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Journal of Experimental Agriculture International, ISSN: 2457-0591, ISSN: 2231-0606 (Past),Vol.: 24, Issue.: 3

Original-research-article

Adjustment of Sampling Grids for Soil Penetration Resistance, Bulk Density, and Soil Moisture Mapping

 

Rodrigo Nogueira Martins1*, Ailton Rodrigues de Oliveira2, Leticia Thália Silva Machado2, Fernando Ferreira Lima dos Santos1, Wagner da Cunha Siqueira2 and Juliana Aparecida de Souza Santos3

1Department of Agricultural Engineering, Federal University of Viçosa, Brazil.

2Department of Agricultural and Environmental Engineering, Federal Institute of Northern Minas Gerais, Brazil.

3Department of Agronomy, Federal Rural University of Rio de Janeiro, Brazil.

Article Information

Editor(s):

(1) Dr. Lixiang Cao, Professor, Department of Biotechnology, Sun Yat-sen University, China.

Reviewers:

(1) Gunnar Bengtsson, Stockholm University, Sweden.

(2) Rebecca Yegon, University of Embu, Kenya.

Complete Peer review History: http://www.sciencedomain.org/review-history/25357

Abstracts

There is still a lack of information in the literature regarding the sampling grid size and its effect on the accuracy of soil attributes spatial variability mapping. Thus, the present study aimed to evaluate the influence of different sampling grid sizes regarding accuracy for soil penetration resistance (SPR), soil bulk density (SBD) and soil moisture (SM) spatial variability characterization, as well as the correlation between these attributes. The study was conducted in a 5.7 ha Red Yellow Latosol area in Januária, Minas Gerais state, Brazil. Soil samples were taken at the 0.00–0.20 m layer, using a regular sampling grid of 20x20 m. (145 points). Other two grids (41 and 21 points) were derived by deleting lines or lines and points from the initial grid. SPR, SBD, and SM data were subjected to descriptive statistics and geostatistical analyses. Furthermore, the similarity of the thematic maps and correlation among these attributes were analyzed through the relative deviation coefficient (RDC), and Pearson's correlation matrix. The reduction of the grid density (number of points) increased the estimation error for SPR, SBD, and SM, especially when using only 21 points (grid C), whereas, denser grids (Grid A and B) showed maps with greater similarity (accuracy). The SPR levels are directly related to SBD levels, in other words, the highest SPR levels in the area occurred due to higher SBD levels, as well as the lowest values, whereas SM levels were inversely proportional to SPR values since wetter areas presented lower SPR levels. Also, denser areas are directly correlated with higher levels of SM in the study area. In essence, only the grid with 25 points per hectare (20x20 m) is recommended for mapping these attributes spatial variability.

Keywords :

Precision agriculture; spatial variability; soil compaction; penetrometer.

Full Article - PDF    Page 1-11 Article Metrics

DOI : 10.9734/JEAI/2018/42681

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