scholarly journals Spatial variability of soil fertility in an integrated crop livestock forest system

2017 ◽  
Vol 8 (2) ◽  
pp. 590-593 ◽  
Author(s):  
A. C. C. Bernardi ◽  
G. M. Bettiol ◽  
G. G. Mazzuco ◽  
S. N. Esteves ◽  
P. P. A. Oliveira ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Fertility ◽  
Soil Properties ◽  
Precision Agriculture ◽  
Acid Soil ◽  
Management Strategies ◽  
Fertilizer Application ◽  
Management Tools ◽  
Site Specific ◽  
The Tropics

Knowledge on spatial variability of soil properties is useful for the rational use of inputs, as in the site specific application of lime and fertilizer. Crop-livestock-forest integrated systems (CLFIS) provide a strategy of sustainable agricultural production which integrates annual crops, trees and livestock activities on a same area and in the same season. Since the lime and fertilizer are key factors for the intensification of agricultural systems in acid-soil in the tropics, precision agriculture (PA) is the tool to improve the efficiency of use of these issues. The objective of this research was to map and evaluate the spatial variability of soil properties, liming and fertilizer need of a CLFIS. The field study was carried out in a 30 ha area at Embrapa Pecuária Sudeste in São Carlos, SP, Brazil. Soil samples were collected at 0–0.2 m depth, and each sample represented a paddock. The spatial variability of soil properties and site-specific liming and fertilizer needs were modeled using semi-variograms, the soil fertility information were modeled. Spatial variability soil properties and site specific liming and fertilizer need were modeled by kriging and inverse distance weighting (IDW) techniques. Another approach used was based on lime and fertilizer recommendation considering the paddocks as the minimum management unit. The results showed that geostatistics and GIS were useful tools for revealing soil spatial variability and supporting management strategies. Soil nutrients were used to classify the soil spatial distribution map and design site-specific lime and fertilizer application zones. Spatial analyses of crop needs and requirement can provide management tools for avoiding potential environmental problems, caused by unbalanced nutrient supplies.

scholarly journals Establishing management zones using soil electrical conductivity and other soil properties by the fuzzy clustering technique

2008 ◽  
Vol 65 (6) ◽  
pp. 567-573 ◽  
Author(s):  
José Paulo Molin ◽  
Cesar Nunes de Castro
Keyword(s):  
Electrical Conductivity ◽  
Soil Fertility ◽  
Soil Properties ◽  
Precision Agriculture ◽  
Principal Component ◽  
Site Specific ◽  
Management Zones ◽  
Physical Attributes ◽  
Definition Of ◽  
Specific Management

The design of site-specific management zones that can successfully define uniform regions of soil fertility attributes that are of importance to crop growth is one of the most challenging steps in precision agriculture. One important method of so proceeding is based solely on crop yield stability using information from yield maps; however, it is possible to accomplish this using soil information. In this study the soil was sampled for electrical conductivity and eleven other soil properties, aiming to define uniform site-specific management zones in relation to these variables. Principal component analysis was used to group variables and fuzzy logic classification was used for clustering the transformed variables. The importance of electrical conductivity in this process was evaluated based on its correlation with soil fertility and physical attributes. The results confirmed the utility of electrical conductivity in the definition of management zones and the feasibility of the proposed method.

Analysis of Spatial Variability of Soil Fertility in Precision Agriculture Technologies

2019 ◽  
Author(s):  
V.I. Zatserkovnyi ◽  
P.I. Trofymenko ◽  
N.V. Trofimenko ◽  
I.O. Makedonska
Keyword(s):  
Spatial Variability ◽  
Soil Fertility ◽  
Precision Agriculture

scholarly journals Spatial variability of vegetation index and soil properties in an integrated crop-livestock system

2017 ◽  
Vol 21 (8) ◽  
pp. 513-518 ◽  
Author(s):  
Alberto C. de C. Bernardi ◽  
Célia R. Grego ◽  
Ricardo G. Andrade ◽  
Ladislau M. Rabello ◽  
Ricardo Y. Inamasu
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Strategies ◽  
Exchange Capacity ◽  
Soil Parameters ◽  
Forage Production ◽  
Soil P ◽  
Livestock System

ABSTRACT The knowledge of soil property spatial variability is useful for determining the rational use of inputs, such as the site-specific application of lime and fertilizer. The objective of this study was to evaluate the vegetation index and spatial variability of physical and chemical soil properties in an integrated crop-livestock system (ICLS). Soil samples were taken from a 6.9 ha area in a regular hexagon grid at 0-0.20 m depths. Soil P, K, Ca, Mg, and cation exchange capacity - CEC; base saturation; clay and sand were analyzed. Soil electrical conductivity (ECa) was measured with a contact sensor. The site was evaluated at the end of the corn season (April) and during forage production (October) using Landsat 5 images, remote sensing techniques and a geographic information system (GIS). Results showed that the normalized difference vegetation index (NDVI) was associated with ECa and soil parameters, indicating crop and pasture variations in the ICLS. Geostatistics and GIS were effective tools for collecting data regarding the spatial variability of soil and crop indicators, identifying variation trends in the data, and assisting data interpretation to determine adequate management strategies.

scholarly journals Spatial variability of soil fertility and its relation with cocoa yield

2017 ◽  
Vol 21 (2) ◽  
pp. 88-93 ◽  
Author(s):  
Railton O. dos Santos ◽  
◽  
Laís B. Franco ◽  
Samuel A. Silva ◽  
George A. Sodré ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Spatial Variability ◽  
Soil Fertility ◽  
Soil Properties ◽  
Crop Yield ◽  
Chemical Properties ◽  
Western Region ◽  
Chemical Attributes ◽  
Cocoa Yield

ABSTRACT The knowledge on the spatial variability of soil properties and crops is important for decision-making on agricultural management. The objective of this study was to evaluate the spatial variability of soil fertility and its relation with cocoa yield. The study was conducted over 14 months in an area cultivated with cocoa. A sampling grid was created to study soil chemical properties and cocoa yield (stratified in season, off-season and annual). The data were analyzed using descriptive and exploratory statistics, and geostatistics. The chemical attributes were classified using fuzzy logic to generate a soil fertility map, which was correlated with maps of crop yield. The soil of the area, except for the western region, showed possibilities ranging from medium to high for cocoa cultivation. Soil fertility showed positive spatial correlation with cocoa yield, and its effect was predominant only for the off-season and annual cocoa.

scholarly journals Monitoring the Spatial Variability of Knapweed (Centaurea diluta Aiton) in Wheat Crops Using Geostatistics and UAV Imagery: Probability Maps for Risk Assessment in Site-Specific Control

Agronomy ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 880
Author(s):  
Montserrat Jurado-Expósito ◽  
Francisca López-Granados ◽  
Francisco Manuel Jiménez-Brenes ◽  
Jorge Torres-Sánchez
Keyword(s):  
Risk Assessment ◽  
Spatial Variability ◽  
Weed Management ◽  
Management Strategies ◽  
Indicator Kriging ◽  
Site Specific ◽  
Weed Density ◽  
Density Mapping ◽  
Probability Maps ◽  
Geostatistical Approach

Assessing the spatial distribution of weeds within a field is a key step to the success of site-specific weed management strategies. Centaurea diluta (knapweed) is an emerging weed that is causing a major agronomic problem in southern and central Spain because of its large size, the difficulty of controlling it, and its high competitive ability. The main objectives of this study were to examine the spatial variability of C. diluta density in two wheat fields by multivariate geostatistical methods using unmanned aerial vehicle (UAV) imagery as secondary information and to delineate potential control zones for site-specific treatments based on occurrence probability maps of weed infestation. The primary variable was obtained by grid weed density field samplings, and the secondary variables were derived from UAV imagery acquired the same day as the weed field surveys. Kriging and cokriging with UAV-derived variables that displayed a strong correlation with weed density were used to compare C. diluta density mapping performance. The accuracy of the predictions was assessed by cross-validation. Cokriging with UAV-derived secondary variables generated more accurate weed density maps with a lower RMSE compare with kriging and cokriging with RVI, NDVI, ExR, and ExR(2) (the best methods for the prediction of knapweed density). Cokriged estimates were used to generate probability maps for risk assessment when implementing site-specific weed control by indicator kriging. This multivariate geostatistical approach enabled the delineation of winter wheat fields into two zones for different prescription treatments according to the C. diluta density and the economic threshold.

Delineation of management zones with measurements of soil apparent electrical conductivity in the southeastern pampas

2013 ◽  
Vol 93 (2) ◽  
pp. 205-218 ◽  
Author(s):  
Nahuel Raúl Peralta ◽  
José Luis Costa ◽  
Mónica Balzarini ◽  
Hernán Angelini
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Stepwise Regression ◽  
Clay Soil ◽  
Crop Yields ◽  
Management Strategies ◽  
Site Specific ◽  
Management Zones ◽  
Apparent Electrical Conductivity ◽  
Specific Management

Peralta, N. R., Costa, J. L., Balzarini, M. and Angelini, H. 2013. Delineation of management zones with measurements of soil apparent electrical conductivity in the southeastern pampas. Can. J. Soil Sci. 93: 205–218. Site-specific management demands the identification of subfield regions with homogeneous characteristics (management zones). However, determination of subfield areas is difficult because of complex correlations and spatial variability of soil properties responsible for variations in crop yields within the field. We evaluated whether apparent electrical conductivity (ECa) is a potential estimator of soil properties, and a tool for the delimitation of homogeneous zones. ECamapping of a total of 647 ha was performed in four sites of Argentinean pampas, with two fields per site composed of several soil series. Soil properties and ECawere analyzed using principal components (PC)–stepwise regression and ANOVA. The PC–stepwise regression showed that clay, soil organic matter (SOM), cation exchange capacity (CEC) and soil gravimetric water content (θg) are key loading factors, for explaining the ECa(R2≥0.50). In contrast, silt, sand, extract electrical conductivity (ECext), pH values and [Formula: see text]-N content were not able to explain the ECa. The ANOVA showed that ECameasurements successfully delimited three homogeneous soil zones associated with spatial distribution of clay, soil moisture, CEC, SOM content and pH. These results suggest that field-scale ECamaps have the potential to design sampling zones to implement site-specific management strategies.

scholarly journals The accuracy of farm machinery for precision agriculture: a case for fertilizer application

1997 ◽  
Vol 45 (1) ◽  
pp. 199-215 ◽  
Author(s):  
D. Goense
Keyword(s):  
Precision Agriculture ◽  
Fertilizer Application ◽  
Positioning Accuracy ◽  
Site Specific ◽  
Positioning Systems ◽  
Application Rates ◽  
Small Influence ◽  
Variance Calculation ◽  
Field Variability ◽  
Different Levels

Work quality, capacity and reliability are important criteria for design and evaluation of farm equipment. With the introduction of precision agriculture, the ability to adapt to spatially variable soil and crop conditions, becomes an additional aspect. A calculation method was developed to find the precision of site specific fertilizer application. The variance between the required rate, RR, and the applied rate, AR, was used as a measure for precision. The theory of geo-statistics was used for variance calculation. Spreading patterns were evaluated for different levels of field variability, positioning accuracy and resolution of the required application rates. The shape of spreading patterns had small influence. The effect of the accuracy of positioning systems was dependent on the resolution of the required application rates and of the working width of independently controlled sections of the spreaders.

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