Lecture 3 - Sample Prep Flashcards

(38 cards)

1
Q

describe the general flow of food analysis

A

sampling, pre-processing, processing, testing

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2
Q

what’s the purpose of pre-treatment and sample processing?

A
  • reduce sample size
  • homogenize
  • prevent changes (contamination, deterioration)
  • avoid matrix interference
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3
Q

name some methods of reducing sample size

A
  • blenders

- coning and quartering (spice)

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4
Q

sample obtained from populations are usually (homogeneous/heterogeneous)

A

heterogenous

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5
Q

variations in properties of different units within the sample causes what?

A

sample heterogeneity

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6
Q

name some methods for homogenizing samples

A
  • grinders
  • mixers
  • slicers
  • blenders
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7
Q

mechanical homogenization often results in the undesirable production of _____

A

heat

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8
Q

grinding frozen samples in liquid nitrogen using a pre-cooled mortar and pestle is known as:

A

cryogenic grinding

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9
Q

what are 3 causes of sample loss?

A
  • dust/particulates
  • volatilization
  • adsorption
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10
Q

list sources of loss of dust/particulates

A
  • dry dust powder
  • air flows generated by changes in temp
  • breathing
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11
Q

how do you avoid loss of dust/particulates?

A
  • never open the door of a hot furnace
  • use a plug of glass or quartz wool to collect particulates when combustion is aided by stream of gas
  • ash or finely ground samples should be covered before they are moved
  • add reagents slowly to prevent losses as spray
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12
Q

list sources of loss via volatilization

A
  • during heating of samples
  • heat generated in grinding (lose water)
  • volatile metals: As, Sb, Sn, Po, Pb, Se, Hg, Ge, B
  • Cr volitized in oxidizing chloride media
  • C, P, Si volitized as hydrates
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13
Q

how do you mitigate loss from volatilization?

A

use properly sealed vessels for wet ashing

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14
Q

how do you get loss from adsorption?

A

molecules adsorb to plastic or glass containers

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15
Q

how do you mitigate adsorption losses?

A
  • use pre-treated glassware with an established hydrated layer
  • soak new glassware overnight in a dilute nitric or hydrochloric acid solution
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16
Q

when sampling, we want to (prevent/enable) change

17
Q

what are some causes of changes in samples? (5)

A
  • enzymes
  • lipid oxidation
  • microbial growth
  • physical change
  • contamination
18
Q

how do you prevent enzymatic changes?

A
  • heat denaturation
  • storage in freezer
  • pH
  • adding reducing agents to prevent oxidative enz
19
Q

(saturated/unsaturated) lipids are sensitive to oxidative degredation

20
Q

exposure to _____ can accelerate lipid peroxidation

21
Q

how do you mitigate lipid oxidation of samples?

A
  • store under nitrogen or vacuum

- use antioxidant if not interfering with analysis

22
Q

what badness do microbes bring to your samples?

A
  • degradation of food components

- introduction of microbial components

23
Q

how do you mitigate microbial changes to your sample?

A
  • addition of preservative (sodium azide)
  • low temp storage
  • freeze drying
  • storage under modified atmosphere
24
Q

what kind of conditions cause physical changes?

A
  • drying
  • fluctuating storage temp
  • fluctuating gas pressure
25
how d you mitigate physical changes?
- storage in airtight humidity controlled containers | - maintaining temperature
26
what are sources of contamination?
- airborne - reagents - glassware/equipment - facilities - cross-contamination
27
how do you reduce matrix interference?
- extraction of target analytes | - removal of interfering substances
28
methods of extracting analytes (4)
- digestion - solvent extraction - sorbent extraction - membrane extraction
29
read slide 18 and 19
ok
30
what's a confidence band?
defines statistical uncertainty of regression line
31
what's r?
correlation coefficient. tells u how well the data fits a straight line
32
what are outliers?
point outside the norm for a variable or population
33
what do outliers do?
- increase error variance - reduce power of statistical tests - decrease normality
34
how do you test for outliers?
Dixon's Q test!
35
what causes outliers?
- errors in data (human) - inherent variability of the data - sampling error - intentional misrepresentation of sample - instrument/assay condition failure - legit cases
36
how do we measure accuracy?
simple t test; determines whether the sample mean is statistically different from a known or hypothesized pop mean.
37
write the formula for a t value
aight
38
write the formula for standard error of the mean
ok