Sampling Strategy
Sampling Strategy - Related Videos
09:27
A Rapid Strategy for the Isolation of New Faustoviruses from Environmental Samples Using Vermamoeba vermiformis
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Cited by 15 •
2016
We describe here the latest advances in viral isolation for the characterization of new genotypes of Faustovirus, a new asfarvirus-related lineage of giant viruses. This protocol can be applied to the high throughput isolation of viruses, especially giant viruses infecting amoeba.
05:07
Sampling Strategies and Processing of Biobank Tissue Samples from Porcine Biomedical Models
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Cited by 20 •
2018
The practical application and performance of methods for generation of representative tissue samples of porcine animal models for a broad spectrum of downstream analyses in biobank projects are demonstrated, including volumetry, systematic random sampling, and differential processing of tissue samples for qualitative and quantitative morphologic and molecular analyses types.
08:14
Sample Preparation Strategies for Mass Spectrometry Imaging of 3D Cell Culture Models
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Cited by 49 •
2014
Immortalized cancer cell lines can be grown as 3D cell cultures, a valuable model for biological research. This protocol describes mass spectrometry imaging of 3D cell cultures, including improvements in the sample preparation platform. The goal of this protocol is to instruct users to prepare 3D cell cultures for mass spectrometry imaging analysis.
10:14
Tactile Conditioning And Movement Analysis Of Antennal Sampling Strategies In Honey Bees (Apis mellifera L.)
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Cited by 9 •
2012
In this protocol we show how to condition harnessed honey bees to tactile stimuli and introduce a 2D motion capture technique for analyzing the kinematics of fine-scale antennal sampling pattern.
09:45
New Variations for Strategy Set-shifting in the Rat
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Cited by 3 •
2017
Set-shifting, a form of behavioral flexibility, requires an attentional shift from one stimulus dimension to another. We extended an established rodent set-shifting task1 by requiring attention to different stimuli according to context. The task was combined with specific lesions to identify neuron subtypes underlying a successful shift.
FAQs
Heterogeneity can cause analytes to vary across locations, times, or portions of the material, so a single collection point may not reflect the larger population. The strategy must therefore account for analyte distribution and select sampling locations and conditions accordingly. Addressing this variation improves the reliability of results and reduces the risk of drawing conclusions from an unrepresentative portion.
Random sampling selects material without a planned positional pattern, whereas systematic sampling follows an organized pattern across the population or process. Stratified sampling divides the material or environment into relevant groups before collection, and replicate sampling collects repeated samples to evaluate consistency. These approaches address different sources of variation and can be selected according to the population structure and analytical objective.
Sample size determines how much of the chemical population contributes to the analytical result, while replicate samples provide evidence about consistency among collections. If the sampled material varies substantially, limited sampling may fail to capture that variation. Planning both factors helps improve precision and supports more defensible interpretation of measurements in chemistry-related investigations.
After collection, samples require appropriate preservation, preparation, and analysis. Preservation helps maintain the material in a condition suitable for measurement, while preparation makes it compatible with the selected analytical process. Recording where and when each sample was taken supports traceability throughout these stages. Together, these steps connect field or process collection with interpretable chemical results.
Contamination risk should be considered when deciding where, when, and how material is collected and handled. A strategy that accounts for this risk helps distinguish analytes originating from the investigated material from substances introduced during sampling or subsequent preparation. Maintaining traceability across collection and analysis further supports identification of potential problems and strengthens confidence in the resulting measurements.
Chemists apply sampling strategies in quality control, environmental monitoring, pharmaceutical testing, and research. The resulting measurements can indicate whether analytical results represent the material or system under investigation and can support assessment of reliability and precision. The same planning principles can be adapted to process materials, environmental populations, pharmaceutical samples, or experimental systems, depending on the analytical purpose.