scholarly journals Spatial variability of soil chemical properties after coffee tree removal

2009 ◽  
Vol 33 (5) ◽  
pp. 1507-1514 ◽  
Author(s):  
Sidney Rosa Vieira ◽  
Osvaldo Guedes Filho ◽  
Márcio Koiti Chiba ◽  
Heitor Cantarella

Assessing the spatial variability of soil chemical properties has become an important aspect of soil management strategies with a view to higher crop yields with minimal environmental degradation. This study was carried out at the Centro Experimental of the Instituto Agronomico, in Campinas, São Paulo, Brazil. The aim was to characterize the spatial variability of chemical properties of a Rhodic Hapludox on a recently bulldozer-cleaned area after over 30 years of coffee cultivation. Soil samples were collected in a 20 x 20 m grid with 36 sampling points across a 1 ha area in the layers 0.0-0.2 and 0.2-0.4 m to measure the following chemical properties: pH, organic matter, K+, P, Ca2+, Mg2+, potential acidity, NH4-N, and NO3-N. Descriptive statistics were applied to assess the central tendency and dispersion moments. Geostatistical methods were applied to evaluate and to model the spatial variability of variables by calculating semivariograms and kriging interpolation. Spatial dependence patterns defined by spherical model adjusted semivariograms were made for all cited soil properties. Moderate to strong degrees of spatial dependence were found between 31 and 60 m. It was still possible to map soil spatial variability properties in the layers 0-20 cm and 20-40 cm after plant removal with bulldozers.

Author(s):  
A. C. Santos ◽  
J. S. Lima ◽  
L. B. T. Oliveira ◽  
S. P. Silva Neto

<p>Objetivou-se com este trabalho avaliar a variabilidade espacial das características produtivas do pasto de <em>Brachiária brizantha</em> cv. Marandu em vertente, em função da fertilidade do solo. O experimento foi conduzido na fazenda da Escola de Medicina Veterinária e Zootecnia da Universidade Federal do Tocantins. Para a caracterização química do solo foi realizada amostragem em pontos da área onde a malha regular possui uma distância média de 2 m de um ponto a outro longitudinalmente e doze metros perpendicularmente, perfazendo um total de 160 pontos. A forrageira também foi coletada seguindo malha regular, porém, com distância média de quatro metros longitudinalmente e 12 m perpendicularmente, totalizando 80 amostras. As análises realizadas foram às seguintes: pH (CaCl<sub>2</sub>); (matéria orgânica, fósforo disponível (P) e potássio trocável (K<sup>+</sup>); cálcio trocável (Ca<sup>2+</sup>), magnésio trocável (Mg<sup>2+</sup>) e alumínio trocável (Al<sup>3+</sup>). Os dados de forragem e de solo foram submetidos à estatística descritiva e a hipótese de normalidade dos dados que foi verificada pelo teste de Kolmogorov-Smirnov. A produção do pasto apresentou baixa dependência espacial, ajustando-se ao modelo esférico para todas as variáveis analisadas. Os coeficientes de variação foram moderados. A produção de forragem foi maior nas posições de topo e pedimento, em contrapartida os atributos químicos do solo, com exceção do pH, foram mais baixos nestas posições. Os atributos químicos do solo, também apresentaram baixa dependência espacial e, com exceção do pH, todos os atributos ajustaram-se ao modelo esférico.</p><p align="center"><strong><em>Spatial variability of qualitative and quantitative characteristics of Marandú grass pasture in topossequence in Tocantins</em></strong><strong><em></em></strong></p><p><strong>Abstract</strong><strong>: </strong>The objective of this study was evaluating the spatial variability of the productive characteristics of pasture of Brachiaria brizantha cv. Marandu in front, depending on soil fertility. The experiment was conducted at farm School of Veterinary Medicine and Animal Science the Federal University of Tocantins. For the chemical characterization of soil sampling was conducted in area of points where the regular grid has an average distance of 2 m from one point to another along and perpendicular twelve meters, a total 160 points. The fodder was also collected following regular grid, however, with an average distance of four meters and along 12 m perpendicular, totaling 80 samples. The analyzes were as follows: pH (CaCl<sub>2</sub>); (Organic matter, available phosphorus (P) and exchangeable potassium (K<sup>+</sup>), exchangeable calcium (Ca<sup>2+</sup>), exchangeable magnesium (Mg<sup>2+</sup>) and exchangeable aluminum (Al<sup>3+</sup>). Data forage and soil were submitted to descriptive statistics and data normality hypothesis was verified using the Kolmogorov-Smirnov test. The production the pasture had low spatial dependence, setting the spherical model for all variables. The coefficients of variation were moderate. Forage production was higher in top positions and dismissal in return the soil chemical properties, except the pH, were lower in these positions. The soil chemical properties, also showed low spatial dependence and, with the exception of pH, all attributes set to spherical model.</p>


2021 ◽  
Vol 51 ◽  
Author(s):  
Diogo Neia Eberhardt ◽  
Robélio Leandro Marchão ◽  
Pedro Rodolfo Siqueira Vendrame ◽  
Marc Corbeels ◽  
Osvaldo Guedes Filho ◽  
...  

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.


2021 ◽  
Vol 29 ◽  
pp. 254-262
Author(s):  
João Luiz Jacintho ◽  
Gabriel Araújo e Silva Ferraz ◽  
Brenon Diennevan Souza Barbosa ◽  
Patrícia Ferreira Ponciano Ferraz ◽  
Sthéfany Airane dos Santos

Precision Agriculture techniques, such as the management of spatial variability of crop attributes, have been studied for several crops. However, few studies have been performed on Tifton 85 bermudagrass. Thus, this work aimed to analyse the spatial variability of chlorophyll content in a Tifton 85 bermudagrass production area, located in Seropédica, Brazil. A georeferenced grid was created to measure the chlorophyll content in two periods using a portable chlorophyll metre. Different geostatistical methods and models were evaluated in order to identify which had the best fit to analyze the spatial dependence of the chlorophyll content.The atribute was mapped based on interpolation by the ordinary kriging method. Therefore, kriging interpolation was used to create isoline maps, which were used to observe the spatial variability of the chlorophyll content. The methodology and maps generated proved to be of great value to the Tifton 85 bermudagrass producers.


Author(s):  
Sergio Salgado García ◽  
Joana Acopa Colorado ◽  
Sergio Salgado-Velázquez ◽  
Samuel Córdova Sánchez ◽  
David Palma López ◽  
...  

Objective: To evaluate the spatial variability of some chemical properties of a Cambisolsoil, in order to establish specific agronomic management zones for cocoa cultivation.Methodology: A sampling of 42 georeferenced points equidistant at 40 m was carriedout. Geostatistical variability maps were made with the results of the chemical analysisof the soil properties, using the ordinary Kriging interpolation technique.Results: It was found that the percentage of saturation of acidity (PSA), acidity and H+showed high variability; P-Olsen and interchangeable K, Ca and Mg displayed mediumvariability, and pH, MO, CIC and Al presented low variability. Soil properties pH, PSA;Exchangeable P-Olsen, Ca and Mg showed high spatial dependence (&lt;25%) and OM,exchangeable K and CIC moderate spatial dependence (25-75%).Study limitations / Implications: The generated maps allowed the identification ofpartial areas with different variability, as well as the direction of greatest variability of theproperty as a function of distance.Conclusions: With the maps, it was possible to make recommendations for agronomicmanagement depending on each specific management area.


2015 ◽  
Vol 39 (1) ◽  
pp. 31-39 ◽  
Author(s):  
Ivanildo Amorim de Oliveira ◽  
Milton César Costa Campos ◽  
José Marques Junior ◽  
Renato Eleotério de Aquino ◽  
Daniel de Bortoli Teixeira ◽  
...  

The lack of information concerning the variability of soil properties has been a major concern of researchers in the Amazon region. Thus, the aim of this study was to evaluate the spatial variability of soil chemical properties and determine minimal sampling density to characterize the variability of these properties in five environments located in the south of the State of Amazonas, Brazil. The five environments were archaeological dark earth (ADE), forest, pasture land, agroforestry operation, and sugarcane crop. Regular 70 × 70 m mesh grids were set up in these areas, with 64 sample points spaced at 10 m distance. Soil samples were collected at the 0.0-0.1 m depth. The chemical properties of pH in water, OM, P, K, Ca, Mg, H+Al, SB, CEC, and V were determined at these points. Data were analyzed by descriptive and geostatistical analyses. A large part of the data analyzed showed spatial dependence. Chemical properties were best fitted to the spherical model in almost all the environments evaluated, except for the sugarcane field with a better fit to the exponential model. ADE and sugarcane areas had greater heterogeneity of soil chemical properties, showing a greater range and higher sampling density; however, forest and agroforestry areas had less variability of chemical properties.


Author(s):  
G. S. Tagore ◽  
G. D. Bairagi ◽  
R. Sharma ◽  
P. K. Verma

A study was conducted to explore the spatial variability of major soil nutrients in a soybean grown region of Malwa plateau. From the study area, one hundred sixty two surface soil samples were collected by a random sampling strategy using GPS. Then soil physico-chemical properties i.e., pH, EC, organic carbon, soil available nutrients (N, P, K, S and Zn) were measured in laboratory. After data normalization, classical and geo-statistical analyses were used to describe soil properties and spatial correlation of soil characteristics. Spatial variability of soil physico-chemical properties was quantified through semi-variogram analysis and the respective surface maps were prepared through ordinary Kriging. Exponential model fits well with experimental semi-variogram of pH, EC, OC, available N, P, K, S and Zn. pH, EC, OC, N, P, and K has displayed moderate spatial dependence whereas S and Zn showed weak spatial dependence. Cross validation of kriged map shows that spatial prediction of soil nutrients using semi-variogram parameters is better than assuming mean of observed value for any un-sampled location. Therefore it is a suitable alternative method for accurate estimation of chemical properties of soil in un-sampled positions as compared to direct measurement which has time and costs concerned.


CATENA ◽  
2017 ◽  
Vol 154 ◽  
pp. 50-62 ◽  
Author(s):  
Igor Bogunovic ◽  
Sebastiano Trevisani ◽  
Miranda Seput ◽  
Darko Juzbasic ◽  
Boris Durdevic

Author(s):  
Ricardo N. Buss ◽  
Raimunda A. Silva ◽  
Glécio M. Siqueira ◽  
Jairo O. R. Leiva ◽  
Osmann C. C. Oliveira ◽  
...  

ABSTRACT The objective of this study was to evaluate the spatial variability of soybean yield, carbon stock, and soil physical attributes using multivariate and geostatistical techniques. The attributes were determined in Oxisols samples with clayey and cohesive textures collected from the municipality of Mata Roma, Maranhão state, Brazil. In the study area, 70 sampling points were demarcated, and soybean yield and soil attributes were evaluated at soil depths of 0-0.20 and 0.20-0.40 m. Data were analysed using multivariate analyses (principal component analysis, PCA) and geostatistical tools. The mean soybean yield was 3,370 kg ha-1. The semivariogram of productivity, organic carbon (OC), and carbon stock (Cst) at the 0-0.20 m layer were adjusted to the spherical model. The PCA explained 73.21% of the variance and covariance structure between productivity and soil attributes at the 0-0.20 m layer [(PCA 1 (26.89%), PCA 2 (24.10%), and PCA 3 (22.22%)] and 68.64% at the 0.20-0.40 m layer [PCA 1 (31.95%), PCA 2 (22.83%), and PCA 3 (13.85%)]. The spatial variability maps of the PCA eigenvalue scores showed that it is possible to determine management zones using PCA 1 in the two studied depths; however, with different management strategies for each of the layers in this study.


SpringerPlus ◽  
2015 ◽  
Vol 4 (1) ◽  
Author(s):  
Upendra M Sainju ◽  
Brett L Allen ◽  
Thecan Caesar-TonThat ◽  
Andrew W Lenssen

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