Lecture 3 - Sample Prep and Data Handling Flashcards

1
Q

General flow of food analysis?

A
  1. sampling
  2. preprocessing
  3. processing
  4. testing
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2
Q

why sample pre treatment and sample processing?

A
  • reduce sample size
  • make samples homogenous
  • prevents changes in samples (contamination and deterioration)
  • avoids matrix interference during analysis
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3
Q

lab samples (large quantity: ie 1kg) need to be reduced to….

A

analytical sample (small quantity: ie 2-5g)

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4
Q

what does the methods used for sample size reduction depend on?

A

the physical form of the sample

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5
Q

what is coning and quartering for?

A

used for powder samples

in reducing sample size

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6
Q

samples obtained from population is usually…

A

heterogeneous

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7
Q

what are reasons that there may be sample heterogeneity?

A

variations of different units within a sample (ie milk from different cows)

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8
Q

what is cryogenic grinding?

A

grinding frozen samples in liquid N using pre-cooled mortar and pestle

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9
Q

reasons for sample losses as dust or particulates during preparation ?

A
  • dry dust powder
  • air flows generated by changes in temperate (ie opening furnace when hot)
  • breathing onto dry powder sample
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10
Q

how to reduce dry dust sample losses during preparation?

A
  • don’t open hot furnace door
  • cover ash or ground samples
  • add reagents slowly to prevent losses as spray
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11
Q

reasons for sample losses through volatilization?

A
  • during heating of samples

- decrease in water during grinding solids b/c of localized heating

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12
Q

how to reduce sample losses through volatilization

A

use properly sealed vessels for wet ashing

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13
Q

chromium can be volatilized under oxidizing conditions in the presence of…?

A

chloride

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14
Q

reasons for losses due to absorption?

A

absorption of molecules to plastic or glass containers

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15
Q

how to avoid losses due to absorption?

A
  • use pretreated glassware with a hydrated layer

- soak new glassware overnight in dilute nitric of HCl solution

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16
Q

5 common types of changes that can occur in samples?

A
  • enzymatic inactivation
  • lipid oxidation
  • microbial growth
  • physical change
  • contamination
17
Q

how to avoid enzymatic degradation in samples?

A
  • heat denaturation (Blanching)
  • storage in freezer (-20 to -30)
  • pH
  • adding reducing agents to prevent oxidative enzymes
18
Q

how to avoid lipid oxidation in samples?

A
  • store under nitrogen or vacuum

- use antioxidant

19
Q

why does lipid oxidation occur?

A
  • unsaturated lipids are sensitive to oxidative degradation

- exposure to light can accelerate lipid peroxidation

20
Q

how to avoid microbial growth?

A
  • add preservatives (eg sodium azide)
  • low temp strorage
  • freeze drying
  • storage under modified atmosphere
21
Q

why does microbial growth occur in samples?

A
  • microbial contamination

- foreign microbial components introduced

22
Q

why does physical change occur?

A

caused by

  • drying
  • fluctuating storage temperature (eg ice cream)
  • fluctuating gas pressure
23
Q

how to avoid physical changes?

A

storage in air tight humidity controlled containers

maintain temp

24
Q

sources of contamination?

A

airborne (moisture and dust)

reagents

glassware/equipment

facilities

cross contamination

25
what are the 2 steps needed for reducing matrix interference?
1. extraction of target analytes | 2. removal of interfering substances
26
why do you need to reduce matrix interference?
matrix components can interfere with assay eg pigments interfering with colorimetric assay for reducing sugars
27
4 methods of analyte extractions?
digestion solvent extraction sorbent extraction membrane extraction
28
what type of extraction method is microwave and UV photolysis?
digestion
29
what are examples of technologies that need no or minimal processing?
MRI (magnetic resonance imaging) infralab-e series: infra red spectroscopy based instruments for measuring moisture, fat, protein, collagen content of meat
30
which axis is the concentration and peak area on the standard curve?
independent variable: concentration = x axis dependent variable: peak area = y axis y = ax + b
31
what is the confidence band?
defines statistical uncertainty of the regression line
32
what is the correlation coefficient (r)
defines how well the data fits to a straight line want value of r as close to +1.00 or -1.00 as possible
33
what is an outlier
a data point that is far outside the norm for a variable or population they: - increase error variance - reduce the power of statistical tests - decreases normality
34
how to determine outlier value? (equation)
dixon Q test Q value = (X2-X1)/W where X1 = outlier value X2 = next closest vale to X1 W= total spread of all values obtained by subtracting the lowest value from the highest value
35
reasons for outlier data
- data errors (human error, error in data collection, recording, entry) - sampling error - intentional misrepresentation of sample - instrument/assay condition failure - legitimate cases =need to be probed