Sampling Design of Soil Physical Properties in a Conilon Coffee Field

Santos, Eduardo Oliveira de Jesus; Gontijo, Ivoney; Silva, Marcelo Barreto da; Partelli, Fábio Luiz

doi:10.1590/18069657rbcs20160426

Cited by 8 publications

(5 citation statements)

References 37 publications

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“…Ceddia et al (2009) found low values of coefficient of variation for soil density and sand (<10%) and high values for silt and clay (>40%). Santos et al (2017) studied the physical attributes of a sandy textured Oxisol cultivated with conilon coffee and found a lower coefficient of variation for macropores (27.60%), total sand (8.72%), silt (18.43%), and clay (18.30%) when compared to the results obtained in our study, being the result of differences in the soil type found in the area. Carmo et al (2016), studying the quality of the beverage coffee as a function of soil color and attributes of an Ultisol (Argissolo Vermelho Amarelo, Brazilian Soil Classification System) from sandstone in the State of São Paulo, verified coefficients of variation for clay that ranged from 17 to 24%.…”

Section: Resultscontrasting

confidence: 56%

“…Souza et al (2006) investigated an optimum sampling density for the physical attributes in an Oxisol (Latossolo Vermelho eutroférrico, Brazilian Soil Classification System) under sugarcane cultivation by using the Cline (1944) formula and observed that higher number of samples are required to characterize Ds (9 points ha −1 ), TPV (49 points ha −1 ), microporosity (59 points ha −1 ), and macroporosity (131 points ha −1 ) on an ultra-detailed scale (1 ha). Santos et al (2017), using the same methodology for the study of sampling density in areas cultivated with conilon coffee in the State of Espírito Santo, found similar results regarding the number of samples needed to characterize Ds, MA, and clay content. Oliveira et al (2014) compared the sampling densities obtained from the range of the semivariogram and the formula proposed by Cline (1944) and observed a significant difference between sampling densities of both methodologies, with that proposed by Cline (1944) presenting the highest number of samples required (376 vs. 4 points ha −1 ).…”

Section: Attributementioning

confidence: 59%

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Sampling Density for Characterizing the Physical Quality of a Soil Under Coffee Cultivation in Southwestern Minas Gerais

et al. 2018

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The elaboration of maps to characterize the spatial variability of soil attributes assists in the strategic planning and decision making of agricultural managers. Precision and accuracy of maps are related to the ideal sampling density to characterize the variability pattern. This study was conducted with the aim of identifying the sampling density to represent the variability of soil physical quality using attributes with different magnitudes of variation in an area cultivated with coffee. Three approaches were used to find the most adequate sampling density (geostatistical analysis, percentage of error associated with the sampling density, and coefficient of variation). A total of 145 soil samples were collected at a depth of 0-0.20 m at the crossing points of a regular grid with a spacing of 50 m. The percentage of clay, silt, and sand, macroporosity, microporosity, total pore volume, and soil density were determined. The data were submitted to descriptive statistical analysis. For elaborating the variability maps with up to 15% error and soil attributes with a coefficient of variation close to 50%, a sampling density of 3 points ha −1 is suggested.

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Section: Resultscontrasting

confidence: 56%

Section: Attributementioning

confidence: 59%

Sampling Density for Characterizing the Physical Quality of a Soil Under Coffee Cultivation in Southwestern Minas Gerais

et al. 2018

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“…Soil sampling was done using Edelman auger at a depth of 0-0.20 m at five different points in a plot using the zigzag method [24] and bulked to make a composite sample. The composite samples from all plots were labeled, packed, and taken to the laboratory for analysis.…”

Section: Soil Sampling and Laboratory Analysismentioning

confidence: 99%

Lime, manure and Inorganic Fertilizer Effects on Soil Chemical Properties, Maize Yield and Profitability in Acidic Soils in Central Highlands of Kenya

Kimiti

Mucheru-Muna

Mugwe

et al. 2021

AJEE

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In Sub-Saharan Africa (SSA), acidic soil covers 29% of the total area. About 13% of the Kenyan total land area has acidic soils, widely distributed in croplands of the central and western Kenyan regions. The high soil acidity, coupled with soil nutrient depletion, negatively affects crop productivity in the region. We conducted an on-farm experiment to determine the effect of lime, manure, and phosphatic fertilizer application, either solely or combined, on soil chemical properties, maize yield, and profitability in acidic soils of Tharaka Nithi County, Kenya. The treatments were different rates of manure, lime, and P fertilizer. The experiment was designed as a randomized complete block design replicated ten times in farmer’s fields. Soil sampling was done at a depth of 0-20 cm prior to the start of the experiment, after crop harvest of SR2016 and LR2017 seasons. The samples were analyzed in the laboratory following standard methods. Results showed that lime significantly increased soil pH by 10.6% during the SR2016 and by 17.7% during the LR2017. Similarly, treatments with lime reduced exchangeable acidity and increased soil available P. Treatments with inorganic fertilizers had significantly higher maize grain yield in comparison with treatments with the sole application of lime, manure, and lime + manure. Lime + fertilizer + manure treatment gave the highest average maize grain yield (5.1 t ha−1), while control gave the lowest (1.5 t ha−1) during the LR2017 season. Economic returns were low due to the prevailing low rainfall experienced during the study period during the SR2016 season. Lime combined with inorganic fertilizer treatment recorded the highest returns (128.75 USD ha-1) followed by sole inorganic fertilizer (105.94 USD ha-1) during the LR2017 season. The study recommends a combination of both lime and inorganic fertilizer for enhanced maize production and profitability in Tharaka-Nithi County, Kenya.

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“…A elevada variabilidade de P (Figura 1) gerou um número impraticável de amostras simples para formar uma amostra composta representativa da unidade de amostragem, mesmo quando se aumentou o volume das amostras simples e se aceitou um desvio em torno da média de 20% (Tabela 2). Outro fato importante é que a amostragem de solo não é realizada separadamente para cada característica química, assim, a precisão final obtida após o processo de amostragem dependerá das características do solo analisadas, concordando com Santos et al (2017) e Rozane et al (2011).…”

Section: Yˆunclassified

“…Uma amostragem representativa é aquela que melhor caracteriza uma área de interesse, realizada por meio da coleta de um número de pontos que alia precisão na estimativa e minimiza o esforço (SANTOS et al, 2017). Assim, para que a amostragem seja eficiente e econômica, deve-se trabalhar com amostras simples e compostas de solo.…”

Section: Introductionunclassified

Representatividade da amostra de solo de acordo com o volume coletado em lavoura de café Arábica

2019

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Para a determinação da fertilidade do solo, uma característica das amostras simples comumente desprezada é o seu volume, que apresenta relação com o número de amostras coletadas para formar uma amostra composta representativa. O objetivo deste trabalho foi estabelecer a influência do volume das amostras simples na estimativa da variabilidade de características químicas do solo e estimar os desvios em torno da média, na coleta de 20 amostras simples com diferentes equipamentos, em um Latossolo Vermelho-Amarelo argiloso, cultivado com café arábica. Foram coletados cinco grupos de 30 amostras simples de solo, com os respectivos volumes: 80, 320, 720, 1.280 e 2.000 cm 3 , na camada de 0-20 cm, totalizando 150 amostras simples, nas quais foram determinados: pH, P, K, Ca 2+ , Mg 2+ e Al 3+. Foram selecionados modelos que explicassem a variação dos teores em função do volume das amostras de solo. Foram calculados os desvios tolerados em torno da média utilizando três equipamentos: trado, sonda e enxadão. O aumento no volume de solo coletado reduziu a variabilidade das características e, consequentemente, o número de amostras simples necessárias para formar uma amostra composta. O enxadão mostrou-se o equipamento de coleta mais eficiente, uma vez que proporciona maior representatividade da amostra composta formada. Palavras-chave: amostragem; fertilidade do solo; amostras simples; variabilidade. Soil sample representativy according to the volume collected in Arabica coffee Abstract For the determination of soil fertility, a characteristic of the commonly overlooked samples is their volume, which is related to the number of samples collected to form a representative composite sample. The objective of this work was to establish the influence of the volume of the simple samples in the estimation of the variability of chemical characteristics of the soil and to estimate the deviations around the average tolerated in the collection of 20 simple samples with different equipments in a clay Red-Yellow Latosol cultivated with arabica coffee. Five groups of 30 simple soil samples were collected, with the respective volumes: 80, 320, 720, 1,280 and 2,000 cm 3 , in the 0-20 cm layer, totaling 150 simple samples. In these samples pH, P, K, Ca 2+ , Mg 2+ and Al 3+ were determined. Models were selected that explained the variation of the contents as a function of the volume of the soil samples. Mean deviations around the mean were also calculated using three equipments: soil, probe and hoe. The increase in the volume of soil collected reduced the variability of the characteristics and consequently the number of simple samples needed to form a composite sample. The hoeing was the most efficient collection equipment, since it would provide greater representativeness of the formed composite sample.

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Sampling Design of Soil Physical Properties in a Conilon Coffee Field

Cited by 8 publications

References 37 publications

Sampling Density for Characterizing the Physical Quality of a Soil Under Coffee Cultivation in Southwestern Minas Gerais

Sampling Density for Characterizing the Physical Quality of a Soil Under Coffee Cultivation in Southwestern Minas Gerais

Lime, manure and Inorganic Fertilizer Effects on Soil Chemical Properties, Maize Yield and Profitability in Acidic Soils in Central Highlands of Kenya

Representatividade da amostra de solo de acordo com o volume coletado em lavoura de café Arábica

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