1) Grain cooling targets aim to prevent insect breeding by cooling grain to certain temperatures within set timeframes, but warmer autumns due to climate change may make these targets more difficult to achieve. 2) Trials in the UK found that automated differential thermostat control of grain cooling fans achieved targets faster and with up to 40% less energy than manual control. 3) Monitoring of grain cooling on 12 UK farms found that most were not achieving targets on time, highlighting a need for improved operator practices and cooling strategies. 4) Climate change projections suggest some areas of the UK may struggle to reliably meet cooling targets in the future, but proper control techniques can still effectively manage insect pest risks.

1. Assessing and addressing the impact of
warmer autumns on the success
of grain cooling
Dean Cook
Science Strategy team

2. Grain Cooling
• Grain is ventilated at low-volume rate
of 10m3
/h/t
• Cooling must be –
– fast enough to prevent insects
breeding; and temperature as low
as to cause death
– Part of an integrated grain storage
strategy in conjunction with drying,
hygiene measures and monitoring

3. As a rule of thumb…….
• Cool to below 15°C within 2 weeks
to prevent the saw-toothed grain
beetle breeding;
• to below 10°C within a further 2
months to prevent the grain weevil
breeding;
• to below 5°C by winter (xmas) to
prevent mites breeding and kill
insects.

4. Cooling targets for UK stores
using low volume aeration at 10
m3
/tonne/hr
Cooling starts on 1 Jul 1 Aug 1 Sep 1 Oct
Latest 15°C 16 Jul 17 Aug 12 Sep 8 Oct
date to 10°C 29 Sep 9 Oct 14 Oct 9 Nov
cool to 5°C 8 Dec 8 Dec 9 Dec 1 Jan
(After – Armitage et al., 1991)

5. Has cooling become more
difficult? – climate change
• Climate change will bring;
 Earlier, hotter harvests
 Shorter milder winters
 Extreme weather events
• Issues for cooling?
 High harvested temperatures
 Fewer “windows” of cold night
time air available
 Challenge to meet targets; speed
and temperature achieved

6. Comparison of mean monthly
temperatures from 1961 to the
present day.
0
5
10
15
20
25
J F M A M J J A S O N D
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
1961/90
(Source: Manley, 1974; Parker et al., 1992 – updated by the Hadley Centre for Climate Prediction and
Research, Met. Office, Berkshire, UK.)

7. Minimum temperatures for the
period immediately after harvest.
0
2
4
6
8
10
12
14
16
18
J A S O
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Target 1.
Target 2.
0
2
4
6
8
10
12
14
16
18
J A S O
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Target 1.
Target 2.
Target 1.
Target 2.
(Source: Manley, 1974; Parker et al., 1992 – updated by the Hadley Centre for Climate Prediction and
Research, Met. Office, Berkshire, UK.)

8. Adaptation to climate change –
demonstration project
Objectives –
“How well are we doing?”
“How can we do things better?”
• Measure on-farm cooling profiles in grain stores
on 15 farms distributed throughout the UK from
harvest 2007
• To compare the performance of automated
differential fan control with manual control at 3 sites
using identical paired stores
• To illustrate potential problems and “best practice”

9. Part 1. Efficient control – using differential
thermostats

10. Differential thermostats
Temperature
probe inserted into
grain
Temperature
sensor at
ambient
Feedback to fan
control
Temperature
probe inserted into
grain
Temperature
sensor at
ambient
Feedback to fan
control

11. Advantages of differential
thermostats; trials work, East
Lincolnshire 1991.
0
5
10
15
20
25
1 3 5 7 9 11 13 15
Weeks storage
Temperature°C
Ambient
Automated store
Manually controlled store
SEPTEMBER DECEMBER
[Auto-control using a 4°C differential in conjunction
with time clock (20.00-07.30, night time only) Vs
manual control.]

12. Trial detail – differential
thermostats vs manual control.
Focusing on 2 sites -
Site 1 -
• Farm site, Darlington
• 700t bulk of wheat at 14.5%mc
• Cooled with pedestals at recommended spacing etc.
• Bulk divided into virtual halves
half bulk controlled by 2°C differential
half bulk controlled by manual operation of fans

13. Darlington trial setup
4.5 – 6 m spacing between pedestals
Small
pedestal/fan to
deal with corner
Door
Leading edge
of heap
PC running
STORECHECK
Single fan
between 2 –
manual control
Single fan
between 2 –
auto control
= pedestals = sensors °C
1
2
3
4
5
6
2
1
3
4
5
6
Zone 1Zone 2
4.5 – 6 m spacing between pedestals
Small
pedestal/fan to
deal with corner
Door
Leading edge
of heap
PC running
STORECHECK
Single fan
between 2 –
manual control
Single fan
between 2 –
auto control
= pedestals = sensors °C
1
2
3
4
5
6
2
1
3
4
5
6
Zone 1Zone 2

14. Site 1 – Results; Temperatures at
Darlington site and progress against
cooling targets
0.0
5.0
10.0
15.0
20.0
7-Sep 17-Sep 27-Sep 7-Oct 17-Oct 27-Oct 6-Nov 16-Nov 26-Nov 6-Dec 16-Dec
Date
Temperature°C
Auto (mean)
Manual (mean)
Ambient (minimum)
15°C Target
due 18-Sep
5°C Target
due 15-Dec
10°C Target
due 20-Oct

15. Site 1 – Results; Cumulative fan
hours run
0
200
400
600
800
1000
1200
1400
15-Sep 25-Sep 05-Oct 15-Oct 25-Oct 04-Nov 14-Nov 24-Nov 04-Dec 14-Dec
Date
No.ofhoursblown
Manual
Auto
Up to 40% energy saving!

16. Comparison of insect control
costs
PROCESS COST FUNCTIONS
Fumigation 150-200p/t - Disinfests
Bulk insecticide admixture 50-75p/t - Prevents and disinfests
Cooling (manually) 50 p/t - Prevents mc
Cooling (automatic) 29 p/t movement
- Prevents infestation
- Preserves quality
- Disinfests over a
season

17. Trial detail – differential
thermostats vs manual control.
Focusing on 2 sites -
Site 2 -
• Co-operative store, Cambridgeshire
• Two 6000t silos of wheat at 14-15%mc
• Cooled with upward aeration system
One silo controlled by 4°C differential
One silo controlled by manual operation of fans

18. Site 2 – Results; Temperatures at
Cambridgeshire site and progress
against cooling targets
Site 2 – Results; Daily spot temperatures (8am)
at Cambridge site
-5
0
5
10
15
20
05-Oct 20-Oct 04-Nov 19-Nov 04-Dec 19-Dec 03-Jan
Date
Temperature°C
Ambient
auto bin (D2)
manual bin (D4)
1 2
Hours run
1. (2-Nov)
Auto; 98
Manual; 83
2. (4-Dec)
Auto; 142
Manual; 155
3. (7-Jan)
Auto; 156
Manual; 236
3
10°C Target
due 14-Oct
5°C Target
due 9-Dec
Site 2 – Results; Daily spot temperatures (8am)
at Cambridge site
-5
0
5
10
15
20
05-Oct 20-Oct 04-Nov 19-Nov 04-Dec 19-Dec 03-Jan
Date
Temperature°C
Ambient
auto bin (D2)
manual bin (D4)
1 2
Hours run
1. (2-Nov)
Auto; 98
Manual; 83
2. (4-Dec)
Auto; 142
Manual; 155
3. (7-Jan)
Auto; 156
Manual; 236
3
10°C Target
due 14-Oct
5°C Target
due 9-Dec

19. Part 2. Monitoring exercise – how well are
growers doing?

20. Monitoring exercise overview
iButtons
monitoring
ambient and
fan
temperature

21. Results – monitoring 12 sites
across the country
Location Air flow
P=Pedestal
U=Under-floor
Differential Target
(o
C)
Target met
Best
performing
Berwickshire ~10m3
/t/h
P
No 15
10
5
On time
1 week early
1 week early
Worst
performing
Suffolk ~10m3
/t/h
U
No 15
10
5
10 weeks late
Not met
Not met
• Only 1 site achieved the 15°C target on time
• 3 sites achieved the 10°C target on time
• 3 sites achieved the target of 5°C on time
• 11 stores cooled to 10°C
• Only 4 stores cooled to 5°C and below

22. Five day running mean of ambient
temperatures at monitoring
locations

23. Oxfordshire – why stop
cooling?

24. Leicestershire – only cooled on
2 occasions

25. Lincolnshire – the importance
of the correct differential

26. Part 3. What about the future?
David Bruce Consulting Ltd

27. Weather data – UKCP09
Weather Generator of UKCP09 hourly weather
Assumptions
• Time into future, in 30yr windows. 2020-2049
• Emissions scenario. High
• ‘Percentile’ is probability of change being as
large as embodied in the data:
– 90% (‘very likely’)
– 50% (‘as likely as not’)
• Control ‘historical’ data. 1960-1989
• Location: Odiham, Hants

28. Cooling parameters
• Strategy - diffstat control set at 4o
C
• Sensor at 0.5m depth
• 4m bed, 14.5% mc, 25o
C, 10 m3
/h.t, start 20
Aug
• Target temperature 5o
C by end December
• Also cooled to end February with the same
target of 5o
C

29. Summary of climate change
results
5
6
7
8
9
10
11
Control
(historic)
90% likely 50% likely
Climate change scenario
Temperature,o
C
Target
temperature
for cooling
88%
61%
38%

30. Conclusions
• Not all storekeepers are hitting their cooling
targets
• Need to continue to improve operator practice
• Differential thermostats can help you achieve
cooling targets and can save up to 40%
energy-use and running costs
• Future climate change may impact on cooling
targets but……will still be able to control
insect pests

31. We would like to thank…….
Participating stores and in particular, Stuart Vernon
(Grower, Country Durham), Andrew Ruff and Philip
Darke (Camgrain) who took part in the differential
control trials.
The work was funded by –
Warwick HRI's Defra-funded Innovation network for
adapting agriculture to climate change.
Defra through the Sustainable Arable LINK programme

32. Thank you for listening!