Scale Up Fermentor

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Validation of a Model for ProcessDevelopment and Scale-Up of Packed-BedSolid-State Bioreactors

Frans J. Weber,1,2 Jaap Oostra,2 Johannes Tramper,2 Arjen Rinzema1,2

1

Wageningen Centre for Food Sciences, P.O. Box 557, 6700 AN Wageningen,The Netherlands2Food and Bioprocess Engineering Group, Wageningen University, P.O. Box8129, 6700 EV Wageningen, The Netherlands; telephone: +31 (0)317 482683;fax: +31 (0)317 482237; e-mail: [email protected]

Received 26 December 2000; accepted 13 July 2001

Abstract: We have validated our previously describedmodel for scale-up of packed-bed solid-state fermenters(Weber et al., 1999) with experiments in an adiabatic 15-dm3 packed-bed reactor, using the fungi Coniothyriumminitans and Aspergillus oryzae. Effects of temperatureon respiration, growth, and sporulation of the biocontrolfungus C. minitans on hemp impregnated with a liquidmedium were determined in independent experiments,and the rst two effects were translated into a kineticmodel, which was incorporated in the material and en-ergy balances of the packed-bed model. Predicted tem-peratures corresponded well with experimental results.As predicted, large amounts of water were lost due toevaporative cooling. With hemp as support no shrinkagewas observed, and temperatures could be adequatelycontrolled, both with C. minitans and A. oryzae. In ex-periments with grains, strong shrinkage of the grainswas expected and observed. Nevertheless, cultivation ofC. minitans on oats succeeded because this fungus didnot form a tight hyphal network between the grains.However, cultivation of A. oryzae failed because shrink-age combined with the strong hyphal network formed bythis fungus resulted in channeling, local overheating ofthe bed, and very inhomogeneous growth of the fungus.For cultivation of C. minitans on oats and for cultivationofA. oryzaeon wheat and hemp, no kinetic models wereavailable. Nevertheless, the enthalpy and water balancesgave accurate temperature predictions when onlinemeasurements of oxygen consumption were used asinput. The current model can be improved by incorpo-ration of (1) gas-solids water and heat transfer kinetics toaccount for deviations from equilibrium observed withfast-growing fungi such as A. oryzae, and (2) the dy-namic response of the fungus to changes in tempera-ture, which were neglected in the isothermal kinetic

experiments.

2002 John Wiley & Sons, Inc. BiotechnolBioeng 77: 381393, 2002; DOI 10.1002/bit.10087

Keywords: Aspergillus oryzae; Coniothyrium minitans;model; packed bed; solid-state fermentation

INTRODUCTION

Many examples of new and promising products from

fungal solid-state fermentation (SSF) are reported in the

literature (Pandey et al., 2000). However, it is unclear

whether these processes can be eectively scaled-up to

industrial scale. One of the major problems to overcome

in large-scale SSF is heat accumulation. Due to the

absence of free-owing water and the low thermal con-

ductivity of solid substrates, removal of the heat pro-

duced by growing microorganisms can be problematic in

SSF. High temperatures must be avoided, as they ad-

versely aect microbial activity. In laboratory-scale

packed-bed reactors, adequate temperature control can

be achieved by wall cooling. However, in larger reactors,

conductive cooling becomes insucient and cooling by

forced aeration has to be used. Cooling by forced ae-

ration is mainly eective due to evaporation (Grajek,

1988; Gutie rrez-Rojas et al., 1996; Oostra et al., 2000;

Sato et al., 1982). This implies that successful tempera-

ture control can only be achieved at the expense of a loss

of moisture from the substrate, which may negativelyaect the cultivation. Furthermore, the shift from con-

ductive cooling to evaporative cooling can result in axial

gradients in packed-bed reactors (Gowthaman et al.,

1993). The axial gradients in industrial-scale packed-

bed reactors can cause dierences in productivity be-

tween lab-scale and industrial packed-bed reactors. A

mathematical model predicting temperature, moisture,

biomass, and/or substrate proles in a large-scale

packed-bed reactor would therefore be a valuable tool

to evaluate scale-up.

Previously, several mathematical models for solid-

state fermenters have been published, so one mightquestion the need for further modeling studies. We will

briey discuss the shortcomings of these previous

models, to show that there is still an urgent need for

models that correctly describe the predominant physical

phenomena and that have been adequately veried by

experimental work (Mitchell et al., 2000). Only models

that describe spatial and temporal gradients in packed-

bed reactors with forced aeration will be considered. In

most of these models, the eect of evaporation on heat

transfer was not taken into account (Gutie rrez-RojasCorrespondence to: F. J. Weber

2002 John Wiley & Sons, Inc.


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et al., 1995; Sangsurasak and Mitchell, 1995; Saucedo-

Castan eda et al., 1990). As discussed above, this is a very

dangerous assumption in a model that will be used to

evaluate scale-up. In addition, these models are ham-

pered by errors in the energy balance (i.e., the formu-

lation of the convection term implies that the solids

move along with the air) (Sangsurasak and Mitchell,

1995; Saucedo-Castan eda et al., 1990) or have been

validated in a bioreactor where conductive radial cool-

ing predominates and axial gradients as well as evapo-ration losses are much less important then they would be

on an industrial scale (Gutie rrez-Rojas et al., 1995;

Saucedo-Castan eda et al., 1990).

A heat transfer model in which evaporation was in-

cluded was only presented in 1998 (Sangsurasak and

Mitchell, 1998). This model very nicely demonstrated

the importance of evaporation for cooling of unmixed

packed-bed reactors with forced aeration. A desired

improvement of this model was the incorporation of a

water balance, as the authors estimated that about 85%

of the initially available water had evaporated after 40 h

of growth (Sangsurasak and Mitchell, 1998).Previously, we proposed a strategy to evaluate

whether an SSF-process can be successfully scaled up to

an industrial scale (Weber et al., 1999). This strategy was

based on a model similar to that proposed by Sangsu-

rasak and Mitchell (1998), but extended with a water

balance to predict the water content of the solid sub-

strate in the packed bed. Based on literature and labo-

ratory data in combination with heat and mass balances,

the aeration and evaporation rates required to remove

the metabolic heat produced by microorganisms grow-

ing in an industrial-scale packed-bed reactor were esti-

mated. Whether large-scale production is feasible

depends on (1) the pressure drop resulting from the re-

quired aeration rate, and (2) the eect of evaporation on

the particle volume and water activity. This approach

was used to decide which of the support materi-

alsoats, hemp, bagasse, or perlitecould be used in

large-scale packed-bed reactors for spore production of

Coniothyrium minitans, an eective biological agent for

pest control in many food crops (Whipps and Gerlagh,

1992). It was shown that moisture control is the limiting

factor for cultivation of C. minitans in a packed-bed

reactor. The model predicted that oats could not be used

due to shrinkage and aw reduction caused by evapora-

tive cooling. Of the three inert supports tested, hempwas expected to provide the best spore yield and control

of water activity (Weber et al., 1999).

Theoretical work thus suggests that mathematical

models will be useful tools in the scale-up process.

However, there is an urgent need to test the accuracy

and robustness of the models by applying them within

real process development (Mitchell et al., 2000). In the

current study, our extended model (Weber et al., 1999) is

validated by measuring the temperature and moisture

proles occurring when C. minitans is cultivated in a

properly downscaled packed-bed reactor (i.e., a well-

insulated column with neglegible conductive cooling). In

addition, the applicability of our model to evaluate

other SSF processes employing fungi with a higher

growth rate than C. minitans is reported. Aspergillus

oryzae, an important food fermentation organism, was

used for these studies.

MATERIALS AND METHODS

Inoculum Preparation

C. minitans isolate IVT1 (CBS 148.96) was kindly pro-

vided by M. Gerlagh of IPO-DLO, Wageningen, The

Netherlands. A. oryzae (CBS 570.65) was obtained from

the Centraal Bureau voor Schimmelcultures, The

Netherlands. Both strains were routinely cultured on

potato-dextrose agar (PDA) (Oxoid, Basingstoke, UK)

at 20C and 35C, respectively. A stock solution of

spores was obtained by ooding a PDA agar dish with a

sterile saline solution and gentle scraping of the plate

with a bent glass rod. Glycerol (20% wt/vol, nal con-

centration) was added to the spore suspension, whichwas subsequently stored at )80C.

Effect of Temperature

The eect of temperature on growth and sporulation of

C. minitans was determined on impregnated hemp.

Glass culture tubes 1(diameter 2.5 cm, height 15 cm) with

screw caps and silicon septa were used. The tubes had

three notches at about 1 cm from the bottom, on which

a stainless steel wire-mesh was placed. About 0.2 g of

dry hemp was placed on the wiring in each tube and 3

mL of demineralized water were added. These tubes and

separate solutions of 500-g glucose/L and 100-g yeast

extract/L were sterilized in an autoclave (20 min,

121C). After sterilization, 1-mL aliquots of the glucose

and yeast-extract solutions were added to the tubes with

hemp. The tubes were gently mixed and left at room

temperature for at least 5 h: in this period, the nutrients

could diuse into the hemp. To each tube, 0.4 mL of a

diluted conidial stock solution was added. After 30 min,

the excess of liquid medium was removed by means of

sterile Pasteur pipettes. After 4 h, the remainder of the

nonabsorbed uid that had dripped from the hemp was

removed. Initially, the tubes were incubated at 20C toallow germination of the conidia. After 2 d, the tubes

were placed in a temperature gradient block (con-

structed by the mechanical workshop of Wageningen

University, The Netherlands). This aluminum block (I

d h: 67 cm 59 cm 18 cm) has temperature condi-

tioning on the left- and right-hand side, by means of

heat exchangers and temperature-controlled water-cir-

culation baths (10 and 32C), and good isolation on the

other sides. A linear temperature gradient exists between

the temperature-controlled sides of the block. The cul-

382 BIOTECHNOLOGY AND BIOENGINEERING, VOL. 77, NO. 4, FEBRUARY 15, 2002


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ture tubes were placed in the holes present in the block.

The temperature of the tubes was recorded with a tem-

perature sensor. Growth was assessed by measuring O2consumption, using a gas chromatograph as described

previously (Weber et al., 1999).

Packed-Bed Reactor

To mimic an industrial packed-bed reactor, wheretemperature losses at the wall are relatively small, we

have constructed a well-isolated pilot-scale reactor. The

reactor is made of polypropylene, and has an internal

diameter of 20 cm and a height of 70 cm (bed height 50

cm). The reactor can be sterilized in an autoclave. At

various heights in the reactor the temperature was

measured with Pt100s. A2 perforated plate (3-mm-di-

ameter holes) at the bottom of the reactor served to

support the solid substrate. The air ow through the

reactor (bottom to top) was controlled with a mass-ow

controller (050 LN/min, Brooks, The Netherlands). The

temperature and humidity of the gas entering the reactorwere controlled at 18C and 100% RH (relative hu-

midity). The air entering the reactor was rst humidied

by blowing air through a stainless steel column (diam-

eter 30 cm, height 80 cm) lled with Raschig rings and

water of 23C. Subsequently, the air was cooled down to

18C and the condensed water was collected. A sterile,

0.2-lm PTFE-membrane lter (PolyVent 1000, What-

man, UK) was used to sterilize the air. The humidity of

the o-gas was continuously measured with a cooled-

mirror dewpoint analyzer (Dewmet SD, Michell, UK).

The concentrations of O2 and CO2 in the o-gas of the

reactor were measured with in-line gas analyzers (Xentra

4100 paramagnetic oxygen analyzer and Series 1400

infrared CO2 analyzer, Servomex, The Netherlands). A

small portion of the o-gas (100 mL/min) was passed

through a glass condenser at 5C to remove most of the

water vapor prior to the gas analysis. The reactor was

monitored and controlled with a PC using Fieldpoint

hardware and Labview software (National Instruments,

The Netherlands).

The thick plastic wall of the reactor prevented the

solids inside the reactor from reaching suciently high

temperatures during sterilization in an autoclave. To

secure sterility, the solid substrates were placed in a

thin autoclave bag connected with its opening to thetop of the reactor. After sterilization in the autoclave

(2.5 h, 121C), the contents of the bag were poured in

the reactor, and the bag remained connected to the

reactor. For the cultivations on grain, about 5 kg of

oats or wheat were placed in the bag and 5 kg of

demineralized water was added. A separate ask con-

taining 20 L of demineralized water was also sterilized.

After sterilization, conidia were aseptically added to

the water, which was subsequently pumped in the re-

actor. When the reactor was completely lled, the ex-

cess of water was removed. For the cultivations on

impregnated hemp, about 1.1 kg of hemp (Hemparade,

HempFlax b.v., The Netherlands) were placed in the

autoclave bag and 10 L of demineralized water was

added. To prevent the occurrence of undesired Mail-

lard reactions, the nutrients were sterilized in separate

asks, one containing glucose (Merck, Germany), the

other yeast extract (Technical grade, Difco, USA). For

the standard medium, 2-kg glucose and 400-g yeast

extract in, respectively, 7- and 3-L water were used. Inone experiment, a threefold higher nutrient concentra-

tion was used: 6-kg glucose and 1.2-kg yeast extract.

After heat sterilization, the hemp was poured in the

reactor. The yeast extract and glucose solutions were

mixed and conidia were added. This solution was

pumped in the reactor; when the reactor was com-

pletely lled with medium it was left to stand for at

least 5 h. A period of 5 h is required for the substrates

to diuse into the hemp and reach equilibrium. After

impregnation, the excess medium was removed from

the reactor. Subsequently, the reactor was weighed,

and a sample was aseptically taken to determine theinitial water content. The sample was taken with the

aid of the autoclave bag, functioning as an aseptic

sampler. The sample was collected from the top of the

bed and positioned in a corner of the bag. Two tie-raps

were placed around the bag to separate the sample

from the reactor. The corner of the bag, containing the

sample, was then removed from the reactor by cutting

the bag between the two tie-raps. The packed-bed re-

actor was placed in a cylindrical container (diameter 40

cm, height 100 cm 3), which was placed in a tempera-

ture-controlled incubator (18C). The space between

the wall of the cylinder and the reactor was lled with

cork granulate (size: 12 mm) to prevent radial heat

losses. After cultivation, the weight of the reactor was

again determined. Samples were taken from various

heights, to determine water content, water activity, and

spore yield. An additional sample was taken after

thorough mixing of the reactor contents.

ANALYSIS

The moisture content was determined from the weight

loss after drying the sample at 80C for 2 d. The water

activity of the sample was determined in a NovasinaThermoconstanter (Type TH200, Switzerland). Spores

were liberated from the substrate by blending and were

counted with an electronic particle counter (Casy 1,

Scha rfe-System, Germany) as described previously

(Weber et al., 1999). The water content and spore yield

were expressed per gram of initial dry weight (IDW) of

substrate. For the samples taken at the end of the cul-

tivation, the measured dry weights could be converted

into IDW with the aid of the measured weight of the

total reactor content.

WEBER ET AL.: LARGE-SCALE PACKED-BED SOLID-STATE FERMENTATION 383


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MATHEMATICAL MODEL

For large-scale packed-bed reactors, it is valid to assume

that heat losses through the reactor wall are negligible

(Gutie rrez-Rojas et al., 1996; Oostra et al., 2000), and

radial gradients in the bed are therefore unimportant.

When it is furthermore assumed that the air follows ideal

plug-ow behavior,the enthalpy and water balances read:

o

ot1 e

i

Ci hi e

j

cj hj2 3

rHHHo DHo

FHHa o

ozha 1

o

ot1 e xws Cs xwx Cx e Cwg

rHHHw FHHa

o

ozyw

2

Ci hi and Cj hj indicate enthalpies of all components

in the moist solid matrix and the gas phase, respectively.

The term for convective enthalpy transport is based on

the mass ow rate of dry air (FHHH

a

kg/m2 per s), and takes

the enthalpy of dry air4 and water vapor into account:

haT cpa T Tref ywT cpwv T Tref DHw

3

The water vapor fraction in saturated air can be calcu-

lated from:

yw Mwwater pw

Mwair Ptot pw 0:622

pw

Ptot pw4

and the water vapor pressure can be calculated from the

following empirical expression, which was obtained by

tting Antoine's law to water vapor pressure data attemperatures between 273 K and 333 K (Kaye and

Laby, 1995):

pw exp 23:59 4045

T 37:70

5

The enthalpy and mass balances can be simplied

considerably (Weber et al., 1999). First, in the accu-

mulation term of the balances, the contributions of

gases and all mass accumulation terms are negligible.

Second, a pseudo-steady state with respect to tempera-

ture and oxygen consumption rate can be assumed, be-

cause the characteristic times for changes in thesevariables are much larger than those for convective axial

enthalpy transport. Third, we assume that the air is at

equilibrium with the solid matrix at any point in the bed.

These simplications reduce the enthalpy balance to:

0 rHHHo DHo FHHa

d

dzha 6

For the simplication of the water mass balance, it is

also assumed that the water production rate is propor-

tional to the oxygen consumption rate:

rHHHw rHHHo Ywo 7

This simplies the mass balance to:

o

ot1 e xws Cs xwx Cx r

HHHo Ywo F

HHa

o

ozyw

8

Note that this model discriminates between water in

biomass and water in the substrate. However, it is hardto measure these variables independently. The change in

the total amount of water can be calculated from:

o

otxw r

HHHo Ywo F

HHa

o

ozyw 9

Table I shows the physical constants used in our

model. An important parameter, the yield coecient

Ywo

, is unknown and dicult to measure accurately. We

have estimated Ywo

from the following stoichiometric

equations for, respectively, glucose and starch:

C6H12 O6 2:59 O2 3 2:85 CH1:8 O0:5 3:44 H2O 3:15 CO2

C6H10 O5 2:59 O2 3 2:85 CH1:8 O0:5 2:44 H2O 3:15CO2

These equations were set up using an average biomass

composition (CH1.8O0.5) (Roels, 1983) and the reported

yield of 0.75 kg biomass per kg of oxygen for C. minitans

(Ooijkaas et al., 2000a). The obtained Ywo

for growth on

glucose (0.75 kg H2O per kg O2) is higher than for

growth on 5starch (0.53 kg H2O per kg O2) as the hy-

drolysis of starch requires water.

Oxygen Consumption

The growth of microorganisms on a solid substrate canbe described by the logistic law (Okazaki et al., 1980):

rHHHX lmax X 1 X

Xmax

10

The oxygen consumption rate is described with the

linear-growth model (Pirt, 1965):

rHHHoqs

1

Yxo r HHHx mo X

11

Table I. Physical properties used in the 9models.

Parameter Value Unit Reference

cpa 1,005 J/kg per K Hamblin (1971)

cpwv 1,857 J/kg per K Hamblin (1971)

DHo 1.4 107 J/kg O2 Cooney et al. (1968)

DHw 2.5 106 (at Tref) J/kg H2O Perry et al. (1984)

Ptot 1.01 105 Pa

Tref 273 K

Ywo 0.75 (glucose),

0.53 (starch)

kg H2O/kg O2 Assumed

qs 64 kg dry hemp/m3

reactor

This study



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It is assumed that Yxo and Xmax are temperature inde-

pendent. The parameters lmax and mo are assumed to be

temperature dependent, and the Ratkowsky equation is

used to describe the temperature dependency (Ratkow-

sky et al., 1983):

lmaxT a1 T Tmin 1 ea2 TTmax

h i2& '12

moT b1 T Tmin 1 eb2 TTmax

h i2& '13

The unknown parameters were obtained by tting

Eqs. (10)(13) on O2 consumption rates measured at

various temperatures using a three-dimensional regres-

sion (SigmaPlot 4.01, SPSS, USA).

RESULTS AND DISCUSSION

To estimate the heat production rate in a solid-state

bioreactor, the growth rate of the microorganisms

should be known. However, reliable methods to quantify

biomass formation on solid substrates are not available

(Ooijkaas et al., 1998). Oxygen consumption, however, is

easily determined and directly correlated with heat pro-

duction (Cooney et al., 1968). We have therefore mea-

sured the O2 consumption to estimate growth.

Effect of Temperature on Growth

For C. minitans growing on hemp impregnated with a

nutrients solution, the O2 consumption was determined

at various temperatures between 12 and 30C. In pre-

liminary experiments, it was observed that temperature

had a remarkable eect on the germination rate of the

conidia. In a solid-state reactor, initially no temperature

gradient will exist and all conidia will germinate at the

same temperature. Only when biomass starts to grow

can an axial temperature gradient develop. Therefore,

we used an initial temperature of 20C for the rst 2 d to

allow germination. Subsequently, the cultures were in-

cubated at temperatures between 12 and 30C, and ox-

ygen consumption was measured (Fig. 1).

The logistic and Pirt equations [Eqs. (10) and (11)]were used to t the O2 consumption measurements. A

temperature-independent yield coecient of 0.75 kg

biomass per kg O2 was used (Ooijkaas et al., 2000a). All

other model parameters were obtained by tting; it was

assumed that the maximum amount of biomass (Xmax) is

the same at all temperatures, and that lmax and mo are

temperature dependent [Eqs. (12) and (13)]. A good

correlation (R2 = 0.977) between measurements and

model description was obtained (Fig. 1B); which was

conrmed by the parity plot of measured values against

predicted values (Fig. 1C). The tted minimum tem-

perature for growth ofC. minitans (261 K) is clearly nota meaningful value (Table II). This is caused by the low

number of measurements at temperatures near Tmin.

Furthermore, the Ratkowsky equation is an arbitrary

function, and the validity of this function to accurately

describe growth and maintenance of C. minitans over

the entire temperature has not been shown yet. Despite

the nonrealistic value for Tmin, a good description

of the temperature-dependent O2 consumption in the

Figure 1. Measured and tted O2 consumption of C. minitans growing on hemp (A) at () 25.0C, (u) 20.2C, and (e) 15.3C, and (B) at alltemperatures measured. (C) Parity plot of the tted O 2 consumption against the measured consumption.

Table II. Obtained 10t parameters describing the O2 consumption of

C. minitans on hemp at temperatures between 12 and 30C [Eqs. (10)(13)].

Parameter Value ( std. error)

X0 (7.59 1.65) 10)4 kgX/kgIDW

Xmax 0.194 0.004 kgX/kgIDWa1 0.0336 0.0022 1/(day0.5K)

a2 0.266 0.038 1/K

b1 (7.99 0.41) 10)3 kgO20:5/(day0.5 kgX

0:5 K)

b2 1.35 3.40 1/K

Tmin 260.6 1.7 K

Tmax 307.3 0.5 K



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temperature range of 12 to 30C, which is of interest

for our experiments, is obtained.

It should furthermore be noted that the obtained

descriptions for biomass formation and maintenance

requirements are not validated by independent mea-

surements. However, the obtained values for the main-

tenance coecient (up to 0.12 kg O2/kg biomass per day

at 30C) are of the same magnitude as reported for fungi

in submerged cultures (Roels, 1983).

Effect of Temperature on Spore Production

The temperature also aects the formation of C. mini-

tans conidia (Fig. 2). At temperatures above 25C, the

number of conidia is signicantly reduced. For an op-

timal production it is thus required that the temperature

in the bed is adequately controlled.

Predicting PBR Behavior

Due to the dierences in eectiveness of various coolingmechanisms in small-scale reactors and large-scale re-

actors, scale-up criteria are required. Previously, we

proposed a strategy to evaluate whether (1) the tem-

perature could be adequately controlled, and (2) exces-

sive evaporation of water would not hamper the

cultivation in large-scale packed-bed reactors (Weber

et al., 1999). It was concluded that production of conidia

of the biocontrol fungus C. minitans in a packed-bed

reactor on an industrial scale is feasible. To mimic a

large-scale packed-bed reactor, we have insulated the

reactor to prevent heat losses via the reactor wall. For C.

minitans growing on hemp, we previously predicted that

an air ow rate of 0.025 kg air/m3 per s would be suf-

cient to prevent axial temperature gradients of more

than 5C. For this prediction we used the measured O2

consumption rate at 20C, as the highest radial growth

rate was observed at this temperature (McQuilken et al.,

1997). It appears now that the highest O2 consumption

rate is not observed at 20C but at 25C (Fig. 1). As a

consequence, the activity of C. minitans was underesti-

mated in our previous evaluation. The dierence in the

reported optimal temperatures is probably caused by the

dierent methods used to determine the optimum (radial

growth versus O2 consumption) and the low number of

temperatures tested by McQuilken. At 25C, the oxygenconsumption rate is maximal 7 10)5 kg O2/m

3 reactor

per s, and an aeration rate of 0.055 kg dry air/m3 per s

was estimated to result in axial temperature gradients of

5C. Figure 3 shows that a slightly higher maximum

axial temperature dierence (ca. 6C) was measured

when C. minitans was cultivated in the insulated packed-

bed reactor.

When we use the mathematical description of the O2consumption as a function of temperature [Eqs. (10)

(13) and Table II] to predict the O2 consumption and

temperature in the PBR, a reasonable correlation be-

tween the measured and predicted temperatures is ob-served (results not shown). However, at this aeration

rate, the dierence in oxygen concentration of the inlet

and outlet is very low (


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used. The small dierence is caused by an inaccuracy in

the prediction of the fungal activity. When the measured

O2 consumption of the reactor is used for the tempera-

ture predictions, a good match between the predicted

and measured temperatures is observed (Fig. 4). The

deviation between predicted and actual O2 consumption

is not unexpected. The eect of temperature on the O 2consumption rate has been measured in isothermal ex-

periments. In the reactor, however, the fungus does not

experience isothermal conditions. It is therefore not

surprising that the response to elevated temperatures

during cultivation is dierent from that which occurs

when the microorganism is subjected to the elevated

temperature from the beginning. Studies with Rhizopus

oligosporus showed that the isothermal approach is not

adequate to describe the eects of temperature changes

during SSF (Ikasari et al., 1999).

Control Strategies

Two control strategies can be applied to prevent too-

high temperatures in the PBR (Weber et al., 1999). The

rst option is to choose the air ow rate based on the

highest oxygen consumption rate during the fermenta-

tion, keep it constant, and let the outlet temperature

vary. The second possibility is to let the air ow rate

vary with the oxygen consumption rate and keep the

outlet temperature constant. In the experiment of Fig. 4,

the rst control option is used (constant ow rate).

Figure 5 shows the results of a cultivation where the

Figure 4. Measured and predicted temperature at the outlet of the reactor (left) and oxygen consumption rate (right) in an aerated (FHHHa

= 0.027

kg/m3 per s; Tair in = 17.7C) packed-bed reactor (experiment 19). Symbols: () measurements; (- - -) prediction using the kinetic model based on

independent isothermal O2 consumption measurements; () predicted temperature using the measured O2 consumption in the reactor.

Figure 5. Measured and predicted temperatures (left), air ow rate (middle), and oxygen consumption rate (right) in an aerated (variable airow)

packed-bed reactor (experiment 23). Symbols: () measurements; (- - -) prediction using independent isothermal O 2-consumption measurements.



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second control strategy was applied. In this cultivation,

the temperature in the top of the reactor was kept at

27.5C by means of a PID controller that continuously

monitored the temperature at the top and adjusted the

air ow rate. We did not use the measured O2 con-

sumption rate to control the ow rate, as the noise on

this signal was high due to the small dierence in inlet

and outlet concentrations.

Again, small deviations between predicted and actual

O2 consumption are observed. As explained before, thesedeviations may be caused by the use of independent O2consumption measurements at isothermal temperatures.

As a consequence, the predicted and measured ow rates

also dier slightly. Despite this small error, the model

gives a reasonable prediction of the temperatures in the

packed-bed reactor (Fig. 5).

With both control options, the maximum axial tem-

perature gradient was about 10C. The use of control

strategy 2 will economically be the most interesting, as

less energy will be required for the aeration. However, the

axial temperature gradient in this system is constantly

high. With strategy 1, high temperatures are only ob-served during a small period of time. As the spore yield of

C. minitans on hemp is reduced at temperatures above

25C (Fig. 2), the total number of conidia produced is

lower when control option 2 is used (Table III). When

control option 1 is used, the number of conidia produced

(Table III) is similar to the maximum obtainable yield at

the optimum isothermal temperature (Fig. 2). Appar-

ently, the temporarily high temperatures in the top of the

bed had no negative eect on formation of conidia.

Probably, most conidia are formed after day 6, when bed

temperatures are again optimal for conidiation (Fig. 3).

With control option 2 it is, of course, also possible to

prevent the occurrence of temperatures above 25C.

When these temperatures are prevented, this strategy is

expected to give spore numbers comparable to those

observed in strategy 1.

Effects of Evaporation

Forced aeration is an eective cooling mechanism in

large-scale packed-bed bioreactors. However, forced

aeration results in evaporation of water and desiccation

of the substrate. Desiccation of the substrate can either

lead to an unfavorably low water activity (aw), resultingin poor microbial activity, or to shrinkage of the sub-

strate particles with subsequent channeling in the bed.

Water Activity

Coniothyrium minitans is very sensitive to reduced water

activities: a small reduction in the aw has a tremendous

eect on spore formation (Weber et al., 1999). For a

high productivity, it is thus essential that the aw remains

close to 1.0 during the cultivation. However, the support TableIII.

Overviewofthesettings

andobtainedresultsinthevariouspacked

-bedexperiments.

11Experi-

ment

Fungus

substrate

(type)

substrate

(kg)

Airow(kg/

m3

pers)

Duration

(d)

O2

consumed

(kgO

2/m3)

Maximum

rO2

kgO2/m3

pers

Finalaa w

Conidia1/m3

Decrea

sedwatercontent(kg)

Measured

Predictedb

11

C.

minitans

HempAc

1.0

1

0.0

27

14.1

25.2

8.2

10)5

1.00

6.2

1014

1.7

0

1.16

1.12

18

C.

minitans

HempA

1.0

8

0.0

27

11.0

22.9

8.3

10)5

1.00

6.0

1014

1.9

7

1.26

1.26

19

C.

minitans

HempA

1.0

1

0.0

27

14.0

24.9

6.9

10)5

1.00

7.9

1014

1.9

2

1.16

1.17

25

C.

minitans

HempA

1.1

8

0.0

27

14.0

26.4

8.3

10)5

1.00

5.3

1014

2.2

1

1.37

1.36

12

C.

minitans

HempA

1.0

1

0.0

55

14.2

24.1

7.1

10)5

1.00

5.4

1014

1.7

3

1.11

1.14

16

C.

minitans

HempBc

1.0

1

0.0

27

17.0

57.3

14

10)5

0.97

1.7

1014

2.9

6

2.93

23

C.

minitans

HempA

1.1

8

Variable

11.6

28.6

9.610-5

1.00

4.7

1014

2.1

0

1.41

1.18

24

C.

minitans

HempA

1.1

8

Variable

11.7

28.2

9.4

10)5

1.00

3.3

1014

2.1

5

1.42

1.33

14

C.

minitans

Oats

4.3

3

0.0

27

17.3

71

10

10)5

0.98

11

1014

4.1

7

4.05

15

C.

minitans

Oats

4.2

5

0.0

27

24.2

83

9.5

10)5

0.98

14

1014

3.8

0

3.78

22

A.

oryzae

HempA

1.0

1

0.0

69

4.0

16.7

15

10)5

1.00

0.9

1

0.88

17

A.

oryzae

Wheat

4.5

2

0.0

69

6.0

a

Wateractivityofathoroughlymixedsampleofthetotalcontentsofthereac

tor.

b

Predicteddecreaseinwaterconten

tcalculatedusingthepredictedO2

consum

ptioninthereactor(rstcolumn)orthem

easuredO2

consumption(secondcolumn).

cHempimpregnatedwitheithersolutionA:100g/Lglucoseand20g/Lyeastextract:orsolutionB:300g/Lglucoseand

60g/Lyeastextract.



9/13

will inevitably lose water during the cultivation due to

evaporation. Ideally, the support should be able to re-

lease this large amount of water without aecting the

water activity. Hemp provided good control of water

activity due to its high water uptake capacity and fa-

vorable sorption isotherm (Weber et al., 1999). A spore

yield of 9 1014 conidia per m3 packed-bed was expected

to be feasible (Weber et al., 1999). Our experiments in

the PBR show that the water activity indeed remained

1.0 and that the expected spore numbers were obtained(Table III). The nal moisture content of impregnated

hemp was suciently high to prevent a drop in the aw. It

was anticipated that a higher initial nutrient concen-

tration could be used to impregnate the hemp, which

might lead to an even higher spore yield. However, a

threefold increase in the nutrient concentration resulted

in a drop of the initial water activity. Due to this re-

duction in water activity, the obtained conidia yield was

low (Table III).

The water activity of oats was expected to become

limiting for conidia formation after 24 d of cultivation

(Weber et al., 1999). The water activity at the end of thecultivation was indeed slightly reduced (aw = 0.98), as

was previously predicted (Weber et al., 1999). Despite

the inhibitory aw levels at the end of the cultivation, the

conidia production on oats was still about 1.1 1015

conidia/m3 (Table III), which is only slightly lower than

that obtained on lab-scale (Weber et al., 1999).

Channeling

Evaporation can negatively aect the cultivation in

various ways. In literature, the attention is primarily

focused on the reduction in water activity. In previous

work, we have emphasized the possibility of shrinkage

and subsequent channeling (Oostra et al., 2000; Weber

et al., 1999). In the current paper, we show that

shrinkage of the solid substrate and channeling can in-

deed have a more signicant eect on the cultivation

than the reduction in water activity.

A disadvantage of grain is that evaporation of water

will cause shrinkage, which we expected to result in

channeling and inhomogeneous aeration (Oostra et al.,

2000; Weber et al., 1999). Indeed, channel formation

was observed when A. oryzae was grown on wheat in the

packed-bed reactor. Evaporation caused shrinkage, andlarge air channels appeared between the tightly bound

substrate and the reactor wall (Fig. 6). As a consequence

of the inhomogeneous aeration, the temperature in the

center of the bed could not be controlled and quickly

reached 45C. At the end of the cultivation, almost no

mycelium was visible in the center of the bed. Only near

the channels, where the temperature could be controlled,

was abundant growth observed (Fig. 6). Surprisingly, no

channeling was observed when C. minitans was culti-

vated on oats in the packed-bed reactor. Contrary to

A. oryzae, C. minitans does not form hyphal bridges

between particles. As a consequence, the grains re-mained free-owing and no channels were observed.

Instead, we observed a reduction of the total bed height.

Our mathematical model cannot be used to predict

temperatures in situations where channeling occurs.

However, it might be extended to predict when shrink-

age will occur. The current prediction of the water

content of the substrate bed can be combined with in-

dependent measurements of substrate volume versus

moisture content (Oostra et al., 2000), to generate a

prediction of bed volume. When combined with obser-

vations from small-scale cultivations on the extent of

hyphal bridge formation, this might be translated into a

rough prediction of channel formation.

Limitations of Evaporative Cooling

Although evaporative cooling is a very ecient way to

remove heat, it has several disadvantages. It may aect

the cultivation by causing a reduction in aw or shrinkage

of the substrate, which may cause channeling. Another

disadvantage might be that the evaporation rate of

water cannot be controlled, and might become rate

limiting.

In our model, we assumed that the evaporation rate is

not limiting, and, therefore, the air is expected to be inequilibrium with the solid matrix at any point in the bed.

The o-gas of the cultivations of C. minitans on hemp

was water-saturated during the whole cultivation, indi-

cating that this assumption is valid. However, when oats

were used as solid substrate, the relative humidity of the

o-gas was only 87% around day 12 (Fig. 7). For this

cultivation our assumption is therefore not valid, and as

a consequence, the measured temperature was higher

than the predicted temperature. Only when the mea-

sured relative humidity of the o-gas was included in the

Figure 6. Channeling in an aerated (FHHHa

= 0.069 kg/m3 per s) packed-

bed reactor with A. oryzae on wheat (experiment 17). Left: Top view

showing the air channel, (C) between the reactor wall, (W) and the bed

(B) Right: Cross section showing poor mycelium distribution in the

bed resulting from the inhomogeneous aeration.



10/13

calculations was good agreement between predicted and

measured temperature observed (Fig. 7). The observed

dierence between hemp and oats might be attributed to

the smaller characteristic particle size of the hemp,

which causes (1) a higher specic surface area for mass

transfer, and (2) a smaller mass transfer resistance inside

the particles.

Aspergillus oryzae has a higher growth rate than C.

minitans: consequently, a higher aeration and evapora-

tion rate is required to remove sucient metabolic heat

when A. oryzae is cultivated on hemp. During cultivation

of A. oryzae on hemp in the PBR, it was observed that

evaporation of water also became rate limiting (Fig. 8).

The o-gas was not water-saturated during the whole

cultivation: after about 35 h, the relative humidity was

only 92%. This observation that the air at the outlet is not

always water-saturated implies that the transfer of water

from particle to air is rate limiting. As evaporation of

water is the main mechanism to remove heat, the

eectiveness of evaporative cooling can be seriously

Figure 7. Temperatures (left) and relative humidity of outlet gas (right) in an aerated (FHHHa

= 0.027 kg/m3 per s) packed-bed reactor with C.

minitans growing on oats (experiment 15). Symbols: () measurements, bottom to top, of temperature of inlet air at 5, 15, 25, and 35 cm bed height

and of outlet air; () predicted outlet temperature using measured O2 consumption and RH of outlet air.

Figure 8. Temperatures (left) and relative humidity (right) in an aerated (FHHHa

= 0.069 kg/m3 per s) packed-bed reactor with A. oryzae on hemp

(experiment. 22). Symbols: () measurements, bottom to top, of temperature of inlet air at 15 and 35 cm bed height and of outlet air; ()

predicted outlet temperature using measured O2 consumption and RH of outlet air.



11/13

limited by the transfer rate of water from the particle

to air. It is therefore expected that the evaporation rate

required to minimize axial temperature gradients cannot

always be reached. Especially for fast growing fungi,

such as A. oryzae, this means that axial temperature

gradients cannot always be prevented in large-scale

packed-bed reactors. As temperature can have a tre-

mendous eect on the production of, for instance, ex-

tracellular enzymes (Suh et al., 1988) or secondary

metabolites (Cooney et al., 1997), the overall produc-tivity in a full-scale packed-bed reactor might be lower

than would be expected on the basis of small-scale ex-

periments.

This unexpected limitation demonstrates very clearly

the necessity to experimentally validate a scale-up

strategy. Recently, Mitchell and colleagues (1999) also

proposed a scale-up strategy for packed-bed reactors,

and assumed that air is always water-saturated at su-

percial aeration rates up to 0.10 m/s. We7 already ob-

served limitations in the evaporation rate at 0.011 m/s

with oats and at 0.021 m/s with hemp. Clearly, the

packed-bed models need to be extended with solids-to-gas mass transfer kinetics for water.

Predicting Moisture Content

Desiccation of the substrate during cultivation cannot

be prevented and might result in unfavorable conditions.

Our model predicts the moisture content of the substrate

during cultivation. This prediction can be used to eval-

uate whether unfavorably low water activities or sub-

strate shrinkage are expected to occur when a process is

scaled up. The model discriminates between water in

biomass and extracellular water. However, as only the

overall water content could be measured, we have only

compared the predicted and measured overall water

content. Although the model predicts moisture content

during cultivation (Weber et al., 1999), moisture content

measurements can only be done by taking samples from

the reactor bed. As the moisture loss will be highest at

the end of the cultivation, we compared the predicted

and measured decrease in overall water content at the

end of the various cultivations (Table III).

For all cultivations of C. minitans on hemp impreg-

nated with 100 g glucose/L, the measured decrease in

water content was higher than predicted. For all othercultivations, the measured and predicted values corre-

spond well (Table III). The fact that the deviations be-

tween predicted and measured water content are only

observed for the cultivations of C. minitans on hemp is

remarkable. Both evaporation and metabolic water

production aect the water content of the substrate. As

the model accurately described temperatures in the

PBR, it is expected that the predicted evaporation rates

are correct. The metabolic production of water is small

compared to evaporation. It is therefore not expected

that a fault in this prediction can account for the ob-

served dierence in predicted and measured water con-

tent. The observed dierences could also be caused by

an error in the water-content measurements. Although

the error in the water-content measurements is relatively

large, it is uncertain whether this accounts for the dif-

ferences. The deviation between measurement and pre-

diction is the same for all cultivations of C. minitans

with hemp, and for the other cultivations the predictions

are similar to the measurements. Therefore, it is unlikelythat the error in the moisture analysis causes the ob-

served deviation.

Another striking dierence between the cultivations

on hemp is the higher amount of O2 consumed by C.

minitans compared to A. oryzae (Table III). The glucose

concentration is expected to be similar for all the ex-

periments, as the same impregnation procedure was

used. C. minitans is known to produce various cell-wall

degrading enzymes (Jones et al., 1974). It is therefore

expected that C. minitans also uses the hemp as sub-

strate, resulting in the higher O2 consumption. The mi-

crobial degradation of hemp will require water, and thismight cause the observed deviation between measured

and predicted water content. The fact that the nal

water content in the cultivation with C. minitans on

hemp with a higher glucose concentration was correctly

predicted supports this hypothesis. Due to the higher

glucose concentration, it is expected that less hemp is

degraded. However, to explain the large deviation be-

tween measured and predicted water content, the

amount of water used for the degradation of hemp

should have been extremely large. The cause for the

dierence therefore remains uncertain.

CONCLUSIONS

Several models predicting the performance of packed-

bed bioreactors for solid-state fermentation have been

published in recent decades. Most of these models cannot

be used for scale-up studies, as they do not take into

account the most important heat transfer mechanism:

evaporation (Gutie rrez-Rojas et al., 1995; Sangsurasak

and Mitchell, 1995; Saucedo-Castan eda et al., 1990).

Another shortcoming in all previous models is the lack of

a water balance to predict moisture losses (Sangsurasak

and Mitchell, 1998). Also, none of the proposed modelshave been properly validated. Several authors tried to

verify their model by tting the model predictions to the

measured temperatures (Sangsurasak and Mitchell,

1998; Saucedo-Castan eda et al., 1990). A t is, of course,

no proof that the models are valid. The results of the

same authors already indicate that their ``validation''

was not properly performed, because when they used

independently determined parameters in their models,

unsatisfactory model predictions were obtained (Sang-

surasak and Mitchell, 1998; Saucedo-Castan eda et al.,



12/13

1990). The urgent need for proper validation experiments

was also recognized by Mitchell and colleagues (2000) in

their review on design and operation of SSF reactors.

Our model consists of two parts: a biological part and

a physical part. The biological part predicts the activity

of the fungus in response to changing temperatures at

various positions in the bed. The physical part of the

model uses these activities to predict temperatures at

various positions in the bed. Both parts of the model

have been veried.Reasonable agreement between predicted and mea-

sured O2 consumption rates was observed. The devia-

tions that were observed may be attributable to the

dynamic response of fungi to changes in temperature,

which was neglected in the model and in the underlying

isothermal kinetic experiments. An eect of the tem-

perature history on fungal growth rates has been re-

ported previously, but remains to be explained (Ikasari

et al., 1999). More research into this area would be re-

quired to further improve the kinetic model.

Very good predictions were obtained when the phys-

ical part of the model was validated using respirationrates measured in the packed bed. Only at certain con-

ditions was a limitation of the current model identied.

Incorporation of gas-solids water and heat transfer ki-

netics to account for deviations from equilibrium ob-

served with fast-growing fungi would improve the

current model.

Our results clearly show that a proper choice of the

solid medium is essential for a successful process. As-

pergillus oryzae could be successfully cultivated on

hemp, but the cultivation failed when wheat was used as

solid substrate. The high water uptake capacity of hemp

provided good control of water activity, and shrinkage

and channeling were not observed. Also, hemp allowed

higher evaporation rates and thus better control of

temperature. Another important advantage of hemp is

that it can be impregnated with an optimized medium

supporting high product yields (Ooijkaas et al., 2000b).

We believe that our model and the previously pre-

sented design approach using a simplied version of the

current model (Weber et al., 1999) are valuable tools to

evaluate: scale-up of SSF processes in packed-bed re-

actors. We hope that continued development of vali-

dated models of this type will contribute to the

development of SSF technology to a feasible alternative

for submerged fermentation.

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NOMENCLATURE8

a1, a2b1, b2

Fit parameters see Table II

Cs concentration of support

in bed

kg dry support/m3 support

Cwg concentration of water in

gas phase

kg water/m3 air

Cx concentration of biomass in

bed

kg dry biomass/m3 support

cpa specic heat of dry air J/kg dry air per K

cpwv specic heat of water vapor J/kg per K

Fa supercial aeration rate kg dry air/m2 per s

ha enthalpy of (moist) air J/kg dry air

DHo reaction enthalpy J/kg O2DHw evaporation enthalpy water J/kg H2O

Mw molecular weight kg/mole

mo maintenance requirements

biomass

kg O2/kg dry biomass per s

Ptot atmospheric pressure Pa

pw

water vapor pressure Pa

rHHHo oxygen production biomass kg O2/m3 reactor per s

rHHHw water production biomass kg H2O/m3reactor per s

rHHHx biomass formation rate kg dry biomass/ kg dry

support per s

t time s

T temperature K

Tmin minimum temperature

for growth

K

Tmax maximum temperature

for growth

K

Tref reference temperature K

X biomass content kg biomass/kg dry support

Xmax maximum content biomass kg biomass/kg dry support

xw water content reactor kg water/m3 reactor

xwx water content biomass kg water/kg dry biomassxws water content support kg water/kg dry support

Yxo yield biomass formation kg biomass/kg O2Ywo yield water formation kg H2O/kg O2yw water content air kg water/kg dry air

z axial position in bed m

Zmax height of the reactor bed m

e void fraction m3 air/m3reactor

lmax maximum specic growth rate 1/s

qs density support kg dry support/m3 reactor



13/13

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