Academic literature on the topic 'Agriculture Simulation Methods'
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Journal articles on the topic "Agriculture Simulation Methods"
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Volk, Tinea. "Effects of agricultural policy on the development of Slovenian agriculture during the transition and the process of accession to the European Union." Journal of Agricultural Sciences, Belgrade 50, no. 1 (2005): 75–88. http://dx.doi.org/10.2298/jas0501075v.
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The thesis analyzes the development of agricultural policy and agriculture in Slovenia in the period from 1992 to 2002. The analysis is based on the classification of agricultural policy and its measures, standard indicators used for analysis of development of agricultural policy and agriculture, and specific methods for evaluating the efficiency of agricultural policy (evaluation methods, simulation methods). The results show that the transition in Slovenia caused no marked shocks for agricultural production. The development goals for agriculture were set forth early (in 1992) and were modeled on the EU standards, and they remained unchanged throughout the transition. A protectionist development concept of agricultural policy was adopted, which assured a relatively high level of support to agriculture. Under this concept, the agricultural policy was substantially reoriented during the transition, but this happened gradually and was reflected above all in the re-instrumentation of policy and changes of the structure of support to agriculture. Agricultural policy was relatively successful. It managed to achieve most of the strategic development goals of agriculture and a high degree of compatibility with the Common Agricultural Policy (CAP).
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Yamashita, Ryohei. "Dialogue with Different Fields Surrounding Agriculture through the Development of Research using Simulation Methods." Journal of Rural Problems 56, no. 1 (March 25, 2020): 11–16. http://dx.doi.org/10.7310/arfe.56.11.
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Fibriansari, Rizeki Dwi, Anggia Astuti, and Dwi Ochta Pebriyanti. "IMPROVING MC-KENZIE EXERCISE CAPABILITIES THROUGH SIMULATION METHOD IN THE AGRICULTURE AREA." Jurnal Pengabdian Masyarakat Dalam Kesehatan 4, no. 2 (December 20, 2022): 69–73. http://dx.doi.org/10.20473/jpmk.v4i2.38363.
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Introduction: Low back pain is one of the factors causing morbidity and mortality in agricultural areas, namely pain syndrome experienced by individuals caused by poor body position. This can injure soft tissue structures that include muscles and ligaments. Community service aims to improve farmers' knowledge and skills in the PTPN XII Gunung Gambir Jember Agricultural Area to prevent low back pain.
Methods: Community service activities are carried out by providing education through simulations to farmers. The reason for choosing this method is that farmers prefer real experiences compared to lectures.
Results: Simulation learning and role play will allow farmers to learn firsthand through watching, practicing, and role-playing how to do the Mc-Kenzie Exercise. Thus, it is hoped that farmers will experience more knowledge and skills in preventing low back pain.
Conclusion: Community service activities can increase farmers' knowledge of skills about Mc-Kenzie exercises to prevent low back pain without side effects.
KEYWORDS
Mc-Kenzie Workout, Low Back Pain, Simulation
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Kiani, Farzad, Amir Seyyedabbasi, Sajjad Nematzadeh, Fuat Candan, Taner Çevik, Fateme Aysin Anka, Giovanni Randazzo, Stefania Lanza, and Anselme Muzirafuti. "Adaptive Metaheuristic-Based Methods for Autonomous Robot Path Planning: Sustainable Agricultural Applications." Applied Sciences 12, no. 3 (January 18, 2022): 943. http://dx.doi.org/10.3390/app12030943.
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The increasing need for food in recent years means that environmental protection and sustainable agriculture are necessary. For this, smart agricultural systems and autonomous robots have become widespread. One of the most significant and persistent problems related to robots is 3D path planning, which is an NP-hard problem, for mobile robots. In this paper, efficient methods are proposed by two metaheuristic algorithms (Incremental Gray Wolf Optimization (I-GWO) and Expanded Gray Wolf Optimization (Ex-GWO)). The proposed methods try to find collision-free optimal paths between two points for robots without human intervention in an acceptable time with the lowest process costs and efficient use of resources in large-scale and crowded farmlands. Thanks to the methods proposed in this study, various tasks such as tracking crops can be performed efficiently by autonomous robots. The simulations are carried out using three methods, and the obtained results are compared with each other and analyzed. The relevant results show that in the proposed methods, the mobile robots avoid the obstacles successfully and obtain the optimal path cost from source to destination. According to the simulation results, the proposed method based on the Ex-GWO algorithm has a better success rate of 55.56% in optimal path cost.
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Radzajewski, Paweł. "Calculation of brake-force distribution on three-axle agricultural trailers using simulation methods." Technical Transactions 2021, no. 1 (2021): 1–18. http://dx.doi.org/10.37705/techtrans/e2021029.
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The paper presents a new methodology for calculating the optimal linear distribution of braking forces for a three-axle trailer with "walking beam" and "bogie" suspension of the rear axle assembly that will meet the requirements of the new European legislation, EU Directive 2015/68. On this basis, a computer program for selecting the linear distribution of braking forces between axles has been developed. The presented calculations and simulation results of the braking process can be used in the design process to select the parameters of the wheel braking mechanisms and then the characteristics of the pneumatic valves of the braking system. The adaptation of the braking system of agriculture trailers is a very important factor for improving the safety of the transportation systems.
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Khoruzhy, Lyudmila Ivanovna, Yury Nikolaevich Katkov, and Anastasiya Alekseevna Romanova. "Modern tools of deep analysis in the system of cost management in inter-organizational relations of agricultural formations." Buhuchet v sel'skom hozjajstve (Accounting in Agriculture), no. 6 (June 1, 2021): 6–15. http://dx.doi.org/10.33920/sel-11-2106-01.
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The article, based on the theoretical analysis and the study of accounting practices, presents the place and role of tools for deep cost analysis in the cost management system of inter-organizational interaction of partners. The features of agriculture that have a significant impact on the interorganizational cooperation of agricultural companies are revealed. The advantages of the introduction and use of modern methods of cost management, including simulation modeling in identifying deviations in business processes, are revealed.
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Klose, Steven L., and Joe L. Outlaw. "Financial and Risk Management Assistance: Decision Support for Agriculture." Journal of Agricultural and Applied Economics 37, no. 2 (August 2005): 415–23. http://dx.doi.org/10.1017/s107407080000688x.
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The Financial and Risk Management (FARM) Assistance program created by Texas Cooperative Extension is a strategic analysis service offered to farmers and ranchers in Texas. The program serves as an example of large-scale, focused programming by extension agencies, as well as the implementation of technical stochastic simulation methods for use on the farm.
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Pandey, Prateek, Shishir Kumar, and Sandeep Srivastava. "A Critical Evaluation of Computational Methods of Forecasting Based on Fuzzy Time Series." International Journal of Decision Support System Technology 5, no. 1 (January 2013): 24–39. http://dx.doi.org/10.4018/jdsst.2013010102.
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The agricultural production is a process, which being nonlinear in nature, due to various influential parameters like weather, rainfall, diseases, disaster, area of cultivation etc., is not governed by any deterministic process. Fuzzy time series forecasting is one of the approaches for predicting the future values where neither a trend is viewed nor a pattern is followed, for example, in case of sugar, Lahi and rice production. Various forecasting methods have been developed on the basis of fuzzy time series data, but accuracy has been a mercurial factor in these forecasts. In this paper, performance analysis of different fuzzy time series (FTS) models has been carried out. The analysis is applicable to any available time series data of product. In this paper performance analysis is done on the data of Indian agro products that include sugarcane, Lahi and rice. The suitability of different FTS models have been critically examined over the production data of the three agro products. The paper establishes the applicability of FTS methods also in the agriculture industry.
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Szőke, Szilvia, Lajos Nagy, Sándor Kovács, and Péter Balogh. "Examination of pig farm technology by computer simulation." Applied Studies in Agribusiness and Commerce 3, no. 5-6 (December 30, 2009): 25–29. http://dx.doi.org/10.19041/apstract/2009/5-6/4.
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Agricultural production is among the riskiest production activities. Similarly to other branches of agriculture in animal breeding the finished product is the result of complex procedures. The biological technological procedure, the creation of the product is affected by an outstanding number of environmental factors which also cause uncertainties. In the North Great Plain Region of Hungary, sows, gilts and slaughter pigs are produced on a corporate farm. The reliable operation data of this company provide a stable basis for and estimating future costs and revenue and their distributions. Monte Carlo methods are one of the generally accepted tools for modeling risks. The significant independent variables, their ranges and probability distributions, and the correlation between them were inputs to the model. The values of the variables were produced using a random number generator. The computer simulation was performed using @Ris (PalisadeCorporation) software. The study concentrates on the factors affecting the number of off spring (piglets). Model inputs were the mating, mortality and farrowing rates; the costs and the income values based on these rates have been analysed as the output data of the model.
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Li, Xiaomin, Lixue Zhu, Xuan Chu, and Han Fu. "Edge Computing-Enabled Wireless Sensor Networks for Multiple Data Collection Tasks in Smart Agriculture." Journal of Sensors 2020 (February 25, 2020): 1–9. http://dx.doi.org/10.1155/2020/4398061.
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At present, precision agriculture and smart agriculture are the hot topics, which are based on the efficient data collection by using wireless sensor networks (WSNs). However, agricultural WSNs are still facing many challenges such as multitasks, data quality, and latency. In this paper, we propose an efficient solution for multiple data collection tasks exploiting edge computing-enabled wireless sensor networks in smart agriculture. First, a novel data collection framework is presented by merging WSN and edge computing. Second, the data collection process is modeled, including a plurality of sensors and tasks. Next, according to each specific task and correlation between task and sensors, on the edge computing server, a double selecting strategy is established to determine the best node and sensor network that fulfills quality of data and data collection time constraints of tasks. Furthermore, a data collection algorithm is designed, based on set values for quality of data. Finally, a simulation environment is constructed where the proposed strategy is applied, and results are analyzed and compared to the traditional methods. According to the comparison results, the proposal outperforms the traditional methods in metrics.
Dissertations / Theses on the topic "Agriculture Simulation Methods"
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Jebari, Asma. "Integrating upscaling simulation methods for predicting soil organic Carbon changes in Spain." Doctoral thesis, Universitat de Lleida, 2022. http://hdl.handle.net/10803/674047.
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L'avaluació d'estocs de C orgànic del sòl (COS) i emissions d'efecte hivernacle (GEH) a escala regional sota escenaris de canvi climàtic és fonamental a l'hora d'implementar estratègies de maneig per mitigar el canvi climàtic. El principal objectiu d'aquesta Tesi és avaluar els canvis del COS i GEH en diferents sistemes agrícoles (en terres de cultiu i de pastura) i en diferents condicions climàtiques (clima mediterrani i temperat humit) d'Espanya sota diferents escenaris climàtics. A més, s’avaluen les estratègies de maneig de la terra amb l'objectiu de mitigar els efectes del canvi climàtic.
A l'estudi de modelització espacial, es va adoptar una versió calibrada del model de COS RothC per estimar els canvis en els estocs de COS en condicions de canvi climàtic a les terres de cultiu de l'Espanya mediterrània en una superfície total de 23 300 km2 durant el període 2010-2100. També es van simular emissions presents i futures (2010-2100) netes per a uns 4050 km2 de terres de pastura associades a la producció lletera de la zona temperada humida d'Espanya. Per a l'estimació del COS, es va modificar el model RothC per adaptar-lo a les terres de pastura temperades humides, considerant: (1) la incorporació dels diferents components dels residus vegetals (part aèria, part subterrània i rizodeposició) diferenciant-ne la qualitat i la quantitat, (2) la diferenciació de la qualitat de l'excreta dels remugants, i (3) l'extensió de la funció d'humitat del sól considerant condicions de saturació. Per a l'estimació dels GEH, es va fer servir la metodologia refinada de l'IPCC (Tier 2) considerant emissions de CH4 i N2O provinents de la fermentació entèrica, del maneig de l'excreta i del sòl de les pastures.
Segons els resultats trobats en els dos agroecosistemes (és a dir, terres de cultiu i de pastura), el canvi climàtic condueix a una disminució en el contingut de COS en comparació amb els escenaris de base de referència. Concloem que l'aportació de C és el factor clau de l'emmagatzematge de COS a les terres de cultiu mediterrànies i les terres de pastura temperades humides i que la temperatura de l'aire és el factor climàtic que contribueix més a les variacions del COS. A més, la densitat ramadera és el factor que més afecta les emissions netes a les terres de pastura associades a la producció lletera al Nord d'Espanya.
En conclusió, les alternatives de maneig milloren la quantitat de COS emmagatzemat i es mostren com a estratègies efectives per reduir les emissions GEH sota les condicions futures de canvi climàtic. La sembra directa, en el cas dels cultius de secà, i la coberta vegetal, per als camps d’oliveres i altres cultius llenyosos, són les alternatives de maneig que resulten més eficaces per a reduir els efectes del canvi climàtic i la pèrdua de COS. A més, en el cas de les terres de pasturea temperades i humides associades a la producció lletera, les pràctiques alternatives de maneig dels fems (en particular, la digestió anaeròbica) afavoreixen a mitigar els efectes del canvi climàtic i a reduir els GEH nets, alhora que contribueixen a la mitigació mitjançant l'optimització de la densitat ramadera.La evaluación de stocks de C orgánico del suelo (COS) y emisiones de efecto invernadero (GEI) a escala regional bajo escenarios de cambio climático es de fundamental importancia a la hora de implementar estrategias de manejo para mitigar el cambio climático. El principal objetivo de esta Tesis es evaluar los cambios del COS y GEI en diferentes sistemas agrícolas (e.g., tierras de cultivo y pastos) y diferentes condiciones climáticas (Mediterráneo y templado húmedo) de España bajo diferentes escenarios climáticos. Además, evalué las estrategias de manejo con el objetivo de mitigar los efectos del cambio climático. En el estudio de modelización espacial, se adoptó una versión calibrada del modelo de COS RothC para estimar los cambios en los stocks de COS en condiciones de cambio climático en las tierras de cultivo de la España mediterránea en una superficie total de 23 300 km2 durante el período 2010 a 2100. También simulé las presentes y futuras (2010-2100) emisiones netas para unos 4050 km2 de pastos asociados a la producción lechera de la zona templada húmeda de España. Para la estimación del COS, se modificó el modelo RothC para adaptarlo a los pastos templados húmedos considerando: (1) la incorporación de los diferentes componentes de los residuos vegetales (parte aérea, parte subterránea y rizodeposición) diferenciando su calidad y cantidad, la diferenciación de la calidad de la excreta de los rumiantes, y la extensión de la función de humedad del suelo considerando condiciones de saturación. Para la estimación de los GEI, se usó la metodología refinada del IPCC (Tier 2) considerando emisiones de CH4 and N2O provenientes de la fermentación entérica, del manejo de la excreta y del suelo de los pastos. Según los resultados encontrados en ambos agroecosistemas (es decir, tierras de cultivo y pastos), el cambio climático generalmente condujo a una disminución en el contenido de COS en comparación con los escenarios baseline de referencia. Concluimos que el aporte de C es el factor clave del almacenamiento de COS en las tierras de cultivo mediterráneas y los pastos templados húmedos y que la temperatura del aire es el factor climático que contribuyó más a las variaciones en el COS. Además, la densidad ganadera fue el factor que más afectó a las emisiones netas en los pastos asociados a la producción lechera en el Norte de España. En conclusión, las alternativas de manejo mejoraron la cantidad de COS almacenado y eran estrategias efectivas para reducir las emisiones GEI bajo las condiciones futuras del cambio climático. La siembra directa, en el caso de los cultivos de secano, y la cubierta vegetal, para los olivares y otros cultivos leñosos, fueron las alternativas de manejo eficaces para reducir los efectos del cambio climático y la pérdida de COS. Además, en el caso de pastos templados y húmedos asociados a la producción lechera, las prácticas alternativas de manejo del estiércol (en particular, la digestión anaeróbica) ayudaron a mitigar los efectos del cambio climático y a reducir los GEI netos, mientras que se podría lograr una mayor mitigación mediante la optimización de la densidad ganadera.
Soil organic carbon (SOC) stocks and greenhouse gas (GHG) emissions assessment at the regional scale under climate change scenarios are of paramount importance in implementing management practices to mitigate climate change effect. The main objective of this Thesis was to assess SOC changes and GHG emissions under different agricultural systems (croplands and grasslands) and climatic conditions (Mediterranean and moist temperate) in Spain under different climate scenarios. Furthermore, different alternative management practices to mitigate climate change effects for the considered agroecosystems were also evaluated. A calibrated version of the SOC model RothC was constructed to estimate the changes in SOC under climate change conditions for croplands of Mediterranean Spain across a total surface area of 23 300km2 during the 2010 to 2100 period. It was also simulated current and future (2010–2100) net GHG emissions in more than 4050 km2 of moist temperate Spanish grasslands associated to dairy production under different climate scenarios. For SOC dynamics estimation, the RothC model was modified to fit to managed moist temperate grasslands considering: (1) the incorporation of distinction for plant residues components (i.e., above- and below-ground residues and rhizodeposition) in terms of quantity and quality, (2) ruminant excreta quality, and (3) the extension of soil moisture up to saturation conditions. For GHG estimation, it was used mainly Tier 2 IPCC methodologies to estimate the CH4 and N2O emissions from enteric fermentation, manure storage and handling, and grassland soils. According to my findings, among both agroecosystems (i.e., croplands and grasslands), climate change generally led to a decline in SOC content compared with baseline scenarios. Furthermore, C input was the key factor of SOC storage across Mediterranean croplands and moist temperate Spanish grasslands. Additionally, it was found that air temperature rather than precipitation was the climatic factor contributing to most of variation in SOC changes values. Moreover, livestock density was the main factor affecting net GHG emissions in the grasslands associated to dairy production of Northern Spain. It was concluded that changes in management could enhance the amount of SOC sequestered and reduce GHG emissions under climate change conditions. Under Mediterranean croplands, no-tillage, in the case of rainfed crops, and vegetation cover, for olive groves and other woody crops, were the alternative management strategies to alleviate climate change effects and SOC loss. In addition, under moist temperate grassland-based dairy livestock systems, alternative manure management practices (particularly, anaerobic digestion) were efficient to mitigate the climate change effects and to reduce the net GHG emissions, while more mitigation could be achieved by optimising the livestock density management.
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Schmidt, Darren John. "Introducing crop simulation technology using soft systems methodology : some issues in agricultural communication." Thesis, Queensland University of Technology, 1994. https://eprints.qut.edu.au/36401/1/36401_Schmidt_1994.pdf.
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Information technology (IT) is emerging as a critical factor in the development of Australian agriculture. The capacity for IT to complement traditional extension
efforts is considerable, given its ability to be effective over distance as well as its ability to store and process vast amounts of information. In addition, IT can be used to 'quantify' risk, or provide a numerical assessment of the chances of a particular crop's success in a particular agronomic and climatic environment. This
function of IT can be seen as useful for primary producers who might wish to experiment with crops and cropping practices with which they have been
previously unfamiliar. Using IT, farmers might be able to hypothetically test the chances of an unfamiliar crop's success on their farm without a significant
physical or capital investment. A real-world example of this scenario currently exists in Queensland whereby farmers in various parts of the state are being
encouraged by Queensland's Department of Primary Industries (DPI) and PMB Australia (a peanut marketing company) to grow peanuts, which have traditionally been grown in the South Burnett and around the Atherton
Tablelands. This thesis reports on a project sponsored by the DPI and PMB Australia designed to explore the possibilities of using IT as a tool to help farmers make
decisions about growing peanuts. The problem has been framed as a communication issue, however it is argued throughout this thesis that the entire knowledge system, incorporating farmers, scientists, IT, knowledge, and
information, needs to be considered from a meta-theoretical standpoint using a multi-disciplinary framework. From this perspective, the thesis reports that
understanding the relationship shared by scientists and farmers is central to the problem of designing IT to meet users' needs. This relationship is shaped by a confluence of factors, and a number of these are identified and critically analysed in this thesis.
This thesis develops the idea that introducing IT to an existing knowledge system is not merely a matter of asking farmers what they need and designing IT accordingly. Rather, the introduction of IT is treated as a sociological phenomenon, and the bulk of this thesis is devoted to investigating the cultural, political, economic, historical, and technological systems in which the major stakeholders engage. This investigation is undertaken using an interpretivist perspective, and the methodology used to collect data - Soft Systems
Methodology (SSM) - also reflects this approach. As such, rich, diverse, qualitatively based observations are used as the basis for recommendations on policy and practice. This thesis generates a number of suggestions for action as well as some theoretical ideas about the relationship shared by scientists and farmers.
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Borodin, Valeria. "Optimisation et simulation d'une chaîne logistique : application au secteur de l'agriculture." Thesis, Troyes, 2014. http://www.theses.fr/2014TROY0034/document.
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Dans le cadre de la thèse portant sur l’optimisation et simulation de la chaîne logistique agricole, c'est l'activité de collecte qui est concernée, la période de moisson étant primordiale en matière de quantité et qualité de production, i.e. des revenus pour les agri-culteurs et des richesses pour le territoire. Plus spécifiquement, celle-ci implique les opérations de récolte, transport et stockage des céréales, réalisées par plusieurs exploitations agricoles, dispersées géographiquement. En vue d'aborder la complexité et la nature dyna-mique de la chaîne logistique d’une coopérative agricole française dans son intégralité, nous avons développé un système d'aide à la décision, qui s'inscrit dans la cadre de la recherche opérationnelle (RO) et plus précisément se réfère à l'optimisation linéaire, robuste et stochastique; la simulation de flux à évènements discrets; ainsi qu'à leur couplage. De plus, la synergie créée entre les outils de la RO, le système d’information géographique, la statistique inférentielle et prédictive rend le système d'aide à la décision compétitif et performant, capable de répondre convenablement au besoin de l’industrielTo overcome the new challenges facing agricultural sector, imposed by globalisation, changing market demands and price instability, the crop production supply chain must particularly be very reactive, flexible, with a high yield and at low cost. Its improving and eventual re-configuration can lead to an upgrade in efficiency, responsiveness, business integration and make it able to confront the market competitiveness. The thesis is thus placed in this particular context and aims to support decision making in crop harvesting activity, which is considered the pivotal stage in the cereal production circuit owing to its high cost and impact on the returns earned. Managing the harvest activity involves gathering, transportation and storage operations, performed by a collection of agricultural holdings geographically dispersed. Besides its practical relevance, this thesis forms part of the Operational Research (OR) and more specifically, refers to the linear and stochastic programming, discrete event simulation, and their coupling. In addition, the synergy created between OR, inferential and predictive statistics, geographical information system tools makes the decision support system competitive, efficient and responsive
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Marinelli, Marco Antonio. "Modelling and communicating the effects of spatial data uncertainty on spatially based decision-making." Thesis, Curtin University, 2011. http://hdl.handle.net/20.500.11937/1842.
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Important economic and environmental decisions are routinely based on spatial/ temporal models. This thesis studies the uncertainty in the predictions of three such models caused by uncertainty propagation. This is considered important as it quantifies the sensitivity of a model’s prediction to uncertainty in other components of the model, such as the model’s inputs. Furthermore, many software packages that implement these models do not permit users to easily visualize either the uncertainty in the data inputs, the effects of the model on the magnitude of that uncertainty, or the sensitivity of the uncertainty to individual data layers. In this thesis, emphasis has been placed on demonstrating the methods used to quantify and then, to a lesser extent, visualize the sensitivity of the models. Also, the key questions required to be resolved with regards to the source of the uncertainty and the structure of the model is investigated. For all models investigated, the propagation paths that most influence the uncertainty in the prediction were determined. How the influence of these paths can be minimised, or removed, is also discussed.Two different methods commonly used to analyse uncertainty propagation were investigated. The first is the analytical Taylor series method, which can be applied to models with continuous functions. The second is the Monte Carlo simulation method which can be used on most types of models. Also, the later can be used to investigate how the uncertainty propagation changes when the distribution of model uncertainty is non Gaussian. This is not possible with the Taylor method.The models tested were two continuous Precision Agriculture models and one ecological niche statistical model. The Precision Agriculture models studied were the nitrogen (N) availability component of the SPLAT model and the Mitscherlich precision agricultural model. The third, called BIOCLIM, is a probabilistic model that can be used to investigate and predict species distributions for both native and agricultural species.It was generally expected that, for a specific model, the results from the Taylor method and the Monte Carlo will agree. However, it was found that the structure of the model in fact influences this agreement, especially in the Mitscherlich Model which has more complex non linear functions. Several non-normal input uncertainty distributions were investigated to see if they could improve the agreement between these methods. The uncertainty and skew of the Monte Carlo results relative to the prediction of the model was also useful in highlighting how the distribution of model inputs and the models structure itself, may bias the results.The version of BIOCLIM used in this study uses three basic spatial climatic input layers (monthly maximum and minimum temperature and precipitation layers) and a dataset describing the current spatial distribution of the species of interest. The thesis investigated how uncertainty in the input data propagates through to the estimated spatial distribution for Field Peas (Pisum sativum) in the agriculturally significant region of south west Western Australia. The results clearly show the effect of uncertainty in the input layers on the predicted specie’s distribution map. In places the uncertainty significantly influences the final validity of the result and the spatial distribution of the validity also varies significantly.
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Popiolek, Nathalie. "Modèle prospectif de consommation d'énergie dans l'agriculture : le cas de la fertilisation azotée a l'horizon 2010." Grenoble 2, 1993. http://www.theses.fr/1993GRE21027.
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La premiere partie de cette these donne une vision critique des methodes de prospective disponibles. A l'issue de ce panorama est presentee la methodologie prospective choisie pour la construction du model. Cette construction constitue la deuxieme etape du travail. Le systeme "energie et fertilisation azotee" est defini, (liste des variables cles pour son evolution a l'horizon 2010, analyse de leurs relations) puis modelise en mettant l'accent sur la demande d'engrais azotes. A l'horizon 2010, celle-ci est determinee a l7aide d'un modele de programmation lineaire (aropaj) traduisant les choix culturaux des agriculteurs. Ce modele, destine au depart au court moyen terme, est adapte a l'horizon 2010 grace a la construction de modeles peripheriques projetant les facteurs fixes (a court termes) des exploitations et leur mode de production. Ces projections sont effectuees suivant differents scenarios d'evolution. L'elaboration de ces scenarios, a partir d'enquetes d'experts (delphi), fait l'objet de la troisieme partie. Dans le cadre de ces scenarios, des simulations sont effectuees sur le modele afin de tester notamment les consequences de la future politique agricole commune ou celles de l'introduction d'innovations technologiquesThe first part of this thesis gives a critical overview of available forecasting methods. After this survey, the methodology chosen for the construction of the model is presented. This construction constitutes the second stage of this work. The "energy and nitrogen fertilization" system is defined (list of key variables for its evolution towards the year 2010 and analysis of their relationships) and then modelized highlighting the nitrogen fertilizers demand. The demand is determined for the year 2010 by the mean of a linear programming model (aropaj) based on farmers' cropping choices. This model, first used for short and middle terms is adapted for the long term (2010) by using peripheral models projecting the fixed factors (in the short term) of agricultural holdings and their way of producing. These projections are based on experts inquiries (delphi) constitutes the third part of this thesis. These scenarios constitute the patterns of simulation running on the linear programme to test the impact of the future common agricultural policy or the introduction of technological innovations
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Haned, Hinda. "Évaluation de méthodes statistiques pour l'interprétation des mélanges d'ADN en science forensique." Phd thesis, Université Claude Bernard - Lyon I, 2010. http://tel.archives-ouvertes.fr/tel-00817181.
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L'analyse et l'interprétation d''echantillons constitu'es de mélanges d'ADN de plusieurs individus est un défi majeur en science forensique. Lorsqu'un expert de la police scientifique a affaire à un mélange d'ADN il doit répondre à deux questions: d'abord, "combien de contributeurs y a-t-il dans ce mélange ?"et puis, "quels sont les génotypes des individus impliqués ?" Le typage seul de cet ADN ne permet pas toujours de r'epondre 'a ces questions. En effet leproblème est posé d'es lors que plus de deux allèles sont observées à un locus donné, plusieurscombinaisons génotypiques sont alors 'a envisager et il est impossible de déterminer avec certitudele nombre d'individus qui ont contribué au m'elange. De plus, la présence d'anomalies liées àl'analyse de marqueurs g'en'etiques, comme la contamination ou la perte d'all'eles ("drop-out"),peut davantage compliquer l'analyse.Les nombreux d'eveloppements statistiques d'edi'es 'a ces probl'ematiques n'ont pas eu le succ'esescompt'e dans la communaut'e forensique, essentiellement, parce que ces m'ethodes n'ont pas 'et'evalid'ees. Or sans cette validation, les experts de la police scientifique ne peuvent exploiter cesm'ethodes sur des m'elanges issus d'affaires en cours d'investigation.Avant d'ˆetre valid'ees, ces m'ethodes doivent passer par une rigoureuse 'etape d''evaluation.Cette derni'ere soul'eve deux questions: d'abord, la question de la m'ethodologie 'a adopter, puis,celle des outils 'a d'eployer. Dans cette th'ese, nous tentons de r'epondre aux deux questions.D'abord, nous menons des 'etudes d''evaluation sur des m'ethodes d'edi'ees 'a deux questions cl'es: i)l'estimation du nombre de contributeurs 'a un m'elange d'ADN et ii) l'estimation des probabilit'esde "drop-out". En second lieu, nous proposons un logiciel "open-source" qui offre un certainnombre de fonctionnalit'es permettant de faciliter l''evaluation de m'ethodes statistiques d'edi'eesaux m'elanges d'ADN.Cette thèse a pour but d'apporter une r'eponse concr'ete aux experts de la police scientifiqueen leur fournissant 'a la fois une d'emarche m'ethodologique pour l''evaluation de m'ethodes, et lapossibilit'e d'analyser la sensibilit'e de leurs r'esultats au travers d'un outil informatique en libreacc'es.
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Halama, Tadeáš. "Pevnostní analýza a optimalizace nosiče výměnných nástaveb MEGA 25." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-318666.
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This Diploma Thesis is dedicated to stress analysis of carrier swap bodies Mega 25 with maximum technical weight 27 000 kg and has been worked out in corporation with ZDT Nové Veselí company. The aim of this work is to stress analysis of trailer in various burdensome conditions. The first section of the Thesis is occupied with original design and burdensome condition. Then, according to these states gained strength to control the finite element method, implement and then modify the design including design of new drawbar and then create selected construction drawings prepared.
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Sharma, Sunil Kumar. "A comparison of combinatory methods and GIS based MOLA (IDRISI®) for solving multi-objective land use assessment and allocation problems." Phd thesis, 2005. http://hdl.handle.net/1885/12855.
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The aim of this study was to provide an informed choice among two combinatory methods and GIS based MOLA module in IDRISI® by comparing their performance in solving a hypothetical Multi-Objective Land use Assessment and Allocation (MOLAA)problem. Among the combinatory methods, Simulated Annealing and Tabu Search algorithms were chosen for study. The application of Simulated Annealing has already been demonstrated in solving a MOLAA problem but Tabu Search has not been used to a MOLAA problem before. The Kioloa Region of New South Wales, Australia was chosen for designing a hypothetical MOLAA problem due to availability and access to the digital datasets at the Australian National University. The MOLAA problem was formulated for accomplishing six land use objectives by allocating the area to four land use types, that is, conservation, agriculture, forestry and development, using altogether 1 7 criteria, including 16 factors and one constraint. The criteria maps were classified in ordinal, continuous and fuzzy scale and combined by using Weighted Linear Combination to produce land use suitability models for each land use type. The ordinal and continuous land use suitability models were used in solving the problem by applying the MOLA
module. In order to apply the combinatory methods, all three land use suitability models, that is, ordinal, continuous and fuzzy, were transferred to cost suitability models where the lowest cost value represented the best suitability and the highest cost value represented the lowest suitability in the interval data set. Three initial input solutions generated by the random, cheapest and greatest difference methods were used for optimising by applying both algorithms. Both combinatory methods maximized overall land use suitability with better spatial compactness by allocating each land unit with the most suitable land use with the lowest cost. At the land use level, MOLA exhibited a bias towards land uses with lower area requirement and allocates more suitable land units to them. Though the MOLA module is highly efficient in solving large grid MOLAA problem, the combinatory methods deliver a solution close to the near-optimal solution with better compactness in an acceptable time frame. Hence, the combinatory methods have been shown to be appropriate choice to solve MOLAA problems. The solutions were not significantly different at their mean cost functions between
Simulated Annealing and Tahu Search at the appropriate parameters. Among the cost
suitability models, both algorithms performed better in the fuzzy models in the large MOLAA problem. The initial input solution influenced the performance of the algorithms. The algorithms produced better results in the cheapest and greatest difference initial input solution in the medium grid MOLAA problem whereas the cost function was more improved using the random initial input solution in the large grid. Although there is no significant difference in the mean cost functions between
Simulated Annealing and Tahu Search, the previous one is found more efficient in
solving large grid MOLAA problem. For the same values of compactness factors, Simulated Annealing produced more spatially compact land use allocation than Tahu Search. Thus decision makers/land use planners or consultants could obtain a better decision alternative to a land use allocation problem by applying Simulated Annealing with the recommended appropriate annealing schedule and initial input cost suitability model. This study recommends further research in Tahu Search to find an effective attribute for a Tahu list, to be applied to a MO LAA problem.
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Sulistyawati, Endah. "An agent-based simulation of land-use in a swidden agricultural landscape of the Kantu' in Kalimantan, Indonesia." Phd thesis, 2001. http://hdl.handle.net/1885/146045.
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(8800949), Patrick N. Maier. "A Bioeconomic Model of Indoor Pacific Whiteleg Shrimp (Litopenaeus Vannamei) Farms With Low-Cost Salt Mixtures." Thesis, 2020.
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Using a bioeconomic model and stochastic simulation to assess the economic viability of small-scale, recirculating shrimp farms in the Midwestern U.S. A series of stress tests were implemented on key input variables including survival rate, selling price, electricity usage, discount rate and the cost of added salt. The key output variable is the Net Present Value of the operation. Books on the topic "Agriculture Simulation Methods"
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Simulation and systems analysis in agriculture. Amsterdam: Elsevier, 1985.
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Roningen, Vernon. A Static World Policy Simulation (SWOPSIM) modeling framework. [Washington, D.C.]: U.S. Dept. of Agriculture, Economic Research Service, International Economics Division, 1986.
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Flichman, Guillermo. Bio-economic models applied to agricultural systems. Dordrecht: Springer, 2011.
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Elderen, E. Van. Scheduling farm operations: A simulation model. Wageningen, Netherlands: Pudoc, 1987.
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Huang, Barney K. Computer simulation analysis of biological and agricultural systems. Boca Raton, FL: CRC Press, 1994.
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Dukes, Richard L. Worlds apart: Collective action in simulated agrarian and industrial societies. Dordrecht: Kluwer Academic, 1990.
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Brouwer, Floor. Environmental and agricultural modelling: Integrated approaches for policy impact assessment. Dordrecht: Springer, 2010.
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Hertel, Thomas W. Adding value to existing models of international agricultural trade. [Washington, DC]: U.S. Dept. of Agriculture, Economic Research Service, 1994.
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Jonathan, Kydd, Maetz Materne, Heath Julia, and Food and Agriculture Organization of the United Nations., eds. Southland: A case study-based training exercise in policy analysis for the agricultural and rural sector. Rome: Food and Agriculture Organization of the United Nations, 2003.
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NIES Workshop on Information Bases and Modeling for Land-Use and Land-Cover Changes Studies in East Asia (1999 Tsukaba, Japan). Proceedings of 1999 NIES Workshop on Information Bases and Modeling for Land-Use and Land-Cover Changes Studies in East Asia. Ibaraki, Japan: Center for Global Environmental Research, National Institute for Environmental Studies, Environment Agency of Japan, 1999.
Find full textBook chapters on the topic "Agriculture Simulation Methods"
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Rueda, J. L., C. Leon-Velarde, T. Walker, and H. Zandstra. "CIP’s experiences in the use of systems analysis and simulation." In Opportunities, use, and transfer of systems research methods in agriculture to developing countries, 289–94. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0762-4_24.
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Rueda, J. L., C. Leon-Velarde, T. Walker, and H. Zandstra. "CIP’s experiences in the use of systems analysis and simulation." In Opportunities, use, and transfer of systems research methods in agriculture to developing countries, 289–94. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0764-8_19.
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Zhao, Peng-fei, Tian-en Chen, Wei Wang, and Fang-yi Chen. "Research on Plant Growth Simulation Method Based on ARToolkit." In Computer and Computing Technologies in Agriculture X, 189–96. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-06155-5_18.
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Husain, Saiful Azmi, and Nor Hamizah Mohd Rhyme. "Decision Support Method for Agricultural Irrigation Scenarios Performance Using WEAP Model." In Theoretical, Modelling and Numerical Simulations Toward Industry 4.0, 99–106. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8987-4_7.
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Huang, Peichen, Xiwen Luo, and Zhigang Zhang. "Headland Turning Control Method Simulation of Autonomous Agricultural Machine Based on Improved Pure Pursuit Model." In Computer and Computing Technologies in Agriculture III, 176–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12220-0_27.
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Adiku, S. G. K., L. R. Ahuja, G. H. Dunn, J. D. Derner, A. A. Andales, L. Garcia, and P. N. S. Bartling. "Parameterization of the GPFARM-Range Model for Simulating Rangeland Productivity." In Methods of Introducing System Models into Agricultural Research, 209–28. Madison, WI, USA: American Society of Agronomy and Soil Science Society of America, 2015. http://dx.doi.org/10.2134/advagricsystmodel2.c7.
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Jabro, Jay D., John L. Hutson, and Ann D. Jabro. "Parameterizing LEACHM Model for Simulating Water Drainage Fluxes and Nitrate Leaching Losses." In Methods of Introducing System Models into Agricultural Research, 95–115. Madison, WI, USA: American Society of Agronomy and Soil Science Society of America, 2015. http://dx.doi.org/10.2134/advagricsystmodel2.c3.
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Wu, Ding-feng, Guo-min Zhou, Jian Wang, and Jian Wang. "Research on the Method of Simulating Knowledge Structure of the Information Searchers — Illustrated by the Case of Pomology Information Retrieval." In Computer and Computing Technologies in Agriculture VII, 450–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54344-9_51.
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Lezhenkin, Oleksandr, Ivan Lezhenkin, Oleksandr Vershkov, and Serhii Kolomiiets. "Simulation of Cereal Crops Harvesting Using the Method of Grain Crops Combing in Standing Position in Conditions of Farming Enterprises." In Modern Development Paths of Agricultural Production, 91–98. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14918-5_10.
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Carter, Timothy R., and Stefan Fronzek. "A Model-Based Response Surface Approach for Evaluating Climate Change Risks and Adaptation Urgency." In Springer Climate, 67–75. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86211-4_9.
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AbstractWe present a new approach to advance methods of climate change impact and adaptation assessment within a risk framework. Specifically, our research seeks to test the feasibility of applying impact models across sectors within a standard analytical framework for representing three aspects of potential relevance for policy: (i) sensitivity—examining the sensitivity of the sectors to changing climate for readily observable indicators; (ii) urgency—estimating risks of approaching or exceeding critical thresholds of impact under alternative scenarios as a basis for determining urgency of response; and (iii) response—determining the effectiveness of potential adaptation and mitigation responses. By working with observable indicators, the approach is also amenable to long-term monitoring as well as evaluation of the success of adaptation, where this too can be simulated. The approach focuses on impacts in climate-sensitive sectors, such as water resources, forestry, agriculture or human health. It involves the construction of impact response surfaces (IRSs) based on impact model simulations, using sectoral impact models that are also capable of simulating some adaptation measures. We illustrate the types of analyses to be undertaken and their potential outputs using two examples: risks of crop yield shortfall in Finland and impact risks for water management in the Vale do Gaio reservoir, Portugal. Based on previous analyses such as these, we have identified three challenges requiring special attention in this new modelling exercise: (a) ensuring the salience and credibility of the impact modelling conducted and outputs obtained, through engagement with relevant stakeholders, (b) co-exploration of the capabilities of current impact models and the need for improved representation of adaptation and (c) co-identification of critical thresholds for key impact indicators and effective representation of uncertainties. The approach is currently being tested for five sectors in Finland.
Conference papers on the topic "Agriculture Simulation Methods"
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Lu, Ling, Weng-lin Song, and Lei Wang. "A simulation method for the fruitage body." In International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009). SPIE, 2009. http://dx.doi.org/10.1117/12.836947.
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Ryan, Sydney D., Andrew G. Gerber, Gorden A. L. Holloway, and Ali Bagherpour. "Computational Study of Aerial Sprays Used for Forest Protection." In ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting collocated with 8th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-30270.
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The efficacy of pesticide sprays is strongly dependent on the accuracy of the droplet size spectrum. Over estimates of droplet size may result in excessive drift or ineffective doses, while under estimates of droplet size result in excessive releases. This situation is not only bad for the environment; it incurs large operating costs (spray usually accounts for 30% of total cost). This paper describes the study of droplet sprays commonly used in the agriculture and forestry management. It combines experimental wind tunnel testing and Computational Fluid Dynamic (CFD) methods to develop a fundamental understanding of droplet generation and dispersion in the wake of the atomizer spray system. The results will assist designers of spray technology and applicators in delivering pesticide to its target. The CFD models that are developed and calibrated will further allow the wind tunnel data to be generalized; thus, allowing less wind tunnel testing and eventually direct simulation of droplet dispersion in aircraft wakes. The CFD models are developed for the poly-dispersed sprays released from a Micronair AU4000 atomizer (a standard atomizer used for forest protection) at an airspeed of 67 m/s. Simulations are performed using a Lagrangian (droplet phase) - Eulerian (fluid phase) procedure and include droplet drag/body forces and turbulent dispersion of droplets. The Base-line Reynolds Stress Model (BSL RSM) turbulence model is used to compute turbulence levels in the air phase. The CFD simulations include the sprayer and a large portion of the wind tunnel geometry in order to facilitate in validation. The computational results are compared to full scale experimental measurements of pressure, gas phase velocity, droplet velocity, and droplet size spectra measured using Phase Doppler Interferometry (PDI) and Hotwire Anemometry. Measurements are available along radial lines at 0.5, 1, 2 and 4 m downstream of the atomizer.
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Gao, GuoHua, XuBo Wang, Tao Ding, ZiHua Zhang, and JinFeng Wei. "Research on agricultural equipment design method based on MBSE." In International Conference on Mechanical Design and Simulation (MDS 2022), edited by Dongyan Shi and Guanglei Wu. SPIE, 2022. http://dx.doi.org/10.1117/12.2638727.
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Borghesi, Giulia, and Giuseppe Vignali. "Life cycle assessment of organic Parmesan Cheese considering the whole dairy supply chain." In The 5th International Food Operations & Processing Simulation Workshop. CAL-TEK srl, 2019. http://dx.doi.org/10.46354/i3m.2019.foodops.004.
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Agriculture and food manufacturing have a considerable effect on the environment emissions: holdings and farms play an important role about greenhouse gas emissions and water consumption. This study aims at evaluating the environmental impact of one of the most important Italian DOP product: organic Parmesan Cheese. Environmental performances of the whole dairy supply chain have been assessed according to the life cycle assessment approach (LCA). In this analysis Parmesan Cheese is made from an organic dairy farm in Emilia Romagna, which uses the milk from three different organic livestock productions. Organic agriculture is different from conventional; the major difference is represented by the avoidance of the use of synthetic fertilizers and pesticides made in chemical industry process. Organic agriculture uses organic fertilizers to encourage the natural fertility of the soil respecting the environment and the agro-system. In this case, life cycle approach is used to assess the carbon footprint and the water footprint of organic Parmesan Cheese considering the milk and cheese production. The object at this level is investigating the environmental impact considering the situation before some improvement changes. The functional unit is represented by 1 kg of organic Parmesan Cheese; inventory data refer to the situation in year 2017 and system boundaries consider the inputs related to the cattle and dairy farm until the ripening (included). The carbon footprint is investigated using IPCC 2013 Global Warming Potential (GWP) 100a method, developed by Intergovernmental Panel on Climate Change, and reported in kg of CO2eq. Otherwise, water footprint allows to measure the water consumption and in this work it is assessed using AWARE method (Available Water REmaining).
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Ren, Haifeng, and Yansheng Song. "A New 3D Crack Simulation Method of High Pressure Rubber Hose Pipe." In 2021 International Conference on Electronic Information Technology and Smart Agriculture (ICEITSA). IEEE, 2021. http://dx.doi.org/10.1109/iceitsa54226.2021.00073.
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Xiaogang Wang, V. E. Kuzmichev, Yun Luo, and Yue Li. "A garment simulating method based on scanning technology." In 2010 International Conference On Computer and Communication Technologies in Agriculture Engineering (CCTAE). IEEE, 2010. http://dx.doi.org/10.1109/cctae.2010.5544116.
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Li, J., Z. H. Zhou, J. J. Liu, and H. Wang. "The simulation methods and application on agricultural nonpoint source pollution: a review." In International Conference on Environmental Science and Biological Engineering. Southampton, UK: WIT Press, 2014. http://dx.doi.org/10.2495/esbe140911.
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Li Chunqing, Li Xingman, and Wang Tao. "Notice of Retraction: Research on MBR modeling and simulation achieved by the least square method." In 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering (CCTAE 2010). IEEE, 2010. http://dx.doi.org/10.1109/cctae.2010.5544232.
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Payungsak Junyusen and Tomohiro Takigawa. "Simulation of a Steering Aid Method for an Agricultural Tractor-Trailer System." In 2010 Pittsburgh, Pennsylvania, June 20 - June 23, 2010. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2010. http://dx.doi.org/10.13031/2013.29711.
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Yang, Yan-min, Yonghui Yang, Shu-min Han, and Yu-kun Hu. "Simulation of temporal and spatial distribution of required irrigation water by crop models and the pan evaporation coefficient method." In International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009). SPIE, 2009. http://dx.doi.org/10.1117/12.836674.
Full textReports on the topic "Agriculture Simulation Methods"
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Shani, Uri, Lynn Dudley, Alon Ben-Gal, Menachem Moshelion, and Yajun Wu. Root Conductance, Root-soil Interface Water Potential, Water and Ion Channel Function, and Tissue Expression Profile as Affected by Environmental Conditions. United States Department of Agriculture, October 2007. http://dx.doi.org/10.32747/2007.7592119.bard.
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Constraints on water resources and the environment necessitate more efficient use of water. The key to efficient management is an understanding of the physical and physiological processes occurring in the soil-root hydraulic continuum.While both soil and plant leaf water potentials are well understood, modeled and measured, the root-soil interface where actual uptake processes occur has not been sufficiently studied. The water potential at the root-soil interface (yᵣₒₒₜ), determined by environmental conditions and by soil and plant hydraulic properties, serves as a boundary value in soil and plant uptake equations. In this work, we propose to 1) refine and implement a method for measuring yᵣₒₒₜ; 2) measure yᵣₒₒₜ, water uptake and root hydraulic conductivity for wild type tomato and Arabidopsis under varied q, K⁺, Na⁺ and Cl⁻ levels in the root zone; 3) verify the role of MIPs and ion channels response to q, K⁺ and Na⁺ levels in Arabidopsis and tomato; 4) study the relationships between yᵣₒₒₜ and root hydraulic conductivity for various crops representing important botanical and agricultural species, under conditions of varying soil types, water contents and salinity; and 5) integrate the above to water uptake term(s) to be implemented in models. We have made significant progress toward establishing the efficacy of the emittensiometer and on the molecular biology studies. We have added an additional method for measuring ψᵣₒₒₜ. High-frequency water application through the water source while the plant emerges and becomes established encourages roots to develop towards and into the water source itself. The yᵣₒₒₜ and yₛₒᵢₗ values reflected wetting and drying processes in the rhizosphere and in the bulk soil. Thus, yᵣₒₒₜ can be manipulated by changing irrigation level and frequency. An important and surprising finding resulting from the current research is the obtained yᵣₒₒₜ value. The yᵣₒₒₜ measured using the three different methods: emittensiometer, micro-tensiometer and MRI imaging in both sunflower, tomato and corn plants fell in the same range and were higher by one to three orders of magnitude from the values of -600 to -15,000 cm suggested in the literature. We have added additional information on the regulation of aquaporins and transporters at the transcript and protein levels, particularly under stress. Our preliminary results show that overexpression of one aquaporin gene in tomato dramatically increases its transpiration level (unpublished results). Based on this information, we started screening mutants for other aquaporin genes. During the feasibility testing year, we identified homozygous mutants for eight aquaporin genes, including six mutants for five of the PIP2 genes. Including the homozygous mutants directly available at the ABRC seed stock center, we now have mutants for 11 of the 19 aquaporin genes of interest. Currently, we are screening mutants for other aquaporin genes and ion transporter genes. Understanding plant water uptake under stress is essential for the further advancement of molecular plant stress tolerance work as well as for efficient use of water in agriculture. Virtually all of Israel’s agriculture and about 40% of US agriculture is made possible by irrigation. Both countries face increasing risk of water shortages as urban requirements grow. Both countries will have to find methods of protecting the soil resource while conserving water resources—goals that appear to be in direct conflict. The climate-plant-soil-water system is nonlinear with many feedback mechanisms. Conceptual plant uptake and growth models and mechanism-based computer-simulation models will be valuable tools in developing irrigation regimes and methods that maximize the efficiency of agricultural water. This proposal will contribute to the development of these models by providing critical information on water extraction by the plant that will result in improved predictions of both water requirements and crop yields. Plant water use and plant response to environmental conditions cannot possibly be understood by using the tools and language of a single scientific discipline. This proposal links the disciplines of soil physics and soil physical chemistry with plant physiology and molecular biology in order to correctly treat and understand the soil-plant interface in terms of integrated comprehension. Results from the project will contribute to a mechanistic understanding of the SPAC and will inspire continued multidisciplinary research.
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Miles, Gaines E., Yael Edan, F. Tom Turpin, Avshalom Grinstein, Thomas N. Jordan, Amots Hetzroni, Stephen C. Weller, Marvin M. Schreiber, and Okan K. Ersoy. Expert Sensor for Site Specification Application of Agricultural Chemicals. United States Department of Agriculture, August 1995. http://dx.doi.org/10.32747/1995.7570567.bard.
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In this work multispectral reflectance images are used in conjunction with a neural network classifier for the purpose of detecting and classifying weeds under real field conditions. Multispectral reflectance images which contained different combinations of weeds and crops were taken under actual field conditions. This multispectral reflectance information was used to develop algorithms that could segment the plants from the background as well as classify them into weeds or crops. In order to segment the plants from the background the multispectrial reflectance of plants and background were studied and a relationship was derived. It was found that using a ratio of two wavelenght reflectance images (750nm and 670nm) it was possible to segment the plants from the background. Once ths was accomplished it was then possible to classify the segmented images into weed or crop by use of the neural network. The neural network developed for this work is a modification of the standard learning vector quantization algorithm. This neural network was modified by replacing the time-varying adaptation gain with a constant adaptation gain and a binary reinforcement function. This improved accuracy and training time as well as introducing several new properties such as hill climbing and momentum addition. The network was trained and tested with different wavelength combinations in order to find the best results. Finally, the results of the classifier were evaluated using a pixel based method and a block based method. In the pixel based method every single pixel is evaluated to test whether it was classified correctly or not and the best weed classification results were 81% and its associated crop classification accuracy is 57%. In the block based classification method, the image was divided into blocks and each block was evaluated to determine whether they contained weeds or not. Different block sizes and thesholds were tested. The best results for this method were 97% for a block size of 8 inches and a pixel threshold of 60. A simulation model was developed to 1) quantify the effectiveness of a site-specific sprayer, 2) evaluate influence of diffeent design parameters on efficiency of the site-specific sprayer. In each iteration of this model, infected areas (weed patches) in the field were randomly generated and the amount of required herbicides for spraying these areas were calculated. The effectiveness of the sprayer was estimated for different stain sizes, nozzle types (conic and flat), nozzle sizes and stain detection levels of the identification system. Simulation results indicated that the flat nozzle is much more effective as compared to the conic nozzle and its relative efficiency is greater for small nozzle sizes. By using a site-specific sprayer, the average ratio between the spraying areas and the stain areas is about 1.1 to 1.8 which can save up to 92% of herbicides, especially when the proportion of the stain areas is small.
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Pullammanappallil, Pratap, Haim Kalman, and Jennifer Curtis. Investigation of particulate flow behavior in a continuous, high solids, leach-bed biogasification system. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600038.bard.
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Recent concerns regarding global warming and energy security have accelerated research and developmental efforts to produce biofuels from agricultural and forestry residues, and energy crops. Anaerobic digestion is a promising process for producing biogas-biofuel from biomass feedstocks. However, there is a need for new reactor designs and operating considerations to process fibrous biomass feedstocks. In this research project, the multiphase flow behavior of biomass particles was investigated. The objective was accomplished through both simulation and experimentation. The simulations included both particle-level and bulk flow simulations. Successful computational fluid dynamics (CFD) simulation of multiphase flow in the digester is dependent on the accuracy of constitutive models which describe (1) the particle phase stress due to particle interactions, (2) the particle phase dissipation due to inelastic interactions between particles and (3) the drag force between the fibres and the digester fluid. Discrete Element Method (DEM) simulations of Homogeneous Cooling Systems (HCS) were used to develop a particle phase dissipation rate model for non-spherical particle systems that was incorporated in a two-fluid CFDmultiphase flow model framework. Two types of frictionless, elongated particle models were compared in the HCS simulations: glued-sphere and true cylinder. A new model for drag for elongated fibres was developed which depends on Reynolds number, solids fraction, and fibre aspect ratio. Schulze shear test results could be used to calibrate particle-particle friction for DEM simulations. Several experimental measurements were taken for biomass particles like olive pulp, orange peels, wheat straw, semolina, and wheat grains. Using a compression tester, the breakage force, breakage energy, yield force, elastic stiffness and Young’s modulus were measured. Measurements were made in a shear tester to determine unconfined yield stress, major principal stress, effective angle of internal friction and internal friction angle. A liquid fludized bed system was used to determine critical velocity of fluidization for these materials. Transport measurements for pneumatic conveying were also assessed. Anaerobic digestion experiments were conducted using orange peel waste, olive pulp and wheat straw. Orange peel waste and olive pulp could be anaerobically digested to produce high methane yields. Wheat straw was not digestible. In a packed bed reactor, anaerobic digestion was not initiated above bulk densities of 100 kg/m³ for peel waste and 75 kg/m³ for olive pulp. Interestingly, after the digestion has been initiated and balanced methanogenesis established, the decomposing biomass could be packed to higher densities and successfully digested. These observations provided useful insights for high throughput reactor designs. Another outcome from this project was the development of low cost devices to measure methane content of biogas for off-line (US$37), field (US$50), and online (US$107) applications.
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Shmulevich, Itzhak, Shrini Upadhyaya, Dror Rubinstein, Zvika Asaf, and Jeffrey P. Mitchell. Developing Simulation Tool for the Prediction of Cohesive Behavior Agricultural Materials Using Discrete Element Modeling. United States Department of Agriculture, October 2011. http://dx.doi.org/10.32747/2011.7697108.bard.
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The underlying similarity between soils, grains, fertilizers, concentrated animal feed, pellets, and mixtures is that they are all granular materials used in agriculture. Modeling such materials is a complex process due to the spatial variability of such media, the origin of the material (natural or biological), the nonlinearity of these materials, the contact phenomenon and flow that occur at the interface zone and between these granular materials, as well as the dynamic effect of the interaction process. The lack of a tool for studying such materials has limited the understanding of the phenomena relevant to them, which in turn has led to energy loss and poor quality products. The objective of this study was to develop a reliable prediction simulation tool for cohesive agricultural particle materials using Discrete Element Modeling (DEM). The specific objectives of this study were (1) to develop and verify a 3D cohesionless agricultural soil-tillage tool interaction model that enables the prediction of displacement and flow in the soil media, as well as forces acting on various tillage tools, using the discrete element method; (2) to develop a micro model for the DEM formulation by creating a cohesive contact model based on liquid bridge forces for various agriculture materials; (3) to extend the model to include both plastic and cohesive behavior of various materials, such as grain and soil structures (e.g., compaction level), textures (e.g., clay, loam, several grains), and moisture contents; (4) to develop a method to obtain the parameters for the cohesion contact model to represent specific materials. A DEM model was developed that can represent both plastic and cohesive behavior of soil. Soil cohesive behavior was achieved by considering tensile force between elements. The developed DEM model well represented the effect of wedge shape on soil behavior and reaction force. Laboratory test results showed that wedge penetration resistance in highly compacted soil was two times greater than that in low compacted soil, whereas DEM simulation with parameters obtained from the test of low compacted soil could not simply be extended to that of high compacted soil. The modified model took into account soil failure strength that could be changed with soil compaction. A three dimensional representation composed of normal displacement, shear failure strength and tensile failure strength was proposed to design mechanical properties between elements. The model based on the liquid bridge theory. An inter particle tension force measurement tool was developed and calibrated A comprehensive study of the parameters of the contact model for the DEM taking into account the cohesive/water-bridge was performed on various agricultural grains using this measurement tool. The modified DEM model was compared and validated against the test results. With the newly developed model and procedure for determination of DEM parameters, we could reproduce the high compacted soil behavior and reaction forces both qualitatively and quantitatively for the soil conditions and wedge shapes used in this study. Moreover, the effect of wedge shape on soil behavior and reaction force was well represented with the same parameters. During the research we made use of the commercial PFC3D to analyze soil tillage implements. An investigation was made of three different head drillers. A comparison of three commonly used soil tillage systems was completed, such as moldboard plow, disc plow and chisel plow. It can be concluded that the soil condition after plowing by the specific implement can be predicted by the DEM model. The chisel plow is the most economic tool for increasing soil porosity. The moldboard is the best tool for soil manipulation. It can be concluded that the discrete element simulation can be used as a reliable engineering tool for soil-implement interaction quantitatively and qualitatively.
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Law, Edward, Samuel Gan-Mor, Hazel Wetzstein, and Dan Eisikowitch. Electrostatic Processes Underlying Natural and Mechanized Transfer of Pollen. United States Department of Agriculture, May 1998. http://dx.doi.org/10.32747/1998.7613035.bard.
Full textAbstract:
The project objective was to more fully understand how the motion of pollen grains may be controlled by electrostatic forces, and to develop a reliable mechanized pollination system based upon sound electrostatic and aerodynamic principles. Theoretical and experimental analyses and computer simulation methods which investigated electrostatic aspects of natural pollen transfer by insects found that: a) actively flying honeybees accumulate ~ 23 pC average charge (93 pC max.) which elevates their bodies to ~ 47 V likely by triboelectrification, inducing ~ 10 fC of opposite charge onto nearby pollen grains, and overcoming their typically 0.3-3.9 nN detachment force resulting in non-contact electrostatic pollen transfer across a 5 mm or greater air gap from anther-to-bee, thus providing a theoretical basis for earlier experimental observations and "buzz pollination" events; b) charge-relaxation characteristics measured for flower structural components (viz., 3 ns and 25 ns time constants, respectively, for the stigma-style vs. waxy petal surfaces) ensure them to be electrically appropriate targets for electrodeposition of charged pollen grains but not differing sufficiently to facilitate electrodynamic focusing onto the stigma; c) conventional electrostatic focusing beneficially concentrates pollen-deposition electric fields onto the pistill tip by 3-fold as compared to that onto underlying flower structures; and d) pollen viability is adequately maintained following exposure to particulate charging/management fields exceeding 2 MV/m. Laboratory- and field-scale processes/prototype machines for electrostatic application of pollen were successfully developed to dispense pollen in both a dry-powder phase and in a liquid-carried phase utilizing corona, triboelectric, and induction particulate-charging methods; pollen-charge levels attained (~ 1-10 mC/kg) provide pollen-deposition forces 10-, 77-, and 100-fold greater than gravity, respectively, for such charged pollen grains subjected to a 1 kV/cm electric field. Lab and field evaluations have documented charged vs. ukncharged pollen deposition to be significantly (a = 0.01-0.05) increased by 3.9-5.6 times. Orchard trials showed initial fruit set on branches individually treated with electrostatically applied pollen to typically increase up to ~ 2-fold vs. uncharged pollen applications; however, whole-tree applications have not significantly shown similar levels of benefit and corrective measures continue. Project results thus contribute important basic knowledge and applied electrostatics technology which will provide agriculture with alternative/supplemental mechanized pollination systems as tranditional pollen-transfer vectors are further endangered by natural and man-fade factors.
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Zhang, Renduo, and David Russo. Scale-dependency and spatial variability of soil hydraulic properties. United States Department of Agriculture, November 2004. http://dx.doi.org/10.32747/2004.7587220.bard.
Full textAbstract:
Water resources assessment and protection requires quantitative descriptions of field-scale water flow and contaminant transport through the subsurface, which, in turn, require reliable information about soil hydraulic properties. However, much is still unknown concerning hydraulic properties and flow behavior in heterogeneous soils. Especially, relationships of hydraulic properties changing with measured scales are poorly understood. Soil hydraulic properties are usually measured at a small scale and used for quantifying flow and transport in large scales, which causes misleading results. Therefore, determination of scale-dependent and spatial variability of soil hydraulic properties provides the essential information for quantifying water flow and chemical transport through the subsurface, which are the key processes for detection of potential agricultural/industrial contaminants, reduction of agricultural chemical movement, improvement of soil and water quality, and increase of agricultural productivity. The original research objectives of this project were: 1. to measure soil hydraulic properties at different locations and different scales at large fields; 2. to develop scale-dependent relationships of soil hydraulic properties; and 3. to determine spatial variability and heterogeneity of soil hydraulic properties as a function of measurement scales. The US investigators conducted field and lab experiments to measure soil hydraulic properties at different locations and different scales. Based on the field and lab experiments, a well-structured database of soil physical and hydraulic properties was developed. The database was used to study scale-dependency, spatial variability, and heterogeneity of soil hydraulic properties. An improved method was developed for calculating hydraulic properties based on infiltration data from the disc infiltrometer. Compared with the other methods, the proposed method provided more accurate and stable estimations of the hydraulic conductivity and macroscopic capillary length, using infiltration data collected atshort experiment periods. We also developed scale-dependent relationships of soil hydraulic properties using the fractal and geostatistical characterization. The research effort of the Israeli research team concentrates on tasks along the second objective. The main accomplishment of this effort is that we succeed to derive first-order, upscaled (block effective) conductivity tensor, K'ᵢⱼ, and time-dependent dispersion tensor, D'ᵢⱼ, i,j=1,2,3, for steady-state flow in three-dimensional, partially saturated, heterogeneous formations, for length-scales comparable with those of the formation heterogeneity. Numerical simulations designed to test the applicability of the upscaling methodology to more general situations involving complex, transient flow regimes originating from periodic rain/irrigation events and water uptake by plant roots suggested that even in this complicated case, the upscaling methodology essentially compensated for the loss of sub-grid-scale variations of the velocity field caused by coarse discretization of the flow domain. These results have significant implications with respect to the development of field-scale solute transport models capable of simulating complex real-world scenarios in the subsurface, and, in turn, are essential for the assessment of the threat posed by contamination from agricultural and/or industrial sources.
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Crowley, David E., Dror Minz, and Yitzhak Hadar. Shaping Plant Beneficial Rhizosphere Communities. United States Department of Agriculture, July 2013. http://dx.doi.org/10.32747/2013.7594387.bard.
Full textAbstract:
PGPR bacteria include taxonomically diverse bacterial species that function for improving plant mineral nutrition, stress tolerance, and disease suppression. A number of PGPR are being developed and commercialized as soil and seed inoculants, but to date, their interactions with resident bacterial populations are still poorly understood, and-almost nothing is known about the effects of soil management practices on their population size and activities. To this end, the original objectives of this research project were: 1) To examine microbial community interactions with plant-growth-promoting rhizobacteria (PGPR) and their plant hosts. 2) To explore the factors that affect PGPR population size and activity on plant root surfaces. In our original proposal, we initially prqposed the use oflow-resolution methods mainly involving the use of PCR-DGGE and PLFA profiles of community structure. However, early in the project we recognized that the methods for studying soil microbial communities were undergoing an exponential leap forward to much more high resolution methods using high-throughput sequencing. The application of these methods for studies on rhizosphere ecology thus became a central theme in these research project. Other related research by the US team focused on identifying PGPR bacterial strains and examining their effective population si~es that are required to enhance plant growth and on developing a simulation model that examines the process of root colonization. As summarized in the following report, we characterized the rhizosphere microbiome of four host plant species to determine the impact of the host (host signature effect) on resident versus active communities. Results of our studies showed a distinct plant host specific signature among wheat, maize, tomato and cucumber, based on the following three parameters: (I) each plant promoted the activity of a unique suite of soil bacterial populations; (2) significant variations were observed in the number and the degree of dominance of active populations; and (3)the level of contribution of active (rRNA-based) populations to the resident (DNA-based) community profiles. In the rhizoplane of all four plants a significant reduction of diversity was observed, relative to the bulk soil. Moreover, an increase in DNA-RNA correspondence indicated higher representation of active bacterial populations in the residing rhizoplane community. This research demonstrates that the host plant determines the bacterial community composition in its immediate vicinity, especially with respect to the active populations. Based on the studies from the US team, we suggest that the effective population size PGPR should be maintained at approximately 105 cells per gram of rhizosphere soil in the zone of elongation to obtain plant growth promotion effects, but emphasize that it is critical to also consider differences in the activity based on DNA-RNA correspondence. The results ofthis research provide fundamental new insight into the composition ofthe bacterial communities associated with plant roots, and the factors that affect their abundance and activity on root surfaces. Virtually all PGPR are multifunctional and may be expected to have diverse levels of activity with respect to production of plant growth hormones (regulation of root growth and architecture), suppression of stress ethylene (increased tolerance to drought and salinity), production of siderophores and antibiotics (disease suppression), and solubilization of phosphorus. The application of transcriptome methods pioneered in our research will ultimately lead to better understanding of how management practices such as use of compost and soil inoculants can be used to improve plant yields, stress tolerance, and disease resistance. As we look to the future, the use of metagenomic techniques combined with quantitative methods including microarrays, and quantitative peR methods that target specific genes should allow us to better classify, monitor, and manage the plant rhizosphere to improve crop yields in agricultural ecosystems. In addition, expression of several genes in rhizospheres of both cucumber and whet roots were identified, including mostly housekeeping genes. Denitrification, chemotaxis and motility genes were preferentially expressed in wheat while in cucumber roots bacterial genes involved in catalase, a large set of polysaccharide degradation and assimilatory sulfate reduction genes were preferentially expressed.
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Warrick, Arthur W., Gideon Oron, Mary M. Poulton, Rony Wallach, and Alex Furman. Multi-Dimensional Infiltration and Distribution of Water of Different Qualities and Solutes Related Through Artificial Neural Networks. United States Department of Agriculture, January 2009. http://dx.doi.org/10.32747/2009.7695865.bard.
Full textAbstract:
The project exploits the use of Artificial Neural Networks (ANN) to describe infiltration, water, and solute distribution in the soil during irrigation. It provides a method of simulating water and solute movement in the subsurface which, in principle, is different and has some advantages over the more common approach of numerical modeling of flow and transport equations. The five objectives were (i) Numerically develop a database for the prediction of water and solute distribution for irrigation; (ii) Develop predictive models using ANN; (iii) Develop an experimental (laboratory) database of water distribution with time; within a transparent flow cell by high resolution CCD video camera; (iv) Conduct field studies to provide basic data for developing and testing the ANN; and (v) Investigate the inclusion of water quality [salinity and organic matter (OM)] in an ANN model used for predicting infiltration and subsurface water distribution. A major accomplishment was the successful use of Moment Analysis (MA) to characterize “plumes of water” applied by various types of irrigation (including drip and gravity sources). The general idea is to describe the subsurface water patterns statistically in terms of only a few (often 3) parameters which can then be predicted by the ANN. It was shown that ellipses (in two dimensions) or ellipsoids (in three dimensions) can be depicted about the center of the plume. Any fraction of water added can be related to a ‘‘probability’’ curve relating the size of the ellipse (or ellipsoid) that contains that amount of water. The initial test of an ANN to predict the moments (and hence the water plume) was with numerically generated data for infiltration from surface and subsurface drip line and point sources in three contrasting soils. The underlying dataset consisted of 1,684,500 vectors (5 soils×5 discharge rates×3 initial conditions×1,123 nodes×20 print times) where each vector had eleven elements consisting of initial water content, hydraulic properties of the soil, flow rate, time and space coordinates. The output is an estimate of subsurface water distribution for essentially any soil property, initial condition or flow rate from a drip source. Following the formal development of the ANN, we have prepared a “user-friendly” version in a spreadsheet environment (in “Excel”). The input data are selected from appropriate values and the output is instantaneous resulting in a picture of the resulting water plume. The MA has also proven valuable, on its own merit, in the description of the flow in soil under laboratory conditions for both wettable and repellant soils. This includes non-Darcian flow examples and redistribution and well as infiltration. Field experiments were conducted in different agricultural fields and various water qualities in Israel. The obtained results will be the basis for the further ANN models development. Regions of high repellence were identified primarily under the canopy of various orchard crops, including citrus and persimmons. Also, increasing OM in the applied water lead to greater repellency. Major scientific implications are that the ANN offers an alternative to conventional flow and transport modeling and that MA is a powerful technique for describing the subsurface water distributions for normal (wettable) and repellant soil. Implications of the field measurements point to the special role of OM in affecting wettability, both from the irrigation water and from soil accumulation below canopies. Implications for agriculture are that a modified approach for drip system design should be adopted for open area crops and orchards, and taking into account the OM components both in the soil and in the applied waters.