Week 1
What is sensory science?
Scientific discipline used to evoke, measure, analyze and interpret reactions to those characteristics of foods and materials as they are perceived by the senses of sight, smell, touch, taste and hearing.
Please describe nominal, ordinal, interval, vs ratio data.
Nominal - used to label, classify, code items (ex: apples, bananas, pears)
Ordinal - the data can be categorized and ranked (ex: degree of browning of toast)
Interval - the data can be categorized and ranked and evenly spaced
Ratio - similar to interval data but with a constant ratio between points and an absolute zero. generates parametric data.
Type I - rejecting a null hypothesis that is actually true
Type II - Failure to reject a null hypothesis that is actually false
What is cross-adaptation?
Adapting to one sample affects tolerance to another
Provide three possible struggles that one might experience when running sensory evaluation tests.
Time constraints, financial expenses, personnel availability, subjectivity of humans
What are 3 reasons for analyzing foods?
Quality, safety, and nutrition & health
Please describe the difference between ortho and retronasal perception
Ortho - perceived exclusively by aroma compounds in the environment
Retro - aroma perception via the oral cavity
Define flavor and the components necessary to perceive flavor
The distinctive taste of something, as perceived by taste, trigeminal sensations, and odor
List 3 principles of chromatographic separation
adsorption, hydrophobic interaction, affinity, partition, ion exchange, size exclusion
There are five methods discussed in class to minimize psychological effects. Describe three of them.
Randomization: Different serving orders for each panelist
Balance: Each serving order is presented at least once
Stabilization: keep experimental context constant across all sessions
Calibration: Calibrate panelists frame of reference
Interpretation: Draw conclusions cautiously
What is a standard of identity?
Defines what food is and what it contains
parametric data - continuous data, follows a normal distribution. analysis = t-test, ANOVA
nonparametric data - not continuous (ex: nominal data), analysis = Spearman's, Friedmans
Describe accuracy and precision and examples of measurements you can use to determine
Accuracy - is the degree of difference between observed and “true” values.
assessed by absolute or relative error
Precision - is the reproducibility of replicate observations.
assessed by standard deviation, coefficient of variation, confidence intervals, standard error of the mean, relative deviation from the mean
Provide some practical considerations for sample preparation when analyzing a food for color
Interest is primarily in how color dimensions deviate from a standard, change from batch to batch, year to year, or during processing and storage
Sampling – must be representative
Samples – often not uniform
Characteristics of sample (e.g., liquid vs. solid; transparent vs. translucent) determine appropriate:
Type of instrument
Instrument conditions
Size and thickness of sample
Number of readings
Describe destructive vs non-destructive analysis
Destructive analysis: Samples analyzed cannot be used further because of destruction or changes made during analysis
Non-destructive analysis: Analysis does not change or destroy the sample
What are the 3 tenets of ethical research?
1) Respect for persons
2) Beneficence
3) Justice
What are potential issues that may occur if utilizing an older adult population to evaluate the crispness and taste of apples?
Older adults may have poor dentition, meaning they may not be able to properly perceive crispness without the aid of an external tool (Dentures). Additionally, this population frequently suffers from a lost of taste, further affecting how they perceive an apple.
Define kinesthesis vs somesthesis in terms of food science
somesthesis: Perception via tactile nerves in hand; includes touch-pressure, temperature, pain
kinesthesis: Perception via nerves in oral cavity
There were 12 types of psychological errors discussed in class. Name and describe 6 of them
Expectation error: Information may trigger preconceived ideas
Habituation error: Tendency to repeat same scores
Stimulus error: Irrelevant criteria influence the panelist
Logical error: Two or more sample characteristics are associated in mind of panelist
Halo effect: Rating of one attribute tends to influence other attributes
Horns effect: One very negative and salient attributes of product, will influence other attributes
Mutual Suggestion: Influence by other panelists
Lack of motivation: Panelists are not comfortable and cannot sustain interest
Dumping bias: Response restriction
Proximity error: Adjacent characteristics tend to be rated similarly than those farther apart
Use of idiosyncratic error:
Central tendency
Tend to use midrange of scale
Overuse of extremes
Preferred number/range
Presentation Order error: randomize
Name and describe a visual and instrumental color specification system
Visual: Munsell
Hue: Red, Yellow, Green, Blue, Purple, Green-Yellow, Yellow-Red, Red-Purple, Purple-Blue, Blue-Green (100 hues around the circle)
Value: lightness and darkness, from white to gray to black; from zero (absolute black) to ten (absolute white)
Chroma: describes extent a color differs from a gray of the same value
Instrumental: Hunter Lab
L: lightness
a: red (+) or green (-)
b: yellow (+) or blue (-)
What is the document that contains standards of identity, grading, and quality?
Code of Federal Regulation (CFR)
Describe the four steps of sensory perception
Stimulus: stimulus hits organ, which is picked up by nerves
Sensation: Nerve signal travels to the brain
Perception: interpretation and integration of sensations
Response: formulation of response
Using the 5 steps of hypothesis testing, create an experiment that determines if consumers can perceive a difference between your already existing chips and your test chip, made with cheaper flavoring agents.
Alternative & Null hypothesis;
Null: They will not perceive a different
Alt: they will perceive a difference
2. Collect Data
3. Perform statistical test (t-test in this case)
4. Do you reject or fail to reject?
5. State your conclusion.
Define: spectroscopy, beer's law (what is states and all variables in the equation), reasons for deviations from beer's law, and factors contributing to the attenuation of a beam of light as it passes through a cuvette
spectroscopy - the science of measuring the emission or absorption of different wavelengths of visible or non-visible light
Beer's law represents the relationship between absorbance and concentration: Absorbance = (absorptivity)(path length)(concentration)
Absorbance is linear with concentration under Beer's law
Deviations:
High analyte concentration (> 10 mM), chemical processes (ionization, reversible association of molecules), polychromatic light (multiple wavelengths)
factors affecting attenuation: absorbing solution, scattering, and reflection at interfaces
Compare SPME vs SBSE
SPME (solid-phase micro extraction)
Fiber coating is bound onto a fine fused silica filament or metal filament (i.e., fiber). Fiber is immersed in the sample, or in the headspace above the sample. At end of extraction time, fiber is removed from sample (pulled into protective metal sheath), and forced through the septum of a GC. Adsorbed volatiles are thermally desorbed from fiber
SBSE (stir-bar sorptive extraction):
Magnet stir bar is jacketed with glass that is coated with layer of absorbent (polydimethylsiloxane, PDMS). Bar absorbs the analytes from sample solution while spinning. Volatiles are thermally desorbed and introduced into GC. Has much higher sensitivity than SPME