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Related Concept Videos

Sampling Plans01:23

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
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Updated: Apr 1, 2026

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
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Validation of a sampling plan to generate food composition data.

N C Sammán1, M A Gimenez1, N Bassett2

  • 1Departamento de Agroindustrias, Facultad de Ingeniería, Universidad Nacional de Jujuy, Avenida Italia esq. Martiarena, 4600 Jujuy, Argentina.

Food Chemistry
|October 5, 2015
PubMed
Summary
This summary is machine-generated.

A new food sampling methodology was developed and validated in Argentina using milk and sunflower oil. This systematic approach ensures accurate food composition analysis, enhancing data reliability for regulatory and research purposes.

Keywords:
Food compositionMethodology validationSampling planVariability

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Area of Science:

  • Food Science
  • Analytical Chemistry
  • Statistics

Background:

  • Accurate food composition data is crucial for regulatory compliance and consumer safety.
  • Developing robust food sampling plans is essential for reliable analytical results.
  • Existing methodologies may not adequately address the variability in food matrices.

Purpose of the Study:

  • To propose and validate a systematic methodology for developing food sampling plans.
  • To determine the optimal number of samples required for accurate food composition analysis.
  • To assess the reliability and accuracy of the proposed sampling plan.

Main Methods:

  • Development of a systematic food sampling plan methodology.
  • Validation using long-life whole milk, skimmed milk, and sunflower oil in Argentina.
  • Determination of fatty acid profiles, proximate composition, and calcium content using AOAC methods.
  • Calculation of sample size (n) using Cochran's formula with specified coefficients and error margins.

Main Results:

  • Calculated sample sizes (n) were 9 for whole milk, 11 for skimmed milk, and 21 for sunflower oil.
  • Experimental data yielded a calculated error (r) of ≤10%, demonstrating high accuracy.
  • The methodology proved effective in managing analyte content with high variability.

Conclusions:

  • The proposed methodology provides a reliable framework for developing systematic food sampling plans.
  • This approach enhances the accuracy and reliability of food composition analysis.
  • The validated methodology is a valuable tool for ensuring data integrity in food analysis.