Abstract
Composite sampling techniques are compared with random sampling methods for determining pesticide concentrations in agricultural fields. Estimates of mean pesticide concentrations and associated standard errors are presented for different experimental conditions. Variance components defined in extended forms of the Brown-Fisher model are estimated. The method of nonlinear least squares was employed to obtain numerical estimates of variance components by equating observed mean squares to expected mean squares for appropriate sampling designs.
Keywords
Composite Sampling, Nonlinear Models
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Parrish, R. S.; Ware, G. O.; Smith, C. N.; and Banks, P. A.
(1990).
"COMPOSITE SAMPLING TECHNIQUES FOR DETERMINING PESTICIDE CONCENTRATIONS,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1429
COMPOSITE SAMPLING TECHNIQUES FOR DETERMINING PESTICIDE CONCENTRATIONS
Composite sampling techniques are compared with random sampling methods for determining pesticide concentrations in agricultural fields. Estimates of mean pesticide concentrations and associated standard errors are presented for different experimental conditions. Variance components defined in extended forms of the Brown-Fisher model are estimated. The method of nonlinear least squares was employed to obtain numerical estimates of variance components by equating observed mean squares to expected mean squares for appropriate sampling designs.
