Variable-rate technologies for sprayer applications stand to increase efficacy by ensuring the right amount of chemical is applied at the right location. However, external environmental factors such as droplet drift caused by variable ambient condition, are not yet integrated into modern sprayer systems. Real-time wind velocity measurements can be used to control droplet spectra for reducing spray drift by actuating a variable-orifice nozzle. This work aimed to develop data processing methods needed to filter noise and remove vehicle speed from wind velocity measurements collected with an ultrasonic anemometer aboard a moving platform. Using a global navigation satellite system (GNSS), vehicle speed was calculated in the field and subtracted from apparent wind velocity for comparison to static measurements. Experiments under stationary and dynamic sensor deployments were used to develop an algorithm to provide instantaneous local wind velocity and to better understand the local spatiotemporal variability of wind under field conditions.

The heavy rainfall, gentle to severe topography with high proportion of bare spots, and weed patches emphasize the need of variable rate split (VRS) fertilization in wild blueberry. Two commercial fields were selected in central Nova Scotia to evaluate the impact of VRS fertilization on ammonia volatilization, subsurface water quality, and crop productivity. Management zones were delineated based on slope variability, and different fertilizer rates were applied using global positioning system (GPS) guided prescription map. Ammonia huts were used to quantify the ammonia volatilization losses, while the lysimeters were installed in the fields to evaluate the impact of different fertilizer treatments on subsurface water quality. The VRS treatment significantly decreased the ammonia volatilization losses and nutrients leaching losses as compared to uniform treatment. Based on the results of this study, it can be concluded that VRS fertilization in wild blueberry fields could reduce environmental contamination and improve crop productivity.

Two wild blueberry fields were selected in central Nova Scotia, to characterize and quantify the spatial pattern of variability in soil properties, leaf nutrients and fruit yield, identification of yield influencing soil properties, and to develop management zones for site-specific fertilization. A combination of classical statistics, geostatistical analysis and mapping in Arc GIS 9.3 indicated substantial variation within field. The stepwise regression suggested that the soil EC, horizontal co-planar geometry (HCP), inorganic nitrogen and moisture content were major yield influencing factors. The cluster analysis of the soil variables with the fruit yield also indicated that HCP, inorganic nitrogen, EC, SOM, and ?v were closely grouped with the fruit yield at a similarity level greater than 70%. Based on the results of this study the wild blueberry fields can be divided into different management zones for variable rate fertilization to improve crop production, increase revenue, and reduce potential environmental contamination.

The popularity of variable-rate technology (VRT) has grown. However, the limitations and errors ofthis technology are generally unknown. Therefore, a spatial data model was developed to generate "asapplied"surfaces to advance precision agricultural (PA) practices. A test methodology based on ASAEStandard S341.2 was developed to perform uniform-rate (UR) and variable-rate (VR) tests to characterizedistribution patterns testing four VRT granular applicators (two spinner spreaders and two pneumaticapplicators). Single-pass UR patterns exhibited consistent shapes for three of the applicators with patternsshifts observed for the fourth applicator. Simulated overlap analysis showed that three of the applicatorsperformed satisfactorily with most CVs less than 20% while one applicator performed poorly (CVs andgt;25%). The spinner spreaders over-applied at the margins but the pneumatic applicators under-appliedsuggesting a required adjustment to the effective swath spacing. Therefore, it is recommended that CVsaccompany overlap pattern plots to ensure proper calibration of VRT application.Quantification of the rate response characteristics for the various applicators illustrated varying delayand transition times. Only one applicator demonstrated consistent delay and transition times. A sigmoidalfunction was used to model the rate response for applicators. One applicator exhibited a linear responseduring a decreasing rate change. Rate changes were quicker for the two newer VR control systemssignifying advancement in hydraulic control valve technology. This research illustrates the need forstandard testing protocols for VRT systems to help guide VRT software developers, equipmentmanufacturers, and users.The spatial data model uses GIS functionality to merge applicator descriptive patterns with a spatialfield application file (FAF) to generate an 'as-applied' surface representing the actual distribution ofgranular fertilizer. Field data was collected and used to validate the "as-applied" spatial model.Comparisons between the actual and predicted application rates for several fields were madedemonstrating good correlations for one applicator (several R2 andgt; 0.70), moderate success for anotherapplicator (0.60 andlt; R2 andlt; 0.66), and poor relationships for the third applicator (R2 andlt; 0.49). A comparison ofthe actual application rates to the prescription maps generated R2 values between 0.16 and 0.81demonstrating inconsistent VRT applicator performance. Thus, "as-applied" surfaces provide a means toproperly evaluate VRT while enhancing researchers' ability to compare VR management approaches.

The world population is projected to rise, and there is a growing concern of future food availability. Precision agriculture technologies are one solution to this problem as they aim to produce more food on less land. This study examines the adoption and intensity of precision agriculture technology usage by producers in North Dakota. Data from a North Dakota State University survey was collected and analyzed using an econometric double-hurdle model. Results of the study describe which producers adopt precision agriculture technologies, which technologies complement each other, and what affects the intensity of technology usage. Several technologies were found to have complementary effects on each other, larger farms are more likely to adopt PATs, and crop choices have varying impacts on the adoption and usage of PATs. Most of these findings agree with previous literature, although new light was shed on some new findings and predictions.

Master of Agribusiness / Department of Agricultural Economics / Gregory Ibendahl / One of the latest buzzes amongst agriculture is the storage and analysis of “Big Data.” There are a number of questions surrounding the quality, quantity, and capacity of big data to form real-world decisions based upon past information. Much like the teachings of history, the storybook that big data can reveal about a grower’s operation may hold the answers to the question of: “what is necessary to increase food production which will be required to feed an ever-growing world?” With the increase in interest in precision agriculture, sustainability practices, and the processing of the immense spatial dataset generated on the farm, the next challenge at hand will be in determining how to make technology not only streamlined, but also profitable. Over the past few years, precision agriculture technology has become widely adopted as an agronomic decision making tool. Much like a scientific experiment, the greater the number of similar observations, the greater the degree of confidence can be placed upon a decision. As a means of increasing the number of observations that a farmer can use to base a decision upon, there is becoming increasing demand in being able to combine the data of similar farming operations in order to increase the size and scope of the dataset to generate better decisions benefitting many farms instead of just one. The growing interest in forming community data pools for farm data demonstrates the need for a study for determining how farming practices can be properly benchmarked. The goal was be to evaluate how to use farm data to make economic decisions in a similar manner as one would make agronomic decisions using similar observations. The objective was to design the proper protocol for benchmarking the farm’s potential, and evaluating potential increases in technical efficiency by adopting precision agriculture technology. To accomplish this, a data envelopment analysis was conducted using scale efficiency as a means of determining the frontier of efficient farms. The resounding goal for this study in the future will be to use the model as a means of implementing the secondary process of pooling precision agriculture data to analyze efficiencies gained by the adoption of technology. By demonstrating the value of generating peer groups to increase observations and refine farming practices, farmers can find increased profitability and efficiency by using resources that may already be held within the operation.

Sensors based on LiDAR (Light Detection and Ranging) technology have the potential to provide accurate 3D models of the trees retrieving information such as canopy volume and height. This information can be used for diagnostics and prescriptions of fertilizers and plant protection products on a site-specific basis. This research aimed to investigate the use of LiDAR sensors in orange crops. Orange is one of the most important tree crop in Brazil. So far, research have developed and tested LiDAR based systems for several tree crops. However, usually individual trees or small field plots have been used. Therefore, several aspects related to data acquisition and processing must still be developed for large-scale application. The first study reported in this document (Chapter 3) aimed to develop and test a mobile terrestrial laser scanner (MTLS) and new data processing methods in order to obtain 3D models of large commercial orange groves and spatial information about canopy geometry. A 2D laser sensor and a RTK-GNSS receiver (Real Time Kinematics - Global Navigation Satellite System) were mounted on a vehicle. The data processing was based on generating a georeferenced point cloud, followed by the filtering, classification and surface reconstruction steps. A 25 ha commercial orange grove was used for field validation. The developed data acquisition and processing system was able to produce a reliable point cloud of the grove, providing high resolution canopy volume and height information. The choice of the type of point cloud classification (by individual trees or by transversal sections of the row) and the surface reconstruction algorithm is discussed in this study. The second study (Chapter 4) aimed to characterize the spatial variability of canopy geometry in commercial orange groves. Understanding such variability allows sensor-based variable rate application of inputs (i.e, applying proportional rates of inputs based on the variability of canopy size) to be considered as a suitable strategy to optimize the use of fertilizers and plant protection products. Five commercial orange groves were scanned with the developed MTLS system. According to the variability of canopy volume found in those groves, the input savings as a result of implementing sensor-based variable rate technologies were estimated in about 40%. The second goal of this study was to understand the relationship between canopy geometry and several other relevant attributes of the groves. The canopy volume and height maps of three groves were analyzed against historical yield maps, elevation, soil electrical conductivity, organic matter and clay content maps. The correlations found between canopy geometry and yield or soil maps varied from poor to strong correlations, depending on the grove. When classifying the groves into three classes according to canopy size, the yield performance and soil features inside each class was found to be significantly different, indicating that canopy geometry is a suitable variable to guide management zones delineation in one grove. Overall results from this research show the potential of MTLS systems and subsequent data analysis in orange crops indicating how canopy geometry information can be used in site-specific management practices. / Sensores baseados em tecnologia LiDAR (Light Detection and Ranging) têm o potencial de fornecer modelos tridimensionais de árvores, provendo informações como o volume e altura de copa. Essas informações podem ser utilizadas em diagnósticos e recomendações localizadas de fertilizantes e defensivos agrícolas. Este estudo teve como objetivo investigar o uso de sensores LiDAR na cultura da laranja, uma das principais culturas de porte arbóreo no Brasil. Diversas pesquisas têm desenvolvido sistemas LiDAR para culturas arbóreas. Porém, normalmente tais sistemas são empregados em plantas individuais ou em pequenas áreas. Dessa forma, diversos aspectos da aquisição e processamento de dados ainda devem ser desenvolvidos para viabilizar a aplicação em larga escala. O primeiro estudo deste documento (Capítulo 3) focou no desenvolvimento de um sistema LiDAR (Mobile Terrestrial Laser Scanner - MTLS) e nova metodologia de processamento de dados para obtenção de informações acerca da geometria das copas em pomares comerciais de laranja. Um sensor a laser e um receptor RTK-GNSS (Real Time Kinematics - Global Navigation Satellite System) foram instalados em um veículo para leituras em campo. O processamento de dados foi baseado na geração de uma nuvem de pontos, seguida dos passos de filtragem, classificação e reconstrução da superfície das copas. Um pomar comercial de laranja de 25 ha foi utilizado para a validação. O sistema de aquisição e processamento de dados foi capaz de produzir uma nuvem de pontos representativa do pomar, fornecendo informação sobre geometria das plantas em alta resolução. A escolha sobre o tipo de classificação da nuvem de pontos (em plantas individuais ou em seções transversais das fileiras) e sobre o algoritmo de reconstrução de superfície, foi discutida nesse estudo. O segundo estudo (Capítulo 4) buscou caracterizar a variabilidade espacial da geometria de copa em pomares comerciais. Entender tal variabilidade permite avaliar se a aplicação em taxas variáveis de insumos baseada em sensores LiDAR (aplicar quantias de insumos proporcionais ao tamanho das copas) é uma estratégia adequada para otimizar o uso de insumos. Cinco pomares comerciais foram avaliados com o sistema MTLS. De acordo com a variabilidade encontrada, a economia de insumos pelo uso da taxa variável foi estimada em aproximadamente 40%. O segundo objetivo desse estudo foi avaliar a relação entre a geometria de copa e diversos outros parâmetros dos pomares. Os mapas de volume e altura de copa foram comparados aos mapas de produtividade, elevação, condutividade elétrica do solo, matéria orgânica e textura do solo. As correlações entre geometria de copa e produtividade ou fatores de solo variaram de fraca até forte, dependendo do pomar. Quando os pomares foram divididos entre três classes com diferentes tamanhos de copas, o desempenho em produtividade e as características do solo foram distintas entre as três zonas, indicando que parâmetros de geometria de copa são variáveis úteis para a delimitação de unidades de gestão diferenciada em um pomar. Os resultados gerais desta pesquisa mostraram o potencial de sistemas MTLS para pomares de laranja, indicando como a geometria de copa pode ser utilizada na gestão localizada de pomares de laranja.

Sensors based on LiDAR (Light Detection and Ranging) technology have the potential to provide accurate 3D models of the trees retrieving information such as canopy volume and height. This information can be used for diagnostics and prescriptions of fertilizers and plant protection products on a site-specific basis. This research aimed to investigate the use of LiDAR sensors in orange crops. Orange is one of the most important tree crop in Brazil. So far, research have developed and tested LiDAR based systems for several tree crops. However, usually individual trees or small field plots have been used. Therefore, several aspects related to data acquisition and processing must still be developed for large-scale application. The first study reported in this document (Chapter 3) aimed to develop and test a mobile terrestrial laser scanner (MTLS) and new data processing methods in order to obtain 3D models of large commercial orange groves and spatial information about canopy geometry. A 2D laser sensor and a RTK-GNSS receiver (Real Time Kinematics - Global Navigation Satellite System) were mounted on a vehicle. The data processing was based on generating a georeferenced point cloud, followed by the filtering, classification and surface reconstruction steps. A 25 ha commercial orange grove was used for field validation. The developed data acquisition and processing system was able to produce a reliable point cloud of the grove, providing high resolution canopy volume and height information. The choice of the type of point cloud classification (by individual trees or by transversal sections of the row) and the surface reconstruction algorithm is discussed in this study. The second study (Chapter 4) aimed to characterize the spatial variability of canopy geometry in commercial orange groves. Understanding such variability allows sensor-based variable rate application of inputs (i.e, applying proportional rates of inputs based on the variability of canopy size) to be considered as a suitable strategy to optimize the use of fertilizers and plant protection products. Five commercial orange groves were scanned with the developed MTLS system. According to the variability of canopy volume found in those groves, the input savings as a result of implementing sensor-based variable rate technologies were estimated in about 40%. The second goal of this study was to understand the relationship between canopy geometry and several other relevant attributes of the groves. The canopy volume and height maps of three groves were analyzed against historical yield maps, elevation, soil electrical conductivity, organic matter and clay content maps. The correlations found between canopy geometry and yield or soil maps varied from poor to strong correlations, depending on the grove. When classifying the groves into three classes according to canopy size, the yield performance and soil features inside each class was found to be significantly different, indicating that canopy geometry is a suitable variable to guide management zones delineation in one grove. Overall results from this research show the potential of MTLS systems and subsequent data analysis in orange crops indicating how canopy geometry information can be used in site-specific management practices. / Sensores baseados em tecnologia LiDAR (Light Detection and Ranging) têm o potencial de fornecer modelos tridimensionais de árvores, provendo informações como o volume e altura de copa. Essas informações podem ser utilizadas em diagnósticos e recomendações localizadas de fertilizantes e defensivos agrícolas. Este estudo teve como objetivo investigar o uso de sensores LiDAR na cultura da laranja, uma das principais culturas de porte arbóreo no Brasil. Diversas pesquisas têm desenvolvido sistemas LiDAR para culturas arbóreas. Porém, normalmente tais sistemas são empregados em plantas individuais ou em pequenas áreas. Dessa forma, diversos aspectos da aquisição e processamento de dados ainda devem ser desenvolvidos para viabilizar a aplicação em larga escala. O primeiro estudo deste documento (Capítulo 3) focou no desenvolvimento de um sistema LiDAR (Mobile Terrestrial Laser Scanner - MTLS) e nova metodologia de processamento de dados para obtenção de informações acerca da geometria das copas em pomares comerciais de laranja. Um sensor a laser e um receptor RTK-GNSS (Real Time Kinematics - Global Navigation Satellite System) foram instalados em um veículo para leituras em campo. O processamento de dados foi baseado na geração de uma nuvem de pontos, seguida dos passos de filtragem, classificação e reconstrução da superfície das copas. Um pomar comercial de laranja de 25 ha foi utilizado para a validação. O sistema de aquisição e processamento de dados foi capaz de produzir uma nuvem de pontos representativa do pomar, fornecendo informação sobre geometria das plantas em alta resolução. A escolha sobre o tipo de classificação da nuvem de pontos (em plantas individuais ou em seções transversais das fileiras) e sobre o algoritmo de reconstrução de superfície, foi discutida nesse estudo. O segundo estudo (Capítulo 4) buscou caracterizar a variabilidade espacial da geometria de copa em pomares comerciais. Entender tal variabilidade permite avaliar se a aplicação em taxas variáveis de insumos baseada em sensores LiDAR (aplicar quantias de insumos proporcionais ao tamanho das copas) é uma estratégia adequada para otimizar o uso de insumos. Cinco pomares comerciais foram avaliados com o sistema MTLS. De acordo com a variabilidade encontrada, a economia de insumos pelo uso da taxa variável foi estimada em aproximadamente 40%. O segundo objetivo desse estudo foi avaliar a relação entre a geometria de copa e diversos outros parâmetros dos pomares. Os mapas de volume e altura de copa foram comparados aos mapas de produtividade, elevação, condutividade elétrica do solo, matéria orgânica e textura do solo. As correlações entre geometria de copa e produtividade ou fatores de solo variaram de fraca até forte, dependendo do pomar. Quando os pomares foram divididos entre três classes com diferentes tamanhos de copas, o desempenho em produtividade e as características do solo foram distintas entre as três zonas, indicando que parâmetros de geometria de copa são variáveis úteis para a delimitação de unidades de gestão diferenciada em um pomar. Os resultados gerais desta pesquisa mostraram o potencial de sistemas MTLS para pomares de laranja, indicando como a geometria de copa pode ser utilizada na gestão localizada de pomares de laranja.

Made available in DSpace on 2014-06-11T19:31:33Z (GMT). No. of bitstreams: 0 Previous issue date: 2006-12-14Bitstream added on 2014-06-13T19:20:42Z : No. of bitstreams: 1 pereira_fjs_dr_botfca.pdf: 1185742 bytes, checksum: 29392c93db0c4947a9ef1eda0e2f548e (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Universidade Estadual Paulista (UNESP) / A tecnologia de aplicação de produtos fitossanitários não tem sido realizada de maneira adequada por grande parte dos agricultores, causando grandes desperdícios do produto e contaminação ambiental. O tamanho único de gotas durante a pulverização ao longo do dia, independentemente das condições climáticas, é um fator que contribui para a baixa eficiência, causando desperdícios por deriva e ineficiência na cobertura do alvo. Para contornar o problema, uma nova possibilidade seria desenvolver metodologias para ajustar o tamanho de gotas às condições climáticas no momento da pulverização. Com este intuito, o presente trabalho teve por objetivo desenvolver um protótipo de pulverizador com sistema de comutação de pontas na barra de pulverização e avaliar este sistema para ajuste da classe do tamanho de gotas às condições climáticas, além de utilizá-lo para aplicações em taxas variáveis (VRT - Variable Rate Technology), através da comutação de pontas de diferentes vazões. Para tanto, foram desenvolvidos algoritmos específicos, denominados algoritmo climático e algoritmo VRT. Foram ensaiados dois sensores de fluxo (fluxômetros de turbina e eletromagnético) para uso no controle da vazão e, também, os sistemas com sensores climáticos (SSCs) de leituras de temperatura e umidade relativa do ar, utilizados no sistema de ajuste às condições climáticas. O tempo de comutação das pontas para os dois algoritmos foi determinado e ajustado para que não houvesse falha nem sobreposição durante a comutação. Os tempos de resposta (TR) dos dois sistemas de aplicação foram obtidos com o auxílio de recursos de videografia, através do cálculo da diferença de tempo entre o instante do comando para 2 comutação das pontas e o instante em que ocorria a última fase da operação... / The application technology of pesticides has not been carried through in adequate way by great part of farmers, causing great losses of pesticides and contamination of water sources and adjacent areas. Spraying target with the same drops sizes during all day long, independent of the climatic conditions, is a factor that contributes for this low efficiency, causing wastefulness by drift and inefficiency in spray coverage of the intended target. To skirt the problem, a new possibility is to develop methodologies that can adjust the sizes of drops to climatic conditions while spraying. With this intent, the objective of this work was to develop a spraying prototype with a nozzle commutation system in the spraying bar and, evaluate this system for adjusting the drops sizes to climatic conditions, beyond using it for application in variables rates (VRT - Variable Rate Technology), through the commutation of nozzles of different outflows, based in recommendation map. For this it was developed specifics algorithms, denominated climatic algorithm and VRT algorithm. Sensors were evaluated in order to know its characteristics of performance. It was carried out tests of two sensors of flow (electromagnetic and turbine) to be used in outflow control. It was also assayed systems with climatic sensors (SSCs) of reading of temperature and relative humidity of the air used in a system that adjusted the spray to climatic conditions. The nozzles commutation time was determined for both algorithms and adjusted so that it did not have imperfections nor overlapping during the commutation. The times responses (TR), of the two systems, 4 was obtained with video resources, by calculating the time difference between the instant of the command for nozzles commutation and the instant that happened the last phase... (Complete abstract, click electronic access below)

Orientador: Ulisses Rocha Antuniassi / Banca: Carlos Gilberto Raetano / Banca: Kléber Pereira Lanças / Banca: Antonio Gabriel Filho / Banca: Marco Antonio Gandolfo / Resumo: A tecnologia de aplicação de produtos fitossanitários não tem sido realizada de maneira adequada por grande parte dos agricultores, causando grandes desperdícios do produto e contaminação ambiental. O tamanho único de gotas durante a pulverização ao longo do dia, independentemente das condições climáticas, é um fator que contribui para a baixa eficiência, causando desperdícios por deriva e ineficiência na cobertura do alvo. Para contornar o problema, uma nova possibilidade seria desenvolver metodologias para ajustar o tamanho de gotas às condições climáticas no momento da pulverização. Com este intuito, o presente trabalho teve por objetivo desenvolver um protótipo de pulverizador com sistema de comutação de pontas na barra de pulverização e avaliar este sistema para ajuste da classe do tamanho de gotas às condições climáticas, além de utilizá-lo para aplicações em taxas variáveis (VRT - Variable Rate Technology), através da comutação de pontas de diferentes vazões. Para tanto, foram desenvolvidos algoritmos específicos, denominados algoritmo climático e algoritmo VRT. Foram ensaiados dois sensores de fluxo (fluxômetros de turbina e eletromagnético) para uso no controle da vazão e, também, os sistemas com sensores climáticos (SSCs) de leituras de temperatura e umidade relativa do ar, utilizados no sistema de ajuste às condições climáticas. O tempo de comutação das pontas para os dois algoritmos foi determinado e ajustado para que não houvesse falha nem sobreposição durante a comutação. Os tempos de resposta (TR) dos dois sistemas de aplicação foram obtidos com o auxílio de recursos de videografia, através do cálculo da diferença de tempo entre o instante do comando para 2 comutação das pontas e o instante em que ocorria a última fase da operação... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The application technology of pesticides has not been carried through in adequate way by great part of farmers, causing great losses of pesticides and contamination of water sources and adjacent areas. Spraying target with the same drops sizes during all day long, independent of the climatic conditions, is a factor that contributes for this low efficiency, causing wastefulness by drift and inefficiency in spray coverage of the intended target. To skirt the problem, a new possibility is to develop methodologies that can adjust the sizes of drops to climatic conditions while spraying. With this intent, the objective of this work was to develop a spraying prototype with a nozzle commutation system in the spraying bar and, evaluate this system for adjusting the drops sizes to climatic conditions, beyond using it for application in variables rates (VRT - Variable Rate Technology), through the commutation of nozzles of different outflows, based in recommendation map. For this it was developed specifics algorithms, denominated climatic algorithm and VRT algorithm. Sensors were evaluated in order to know its characteristics of performance. It was carried out tests of two sensors of flow (electromagnetic and turbine) to be used in outflow control. It was also assayed systems with climatic sensors (SSCs) of reading of temperature and relative humidity of the air used in a system that adjusted the spray to climatic conditions. The nozzles commutation time was determined for both algorithms and adjusted so that it did not have imperfections nor overlapping during the commutation. The times responses (TR), of the two systems, 4 was obtained with video resources, by calculating the time difference between the instant of the command for nozzles commutation and the instant that happened the last phase... (Complete abstract, click electronic access below) / Doutor