PMID- 29902006
OWN - NLM
STAT- MEDLINE
DCOM- 20180829
LR  - 20181202
IS  - 1520-5118 (Electronic)
IS  - 0021-8561 (Linking)
VI  - 66
IP  - 27
DP  - 2018 Jul 11
TI  - Statistical Techniques to Analyze Pesticide Data Program Food Residue 
      Observations.
PG  - 7165-7171
LID - 10.1021/acs.jafc.8b00863 [doi]
AB  - The U.S. EPA conducts dietary-risk assessments to ensure that levels of 
      pesticides on food in the U.S. food supply are safe. Often these assessments 
      utilize conservative residue estimates, maximum residue levels (MRLs), and a 
      high-end estimate derived from registrant-generated field-trial data sets. A more 
      realistic estimate of consumers' pesticide exposure from food may be obtained by 
      utilizing residues from food-monitoring programs, such as the Pesticide Data 
      Program (PDP) of the U.S. Department of Agriculture. A substantial portion of 
      food-residue concentrations in PDP monitoring programs are below the limits of 
      detection (left-censored), which makes the comparison of regulatory-field-trial 
      and PDP residue levels difficult. In this paper, we present a novel adaption of 
      established statistical techniques, the Kaplan-Meier estimator (K-M), the robust 
      regression on ordered statistic (ROS), and the maximum-likelihood estimator 
      (MLE), to quantify the pesticide-residue concentrations in the presence of 
      heavily censored data sets. The examined statistical approaches include the most 
      commonly used parametric and nonparametric methods for handling left-censored 
      data that have been used in the fields of medical and environmental sciences. 
      This work presents a case study in which data of thiamethoxam residue on bell 
      pepper generated from registrant field trials were compared with PDP-monitoring 
      residue values. The results from the statistical techniques were evaluated and 
      compared with commonly used simple substitution methods for the determination of 
      summary statistics. It was found that the maximum-likelihood estimator (MLE) is 
      the most appropriate statistical method to analyze this residue data set. Using 
      the MLE technique, the data analyses showed that the median and mean PDP bell 
      pepper residue levels were approximately 19 and 7 times lower, respectively, than 
      the corresponding statistics of the field-trial residues.
FAU - Szarka, Arpad Z
AU  - Szarka AZ
AUID- ORCID: 0000-0003-2330-2493
AD  - Operator and Consumer Safety , Syngenta Crop Protection, LLC , Greensboro , North 
      Carolina 27419 , United States.
FAU - Hayworth, Carol G
AU  - Hayworth CG
AD  - Operator and Consumer Safety , Syngenta Crop Protection, LLC , Greensboro , North 
      Carolina 27419 , United States.
FAU - Ramanarayanan, Tharacad S
AU  - Ramanarayanan TS
AD  - Operator and Consumer Safety , Syngenta Crop Protection, LLC , Greensboro , North 
      Carolina 27419 , United States.
FAU - Joseph, Robert S I
AU  - Joseph RSI
AD  - Operator and Consumer Safety , Syngenta Crop Protection, LLC , Greensboro , North 
      Carolina 27419 , United States.
LA  - eng
PT  - Journal Article
DEP - 20180626
PL  - United States
TA  - J Agric Food Chem
JT  - Journal of agricultural and food chemistry
JID - 0374755
RN  - 0 (Neonicotinoids)
RN  - 0 (Nitro Compounds)
RN  - 0 (Oxazines)
RN  - 0 (Pesticide Residues)
RN  - 0 (Thiazoles)
RN  - 747IC8B487 (Thiamethoxam)
SB  - IM
MH  - Capsicum
MH  - Dietary Exposure/*analysis/statistics & numerical data
MH  - Food Contamination/*analysis/*statistics & numerical data
MH  - Humans
MH  - Kaplan-Meier Estimate
MH  - Likelihood Functions
MH  - Limit of Detection
MH  - *Models, Statistical
MH  - Neonicotinoids/analysis
MH  - Nitro Compounds/analysis
MH  - Oxazines/analysis
MH  - Pesticide Residues/*analysis
MH  - Regression Analysis
MH  - Thiamethoxam
MH  - Thiazoles/analysis
MH  - United States
OTO - NOTNLM
OT  - Kaplan-Meier survival analysis
OT  - censored data
OT  - dietary-risk assessment
OT  - maximum-likelihood estimator
OT  - pesticide food monitoring
OT  - regression on ordered statistic
EDAT- 2018/06/15 06:00
MHDA- 2018/08/30 06:00
CRDT- 2018/06/15 06:00
PHST- 2018/06/15 06:00 [pubmed]
PHST- 2018/08/30 06:00 [medline]
PHST- 2018/06/15 06:00 [entrez]
AID - 10.1021/acs.jafc.8b00863 [doi]
PST - ppublish
SO  - J Agric Food Chem. 2018 Jul 11;66(27):7165-7171. doi: 10.1021/acs.jafc.8b00863. 
      Epub 2018 Jun 26.