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11	Soil landscape characterization of crop stubble covered fields using Ikonos high resolution panchromatic images Pelcat, Yann S. 28 March 2006 (has links) Soil landscape characterization into landform elements for precision agriculture has become an important issue. As soil properties and crop yields change over the landscape, delineating landform elements as a basis for site-specific application of crop inputs has become a reality. Two different methods of delineating landform elements from agricultural fields were tested and compared. The first method delineated landform elements from digital elevation maps with the use of the LandMapR(tm) software, the second method delineated classes from IKONOS high resolution panchromatic images using an unsupervised classification algorithm. The LandMapR(tm) model delineated landform elements from true elevation data collected in the field and was considered the reference dataset to which the image classification maps were compared to. The IKONOS imagery was processed using a combination of one filtering algorithm and one unsupervised classification method prior to being compared to the classified DEM. A total of 20 filtering algorithms and two unsupervised methods were used for each of the five study sites. The study sites consisted of four agricultural fields covered with crop stubble and one field in summer fallow. Image classification accuracy assessment was reported as overall, producer’s and user’s accuracy as well as Kappa statistic. Results showed that filtering algorithms and classification methods had no effects on image classification accuracies. Highest classification accuracy of image map to landform element map comparison achieved for all study sites was 17.9 %. Classification accuracy was affected by the heterogeneity of the ground surface cover found in each field. However, the classification accuracy of the fallow field was not superior to the stubble fields. landform elements IKONOS imagery Remote sensing and soils landmapR software soil landscape DEM morphometrics topography precision agriculture precision farming management zones topography mapping GPS / GIS Image analysis
12	Soil landscape characterization of crop stubble covered fields using Ikonos high resolution panchromatic images Pelcat, Yann S. 28 March 2006 (has links) Soil landscape characterization into landform elements for precision agriculture has become an important issue. As soil properties and crop yields change over the landscape, delineating landform elements as a basis for site-specific application of crop inputs has become a reality. Two different methods of delineating landform elements from agricultural fields were tested and compared. The first method delineated landform elements from digital elevation maps with the use of the LandMapR(tm) software, the second method delineated classes from IKONOS high resolution panchromatic images using an unsupervised classification algorithm. The LandMapR(tm) model delineated landform elements from true elevation data collected in the field and was considered the reference dataset to which the image classification maps were compared to. The IKONOS imagery was processed using a combination of one filtering algorithm and one unsupervised classification method prior to being compared to the classified DEM. A total of 20 filtering algorithms and two unsupervised methods were used for each of the five study sites. The study sites consisted of four agricultural fields covered with crop stubble and one field in summer fallow. Image classification accuracy assessment was reported as overall, producer’s and user’s accuracy as well as Kappa statistic. Results showed that filtering algorithms and classification methods had no effects on image classification accuracies. Highest classification accuracy of image map to landform element map comparison achieved for all study sites was 17.9 %. Classification accuracy was affected by the heterogeneity of the ground surface cover found in each field. However, the classification accuracy of the fallow field was not superior to the stubble fields. landform elements IKONOS imagery Remote sensing and soils landmapR software soil landscape DEM morphometrics topography precision agriculture precision farming management zones topography mapping GPS / GIS Image analysis
13	Uso da Krigagem Indicativa na seleção de áreas propícias ao cultivo de café em consorciação ou rotação com outras culturas / Use of Kriging Indicative in selecting areas for the cultivation of coffee in intercropping or rotation with other crops Almeida, Maria de Fátima Ferreira 28 February 2013 (has links) Made available in DSpace on 2015-03-26T13:32:19Z (GMT). No. of bitstreams: 1 texto completo.pdf: 1676755 bytes, checksum: 2df7ed933bf4edc87e49ea0558d83114 (MD5) Previous issue date: 2013-02-28 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Geoestatistics stands out, mainly because it is an an interdisciplinary science that allows an exchange of information between geologists, petroleum engineers, mathematicians, statisticians and other professional groups thus enabling better interpretation of geological and environmental reality. Among the highlights Kriging techniques to Ordinary Kriging and Kriging Indicative. Where the first is a linear kriging predictor of timely considering the average unknown and incorporates in its formulation the procedure a weighted mobile, but what sets it apart is the fact that the weights are obtained taking into account the continuity represented by the semivariograma. The Indicative Kriging predictor is one that uses the technique of ordinary kriging or simple kriging of the data processed through a nonlinear function composed of binary 0 and 1. One of the great advantages of Kriging Indicative is the fact of being a nonparametric estimator that allows transform qualitative variables (presence or absence) or quantitative variables (according to a cutoff point of interest) and to estimate ranges of probability of occurrence of the variable. In agriculture, its use allows planning of soil correction of localized and identify management zones for rotation or intercropping. This paper aims to present a theoretical and practical study of the advantages and disadvantages of using the Kriging Indicative planning soil remediation technique for implantation of intercropping with banana cultivation of coffee, using data from soil chemical properties through samples collected at a farm cultivated with coffee in the city of Araponga - Zona da Mata Mineira. / A Geoestatística se destaca, principalmente por ser uma ciência interdisciplinar que permite uma troca de informações entre geólogos, engenheiros de petróleo, matemáticos, estatísticos e demais categorias profissionais possibilitando assim uma melhor interpretação da realidade geológica e ambiental. Dentre as técnicas de Krigagem destaca-se a Krigagem Ordinária e a Krigagem Indicativa. Em que a primeira é um preditor de Krigagem linear pontual que considera a média desconhecida e incorpora em sua formulação o procedimento de uma média ponderada móvel, porém o que a diferencia é o fato de que os pesos são obtidos levando em consideração a continuidade representada pelo semivariograma. A Krigagem Indicativa é um preditor que utiliza-se da técnica de Krigagem Ordinária ou de Krigagem Simples dos dados transformados por meio de uma função não linear binária composta por 0 e 1. Uma das grandes vantagens da Krigagem Indicativa reside no fato de ser um estimador não paramétrico que permite transformar variáveis qualitativas (presença ou ausência) ou variáveis quantitativas (de acordo com um ponto de corte de interesse) e estimar probabilidade de ocorrência da variável. Na agricultura, o seu uso permite fazer planejamento de correção do solo de forma localizada e identificar zonas de manejo para rotação ou consorciação de culturas. Este trabalho tem por objetivo apresentar um estudo teóricoaplicado das vantagens e desvantagens no uso da Krigagem Indicativa para o planejamento de correção do solo para implantação da técnica de consorciação de cultivo de bananeira com o cultivo de café, utilizando dados de propriedades químicas do solo por meio de amostras coletadas em uma fazenda cultivada com café no Município de Araponga- Zona da Mata Mineira. Krigagem indicativa Consorciação de culturas Propriedades químicas do solo Seleção de zonas de manejo Cultivo de café Kriging indicative Intercropping Soil chemical properties Selection of management zones Coffee cultivation CNPQ::CIENCIAS AGRARIAS
14	MANEJO POR AMBIENTE: ATRIBUTOS DE SOLO E DESEMPENHO DE CULTIVARES DE SOJA / ENVIRONMENTAL MANAGEMENT: SOIL ATTRIBUTES AND PERFORMANCE OF SOYBEAN CULTIVARS Corassa, Geomar Mateus 16 February 2015 (has links) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The crop productivity mapping is an important precision farming tool enabling more efficient spatial management of agricultural areas. In this sense, the objective of this work was to identify and analyze zones with different grain yield potential (Article I), check the association of chemical and physical properties of the soil with the yield zones (Article II), and evaluate the agronomic performance of six soybean cultivars in zones with different grain yield potential. For the definition of the yield zones were used three harvest maps of different cultures in two experimental areas. The maps were filtered and the defined zones and grouped from the overlap of crops (Article I). The search for chemical and physical atributes of the soil associated with grain yield was performed by systematic soil collection, according to grain yield zones (high, medium and low) (Article II), and analyzed 80 chemical variables and 33 physical variables by using descriptive statistics and ranked by principal component analysis (PCA). The agronomic performance of soybean cultivars in different grain yield zones (Article III) was evaluate in two agricultural areas, being allocated experiments in the random block design in factorial 3x6, with three grain yield zones (high, medium and low) and six soybean cultivars (BMX Ativa RR, Fundacep 65 RR, FPS Urano RR, FPS Júpiter RR, Nidera 5909 RG and BMX Força RR), with three replications. The results showed that the use of a historical series of harvest maps is an efficient tool to characterize sites with different grain yield potential, in addition to serving as a base for improving the spatial management of agricultural areas. The systematic soil sampling was able to reveal explanatory variables for grain yield, and the order for intervention in chemical attributes in the área is: Liming, phosphate fertilization and potassium fertilization. The presence of attributes of difficult management in the short time (organic matter and clay) associated with grain yield potential suggests the crop management in the management zones. The yield zones influenced the grain yield of soybean cultivars, and the cultivar BMX Força RR presented its highest grain yield in the ZB, whereas NA 5909 RG was more productive in the ZA and ZM. The cultivar BMX Ativa RR was on average more productive and more stable. The results indicate that the positioning of soybean cultivars in accordance with management zones is a important strategy for the precision agriculture and characterized as a new concept of the ―multi-cultivars‖ sowing. / O mapeamento da produtividade das culturas é uma importante ferramenta da agricultura de precisão permitindo o manejo espacial e temporal mais eficiente das áreas agrícolas. Neste sentido, o trabalho teve por objetivo identificar e analisar zonas com diferentes potenciais de rendimento de grãos (Artigo I), verificar a associação de atributos químicos e físicos do solo com as zonas de rendimento (Artigo II) e, avaliar o desempenho agronômico de seis cultivares de soja em zonas de alto (ZA), médio (ZM) e baixo (ZB) potencial de rendimento de grãos. Para a definição das zonas de rendimento foram utilizados três mapas de colheita de diferentes culturas em duas áreas experimentais. Os mapas foram filtrados e as zonas definidas e agrupadas a partir da sobreposição das safras (Artigo I). A busca por atributos químicos e físicos do solo associados ao rendimento de grãos foi procedida por meio da coleta sistemática do solo, de acordo com as zonas de rendimento (alto, médio e baixo) (Artigo II), sendo analisadas 80 variáveis químicas e 33 variáveis físicas por meio da estatística descritiva e ranqueadas por meio da análise de componentes principais (ACP). O desempenho agronômico de cultivares de soja nas diferentes zonas de rendimento (Artigo III) foi avaliado em duas áreas agrícolas, sendo os experimentos alocados em delineamento de bloco aos acaso em esquema fatorial 3x6, com três zonas de rendimento (alto, médio e baixo) e seis cultivares de soja (BMX Ativa RR, Fundacep 65 RR, FPS Urano RR, FPS Júpiter RR, NA 5909 RG e BMX Força RR), com três repetições. Os resultados comprovaram que o uso de uma série histórica de mapas de colheita é uma ferramenta eficiente para caracterizar locais com diferentes potenciais de rendimento, além de servir como base para a melhoria da gestão espacial das áreas agrícolas. A amostragem sistemática do solo foi capaz de revelar variáveis explicativas para o rendimento de grãos, sendo a ordem para intervenção em atributos químicos na área: calagem, fertilização fosfatada e fertilização potássica. A presença de atributos de difícil manejo em curto prazo (matéria orgânica e argila) associados ao rendimento de grãos sugere o manejo das culturas por zona de manejo. As zonas influenciaram o rendimento de grãos das cultivares de soja, sendo que a cultivar BMX Força RR apresentou seu maior rendimento na ZB, enquanto que NA 5909 RG, foi mais produtiva em ZA e ZM. A cultivar BMX Ativa RR foi em média a mais produtiva e mais estável. Os resultados indicam que o posicionamento de cultivares de soja de acordo com zonas de manejo é uma importante estratégia para a agricultura de precisão e se caracteriza como um novo conceito de semeadura ―multi-cultivares‖ Agricultura de precisão Mapas de colheita Zonas de manejo Atributos de solo Glycine max (L.) Merrill Precision agriculture Yield maps Management zones Soil atributes Glycine max (L.) Merrill CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
15	Condutividade elétrica aparente do solo como ferramenta para agricultura de precisão em uma área sob Cerrado / Condutividade elétrica aparente do solo como ferramenta para agricultura de precisão em uma área sob Cerrado / Apparent soil electrical conductivity as a tool for precision agriculture in an area under Cerrado / Apparent soil electrical conductivity as a tool for precision agriculture in an area under Cerrado Costa, Marcelo Marques 20 July 2011 (has links) Made available in DSpace on 2015-03-26T13:23:38Z (GMT). No. of bitstreams: 1 texto completo.pdf: 1452064 bytes, checksum: 3c07661ce61a2de096f75bbba839cfd4 (MD5) Previous issue date: 2011-07-20 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / Precision agriculture seeks the management of fields in order to maximize profit and reduce environmental impacts. For this, one must consider the spatial variability of the attributes that define the yield of agricultural crops. The management considering the variability of soil properties provides improvements in the management of inputs, however, a spatial database for this purpose requires a large number of soil samples. To map the soil attributes using direct samples generally is not the option most cost effective. Indirect samplings are preferable, and the apparent soil electrical conductivity (ECa) is a technique with high acceptance in precision agriculture. The objective of this work is to advance the knowledge about this technique by testing it in a Cerrado condition. Therefore, the sampling conditions, the spatial and temporal variability, and the usefulness these information for precision agriculture were evaluated. The results regarding the sampling condition show that when the soil moisture is higher, the ECa correlated most closely with soil attributes and correlated less with soil moisture and was considered to be the best condition for sampling. The spatial variability of ECa generated four classes when used the fuzzy c-means classifier. However, a method of analysis of soil samples within classes combined them in just two, which were distinct for the attributes most correlated with the ECa and the obtained semivariogram showed low discontinuity at the origin. These attributes were the potential of hydrogen (pH), base saturation (V), potential acidity (H + Al), iron (Fe) and full cation exchange capacity (T). The temporal variability of ECa was analyzed by using the principal component technique. The component that best described the temporal variability of ECw explained 18% of the total variability of the data and presented spatial dependence. This component was correlated with altitude, T and electrical conductivity of saturation extract (CEes). In this study the altitude was considered the attribute that most influenced the temporal variability of the ECa. In this study case, the ECa represented a good information for analysis of spatial variability of physical and chemical attributes of soil. / A agricultura de precisão busca o manejo dos campos de forma a maximizar o lucro e reduzir os impactos ambientais. Para tanto, deve-se considerar a variabilidade espacial dos atributos que definem a produtividade das culturas agrícolas. O manejo considerando a variabilidade de propriedades do solo proporciona melhorias no gerenciamento de insumos, entretanto, um banco de dados espacial para essa finalidade necessita de um grande número de amostras de solo. Por esse motivo o mapeamento de atributos do solo por meio de amostras diretas não é a opção com melhor relação custo/benefício. Amostragens indiretas são preferíveis e a condutividade elétrica aparente do solo (CEa) é uma técnica com elevada aceitação em agricultura de precisão. Esse trabalho tem o objetivo de avançar nos conhecimentos a respeito dessa técnica, testando-a em uma condição de Cerrado. Para tanto, foi avaliada as condições de amostragem, a variabilidade espacial, temporal e a utilidade dessas informações para a agricultura de precisão. Os resultados revelam que na condição de amostragem com teor de água no solo mais elevada, a CEa mais se correlaciona com atributos do solo e menos se correlaciona com o teor de água no solo, sendo considerada a melhor condição de amostragem. A variabilidade espacial da CEa gerou quatro classes, quando utilizando o classificador Fuzzy c-means. Entretanto, um método de análise de amostras de solo no interior das classes combinou-as em apenas duas, que foram distintas para os atributos mais correlacionados com a CEa e que apresentaram forte dependência espacial. Esses atributos foram, potencial hidrogeniônico (pH), saturação por bases (V), acidez potencial (H+Al), ferro (Fe) e capacidade total de troca catiônica (T). A variabilidade temporal da CEa foi avaliada por meio da análise de componentes principais. A componente que melhor descreveu a variabilidade temporal da CEa explicou 18 % da variabilidade total dos dados e apresentou dependência espacial. Essa componente correlacionou com a altitude, T e a condutividade elétrica do extrato de saturação (CEes). Nesse estudo, a altitude foi considerada o atributo que mais influenciou a variabilidade temporal da CEa. Para as condições desse trabalho a CEa representou uma boa informação para análise indireta de importantes atributos do solo. Teor de água no solo Zonas de manejo Variabilidade espacial e temporal Water content in soil Management zones Spatial and temporal variability
16	Utilização de métodos de interpolação e agrupamento para definição de unidades de manejo em agricultura de precisão / Interpolator method and clustering to definition of management zones on precision agriculture Schenatto, Kelyn 04 February 2014 (has links) Made available in DSpace on 2017-07-10T19:23:44Z (GMT). No. of bitstreams: 1 Kelyn Schenatto.pdf: 4212903 bytes, checksum: 0ba04350cc25aff5e6acb249938e5375 (MD5) Previous issue date: 2014-02-04 / Despite the benefits offered by the technology of precision agriculture (PA), the necessity of dense sampling grids and use of sophisticated equipment for the soil and plant handling make it financially unfeasible in many cases, especially for small producers. With the aimof making viable the PA, the definition of management zones (MZ) consists in dividing the plotin subregions that have similar physicochemical features, where it is possible to work in the conventional manner (without site-specific input application), differing them from the other sub-regions of the field. Thus we use concepts from PA, but adapting some procedures to the reality of the producer, not requiring the replacement of machinery traditionally used.Therefore, yield is usually correlated with physical and chemical properties through statistical and geostatistical methods, and attributes are selected to generate thematic maps, which are then used to define the MZ. In the generation of thematic maps step, are commonly used traditional interpolation methods (Inverse Distance - ID , inverse of the square distance - ISD, and kriging - KRI), and it is important to assess if the quality of thematic maps generated influences in the MZ drafting process and can not justify the interpolation data using robust methods such as KRI. Thus, the present study aimed to evaluate three interpolation methods (ID , ISD and KRI ) for generation of thematic maps used in the generation of MZ by clustering methods K-Means and Fuzzy C-Meas, in two experimental areas (9.9 ha and 15.5 ha), and been used data from four seasons (three crops of soybeans and one of corn). The KRI interpolation and ID showed similar UM. The agreement between the maps decreased when an increase in the number of classes, but with greater intensity with the Fuzzy C-Means method. Clustering algorithms K-Means and Fuzzy C-Means performed similar division on two UM. The best interpolation method was KRI following the ID, what justifies the choice of a more robust interpolation (KRI) to generate UM / Apesar dos benefícios proporcionados pela tecnologia de agricultura de precisão (AP), a necessidade de grades amostrais densas e uso de equipamentos sofisticados para o manejo do solo e da planta tornam o seu cultivo em muitos casos inviável financeiramente, principalmente para pequenos produtores. Com a finalidade de viabilizar a AP, a definição de unidades de manejo (UM) consiste em dividir o talhão em sub-regiões que possuam características físico-químicas semelhantes, onde se pode trabalhar de forma convencional (sem aplicação localizada de insumos), diferenciando-se das outras sub-regiões do talhão. Dessa forma, utilizam-se conceitos de AP, mas adaptam-se alguns procedimentos para a realidade do produtor, não havendo necessidade da substituição de máquinas tradicionalmente utilizadas. Para isso, são geralmente correlacionados atributos físicos e químicos com a produtividade das culturas e, por meio de métodos estatísticos e geoestatísticos, selecionam-se atributos que darão origem a mapas temáticos posteriormente utilizados para definição das UM. Na etapa de geração dos mapas temáticos, são normalmente utilizados métodos tradicionais de interpolação (inverso da distância ID, inverso da distância ao quadrado IDQ e krigagem KRI) e é importante avaliar se a qualidade dos mapas temáticos gerados influencia no processo de definição das UM, podendo desta forma não se justificar a interpolação de dados a partir do uso de métodos robustos como a KRI. O presente trabalho teve como objetivo a avaliação de três métodos de interpolação (ID, IQD e KRI) para definição dos mapas temáticos utilizados na confecção de UM pelos métodos de agrupamento K-Means e Fuzzy C-Means, em duas áreas experimentais (de 9,9 ha e 15,5 ha), sendo utilizados dados de quatro safras (três safras de soja e uma de milho). Os interpoladores ID e KRI apresentaram UM similares. A concordância entre os mapas diminuiu quando houve aumento do número de classes, mas teve maior intensidade com o método Fuzzy C-Means. Os algoritmos de agrupamento K-Means e Fuzzy C-Means se apresentaram similares na divisão em duas UM. O melhor método de interpolação foi a KRI, seguida do ID, o que justifica a escolha do interpolador mais robusto (KRI) na geração de UM krigagem zonas de manejo K-Means Fuzzy C-Means krigagem management zones K-Means Fuzzy C-Means
17	DELINEAMENTO DE ZONAS POTENCIAIS PARA MANEJO DIFERENCIADO EM NÍVEL DE TALHÃO APARTIR DE DADOS DE COLHEITA E DE IMAGENS DE SATÉLITE / DESIGN AREAS FOR POTENTIAL MANAGEMENT IN DIFFERENTIAL FIELD LEVEL HARVEST DATA FROM AND SATELLITE IMAGES Veiverberg, Kelly Taline 26 April 2016 (has links) Precision agriculture has been used to assist farmers to choose the best management strategies, by identifying variability present in the area and from that, to determine the limiting factors and propose different management alternatives, according to the needs of each zone. It is important to create instruments that respond to one of the main issues, common to all of those who have ambition to the adoption and implementation of production modernization techniques: the technical and economic viability of modern production agriculture. The aim of this study was to relate stability maps for yield productivity and stability maps by Normalized Difference Vegetation Index (NDVI) for determination of management zones. The study was based on an analysis of five years of crop yield data and five satellite images Landsat 5 and Landsat 8 for Vegetation Index (NDVI) data for 2007 (wheat), 2008 (soybean), 2009 (soybean), 2013 (wheat) and 2014 (soybean). With processed data, stability maps for yield productivity and stability maps by Normalized Difference Vegetation Index (NDVI) were generated, following data parameters and coefficient of variation. Both maps were compared and validated by the Kappa index. As a result, we obtained a weak Kappa index relationship (0.2623), but 57.48% of the area could be classified correctly, when comparing the correlation maps. We concluded that crossing data of areas classified by productivity yield and NDVI is valid and that the zoning method for NDVI method is a way to determines areas, but with greater emphasis in areas classified as "Stable High." / A agricultura de precisão surge para auxiliar o produtor na escolha das melhores estratégias de manejo, permitindo identificar a variabilidade presente na área e, a partir disso, averiguar os fatores limitantes e propor alternativas de manejo diferenciado, de acordo com as necessidades de cada zona de manejo. É necessário criar instrumentos que respondam a uma das principais questões, comum a todos aqueles que têm ambição à adoção e aplicação de técnicas de modernização da produção: a viabilização técnica-econômica da produção moderna na agricultura. O objetivo deste trabalho foi relacionar mapas de Estabilidade de Rendimento por produtividade e de Estabilidade de Rendimento por Índice de Vegetação por Diferença Normalizada para determinação de zonas de manejo. O estudo foi baseado na análise de cinco anos de dados de produtividade, em rendimento absoluto, e consecutivamente, cinco imagens de satélite Landsat 5 e Landsat 8, para Índice de Vegetação por Diferença Normalizada (NDVI), dados referentes aos anos de 2007 (cultura do trigo), 2008 (cultura de soja), 2009 (cultura de soja), 2013 (cultura de trigo) e 2014 (cultura de soja). Com esses dados processados foram gerados os mapas de Estabilidade de Rendimento por Produtividade e Estabilidade de Rendimento por NDVI, seguindo parâmetros de dados relativizados e coeficiente de variação. Com os dois mapas de Estabilidade processados, foi feito o comparativo e validação dos dados através do índice Kappa. Como resultado obteve-se um índice Kappa de fraca relação com valor de 0,2623, porém 57,48% da área pode ser classificada corretamente quando comparando zonas geradas por mapas de produtividade com zonas geradas por mapas de NDVI. Concluiu-se, assim, que o cruzamento dos dados das zonas classificadas em Estabilidade de Rendimento por Produtividade e Estabilidade de Rendimento por NDVI é válido e que o método de definição de zonas por Estabilidade de Rendimento por NDVI permite determinar zonas, porém com maior ênfase em zonas classificadas como Estável Alta . Mapas de produtividade Zonas de manejo Yield maps Management zones Normalized difference vegetation index CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
18	Recuperação de uma pastagem degradada e variação de atributos do solo : um estudo geoestatístico e econômico / Barbieri, Rayner Sversut. January 2020 (has links) Orientador: Rafael Montanari / Resumo: Na busca por soluções que otimizem as operações, auxiliem no planejamento e reduzam os custos operacionais no manejo do solo, a geoestatística tem sido aplicada em diversas áreas. Utilizando a geoestatística como ferramenta e forma de planejamento de manejo, o presente trabalho objetivou-se analisar economicamente a recuperação da fertilidade do solo de uma pastagem potencialmente degradada no cerrado brasileiro em dois sistemas de intervenção: convencional (SC) e agricultura de precisão (AP) e gerar informações por meio da análise de variabilidade e estabelecimento da estrutura de dependência espacial, a fim de auxiliar no planejamento de atividades agrícolas em seis cidades na província de El Oro, Equador. O trabalho foi realizado no ano agrícola de 2015/2016 na área experimental de sistemas de produção em bovinocultura de corte pertencente à Faculdade de Engenharia – UNESP, Campus de Ilha Solteira, São Paulo, Brasil e na Universidade Técnica de Machala (UTMACH), Machala, Equador. A recuperação no SC apresentou índice de lucratividade negativa (-1,32%) e no AP positiva (0,26%) proporcionando um preço de custo @-1 de R$ 155,52 e R$ 153,10 para o SC e AP, respectivamente. Comparando-se áreas cultivadas com AP e SC, é provável que se obtenha resultados mais confiáveis e com melhores perspectivas em maiores áreas de cultivo de forma a aumentar a rentabilidade do sistema. Na província de El Oro, o teor de Zinco obteve o maior coeficiente de determinação espacial. O pH se destaco... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: A demand for solutions that optimize operations, support planning and reduce operational costs in soil management, geostatistics has been applied in several areas. Using geostatistics as a tool and management planning method, the present work aimed to economically analyze the soil fertility recovery of a potentially degraded pasture in the Brazilian cerrado in two intervention systems: conventional (CS) and precision agriculture (PA) and generate information through variability analysis and establishment of spatial dependence structure to assist in the planning of agricultural activities in six cities in El Oro province, Ecuador. The work was carried out in the 2015/2016 agricultural year in the experimental area of beef cattle production systems belonging to the Faculty of Engineering - UNESP, Ilha Solteira Campus, São Paulo, Brazil and the Technical University of Machala, Machala, Ecuador. The recovery in CS presented negative profitability index (-1,32%) and positive in PA (0,26%) providing a cost @ -1 price of R$ 155,52 and R$ 153,10 for CS and PA, respectively. Comparing cultivated areas with PA and CS, it is likely that more reliable results and better prospects will be obtained in larger cultivated areas in order to increase the profitability of the system. In El Oro province, the Zinc content obtained the highest coefficient of special determination, but low range, which may be influence by the numbers of pairs in the first Lag. The pH stood out as the major influence... (Complete abstract click electronic access below) / Doutor Custos. Fertilidade do solo. Variabilidade espacial Sustentabilidade. Forragicultura Zonas específicas de manejo Costs Soil fertility Spatial variability Sustainability Forage farming Specific management zones
19	An analysis of precision agriculture in the South African summer grain producing areas / Hendriks J. Hendriks, Joseph January 2011 (has links) Both globally and locally, agriculture faces ever increasing challenges such as high input costs, strict environmental laws, decrease in land for cultivation and an increase in demand due to the growing global population. Profitability and sustainability requires more effective production systems. Precision agriculture is identified as such a system and is built upon a system approach that aims to restructure the total system of agriculture towards low input, high efficiency and sustainable agriculture. The aim of this study was to analyse the state of precision agriculture in the summer grain producing areas of South Africa, specifically the North West and Free State provinces. In order to achieve this, a literature study was conducted. During the literature study the term ‘precision agriculture’ was defined and discussed. The precision agriculture cycle and its components were explained and benefits of precision agriculture were identified. The literature study was concluded with identifying and discussing the most widely used and most beneficial technologies as well as reasons for slow adoption. Findings from the literature study were used to investigate the state of precision agriculture locally. In order to achieve this, a quantitative approach was used and information was collected by means of an empirical study using a questionnaire. Questionnaires were distributed to farmers using selling agents of an agricultural company that is well represented in the targeted areas. The data was then statistically analysed. The survey showed that only 52% of summer grain producing farmers in the North West and Free State provinces of South Africa practises precision agriculture as defined in the v literature study. The study also revealed that the majority of precision agriculture farmers are over the age of 40, have more than 16 years of farming experience, are well educated, cultivate more than 1,000 hectares and uses none or little irrigation. The most commonly used precision agriculture technologies were grid soil sampling and yield monitors. The perception among most of the farmers was that precision technologies are not very affordable, not easily available and that it lacks proper testing with regards to efficiency. The group of summer grain–producing farmers that have correctly implemented precision agriculture as per definition stated that the benefits they derived from precision technologies include reduction in input costs, increased outputs and improved management skills. Too high implementation costs and technologies not providing enough benefits were among the main reasons farmers do not implement precision agriculture. It was concluded that a significant effort and amount of work is needed to increase the use of precision agriculture among summer grain–producing farmers in the targeted areas. A consolidated effort from government, agricultural institutions and agricultural companies will be needed to achieve this goal. Implementing precision agriculture as a system will require education (from primary to tertiary institutions) and improved marketing strategies. Only then will precision technologies be able to help meet the future demands placed on the agriculture sector. / Thesis (M.B.A.)--North-West University, Potchefstroom Campus, 2012. Precision agriculture Precision farming Precision farmers Sustainable farming Crop management Management strategy Information technology Precision agriculture technologies Crop production Production areas Production method Cultivation Variability Management zones Sensors Monitoring Precision agriculture cycle Information Data analysis Decision making Implementation Evaluation Implementation systems Variable rate technology Outputs Inputs Economic advantages Environmental advantages Adoption Farming experience Perceptions Attitudes Precision agriculture group Non-precision agriculture group Total sample Education Marketing strategies Presisielandbou Presisieboerdery Presisieboere Volhoubare boerdery Gewasbestuur Bestuursstrategie Inligtingstegnologie Presisieboerderytegnologie Gewasproduksie Produksieareas Produksiemetode Verbouing Veranderlikheid Bestuursgebiede Sensors Monitering Presisieboerderysiklus Inligting Data-analise Besluitneming Implementering Evaluering Implementeringsisteme Differensiële tegnologie Uitsette Insette Ekonomiese voordele Omgewingsvoordele Boerdery-ondervinding Persepsies Ingesteldheid Presisieboerderygroep Nie-presisieboerderygroep Totale monster Onderwys Bemarkingstrategie
20	An analysis of precision agriculture in the South African summer grain producing areas / Hendriks J. Hendriks, Joseph January 2011 (has links) Both globally and locally, agriculture faces ever increasing challenges such as high input costs, strict environmental laws, decrease in land for cultivation and an increase in demand due to the growing global population. Profitability and sustainability requires more effective production systems. Precision agriculture is identified as such a system and is built upon a system approach that aims to restructure the total system of agriculture towards low input, high efficiency and sustainable agriculture. The aim of this study was to analyse the state of precision agriculture in the summer grain producing areas of South Africa, specifically the North West and Free State provinces. In order to achieve this, a literature study was conducted. During the literature study the term ‘precision agriculture’ was defined and discussed. The precision agriculture cycle and its components were explained and benefits of precision agriculture were identified. The literature study was concluded with identifying and discussing the most widely used and most beneficial technologies as well as reasons for slow adoption. Findings from the literature study were used to investigate the state of precision agriculture locally. In order to achieve this, a quantitative approach was used and information was collected by means of an empirical study using a questionnaire. Questionnaires were distributed to farmers using selling agents of an agricultural company that is well represented in the targeted areas. The data was then statistically analysed. The survey showed that only 52% of summer grain producing farmers in the North West and Free State provinces of South Africa practises precision agriculture as defined in the v literature study. The study also revealed that the majority of precision agriculture farmers are over the age of 40, have more than 16 years of farming experience, are well educated, cultivate more than 1,000 hectares and uses none or little irrigation. The most commonly used precision agriculture technologies were grid soil sampling and yield monitors. The perception among most of the farmers was that precision technologies are not very affordable, not easily available and that it lacks proper testing with regards to efficiency. The group of summer grain–producing farmers that have correctly implemented precision agriculture as per definition stated that the benefits they derived from precision technologies include reduction in input costs, increased outputs and improved management skills. Too high implementation costs and technologies not providing enough benefits were among the main reasons farmers do not implement precision agriculture. It was concluded that a significant effort and amount of work is needed to increase the use of precision agriculture among summer grain–producing farmers in the targeted areas. A consolidated effort from government, agricultural institutions and agricultural companies will be needed to achieve this goal. Implementing precision agriculture as a system will require education (from primary to tertiary institutions) and improved marketing strategies. Only then will precision technologies be able to help meet the future demands placed on the agriculture sector. / Thesis (M.B.A.)--North-West University, Potchefstroom Campus, 2012. Precision agriculture Precision farming Precision farmers Sustainable farming Crop management Management strategy Information technology Precision agriculture technologies Crop production Production areas Production method Cultivation Variability Management zones Sensors Monitoring Precision agriculture cycle Information Data analysis Decision making Implementation Evaluation Implementation systems Variable rate technology Outputs Inputs Economic advantages Environmental advantages Adoption Farming experience Perceptions Attitudes Precision agriculture group Non-precision agriculture group Total sample Education Marketing strategies Presisielandbou Presisieboerdery Presisieboere Volhoubare boerdery Gewasbestuur Bestuursstrategie Inligtingstegnologie Presisieboerderytegnologie Gewasproduksie Produksieareas Produksiemetode Verbouing Veranderlikheid Bestuursgebiede Sensors Monitering Presisieboerderysiklus Inligting Data-analise Besluitneming Implementering Evaluering Implementeringsisteme Differensiële tegnologie Uitsette Insette Ekonomiese voordele Omgewingsvoordele Boerdery-ondervinding Persepsies Ingesteldheid Presisieboerderygroep Nie-presisieboerderygroep Totale monster Onderwys Bemarkingstrategie

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