scholarly journals Spatial Variability of Irrigated Corn Yield in Relation to Field Topography and Soil Chemical Characteristics

2005 ◽  
Vol 6 (5) ◽  
pp. 453-466 ◽  
Author(s):  
J. R. Marques Da Silva ◽  
C. Alexandre
Keyword(s):  
Spatial Variability ◽  
Chemical Characteristics ◽  
Corn Yield

scholarly journals Yield mapping, soil fertility and tree gaps in an orange orchard

2012 ◽  
Vol 34 (4) ◽  
pp. 1256-1265 ◽  
Author(s):  
José Paulo Molin ◽  
André Freitas Colaço ◽  
Eduardo Fermino Carlos ◽  
Dirceu de Mattos Junior
Keyword(s):  
Spatial Variability ◽  
Soil Fertility ◽  
Precision Agriculture ◽  
Nutrient Management ◽  
Fruit Production ◽  
Fruit Yield ◽  
Chemical Characteristics ◽  
Yield Mapping ◽  
Orange Orchard ◽  
Representative Area

The current high competition on Citrus industry demands from growers new management technologies for superior efficiency and sustainability. In this context, precision agriculture (PA) has developed techniques based on yield mapping and management systems that recognize field spatial variability, which contribute to increase profitability of commercial crops. Because spatial variability is often not perceived the orange orchards are still managed as uniform and adoption of PA technology on citrus farms is low. Thus, the objective of the present study was to characterize the spatial variability of three factors: fruit yield, soil fertility and occurrence of plant gaps caused by either citrus blight or huanglongbing (HLB) in a commercial Valencia orchard in Brotas, São Paulo State, Brazil. Data from volume, geographic coordinates and representative area of the bags used on harvest were recorded to generate yield points that were then interpolated to produce the yield map. Soil chemical characteristics were studied by analyzing samples collected along planting rows and inter-rows in 24 points distributed in the field. A map of density of tree gaps was produced by georeferencing individual gaps and later by counting the number of gaps within 500 m² cells. Data were submitted to statistical and geostatistical analyses. A t test was used to compare means of soil chemical characteristics between sampling regions. High variation on yield and density of tree gaps was observed from the maps. It was also demonstrated overlapping regions of high density of plant absence and low fruit yield. Soil fertility varied depending on the sampling region in the orchard. The spatial variability found on yield, soil fertility and on disease occurrence demonstrated the importance to adopt site specific nutrient management and disease control as tools to guarantee efficiency of fruit production.

Spatial variability of the chemical characteristics of a trace-element-contaminated soil before and after remediation

Geoderma ◽  
2006 ◽  
Vol 130 (1-2) ◽  
pp. 157-175 ◽  
Author(s):  
Pilar Burgos ◽  
Engracia Madejón ◽  
Alfredo Pérez-de-Mora ◽  
Francisco Cabrera
Keyword(s):  
Spatial Variability ◽  
Trace Element ◽  
Contaminated Soil ◽  
Chemical Characteristics ◽  
Before And After

scholarly journals Soil sampling intensity and spatial distribution pattern of soils attributes and corn yield in no-tillage system

2012 ◽  
Vol 32 (5) ◽  
pp. 852-865 ◽  
Author(s):  
Marcos S. Rodrigues ◽  
José E. Corá ◽  
Carolina Fernandes
Keyword(s):  
Spatial Distribution ◽  
Spatial Variability ◽  
Distribution Pattern ◽  
Clay Content ◽  
Soil Sampling ◽  
Spatial Distribution Pattern ◽  
Corn Yield ◽  
Soil Attributes ◽  
Point Sampling ◽  
Sampling Intensity

Taking into account that the sampling intensity of soil attributes is a determining factor for applying of concepts of precision agriculture, this study aims to determine the spatial distribution pattern of soil attributes and corn yield at four soil sampling intensities and verify how sampling intensity affects cause-effect relationship between soil attributes and corn yield. A 100-referenced point sample grid was imposed on the experimental site. Thus, each sampling cell encompassed an area of 45 m² and was composed of five 10-m long crop rows, where referenced points were considered the center of the cell. Samples were taken from at 0 to 0.1 m and 0.1 to 0.2 m depths. Soil chemical attributes and clay content were evaluated. Sampling intensities were established by initial 100-point sampling, resulting data sets of 100; 75; 50 and 25 points. The data were submitted to descriptive statistical and geostatistics analyses. The best sampling intensity to know the spatial distribution pattern was dependent on the soil attribute being studied. The attributes P and K+ content showed higher spatial variability; while the clay content, Ca2+, Mg2+ and base saturation values (V) showed lesser spatial variability. The spatial distribution pattern of clay content and V at the 100-point sampling were the ones which best explained the spatial distribution pattern of corn yield.

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 Different limestone particle sizes for soil acidity correction, Ca and Mg supply and corn yield

2018 ◽  
Vol 9 (2) ◽  
pp. 175-184 ◽  
Author(s):  
Rafael Felipe Ratke ◽  
Hamilton Seron Pereira ◽  
João de Deus Gomes dos Santos_Júnior ◽  
Juliano Magalhães Barbosa ◽  
Liliane Oliveira Lopes
Keyword(s):  
Particle Size ◽  
Grain Yield ◽  
Soil Acidity ◽  
Residual Effect ◽  
Chemical Characteristics ◽  
Corn Yield ◽  
Particle Sizes ◽  
Lime Application ◽  
Yield Responses ◽  
Lower Particle Size

The aim of this study was to evaluate the soil acidity correction and the grain yield responses for the lime application in different granulometric particles. The limestone particle sizes incorporated into the distroferric red Oxisol were: 0.20 mm to 0.30 mm; 0.30 mm to 0.56 mm; 0.56 mm to 0.82 mm and 0.82 mm to 2.00 mm, at doses of 1.3 t ha-1; 2.6 t ha-1; 3.9 t ha-1 and 6.6 t ha-1 respectively, and a control respectively, and a control (no lime incorporation in the soil). The soil chemical characteristics pH, H+Al3+, Al3+, Ca2+ e Mg2+ were evaluated at 6 months and 18 months after the lime application. The corn yields were evaluated during the 2008/2009 and 2009/2010 crop years. Higher limestone contents and lower particle size resulted in the same effect on soil acidity correction, reducing Al3+ and increasing Ca2+ and Mg2+ in the soil when the 0.30 mm limestone was incorporated, with residual effect at 18 months. Highest corn yield was obtained when the 0.82 mm to 2.00 mm particle size was incorporated in the first crop year, when compared to the lowest limestone particle size used.

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