Management zones definition using soil chemical and physical attributes in a soybean area

Several equipments and methodologies have been developed to make available precision agriculture, especially considering the high cost of its implantation and sampling. An interesting possibility is to define management zones aim at dividing producing areas in smaller management zones that could be treated differently, serving as a source of recommendation and analysis. Thus, this trial used physical and chemical properties of soil and yield aiming at the generation of management zones in order to identify whether they can be used as recommendation and analysis. Management zones were generated by the Fuzzy C-Means algorithm and their evaluation was performed by calculating the reduction of variance and performing means tests. The division of the area into two management zones was considered appropriate for the present distinct averages of most soil properties and yield. The used methodology allowed the generation of management zones that can serve as source of recommendation and soil analysis; despite the relative efficiency has shown a reduced variance for all attributes in divisions in the three sub-regions, the ANOVA did not show significative differences among the management zones.

[1]  B. Koch,et al.  A synthesis of multi-disciplinary research in precision agriculture: site-specific management zones in the semi-arid western Great Plains of the USA , 2008, Precision Agriculture.

[2]  R. Reich,et al.  Spatial Cross-Correlation of Bouteloua gracilis with Site Factors , 1995 .

[3]  L. Silva,et al.  Fertilidade do solo e nutrição de plantas , 2010 .

[4]  M. Uribe-Opazo,et al.  DETERMINATION OF MANAGEMENT ZONES FROM NORMALIZED AND STANDARDIZED EQUIVALENT PRODUTIVITY MAPS IN THE SOYBEAN CULTURE 1 , 2011 .

[5]  Rodrigo Ortega,et al.  Determination of management zones in corn (Zea mays L.) based on soil fertility , 2007 .

[6]  Zhou Shi,et al.  Delineation of site-specific management zones using fuzzy clustering analysis in a coastal saline land , 2007 .

[7]  Li Xiang,et al.  Delineation and Scale Effect of Precision Agriculture Management Zones Using Yield Monitor Data Over Four Years , 2007 .

[8]  Pierre Roudier,et al.  Management zone delineation using a modified watershed algorithm , 2008, Precision Agriculture.

[9]  F. Pimentel-Gomes,et al.  Estatística aplicada a experimentos agronômicos e florestais: exposição com exemplos e orientações para uso de aplicativos , 2002 .

[10]  P. Mielke,et al.  Permutation Methods: A Distance Function Approach , 2007 .

[11]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[12]  Lazaros S. Iliadis,et al.  An intelligent system employing an enhanced fuzzy c-means clustering model: Application in the case of forest fires , 2010 .

[13]  Miguel Angel Uribe-Opazo,et al.  Unidades de manejo a partir de mapas de produtividade normalizada e padronizada equivalente , 2011 .

[14]  David W. Franzen,et al.  Field Soil Sampling Density for Variable Rate Fertilization , 1995 .

[15]  Brigitte Charnomordic,et al.  A segmentation algorithm for the delineation of agricultural management zones , 2010 .

[16]  Brett Whelan,et al.  Establishing Management Classes for Broadacre Agricultural Production , 2007 .

[17]  Daniel Marçal de Queiroz,et al.  Geração de zonas de manejo para cafeicultura empregando-se sensor SPAD e análise foliar , 2011 .