scholarly journals VARIABILIDADE ESPACIAL E CORRELAÇÃO DOS ATRIBUTOS DO SOLO COM PRODUTIVIDADE DO MILHO E DA SOJA

Nativa ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 536-543
Author(s):  
Evandro Gelain ◽  
Eduardo Leonel Bottega ◽  
Anamari Viegas de Araujo Motomiya ◽  
Zanandra Boff de Oliveira
Keyword(s):  
Decision Making ◽  
Zea Mays ◽  
Glycine Max ◽  
Spatial Variability ◽  
Spatial Dependence ◽  
Soil Samples ◽  
Geostatistical Analysis ◽  
Sample Point ◽  
Iron And Zinc ◽  
Potential Acidity

O emprego de técnicas de agricultura de precisão, associadas a análises geoestatísticas, possibilita mapear a variabilidade espacial existente em um campo de produção. O conhecimento da variabilidade é importante ferramenta na tomada de decisões quanto ao manejo da área, uma vez que possibilita que este seja realizado de forma localizada. O estudo foi realizado em um talhão da Fazenda Planalto, localizada no município de Maracaju – MS, com o objetivo de avaliar a variabilidade espacial e correlação entre os atributos químicos e granulométricos do solo e a produtividade do milho e da soja. Foi utilizada uma grade amostral contendo 187 pontos, utilizando-se 10 amostras simples de solo por ponto amostral. Não foi detectado dependência espacial para o cálcio, alumínio, acidez potencial, soma de bases, ferro e zinco. As melhores estimativas em locais não amostrados foram obtidos para a areia e argila. A produtividade da soja apresentou forte dependência espacial e se correlacionou positivamente de forma forte com o fósforo e moderada com o magnésio. Palavras-chave: Latossolo; dependência espacial; Glycine max; Zea mays.   Spatial variability and correlation of chemicals and physical soil attributes with corn and soybean yield   ABSTRACT: The use of precision farming techniques, associated with geostatistical analysis, makes it possible to map the spatial variability in a production field. The knowledge of variability is an important tool in decision making regarding the management of the area, since it allows it to be carried out in a localized manner. The study was carried out in a plot of Fazenda Planalto, located in the municipality of Maracaju - MS, with the objective of evaluating the spatial variability and correlation between the chemical and granulometric attributes of the soil and the corn and soybeans yield. A sampling grid containing 187 points was used, using 10 simple soil samples per sample point. No spatial dependence was detected for calcium, aluminum, potential acidity, sum of bases, iron and zinc. The best estimates in unsampled locations were obtained for sand and clay. The soybeans yield showed strong spatial dependence and was positively correlated strongly with phosphorus and moderately with magnesium. Keywords: Oxisol; spatial dependence; Glycine max; Zea mays.

Soybean Injury from Triazine Residues in Soil

Weed Science ◽  
1969 ◽  
Vol 17 (1) ◽  
pp. 35-36 ◽  
Author(s):  
Rodney J. Fink ◽  
O. Hale Fletchall
Keyword(s):  
Zea Mays ◽  
Glycine Max ◽  
Soil Samples ◽  
Herbicide Treatment ◽  
Forage Yields

Plots were planted to corn (Zea mays L., var. Mo. 880) and treated with 0, 2.5, 5.0, and 10 lb/A of 2-chloro-4-ethylamino-6-isopropylamino-s-triazine (atrazine) or 2-chloro-4,6-bis(ethylamino)-s-triazine (simazine) in 1964 and in 1965. Soybean (Glycine max L., var. Clark 63) forage yields from soil samples collected in the spring, 1 year after application, were not affected by treatments of 5.0 lb/A or less of atrazine. Yields were reduced on soils collected in the fall (6 months) after application. Following 2 years of treatment, substantial reductions in yields of soybean forage occurred. Soybeans planted in the field following 2 consecutive years of herbicide treatment, yielded similarly to the control plots except when rates of 10 lb/A had been applied.

scholarly journals Spatial variability and sampling density of chemical attributes in archaeological black earths under pasture in southern Amazonas, Brazil

2019 ◽  
Author(s):  
Alan F. L. de Lima ◽  
Milton C. C. Campos ◽  
José M. da Cunha ◽  
Laércio S. Silva ◽  
Flávio P. de Oliveira ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Spatial Dependence ◽  
Spatial Behavior ◽  
Dependence Structure ◽  
Sampling Efficiency ◽  
Sampling Density ◽  
Agricultural Planning ◽  
Chemical Attributes ◽  
Spatial Dependence Structure ◽  
Potential Acidity

Abstract. Spatial mapping of soil chemical attributes is essential for sampling efficiency and agricultural planning management, ensuring a regional development and sustainability of the unique characteristics of archaeological black earths (ABEs). Thus, this study was developed aiming at assessing the spatial variability and sampling density of chemical attributes in soils of ABEs under pasture in southern Amazonas, Brazil. A sampling grid of 56 × 80 m with regular spacings of 8 m was installed in the experimental area and samples were taken from the crossing points at depths of 0.0–0.05, 0.05–0.10, and 0.10–0.20 m, totaling 264 georeferenced points. The chemical attributes pH in water, organic carbon, Ca, Mg, K, P, Al, and potential acidity were determined in these samples, while CEC, SB, V, t, T, and m were calculated. The attributes present a spatial dependence varying from strong to moderate, being Al3+ the only chemical attribute that does not present a spatial dependence structure in the assessed depths. Scaled semivariograms satisfactorily reproduce the spatial behavior of attributes in the same pattern of individual semivariograms, allowing their use to estimate the variability of soil attributes. Sampling density is higher at a depth of 0.0–0.05 m, requiring 2 and 1 point ha−1 at depths of 0.05–0.10 and 0.10–0.20 m, respectively, to represent the spatial pattern of chemical attributes.

scholarly journals Escala de independencia espacial de la mesofauna edáfica en un transecto bosque-pastizal del Jardín Botánico “Francisco Javier Clavijero”

2011 ◽  
Vol 27 (1) ◽  
Author(s):  
Diana Marcela Rueda ◽  
Simoneta Negrete Yankelevich ◽  
Carlos Fragoso González
Keyword(s):  
Spatial Patterns ◽  
Spatial Dependence ◽  
Soil Samples ◽  
Geostatistical Analysis ◽  
Sampling Intensity

In order to evaluate the scale of spatial patterns in edaphic mesofauna in a pasture-forest gradient, a collection of soil samples was obtained from a transect, followed by faunal extraction, counting and sorting. Only Sternorrhyncha (except Coccidae) and Coccidae geostatistical analysis showed spatial dependence within the scale 25-500 cm. Results suggest a revision of the current methods of soilfauna sampling, in which sampling intensity and intervals could be optimized for each taxon.

scholarly journals Geostatistical Analysis of the Permeability Coefficient in Different Soil Textures

2018 ◽  
Vol 67 (2) ◽  
pp. 119-124 ◽  
Author(s):  
Lida Issazadeh ◽  
Mustafa Ismail Umar ◽  
Said I.A. Al-Sulaivany ◽  
Jian Hassanpour
Keyword(s):  
Spatial Variability ◽  
Permeability Coefficient ◽  
Soil Samples ◽  
Geostatistical Analysis ◽  
Soil Parameters ◽  
Kurdistan Region ◽  
Soil Permeability ◽  
Interpolation Methods ◽  
Soil Hydraulic ◽  
Irrigation Drainage

Summary Estimating soil hydraulic properties are so important for hydrological modeling, designing irrigation-drainage systems and soil transmission of soluble salts and pollutants, although measurements of such parameters have been found costly and time-consuming. Owing to a high spatial variability of soil hydraulic characteristics, a large number of soil samples are required for proper analysis. Nowadays, geostatistical methods are used to estimate soil parameters on the basis of limited data. The purpose of this research is to investigate the spatial variability of the permeability coefficient in different soil textures (26 soil samples) found in the Kurdistan region of Iraq. The parameter values obtained indicated a normal trend in particle size distribution, whereas the values of permeability coefficient showed aberrant distribution patterns. Geostatistical analysis results indicated the best fitted theoretical model was Gaussian model and the proportion of sill/(sill + nugget) was 0.17 indicated strong spatial dependency of soil permeability. Furthermore, the optimal distance for estimating the soil permeability coefficient was 109,119 meters. A comparison of the kriging and IDW interpolation methods showed that both methods can estimate soil permeability with high accuracy and less error. The prediction maps of the applied methods indicated that high soil permeability rates were recorded in the south-east of the Kurdistan region of Iraq compared to low soil permeability rates recorded in the remainder of this region. It is recommended other interpolation methods such as co-kriging and indicator or simple kriging methods could be used to simulate data in large scale areas as well.

VARIABILIDADE ESPACIAL DE ATRIBUTOS QUÍMICOS EM UM LATOSSOLO VERMELHO AMARELO SOB CULTIVO COM GOIABA (Psidium guajava L.)

2017 ◽  
Vol 32 (1) ◽  
pp. 96
Author(s):  
José Marcílio Da Silva ◽  
Lucas Figueira Da Silva ◽  
Daniel Rosendo Da Silva Sobrinho ◽  
João Pedro Figueira Da Silva
Keyword(s):  
Spatial Variability ◽  
Spatial Dependence ◽  
Soil Management ◽  
Theoretical Models ◽  
Psidium Guajava ◽  
Geostatistical Analysis ◽  
Regular Grid ◽  
Semivariogram Model ◽  
Chemical Attributes ◽  
Geostatistics Analysis

O objetivo do trabalho foi avaliar a variabilidade espacial de atributos químicos do solo sob cultivo com goiaba por meio da análise de geoestatística nas profundidades de 0,0-0,10 m e 0,10-0,20 m. Foi realizado amostragem regionalizada utilizando malha regular com dimensão de 50 m x 50 m, totalizando 36 pontos georreferenciado equidistantes 10 m. A análise geoestatística foi utilizada para a determinação de modelos teóricos de variogramas e para a interpolação por krigagem dos dados que foram gerados, a fim de analisar a variabilidade espacial dos atributos dos solos. O pH apresentou variabilidade espacial baixa nas duas profundidades e o Al na profundidade de 0,10-0,20 m com moderada variabilidade espacial na profundidade de 0,0-0,10 m. O Ca e Mg apresentaram moderada  variabilidade espacial nas duas profundidades. O modelo esférico de semivariograma foi ajustado para todos atributos nas duas profundidades, com alcances variando entre 12,5 m e 24,1 m para os atributos pH e Al, respectivamente.PALAVRAS-CHAVE: Geoestatística, manejo do solo, dependência espacial, krigagem. SPATIAL VARIABILITY OF THE CHEMICAL ATTRIBUTES IN A RED-YELLOW LATOSOL UNDER CULTIVATION CONTINUOUSABSTRACT: The objective of the work was to evaluate the spatial variability of soil chemical attributes under cultivation with guava through geostatistics analysis in the depths of 0.0-0.10 m and 0.10-0.20 m. Sampling was performed regionalized using regular grid with dimension of 50 m x 50 m, totaling 36 georeferenced points equidistant 10 m. The geostatistical analysis was applied to determine theoretical models of variograms and interpolation kriging of the data that have been generated in order to analyze the spatial variability of the soil attributes. The pH presented low spatial variability on both depths and Al on depth 0.10-0.20 m with moderate spatial variability on the depth 0.0-0.10 m. Ca and Mg showed moderate spatial variability in both depths. The spherical semivariogram model was adjusted for all attributes in both depths, close to 12.5 m and 24.1 m for pH and Al, respectively.KEYWORDS: Geostatistics; soil management; spatial dependence, kriging.

scholarly journals Spatial variability of the horizontal structure and production of biomass in Massai grass in an agropastoral system

2021 ◽  
Vol 16 (3) ◽  
pp. 238-244
Author(s):  
Carlos Henrique Batista ◽  
Otacílio Silveira Júnior ◽  
Ítalo Cordeiro Silva Lima ◽  
José Alberto Ferreira Cardoso ◽  
Rossini Sôffa da Cruz ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Spatial Dependence ◽  
Structural Characteristics ◽  
Management Plan ◽  
High Variability ◽  
Geostatistical Analysis ◽  
Descriptive Statistics ◽  
Horizontal Structure ◽  
Degraded Pasture ◽  
Recovery Management

In Brazil, 60% to 80% of cultivated pastures show some degradation level. Thus, the objective was to evaluate the variability of the horizontal structure and biomass of Massai grass in an agropastoral system as a diagnosis of degraded pasture. We performed the georeferencing in a 12m × 13m mesh, totaling 48 sampling stations, and evaluated grass's biomass and structural characteristics at each station. We submitted the data to descriptive statistics and geostatistical analysis. We observed a process of degradation of pasture in the experimental area. Under these conditions, most of the characteristics of the pasture's horizontal structure and the production of biomass showed spatial dependence with high variability. Geostatistics efficiently represented and understood the variability of the studied attributes, enabling developing a specific pasture recovery management plan.

Influence of phosphate status on phosphate uptake kinetics of maize (Zea mays) and soybean (Glycine max)

1990 ◽  
Vol 124 (2) ◽  
pp. 175-182 ◽  
Author(s):  
A. Jungk ◽  
C. J. Asher ◽  
D. G. Edwards ◽  
D. Meyer
Keyword(s):  
Zea Mays ◽  
Glycine Max ◽  
Phosphate Uptake ◽  
Uptake Kinetics ◽  
Kinetics Of

scholarly journals Spatial variability and mapping of soil fertility status in a high-potential smallholder farming area under sub-humid conditions in Zimbabwe

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Gabriel Soropa ◽  
Olton M. Mbisva ◽  
Justice Nyamangara ◽  
Ermson Z. Nyakatawa ◽  
Newton Nyapwere ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Soil Ph ◽  
Strong Evidence ◽  
Spatial Dependence ◽  
Random Component ◽  
Smallholder Farming ◽  
Mineral N ◽  
Spatial Trend ◽  
Spatial Trends

AbstractA study was conducted to examine spatial variability of soil properties related to fertility in maize fields across varying soil types in ward 10 of Hurungwe district, Zimbabwe; a smallholder farming area with sub-humid conditions and high yield potential. Purposively collected and geo-referenced soil samples were analyzed for texture, pH, soil organic carbon (OC), mineral N, bicarbonate P, and exchangeable K. Linear mixed model was used to analyze spatial variation of the data. The model allowed prediction of soil properties at unsampled sites by the empirical best linear unbiased predictor (EBLUP). Evidence for spatial dependence in the random component of the model was evaluated by calculating Akaike’s information criterion. Soil pH ranged from 4.0 to 6.9 and showed a strong spatial trend increasing from north to south, strong evidence for a difference between the home and outfields with homefields significantly higher and between soil textural classes with the sand clay loam fraction generally higher. Soil OC ranged from 0.2 to 2.02% and showed no spatial trend, but there was strong evidence for a difference between home and outfields, with mean soil OC in homefields significantly larger, and between soil textural classes, with soil OC largest in the sandy clay loams. Both soil pH and OC showed evidence for spatial dependence in the random effect, providing a basis for spatial prediction by the EBLUP, which was presented as a map. There were significant spatial trends in mineral N, available P and exchangeable K, all increasing from north to south; significant differences between homefields and outfields (larger concentrations in homefields), and differences between the soil textural classes with larger concentrations in the sandy clay loams. However, there was no evidence for spatial dependence in the random component, so no attempt was made to map these variables. These results show how management (home fields vs outfields), basic soil properties (texture) and other factors emerging as spatial trends influence key soil properties that determine soil fertility in these conditions. This implies that the best management practices may vary spatially, and that site-specific management is a desirable goal in conditions such as those which apply in Ward 10 of Hurungwe district in Zimbabwe.

Effect of Savanna windrow wood burning on the spatial variability of soil properties

2021 ◽  
Vol 51 ◽  
Author(s):  
Diogo Neia Eberhardt ◽  
Robélio Leandro Marchão ◽  
Pedro Rodolfo Siqueira Vendrame ◽  
Marc Corbeels ◽  
Osvaldo Guedes Filho ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Spatial Variability ◽  
Spatial Dependence ◽  
Chemical Properties ◽  
Spatial Arrangement ◽  
Nugget Effect ◽  
Tropical Savannas ◽  
Geostatistical Methods ◽  
Exchangeable Ca ◽  
Spherical Models

ABSTRACT Tropical Savannas cover an area of approximately 1.9 billion hectares around the word and are subject to regular fires every 1 to 4 years. This study aimed to evaluate the influence of burning windrow wood from Cerrado (Brazilian Savanna) deforestation on the spatial variability of soil chemical properties, in the field. The data were analysed by using geostatistical methods. The semivariograms for pH(H2O), pH(CaCl2), Ca, Mg and K were calculated according to spherical models, whereas the phosphorus showed a nugget effect. The cross semi-variograms showed correlations between pH(H2O) and pH(CaCl2) with other variables with spatial dependence (exchangeable Ca and Mg and available K). The spatial variability maps for the pH(H2O), pH(CaCl2), Ca, Mg and K concentrations also showed similar patterns of spatial variability, indicating that burning the vegetation after deforestation caused a well-defined spatial arrangement. Even after 20 years of use with agriculture, the spatial distribution of pH(H2O), pH(CaCl2), Ca, Mg and available K was affected by the wood windrow burning that took place during the initial deforestation.

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