scholarly journals Sample arrangements and spatial variability characterization of dendometrics parameters of Eucalyptus camaldulensis and physical soil attributes

Revista CERES ◽  
2021 ◽  
Vol 68 (6) ◽  
pp. 597-608
Author(s):  
César Gustavo da Rocha Lima ◽  
Alan Rodrigo Panosso ◽  
Nídia Raquel Costa ◽  
Mariana Barbosa de Carvalho ◽  
Nelson Giovanini Júnior ◽  
...  
2011 ◽  
Vol 31 (6) ◽  
pp. 1162-1169 ◽  
Author(s):  
David L Rosalen ◽  
Marcos S Rodrigues ◽  
Carlos A Chioderoli ◽  
Flavia J. C Brandão ◽  
Diego S Siqueira

The characterization of the spatial variability of soil attributes is essential to support agricultural practices in a sustainable manner. The use of geostatistics to characterize spatial variability of these attributes, such as soil resistance to penetration (RP) and gravimetric soil moisture (GM) is now usual practice in precision agriculture. The result of geostatistical analysis is dependent on the sample density and other factors according to the georeferencing methodology used. Thus, this study aimed to compare two methods of georeferencing to characterize the spatial variability of RP and GM as well as the spatial correlation of these variables. Sampling grid of 60 points spaced 20 m was used. For RP measurements, an electronic penetrometer was used and to determine the GM, a Dutch auger (0.0-0.1 m depth) was used. The samples were georeferenced using a GPS navigation receiver, Simple Point Positioning (SPP) with navigation GPS receiver, and Semi-Kinematic Relative Positioning (SKRP) with an L1 geodetic GPS receiver. The results indicated that the georeferencing conducted by PPS did not affect the characterization of spatial variability of RP or GM, neither the spatial structure relationship of these attributes.


2016 ◽  
Vol 51 (9) ◽  
pp. 1349-1358 ◽  
Author(s):  
Diego Silva Siqueira ◽  
José Marques Júnior ◽  
Daniel De Bortoli Teixeira ◽  
Sammy Sidney Rocha Matias ◽  
Livia Arantes Camargo ◽  
...  

Abstract The objective of this work was to evaluate the use of magnetic susceptibility for characterizing the spatial variability of soil attributes and identifying areas with different potentials for sugarcane (Saccharum spp.) production. Samples were collected at 110 points (1 per 7 ha) in the layers of 0.00-0.20 and 0.20-0.40 m, to determine the magnetic susceptibility and physical and chemical attributes of the soil. Fiber content, sucrose polarization (POL), and sugarcane yield were determined in 33 points. The spatial variability model for magnetic susceptibility was 63 and 22% more accurate in delimiting soil potential for sugarcane production than soil physical and chemical attributes at the 0.0-0.2 and 0.2-0.4-m layers, respectively. The spatial variability map for magnetic susceptibility was strongly correlated with clay (0.83 and 0.89, respectively, for the layers) and sand contents (-0.84 and -0.88); moderately correlated with organic matter (-0.25 and -0.35), sum of bases (-0.46 and 0.37), cation exchange capacity (0.22 and 0.47), pH (-0.52 and 0.13), and POL (0.43 and 0.53); and weakly correlated with sugarcane yield (0.26 and 0.23). Magnetic susceptibility can be used to characterize the spatial variability of soil attributes and to identify areas with different potentials for sugarcane production.


2013 ◽  
Vol 37 (1) ◽  
pp. 68-77 ◽  
Author(s):  
Marcela de Castro Nunes Santos ◽  
José Marcio de Mello ◽  
Carlos Rogério de Mello ◽  
Léo Fernandes Ávila

The spatial characterization of soil attributes is fundamental for the understanding of forest ecosystems. The objective of this work was to develop a geostatistical study of chemical and physical soil attributes at three depths (D1 - 0-20 cm; D2 - 20-50 cm; D3 - 50-100 cm), in an Experimental Hydrographic Micro-catchment entirely covered by Atlantic Forest, in the Mantiqueira Range region, Minas Gerais. All the considered variables presented spatial dependence structure in the three depths, and the largest degrees of spatial dependence were observed for pH in the three depths, soil cation exchange capacity potential in D3, soil organic matter in D1 and D3 and clay and soil bulk density in D2. The method most used for the adjustments of semi-variogram models was the Maximum Likelihood and the most selected model was the Exponential. Furthermore, the ordinary kriging maps allowed good visualization of the spatial distribution of the variables.


2004 ◽  
Vol 18 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Richard M. Petrone ◽  
J. S. Price ◽  
S. K. Carey ◽  
J. M. Waddington

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

Sign in / Sign up

Export Citation Format

Share Document