Delineating productivity zones on claypan soil fields using apparent soil electrical conductivity

Kitchen, Newell R.; Sudduth, K. A.; Myers, D. Brenton; Drummond, S. T.; Hong, Soon-Jung

doi:10.1016/j.compag.2004.11.012

Cited by 161 publications

(118 citation statements)

References 26 publications

Supporting

Mentioning

101

Contrasting

Unclassified

Order By: Relevance

“…To analyze the agreement between the management zones and the soil properties, cross-tabulation between each management zone map and each soil property map with the same number of classes was performed (Kitchen et al, 2005). Thus, tabulations were performed between six maps of management zones and 22 soil property maps.…”

Section: Analytical Methods For Comparing the Class Map With The Soil mentioning

confidence: 99%

“…The Hungarian algorithm for combinatorial optimization was used in this reclassification. After reclassifying the management zone map and calculating the confusion matrix, the kappa coefficient was obtained (Kitchen et al, 2005;Valckx et al, 2009). The kappa coefficient indicates the superiority of the reclassification over a random classification.…”

Section: Analytical Methods For Comparing the Class Map With The Soil mentioning

confidence: 99%

“…The kappa coefficient indicates the superiority of the reclassification over a random classification. According to Kitchen et al (2005), the highest kappa coefficient between the two ratings occurs when the correlation is maximized. Thus, one considered the classes of soil properties to be the true data and the management zone map to be the classifier.…”

Section: Analytical Methods For Comparing the Class Map With The Soil mentioning

confidence: 99%

See 2 more Smart Citations

Definition of management zones in coffee production fields based on apparent soil electrical conductivity

Valente¹,

Queiroz²,

Pinto³

et al. 2012

Sci. agric. (Piracicaba, Braz.)

View full text Add to dashboard Cite

Fertilizer application at variable rates requires dense sampling to determine the resulting field spatial variability. Defining management zones is a technique that facilitates the variable-rate application of agricultural inputs. The apparent electrical conductivity of the soil is an important factor in explaining the variability of soil physical-chemical properties. Thus, the objective of this study was to define management zones for coffee (Coffea Arabica L.) production fields based on spatial variability of the apparent electrical conductivity of the soil. The resistivity method was used to measure the apparent soil electrical conductivity. Soil samples were collected to measure the chemical and physical soil properties. The maps of spatial variability were generated using ordinary kriging method. The fuzzy k-means algorithm was used to delimit the management zones. To analyze the agreement between the management zones and the soil properties, the kappa coefficients were calculated. The best results were obtained for the management zones defined using the apparent electrical conductivity of the soil and the digital elevation model. In this case, the kappa coefficient was 0.45 for potassium, which is an element that is associated with quality coffee. The other variable that had a high kappa coefficient was remaining phosphorous; the coefficient obtained was 0.49. The remaining phosphorus is an important parameter for determining which fertilizers and soil types to study.

show abstract

Section: Analytical Methods For Comparing the Class Map With The Soil mentioning

confidence: 99%

Section: Analytical Methods For Comparing the Class Map With The Soil mentioning

confidence: 99%

Section: Analytical Methods For Comparing the Class Map With The Soil mentioning

confidence: 99%

See 1 more Smart Citation

Definition of management zones in coffee production fields based on apparent soil electrical conductivity

Valente¹,

Queiroz²,

Pinto³

et al. 2012

Sci. agric. (Piracicaba, Braz.)

View full text Add to dashboard Cite

show abstract

“…Ferguson et al(2003) compared management zones based on slope and surface soil texture with those based on soil EC, and concluded that the management zones based on easily obtained soil EC measurements were preferable and had the potential for use in the site-specific management of nitrification inhibitors. Kitchen et al(2005) concluded that EC and elevation measurements could be reliably used for creating management zones on claypan soil fields.…”

Section: Introductionmentioning

confidence: 99%

Determination of potential management zones from soil electrical conductivity, yield and crop data

Shi

et al. 2008

J. Zhejiang Univ. Sci. B

View full text Add to dashboard Cite

Abstract:One approach to apply precision agriculture to optimize crop production and environmental quality is identifying management zones. In this paper, the variables of soil electrical conductivity (EC) data, cotton yield data and normalized difference vegetation index (NDVI) data in an about 15 ha field in a coastal saline land were selected as data resources, and their spatial variabilities were firstly analyzed and spatial distribution maps constructed with geostatistics technique. Then fuzzy c-means clustering algorithm was used to define management zones, fuzzy performance index (FPI) and normalized classification entropy (NCE) were used to determine the optimal cluster numbers. Finally one-way variance analysis was performed on 224 georeferenced soil and yield sampling points to assess how well the defined management zones reflected the soil properties and productivity level. The results reveal that the optimal number of management zones for the present study area was 3 and the defined management zones provided a better description of soil properties and yield variation. Statistical analyses indicate significant differences between the chemical properties of soil samples and crop yield in each management zone, and management zone 3 presented the highest nutrient level and potential crop productivity, whereas management zone 1 the lowest. Based on these findings, we conclude that fuzzy c-means clustering approach can be used to delineate management zones by using the given three variables in the coastal saline soils, and the defined management zones form an objective basis for targeting soil samples for nutrient analysis and development of site-specific application strategies.

show abstract

“…In spatial variability management of fields, the approach based on management zones (MZs) divides the plot into sub-regions, which have topography and soil conditions spatially homogeneous (FLEMING et al, 2004;MORAL et al, 2011;XIN-ZHONG et al, 2009). Such MZs should lead to the same results, such as potential crop yields, allowing a single nutrient input rate in each sub-region (DIACONO et al, 2012;KITCHEN et al, 2005;MILNE et al, 2012;SCHEPERS et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

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

Schenatto

Souza

Bazzi

et al. 2017

SCA

View full text Add to dashboard Cite

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

show abstract

Delineating productivity zones on claypan soil fields using apparent soil electrical conductivity

Cited by 161 publications

References 26 publications

Definition of management zones in coffee production fields based on apparent soil electrical conductivity

Definition of management zones in coffee production fields based on apparent soil electrical conductivity

Determination of potential management zones from soil electrical conductivity, yield and crop data

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

Contact Info

Product

Resources

About