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

Bazzi, Cláudio Leones; Souza, Eduardo Godoy de; Uribe-Opazo, Miguel Ángel; Nóbrega, Lúcia Helena Pereira; Rocha, Davi Marcondes

doi:10.1590/s0100-69162013000500007

Cited by 36 publications

(34 citation statements)

References 10 publications

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“…Following the method proposed by Bazzi et al (2013) to identify the attributes used to generate the management zones, it was verified which variables had highest correlation with yield, ordering them according to the highest values of correlation, i.e., variables with highest correlation are better candidates to define management zones. Among the variables that showed correlation with each other, those with highest absolute correlation with yield were selected.…”

Section: Methodsmentioning

confidence: 99%

Management zones in coffee cultivation

Jacintho

Ferraz

Silva

et al. 2017

Rev. bras. eng. agríc. ambient.

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A B S T R A C TThis study aimed to apply precision agriculture techniques in coffee production, using correlation analysis in the definition of management zones. This work was carried out in a 22-ha area of coffee (Coffea arabica L.), cv. 'Topázio MG 1190' , which was sampled on a regular grid, using a topographic GPS, totaling 64 georeferenced samples (on average, 2.9 points per ha). Descriptive analysis was used in the data, followed by Pearson's correlation analysis at 0.05 significance between soil chemical attributes, agronomic characteristics of the plants and altitude. It was possible to verify the correlation of soil chemical attributes, agronomic characteristics of the plants and altitude with coffee yield. Altitude was the variable most correlated with coffee yield through correlation analysis. Therefore, it was chosen as the best variable to define management zones and thematic maps capable to support coffee farmers. Three maps were generated to characterize the area in two, three and four management zones. There was a direct influence on mean yield.Definição de zonas de manejo para cafeicultura R E S U M O Objetivou-se, com o presente estudo, aplicar técnicas de agricultura de precisão no cultivo do café utilizando análise de correlação na definição de zonas de manejo. O trabalho foi desenvolvido em uma área de 22 ha de lavoura de cafeeiro (Coffea arabica L.) da cultivar Topázio MG 1190. Demarcou-se na área em estudo e com a utilização de GPS topográfico, uma malha amostral regular totalizando 64 pontos amostrais georreferenciados (em média 2,9 pontos por ha). Utilizou-se o método de análise descritiva dos dados seguido da análise de correlação de Pearson a 0,05 de significância entre os atributos de solo, características agronômicas da planta e altitude. Foi possível verificar a correlação dos atributos do solo, das características agronômicas das plantas e da altitude com a produtividade. Através da análise de correlação observou-se que a altitude foi a variável que mais se correlacionou com a produtividade sendo, assim, selecionada como variável mais propícia para geração de zonas de manejo e de mapas temáticos capazes de auxiliar os cafeicultores. Foram gerados três mapas que caracterizam a área em duas, três e quatro zonas de manejo. Verificou-se que houve influência direta na média da produtividade.

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Section: Methodsmentioning

confidence: 99%

Management zones in coffee cultivation

Jacintho

Ferraz

Silva

et al. 2017

Rev. bras. eng. agríc. ambient.

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“…This enabled examination of the attributes that influenced the yield positively or negatively. After generating the spatial correlation matrix, the variables to be used in the generation of MZs were selected using the variable selection method proposed by Bazzi et al (2013): (a) elimination of variables with no significant spatial autocorrelation at 95% significance; (b) removal of the variables that were not correlated with yield; (c) decreasing ordination of the remaining variables, considering the degree of correlation with yield; and (d) elimination of variables which are correlated with each other, with preference to the withdrawal of those variables with lower correlation with yield.…”

Section: Methodsmentioning

confidence: 99%

“…The algorithm Fuzzy C-Means (BAZZI et al, 2013;LI et al, 2007;MORARI et al, 2009;MILNE et al, 2012;XIN-ZHONG et al, 2009) is a clustering method based on the fuzzy logic, defined by Zadeh (1965), which matches uncertainties associated with class and association boundaries (DOBERMANN et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Use of the farmer’s experience variable in the generation of management zones

Schenatto

Souza

Bazzi

et al. 2017

SCA

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In the spatial variability management of fields, the approach based on management zones (MZs) divides the area into sub-regions, which have spatially homogeneous topography and soil conditions. Such MZs should lead to the same potential yields. Farmers understand which areas of a field have high and low yields, and use of this knowledge may allow the identification of MZs in a field based on production history. The objective of the present study was to evaluate the application of farmer's experience to determine MZs. The study was conducted in three agricultural fields located in the west of the Paraná State in Brazil, and the MZs were generated considering three cases: a) without the use of the farmer's experience variable; b) with the variable of farmer's experience and the stable soil properties selected at the variable selection stage; and c) only with the farmer's experience variable. The generated MZs were evaluated using the Variance Reduction (VR) index, Fuzziness Performance Index (FPI), Modified Partition Entropy (MPE), Smooth Index (SI), and Analysis of Variance (ANOVA). The study showed that the use of farmer's experience to set MZs could be an efficient and simple tool, that it could reduce costs for the processes of setting MZs, compared to the traditional method of using stable soil variables and relief. Key words: Precision agriculture. Clustering. Farmer feeling. Management units. ResumoNo gerenciamento da variabilidade espacial das lavouras a abordagem baseada em zonas de manejo (ZMs) divide o talhão em sub-regiões, que apresentam topografia e condições do solo espacialmente homogêneas, de tal forma que tais ZMs devem conduzir aos mesmos resultados em potencial de rendimento das culturas. Os produtores têm experiência de quais áreas de um talhão apresentam altas e baixas produtividades e fazer uso dessa base de conhecimento pode permitir a identificação de ZMs em um campo com base no histórico de produção. O objetivo desse trabalho foi avaliar a eficiência de utilização da experiência do produtor na definição de ZMs. A pesquisa foi realizada em três áreas agrícolas localizadas na região Oeste do estado do Paraná/ Brasil e as ZMs foram geradas considerando

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“…Os critérios utilizados são a produtividade e os atributos químicos e físicos do solo, entre os quais a RSP e a textura. Os custos para dividir o campo em classes de manejo compensam, se houver diferenças na resposta agronômica entre elas e praticabilidade do manejo variável (Taylor et al, 2007;Bazzi et al, 2013).…”

Section: Introductionunclassified

Compactação de solo cultivado com cana-de-açúcar em Baía Formosa, Rio Grande do Norte

et al. 2016

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Soil compaction in a sugarcane field at Baía Formosa, Rio Grande do Norte, BrazilSoil compaction is one of the main constraints imposed to growth of sugar cane root system, with consequences as reduction on plant ability to absorb water and nutrients. In this context, this study had as objective to identify regions in the field with different compaction levels, allowing the adoption of site specific management. The work was carried out at the Green Valley Sugarcane Mill, in Baía Formosa, RN, Brazil. Soil penetration resistance (RSP) was used as indicative parameter of soil compaction, and was assessed in an area of 113.59 ha, divided in 12 sugarcane fields, where 113 georeferenced points were located. Determinations were made in the 0-10, 11-20, 21-30 and 31-40 cm depths, by means of a soil penetrometer with automatic data acquisition system. Data were analyzed through descriptive statistics and geostatistical tools, which were used for evaluating spatial dependence of variables and draw contour maps, after kriging interpolation. Contour maps show regions in the area with different soil compaction levels. Subsoiling may be avoided in 18.80% of the total area, mainly in the fields 45 and 48. In other regions subsoiling must be performed deeper than 40 cm.

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

Cited by 36 publications

References 10 publications

Management zones in coffee cultivation

Management zones in coffee cultivation

Use of the farmer’s experience variable in the generation of management zones

Compactação de solo cultivado com cana-de-açúcar em Baía Formosa, Rio Grande do Norte

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