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

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1 6

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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.)

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4

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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

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Li

ve Y

east

[% o

f tot

al y

east

]

Time [h]

Fed-batch

Batch

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Liv

e Y

east

(%)

Time (h)

Yeast viability

Fed-batch

Batch

Sugar concentrations

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Tota

l Sug

ar [g

/L]

Time [h]

BatchFed-batch

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100

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300

Time [h]

Tot

al S

ugar

(g l-1

)

24681012141618

Eth

anol

(% v

/v)

Sugar/alcohol concentrations

Batch

Fed-batch

Ethanol concentrations

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10

15

Eth

anol

[% v

/v]

Time [h]

Batch

Fed-batch

Acetic acid

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0.25

0.50

0.75

1.00

Ace

tic a

cid

[g/L

]

Time [h]

Batch

Fed-batch

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2

4

6

8

10

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0.05

0.10

0.15

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Glycerol Acetic Acid

Glycerol / Acetic acid

Batch

Fed-batch

Acetaldehyde

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100

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200A

ceta

ldeh

yde

[mg/

L]

Time [h]

BatchFed-batch

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40

Ace

tald

ehyd

e (m

g l-1

)

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Pyru

vate

(mg

l-1)

Time (h)

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a-ke

togl

utar

ate

(mg

l-1)

Time (h)

50 100 150 200 250 300 350

10

20

30

40

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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

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300

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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)

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14000

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18000

20000V

olum

e [m

l]

Process Time [h]

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101112

Alc

ohol

[% v

ol.]

V o lum e A dded (l)

Ethanol/Volume (at 50 g/l sugars)

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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