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The Application of Biosensors in Monitoring Internal
Cooking Temperature in Poultry Products
Fenghua Jin
Bio-imaging & Machine Vision Laboratory
University of Maryland
Outbreak Alert!
(CSPI report, 2001)
Introduction
• Foodborne outbreaks: 76 million cases foodborne
illness occurs and 5,000 dead annually
(Morbidity and Mortality Weekly Report, 1999).
• Cost of foodborne diseases is considerable
— Annual cost of medical treatment and
productivity lost $1.8 to $4.8 billion
(Agricultural Economic report, 1996).
Introduction (cont.)
• most outbreaks are linked to inadequate cooking of meat and
poultry products
Handling the food with sufficient cooking
• What does the sufficient mean?
— Undercook  bacteria would survive and threaten
consumers’ health
— Overcook  the bacteria are cooked away, as well as meat
tenderness and juiciness
(USDA: Chicken breast: 76.7oC )
Problem
• How to confirm that the internal cooking
temperatures of meat products have reached
the requirements?
Methods to Measure Internal Cooking Temperature
• One simple Method:
Using Thermocouple
—Thermocouple is the
most widely used
temperature sensor.
What are thermocouples and how do they work?
• Any two wires of different materials can be used as a thermocouple
if connected together
• TJct : Junction temperature
• TRef: Reference temperature
• E : A low-lever DC voltage
(depends on the materials A and B, TJct , and TRef )
What are thermocouples and how do they work? (cont.)
• Thermocouple materials
—The three most common thermocouple alloys are:
1. Iron-Constantan (Type J)
2. Copper-Constantan (Type T)
3. Chromel-Alumel (Type K)
* The first named element of the pair is the positive element and the
negative wire is color coded red (current U.S. standards)
What are thermocouples and how do they work? (cont.)
• Establish Reference Temperature
— Ice Baths
accurate and inexpensive
— Electronically Controlled References
not as accurate as ice-baths but convenient
What are thermocouples and how do they work? (cont.)
• Circuit
— The signal is brought out of the reference temperature
region to a voltmeter at room temperature. This is done using
a pair of copper wires.
Limitation of the thermocouple
• It is sporadic and does not ensure that all portions of
the meat reach the required cooking temperature.
• The process is slow, invasive and susceptible to
cross-contamination.
Need new approaches to measure the internal
cooking temperatures of poultry meat
Infrared Imaging in Food Analysis
• What is Infrared Imaging?
— Infrared means "below red"
and has longer wavelength than
red light.
— Infrared light is invisible to
the unaided eye, but can be felt
as heat on one’s skin.
— Warm objects emit infrared
light.
electromagnetic spectrum
Infrared Imaging in Food Analysis (cont.)
• The theoretical foundation behind this technology is
described by Stefan-Boltzmann law:
E   T
4
— E is the radiation intensity of an emitter
— σ is Stefan-Boltzmann constant
—ε is emissivity, a material property of the object
— T is the absolute surface temperature of the object
E depends on the fourth power of T
Infrared Imaging in Food Analysis (cont.)
• Sequential Infrared images:
Temperature (oC)
95
thermocouple
83
(1)
0
70
(2)
10
(i)
Time
(second)
57
47

Advantage of Infrared Imaging
1. can measure the surface temperature of solid materials
for which it is difficult to insert the probe;
2. can measure the temperature of some material that can
erode the probe or reduce its usage time;
3. nondestructive, high-speed, automatic monitoring and
accuracy
Infrared Imaging in Food Analysis (an example)
•
Ibarra et al. (1999) developed a method using IR imaging
to estimate the internal cooking temperature in chicken
breast.
The internal temperatures recorded by thermocouples
(TCs).
External temperatures was recorded by an IR camera
Time series observations of simultaneous internal and
external temperatures were obtained.
Using Artificial Neural Network (ANN) to model the
nonlinear heat transfer process and to predict the internal
cooking temperature
Infrared Imaging in Food Analysis (an example cont.)
•
Limitations: The chicken samples had similar shape and
thickness
— Variant shapes and thickness may directly affect the
heat transfer process in meats.
 We need to extract 3D information of poultry meat
— Laser range imaging is a well-established technique to
get 3D information of the object.
Laser Range Imaging
laser projector
camera
(xi, yi)
x
lens
(0, 0, 0)
detector
.
(xs, ys, zs)
f
y
z
zref
θx (xo, yo, zo)
d object
encoder pulse
z

z 1 
xz
d 
ref
o
i
ref
f
x
s
( Z ref  Z o )
cos  x
Artificial Neural Network Modeling
•
Internal temperature
•
External temperature
•
3D information of poultry meat
 use Artificial Neural Network to model the nonlinear heat
transfer process and to predict the internal cooking
temperature
Introduction to Artificial Neural Network
hidden layer
input layer
output layer
wij
bi
Inputs: p
Outputs: a
node
•
Two procedures of ANN modeling:
— Learning
— Testing
Learning Process
Initialize W, b
a p
f W a  b
aa
0
a
m 1

m 1
m 1
m
m 1

M
Calculate E
Stop
Y
E=0
E < Emax
E: Performance index;
N
Emax: Performance goal.
W = W + ∆W
b = b + ∆b
* performance of network is defined by performance index
e.g.: mean square errors (MSE)
Two procedures of ANN modeling
• Training
weights and biases of the ANN were determined by the
ANN training process;
.
• Testing
The surface temperature and the geometric information
were inputted into the ANN to predict the internal cooking
temperature in chicken samples.
Illustration of the IR and laser range imaging system
IR camera
Laser
projector
Oven
CCD
camera
Oven
Infrared Camera
Laser projector and CCD cameral
T type thermocouple
System block diagram
ANN Modeling
Endpoint
Temperature
Monitoring System
Internal Temperature
Recording
IR Imaging
Cooking System
Laser Range Imaging
Extended real-time endpoint temperature
estimation system
ANN Modeling
Endpoint
Temperature
Monitoring System
IR Imaging
Laser Range Imaging
Cooking System
Decision
System
Control
Unit