Within and between field variability of residue data and sampling implications

Area of Science:

• Agricultural Science
• Environmental Chemistry
• Food Safety

Background:

• Accurate estimation of acute dietary pesticide exposure depends on understanding residue variability in individual fruits and vegetables.
• Field experiments are crucial for reflecting commercial farming practices and residue distribution.

Purpose of the Study:

• To investigate the distribution of pesticide residues in various crops (apples, kiwi, potatoes, butter beans).
• To determine the necessary sample sizes for estimating residue percentiles at specific confidence levels.
• To identify factors influencing residue distribution and propose variability factors for risk assessment.

Main Methods:

• Field experiments were conducted on apples, kiwi fruits, potatoes, and butter beans under commercial farming conditions.
• Statistical analysis of residue concentration data, including frequency distributions and log-normal transformations.
• Calculation of required sample sizes for estimating 99th, 97.5th, and 95th percentiles of residues at a 95% confidence level.

Main Results:

• Pesticide residue distributions were continuous and positively skewed, not normalizing with log-transformation.
• No correlation was observed between residue concentration and the mass of apples.
• Sample sizes of 299, 120, and 59 are recommended for estimating 99th, 97.5th, and 95th percentiles, respectively.
• Residue distribution was not significantly affected by factors like mean residue or pesticide properties, but influenced by plant characteristics and application method.

Conclusions:

• Pesticide residue variability in crops necessitates specific sampling strategies beyond simple random sampling.
• Recommended variability factors are 5 for medium-sized fruits and 9 for potatoes after granular pesticide application.
• Understanding residue distribution is key for refining dietary exposure assessments and pesticide risk management.