Performance of coherent optical receivers using PSK modulation.

Vivemos numa era onde informação tem se tornado parte fundamental do dia a dia de nossas vidas. Os avanços recentes na tecnologia de comunicações ópticas vem revolucionando a infra-estrutura das telecomunicações em diversos países. Processo semelhante poderá vir a ocorrer no Brasil ao longo desta e das próximas décadas. Capacidades de transmissão cada vez mais elevadas tem possibilitado a implantação de redes de comunicações que viabilizam a integração de diferentes tipos de trafego, a sofisticação dos serviços disponíveis, a interconexão de redes remotas, etc. Os progressos na tecnologia de processadores rápidos para comunicações, importantes para a implementação de protocolos de acesso múltiplo ao canal óptico, vem aos poucos abrindo novas possibilidades para a exploração do enorme potencial para transporte de informação inerente as fibras ópticas monomodo.We live in an age where information has become a fundamental part of everyday life. of our lives. Recent advances in optical communications technology have come revolutionizing telecommunications infrastructure in many countries. Process This may occur in Brazil over this and the coming decades. Increasing transmission capacities have enabled the deployment of communications networks that enable the integration of different types of traffic, the sophistication of available services, the interconnection of remote networks, etc. Advances in fast communications processor technology, important for the implementation of optical channel multiple access protocols, are gradually opening up new possibilities for exploiting the enormous potential for information transport inherent in single-mode optical fibers

Índices de vegetação obtidos por imagens de satélite como estimadores do IAF e nitrogênio no algodoeiro

Spectral indices have been studied on evaluating of their sensitivity to vegetation biophysical parameters, as well as to external factors affecting canopy reflectance. Because the Leaf Area Index (LAI) is functionally linked to the canopy spectral reflectance, its retrieval from remote sensing data has stimulated many investigations in recent years. In this context, five vegetation indexes (NDVI, SAVI, RDVI, MSAVI and MTVI2) were evaluated as predictors to leaf nitrogen, leaf area index (LAI) and lint yield for irrigated cotton. Were done assessments in three different seasons when was determined the leaf nitrogen content, SPAD index and LAI during the evaluation, and lint yield on the harvest. Vegetations indexes, LAI and lint yield were estimated using TM lansat-5 images for these evaluation seasons. It was observed that leaf nitrogen content can be estimated from the chlorophyll content using SPAD index. It´s possible to estimate leaf N contents using the IAF obtained by satellite images at later stages and especially during cotton flowering. All evaluated vegetation indices appeared as good predictors of leaf area index of irrigated cotton. Lint yield could be estimated with high accuracy by the IAF obtained with images from TM Landsat-5 during the flowering and fruiting stage.Pages: 659-66

Spatial variability of physical-chemical attributes of soil and its effects on cotton yield

No Brasil, a utilização de sensores de produtividade no algodoeiro é recente. A variabilidade de atributos físicos e químicos de solo abre a possibilidade de delimitar zonas homogêneas dentro da lavoura. Relações entre esses atributos e a produtividade do algodoeiro podem ser obtidas indicando o potencial da cultura em cada condição de solo. O objetivo deste trabalho foi estabelecer relações entre atributos de solo que determinem sua variabilidade espacial e que interferem na produtividade do algodoeiro. Foi conduzido um experimento em área de 56,1 ha, em Cristalina, GO, com a cultura do algodão. Amostragens de solo foram realizadas em uma grade regular de 80 x 80 m para avaliação dos atributos químicos e físicos e leituras contínuas de condutividade elétrica aparente (CEa). Os dados de produtividade do algodoeiro foram obtidos por colhedoras equipadas com sensor de fluxo, nas safras 2010/11 e 2011/12. A produtividade apresentou forte dependência espacial e possui correlação negativa com CEa, pH CaCl2; a CEa foi uma ferramenta adequada para identificação da variabilidade de acidez e de nutrientes no solo na condição estudada possibilitando delimitar zonas homogêneas, para o manejo de forma diferenciada.The use of cotton productivity sensors is recent in Brazil. Variability of physical and chemical properties of soil opens the possibility of delimiting homogeneous zones in crop fields. Relationships between these properties and cotton yield can be obtained, indicating the crop potential for each soil condition. The objective of this study was to establish relationships between soil attributes that have spatial variability and its interference in cotton yield. The experiment was carried out in 56.1 ha, in Cristalina, GO, with cotton. Soil samples were collected on a regular grid of 80 x 80 m for evaluation of chemical and physical attributes and apparent electrical conductivity of soil (ECa). The cotton yield was measured by machines equipped with flow sensor during 2010/11 and 2011/12 cropping seasons. Cotton yield showed strong spatial dependence and has negative correlation with ECa and pH CaCl2. The ECa was an useful tool to identify the variability of acidity and soil nutrients in this study, allowing to delimit homogeneous zones to a distinct management

Spatial variability of physical-chemical attributes of soil and its effects on cotton yield

No Brasil, a utilização de sensores de produtividade no algodoeiro é recente. A variabilidade de atributos físicos e químicos de solo abre a possibilidade de delimitar zonas homogêneas dentro da lavoura. Relações entre esses atributos e a produtividade do algodoeiro podem ser obtidas indicando o potencial da cultura em cada condição de solo. O objetivo deste trabalho foi estabelecer relações entre atributos de solo que determinem sua variabilidade espacial e que interferem na produtividade do algodoeiro. Foi conduzido um experimento em área de 56,1 ha, em Cristalina, GO, com a cultura do algodão. Amostragens de solo foram realizadas em uma grade regular de 80 x 80 m para avaliação dos atributos químicos e físicos e leituras contínuas de condutividade elétrica aparente (CEa). Os dados de produtividade do algodoeiro foram obtidos por colhedoras equipadas com sensor de fluxo, nas safras 2010/11 e 2011/12. A produtividade apresentou forte dependência espacial e possui correlação negativa com CEa, pH CaCl2; a CEa foi uma ferramenta adequada para identificação da variabilidade de acidez e de nutrientes no solo na condição estudada possibilitando delimitar zonas homogêneas, para o manejo de forma diferenciada.The use of cotton productivity sensors is recent in Brazil. Variability of physical and chemical properties of soil opens the possibility of delimiting homogeneous zones in crop fields. Relationships between these properties and cotton yield can be obtained, indicating the crop potential for each soil condition. The objective of this study was to establish relationships between soil attributes that have spatial variability and its interference in cotton yield. The experiment was carried out in 56.1 ha, in Cristalina, GO, with cotton. Soil samples were collected on a regular grid of 80 x 80 m for evaluation of chemical and physical attributes and apparent electrical conductivity of soil (ECa). The cotton yield was measured by machines equipped with flow sensor during 2010/11 and 2011/12 cropping seasons. Cotton yield showed strong spatial dependence and has negative correlation with ECa and pH CaCl2. The ECa was an useful tool to identify the variability of acidity and soil nutrients in this study, allowing to delimit homogeneous zones to a distinct management

COTTON RESPONSE TO WATER DEFICITS AT DIFFERENT GROWTH STAGES

Water deficit at certain cotton growth stages can cause severe damage to crop development, affecting physiological processes and reducing reproductive structures, with consequent yield losses. The objective of this study was to evaluate the response of cotton cultivars under water deficit applied at different stages of the crop cycle. We compared the number of bolls per meter, cotton yield, and water use efficiency for eight different cotton cultivars under a water deficit of 15 days. We selected the following growth stages: Emergence (EM), First Square (FS), First Flower (FL), Peak Bloom (PB), and First Open Boll (FOB). The control treatment was irrigated with 100% ETc. The experiment was conducted in Apodi, RN State of Brazil, semiarid region, using a sprinkler irrigation system. The number of bolls per meter, cotton yield, and water use efficiency were influenced by the interaction of cultivars x deficit periods. Lowest values were observed for water suppression in the FL and PB stages. When the water deficit was imposed in the initial stages of growth (EM to FS) or after the FOB stage, the cotton yield reduction was not significant. At the same stage and water deficit, the behavior of the different cultivars was similar. Producers are urged to take this information into account when developing irrigation schemes for cotton crops, thereby avoiding water deficits during the most critical periods of the crop cycle

Evapotranspiração real obtida através da relação entre o coeficiente dual de cultura da FAO-56 e o NDVI Real actual evapotranspiration obtained through the relationship between the FAO-56 crop dual coefficient and NDVI

Um requisito fundamental para adoção de manejo da irrigação é a determinação diária da evapotranspiração (ET) das culturas. Em caráter operacional o método do coeficiente de cultura proposto pela Food Agriculture Organization (FAO), através do seu relatório 56 (Irrigation and Drainage Paper), é largamente utilizado na determinação da ET, e tem apresentado precisões que o tornam mundialmente aceito. A ET com base no coeficiente de cultura (Kc), obtido a partir de índices de vegetação, particularmente o NDVI, tem sido calculada em vários estudos e para diversas culturas alcançando muita precisão, quando comparado com observações de campo. Diante do exposto, este trabalho teve por objetivo calcular a ET diária e sazonal da cultura do algodoeiro utilizando o método do Kc dual obtido em função do Índice de Vegetação por Diferença Normalizada - NDVI, obtido a partir de imagens TM - Landsat 5 livre da presença de nuvens. Os resultados revelaram precisões bastante confiáveis, pois foram verificadas diferenças menores que 10%, quando comparados com valores da ET obtidos pela técnica da Bowen, corroborando com o desempenho alcançado pelo método em outras pesquisas realizadas em outras regiões do planeta. Dessa forma, pode-se concluir que o método apresenta bastante confiabilidade e simplicidade.A fundamental requirement for adoption of irrigation management is to determine the crop daily evapotranspiration (ET). On an operational basis the crop coefficient method proposed by the Food and Agriculture Organization (FAO) through its report 56 (Irrigation and Drainage Paper) is widely used in the determination of ET and due to its accurate estimative, it has been globally accepted. The ET-based crop coefficient (Kc) obtained from vegetation indices, particularly the Vegetation Index Normalized Difference (NDVI) has been measured in several studies and various crops showing great accuracy when compared to field observations. The objective of this study was to calculate the daily and seasonal ET of cotton crop using the method of dual Kc obtained as a function of the NDVI obtained from TM - Landsat 5 images clouds free. The obtained results are reliable, because less than 10% differences were found when comparing to the Bowen ratio technique observations, corroborating to the method performance achieved in other experiments conducted in other regions of the Earth. Thus, one can conclude that the method both simple and reliable

Detecção da necessidade de suplementação nitrogenada para o algodoeiro usando imagens do sensor AWiFS e espectrorradiometria

Rapid and non-destructive estimation of crop nitrogen content is a potentially important application for farmers optimize the management of nitrogen fertilization. The objective of this work was to study the behavior of three vegetation indices obtained by both AWiFS satellite images as by field spectroradiometry data and evaluate their sensitivity to distinguish the leaf N content during the 2011 cotton season, in commercial field of Goiás state. Hyperspectral reflectance was measured at 0.5 m above the cotton canopy on February 08 and April 01, 2011 using an PAR-NIR Apogee\uae spectroradiometer. Corresponding leaf area index, SPAD-502 readings and plant height were also measured on these dates. Hyperspectral data were carried out to compare performances of existing vegetation indices: Normalized Difference Vegetation Index (NDVI), Modified Soil-Adjusted Vegetation Index (MSAVI) and Tranformed Vegetation Index (TVI).Results show that hyperspectral reflectance data using vegetation indices reached significant levels of accuracy in the retrieval of N levels for both evaluation dates, where the NDVI and TVI showed the best performance. The low resolution of the images sensor AWiFS not allow identification of the spatial variability of nitrogen content in cotton plants at first flowering on February, 08. At the stage of maximum flowering, both hyperspectral vegetation indices as obtained by satellite images of medium resolution presented themselves as good estimators of leaf nitrogen. The NDVI and TVI obtained by spectroradiometry can be used as an economical and quick alternative to recommend supplementation of nitrogen fertilization on cotton planting in the Brazilian cerrado.Pages: 778-78

Estimativa da necessidade hídrica do algodoeiro irrigado usando imagens de satélite

Remote sensing data in the thermal infrared part of the spectrum provides indirect estimates of water stress for vegetated surfaces that is defined as a function of the ratio between actual and potential evapotranspiration rates. Methods to estimate the actual evapotranspiration (ETr) from satellite images with thermal bands are very useful, because they can provide an accurate estimate for large areas. In this context, in 2008 an experiment was carried out in Apodi, RN, in order to estimate the ETr for irrigated cotton. It was used the Bowen ratio obtained with field data to validate data obtained by satellite images through the SEBAL (Surface Energy Balance Algorithm for Land methodology) algorithm. The cotton was seeded in 3.6 ha with 0.9 m between rows. The crop actual evapotranspiration was estimated using three images from Landsat 5, obtained at the 34DAE, 50DAE and 82DAE. The Bowen ratio and reference evapotranspiration (ET0) were determined using meteorological data and also from equipments installed in the experimental area. After the estimation of ET obtained under field conditions and the estimation of ETr by satellite, results were analyzed to evaluate the comparative error. It was observed that the ETr estimated from the algorithm SEBAL shows similar results to those obtained by Bowen ratio and can be used to assess the water requirement of cotton.Pages: 653-65

Non-destructive analysis of photosynthetic pigments in cotton plants=Análise não destrutiva dos pigmentos fotossintéticos em plantas de algodoeiro.

Analytical techniques used to extract chlorophyll from plant leaves are destructive and based on the use of organic solvents. This study proposes a non-destructive quantification of the photosynthetic pigment concentration in cotton leaves using two portable chlorophyll meters, the SPAD-502 and the CLOROFILOG 1030. After obtaining 200 leaf discs, each with an area of 113 mm2, the greening rate in each disc was determined by the average of five readings from both meters. Immediately after measurement, 5 mL of dimethyl sulfoxide (DMSO) was added, and the samples were kept in a water bath at 70ºC for 30 min. After cooling, 3 mL of the liquid extract was used for analyses by spectrophotometry at 470, 646 and 663 nm. Mathematical models were adjusted from analytical results using the reading index obtained from both devices to predict the contents of chlorophyll a, chlorophyll b, total chlorophyll and carotenoids. Based on these results, it was concluded that both portable chlorophyll meters are an effective way to estimate the concentration of photosynthetic pigments in cotton leaves, thus saving time, space and the resources that are often required for these analyses.<br><br>Técnicas analíticas empregadas na extração de clorofila em plantas são destrutivas e fundamentam-se no uso de solventes orgânicos. Este estudo propõe a quantificação não destrutiva da concentração de pigmentos fotossintéticos em folhas de algodoeiro utilizando os medidores portáteis de clorofila SPAD-502 e CLOROFILOG 1030. Com as folhas coletadas foram elaborados 200 discos foliares com área de 113 mm2. A determinação do índice de esverdeamento em cada disco foi realizada por meio da média de cinco leituras com ambos clorofilômetros portáteis e imediatamente após a determinação, adicionaram-se 5 mL de Dimetil sulfóxido (DMSO). Os discos foram mantidos em banho-maria a temperatura de 70ºC por um período de 30 min. Após o resfriamento do extrato líquido, uma alíquota de 3,0 mL foi utilizada para leitura utilizando espectrofotometria a 470, 646 e 663 nm. A partir dos resultados analíticos obtidos foram ajustados modelos matemáticos utilizando-se o índice das leituras efetuadas por ambos os equipamentos para estimar os teores de clorofila a, clorofila b, clorofila total e carotenóides. Considerando os resultados obtidos conclui-se que ambos medidores portáteis de clorofila poderão ser utilizados para estimar a concentração dos pigmentos fotossintéticos em folhas de algodoeiro, economizando tempo, espaço e recursos comumente demandados nessas análises

Soil and satellite remote sensing variables importance using machine learning to predict cotton yield

Remote sensing (RS) in agriculture has been widely used for mapping soil, plant, and atmosphere attributes, as well as helping in the sustainable production of the crop by providing the possibility of application at variable rates and estimating the productivity of agricultural crops. In this way, proximal sensors used by RS help producers in decision-making to increase productivity. This research aims to identify the best feature importance ranking to the Random Forest Classifier to predict cotton yield and select which one best correlates with cotton yield. This work was developed in four commercial fields on a Newellton, LA, USA farm. We evaluated the cotton in different years as 2019, 2020, and 2021. The variables evaluated were: soil parameters, topographic indices, elevation derivatives, and orbital remote sensing. The soil sensor used was: GSSI Profiler EMP400 (soil electromagnetic induction sensor) at a frequency of 15 kHz, and the RS data were collected from satellite images from Sentinel 2 (passive sensor) and active sensor from LiDAR (Light Detection and Ranging). For training (70%) and validation (30%) of dataset results, Spearman correlation was used between sensors and cotton yield data, machine learning (Random Forest Classifier and Regressor - RFC and RFR). The metric parameters were the coefficient of determination (R²), the Mean Absolute Error (MAE), and the Root Mean Square Error (RMSE). This study found that profiler, Sentinel-2 (blue, red, and green), TPI, LiDAR, and RTK elevation show the best correlations to predicting cotton yield