Estimating Sample Size of Soil Cone Index Profiles by Bootstrapping
Alesso, Carlos Agustín, Masola, María Josefina, Carrizo, María Eugenia, Imhoff, Silvia Del Carmen
Rev. Bras. Ciênc. Solo
DATA DE PUBLICAÇÃO
ABSTRACT Measurements of the soil cone index are widely used to assess soil resistance to root penetration (SR) and to monitor the soil compaction status of agricultural fields. However, soil sampling for SR estimation is a rather challenging task in view of the high spatial and temporal variability of the soil. This study proposed a bootstrapping method to determine the minimum sample size required to estimate the vertical profile of mean soil cone index (CI) values at different levels of precision and confidence. For this purpose, CI data from a Typic Argiudoll under no-tillage before and after chiseling was used. A total of 151 CI profiles were recorded before and after chiseling in a 3,200 m2 (40 × 80 m) no-tillage area at sampling points distributed on a horizontal 5 × 5 m aligned grid and from the top layer to 0.40 m depth by in 0.02 m intervals. A modified bootstrap routine was developed to estimate the sampling distribution of the sample mean and medians of CI values per layer. The minimum sample size to estimate the vertical profile of mean CI values at different levels of precision and confidence was determined from data of the whole soil profile, including the autocorrelation of CI readings in the vertical direction. Tilling increased the variability of this measurement and thus the sampling efforts to achieve the same level of precision and confidence were different before and after the procedure. The standard errors of sample medians estimated by bootstrapping were higher than those corresponding to sample means. In addition, to achieve the same level of precision and confidence, the estimation of the vertical profile of mean CI values based on sample medians required more observations than based on sample means. This study shows that the viability of the bootstrap approach to determine the implications of soil variability on the sampling efforts required for an accurate estimation of the vertical distribution of resistance in soils under different managements.
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