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Crop development models are commonly used in research. However, their use as crop management tools for growers is rare. Decision support systems (DSS), which combine crop models with expert systems, are being developed to provide management assistance to growers. Researchers at Oregon State University are in the process of developing a DSS. Research was conducted to develop a computer program to provide current and generated weather data for use by the DSS. The objectives of this research were to obtain a weather station, develop a set of quality control procedures to check data from the station, obtain a weather generator program, and create a weather data manager program to implement the above objectives. A weather station was obtained and was placed near two existing weather stations for ten months. Data from the weather station was compared with the other two stations for values of monthly average maximum temperature, minimum temperature, and daily total solar radiation and monthly total precipitation. The weather station performed well. Only measurements of total daily solar radiation were consistently different from the other stations. Based on a comparison of the weather station with an Eppley pyranometer, a factor was calculated to correct the solar radiation readings. The quality control procedures used on the weather data were adapted from automated procedures given in the literature. When tested, the procedures performed as desired. When used on actual data from the weather station, values that failed the procedures were apparently legitimate values. Options were added to the data manager program that allow the user to quickly decide what to do with failed values. For a weather data generator, WGEN was chosen from the generators presented in the literature. An input parameter file was created for the Corvallis, Oregon area and thirty years of data were generated. Monthly means from this data were compared with thirty-year historical monthly means for Corvallis. Precipitation data from WGEN compared well with the historical data. The generated data for maximum and minimum temperature and daily total solar radiation had great differences from the historical data. It is believed that the input parameters for the Corvallis area suggested by the authors of WGEN are not appropriate. The weather data manager program was written in the C programming language, and occupies approximately 98 kilobytes of disk space, not including the eleven files created directly and indirectly by the program. The main functions of the program are: 1) retrieving data from the weather station and performing quality control procedures on the data (allowing the user to decide what to do with values that failed QC); 2) viewing and editing of files by the user; 3) weather data generation (creating a file of only generated data or appending generated data to the file of current data from the weather station to create a file containing a full year of weather data); and 4) miscellaneous functions (monitoring the weather station, setting the calendar in the station's datalogger, and changing information used by the data manager program). It is hoped that this program will be a significant contribution towards the development of a decision support system. / Graduation date: 1992

Made available in DSpace on 2017-07-21T14:19:26Z (GMT). No. of bitstreams: 1 Giuvane Conti.pdf: 4640595 bytes, checksum: 144683112870e74bdbcd0335c9aac15a (MD5) Previous issue date: 2015-10-29 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The growth of the smartphone market, combined with the technologies used in these devices, motivates the use of this equipment in field applications because of its georeferencing potential and internet access. In cloud computing, a prominent concept is the Internet of Things (IoT) due to the exponential growth of data where are generated in day-to-day. The idea of centralization of this data, acquired from various areas, such as agriculture, urban mobility, urbanization, government, health, business, etc., are current challenges that the IoT find out to solve. It still in contrast, NoSQL databases, which have some differentiating features from relational models and they have the potential to solve some of these challenges, such as horizontal growth, high data availability and easy storage of complex structures. Another promising technology to solve some of these challenges is the RESTful, a web service that provides faster and works with fewer bytes than the communication with Simple Object Access Protocol (SOAP). In this context, this research was developed with the goal of creating a GIS Mobile application, to collect geospatial data (points, lines and polygons) and store them in an application server, in Software as a Service (SaaS) architecture, using RESTful and NoSQL. The structure follows the concept of IoT, with high potential for integration data from different areas, such as in this study. In this research were performed tests in field at the Fazenda Escola Capão-da-onça (FESCON) on 11 and 13 August 2015. A planning missions, has been pre - set to get the best results from Global Positioning System (GPS). On those dates were collected geo data on crop plots, lines and points of interest, such as erosion areas, failures in the soil and low productivity areas. The samples taken were successful and had no problems or failures, that is, the application provided facility of use and synchronization of the data with the application server. The results of the field surveys, have been exported to files in KML format and presented on thematic maps with the help of Google Earth tool. In conclusion, the project has a high potential for registration of agricultural properties and spatial geo data and, your architecture is relevant for the development of geospatial, agricultural projects in GIS Mobile area, where need to handle complex data and provide high data availability, such as Rural environmental registry (CAR, in brazil); Precision agriculture; Georeferenced control of agricultural, natural resources and urbanization data; and Business logistics applications. / O crescimento do mercado de smartphones, combinado com as tecnologias empregadas nestes aparelhos, motiva seu uso em aplicações a campo devido ao seu potencial de georreferenciamento e acesso a internet. Em computação na nuvem, um conceito proeminente é a Internet of Things (IoT) ou Internet das Coisas devido ao crescimento exponencial de dados que são gerados no dia-a-dia. A ideia da centralização destes dados, provenientes de várias áreas, como: agricultura, mobilidade urbana, urbanização, governamentais, saúde, empresariais, etc., são desafios atuais que a Internet das Coisas procura solucionar. Destaca-se ainda, os bancos de dados NoSQL, os quais possuem potencial para solução de alguns destes desafios. Outra tecnologia promissora para solucionar alguns destes desafios é o padrão RESTful, um web service que apresenta rapidez e trabalha com quantidades reduzidas de bytes em sua comunicação. Neste contexto, esta pesquisa foi desenvolvida com o objetivo de criar um Sistema de Informação Geográfica (SIG) Móvel, que realize a coleta de dados geoespaciais (pontos, linhas e polígonos), se comunique com um servidor de aplicação, no modelo Software as a Service (SaaS) que irá armazenar os dados em um banco de dados MongoDB e sua arquitetura segue o conceito de Internet das Coisas. Foram realizados testes a campo na Fazenda Escola Capão-da-onça (FESCON) nos dias 11 e 13 de agosto de 2015. Um planejamento de missões, foi pré - estabelecido, para obter os melhores resultados do Sistema de Posicionamento Global (GPS). Nas referidas datas foram coletados polígonos em talhões de culturas, linhas e pontos de interesse, tais como áreas de erosão, falhas no solo e áreas de baixa produtividade. As coletas realizadas foram bem sucedidas, o aplicativo proporcionou facilidade de uso e de sincronismo dos dados com o servidor de aplicação. Os resultados, dos levantamentos à campo, foram exportados para arquivos no formato KML e apresentados em mapas, com auxílio da ferramenta Google Earth. Conclui-se que, o projeto apresenta alto potencial de uso para cadastro de propriedades agrícolas e dados espacializados e, sua arquitetura é pertinente para o desenvolvimento de projetos geoespaciais, agrícolas em SIG Móvel, que necessitem tratar dados complexos e apresentem alta disponibilidade de dados, tais como: Cadastro Ambiental Rural (CAR); Agricultura de precisão; Controle georreferenciado de dados agrícolas, recursos naturais e urbanização; e Aplicações empresariais de logística.

Thesis (MSc)--Stellenbosch University, 2003. / ENGLISH ABSTRACT: With the inception of precision farming techniques during the last decade, agricultural efficiency has improved, leading to greater productivity and enhanced economic benefits associated with agriculture. The awareness of health risks associated with food borne diseases has also increased. Systems such as Hazard Analysis and Critical Control Points (RACCP) in the USA and Good Agricultural Practices (GAP) in Europe are trying to ensure that no food showing signs of microbial contamination associated with production techniques are allowed onto the export market. Growers participating in exporting are thus being forced to conform to the requirements set by international customers. The aim of this study was to compile a computerized record keeping system that would aid farmers with the implementation of GAP on farms, by making use of GIS capabilities. A database, consisting of GAP-specific data was developed. ArcView GIS was used to implement the database, while customized analyses procedures through the use of Avenue assisted in GAP-specific farming related decisions. An agricultural area focusing on the export market was needed for this study, and the nut producing Levubu district was identified as ideal. By making use of ArcView GIS, distinct relationships between different data sets were portrayed in tabular, graphical, geographical and report format. GAP requirements state that growers must base decisions on timely, relevant information. With information available in the above-mentioned formats, decisions regarding actions taken can be justified. By analysing the complex interaction between datasets, the influences that agronomical inputs have on production were portrayed, moving beyond the standard requirements of GAP. Agricultural activities produce enormous quantities of data, and GIS proved to be an indispensable tool because of the ability to analyse and manipulate data with a spatial component. The implementation of good agricultural practices lends itself to the use of GIS. With the correct information available at the right time, better decisions can promote optimal croppmg, whilst rmmrrnzmg the negative effects on the consumer and environment. / AFRIKAANSE OPSOMMING: Gedurende die afgelope dekade het die gebruik van presisie boerderytegnieke tot verbeterde gewasverbouing gelei, wat verhoogde produktiwiteit en ekonomiese welvarendheid tot gevolg gehad het. 'n Wêreldwye bewustheid ten opsigte van die oordrag van siektekieme geasosieer met varsprodukte het ontstaan. Met die implementering van Hazard Analysis and Critical Control Points (HACCP) en Good Agricultural Practices (GAP), poog die VSA en Europa om voedsel wat tekens van besmetting toon van die invoermark te weerhou. Buitelandse produsente en uitvoerders word dus hierdeur gedwing om by internasionale voedselstandaarde aan te pas. Hierdie navorsing het ten doel gehad om 'n gerekenariseerde rekordhouding stelsel daar te stel wat produsente sal bystaan tydens die implementering van GAP, deur gebruik te maak van GIS. 'n Databasis gerig op die implementering van GAP is ontwerp. ArcView GIS is gebruik word om die databasis te implementeer, waarna spesifieke navrae die data ontleed het om sodoende die besluitnemingsproses te vergemaklik. 'n Landbou-area wat aktief in die uitvoermark deelneem was benodig vir dié studie, en die Levubu distrik was ideaal. Verwantskappe tussen datastelle is bepaal en uitgebeeld in tabel-, grafiek- en verslag vorm. Die suksesvolle implementering van GAP vereis dat alle besluite op relevante inligting gebaseer word, en met inligting beskikbaar in die bogenoemde formaat kan alle besluite geregverdig word. Deur die komplekse interaksie tussen insette en produksie te analiseer, was dit moontlik om verwantskappe uit te beeld wat verder strek as wat GAP vereistes stipuleer. Deur die gebruikerskoppelvlak in ArcView te verpersoonlik is die gebruiker nie belaai met onnodige berekeninge nie. Aktiwiteite soos landbou produseer groot datastelle, en die vermoë van GIS om die ruimtelike verwantskappe te analiseer en uit te beeld, het getoon dat GIS 'n instrumentele rol in die besluitnemingsproses speel. Deur middel van beter besluitneming kan optimale gewasverbouing verseker word, terwyl die negatiewe impak op die verbruiker en omgewing tot 'n minimum beperk word.