MÉTODOS DE INTERPOLAÇÕES DE DADOS OBTIDOS POR SENSORES DE AGRICULTURA DE PRECISÃO

Os sensores que medem as características do solo em campo são importantes ferramentas para o manejo da agricultura de precisão, entre eles, destaca-se o sensor de contato, que mede a condutividade elétrica (CE), matéria orgânica (MO) e potencial hidrogeniônico (pH) do solo. Objetivou-se avaliar os erros dos métodos de interpolação por krigagem, inverso da distância e normal da distância a partir de dados de CE, MO e pH do solo. O experimento foi realizado no município de Candói – PR, onde foram amostradas duas áreas, os dados foram coletados por sensor de contato, o qual foi conFigurado para uma coleta de 150 pontos por hectare para a condutividade elétrica e a matéria orgânica, e para potencial hidrogeniônico a frequência de coleta foi de 15 pontos por hectare, o equipamento foi acoplado em um trator operado a uma velocidade de 8 km h-1 com passadas paralelas de 20 m. Realizaram-se análises variográficas, validação cruzada e elaboração de mapas. Os menores erros de interpolação ou “jack knifing” para CE, MO e pH foram apresentados pelo método de interpolação inverso da distância, para o talhão T2, e no talhão T1 o método da Krigagem obteve os menores erros para o pH. Concluiu-se que distância das amostragens foi adequada e a krigagem e o inverso da distância foram mais eficientes que o normal da distância. Verificou-se que quanto maior a potência de elevação, tanto para o método do inverso da distância quanto para normal da distância, os erros aumentam e também o grau de contagiosidade.Palavras-chave: geoestatística, sensor Veris, variabilidade espacial. METHODS OF DATA INTERPOLATIONS OBTAINED BY PRECISION AGRICULTURE SENSORS ABSTRACT:The sensors that measure soil characteristics in the field are important tools for the management of precision agriculture, among them the contact sensor, which measures the electrical conductivity (EC), organic matter (OM) and hydrogenation potential (pH) of the soil. The objective of this study was to evaluate the errors of the interpolation methods by kriging, inverse distance and normal distance from the data of EC, MO and soil pH. The experiment was carried out in the city of Candói - PR, where two areas were sampled, the data were collected by contact sensor, which was configured for a collection of 150 points per hectare for electrical conductivity and organic matter, and for potential the collection frequency was 15 points per hectare, the equipment was coupled in a tractor operated at a speed of 8 km h-1 with parallel passes of 20 m. Variographic analysis, cross-validation and mapping were performed. The smallest interpolation errors or jack knifing for CE, MO and pH were presented by the inverse distance interpolation method for the T2 field, and in T1 field the Kriging method obtained the lowest errors for pH. It was concluded that distance from the samplings was adequate and the kriging and the inverse of the distance were more efficient than the normal distance. It was verified that the higher the elevation power, both for the inverse distance and the normal distance method, the errors increase and also the degree of contagiousness.Keywords: geostatistics, Veris sensor, spatial variability.

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Differences between laboratory and sensor analyses for soil attributes

Pesquisa Agropecuária Tropical ◽

10.1590/1983-40632021v5165491 ◽

2021 ◽

Vol 51 ◽

Author(s):

Gabriel Benhossi ◽

Étore Francisco Reynaldo ◽

Thiago Martins Machado

Keyword(s):

Electrical Conductivity ◽

Organic Matter ◽

Precision Agriculture ◽

Interpolation Method ◽

Kriging Interpolation ◽

Statistical Correlations ◽

Kriging Interpolation Method ◽

Map Generation ◽

Operational Capacity

ABSTRACT Sensors used in precision agriculture can perform readings of georeferenced points aiming to determine the electrical conductivity, pH and organic matter. These devices have a high operational capacity, but with little information on the quality of their collected data. This study aimed to establish correlations and differences among electrical conductivity, pH and organic matter data collected by sensor and obtained by laboratory analyses. The results were analyzed by statistical correlations, geostatistical analyses and map generation by the kriging interpolation method of electrical conductivity, pH and organic matter, using dedicated softwares. The sensor showed that the data collected for electrical conductivity, pH and organic matter are reliable and robust, due to the high spatial dependence and correct sampling distance confirmed by the range values.

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Efficacy of Variable Rate Soil-applied Herbicides Based on Soil Electrical Conductivity and Organic Matter Differences

Advances in Animal Biosciences ◽

10.1017/s2040470017000553 ◽

2017 ◽

Vol 8 (2) ◽

pp. 277-282

Author(s):

G. J. Gundy ◽

J. A. Dille ◽

A. R. Asebedo

Keyword(s):

Electrical Conductivity ◽

Organic Matter ◽

Soil Organic Matter ◽

Weed Control ◽

Precision Agriculture ◽

Visual Assessment ◽

Grain Sorghum ◽

Variable Rate ◽

Soil Electrical Conductivity ◽

Flat Rate

Soil application of herbicides for preemergence (PRE) weed control in grain sorghum is vital to control weeds. Efficacy of soil-applied herbicides is impacted by herbicide adsorption which is influenced by soil organic matter (SOM) and texture. With precision agriculture technologies, variable rate applications (VRA) can be utilized to maximize herbicide effectiveness. In 2016, algorithms were developed for two locations to use VRA of two tank mixed herbicides based on SOM and soil electrical conductivity (EC) collected by a Veris MSP3 system. Drone imagery provided an effective way to evaluate the efficacy of herbicide applications along with visual assessment. VRA applications of herbicide tank mixes provided equal weed control compared to flat rate applications.

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Spatial Behavior of Soil Erodibility in the La Villa River Basin, Panama

International Journal of Plant & Soil Science ◽

10.9734/ijpss/2021/v33i2330745 ◽

2021 ◽

pp. 309-315

Author(s):

Lwonel Agudo Martínez ◽

José Villarreal Núñez ◽

Jhon Villalaz Pérez ◽

Iván Ramos Zachrisson

Keyword(s):

Organic Matter ◽

River Basin ◽

Land Surface ◽

Interpolation Method ◽

Fine Sand ◽

Complete Information ◽

Spatial Behavior ◽

Soil Erodibility ◽

Spatial Analyst ◽

Inverse Distance

Introduction: Soil erodibility is an important factor in understanding the erosion that takes place in a territory. This is a parameter that can behave erratically in small spaces, but that describes a trend in larger spaces. Aim: Determine the K factor of soil erodibility in the La Villa-Panama river basin. Place and Duration of Study: La Villa River Basin-Azuero Peninsula, Panama. 2010-2012. Methodology: 98 points of the La Villa river watershed were sampled. Factor K was calculated using the adaptation to the sol-erodibility nomogram. The percentage of organic matter, structure class (in the field), permeability (combination permeameter) and the percentages of sand, silt and very fine sand (Bouyoucos method) were determined. To obtain the most complete information possible on the distribution of erodibility, a superficial interpolation of the point values corresponding to the soil samples taken was carried out. The software used was Arcview 3.3 and the Spatial Analyst extension. The interpolation method was IDW (Inverse Distance Weight). The erodibility values were categorized into seven intervals in such a way that it was possible to observe the differences on the map. Results: The erodibility values were influenced by the content of organic matter and coarse particles (percentage of sand and silt + very fine sand) of the soil. In the province of Herrera, 86% of the land surface and 76% in the province of Los Santos presents susceptibility to erosion in the ranges of 0.032 to 0.043 Ton ha h ha-1 Mj-1 mm-1. Conclusion: The results indicate that 80% of the soils of the La Villa river basin present a moderately high erodibility factor, with the highest values being registered in the upper middle zone.

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Distribuição Espacial da Condutividade Elétrica e Matéria Orgânica em um Solo Neossolo Flúvico (Spatial Distribution of Electrical Conductivity and Organic Matter in a Soil Fluvic Neosol)

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v6i4.233067 ◽

2013 ◽

Vol 6 (4) ◽

pp. 764 ◽

Cited By ~ 1

Author(s):

Jucicléia Soares da Silva ◽

Abelardo Antônio de Assunção Montenegro ◽

Ênio Farias de França e Silva ◽

Carolyne Wanessa Lins de Andrade ◽

José Roberto Lopes da Silva

Keyword(s):

Electrical Conductivity ◽

Organic Matter ◽

Spatial Distribution ◽

Organic Carbon ◽

Total Organic Carbon ◽

Precision Agriculture ◽

Spherical Model ◽

Contour Maps ◽

Saturation Extract ◽

Cultivar Selection

A agricultura de precisão permite, pelo uso de delimitação de lavouras por coordenadas georreferenciadas, um planejamento mais racional do manejo de nutrientes, incidência de pragas, umidade do solo, plantas daninhas, além de seleção de cultivares em função de sua adaptabilidade às diferentes condições identificadas nas áreas cultivadas. Com isso, o objetivo do presente trabalho foi avaliar a distribuição espacial da condutividade elétrica do extrato de saturação, carbono orgânico total e matéria orgânica em um solo Neossolo Flúvico. O experimento foi conduzido em uma área com malha regular 4 x 4 m, totalizando com 49 pontos, onde foram coletadas amostras nas camadas de 0- 0,20 m para analisar a condutividade elétrica do extrato de saturação, carbono orgânico total e matéria orgânica. As variáveis foram analisadas por meio da estatística descritiva e de ferramentas de geoestatística. As variáveis apresentaram distribuição normal, os semivariogramas se ajustaram a um modelo esférico, a variabilidade do carbono orgânico total e matéria orgânica apresentaram moderadas, a condutividade elétrica do extrato de saturação apresentou fraca dependência espacial. Os mapas de isolinhas apresentaram homogeneidade e similaridade, os mapas condutividade elétrica do extrato de 0-0,20 m foram inversamente proporcionais aos da matéria orgânica e do carbono orgânico. A B S T R A C T Precision agriculture allows, by the use of delimitation of crops for georeferenced coordinates, more rational planning of the management of nutrients, pests, soil moisture, weeds, and cultivar selection due to its adaptability to different conditions in the areas identified cultured. With it, the objective of this study was to evaluate the spatial distribution of the electrical conductivity of the saturation extract, total organic carbon and organic matter in soil Fluvic Neosol. The experiment was conducted in an area with regular mesh 4 x 4 m, with a total of 49 points, samples were collected in layers from 0 to 0.20 m to analyze the electrical conductivity of the saturation extract, total organic carbon and organic matter. The variables were analyzed using descriptive statistics and geostatistical tools. The variables were normally distributed, the semivariogram adjusted to a spherical model, the variability of total organic caborn and organic matter showed a moderate electrical conductivity of the saturation extract showed weak spatial dependence. The contour maps showed homogeneity and similarity maps the electrical conductivity of the extract of 0-0.20 m was inversely proportional to the organic matter and organic carbon. Key-Words: Geostatistics, salinity, total organic carbon, organic matter

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Applying the Method of Lagrange Multipliers to Derive an Estimator for Unsampled Soil Properties

Scientific Research Journal ◽

10.24191/srj.v11i1.5416 ◽

2014 ◽

Vol 11 (1) ◽

pp. 15

Author(s):

Set Foong Ng ◽

Pei Eng Ch’ng ◽

Yee Ming Chew ◽

Kok Shien Ng

Keyword(s):

Soil Properties ◽

Lagrange Multipliers ◽

Unbiased Estimator ◽

Soil Property ◽

Minimum Variance ◽

Distance Method ◽

True Value ◽

A Site ◽

Method Of Lagrange Multipliers ◽

Inverse Distance

Soil properties are very crucial for civil engineers to differentiate one type of soil from another and to predict its mechanical behavior. However, it is not practical to measure soil properties at all the locations at a site. In this paper, an estimator is derived to estimate the unknown values for soil properties from locations where soil samples were not collected. The estimator is obtained by combining the concept of the ‘Inverse Distance Method’ into the technique of ‘Kriging’. The method of Lagrange Multipliers is applied in this paper. It is shown that the estimator derived in this paper is an unbiased estimator. The partiality of the estimator with respect to the true value is zero. Hence, the estimated value will be equal to the true value of the soil property. It is also shown that the variance between the estimator and the soil property is minimised. Hence, the distribution of this unbiased estimator with minimum variance spreads the least from the true value. With this characteristic of minimum variance unbiased estimator, a high accuracy estimation of soil property could be obtained.

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The impact of urban effluents on the coastal marine environment of Mediterranean islands

Water Science & Technology ◽

10.2166/wst.1995.0673 ◽

1995 ◽

Vol 32 (9-10) ◽

pp. 85-94 ◽

Cited By ~ 1

Author(s):

Michael O. Angelidis

Keyword(s):

Heavy Metals ◽

Organic Matter ◽

Marine Environment ◽

Suspended Particle ◽

Pollution Source ◽

Mediterranean Islands ◽

Coastal Marine Environment ◽

Coastal Marine ◽

The Impact ◽

The City

The impact of the urban effluents of Mytilene (Lesvos island, Greece) on the receiving coastal marine environment, was evaluated by studying the quality of the city effluents (BOD5, COD, SS, heavy metals) and the marine sediments (grain size, organic matter, heavy metals). It was found that the urban effluents of Mytilene contain high organic matter and suspended particle load because of septage discharge into the sewerage network. Furthermore, although the city does not host important industrial activity, its effluents contain appreciable metal load, which is mainly associated with the particulate phase. The city effluents are discharged into the coastal marine environment and their colloidal and particulate matter after flocculation settles to the bottom, where is incorporated into the sediments. Over the years, the accumulation of organic matter and metals into the harbour mud has created a non-point pollution source in the relatively non-polluted coastal marine environment of the island. Copper and Zn were the metals which presented the higher enrichment in the sediments of the inner harbour of Mytilene.

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Mapping the Pollution Plume Using the Self-Potential Geophysical Method: Case of Oum Azza Landfill, Rabat, Morocco

Water ◽

10.3390/w13070961 ◽

2021 ◽

Vol 13 (7) ◽

pp. 961

Author(s):

Meryem Touzani ◽

Ismail Mohsine ◽

Jamila Ouardi ◽

Ilias Kacimi ◽

Moad Morarech ◽

...

Keyword(s):

Electrical Conductivity ◽

Water Table ◽

Soil Surface ◽

The Self ◽

Drainage Network ◽

Geophysical Method ◽

Direct Measurements ◽

Sandy Material ◽

The City ◽

Self Potential

The main landfill in the city of Rabat (Morocco) is based on sandy material containing the shallow Mio-Pliocene aquifer. The presence of a pollution plume is likely, but its extent is not known. Measurements of spontaneous potential (SP) from the soil surface were cross-referenced with direct measurements of the water table and leachates (pH, redox potential, electrical conductivity) according to the available accesses, as well as with an analysis of the landscape and the water table flows. With a few precautions during data acquisition on this resistive terrain, the results made it possible to separate the electrokinetic (~30%) and electrochemical (~70%) components responsible for the range of potentials observed (70 mV). The plume is detected in the hydrogeological downstream of the discharge, but is captured by the natural drainage network and does not extend further under the hills.

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The Relationship between Soil Electrical Parameters and Compaction of Sandy Clay Loam Soil

Agriculture ◽

10.3390/agriculture11020114 ◽

2021 ◽

Vol 11 (2) ◽

pp. 114

Author(s):

Katarzyna Pentoś ◽

Krzysztof Pieczarka ◽

Kamil Serwata

Keyword(s):

Electrical Conductivity ◽

Magnetic Susceptibility ◽

Precision Agriculture ◽

Soil Compaction ◽

Soil Layer ◽

Soil Parameters ◽

Soil Electrical Conductivity ◽

Electrical Parameters ◽

Management Zones ◽

Additional Information

Soil spatial variability mapping allows the delimitation of the number of soil samples investigated to describe agricultural areas; it is crucial in precision agriculture. Electrical soil parameters are promising factors for the delimitation of management zones. One of the soil parameters that affects yield is soil compaction. The objective of this work was to indicate electrical parameters useful for the delimitation of management zones connected with soil compaction. For this purpose, the measurement of apparent soil electrical conductivity and magnetic susceptibility was conducted at two depths: 0.5 and 1 m. Soil compaction was measured for a soil layer at 0–0.5 m. Relationships between electrical soil parameters and soil compaction were modelled with the use of two types of neural networks—multilayer perceptron (MLP) and radial basis function (RBF). Better prediction quality was observed for RBF models. It can be stated that in the mathematical model, the apparent soil electrical conductivity affects soil compaction significantly more than magnetic susceptibility. However, magnetic susceptibility gives additional information about soil properties, and therefore, both electrical parameters should be used simultaneously for the delimitation of management zones.

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A Multimethod Analysis for Average Annual Precipitation Mapping in the Khorasan Razavi Province (Northeastern Iran)

Atmosphere ◽

10.3390/atmos12050592 ◽

2021 ◽

Vol 12 (5) ◽

pp. 592

Author(s):

Mehdi Aalijahan ◽

Azra Khosravichenar

Keyword(s):

Regional Planning ◽

Interpolation Method ◽

Absolute Error ◽

Rain Gauge ◽

Annual Precipitation ◽

Coefficient Of Determination ◽

Distance Weighting ◽

Average Annual Precipitation ◽

Inverse Distance

The spatial distribution of precipitation is one of the most important climatic variables used in geographic and environmental studies. However, when there is a lack of full coverage of meteorological stations, precipitation estimations are necessary to interpolate precipitation for larger areas. The purpose of this research was to find the best interpolation method for precipitation mapping in the partly densely populated Khorasan Razavi province of northeastern Iran. To achieve this, we compared five methods by applying average precipitation data from 97 rain gauge stations in that province for a period of 20 years (1994–2014): Inverse Distance Weighting, Radial Basis Functions (Completely Regularized Spline, Spline with Tension, Multiquadric, Inverse Multiquadric, Thin Plate Spline), Kriging (Simple, Ordinary, Universal), Co-Kriging (Simple, Ordinary, Universal) with an auxiliary elevation parameter, and non-linear Regression. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and the Coefficient of Determination (R2) were used to determine the best-performing method of precipitation interpolation. Our study shows that Ordinary Co-Kriging with an auxiliary elevation parameter was the best method for determining the distribution of annual precipitation for this region, showing the highest coefficient of determination of 0.46% between estimated and observed values. Therefore, the application of this method of precipitation mapping would form a mandatory base for regional planning and policy making in the arid to semi-arid Khorasan Razavi province during the future.

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Temporal stability of electrical conductivity in a sandy soil

International Agrophysics ◽

10.1515/intag-2016-0005 ◽

2016 ◽

Vol 30 (3) ◽

pp. 349-357 ◽

Cited By ~ 12

Author(s):

Aura Pedrera-Parrilla ◽

Eric C. Brevik ◽

Juan V. Giráldez ◽

Karl Vanderlinden

Keyword(s):

Electrical Conductivity ◽

Spatial Variability ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Precision Agriculture ◽

Temporal Stability ◽

Principal Component ◽

Model Parameters ◽

Soil Spatial Variability

Abstract Understanding of soil spatial variability is needed to delimit areas for precision agriculture. Electromagnetic induction sensors which measure the soil apparent electrical conductivity reflect soil spatial variability. The objectives of this work were to see if a temporally stable component could be found in electrical conductivity, and to see if temporal stability information acquired from several electrical conductivity surveys could be used to better interpret the results of concurrent surveys of electrical conductivity and soil water content. The experimental work was performed in a commercial rainfed olive grove of 6.7 ha in the ‘La Manga’ catchment in SW Spain. Several soil surveys provided gravimetric soil water content and electrical conductivity data. Soil electrical conductivity values were used to spatially delimit three areas in the grove, based on the first principal component, which represented the time-stable dominant spatial electrical conductivity pattern and explained 86% of the total electrical conductivity variance. Significant differences in clay, stone and soil water contents were detected between the three areas. Relationships between electrical conductivity and soil water content were modelled with an exponential model. Parameters from the model showed a strong effect of the first principal component on the relationship between soil water content and electrical conductivity. Overall temporal stability of electrical conductivity reflects soil properties and manifests itself in spatial patterns of soil water content.

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