The Future of Quality Traits
Analysis
Charles R. Hurburgh, Jr.,
Professor
Agricultural and Biosystems
Engineering
September 19, 2007
General Outline
• Product Quality Control
– Near Infrared Analysis
– Measurement Uniformity
– Quality Factors and Production Control
• Process Quality Control
– Traceability,
– Consistency within Use
NIRS Instruments
• Monochromator
– Bruins/Dickey-john Omega G
– Foss Infratec 122x and 1241
– Foss NIRSystems 6500
T
T
R
NIRS Instruments
• Array Detection
– Zeiss Corona
– Perten DA7200
– ASD Lab Spec Pro
R
R
R
Image Data
False-color signal @ 850 nm
• Kernels were scanned in transmittance
• 750 – 1090 nm ( approx. 5 nm increment)
Image Scanning
Source: www.specim.fi
NIRS Can Be Very Accurate
Protein NIR C 2005 Soybeans
50.00
50.00
45.00
45.00
CNAProtein @13% MB
CNAProtein @13% MB
Protein NIR A 2005 Soybeans
40.00
35.00
y = 0.9971x + 0.0467
R2 = 0.9781, SD = 0.51
30.00
25.00
25.00
y = 1.0321x - 1.4556
R2 = 0.9817, SD = 0.48
40.00
35.00
30.00
30.00
35.00
40.00
45.00
50.00
25.00
25.00
30.00
NIR A Protein
35.00
40.00
45.00
50.00
NIR C Protein
Protein NIR B 2005 Soybeans
Protein NIR D 2005 Soybeans
50.00
50.00
45.00
CNAProtein @13% MB
CNA Protein @13% MB
45.00
y = 0.9823x + 0.9591
R2 = 0.9689, SD =0.70
40.00
35.00
y = 0.9751x + 0.8264
R2 = 0.9718, SD = 0.55
40.00
35.00
30.00
30.00
25.00
25.00
25.00
25.00
30.00
35.00
40.00
NIR D Protein
45.00
50.00
30.00
35.00
40.00
NIR B Protein
45.00
50.00
Comparison of NIR Units
Protein NIR A vs NIR C 2005 Soybeans
45.0
Protein NIR D vs NIR C 2005 Soybeans
40.0
50.0
35.0
y = 0.9971x + 0.0467
R2 = 0.9781, SD =0.40
30.0
25.0
25.0
30.0
35.0
40.0
45.0
50.0
NIR A Protein
Similar technology (transmittance)
NIR C Protein @13% MB
NIR C Protein @13% MB
50.0
45.0
y = 1.0127x - 0.9198
R2 = 0.9075, SD = 1.13
40.0
35.0
30.0
25.0
25.0
30.0
35.0
40.0
45.0
NIR D Protein
Reflectance vs. Transmittance
50.0
NIRS Corn Factors
• Moisture, Protein, Oil, Crude Starch
– USDA-GIPSA does M, P, O
• Density (specific gravity)
• Functional properties (Indirect)
– Extractable Starch (Wet-Mill)
?????
– Fermentable Starch (Dry Grind) ?????
• Correlations with others?
• Amino Acids-No one yet but ….
Perten DA7200 Corn
NIR Standardization - Corn Protein
16.0
15.0
14.0
NIR Protein (%)
13.0
12.0
11.0
10.0
y = 0.9085x + 0.4575
R2 = 0.986
9.0
8.0
7.0
6.0
6.0
8.0
10.0
12.0
Reference Protein (%)
14.0
16.0
NIR Calibration
Spectral Data
X
Regression
algorithm
Mathematical relationship
(calibration model)
Y=f (X)
Constituent concentration
Y
(standard wet chemistry
methods)
Multiple Linear Regression (MLR)
Principal Component Regression
(PCR)
Partial Least Squares (PLS)
Artificial Neural Networks (ANN)
Locally Weighted Regression (LWR)
Support Vector Machines (SVM)
ISU-GQL NIR Quality Control
NIR Daily Check Control Chart
Soybeans Protein Daily Check, IT 1241 12410350, Sample
20010461
38.8
38.6
Protein (%)
38.4
38.2
38.0
Method 1
Method 2
37.8
37.6
37.4
37.2
11/09/04
Data
02/17/05
10 MA
05/28/05
UCL MA
09/05/05
12/14/05
Date
LCL MA
UCL
Mean
03/24/06
LCL
07/02/06
10/10/06
10 per. Mov. Avg. (Data)
NIR Duplicates Differences Control
Chart
Soybeans Protein Duplicate Differences, IT 1229
553075, 2005
2.0
Method 1
Duplicate Diff. (%)
1.5
1.0
0.5
0.0
-0.5
0
50
100
-1.0
150
200
Method 2
-1.5
Number
Differences
Mean1
UCL1
LCL1
Mean2
UCL2
LCL2
Be Sure Everyone Agrees on the
Reference Method
Acid Hydrolysis vs Ether Extract, Corn Oil 2004, dry basis
10.00
Acid Hydrolysis Oil, %
9.00
8.00
7.00
6.00
y = 1.0134x + 0.9138
R2 = 0.8459
SEP= 0.29
5.00
4.00
3.00
2.00
2.00
3.00
4.00
5.00
6.00
7.00
Ether Extract Oil, %
8.00
9.00
10.00
The Future of Grain Analytics
• Very high throughput (100s/hour)
• Single Seed Analysis
– Brimrose Seed Meister
– ARS Light Tube
– Flat Deck Image Scanner
• Robiotics
• Automated ELISA
• NMR
74
Plants
66Potential
Planned +Iowa
current
in Iowa
63
11Just
Just across
across the
borders
11
IA Borders
*
*
*
*
*
* HowardWinnesh
Osceola
* DickensonEmmet
* Mitchell
* WinnebagoWorth
Allamakee
iek
*
O’Brien Clay Palo
* Kosuth Hancoc * Floyd
Sioux*
* * *Chickasaw Fayette
C
erroG
ordo
Alto
*
k
Clayton
Humbol
Cherokee
* BuenaV*ista Pocahontas dt* *Wright Franklin Butler Bremer
Plymouth
*
*
*
*
BlackHawk Buchana Delawa
*a *Sac Calhoun Webster
* Hamilton
Woodbury Id
*
re
** Grundy
Hardin
n
*
*
Lyon
Tama
*
Monona Crawford Carroll Greene
*
*
*
*
Shelby Audubon Guthrie
*Pottawattamie
Mills
*
Fremont
Figure 1.
Boone
*
Harrison
*
*
Montgomery
*Page
Adair
Cass
*
Adams
*
Story
r
*
Dalla Polk
s
Madis
on
*
Union
Marshal
l
Jasper
Benton
n
Jackson
Jones
* ** **
*
Poweshiek
Johnson
Cedar
Iowa
*
Mucatine
*
Warren Marion
Mahask Keokuk
a
Clarke
Linn
Dubuque
Lucas Monroe
Taylor Ringgold Decatur Wayne
Appanoose
*Wapello
Davis
*
Scott *
Clinton
n
Washington
Jefferson
Louisa
Henry
*
DesMoines
VanBuren Lee
Capacity: 139%
129% of
Capacity:
of 2006
2006crop
Crop
*
corn
processing
&
plants,
current
&&planned,
06
Iowa
processing
& ethanol
ethanol
plants,
current
planned,
10/26/06
Iowa
Corn
Processing
Plants,
Current
& Actual
Planned,
3/16/07
Iowa
Corn
Processing
& Ethanol
Plant
Locations,
Locations,
Actual
&
& Planned
Planned.
, 11/20/
. 9/26/06
Value Added Agriculture Program
Current Iowa Dry-Grind plants
• Average production
– 60 million gal/yr
• Range
– 20 mgy – 110 mgy
• Plants produce at 105-110%
above rated capacity
• Most have outbound rail access
• Few (none) have unit-train inbound rail access
www.iavaap.org
Value Added Agriculture Program
Corn consumption and storage
Current capacity*
(mil gal)
Minimum
Maximum
24.0
120.0
Corn Usage*
(million bu)
8.6
42.9
Average
64.6
22.4
Std. Dev.
27.6
10.1
Sum
1,448.0
516.1
Corn Storage*
(thousand bu)
220
5,500
1,214
1,108
27,920
19,420**
Corn Percent*
(storage/usage)
1.87 %
59.23 %
7.79 %
(4.38%)**
12.54 %
n/a
*Represents 23 dry-grind plants in 2006
**Without two “high storage” plants
Distillers Grains storage
2.62%
www.iavaap.org
Value Added Agriculture Program
Corn sources for ethanol plants
• 62% of corn is purchased directly from
farmers
• 16 plants purchase >50% of corn from
farmers
• 5 plants tied to local elevators; 60-95% of
corn comes from elevator
www.iavaap.org
Value Added Agriculture Program
Corn Quality
• US Grade #2 Yellow Corn - no premium for better
quality or special traits
• Moisture limit: 17% (a few take 18%)
• Test Weight low limit: 54 lb/bu
• Damage limit: 10% (discount from 5%)
• Broken Corn: 12% max
Producers must meet #2YC quality spec to sell to
ethanol plants. Otherwise, corn is rejected.
www.iavaap.org
Value Added Agriculture Program
Producer Awareness of
Ethanol Quality Needs
• Aware of specific quality requirements
– 28.6% Yes
– 71.4% No
• Believe that quality must be higher for EtoH
– 1(no) – 5(yes) Scale: 2.9 average
– Only moderately aware.
Iowa Rural Life Poll, 2007 Preliminary
www.iavaap.org
Traceability
Ability to trace the history, application or location of an
entity by means of recorded identifications. (EU 1830)
 Respond to security threats
 Respond to food safety problems
 Document chain-of-custody
 Document production practices (eg. organic)
 Meet consumer desires or social preferences
 Provide safety/quality assurance
 Protect integrity of brand name
 Authenticate claims (eg. Regional foods)
 Regulatory compliance – FDA Bioterror Rules
 Analyze logistics and production costs
 Validate production or revenue claims
Overview of Bioterrorism Act
Establishment and Maintenance of
Records Final Rule
Leslye M. Fraser, Esq.
Director, Office of Regulations and Policy
Center for Food Safety and Applied Nutrition
Example 1: Common Storage Silo
for An Ingredient (e.g., Flour)
Source
B
Source
A
Source
C
Common
Storage
Silo
Cookies
Manufacturing
Plant
Information reasonably available is the identity of all potential sources of the
flour for each finished product
Wheat Gluten in Pet Food
5/2007 and Still Growing
Mass recall of dog and cat food after pets die
FDA Announces New Chemical Found in Recalled Pet Food
Breaking News From FDA Confirms ASPCA's
Suspicions on Pet Food Toxin
Presence of Melamine Identified in Contaminated
Food
Trends in Corn Quality
• Food and processing systems diverging
gradually.
• Direct food consumption-lower volume
• Monogastric animal nutrition=food
• Food/feed: Protein, amino acids, hardness
• Processing: Low protein, soft, high starch
• Corn oil – biodiesel feedstock; oleic acid
• Where is the niche for GEM?
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