vollautomatisierung von fermentationen mittels ft-nir ... · vollautomatisierung von fermentationen...
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Vollautomatisierung von Fermentationen mittels FT-NIR Spektroskopie:
Eine Innovation mit signifikantem Potential
Ramón Mira de Orduña HeidingerHaute Ecole Spécialisée de Suisse Occidentale
Ecole d’Ingénieurs de Changins
Charles FrohmanCornell University, Takasago
Haute Ecole Spécialisée de Suisse OccidentaleEcole d’Ingénieurs de Changins
Nyon
Saccharomyces cerevisiaeAn excellent production organism
• Acid tolerant• Anaerobic / aerobic metabolism• Robust growth• Large number of molecular tools
• Traditional fermentations• wine, beer, bread
• Modern applications• bio-fuels• proteins• aromas
Industrial Batch FermentationsExample: alcoholic fermentation
0 100 200 3000
100
200
300
0
5
10
15
Eth
anol
(% v
/v)
To
tal S
ugar
(g/L
)
Time (h)
• Large concentration gradients
• Substrate feedback inhibition• Sluggish / failed
fermentations• Increased spoilage risk
• High gravity media• may be desriable for efficiency reasons• may be imposed
• hot climates, sweet wines• Increased by-product formation
• Acetic acid• Glycerol• Acetaldehyde
• Reduced Product yields• Fermentation failures
Industrial Batch FermentationsOsmotic stress response
Fermentation Control in Enology • Temperature control• Measure fermentation rate manually
ThermostatSet-point: 14°CProcess variable: 16°C Cool!
Current measurement units
Fermentation rateSet-point: 1 Brix/dayProcess variable: 1.2 Brix/day Cool!
Fermentation monitor
0 2 4 6 8 1 00
2
4
6
8
1 0
1 2
1 4
1 6
1 8
2 0
2 2
AF
Rat
e
T im e
Automated Fermentation RateControl
• Automated temperature & fermentation rate control– Remote monitoring of fermentations (cell phones)– Adapt temperature to fermentation– Recognize sluggish/stuck AF early on– Coordinate/reduce cooling energy utilization
across entire winery– Can not measure
sugar levels
Automated Fermentation RateControl
Fully Automated Fermentation Control• Continuous in-line measurement of sugars /
other parametersFermentation monitorGlucose: 30 g/lFructose: 70 g/lTotal Sugars: 100 g/lEthanol: 6.5 % (vol.)
0 2 4 6 8 1 00
2
4
6
8
1 0
1 2
1 4
1 6
1 8
2 0
2 2
Fully Automated Fermentation Control
• Continuous in-line measurement of sugars– Fermentation temperature control– Fermentation rate management– Automatic AF termination at certain residual
sweetness– Fed-batch fermentations
Addition of carbon-source during fermentation
Advantages• Avoid substrate concentration extremes
– reduce osmotic stress– avoid feedback inhibition– reduce by-product formation
• Challenges– regulation of substrate feed
Fed-Batch Fermentations
Control of feed addition• Fixed addition rate
– does not consider fermentation kinetics• Variable feed addition
– Empiric addition - manual adjustment• does not allow for process variations• may not consider actual kinetics
– Off-line (discontinuous) measurement • organizational, labour considerations
– On-line (continuous) measurement • based on actual metabolism• requires continuous metabolite analysis
– In-line (continuous) measurement and automatic control
Feeding Options
A simple proposal
BATCH• Adding yeast to must
FED-BATCH• automatic, continuous, in-line• Adding must (slowly) to yeast
• yeast degrade sugar as it is provided
Sugar measurement Options
• Chromatography• Segmented flow analysis, flow injection
analysis• CO2 mass flow or density sensors• Automated discrete analyzers• Bio/Chemo-sensors• Ultrasound• Vibrational Spectroscopy
Processing Challenges• Specificity, cross sensitivity• Inhibitors• Diffusion limitations• Temperature sensitivity• Signal stability / drift• Sensor robustness / sterilization• Need for sample taking / pre-treatment• CO2 / air bubbles• Sample turbidity
• Yeast, nutrients: > 1'000 NTU
FTNIR - Spectroscopy
• Direct insertion into tank • non-destructive• no sample taking
required• Not diffusion limited• No consumables• Autoclavable• Flexible metabolite range• Requires calibration with
reference method
Bruker Multi-purpose FT-NIR Analyzer (MPA)
• 2 mm optical path length transflectance probe (1mm slit)
• 12,500 – 4,000 cm-1 spectral range• 16 cm-1 resolution• long acquisition times (> 500 spectra)• in-line control via Opus Quant / Process
– PROCESS > OPC > PLC > 4-20 mA signal
Equipment and Settings
Sample spectra before processing
Sample spectra after vector normalization
Spectral regions (after vector normalization)
Fermentation course
0 100 200 3000
1020304050607080
Eth
anol
(% v
/v)
Tot
al S
ugar
(g l-1
)
Time (h)
0246810121416
Calibrations and Cross validationEthanol
Calibrations and Cross validationTotal Sugars
Yeast viability
0 200 400 6000
20
40
60
80
100
Li
ve Y
east
[% o
f tot
al y
east
]
Time [h]
Fed-batch
Batch
0 50 100 150 200 250 300 350 40060
65
70
75
80
85
90
95
Liv
e Y
east
(%)
Time (h)
Yeast viability
Fed-batch
Batch
Sugar concentrations
0 200 400 6000
100
200
300
Tota
l Sug
ar [g
/L]
Time [h]
BatchFed-batch
50 100 150 200 250 300 350
50
100
150
200
250
300
Time [h]
Tot
al S
ugar
(g l-1
)
24681012141618
Eth
anol
(% v
/v)
Sugar/alcohol concentrations
Batch
Fed-batch
Ethanol concentrations
0 200 400 6000
5
10
15
Eth
anol
[% v
/v]
Time [h]
Batch
Fed-batch
Acetic acid
0 200 400 6000.00
0.25
0.50
0.75
1.00
Ace
tic a
cid
[g/L
]
Time [h]
Batch
Fed-batch
50 100 150 200 250 300 350
2
4
6
8
10
0 50 100 150 200 250 300 350 4000.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
Glycerol Acetic Acid
Glycerol / Acetic acid
Batch
Fed-batch
Acetaldehyde
0 200 400 6000
50
100
150
200A
ceta
ldeh
yde
[mg/
L]
Time [h]
BatchFed-batch
50 100 150 200 250 300 350
10
20
30
40
Ace
tald
ehyd
e (m
g l-1
)
50 100 150 200 250 300 3500
10
20
30
40
Pyru
vate
(mg
l-1)
Time (h)
50 100 150 200 250 300 3500
20
40
60
80
100
120
140
160
a-ke
togl
utar
ate
(mg
l-1)
Time (h)
50 100 150 200 250 300 350
10
20
30
40
50
60
Ace
toin
(mg
l-1)
Glycerol Acetic Acid
Carbonyls
Batch
Fed-batch
Propionic acid ethyl ester
0 50 100 150 200 250 300 3500
100
200
300
400
500
600C
once
ntra
tion
[µg/
l]
Time [h]
Fed-batch
Batch
0 50 100 150 200 250 300 3500
100
200C
once
ntra
tion
[µg/
l]
Time [h]
Hexanoic acid ethyl ester
Batch
Fed-batch
0 50 100 150 200 250 300 3500
25
50
75
100
125
150
175
200C
once
ntra
tion
[µg/
l]
Time [h]
Octanoic acid ethyl ester
Batch
Fed-batch
Dynamics of Volume(Volume/Time)
0 200 400 600 800
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000V
olum
e [m
l]
Process Time [h]
0 2 4 6 8 10 12 14 16 18 200123456789
101112
Alc
ohol
[% v
ol.]
V o lum e A dded (l)
Ethanol/Volume (at 50 g/l sugars)
0 200 400 600 800
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
Volu
me
[ml]
Process Time [h]
Summary
• FT-NIR based system with ±5 g/l sugar accuracy under (turbid) production conditions• glucose, fructose, ethanol, glycerol
• Fully automated fermentations possible• Traditional batch fermentations• Fed-batch fermentations
• Higher yeast viability• Fundamentally altered yeast metabolism
• decreased formation of osmotic stress related compounds
• Reduced cooling requirements
Outlook
• Process up-scaling• Process multiplication / platform transfer
• oenology - other analytes• production of
• organic acids• amino acids• proteins• aromas
• Process miniaturization / improvement
Fed-batch in Process Development
FeedBeadsEnBase - EnPresso
Acknowledgements• Canandaigua Wine Company, John Dyson, Mike Nolan,
Goichman Endowments
• Bruker Germany:
Dr. JP Conzen, Dr. A Niemöller, Dr. Taraschewski• Spectroscopic parameters, chemometrics, Opus script support
• Bruker USA:
Michael Surgeary, Stephen Medlin, Li Hui• Probe selection, calibrations, Opus scripts