GPS receivers for georeferencing of spatial variability of soil attributes

Rosalen, David Luciano; Rodrigues, Marcos Sales; Chioderoli, Carlos Alessandro; Brandão, Flávia Janaína Carvalho; Siqueira, Diego Silva

doi:10.1590/s0100-69162011000600013

Cited by 8 publications

(6 citation statements)

References 12 publications

(12 reference statements)

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“…In a certain way, these results are similar to those found for this study, in which there is also a variation in the accuracy of GPS receivers to carry out samplings of RP and WC, which may come to influence future soil operations in rates variables, under or overestimating the compacted layers scattered around the area. When ROSALEN et al (2011) studied the GPS receivers for the georeferencing of soil attributes spatial variability, they found spherical models using navigation and geodetic GPS for the resistance to penetration and exponential, using the same receivers for the WC in layers of 0-0.10m, these results are different from this study in which the navigation receivers showed e xponential and Gaussian model for the navigation GPS in relation to the RP.…”

Section: Resultscontrasting

confidence: 84%

Variations on the expertise of two attributes of physical soil due to differences in the method of global satellite navigation

et al. 2016

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ABSTRACT:The mechanical resistance to penetration when related to the water content is an indicator often used of soil compaction, the use of positioning methods for greater accuracy of this review is important. In this context, this study aimed to determine the variability of positioning methods provided by GPS receivers to determine the spatial behavior of physical attributes related to soil compaction. The study area is located in the municipality of Jaboticabal, around the latitude 21º15'22"S and longitude 48º18'58"W, being characterized with a clayey Oxisol. The variables used as parameters of soil physical properties were the mechanical resistance to penetration and water content, using a sampling grid of 20 x 20 m, totaling 60 points. We used six models of GPS receivers: Garmin Etrex Vista, Garmin Etrex 30, Ashtech MM6, Trimble Nomad, Garmin Map 62 and Trimble R6, with all georeferenced points in the regular grid intersections. The georeferencing using GPS receivers (single point positioning and post-processed differential correction) interfered in characterizing the spatial variability of soil resistance to penetration, differently for some receivers to the water content attribute. Positioning methods with post-processed differential correction, using R6 and MM6 models, better define the management zones of soil resistance to penetration.

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Section: Resultscontrasting

confidence: 84%

Variations on the expertise of two attributes of physical soil due to differences in the method of global satellite navigation

et al. 2016

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“…Several types of information have been used to delineate management zones, such as: terrain attributes, electrical conductivity, soil resistance to penetration, chemical soil attributes, crop indices like NDVI (Normalized Difference Vegetation Index ), and crop yield maps (FRAISSE et al, 2001;JIANG et al, 2011;ROSALEN et al, 2011;DELALIBERA et al, 2012). Among these types of information, some studies in Brazil (MOLIN, 2002;AMADO et al, 2007) have defined management zones based on yield maps from data collected over time.…”

Section: Introductionmentioning

confidence: 99%

Management zones using fuzzy clustering based on spatial-temporal variability of soil and corn yield

Rodrigues

Corá

2015

Eng. Agríc.

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Clustering soil and crop data can be used as a basis for the definition of management zones because the data are grouped into clusters based on the similar interaction of these variables. Therefore, the objective of this study was to identify management zones using fuzzy c-means clustering analysis based on the spatial and temporal variability of soil attributes and corn yield. The study site (18 by 250-m in size) was located in Jaboticabal, São Paulo/Brazil. Corn yield was measured in one hundred 4.5 by 10-m cells along four parallel transects (25 observations per transect) over five growing seasons between 2001 and 2010. Soil chemical and physical attributes were measured. SAS procedure MIXED was used to identify which variable(s) most influenced the spatial variability of corn yield over the five study years. Basis saturation (BS) was the variable that better related to corn yield, thus, semivariograms models were fitted for BS and corn yield and then, data values were krigged. Management Zone Analyst software was used to carry out the fuzzy cmeans clustering algorithm. The optimum number of management zones can change over time, as well as the degree of agreement between the BS and corn yield management zone maps. Thus, it is very important take into account the temporal variability of crop yield and soil attributes to delineate management zones accurately.KEYWORDS: management zone analyst, precision agriculture, soil pH, tropical soils, Zea mays L. ALGORITMO DE AGRUPAMENTO 'FUZZY' PARA DEFINIÇÃO DE ZONAS DE MANEJO COM BASE NA VARIABILIDADE ESPAÇO-TEMPORAL DOS ATRIBUTOS DO SOLO E DA PRODUTIVIDADE DE MILHORESUMO: O agrupamento de dados de solo e de plantas pode ser utilizado para definir zonas de manejo. O objetivo do estudo foi identificar zonas de manejo usando o algorit mo de grupamento fuzzy c-means com base na variabilidade espacial e temporal dos atributos do solo e da produtividade de milho (PM). A área de estudo (18 por 250 m) está localizada em Jaboticabal-SP. A produtividade de milho foi medida em 100 células amostrais de 4,5 x 10 m, dispostas em quatro transectos (25 pontos por transecto), em cinco anos agrícolas, no período de 2001 a 2010. O procedimento MIXED do SAS foi utilizado para identificar quais variáveis mais influenciaram a variabilidade espacial da PM ao longo dos cinco anos de estudo. A saturação por bases (V) foi a variável que melhor se relacionou com a PM; portanto, modelos de semivariogramas foram ajustados aos dados destas variáveis e, posteriormente, interpolados pelo método da krigagem. O software Management Zone Analyst foi utilizado para realizar o agrupamento com o algor itmo fuzzy c-means. O número ótimo de zonas de manejo alterara-se ao longo do tempo, assim como o grau de similaridade espacial entre as zonas de manejo de V e da PM. Portanto, é de fundamental importância levar em consideração a variabilidade temporal da produtividade das culturas e dos atributos do solo para obter zonas de manejo com maior acurácia.

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“…Essa variabilidade pode ser ocasionada por diversos fatores, desde a forma de preparo do solo até a heterogeneidade do próprio material de origem (Cavalcante et al, 2007;Dalchiavon et al, 2012). O advento do Sistema de Posicionamento Global (GPS) e a utilização de técnicas geoestatíticas tornam possível a compreensão da variabilidade espacial das características do solo e das plantas possibilitando a partir de dados amostrados, inferir valores a pontos intermediários utilizando-se as técnicas do semivariograma e da interpolação (Rosalen et al, 2011).…”

Section: Introductionunclassified

Fertilidade do solo na qualidade fisiológica de sementes de soja

Mattioni

Schuch

Villela

et al. 2013

Agraria

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RESUMOO objetivo deste trabalho foi estudar, através de ferramentas da agricultura de precisão, a variabilidade da fertilidade do solo em campos de produção de sementes de soja e o efeito na qualidade fisiológica das sementes produzidas. Inicialmente, foi estabelecido um grid de amostragem de 1 ponto por hectare onde foram realizadas as coletas de amostras de solo e de sementes. No solo foram determinados teores de fósforo (P), potássio (K), cálcio (Ca), magnésio (Mg), matéria orgânica (%), argila (%), saturação de bases (%), saturação por alumínio (%), pH em água e CTC efetiva (CTC). Realizou-se a avaliação da qualidade fisiológica das sementes por meio dos testes de germinação, primeira contagem da germinação, envelhecimento acelerado e emergência de plântulas. A partir dos dados obtidos foram gerados os mapas de interpolação e a análise de correlação entre os fatores estudados. Observou-se a existência de variabilidade espacial em diferentes intensidades para os atributos químicos do solo avaliados e a qualidade fisiológica das sementes produzidas. Além disto, o incremento de Ca e da CTC efetiva contribui positivamente para a germinação de sementes de soja, enquanto a saturação por Al do solo afeta negativamente o vigor. Palavras-chave: agricultura de precisão, Glycine max (L.) Merrill, qualidade de sementes Soil fertility on the physiological quality of soybean seeds ABSTRACTThis study aimed to determine the variability of soil fertility in the fields of seed production and its effect on seed physiological quality of soybean seeds by precision agriculture tools. A sampling grid of 1 point per hectare was established, where soil and seed samples were collected. In soil samples were determined the concentrations of phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), organic matter (%), clay contents (%), bases saturation (%), aluminum saturation (%), pH and cation exchange capacity (CEC). Seed quality was evaluated by germination test, first count of germination, accelerated aging and seedling emergence. From the obtained data, interpolation maps were created, besides correlation analysis among the factors studied. Soil properties evaluated, as well as the seed physiological quality showed spatial variability at different concentrations. Furthermore, the increase of Ca and effective CEC positively affect the germination of soybean seeds, while Al saturation of the soil adversely affects the soybean seeds vigor.

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GPS receivers for georeferencing of spatial variability of soil attributes

Cited by 8 publications

References 12 publications

Variations on the expertise of two attributes of physical soil due to differences in the method of global satellite navigation

Variations on the expertise of two attributes of physical soil due to differences in the method of global satellite navigation

Management zones using fuzzy clustering based on spatial-temporal variability of soil and corn yield

Fertilidade do solo na qualidade fisiológica de sementes de soja

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