-sequestering), with a further 12% reduction when AF is produced on wastewater. Embodied energy was lowest for AF-SF blends and could be reduced by 32% when cultivating algae on wastewater. We conclude that (i) microalgae offer a sustainable alternative to synthetic N-fertiliser in spinach production and potentially other crop systems, and (ii) microalgae biofertilisers support the circular nutrient economy and several sustainable development goals.

Keywords: bioeconomy, decarbonisation, energy footprint, microalgae

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Larry V. Aceres, Jesryl B. Paulite, Emelie M. Pelicano, J. B. Anciano, J. A. Esteban

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Enhancing the population of beneficial arthropods under less diverse agroecosystem is the most sought by many researchers and plant growers. This strategy was done through the establishment of pintoi peanut, Arachis pintoi as live mulch or cover crop in pummelo orchard of the University of Southeastern Philippines (USeP), Mabini, Compostela Valley Province, Philippines. This study was conducted to compare and compute population dynamics and diversity of beneficial arthropods in pummelo in with and without Arachis pintoi cover crop. Data collections were done for the 12-month period (from June 2013 to May 2014) at the pummelo orchard of USeP Mabini Campus, COMVAL Province, Philippines and data were analyzed using the Independent Samples T-Test to compare the effect of the presence and absence of Arachis pintoi on beneficial arthropods incidence in pummelo orchard. Moreover, diversity and family richness analyses were computed using the Margalef’s diversity index for family richness; the Shannon index of general diversity and the evenness index; and the Simpson index of dominance. Results revealed numerically and statistically higher density of important beneficial arthropods such as microhymenopterans, macrohymenopterans, spiders, tachinid flies and ground beetles were recorded in pummelo orchard with Arachis pintoi than from without Arachis pintoi cover crop for the 12-month observation period. Further, the result of the study revealed the high family richness and diversity index with more or less even distribution of individuals within the family and low dominance index were documented in pummelo with Arachis pintoi cover crop than from pummelo without Arachis pintoi cover crop. The study revealed that planting A. pintoi in pummelo orchard could enhance natural enemy populations.

Keywords: Arachis pintoi, cover crop, beneficial arthropods, pummelo

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Authors: Nadeem Munawar, Tariq Mahmood

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Habitat manipulation is an important technique that can be used for controlling rodent damage in agricultural ecosystems. It involves intentionally manipulation of vegetation cover in adjacent habitats around the active burrows of rodents to reduce shelter, food availability and to increase predation pressure. The current study was conducted in the Pothwar Plateau during the respective non-crop period of wheat-groundnut (post-harvested and un-ploughed/non-crop fallow lands) with the aim to assess the impact of the reduction in vegetation height of adjacent habitats (field borders) on rodent’s richness and abundance. The study area was divided into two sites viz. treated and non-treated. At the treated sites, habitat manipulation was carried out by removing crop cache, and non-crop vegetation’s over 10 cm in height to a distance of approximately 20 m from the fields. The trapping sessions carried out at both treated and non-treated sites adjacent to wheat-groundnut fields were significantly different (F 2, 6 = 13.2, P = 0.001) from each other, which revealed that a maximum number of rodents were captured from non-treated sites. There was a significant difference in the overall abundance of rodents (P < 0.05) between crop stages and between treatments in both crops. The manipulation effect was significantly observed on damage to crops, and yield production resulted in the reduction of damage within the associated croplands (P < 0.05). The outcomes of this study indicated a significant reduction of rodent population at treated sites due to changes in vegetation height and cover which affect important components, i.e., food, shelter, movements and increased risk sensitivity in their feeding behavior; therefore, they were unable to reach levels where they cause significant crop damage. This method is recommended for being a cost-effective and easy application.

Keywords: agricultural ecosystems, crop damage, habitat manipulation, rodents, trapping

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Authors: A. H. Nanher, N. P. Singh

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In India, Agriculture is largely in rice- based cropping system. It has indicated decline in factor productivity along with emergence of multi - nutrient deficiency, buildup of soil pathogen and weed flora because it operates and removes nutrients from the same rooting depth. In designing alternative cropping systems, the common approaches are crop intensification, crop diversification and cultivar options. The intensification leads to the diversification of the cropping system. Intensification is achieved by introducing an additional component crop in a pre-dominant sequential system by desirable adjustments in cultivars of one or all the component crops. Invariably, this results in higher land use efficiency and productivity per unit time Crop Diversification through such crop and inclusion of fodder crops help to improve the economic situation of small and marginal farmers because of higher income. Inclusion of crops in sequential and intercropping systems reduces some obnoxious weeds through formation of canopies due to competitive planting pattern and thus provides an opportunity to utilize cropping systems as a tool of weed management with non-chemical means. Use of organic source not only acts as supplement for fertilizer (nitrogen) but also improve the physico-chemical properties of soils. Production and use of nitrogen rich biomass offer better prospect for supplementing chemical fertilizers on regular basis. Such biological diversity brings yield and economic stability because of its potential for compensation among components of the system. In a particular agro-climatic and resource condition, the identification of most suitable crop sequence is based on its productivity, stability, land use efficiency as well as production efficiency and its performance is chiefly judged in terms of productivity and net return.

Keywords: integrated farming systems, sustainable intensification, system of crop intensification, wheat

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Authors: Iqra Yaseen

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One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

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Authors: Muleya Nqobile, Winston Garira

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We presented a compartmental deterministic multi-scale model which encompass internal plant defensive mechanism and pathogen interaction, then we consider nesting the model into the epidemiological model. The objective was to improve our understanding of the transmission dynamics of within host and between host of Guignardia citricapa Kiely. The inflow of infected class was scaled down to individual level while the outflow was scaled up to average population level. Conceptual model and mathematical model were constructed to display a theoretical framework which can be used for predicting or identify disease pattern.

Keywords: epidemiological model, mathematical modelling, multi-scale modelling, immunological model

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Authors: Tshilidzi C. Manyanya, Nthaduleni S. Nethengwe, Edmore Kori

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The UNFCCC, FAO, GCF, IPCC and other global structures advocate for agro-ecology do address food security and sovereignty. However, most of the expected outcomes concerning agro-ecological were not empirically tested for universal application. Agro-ecology is theorised to increase crop health over ago-ecological farms and decrease over conventional farms. Increased crop health means increased carbon sequestration and thus less CO2 in the atmosphere. This is in line with the view that global warming is anthropogenically enhanced through GHG emissions. Agro-ecology mainly affects crop health, soil carbon content and yield on the cultivated land. Economic sustainability is directly related to yield capacity, which is theorized to increase by 3-10% in a space of 3 - 10 years as a result of agro-ecological implementation. This study aimed to empirically assess the practicality and validity of these assumptions. The study utilized mainly GIS and RS techniques to assess the effectiveness of agro-ecology in crop health improvement from satellite images. The assessment involved a longitudinal study (2013 – 2015) assessing the changes that occur after a farm retrofits from conventional agriculture to agro-ecology. The assumptions guided the objectives of the study. For each objective, an agro-ecological farm was compared with a conventional farm in the same climatic conditional occupying the same general location. Crop health was assessed using satellite images analysed through ArcGIS and Erdas. This entailed the production of NDVI and Re-classified outputs of the farm area. The NDVI ranges of the entire period of study were thus compared in a stacked histogram for each farm to assess for trends. Yield capacity was calculated based on the production records acquired from the farmers and plotted in a stacked bar graph as percentages of a total for each farm. The results of the study showed decreasing crop health trends over 80% of the conventional farms and an increase over 80% of the organic farms. Yield capacity showed similar patterns to those of crop health. The study thus showed that agro-ecology is an effective strategy for crop-health improvement and yield increase.

Keywords: agro-ecosystem, conventional farm, dialectical, sustainability

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Authors: Baha Hasan, Jan Wikander

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This paper describes a part of the integrating work between assembly design and assembly process planning domains (APP). The work is based, in its first stage, on modelling assembly features to support APP. A multi-layer architecture, based on feature-based modelling, is proposed to establish a dynamic and adaptable link between product design using CAD tools and APP. The proposed approach is based on deriving “specific function” features from the “generic” assembly and form features extracted from the CAD tools. A hierarchal structure from “generic” to “specific” and from “high level geometrical entities” to “low level geometrical entities” is proposed in order to integrate geometrical and assembly data extracted from geometrical and assembly modelers to the required processes and resources in APP. The feature concept, feature-based modelling, and feature recognition techniques are reviewed.

Keywords: assembly feature, assembly process planning, feature, feature-based modelling, form feature, ontology

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R²) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: time series modelling, ARIMA model, river runoff, Karkheh River, CLS method

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Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

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The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model

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Authors: Jan M. Mari

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Safflower is a renowned drought tolerant oil seed crop. Previously its flowers were used for cooking and herbal medicines in China and it was cultivated by small growers for his personal needs of oil. A field study was conducted at experimental field, faculty of crop protection, Sindh Agricultural University Tandojam, during winter, 2012-13, to observe ecological effect on aphid population in safflower crop. Aphid population gradually increased with the growth of safflower. It developed with maximum aphid per leaf on 3rd week of February and it decreased in March as crop matured. A non-significant interaction was found with temperature of aphid, zigzag and hoverfly, respectively and a highly significant interaction with temperature was found with 7-spotted, lacewing, 9-spotted, and Brumus, respectively. The data revealed the overall mean population of zigzag was highest, followed by 9-spotted, 7-spotted, lace wing, hover fly and Brumus, respectively. In initial time the predator and prey ratio indicated that there was not a big difference between predator and prey ratio. After January 1st, the population of aphid increased suddenly until 18th February and it established a significant difference between predator prey ratios. After that aphid population started decreasing and it affected ratio between pest and predators. It is concluded that biotic factors, 7-spotted, zigzag, 9-spotted Brumus and lacewing exhibited a strong and positive correlation with aphid population. It is suggested that aphid pest should be monitored regularly and before reaching economic threshold level augmentation of natural enemies may be managed.

Keywords: aphid, ecology, population, safflower

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Authors: Nidhi Gaur, Padmaja Joshi, Vijay Jain, Rajeev Srivastava

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Web application architecture is important to achieve the desired performance for the application. Performance analysis studies are conducted to evaluate existing or planned systems. Web applications are used by hundreds of thousands of users simultaneously, which sometimes increases the risk of server failure in real time operations. We use Coloured Petri Net (CPN), a very powerful tool for modelling dynamic behaviour of a web application system. CPNs extend the vocabulary of ordinary Petri nets and add features that make them suitable for modelling large systems. The major focus of this work is on server side of web applications. The presented work focuses on modelling restructuring aspects, with major focus on concurrency and architecture, using CPN. It also focuses on bringing out the appropriate architecture for web and database servers given the number of concurrent users.

Keywords: coloured Petri Nets (CPNs), concurrent users, per- formance modelling, web application architecture

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Authors: H. Parameshwar Naik, Shripad Kulkarni

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Powdery mildew is a serious disease among the fungal in high humid areas with varied temperature conditions. In recent days disease becomes very severe due to uncertain weather conditions and unique character of the disease is, it produces white mycelia growth on upper and lower leaf surfaces and in severe conditions it leads to defoliation. Results of the experiment revealed that sowing of crop in the I fortnight (FN) of July recorded the minimum mean disease severity (7.96 %) followed by crop sown in II FN of July (13.19 %) as against the crop sown in II FN of August (41.44 %) and I FN of September (33.78 %) and the I fortnight of October (33.77 %). In the first date of sowing infection started at 45 DAS and progressed till 73 DAS and it was up to 14.66 Percent and in second date of sowing disease progressed up to 22.66 percent and in the third date of sowing, it was up to 59.35 percent. Afterward, the disease started earlier and progressed up to 66.15 percent and in sixth and seventh date of sowing disease progressed up to 43.15 percent and 59.85 percent respectively. Disease progress is very fast after 45 days after sowing and highest disease incidence was noticed at 73 DAS irrespective of dates of sowing. From the results of the present study, it is very clear that disease development will be very high if crop sown in between 1st fortnight of August and the 1st fortnight of September.

Keywords: cucumber, India, Karnataka, powdery mildew

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Authors: Melike Sultan Karasu Asnaz, Ayse Ozdogan Dolcek

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Crop drying, which aims to reduce the moisture content to a certain level, is a method used to extend the shelf life and prevent it from spoiling. One of the oldest food preservation techniques is open sunor shade drying. Even though this technique is the most affordable of all drying methods, there are some drawbacks such as contamination by insects, environmental pollution, windborne dust, and direct expose to weather conditions such as wind, rain, hail. However, solar dryers that provide a hygienic and controllable environment to preserve food and extend its shelf life have been developed and used to dry agricultural products. Thus, foods can be dried quickly without being affected by weather variables, and quality products can be obtained. This research is mainly devoted to investigating the modelling of drying kinetics of cantaloupe in a forced convection solar dryer. Mathematical models for the drying process should be defined to simulate the drying behavior of the foodstuff, which will greatly contribute to the development of solar dryer designs. Thus, drying experiments were conducted and replicated five times, and various data such as temperature, relative humidity, solar irradiation, drying air speed, and weight were instantly monitored and recorded. Moisture content of sliced and pretreated cantaloupe were converted into moisture ratio and then fitted against drying time for constructing drying curves. Then, 10 quasi-theoretical and empirical drying models were applied to find the best drying curve equation according to the Levenberg-Marquardt nonlinear optimization method. The best fitted mathematical drying model was selected according to the highest coefficient of determination (R²), and the mean square of the deviations (χ^²) and root mean square error (RMSE) criterial. The best fitted model was utilized to simulate a thin layer solar drying of cantaloupe, and the simulation results were compared with the experimental data for validation purposes.

Keywords: solar dryer, mathematical modelling, drying kinetics, cantaloupe drying

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Authors: J. Fernandez de Canete, S. Fernandez-Calvo, I. García-Moral

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This paper presents and discusses the application of the object-oriented modelling software SIMSCAPE to hydraulic systems, with particular reference to multivariable proportional-integral-derivative (PID) control. As a result, a particular modelling approach of a double cylinder-piston coupled system is proposed and motivated, and the SIMULINK based PID tuning tool has also been used to select the proper controller parameters. The paper demonstrates the usefulness of the object-oriented approach when both physical modelling and control are tackled.

Keywords: object-oriented modeling, multivariable hydraulic system, multivariable PID control, computer simulation

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Authors: Zoja Raud, Valery Vodovozov

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Modelling and simulation provide effective way to acquire engineering experience. An active approach to modelling and simulation proposed in the paper involves, beside the compulsory part directed by the traditional step-by-step instructions, the new optional part basing on the human’s habits to design thus stimulating the efforts towards success in active learning. Computer exercises as a part of engineering curriculum incorporate a set of effective activities. In addition to the knowledge acquired in theoretical training, the described educational arrangement helps to develop problem solutions, computation skills, and experimentation performance along with enhancement of practical experience and qualification.

Keywords: modelling, simulation, engineering education, electronics, active learning

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Authors: Nathenal Thomas Lambamo

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Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

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Authors: Emmanuel Olasope Bamigboye, Ismail Oladeji Oladosu

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Local people of south-western Nigeria like in other climes, continue to be confronted with the vagaries of changing environments. Through the modification of existing practice and shifting resource base, their strategies for coping with change have enabled them to successfully negotiate the shifts in climate change and the environment. This article analyses indigenous adaptation strategies for climate change with a view to enhancing sustainable crop farming in south –western Nigeria. Multi-stage sampling procedure was used to select 340 respondents from the two major ecological zones (Forest and Derived Savannah) for good geographical spread. The article draws on mixed methods of qualitative research, literature review, field observations, informal interview and multinomial logit regression to capture choice probabilities across the various options of climate change adaptation options among arable crop farmers. The study revealed that most 85.0% of the arable crop farmers were males. It also showed that the use of local climate change adaptation strategies had no relationship with the educational level of the respondents as 77.3% had educational experiences at varying levels. Furthermore, the findings showed that seven local adaptation strategies were commonly utilized by arable crop farmers. Nonetheless, crop diversification, consultation with rainmakers and involvement in non-agricultural ventures were prioritized in the order of 1-3, respectively. Also, multinomial logit analysis result showed that at p ≤ 0.05 level of significance, household size (P<0.08), sex (p<0.06), access to loan(p<0.16), age(p<0.07), educational level (P<0.17) and functional extension contact (P<0.28) were all important in explaining the indigenous climate change adaptation utilized by the arable crops farmers in south-western Nigeria. The study concluded that all the identified local adaptation strategies need to be integrated into the development process for sustainable climate change adaptation.

Keywords: crop diversification, climate change, adaptation option, sustainable, small farmers

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Authors: Najla Kamergi

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In a world context of increasing interest in environmental issues, this paper investigates the effect of agri-environmental regulations heterogeneity on the volume of crop commodities’ exports using a theoretically justified gravity model of Anderson and van Wincoop (2003) for the 2003–2013 period. Our findings show that the difference in exporter and importer environmental regulations is more relevant to agricultural trade than trade agreements. In fact, the environmental gap between the two partners is decreasing slightly but significantly crop commodities’ exports according to our results. We also note that the sector of fruit and vegetables is more sensitive to this determinant, unlike cereals that remain relatively less affected. Furthermore, high-income countries have more tendency to trade with countries characterized by similar environmental stringency. Further results show that the BRICS are clearly importing from developed countries where the environmental difference is relatively important. It is likely that emerging countries are witnessing a growing demand for high-quality and “green” crop commodities captured by high-income exporters. Surprisingly, our results suggest that low and middle-income countries with the same level of environmental stringency are more likely to trade crop commodities.

Keywords: agricultural trade, environment, gravity model, food crops, agri-environmental efficiency, DEA

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Authors: Astrid Rivera, Diego Villatoro

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The world population increases at an accelerated pace, and it is essential to find solutions to feed the population. Nevertheless, crop diversity has significantly decreased in the last years, and the increase in food production is not the optimal solution. It is essential to consider the origin of the food, the nutriment contributions, among other dimensions. In this regard, biodiversity plays an indispensable role when designing an effective strategy to face the actual food security problems. Consequently, the purpose of this work is to analyze biodiversity in the Mexican national food production and suggest a proper crop selection based on companion plants, for which empirical and experimental knowledge shows a better scenery than current efforts. As a result, we get a set of crop recommendations to increase production in sustainable and nutritive planning. It is essential to explore more feasible options to advance sustainable development goals beyond an economic aspect.

Keywords: biodiversity, food security, companion plats, nutrition

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Authors: Ademuyiwa Agbonyin, Stamatis Zoras, Mohammad Zandi

Abstract:

This paper investigates the extent to which building energy modelling can be informed based on preliminary information provided by infrared thermography using a thermal imaging camera in a walkthrough audit. The case-study building is the Sheffield Cathedral, built in the early 1400s. Based on an informative qualitative report generated from the thermal images taken at the site, the regions showing significant heat loss are input into a computer model of the cathedral within the integrated environmental solution (IES) virtual environment software which performs an energy simulation to determine quantitative heat losses through the building envelope. Building data such as material thermal properties and building plans are provided by the architects, Thomas Ford and Partners Ltd. The results of the modelling revealed the portions of the building with the highest heat loss and these aligned with those suggested by the thermal camera. Retrofit options for the building are also considered, however, may not see implementation due to a desire to conserve the architectural heritage of the building. Results show that thermal imaging in a walk-through audit serves as a useful guide for the energy modelling process. Hand calculations were also performed to serve as a 'control' to estimate losses, providing a second set of data points of comparison.

Keywords: historic buildings, energy retrofit, thermal comfort, software modelling, energy modelling

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Authors: Fahad Suleiman

Abstract:

Agriculture has been the mainstay of the nation’s economy in Nigeria. It provides food for the ever rapidly increasing population and raw materials for the industries. People especially the rural dwellers are gainfully employed on their crop farms and small-scale livestock farms for income earning. In farming, availability of funds and time management are one of the major factors that influence the system of farming in Nigeria in which mathematical science knowledge was highly required in order for farms to be managed effectively. Farmers often applied mathematics, almost every day for a variety of tasks, ranging from measuring and weighing, to land marking. This paper, therefore, explores some of the ways math is used in farming. For instance, farmers use arithmetic variety of farm activities such as seed planting, harvesting crop, cultivation and mulching. It is also important in helping farmers to know how much their livestock weighs, how much milk their cows produce and crop yield per acres, among others.

Keywords: agriculture, application, economic, farming, mathematics

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Authors: Hoda Zolfagharnejad, Behnam Kamkar, Omid Abdi

Abstract:

Crop coefficient (Kc) is an important factor contributing to estimation of evapotranspiration, and is also used to determine the irrigation schedule. This study investigated and determined the monthly Kc of winter wheat (Triticum aestivum L.) using five vegetation indices (VIs): Normalized Difference Vegetation Index (NDVI), Difference Vegetation Index (DVI), Soil Adjusted Vegetation Index (SAVI), Infrared Percentage Vegetation Index (IPVI), and Ratio Vegetation Index (RVI) of four basins in Golestan province, Iran. 14 Landsat-8 images according to crop growth stage were used to estimate monthly Kc of wheat. VIs were calculated based on infrared and near infrared bands of Landsat 8 images using Geographical Information System (GIS) software. The best VIs were chosen after establishing a regression relationship among these VIs with FAO Kc and Kc that was modified for the study area by the previous research based on R² and Root Mean Square Error (RMSE). The result showed that local modified SAVI with R²= 0.767 and RMSE= 0.174 was the best index to produce monthly wheat Kc maps.

Keywords: crop coefficient, remote sensing, vegetation indices, wheat

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Authors: Ijaz Ahmad

Abstract:

Weed competition is one of the major biotic constraints in wheat crop productivity. Avena fatua L. and Silybum marianum (L.) Gaertn. are among the worst weeds of wheat, greatly deteriorating wheat quality subsequently reducing its market value. In this connection, two-year experiments were conducted in 2018 & 2019. Different seeding rate wheat viz; 80, 100, 120 and 140 kg ha-1 and different weeds ratio (A. fatua: S. marianum ) sown at the rate 1:8, 2:7, 3:6, 4:5, 5:4, 6:3, 7:2, 8:1 and 0:0 respectively. The weeds ratio and wheat densities are indirectly proportional. However, the wheat seed at the rate of 140 kg ha-1 has minimal weeds interference. Yield losses were 17.5% at weeds density 1:8 while 7.2% at 8:1. However, in wheat density, the highest percent losses were computed on 80 kg ha-1 while the lowest was recorded on 140 kg ha-1. Since due to the large leaf canopy of S. marianum other species can't sustain their growth. Hence, it has been concluded that S. marianum is the hotspot that causes reduction to the yield-related parameters, followed by A. fatua and the other weeds. Due to the morphological mimicry of A. fatua with wheat crop during the vegetative growth stage, it cannot be easily distinguished. Therefore, managing A. fatua and S. marianum before seed setting is recommended for reducing the future weed problem. Based on current studies, it is suggested that sowing wheat seed at the rate of 140 kg ha-1 is recommended to better compete with all the field weeds.

Keywords: fat content, holly thistle, protein content, weed competition, wheat, wild oat

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Authors: Wassie Molla, Klaas Frankena, Mart De Jong

Abstract:

Lumpy skin disease (LSD) is a severe viral disease of cattle, which often occurs in epidemic form. It is caused by lumpy skin disease virus of the genus capripoxvirus of family poxviridae. Mathematical models play important role in the study of infectious diseases epidemiology. They help to explain the dynamics and understand the transmission of an infectious disease within a population. Understanding the transmission dynamics of lumpy skin disease between animals is important for the implementation of effective prevention and control measures against the disease. This study was carried out in central and north-western part of Ethiopia with the objectives to understand LSD outbreak dynamics, quantify the transmission between animals and herds, and estimate the disease reproduction ratio in dominantly crop-livestock mixed and commercial herd types. Field observation and follow-up study were undertaken, and the transmission parameters were estimated based on a SIR epidemic model in which individuals are susceptible (S), infected and infectious (I), and recovered and immune or dead (R) using the final size and generalized linear model methods. The result showed that a higher morbidity was recorded in infected crop-livestock (24.1%) mixed production system herds than infected commercial production (17.5%) system herds whereas mortality was higher in intensive (4.0%) than crop-livestock (1.5%) system and the differences were statistically significant. The transmission rate among animals and between herds were 0.75 and 0.68 per week, respectively in dominantly crop-livestock production system. The transmission study undertaken in dominantly crop-livestock production system highlighted the presence of statistically significant seasonal difference in LSD transmission among animals. The reproduction numbers of LSD in dominantly crop-livestock production system were 1.06 among animals and 1.28 between herds whereas it varies from 1.03 to 1.31 among animals in commercial production system. Though the R estimated for LSD in different production systems at different localities is greater than 1, its magnitude is low implying that the disease can be easily controlled by implementing the appropriate control measures.

Keywords: commercial, crop-livestock, Ethiopia, LSD, reproduction number, transmission

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Authors: Safari Mat Desa, Othman A. Karim, Mohd Kamarulhuda Samion, Saiful Bahri Hamzah

Abstract:

Rubble mound breakwater was one of the most popular designs in Malaysia, constructed at the river mouth to dissipate the incoming wave energy from the seaward. Geometrically characteristics in trapezoid, crest width, and bottom width will determine the hypotonus stability, whilst structural height was designed for wave overtopping consideration. Physical hydraulic modelling in two-dimensional facilities was instigated in the flume to test the stability as well as the overtopping rate complied with the method of similarity, namely kinematic, dynamic, and geometric. Scaling effects of wave characteristics were carried out in order to acquire significant interaction of wave height, wave period, and water depth. Results showed two-dimensional physical modelling has proven reliable capability to ascertain breakwater stability significantly.

Keywords: breakwater, geometrical characteristic, wave overtopping, physical hydraulic modelling, method of similarity, wave characteristic

Procedia PDF Downloads 78