Lecture 3 - Sample Prep and Data Handling Flashcards
General flow of food analysis?
- sampling
- preprocessing
- processing
- testing
why sample pre treatment and sample processing?
- reduce sample size
- make samples homogenous
- prevents changes in samples (contamination and deterioration)
- avoids matrix interference during analysis
lab samples (large quantity: ie 1kg) need to be reduced to….
analytical sample (small quantity: ie 2-5g)
what does the methods used for sample size reduction depend on?
the physical form of the sample
what is coning and quartering for?
used for powder samples
in reducing sample size
samples obtained from population is usually…
heterogeneous
what are reasons that there may be sample heterogeneity?
variations of different units within a sample (ie milk from different cows)
what is cryogenic grinding?
grinding frozen samples in liquid N using pre-cooled mortar and pestle
reasons for sample losses as dust or particulates during preparation ?
- dry dust powder
- air flows generated by changes in temperate (ie opening furnace when hot)
- breathing onto dry powder sample
how to reduce dry dust sample losses during preparation?
- don’t open hot furnace door
- cover ash or ground samples
- add reagents slowly to prevent losses as spray
reasons for sample losses through volatilization?
- during heating of samples
- decrease in water during grinding solids b/c of localized heating
how to reduce sample losses through volatilization
use properly sealed vessels for wet ashing
chromium can be volatilized under oxidizing conditions in the presence of…?
chloride
reasons for losses due to absorption?
absorption of molecules to plastic or glass containers
how to avoid losses due to absorption?
- use pretreated glassware with a hydrated layer
- soak new glassware overnight in dilute nitric of HCl solution
5 common types of changes that can occur in samples?
- enzymatic inactivation
- lipid oxidation
- microbial growth
- physical change
- contamination
how to avoid enzymatic degradation in samples?
- heat denaturation (Blanching)
- storage in freezer (-20 to -30)
- pH
- adding reducing agents to prevent oxidative enzymes
how to avoid lipid oxidation in samples?
- store under nitrogen or vacuum
- use antioxidant
why does lipid oxidation occur?
- unsaturated lipids are sensitive to oxidative degradation
- exposure to light can accelerate lipid peroxidation
how to avoid microbial growth?
- add preservatives (eg sodium azide)
- low temp strorage
- freeze drying
- storage under modified atmosphere
why does microbial growth occur in samples?
- microbial contamination
- foreign microbial components introduced
why does physical change occur?
caused by
- drying
- fluctuating storage temperature (eg ice cream)
- fluctuating gas pressure
how to avoid physical changes?
storage in air tight humidity controlled containers
maintain temp
sources of contamination?
airborne (moisture and dust)
reagents
glassware/equipment
facilities
cross contamination
what are the 2 steps needed for reducing matrix interference?
- extraction of target analytes
2. removal of interfering substances
why do you need to reduce matrix interference?
matrix components can interfere with assay
eg pigments interfering with colorimetric assay for reducing sugars
4 methods of analyte extractions?
digestion
solvent extraction
sorbent extraction
membrane extraction
what type of extraction method is microwave and UV photolysis?
digestion
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
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
what is the confidence band?
defines statistical uncertainty of the regression line
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
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
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
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
