22 research outputs found

    Teor de clorofila e produção de matĂ©ria seca de Brachiaria brizantha cv. Marandu, adubada com duas fontes de nitrogĂȘnio.

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    O objetivo deste estudo foi determinar o conteĂșdo de clorofila a + b (valores SPAD), por meio do uso de um clorofilĂŽmetro portĂĄtil, em folhas de Brachiaria brizantha cv. Marandu adubada com duas fontes de N. em dois cortes. Os valores SPAD variaram de 29 a 51`. Os coeficientes de correlação mĂ©dio entre os valores SPAD e as doses de N de urĂ©ia e do nitrato de amĂŽnio variaram entre 0,83 e 0,95, conforme o corte e entre os valores SPAD e a produção de matĂ©ria seca foram de 0,83 e 0,93, respectivamente, para as parcelas adubadas com urĂ©ia e nitrato de amĂŽnio. Os valores SPAD determinadas para 90% da producao mĂĄxima de matĂ©ria seca ficaram entre 22 a 48, para ambas fontes de N. Dessa forma, o clorofilĂŽmetro pode ser ferramenta Ăștil para o manejo de N em pastagem de gramĂ­nea tropical

    Appropriateness of Management Zones for Characterizing Spatial Variability of Soil Properties and Irrigated Corn Yields across Years

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    Recent precision-agriculture research has focused on use of management zones (MZ) as a method for variable application of inputs like N. The objectives of this study were to determine (i) if landscape attributes could be aggregated into MZthat characterize spatial varia- tion in soil chemical properties and corn yields and (ii) if temporal variability affects expression of yield spatial variability. This work was conducted on an irrigated cornfield near Gibbon, NE. Five landscape attributes, including a soil brightness image (red, green, and blue bands), elevation, and apparent electrical conductivity, were acquired for the field.Ageoreferenced soil-sampling scheme was used to determine soil chemical properties (soil pH, electrical conductivity, P, and organic matter). Georeferenced yield monitor data were collected for five (1997–2001) seasons. The five landscape attributes were aggregated into four MZ using principal-component analysis of landscape attributes and unsupervised classification of principal-component scores. All of the soil chemical properties differed among the four MZ. While yields were observed to differ by up to 25% between the highest- and lowest-yielding MZ in three of five seasons, receiving average precipitation, less-pronounced (≀5%) differences were noted among the same MZ in the driest and wettest seasons. This illustrates the significant role temporal variability plays in altering yield spatial variability, even under irrigation. Use of MZ for variable application tem, of inputs like N would only have been appropriate for this field in three out of the five seasons, seriously restricting the use of this approach under variable environmental conditions

    Appropriateness of Management Zones for Characterizing Spatial Variability of Soil Properties and Irrigated Corn Yields across Years

    Get PDF
    Recent precision-agriculture research has focused on use of management zones (MZ) as a method for variable application of inputs like N. The objectives of this study were to determine (i) if landscape attributes could be aggregated into MZthat characterize spatial varia- tion in soil chemical properties and corn yields and (ii) if temporal variability affects expression of yield spatial variability. This work was conducted on an irrigated cornfield near Gibbon, NE. Five landscape attributes, including a soil brightness image (red, green, and blue bands), elevation, and apparent electrical conductivity, were acquired for the field.Ageoreferenced soil-sampling scheme was used to determine soil chemical properties (soil pH, electrical conductivity, P, and organic matter). Georeferenced yield monitor data were collected for five (1997–2001) seasons. The five landscape attributes were aggregated into four MZ using principal-component analysis of landscape attributes and unsupervised classification of principal-component scores. All of the soil chemical properties differed among the four MZ. While yields were observed to differ by up to 25% between the highest- and lowest-yielding MZ in three of five seasons, receiving average precipitation, less-pronounced (≀5%) differences were noted among the same MZ in the driest and wettest seasons. This illustrates the significant role temporal variability plays in altering yield spatial variability, even under irrigation. Use of MZ for variable application tem, of inputs like N would only have been appropriate for this field in three out of the five seasons, seriously restricting the use of this approach under variable environmental conditions
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