ABSTRACT Remote sensing (RS) and geographic information systems (GIS) have been used to guide the selection of suitable areas for aquaculture. This systematic review synthesizes the key suitability factors and constraints reported in the literature for establishing inland pond aquaculture. We searched for primary studies on Scopus and Web of Science according to preferred reporting items for systemic reviews and meta-analysis (PRISMA) guidelines. Between 1991 and 2020, 354 articles were published in 104 academic journals. The maximum annual number of publications occurred in 2020, with 22 publications, and there is an increasing trend in studies published over the past 30 years. From 12 selected studies, we identified 48 suitability factors, 11 related to soil suitability, 19 to socioeconomic and infrastructure suitability, and 18 to water quality and availability. The most frequently used suitability factors were road proximity, local market center distance, soil texture, soil slope, and water temperature. We listed 15 constraints that restrict or limit the selection of specific geographic locations for inland aquaculture. Urbanized areas, roads, and forests were the most frequently restricted areas. Geotechnologies provide powerful tools for spatial planning and management of aquaculture. Availability, quality, and access to spatial data are critical for the use of geotechnologies in the process of aquaculture site selection.

ABSTRACT The main objective of this study was to carry out a bibliometric search in the literature on the use of UAVs in the wheat crop. For this purpose, a search of all scientific articles published until 2021 was carried out in the Web of Science database. Subsequently, bibliometric literature analysis techniques were applied using the software VOSviewer, which allowed evaluating the co-authorships between countries and institutions and the co-occurrences of words between studies. The journals and authors that publish the most on this topic were verified. The results indicate a growing trend of publications on UAV applications in the last 7 years, with China, the United States, and the United Kingdom being the main researchers on this topic. However, China stands out with approximately 40% of the publications. This analysis reveals the main current issues and the most influential institutions around the world that have carried out relevant research in scientific publications, showing the journals that include more publications and the collaborative patterns related to the use of UAVs in the wheat crop. Multi-rotor platforms with embedded multispectral cameras are the most used for this purpose. About 27.8% of the publications are from the topic related to the monitoring of productivity/phenotyping. Therefore, this application is in evidence, but further studies on the use of drones in regions with high wheat production, such as South American countries, are needed.

RESUMO O presente trabalho tem como objetivo principal realizar uma pesquisa bibliométrica de literatura sobre o uso de VANTs na cultura de trigo. Para tanto, foi realizada uma pesquisa na base de dados da Web of Science, de todos os artigos científicos publicados até o ano de 2021. Posteriormente foram aplicadas técnicas de análise bibliométrica de literatura através do software VOSviewer, no qual avaliou-se as coautorias entre países e instituições, bem como as coocorrências de palavras entre as obras. Foram verificados os periódicos que mais publicam sobre esta temática e os autores que mais publicam. Os resultados indicam uma tendência crescente de publicações com essa aplicação de VANTs nos últimos 7 anos, e que a China, Estados Unidos da América e Reino Unido são os maiores pesquisadores desse tema, porém a china se destaca com aproximadamente 40% das publicações. Esta análise revela os principais assuntos atuais, e as instituições mais influentes em todo o mundo que realizaram pesquisas relevantes em publicações científicas; este estudo expõe os periódicos que incluem mais publicações e os padrões colaborativos relacionados ao uso de VANTs na cultura do trigo. As plataformas mais utilizadas para essa finalidade são do tipo multirotor, embarcados com câmeras multiespectrais. Cerca de 27,8% das publicações são do eixo temático ligado ao monitoramento da produtividade/fenotipagem. Conclui-se que esta aplicação está em bastante evidência, porém são necessários mais estudos com emprego de drones em regiões com alta produção tritícola como países da América do Sul.

RESUMO No Estado do Paraná, Brasil, não há grandes mudanças nas áreas cultivadas com culturas anuais, principalmente devido a leis ambientais que não permitem expansões para novas áreas. Há grande contribuição das culturas anuais para a demanda doméstica de alimentos e econômica nas exportações. Assim, a área e distribuição das culturas anuais são informações de grande importância. Novas metodologias, como data mining, estão sendo testadas com o objetivo de analisar e melhorar seu potencial de uso para classificação do uso e cobertura da terra. Neste estudo, foram utilizados os classificadores decision tree e random forest com métricas temporais de Normalized Difference Vegetation Index (NDVI) em imagens do Operational Land Imager (OLI)/ Landsat-8. Os resultados foram comparados com os métodos tradicionais (imagens espectrais e classificador Maximum Likelihood Classifier - MLC). Inicialmente, foram mapeadas sete classes (corpos d’água, cana-de-açúcar, área urbana, culturas anuais, floresta, pastagem e áreas de reflorestamento) e posteriormente apenas duas classes foram consideradas (culturas anuais e outras classes). Ao classificar os sete alvos, ambos os métodos tiveram resultados correspondentes, mostrando exatidão global próxima a 84%. As métricas temporais de NDVI mostraram a acurácia do produtor e do usuário para a classe de cultura de 86 e 100%, respectivamente. No entanto, considerando-se apenas duas classes, as métricas temporais do NDVI alcançaram exatidão global próxima a 98% e a acurácia do produtor e do usuário acima de 94%.

ABSTRACT In the state of Paraná, Brazil, there are no major changes in areas cultivated with annual crops, mainly due to environmental laws that do not allow expansions to new areas. There is a great contribution of the annual crops to the domestic demand of food and economic demand in the exports. Thus, the area and distribution of annual crops are information of great importance. New methodologies, such as data mining, are being tested with the objective of analyzing and improving their potential use for classification of land use and land cover. This study used the classifiers decision tree and random forest with Normalized Difference Vegetation Index (NDVI) temporal metrics on images from Operational Land Imager (OLI)/Landsat-8. The results were compared with traditional methods spectral images and Maximum Likelihood Classifier (MLC). At first, seven classes were mapped (water bodies, sugarcane, urban area, annual crops, forest, pasture and reforestation areas); then, only two classes were considered (annual crops and other targets). When classifying the seven targets, both methods had corresponding results, showing global accuracy near 84%. NDVI temporal metrics showed producer’s and user’s accuracy for the annual crop class of 86 and 100%, respectively. However, if considering only two classes, the NDVI temporal metrics reached global accuracy of near 98% and producer’s and user’s accuracy above 94%.

RESUMO A Estimativa da evapotranspiração é um fator chave para alcançar uma gestão sustentável da água na agricultura irrigada, pois representa o uso consuntivo da água dos cultivos agrícolas. Estimativas baseadas em imagens de satélite oferecem vantagens em comparação aos métodos diretos como lisímetros, especialmente quando o objetivo é calcular a evapotranspiração em escala regional. O presente estudo teve como objetivo estimar a evapotranspiração real (ETr) em escala regional, utilizando imagens Landsat 8 - OLI/TIRS e dados complementares coletados de estação meteorológica. O modelo SEBAL foi aplicado no Sudoeste do Paraná, região composta por áreas agrícolas irrigadas e sequeiro, vegetação nativa e áreas urbanas. Cinco imagens Landsat 8, órbita/ponto 223/78, dia do ano 336/2013, 19/2014, 35/2014, 131/2014 e 195/2014, foram utilizadas a partir da qual a ETr em escala diária foi estimada como parte residual do balanço de energia de superfície para produzir mapas de ETr. Os procedimentos para obter ETr usando SEBAL incluem calibração radiométrica, cálculo da refletância, albedo da superfície, índices de vegetação (NDVI, SAVI e IAF) e emissividade. Estes parâmetros foram obtidos com base nas bandas reflectivas do sensor orbital com a superfície temperatura estimada utilizando a banda térmica. Os valores de ETr estimados em áreas agrícolas, vegetação nativa e áreas urbanas utilizando o algoritmo SEBAL foram compatíveis com os apresentados na literatura e o erro entre evapotranspiração estimada com o SEBAL e a equação de Penman Monteith FAO 56 foram inferiores ou iguais a 1,00 mm dia- 1.

ABSTRACT Estimation of evapotranspiration is a key factor to achieve sustainable water management in irrigated agriculture because it represents water use of crops. Satellite-based estimations provide advantages compared to direct methods as lysimeters especially when the objective is to calculate evapotranspiration at a regional scale. The present study aimed to estimate the actual evapotranspiration (ET) at a regional scale, using Landsat 8 - OLI/TIRS images and complementary data collected from a weather station. SEBAL model was used in South-West Paraná, region composed of irrigated and dry agricultural areas, native vegetation and urban areas. Five Landsat 8 images, row 223 and path 78, DOY 336/2013, 19/2014, 35/2014, 131/2014 and 195/2014 were used, from which ET at daily scale was estimated as a residual of the surface energy balance to produce ET maps. The steps for obtain ET using SEBAL include radiometric calibration, calculation of the reflectance, surface albedo, vegetation indexes (NDVI, SAVI and LAI) and emissivity. These parameters were obtained based on the reflective bands of the orbital sensor with temperature surface estimated from thermal band. The estimated ET values in agricultural areas, native vegetation and urban areas using SEBAL algorithm were compatible with those shown in the literature and ET errors between the ET estimates from SEBAL model and Penman Monteith FAO 56 equation were less than or equal to 1.00 mm day-1.

ABSTRACT Aquatic sediments are widely used for the evaluation of anthropogenic contamination due to their ability to adsorb particles and contaminants, making them historical environmental archives. Therefore, the objective was to evaluate the contamination of the Pelotas River sediments, at the border between the states of Santa Catarina and Rio Grande do Sul, by organochlorine and organophosphorus compounds, determining the ecological risk. The evaluation was carried out with quarterly sediment collections in 8 points, totalizing four campaigns within one year, with the aid of the Peterson dredger. Among organochlorines, p'p'DDT stands out regarding environmental persistence, representing 53.23% of the contaminated samples, with values varying up to 0.158 ppb. As for the organophosphates, Methyl Parathion obtained larger representation with 48.4% of the contaminated samples, with concentrations ranging up to 2.42 ppb. The ecological risk of selected organochlorines demonstrated no problems associated with the biota. Regarding the organophosphates studied, Disulfoton presented a risk factor with significant potential for adverse effects on organisms. Therefore, the need for monitoring and sustainability in the use and application of pesticides is well known, aiming at environmental quality and the preservation of natural resources.

ABSTRACT This study demonstrates using remote sensing, geographic information systems and multivariate statistics to study water quality in an agricultural watershed. The monitoring of water quality in the watershed of Lontras's river in the southwestern region of the State of Paraná had been done in 2012 and 2013 with a multi-parameter probe in ten sites that were defined upstream and downstream watershed, during four different seasons. Mosaicked images were used from Google Earth, Digital Elevation Model and soil types of maps, defined as the explanatory variables. The definition of the areas of influence and multivariate statistical techniques, particularly the Redundancy Analysis (RDA), were used for the correlation between variables. In a spring area, located upstream watershed, the contribution on water quality variation has gotten smaller, when compared with the other monitoring sites. There was interference in water quality in downstream sites that has become greater due to the effects of diffuse pollution. The RDA enabled synthesizes the data variability structure and the relationship of multidimensional variables. These statistical techniques added to products resulting from the GIS contributed to a better understanding of the variation of water quality in the watershed.

ABSTRACT The knowledge of pesticide residual concentrations in the environment is important to understand the threats to the environment and human health, especially when natural resources are used for human consumption. In this context, this study aimed to assess the potential ecological risk and respective sources of sediment contamination by organochlorine and organophosphorus pesticides. The study site was an urban lake located in Cascavel city, western Paraná state, Brazil, where the history of land use and occupation in the urban environment is typically agricultural. Surface sediment samples were collected every three months from April 2010 to June 2013 at five different collection points, totaling 65 samples. Analyses showed that contamination by organochlorine pesticides is related to agricultural activities in the past, with a low ecological risk to benthic organisms. Conversely, organophosphorus pesticides presented a recent and continuous contamination from urban activities, with a risk coefficient, especially for disulfoton, indicating a significant potential adverse effect on organisms. However, in general, the obtained results did not indicate an immediate risk to public health.

RESUMO Aplicações de sensoriamento remoto na agricultura se apresentam como realidade muito promissora, contudo ainda há necessidade de pesquisas para a correta utilização dos dados espectrais. Objetivou-se, neste estudo, avaliar os padrões espectro-temporais de onze cultivares de trigo (Triticum aestivum L.). O experimento foi conduzido, em Cascavel, PR, no ano de 2014. Com o auxílio dos sensores terrestres GreenSeeker e FieldSpec 4 foram determinadas assinaturas espectrais e criados os perfis temporais do Índice de Vegetação por Diferença Normalizada (NDVI). Verificou-se diferenças estatísticas entre as cultivares de trigo por meio da análise de variância (ANOVA) e do teste de médias de Scott-Knott. Correlacionaram-se as produtividades de grãos obtidas com os fatores INSEY (IN-Season Estimate of Yield). O NDVI normalizado por graus-dias acumulados dos estádios de desenvolvimento Feekes 2 e 8, mostrou-se mais consistente na estimativa da produtividade de grãos, explicando aproximadamente 70% da variação. No estádio Feekes 10.1, as cultivares de trigo apresentaram padrões espectrais diferentes nas faixas do infravermelho próximo e médio. Isto sugere que essas bandas espectrais podem ser utilizadas para diferenciar as cultivares de trigo.

ABSTRACT Remote sensing applications in agriculture are presented as a very promising reality, but research is still needed for the correct use of spectral data. The objective of this study was to evaluate the spectral-temporal patterns of eleven wheat cultivars (Triticum aestivum L.). The experiment was conducted in Cascavel, PR, in the year 2014. With the help of the GreenSeeker and FieldSpec 4 terrestrial sensors, spectral signatures were determined and the temporal profiles of the Normalized Difference Vegetation Index (NDVI) were created. Statistical differences between wheat cultivars were analysed using analysis of variance (ANOVA) and Scott-Knott test. Grain yields obtained with INSEY (In-Season Estimate of Yield) factors were correlated. NDVI normalized by degree-days accumulated from the Feekes growth stages 2 and 8 showed to be more consistent in the estimation of grain yield, explaining approximately 70% of the variation. At the Feekes stage 10.1, wheat cultivars presented different spectral patterns in the near and medium infrared bands. This suggests that these spectral bands can be used to differentiate wheat cultivars.

ABSTRACT: The traditional per-pixel classification methods consider only spectral information, and may be limited. Object-based classifiers, however, also consider shape and texture, firstly segmenting the image, and then classifying individual objects. Thus, a Geographic Object-Based Image Analysis (GEOBIA) was compared in conjunction with data mining techniques and a traditional per-pixel method. A cut of Landsat-8, bands 2 to 7, orbit/point 223/77, located between the municipalities of Cascavel, Corbélia, Cafelândia and Tupãssi, in the west part of the state of Paraná, from 12/18/2013 was used. In the GEOBIA approach was realized image segmentation, spatial and spectral attribute extraction, and classification using the decision tree supervised algorithm, J48. For the per-pixel method, we used the supervised Maximum Likelihood Classifier. Both approaches presented equivalent results, with Kappa Index of 0.75 and Global Accuracy (GA) of 78.97% for the approach by GEOBIA and Kappa Index of 0.72 and GA of 77.44% for the perpixel classification. The classification by GEOBIA showed better accuracy for the soil, forest and soybean classes, and did not show the splash aspect, which visually improves the classification result.

RESUMO: O estudo objetivou avaliar o uso das ferramentas do controle estatístico de qualidade na análise da uniformidade de um sistema de irrigação por microaspersão. Para a análise da irrigação foram utilizados os coeficientes de uniformidade de Christiansen (CUC) e o coeficiente de uniformidade de distribuição (CUD), e estes foram analisados estatisticamente através dos gráficos de controle de Shewhart e do índice de capacidade do processo (Cp). Para o experimento foram realizados 25 ensaios com um único microaspersor, sendo posteriormente simulados sete diferentes espaçamentos entre microaspersores. Os gráficos de controle contribuíram para o diagnóstico dos tratamentos sob controle e com resultados satisfatórios de uniformidade. O aumento do índice de capacidade do processo mostrou-se diretamente proporcional as médias dos valores de CUC e CUD.

ABSTRACT: The objective of this study was to evaluate the use of statistical quality control tools in the analysis of the uniformity of a microsprinkler irrigation system. For the analysis of irrigation Christiansen uniformity coefficient (CUC) and the distribution uniformity coefficient (DU) were statistically analyzed by means of the Shewhart control charts and process capability index (Cp). For the experiment 25 tests were carried out with a single micro sprinkler and subsequently seven different spacing between micro sprinklers were simulated. Control charts contributed to the diagnosis of the treatments to be under control and with satisfactory uniformity outcomes. Increase in process capability index was directly proportional to the average of CUC and DU.

RESUMO O Estado do Paraná caracteriza-se por uma grande variabilidade de épocas de semeadura (DS) e, consequentemente, pelo desenvolvimento máximo vegetativo (DMDV), colheita (DC) e ciclo (CI) para a cultura da soja. O objetivo deste trabalho foi estimar essas datas para o período de primavera-verão do ano-safra de 2011/2012, por meio de séries temporais de imagens do Índice de Vegetação Realçado (do inglês Enhanced Vegetation Index - EVI) do sensor Modis (Moderate Resolution Imaging Spectroradiometer). Gerou-se um perfil espectrotemporal médio de EVI, considerando todos os pixels mapeados como soja dentro de cada município. Estes dados serviram de entrada no software Timesat para estimar os decêndios do ciclo da cultura (DS, DMDV, DC e CI) por municípios. Os resultados mostraram que existe grande variabilidade de datas de plantio em diferentes mesorregiões do Estado. Verificaram-se também divergências entre os resultados encontrados e os dados oficiais de DS e DC. A maior parte da semeadura (65,16%) esteve entre o terceiro decêndio de outubro e o primeiro decêndio de novembro. A maior parte da área de soja do Estado do Paraná (65,46%) teve seu DMDV em janeiro e colheita em março (53,92%).

ABSTRACT Soybean sowing can be performed at a various dates (DS) in Paraná state, with subsequent maximum vegetative development (DMDV), harvest (DC) and cycle (CI). The purpose of this study was to estimate these dates within spring-summer season from the 2011/ 2012 crop harvest, by means of temporal series of the Enhanced Vegetation Index (EVI) from Moderate Resolution Imaging Spectroradiometer (Modis) sensor. We generated an average EVI spectro-temporal profile considering all pixels mapped as soybean within each municipality. These data were used as input to the Timesat software for estimates of 10-day crop cycle periods (DS, DMDV, DC and CI). The results demonstrated great variability of dates at different areas of the Paraná state. We could also observe differences between our results and official estimates for DS and DC. Sowing was majorly (65.16%) performed in the third 10-day period of October and in the first 10-day period of November. Most of the Southern Paraná soybean area (65.46%) had their maximum vegetative development (MDV) in January and harvest in March (53.92%).

The purpose of this study was to analyze the spatial variability of soil properties and productivity and the chemical and physical properties of oranges (Monte Parnaso variety) in their geographical quadrants. This experiment was conducted in a commercial orange orchard in the municipality of Nova Laranjeiras in the State of Paraná, Brazil. A GPS receiver and a total station were used to measure the spatial location of the fruit and to determine which quadrant they were located in. In this experiment, 13 trees were studied. Twelve fruits were evaluated in each geographical quadrant, and 156 fruits were considered. After harvest, the productivity was expressed as kg per quadrant (kg quadrant-1). Next, physical tests (equatorial diameter (EqD), total fruit mass (TFM), juice yield (JY)) and chemical tests (total soluble solids (TSS), total titrable acidity (TTA), the TSS/TTA ratio, and the ascorbic acid (AA) content) were conducted in the laboratory. In addition, the data were subjected to analysis by descriptive statistics and geostatistics to determine the spatial variability of the physical and chemical properties of the oranges, the variations of the soil properties and the correlations between the following parameters: the pH properties of the fruit and Zn; TFM and K; EqD and K, and C and TSS. The orchard varies spatially, especially regarding the EqD, TFM, JcP, TSS and AA for the quadrants with the highest values (the Northwest, Southeast, Northeast, Southwest and Southeast, respectively). The soil potassium and zinc contents were strongly correlated with the physical and chemical properties of the orange fruits.

El objetivo de este estudio ha sido analizar la variabilidad espacial de los atributos del suelo, de la productividad y de las propiedades físicas y químicas de los frutos de la variedad de naranja "Monte Parnaso", en relación a los cuadrantes geográficos en que se ubican los frutos analizados. El experimento se realizó en un huerto comercial de naranjos en Nova Laranjeiras, Estado de Paraná, Brasil. En el procedimiento de georreferenciación de la área y de cada árbol de la muestra, se utilizó un GPS y una estación total para medir la localización espacial de la fruta y luego la definición de qué cuadrante se ubicaban. En el experimento, se utilizaron 13 árboles en las cuales se analizaron tres frutas por cuadrante geográfico de cada árbol, por un total de 156 frutas. Después de la cosecha se estimó la productividad en kg cuadrante-1 y en el laboratorio fueran realizados análisis física (diámetro ecuatorial (ED), masa total de la fruta (MT), rendimiento de jugo (RS)) y químicos (sólidos solubles totales (SST), acidez titulable (AT), relación SST/AT y ácido ascórbico (AA)) de la fruta. Los datos fueron sometidos a análisis de la estadística descriptiva y de la geoestadística señalando la variabilidad espacial de las propiedades físico-químicas de las naranjas y los atributos del suelo y también correlación entre los atributos de la fruta pH y Zn, MT y K, ED y K y finalmente SST y C. El huerto tiene variaciones espaciales principalmente para los atributos diámetro ecuatorial, masa total de la fruta, rendimiento del jugo, SST y ácido ascórbico, siendo los cuadrantes con mayores valores fueron, respectivamente, noroeste, sureste, noreste, suroeste y sureste. Especialmente potasio y zinc, las propiedades del suelo, fuertemente correlacionados con las propiedades físicas y químicas de las frutas de color naranja.

No presente trabalho, realizou-se a análise da distribuição espacial de área dos valores de produção municipal para a cultura da soja, no Estado do Paraná. Os dados dos sete anos-safras, entre 2003/2004 e 2009/2010, foram obtidos da Secretaria da Agricultura e do Abastecimento do Paraná (SEAB). Elaborou-se um Boxmap para cada ano-safra, com o intuito de demonstrar como ocorreu a alternância dos valores de produção de soja neste intervalo de tempo. O Índice de Moran foi utilizado para apresentar os níveis de autocorrelação espacial a nível global entre os municípios e o índice de autocorrelação LISA, para estudar a autocorrelação espacial a nível local, com diferentes matrizes de contiguidade e com diferentes ordens de contiguidade, assim como o estudo dos níveis de significância. Através destes métodos, foi possível demonstrar como os municípios se relacionam espacialmente quanto à produção da soja, o que permitiu a indicação de clusters de alta-baixa produção, possibilitando assim que se conheçam os principais municípios produtores de soja, subsidiando os membros da cadeia produtiva com informações para melhorar seus planos no fortalecimento da cultura no Paraná.

In the current study, we performed a soybean production spatial distribution analysis in Paraná State. Seven crop-year data, from 2003-04 to 2009-10, obtained from the Paraná Department of Agriculture and Supply (SEAB) were used to develop a Boxmap for each crop-year, show soybean production throughout this time interval. Moran's index was used to measure spatial autocorrelation among municipalities at an aggregate level, while LISA index local correlation. For each index, different contiguity matrix and order were used and there was a significance level study. As a result, we have showed spatial relationship among cities regarding the production, which allowed the indication of high and low production clusters. Finally, identifying main soybean-producing cities, what may provide supply chain members with information to strengthen the crop production in Paraná.

S.C. Wrublack, V.H.R. Prudente, E. Mercante, and S.R.M Coelho. 2013. Spatial distribution of Canola culture in the State of Paraná (Brazil) between the agricultural years of 2005 and 2009. Cien. Inv. Agr. 40(3): 513-521. There are a number of crops that are viable for small farms. To increase our knowledge of the occurrence of canola cultivation in the State of Paraná, the present study aimed to identify the areas sown with canola (ha) and to examine canola production (t) during the growing seasons of 2005 to 2009. The methodology involved a literature review and analysis of spatial data from the Secretaria da Agricultura e do Abastecimento do Paraná (SEAB/PR). We used the software ArcGis 9.3 for elaboration of thematic maps of variables as well as the free software GeoDa 0.9.5-i. The identification of spatial dependence was conducted through global univariate spatial autocorrelation using Moran's Index (I) statistic and, at a local level, using Local Indicators of Spatial Association (LISA). Spatial correlation was detected in the data on the area sown (ha) and production (t) for the canola crop. The results also indicated the possibility of expansion of cultivated areas in the State of Paraná, in addition to providing interesting options regarding the composition of systems of crop rotation and soil cover. The application of the spatial statistical area contributed to the recognition of the evolution of the canola crop in the State of Paraná, based on the spatialization of production and sown areas in its municipalities. It is evident that most municipalities show no significant pattern, demonstrating the potential for the expansion of sown areas in the State. For the High-High standard, it was noted that the municipalities were grouped mainly in the western and south-central State of Paraná.

S.C. Wrublack, V.H.R. Prudente, E. Mercante y S.R.M. Coelho. 2013. Distribución espacial del cultivo de canola en el Estado de Paraná (Brasil) entre los años agrícolas de 2005 a 2009. Cien. Inv. Agr. 40(3): 513-521. Hay varios cultivos viables para las pequeñas fincas. A fin de proporcionar un mayor conocimiento de la ocurrencia del cultivo de canola en el Estado de Paraná, el presente estudio tuvo como objetivo identificar la superficie sembrada (ha) y producción de canola (t) durante el período de 2005 a 2009. La metodología implicó en una revisión de literatura y análisis de datos espaciales del Secretaria da Agricultura e do Abastecimento do Paraná (SEAB/PR). Se utilizó el software ArcGIS 9.3 para la preparación de mapas temáticos de las variables y el software libre OpenGeoda 0.9.9.6. La identificación de la dependencia espacial se realizó a nivel global mediante la autocorrelación espacial univariado por intermedio de la estadística I de Moran y a nivel local por el indicador local de asociación espacial (LISA). Fue observada la existencia de correlación espacial en el área de datos sembrada (ha) y producción (t) con cultivo de canola. Los resultados también indican que el Estado de Paraná tiene un gran potencial para la expansión del cultivo, además de ser una opción interesante para componer sistemas de rotación de cultivos y la cobertura del suelo. La aplicación de la estadística espacial de área, contribuyó al reconocimiento de la evolución de los cultivos de canola en el Estado de Paraná, a través de la distribución espacial de la producción y de las superficies sembradas de los municipios. Es evidente un mayor número de municipios sin un patrón significativo, lo que demuestra el potencial de expansión de la superficie a sembrar en el Estado. En el estándar Alto-Alto, se observó que los municipios se agrupan principalmente en la región occidental y centro-sur del estado del Paraná.

Os objetivos do trabalho consistiram no mapeamento do uso e ocupação do solo e na avaliação da qualidade da água utilizada para irrigação, no município de Salto do Lontra, Estado do Paraná. Foram utilizadas imagens do satélite SPOT-5 para a realização da classificação supervisionada pelo algoritmo de Máxima Verossimilhança - MAXVER, e para a averiguação da qualidade da água foram analisados os parâmetros pH, CE, HCO3-, Cl-, PO4(3-), NO3-, turbidez, temperatura e coliformes termotolerantes, em dois períodos anuais distintos de precipitação. Os dados de qualidade da água foram submetidos às análises estatísticas pelas técnicas de ACP e AF, para a identificação das variáveis mais relevantes na avaliação da qualidade da água de irrigação. A caracterização de uso e ocupação do solo pelo classificador MAXVER permitiu a identificação das classes: culturas agrícolas, solo exposto/resteva, mata e área urbana. A aplicação da técnica ACP dos dados de qualidade da água de irrigação explicou 53,27% da variação na qualidade da água entre os pontos amostrados. Verificou-se que os parâmetros nitrato, coliformes termotolerantes, temperatura, condutividade elétrica e bicarbonato foram os parâmetros que melhor explicaram a variação espacial da qualidade da água.

The objective of this study consisted on mapping the use and soil occupation and evaluation of the quality of irrigation water used in Salto do Lontra, in the state of Paraná, Brazil. Images of the satellite SPOT-5 were used to perform the supervised classification of the Maximum Likelihood algorithm - MAXVER, and the water quality parameters analyzed were pH, EC, HCO3-, Cl-, PO4(3-), NO3-, turbidity, temperature and thermotolerant coliforms in two distinct rainfall periods. The water quality data were subjected to statistical analysis by the techniques of PCA and FA, to identify the most relevant variables in assessing the quality of irrigation water. The characterization of soil use and occupation by the classifier MAXVER allowed the identification of the following classes: crops, bare soil/stubble, forests and urban area. The PCA technique applied to irrigation water quality data explained 53.27% of the variation in water quality among the sampled points. Nitrate, thermotolerant coliforms, temperature, electrical conductivity and bicarbonate were the parameters that best explained the spatial variation of water quality.