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Spencer S. Walse
Postharvest Fumigation Research at
USDA-ARS-SJVASC
http//fresno.ars.usda.gov
Update on Postharvest Fumigation
• QPS scenario & methyl bromide
– low-emission fumigations
– alternatives
• PH3, SF
• breaking specialty crop trade barriers
– pests (insects)
– systems/processing-based
– mathematical modeling
– residues
Cl
Cl
Cl
Cl
Cl
Cl
OS
O
O
Trade Barriers
politics
$ economics
science
X
trade
barriers
Postharvest Conundrum
pest-free security
food safety no residue
Navel Orangeworm to EU
Mathematical modeling of fumigation (insect-, fumigant-, commodity-specific)
central-composite design
(matrix comparison)
center-point
axial
factorial
Factor (original units) Factor levels
- 2 - 1 0 a
1 2
x 1 : dose (mg/L)
0 24 48 72 96
x 2 : temp ( C) 5 10 15 20 25
x 3 : duration (h) 1 12 24 36 48
x 4 : pressure ( - inch. Hg)
0 7 14 21 28
a 0 = center point
axial
14 1 4 23 2 3 24 2 4 34 3 4
y = b 0 + b
1 x 1 + b
11 x 1
2 + b 2 x
2 + b 22 x
2 2 + b
3 x 3 + b
33 x 3 2 + b
4 x 4 + b
44 x 4
2 + b 12 x
1 x 2 + b
13 x 1 x
3
+ b x x + b x x + b x x + b x x
y = SF depuration y = egg survivability
y = b0 + b1x1 + b2x2 + b3x3 + b4x4
Multifactorial Modeling fumigant residues: SF-walnuts
Initial residues (30 min post fum.):
y = 1.36 + 0.87x1 – 0.51x2
mean p - value d
source sum of squares a df square b F - value c Prob > F
model 24.7 4 6.17 16.4 < 0.0001
residual 9.4 25 0.38
lack of fit 9.4 20 0.47 174.2 < 0.0001
a total for the sum of squares for the terms in the model
b estimate of variance, models sum of squares / model degrees o f freedom
c comparison of term variance (mean square) with residual variance (res. mean square)
d probability of seeing observed F value if the null hypothesis is true (no factor effect)
dose 18.0 1 17.9 47.8 < 0.0001
temp 6.14 1 6.14 16.4 0.0004
duration 0.44 1 0.44 1.2 0.2884
vacuum 0.09 1 0.09 0.24 0.6267
mean p - value d
source sum of squares a df square b F - value c Prob > F
model 24.7 4 6.17 16.4 < 0.0001
residual 9.4 25 0.38
lack of fit 9.4 20 0.47 174.2 < 0.0001
a total for the sum of squares for the terms in the model
b estimate of variance, models sum of squares / model degrees o f freedom
c comparison of term variance (mean square) with residual variance (res. mean square)
d probability of seeing observed F value if the null hypothesis is true (no factor effect)
a total for the sum of squares for the terms in the model
b estimate of variance, models sum of squares / model degrees o f freedom
c comparison of term variance (mean square) with residual variance (res. mean square)
d probability of seeing observed F value if the null hypothesis is true (no factor effect)
dose 18.0 1 17.9 47.8 < 0.0001
temp 6.14 1 6.14 16.4 0.0004
duration 0.44 1 0.44 1.2 0.2884
vacuum 0.09 1 0.09 0.24 0.6267
temp
(r2 = 0.76)
SF depuration rates:
- attempts to model failed, relative to an average rate
- ave. rate of 0.59 d-1, half-life of 1.17 d ± 20%
-125 mg/L max dose @ 60F, SF below 3ppm MRL in ~30 min
Egg biology & toxicology IMM
DFB
NOW
CM
Peach Twig Borer vs. AUS
1
2
3
4
1 2 3 4 5
10
11
12
13
14
15
16
0
post-fumigation time (day)
met
hyl b
rom
ide
resi
dues
(pp
m)
1
2
3
4
1 2 3 4 5
10
11
12
13
14
15
16
0
1
2
3
4
1 2 3 4 5
10
11
12
13
14
15
16
10
11
12
13
14
15
16
0
post-fumigation time (day)
met
hyl b
rom
ide
resi
dues
(pp
m)
Residues : MB & T104-a-1
- 0.6
- 0.5
- 0.4
- 0.3
- 0.2
- 0.1
0 0.5 1 1.5 2
time (hours)
ln (
[ MB
] t /[
MB
] o )
- 7
- 6
- 5
- 4
- 3
- 2
- 1
0 1 2 3 4
time (days)
ln (
[ MB
] t /[M
B] o
)
“ plums sorb slower ”
“ plums desorb slower ”
t 1/2 = 0.93
t 1/2 = 0.47
t 1/2 = 0.45
- 0.6
- 0.5
- 0.4
- 0.3
- 0.2
- 0.1
0 0.5 1 1.5 2
- 0.6
- 0.5
- 0.4
- 0.3
- 0.2
- 0.1
0 0.5 1 1.5 2
time (hours)
ln (
[ MB
] t /[
MB
] o )
- 7
- 6
- 5
- 4
- 3
- 2
- 1
0 1 2 3 4
- 7
- 6
- 5
- 4
- 3
- 2
- 1
0 1 2 3 4
time (days)
ln (
[ MB
] t /[M
B] o
)
“ plums sorb slower ”
“ plums desorb slower ”
t 1/2 = 0.93
t 1/2 = 0.47
t 1/2 = 0.45
MB sorption
Systems-based approaches: future?
CUMULATIVE JOINT PROBABILITIES
SWD
=
New Pest: back to MB
(preserve MB)
Development of low-emission chamber fumigations
0
20
40
60
80
10
0
12
0
14
0
16
0
18
0
Enclosure
0.1
1
10
100
1000
10000
100000
Me
Br
Co
nc
en
tra
tio
n, p
pm
Time, Minutes
Enclosure
Stack
Note log scale
Fumigation period
Begin Aeration
16,000 ppm
~5 ppm from
fumigation bay
~1 ppm from
adsorber exhaust
Switch to bypass
at 500 ppm
Terminate aeration
at 5 ppm
0
20
40
60
80
10
0
12
0
14
0
16
0
18
0
Enclosure
0.1
1
10
100
1000
10000
100000
Me
Br
Co
nc
en
tra
tio
n, p
pm
Time, Minutes
Enclosure
Stack
Note log scale
Fumigation period
Begin Aeration
16,000 ppm
~5 ppm from
fumigation bay
~1 ppm from
adsorber exhaust
Switch to bypass
at 500 ppm
Terminate aeration
at 5 ppm
Collaborators: Joe Pignatello (Yale)
William Mitch (Yale)
David Zilberman (UC Berkeley)
Gary Knapp (consultant)
Jim Leesch (ARS retired)
Scott Wood (APHIS-TQAU)
Development of low-emission chamber fumigations
trade
barriers
Postharvest Conundrum
pest-free security
food safety no residue
Residue remediation
fenhexamid 1-methylcyclohexanecarboxamide
CO2
+
• Soak tanks (HOCl, O3)
– oxidant-induced color changes
– other cosmetic damage
– shallow pitting on fruit surfaces
– natural organic matter competition
– inadequate activity of O3 against surface-
sorbed residues (low water sol.)
– disinfection byproducts (DBPs!)
History: wet approaches
Hakan Karaca, Joe Smilanick
1000 ppm O3
REMEDIATION OF FUNGICIDE RESIDUES
ON FRESH PRODUCE USING
GASEOUS OZONE
Environmental Science & Technology, 2011, in press
Residue remediation w/ O3: structurally selective
~2 ~2 64 38 40 % degradation
Ozone fumigation
Will my product look worse?
Situation dependent
Will worse products form?
more polar = less toxic (ozone)
• Endocrine disruptors
– endosulfan and sulfate
• POPs
– paraoxon and parathion
Ozone fumigation
oxidation
paraoxon parathion
O N O 2 P
O C 2 H 5
O C 2 H 5
S O N O 2 P
O C 2 H 5
O C 2 H 5
O
oxidation
paraoxon parathion
O N O 2 P
O C 2 H 5
O C 2 H 5
S O N O 2 P
O C 2 H 5
O C 2 H 5
O
Case studies: endocrine disruptor (ES) and POP
C l
C l
C l
C l
C l
C l O
O S
O
C l
C l
C l
C l
C l
C l O
O S
O
O
oxidation C l
C l
C l
C l
C l
C l O
O S
O
C l
C l
C l
C l
C l
C l O
O S
O
O
oxidation
endosulfan endosulfan sulfate
t=0
t=30 min
Next steps
• Develop structurally indiscriminate techs.
– Free radical processes (●OH, ●OOR)
• Obtain funding/agreements
• Tailor to commercial needs
THANK YOU!
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