scholarly journals Mapping of yield, economic return, soil electrical conductivity, and management zones of irrigated corn for silage

2018 ◽  
Vol 53 (12) ◽  
pp. 1289-1298 ◽  
Author(s):  
Alberto Carlos de Campos Bernardi ◽  
Oscar Tupy ◽  
Karoline Eduarda Lima Santos ◽  
Giulia Guillen Mazzuco ◽  
Giovana Maranhão Bettiol ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Spatial Variability ◽  
Precision Agriculture ◽  
Temporal Variability ◽  
Production Cost ◽  
Spatial And Temporal Variability ◽  
Corn Yield ◽  
Soil Electrical Conductivity ◽  
Economic Return ◽  
Management Zones

Abstract: The objective of this work was to evaluate the spatial and temporal variability of the dry matter yield of irrigated corn for silage, as well as its economic return. The study was conducted in an irrigated silage corn field of 18.9 ha in the municipality of São Carlos, in the state of São Paulo, Brazil. The spatial variability of the yield of three crop seasons, normalized yield indexes, production cost, profit, and soil electrical conductivity (EC) were modeled using semivariograms. Yield maps were obtained by kriging, and management zones were mapped based on average yield, normalized index, and EC. The results showed a structured spatial variability of corn yield, production cost, profit, and soil EC within the irrigated area. The adopted precision agriculture tools were useful to indicate zones of higher yield and economic return. The sequences of yield maps and the analysis of spatial and temporal variability allow the definition of management zones, and soil EC is positively related to corn yield.

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

Agriculture ◽  
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.

scholarly journals Spatial variability of apparent electrical conductivity and soil properties in a coffee production field

2014 ◽  
Vol 34 (6) ◽  
pp. 1224-1233 ◽  
Author(s):  
Domingos S. M. Valente ◽  
Daniel M. de Queiroz ◽  
Francisco de A. de C. Pinto ◽  
Fábio L. Santos ◽  
Nerilson T. Santos
Keyword(s):  
Electrical Conductivity ◽  
Spatial Variability ◽  
Soil Properties ◽  
Precision Agriculture ◽  
Chemical Properties ◽  
Coffee Production ◽  
Management Zones ◽  
Apparent Electrical Conductivity ◽  
The Relationship ◽  
Dense Sampling

Precision agriculture based on the physical and chemical properties of soil requires dense sampling to determine the spatial variability of these properties. This dense sampling is often expensive and time-consuming. One technique used to reduce sample numbers involves defining management zones based on information collected in the field. Some researchers have demonstrated the importance of soil electrical variables in defining management zones. The objective of this study was to evaluate the relationship between the spatial variability of the apparent electrical conductivity and the soil properties in the coffee production of mountain regions. Spatial variability maps were generated using a geostatistical method. Based on the spatial variability results, a correlation analysis, using bivariate Moran's index, was done to evaluate the relationship between the apparent electrical conductivity and soil properties. The maps of potassium (K) and remaining phosphorus (P-rem) were the closest to the spatial variability pattern of the apparent electrical conductivity.

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

2015 ◽  
Vol 35 (3) ◽  
pp. 470-483 ◽  
Author(s):  
Marcos S. Rodrigues ◽  
José E. Corá
Keyword(s):  
Temporal Variability ◽  
Clustering Algorithm ◽  
Spatial And Temporal Variability ◽  
Optimum Number ◽  
Corn Yield ◽  
Management Zones ◽  
Soil Attributes ◽  
Fuzzy C Means ◽  
Management Zone ◽  
Fuzzy C Means Clustering

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 c-means 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.

scholarly journals Precision agriculture applied to soybean: Part III - Spatial and temporal variability of yield

2017 ◽  
pp. 799-805
Author(s):  
Eduardo Leonel Bottega ◽  
◽  
Daniel Marçal de Queiroz ◽  
Francisco de Assis de Carvalho Pinto ◽  
Domingos Sárvio Magalhães Valente ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Temporal Variability ◽  
Spatial And Temporal Variability

scholarly journals Temporal stability of electrical conductivity in a sandy soil

2016 ◽  
Vol 30 (3) ◽  
pp. 349-357 ◽  
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.

scholarly journals Applying Nitrogen Site-Specifically Using Soil Electrical Conductivity Maps and Precision Agriculture Technology

2001 ◽  
Vol 1 ◽  
pp. 767-776 ◽  
Author(s):  
E.D. Lund ◽  
M.C. Wolcott ◽  
G.P. Hanson
Keyword(s):  
Electrical Conductivity ◽  
Case Studies ◽  
Crop Yield ◽  
Soil Texture ◽  
Precision Agriculture ◽  
Management Practices ◽  
N Availability ◽  
Soil Electrical Conductivity ◽  
Variable Yield ◽  
Wide Range

Soil texture varies significantly within many agricultural fields. The physical properties of soil, such as soil texture, have a direct effect on water holding capacity, cation exchange capacity, crop yield, production capability, and nitrogen (N) loss variations within a field. In short, mobile nutrients are used, lost, and stored differently as soil textures vary. A uniform application of N to varying soils results in a wide range of N availability to the crop. N applied in excess of crop usage results in a waste of the grower’s input expense, a potential negative effect on the environment, and in some crops a reduction of crop quality, yield, and harvestability. Inadequate N levels represent a lost opportunity for crop yield and profit. The global positioning system (GPS)-referenced mapping of bulk soil electrical conductivity (EC) has been shown to serve as an effective proxy for soil texture and other soil properties. Soils with a high clay content conduct more electricity than coarser textured soils, which results in higher EC values. This paper will describe the EC mapping process and provide case studies of site-specific N applications based on EC maps. Results of these case studies suggest that N can be managed site-specifically using a variety of management practices, including soil sampling, variable yield goals, and cropping history.

CHARACTERIZATION OF SPATIAL VARIABILITY OF SOIL ELECTRICAL CONDUCTIVITY AND CONE INDEX USING COULTER AND PENETROMETER-TYPE SENSORS

Soil Science ◽  
2006 ◽  
Vol 171 (8) ◽  
pp. 627-637 ◽  
Author(s):  
Jay David Jabro ◽  
Robert G. Evans ◽  
Yunseup Kim ◽  
William B. Stevens ◽  
William M. Iversen
Keyword(s):  
Electrical Conductivity ◽  
Spatial Variability ◽  
Soil Electrical Conductivity ◽  
Cone Index

scholarly journals SPACE DEPENDENCE OF SOIL MOISTURE AND SOIL ELECTRICAL CONDUCTIVITY IN ALUVIAL REGION1

Irriga ◽  
2019 ◽  
Vol 24 (1) ◽  
pp. 1-15
Author(s):  
Iug Lopes ◽  
Abelardo A. A. Montenegro
Keyword(s):  
Electrical Conductivity ◽  
Soil Moisture ◽  
Precision Agriculture ◽  
Spatial Dependence ◽  
Spatial Information ◽  
Gravimetric Method ◽  
Research Unit ◽  
Soil Electrical Conductivity ◽  
Agricultural Engineering ◽  
Space Dependence

SPACE DEPENDENCE OF SOIL MOISTURE AND SOIL ELECTRICAL CONDUCTIVITY IN ALUVIAL REGION1     IUG LOPES2 E ABELARDO ANTONIO DE ASSUNÇÃO MONTENEGRO3   1Paper extracted from the doctoral thesis of the first author. 2Department of Agronomy, Instituto Federal de Educação, Ciência e Tecnologia Baiano, BR 349, Km 14 - Zona Rural, CEP: 47600-000, Bom Jesus da Lapa - BA, Brazil; [email protected] - ORCID: 0000-0003-0592-4774. 3Department of Agricultural Engineering, Universidade Federal Rural de Pernambuco, Rua Dom Manoel de Medeiros, Dois Irmão, CEP: 52171-900, Recife - PE, Brazil; [email protected] -ORCID: 0000-0002-5746-8574.     1 ABSTRACT   Spatial information on soil characteristics is essential to proper decision-making regarding to the environment and land use management. The objective of this work was the investigation of cross - variance between soil moisture and apparent soil electrical conductivity (CEa), under different land uses in an alluvial valley of Pernambuco. The study was developed at the Advanced Research Unit of Universidade Federal Rural de Pernambuco (UFRPE), located at  Brígida River Basin, municipality of Panamirim-PE. Soil samples were collected in a regular mesh of 20 x 10 m, for soil moisture by gravimetric method and, following a regular 10 x 10 m mesh, CEa measurements were performed using EM38® device. Cross-semivariograms were assessed and spatial dependence was verified by geostatistical procedures. It was verified in geostatistical procedures  low variation for soil moisture and intermediate variation for CEa. The use of geostatistics allowed identification of covariance between soil moisture and ECa, as well as spatial dependence for both variables, for agricultural areas. It was verified that soil moisture, even at levels close to residual, constitutes a relevant secondary component for increasing soil salinity maps precision, and hence to precision agriculture.   Keywords: geostatistics, semi-arid, precision agriculture     LOPES, I. E MONTENEGRO, A. A. DE A. DEPENDÊNCIA ESPACIAL DA UMIDADE DO SOLO E CONDUTIVIDADE ELÉTRICA EM REGIÃO ALUVIAL     2 RESUMO   Informações espaciais sobre as características do solo são essenciais para uma tomada de decisão adequada em relação ao meio ambiente e ao gerenciamento do uso do solo. O objetivo deste trabalho foi investigar a variância cruzada entre a umidade do solo e a condutividade elétrica aparente do solo (CEa), sob diferentes usos do solo em um vale aluvial de Pernambuco. O estudo foi desenvolvido na Unidade de Pesquisa Avançada da Universidade Federal Rural de Pernambuco (UFRPE), localizada na bacia do rio Brígida, município de Panamirim-PE. As amostras de solo foram coletadas em uma malha regular de 20 x 10 m, para a umidade do solo pelo método gravimétrico e, seguindo uma malha regular de 10 x 10 m, as medidas de CEa foram realizadas usando o dispositivo EM38®. Os semivariogramas cruzados foram avaliados e a dependência espacial foi verificada por procedimentos geoestatísticos. Verificou-se procedimentos geoestatísticos, uma baixa variação da umidade do solo e variação intermediária para CEa. O uso da geoestatística permitiu identificar a covariância entre a umidade do solo e o CEa, bem como a dependência espacial para ambas as variáveis, para as áreas agrícolas. Verificou-se que a umidade do solo, mesmo em níveis próximos ao residual, constitui um componente secundário relevante para o aumento da precisão do mapeamento da salinidade do solo e, consequentemente, para a agricultura de precisão.   Palavras-chave: geoestatística, semiárido, agricultura de precisão

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