Optimizing Seed Sample Size for Zinc and Iron Analysis of Wild and Cultivated Lentil

2017 ◽  
Vol 48 (13) ◽  
pp. 1584-1594 ◽  
Author(s):  
S. S. Kundu ◽  
R. Podder ◽  
K. E. Bett ◽  
J. J. Schoenau ◽  
A. Vandenberg
2001 ◽  
Vol 84 (6) ◽  
pp. 1941-1946 ◽  
Author(s):  
Thomas B Whitaker ◽  
Larry Freese ◽  
Francis G Giesbrecht ◽  
Andrew B Slate

Abstract Using the binomial distribution, the effect of sample size on the variability among sample test results when sampling a lot with 1.0% genetically modified (GM) or biotech seed was evaluated. The coefficient of variation, cv, among 500-seed sample test results taken from a lot with truly 1.0% was computed to be 44.5%. Increasing sample size to 1000 seeds reduced the cv among sample test results to 31.5%. The effects of sample size and accept/reject limits on the buyer's risk (bad lots accepted) and the seller's risk (good lots rejected) was also evaluated assuming a tolerance of 1.0% GM seed. Increasing sample size decreases both the buyer's and seller's risks at the same time. Using an accept/reject limit below the regulatory tolerance decreases the buyer's risk, but increases the seller's risk. Using an accept/reject limit above the regulatory tolerance decreases the seller's risk but increases the buyer's risk.


2005 ◽  
Vol 112 (1) ◽  
pp. 268-279 ◽  
Author(s):  
Richard B. Anderson ◽  
Michael E. Doherty ◽  
Neil D. Berg ◽  
Jeff C. Friedrich
Keyword(s):  

2011 ◽  
Author(s):  
M. Lopez-Ramon ◽  
C. Castro ◽  
J. Roca ◽  
J. Lupianez

2009 ◽  
Author(s):  
Dennis L. Jackson ◽  
Marc Frey ◽  
Jennifer Voth
Keyword(s):  

2007 ◽  
Author(s):  
Natalie A. Obrecht ◽  
Gretchen B. Chapman ◽  
Rochel Gelman

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