Successful moisture control of aquafeed can be seen through the safety of the product and in its profitability. Feed products must be dried sufficiently in order to prevent growth of microorganisms after the packaging process. However, over-drying the products will result in poor production yields and energy losses. The two challenges for feed manufacturers are 1) to find the highest moisture content for a given product that will still prevent growth of moulds and other microorganisms, and 2) to find a drying control method that will help achieve and maximise that moisture content.

1. I N C O R P O R AT I N G
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January | February 2014
Successful moisture control in aquatic feeds
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3. FEATURE
Successful moisture
control in aquatic feeds
by Roger E. Douglas, director of engineering, Drying Technology, Inc.,
Texas, United States
S
uccessful moisture control of
aquafeed can be seen through the
safety of the product and in its
profitability. Feed products must be
dried sufficiently in order to prevent growth
of microorganisms after the packaging
process. However, over-drying the products
will result in poor production yields and
energy losses. The two challenges for feed
manufacturers are 1) to find the highest
moisture content for a given product that
will still prevent growth of moulds and other
microorganisms, and 2) to find a drying
control method that will help achieve and
maximise that moisture content.
The first challenge requires the feed manufacturer to determine the highest possible
target and upper moisture limits for each
individual product. One of the main reasons
to keep moisture content as high as possible
is profitability. The incremental amount of
water left in the product can be considered
a production increase, and energy is saved by
not having to remove it. However, for reasons
of product stability and safety it is important
to set an upper limit on the feed’s moisture
content.
The water activity and moisture content
of a specific product are related values, but
are calculated in different ways. Both centre
on the ‘free’ water or free moisture, in
other words the water that is readily available for biological use. Moisture content is
a measurement of the total free and bound
water in the product, whereas water activity only takes into account the free water.
Bacteria, mould and yeast all require moisture for growth and each microorganism
has a minimum water activity, below which
it would not grow. Therefore, for a safe
product that will not develop mould during
storage, the water activity
level should be below the
minimum value for some
or all types of microorganism. Table 1 lists some
major microorganisms and
the minimum water activity level that makes their
growth viable.
Constructing
an isotherm
Figure 1: Typical water isotherm for a product
Water activity values are
a more accurate reflection
of the stability and safety of
feed products than the total
moisture content. Many food
12 | InternatIonal AquAFeed | January-February 2014
table 1: Typical minimum water activity
levels for common microorganisms
(Source: Fontana, 2000)
Water
activity
Microorganisms generally inhibited
0.950
Pseudomonas, escherichia, Bacillus,
Clostridium perfringens, some yeast
Salmonella, C. botulinum,
0.910 lactobacillus, Pediococcus, some
moulds
0.870 Many yeasts
Most moulds (mycotoxigenic
0.800 penicillia), Staphylococcus aureus,
most Saccharomyces
0.750
Most halophilic bacteria,
mycotoxigenic aspergilla
0.650 Xerophilic moulds
0.600 osmopholic yeasts, few moulds
and feed industries use 0.65 as a minimum
water activity value in manufacturing their
products, each of which will have its own
relationship between moisture content and
minimum water activity value. By analysing
product samples at various moisture content
levels, a water isotherm can be constructed,
plotting moisture content against the water
activity value (see Figure 1). The moisture
content for any given water activity value can
then be determined with accuracy.
The moisture content corresponding to
the industry standard 0.65 water activity can
be different for each product. Relative differences in the raw materials used can affect the
amounts of free and bound water it contains,
producing unique isotherms for each formulation. In fact, the formulation used can be a

4. FEATURE
helpful tool in increasing the moisture content
allowed by the minimum water activity.
Moreover, the water isotherm and moisture sample data can be used to calculate the
moisture target and the upper control limit.
For most dried products, the portion of the
isotherm at and well below the critical water
activity value of 0.65 is linear, giving a proportional relationship between water activity and
moisture content. A simple linear equation
can therefore be used to determine the water
activity value from the moisture content, or
vice versa. The isotherm in Figure 1 shows
that a moisture content of 8.92 percent will
give a water activity of 0.65. For this product,
then, 8.9 percent would be the upper control
limit.
Sample variance
The target moisture value must also take
into account variance between samples. Here,
the moisture sample history can be used to
calculate a standard deviation: ±3 standard
deviations from the average will account for
nearly 100 percent of samples. The moisture
target can then be calculated using the upper
control limit and the number of standard
deviations required.
Target moisture = UCL – N(s.d.)
UCL: Upper control limit
N: No. of standard deviations
s.d.: Standard deviation of the product samples
To give an example, using a standard
deviation of 0.6 and the above upper control
limit of 8.9 percent, and three standard
deviations, you would receive a target moisture level of 7.12 percent. With current
dryer control methods, only 0.14 percent
of moisture samples would have a chance
of exceeding the upper control limit. Many
users of statistical process control methods
will use 2 or 2.5 standard deviations in the
target moisture calculation, giving targets of
7.42 percent and 7.72 percent respectively
(see Table 2). The key values here are the
percentage of samples that may be statistically above the upper limit.
table 2: Results of altering the number of
standard deviations on target moisture
calculation
target
moisture
UCl
number
of
Standard
standard deviation
deviations
As seen in the equation above, a reduction
in the standard deviation will result in an
increase in the target moisture. The results
of this are increased production and energy
savings.
Assume, for example, that through
improved dryer control the standard deviation was reduced by 30 percent, to 0.42 (see
Table 3). The new target moisture would
be 7.66 percent, 0.54 percent higher than
the previous figure of 7.12. As this shows,
improved dryer control – obtained by drying
with cooler temperatures and being careful
not to over-dry the product – can allow a safe
increase in average moisture levels, resulting
in a 0.5 percent production increase. Cooler
drying temperatures would also result in
energy savings.
%
above
UCl
7.12
8.92
3
0.6
0.14
7.42
8.92
2.5
0.6
8.92
2
0.6
target moisture, with improved standard
deviation values
number
of
Standard % above
standard deviation UCl
deviations
target
moisture
UCl
7.66
8.92
3
0.42
0.14
7.87
8.92
2.5
0.42
0.62
8.08
8.92
2
0.42
2.28
0.62
7.72
table 3: Number of standard deviations vs
2.28
With a method of calculating target
moistures and upper control limits in place,
we can give attention to optimising dryer
control to reduce the moisture variance.
A/S
January-February 2014 | InternatIonal AquAFeed | 13

5. FEATURE
Figure 2: Locations and dead times of moisture sensing
package based on a model derived from first
principles. The Delta T model,
Moisture = K1(ΔT)p – K2/Sq
relates the product moisture exiting a
dryer to the temperature drop (ΔT) of the
hot air after contact with the wet product,
and the production rate or evaporative load
(S). The model solves the two main problems
with sensing and control by producing a
rugged, reliable, ‘inside-the-dryer’ moisture
sensor, and a control algorithm that precisely
adjusts the dryer temperatures for evaporative load changes.
Figure 2 illustrates an example of the soft
sensor location, compared with the present
standard moisture sample methods of online
moisture meters and hand-sampling. As previously discussed, the reduction of standard
deviation is in part tied to the reduction of
dead time in the process, and therefore to the
location of the sensor.
Consumer benefit
Figure 3: Actual results of improved moisture control
Lowering dead time,
improving control
Even when the dryer is well maintained
and running well, a main reason for poor
moisture control is the timeliness and
accuracy of the moisture sensing and
the resulting control changes. The usual
practice for most manufacturers is to
periodically take moisture samples, using
these for feedback to adjust the dryer
temperatures. A few have had success
with online moisture sensors, however,
these are always after the dryer exit or
after-the-fact.
In either case, the ‘dead time’ – the time
it takes for a load change entering the dryer
to be detected – is long, and detection of
moisture changes only take place after the
product has left the dryer. By lowering the
dead time, or by sensing the load changes earlier in the drying process, control
changes could be made in a timelier manner, lowering the standard deviation. The
standard deviation of the moisture samples
is proportional to the dead time and, as
previously stated, lowering the standard
deviation allows the target moisture to be
increased.
Sensing moisture changes earlier in
the dryer and making immediate control
changes would reduce the dead time and
improve moisture variance. In recent years,
advances in process control and modelling have improved the drying process: for
example, a soft sensor now exists that can
measure and detect changes inside the
dryer. Soft sensors use measurable process inputs and a mathematical model to
produce a measurement of a process variable that cannot be measured directly with
a hardware sensor. In this particular case,
the soft sensor uses dryer temperatures to
derive a measurement of product moisture
while the product is still in the dryer. By
detecting the moisture changes in this way,
control adjustments can be made immediately, and moisture correction can begin
before the product leaves the dryer.
The Delta T Moisture/Dryer Control
System is one such soft sensor and control
14 | InternatIonal AquAFeed | January-February 2014
With the combined approach of finding
the highest moisture content that product
safety allows and using a moisture sensing/
control method, the average product moisture can be optimised. The opportunity to
‘sell more water’ is too financially beneficial to
ignore. For example, a 0.5 percent increase
in average moisture content for a feed plant
producing 25,000 tons per year at $800/ton
would realise $100,000 extra sales revenue.
The increase in moisture would also bring
with it significant energy savings.
Figure 3 shows actual moisture sample
data before and after the advanced moisture
control system was implemented in the feed
dryer. The new regime achieved a 35.5
percent reduction in the moisture variance’s
standard deviation, and a 0.5 percent increase
in the actual moisture level of the product.
Regardless of the formulation of feed
products, the water activity value can be used
to find the highest possible moisture content
while protecting against mould growth, and
do this in a relatively short period of time.
The method of storing products at different
moisture contents for months at a time, and
continually checking for microbial growth
throughout the period, is long and tedious
for determining each individual upper moisture limit. Advances in sensors and process
control provide the ability to control dryers
and related equipment to produce the
highest quality and safest product for your
customers.
More
inforMation:
Roger Douglas
roger@moisturecontrols.com
Website: www. moisturecontrols.com

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