14 research outputs found
Cacao crop management zones determination based on soil properties and crop yield
The use of management zones has ensured yield success for numerous agricultural crops. In spite of this potential, studies applying precision agricultural techniques to cacao plantations are scarce or almost nonexistent. The aim of the present study was to delineate management zones for cacao crop, create maps combining soil physical properties and cacao tree yield, and identify what combinations best fit within the soil chemical properties. The study was conducted in 2014 on a cacao plantation in a Nitossolo Háplico Eutrófico (Rhodic Paleudult) in Bahia, Brazil. Soil samples were collected in a regular sampling grid with 120 sampling points in the 0.00-0.20 m soil layer, and pH(H2O), P, K+, Ca2+, Mg2+, Na+, H+Al, Fe, Zn, Cu, Mn, SB, V, TOC, effective CEC, CEC at pH 7.0, coarse sand, fine sand, clay, and silt were determined. Yield was measured in all the 120 points every month and stratified into annual, harvest, and early-harvest cacao yields. Data were subjected to geostatistical analysis, followed by ordinary kriging interpolation. The management zones were defined through a Fuzzy K-Means algorithm for combinations between soil physical properties and cacao tree yield. Concordance analysis was carried out between the delineated zones and soil chemical properties using Kappa coefficients. The zones that best classified the soil chemical properties were defined from the early-harvest cacao yield map associated with the clay or sand fractions. Silt content proved to be an inadequate variable for defining management zones for cacao production. The delineated management zones described the spatial variability of the soil chemical properties, and are therefore important for site-specific management in the cacao crop
Diversidade genética de populações de Xanthomonas phaseoli pv. manihotis em mandioca por meio de marcadores rep-PCR e VNTRs
The objective of this work was to evaluate the genetic diversity of Xanthomonas phaseoli pv. manihotis (Xpm) from eight populations from five cassava producing states in Brazil, through the rep-PCR (BOX-PCR and ERIC-PCR) and variable number of tandem repeat (VNTR) markers. Cassava leaves with symptoms of cassava bacterial blight were collected in eight municipalities, and the Xpm isolates were identified by amplification with primers specific for these isolates. The identity of the Xpm isolates was confirmed with the BOX-PCR, ERIC-PCR, and VNTR markers. The observed selection pressure, together with the mode of reproduction and the mechanisms that increase genetic variability, allows of the pathogen populations to adapt according to microclimate variation, contributing to a differentiated reproductive success. ERIC-PCR and VNTRs are the best markers for evaluating the genetic variability in the eight studied Xpm populations. However, ERIC-PCR is the marker that best separated the groups by population and presented a higher similarity between the isolates of the same population. The study of the genetic diversity of Xpm is key to improve disease monitoring and management strategies in cassava crops.O objetivo deste trabalho foi avaliar a diversidade genética de Xanthomonas phaseoli pv. manihotis (Xpm) de oito populações de cinco estados produtores de mandioca no Brasil, por meio de marcadores rep-PCR (BOX-PCR e ERIC-PCR) e variable number of tandem repeats (VNTRs). Folhas de mandioca com sintomas de crestamento bacteriano foram coletadas em oito municípios, e os isolados Xpm foram identificados por amplificação com iniciadores específicos para esses isolados. A identidade dos isolados Xmp foi confirmada com os marcadores BOX-PCR, ERIC-PCR e VNTRs. A pressão de seleção observada, junto com o modo de reprodução e os mecanismos que aumentam a variabilidade genética, permite que as populações do patógeno se adaptem de acordo com a variação dos microclimas, o que contribui para o sucesso reprodutivo diferenciado. ERIC-PCR e VNTRs são os melhores marcadores para avaliar a variabilidade genética das oito populações Xpm estudadas. No entanto, ERIC-PCR é o marcador que melhor separou os grupos por população e apresentou maior similaridade entre os isolados de uma mesma população. O estudo da diversidade genética de Xpm é fundamental para delinear estratégias de manejo e monitoramento de doenças na cultura da mandioca
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4
While the increasing availability of global databases on ecological communities has advanced our knowledge
of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In
the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of
Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus
crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced
environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian
Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by
2050. This means that unless we take immediate action, we will not be able to establish their current status,
much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio
Anais do V Encontro Brasileiro de Educomunicação: Educação midiática e políticas públicas
A presente coletânea, que chega ao público através de um suporte digital, tem como objetivo disponibilizar os papers, bem como os relatos de experiências educomunicativas apresentados durante o V ENCONTRO BRASILEIRO DE EDUCOMUNICAÇÃO, que teve como tema central: “Educação Midiática e Políticas Públicas”. O evento foi realizado em São Paulo, entre 19 e 21 de setembro de 2013, a partir de uma parceria entre o NCE/USP - Núcleo de Comunicação e Educação da USP, a Licenciatura em Educomunicação da ECA/USP, a ABPEducom – Associação Brasileira de Pesquisadores e Profissionais da Educomunicação e a FAPCOM – Faculdade Paulus de Tecnologia e Comunicação, que ofereceu seu campus, na Vila Mariana, para os atos do evento.
Os presentes anais disponibilizam o texto de abertura, de autoria do coordenador geral do evento, denominado “Educação midiática e políticas públicas: vertentes históricas da emergência da Educomunicação na América Latina”. Na sequência, apresentam 61 papers sobre aspectos específicos da temática geral, resultantes de pesquisas na área, seguidos de 27 relatos de práticas educomunicativas, em nível nacional
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
Irrigation management via soil sensors and nitrogen sources in sugarcane growth
O manejo da irrigação, por meio da utilização de sensores eletrônicos que estimam em tempo real o conteúdo de água no solo, e de N-fertilizante têm demonstrado efeito sinérgico positivo no desenvolvimento vegetal e potencial produtivo da cana-de-açúcar. Assim, o objetivo desta pesquisa foi avaliar o desempenho de diferentes sensores eletrônicos de umidade do solo na otimização do manejo da irrigação, visando elevar a precisão no uso racional da água, como também comparar o desenvolvimento inicial da cana-de-açúcar sob diferentes fontes de nitrogênio. O experimento foi conduzido em ambiente protegido do Departamento de Engenharia Agrícola da Universidade Federal Rural de Pernambuco, campus Recife-PE, entre os meses de abril a maio de 2019, inicialmente para calibração dos sensores; e, de dezembro de 2019 e março de 2020, para avaliação do desempenho destes no desenvolvimento inicial da cultura estudada sob diferentes fontes de nitrogênio. Para calibração, os sensores EC-5, 5TE e Diviner foram posicionados verticalmente nos vasos, com quatro repetições para cada tipo de solo (texturas franco argilo arenosa e areia). Após atingir a saturação por capilaridade, os vasos foram colocados em uma bancada, a fim de permitir a drenagem do excesso de água. Em seguida, os vasos foram pesados e realizadas as respectivas leituras de umidade do solo, representando a umidade equivalente à capacidade de campo. Diariamente, e em horário fixo (8 h), foram realizadas as pesagens e a leitura de cada sensor eletrônico. Os resultados foram submetidos à análise de regressão e, os índices estatísticos de Willmott, RMSE, coeficiente de determinação e erro médio foram utilizados para avaliar a qualidade do ajuste entre os valores medidos (umidade gravimétrica) e estimados pelos sensores de umidade de solo. Os sensores apresentaram equações de calibração de modelo linear para ambos os solos, e as análises apontaram boa correlação entre as leituras de umidade volumétrica medida e a estimada para ambos os solos com R2 acima de 0,94. A equação de calibração dos fabricantes de todos os sensores, EC-5, 5TE e Diviner superestimaram 2,77; 9,88 e 7,51%, respectivamente, os valores reais de umidade para o solo de textura mais arenosa e subestimaram em 21,88, 15,63 e 7,64%, de modo respectivo, no solo franco argilo arenosa, resultando em erros da determinação da lâmina de irrigação e, consequentemente, na quantidade de água demandada pela cultura. Sendo assim, e considerando a importância da mensuração da umidade do solo para o manejo da agricultura irrigada, os resultados desta pesquisa reforçam a necessidade de calibrar os sensores capacitivos ECH2O e Diviner em solos franco argilo arenosa e areia para fins de irrigação, visando o uso racional dos recursos naturais. De posse das equações de calibração, o segundo experimento foi conduzido para avaliar o desempenho dos sensores de umidades do solo (EC-5, 5TE e Diviner 2000) e da aplicação de duas fontes de nitrogênio (NH4)2SO4 e NH4NO3) nas variáveis biométricas da cana-de-açúcar. Para tanto, os tratamentos foram arranjados em delineamento inteiramente casualizado, em esquema fatorial 3 x 2, com 4 repetições, totalizando 24 parcelas experimentais. A irrigação foi realizada automaticamente, mediante um controlador eletrônico, de modo a aplicar as lâminas de irrigação de acordo com os tratamentos estabelecidos. As variáveis biométricas foram avaliadas mensalmente e ao final do experimento. Os resultados das variáveis biométricas foram submetidos à análise de variância, em nível de 0,05 de probabilidade. Como resultado para o solo franco argilo arenosa, os tratamentos nitrato de amônio utilizando o sensor 5TE e sulfato de amônio com EC-5 apresentaram maior eficiência do uso da água para as variáveis de massa seca 0,17 e 0,19 kg m-3, respectivamente, e massa fresca com 0,49 kg m-3 para ambos os tratamentos.The management of irrigation, through the use of electronic sensors that estimate in real time the soil water content, and of N-fertilizer have demonstrated a positive synergistic effect on plant development and productive potential of different varieties of sugarcane. Thus, the objective of this research was to evaluate the performance of different electronic sensors of soil moisture in the optimization of irrigation management, aiming to increase the precision in the rational use of water, as well as to compare the initial development of sugarcane under different sources of nitrogen. The experiment was carried out in a protected environment at the Agricultural Engineering Department of the Federal Rural University of Pernambuco, campus Recife-PE, between April and May 2019, initially for the calibration of sensors; and, from December 2019 and March 2020, to assess their performance in the initial development of the sugarcane under different sources of nitrogen. For calibration, the EC-5, 5TE and Diviner sensors were positioned vertically in the pots, with four replicates for each type of soil (sandy clay loam and sandy textural classes). After reaching capillarity saturation, the pots were placed on a bench in order to allow the drainage of excess water. Then, the pots were weighed and the respective soil moisture readings were performed, representing the moisture equivalent to the field capacity. Weighing and reading each electronic sensor was performed daily and at a fixed time (8 am). The results were subjected to regression analysis and the statistical indexes Willmott, RMSE, determination coefficient and mean error were used to assess the quality of the fit between the measured values (gravimetric moisture) and estimated by soil moisture sensors. The sensors presented linear model calibration equations for both soils, and the analyzes showed a good correlation between the readings measured volumetric moisture and the estimated for both soils with R2 above 0.94. The manufacturers calibration equation of all sensors, EC-5, 5TE and Diviner overestimated 2.8; 13.86 and 7.51%, respectively, the real moisture values for the sandy soil and underestimated by 21.88, 15.63 and 7.64%, respectively, in the sandy clay loam soil, resulting in errors in determining the irrigation depth and, consequently, in the amount of water required by the crop. Thus, and considering the importance of measuring soil moisture for the management of irrigated agriculture, the results of this research reinforce the need to calibrate the capacitive sensors ECH2O and Diviner in sandy clay loam and sandy soils for irrigation purposes, aiming at the use rational use of natural resources. After this step, the second experiment was carried out to evaluate the performance of soil moisture sensors (EC-5, 5TE and Diviner 2000) and the effects of application of two sources of nitrogen ((NH4)2SO4 and NH4NO3), in the biometric variables. Therefore, the treatments were arranged in a completely randomized design, in a 3 x 2 factorial scheme, with 4 replications, totaling 24 experimental plots. The irrigation was carried out automatically, using an electronic controller, in order to apply the irrigation depths according to the established treatments. Biometric variables were assessed monthly and at the end of the experiment. The results of the biometric variables were subjected to analysis of variance, at the level of 0.05 probability. As a result for the sandy clay loam soil, the ammonium nitrate treatments using the 5TE sensor and ammonium sulfate with EC-5 showed greater water use efficiency for dry mass 0.17 and 0.19 kg m-3, respectively, and fresh mass with 0.49 kg m-3 and for both treatments.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPE
Cacao Crop Management Zones Determination Based on Soil Properties and Crop Yield
ABSTRACT: The use of management zones has ensured yield success for numerous agricultural crops. In spite of this potential, studies applying precision agricultural techniques to cacao plantations are scarce or almost nonexistent. The aim of the present study was to delineate management zones for cacao crop, create maps combining soil physical properties and cacao tree yield, and identify what combinations best fit within the soil chemical properties. The study was conducted in 2014 on a cacao plantation in a Nitossolo Háplico Eutrófico (Rhodic Paleudult) in Bahia, Brazil. Soil samples were collected in a regular sampling grid with 120 sampling points in the 0.00-0.20 m soil layer, and pH(H2O), P, K+, Ca2+, Mg2+, Na+, H+Al, Fe, Zn, Cu, Mn, SB, V, TOC, effective CEC, CEC at pH 7.0, coarse sand, fine sand, clay, and silt were determined. Yield was measured in all the 120 points every month and stratified into annual, harvest, and early-harvest cacao yields. Data were subjected to geostatistical analysis, followed by ordinary kriging interpolation. The management zones were defined through a Fuzzy K-Means algorithm for combinations between soil physical properties and cacao tree yield. Concordance analysis was carried out between the delineated zones and soil chemical properties using Kappa coefficients. The zones that best classified the soil chemical properties were defined from the early-harvest cacao yield map associated with the clay or sand fractions. Silt content proved to be an inadequate variable for defining management zones for cacao production. The delineated management zones described the spatial variability of the soil chemical properties, and are therefore important for site-specific management in the cacao crop