Fruit set

Avances e
Innovación en la
Producción de Cerezas
Mateo Whiting
What we have……
• Aged genetics
• Lengthy production cycles
• Inefficient/static production
systems
• Compartmentalized system
for production, processing,
marketing
• Increasing competition
• Increasing cost &
decreasing supply of labor
• Inadequate education and
outreach
Output vs. Input:
Production systems
HI/LO
HI/HI
LO/LO
LO/HI
OUTPUT
INPUT
Innovations in cherry
production
• Genetic
• Orchard systems
• Automation/mechanization
– Mechanical pruning
– Mechanical harvest
• Precision management
• Plant growth regulators
Mechanical pruning
• Simplified planar systems – simplify pruning
• Investigated potential for mechanical
pruning in UFO since 2011
Mechanical pruning
•
•
•
•
Collard system
7 (vertical) or 4 (horizontal) circular saw blades
6-th leaf UFO
Hand vs. Mech. Vs. Mech + hand
Objective
Determine best
management practices
for pruning sweet cherry
and apple mechanically,
by understanding
equipment and orchard
requirements.
Mechanical pruning
•
Gillison’s GVF Center Mount
Topper and Hedger
•
Side shift ca. 1 .2 m on
either side of the tractor
•
Height adjustment of 1 m to
6.5 m
•
360° rotation of cutting head
Experiment outline
Sweet cherry
Mechanical hedging and
topping vs/+ hand pruning
Pre/postharvest topping
Apple
Mechanical pruning vs. hand
pruning
Sweet cherry trials:
Trial block details
Variety
Tieton
Rootstock
Training system
‘Gisela ®5’
UFO
Tree age
8th leaf
Tree spacing
2.5 x 3.1 m
Trial design:
Mechanical pruning vs. Hand pruning
3 treatments
•
•
•
x
5 reps
20 trees/rep
Completely randomized design
Post-harvest hedging and topping
YEAR 1
1. Hand pruning
2. Mechanical pruning (1)
3. Mechanical pruning (2)
YEAR 2
1. Hand pruning
2. Mechanical pruning
3. Mechanical pruning + Hand pruning
Data collection
• Time to prune
• Performance of the
machine
• Weight wood pruned
• Wood damage
• Economic evaluation
Preliminary results
(2014)
Wood pruned
0,07
0,06
Kg/cm2
0,05
0,04
0,03
0,02
0,01
0
Hand pruning
•
•
•
•
Mechanical pruning
Hand pruning removed 2 x wood removed than mechanical pruning
Hand pruning 10 kg/tree
Mechanical pruning 5 kg/tree
“Dirty cuts”
Results - Time
140
120
Time/rep (min)
100
80
60
40
20
0
Mechanical pruning
•
•
•
•
Hand pruning
Mechanical pruning 23 x faster than hand pruning (hedging and topping)
Hand pruning 374 sec/tree
6 min/tree
Mechanical pruning 16 sec/tree
0.3 min/tree
Tractor speed: 1.9 km/h
Example
• Sweet cherry orchard trained to
UFO training system
• Spacing: 2 m x 3.1 m
• 8 h work/day
• Mechanical pruning:
•
6 h/ha
• 1.3 ha/day
• Hand pruning:
•
135 h/ha
•
0.06 ha/day
Mechanical pollination
• Colony collapse disorder,
variable environmental
conditions, poor bloom
overlap, insufficient
pollenizers/pollinators all
threaten ability to set a crop
Solution:
• Collect pollen
• Suspend pollen
• Apply pollen via sprayer
Mechanical pollination
‘Tieton’/ ‘Gisela 5’: 8 years old trained to UFO
Mechanical pollination
f concept study
d pollen through bee exclusion
a
b
• Proof of concept study
• Sprayed pollen through bee
exclusion netting
• Two applications (50% and 90%
)
• Yield similar to open-pollinated trees
Fruit yield (kg/tree)
Mechanical pollination
7
6
5
4
3
2
1
0
a
b
Control
Treated
Mechanical pollination
Fruit set (%)
Mechanical shaking to transfer pollen
Self-fertile cultivars
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
a
b
Treated
Control
Mechanical harvest
• Harvest costs are >50% of all
• Labor cost increasing
• Labor availability decreasing
Mechanical harvest
• Taking short- and long-term approach
using total systems approach
– Mechanical assist (shake-and-catch)
– Fully mechanical harvest
In domestic and export markets, stem-free cherries are accepted/preferred
Plant growth regulators
• Post-bloom thinning
• GA3
• AVG for improving fruit set
15 May
73 DBH
9.7 mm
22 May
66 DBH
13.4 mm
29 May
59 DBH
14.0 mm
8 June
49 DBH
14.5 mm
Summary of 2012 trials
•
•
•
•
Ethephon is an effective post-bloom thinner
Efficacy is rate dependent
Early applications more effective
Quality improvements not assoc. with thinning
‘Skeena’
90%
140%
80%
120%
70%
100%
Fruit set (%)
60%
80%
50%
60%
40%
100 ppm
40%
30%
200 ppm
20%
20%
300 ppm
0%
11-may
10%
16-may
0%
11,00
Control
Hand thin
100
200
15 May
Fruit set (% of control)
Fruit weight (g)
10,00
300
9,00
8,00
7,00
6,00
5,00
4,00
Control
Hand thin
100
200
300
21-may
26-may
31-may
05-jun
10-jun
‘Sweetheart’
100%
90%
80%
15-May
Fruit set (%)
70%
60%
22-May
50%
29-May
40%
8-Jun
30%
Mean
20%
10%
0%
Control
Hand thin
100
200
300
Thinning efficacy declines with later applicatio
22 May
Fruit set (% of control)
160%
R² = 0,89
140%
120%
100%
100 ppm
80%
200 ppm
60%
300 ppm
40%
20%
0%
11-may
16-may
21-may
26-may
31-may
05-jun
10-jun
2013 Trials:
•
•
•
•
Lapins
Sweetheart x 2
Skeena
Santina
‘Lapins’
Fruit quality – weight (g) vs. fruit per foot
Allppm
treatments
200
ppm
100
Control
Ethephon
Ethephon
16
Fruit weight (g)
14
12
10
8
6
4
2
0
0
20
40
60
80
Fruit per foot
100
120
GA3 pre-harvest application timing
2010
2010
2010
GA Rates Sweetheart Skeena Staccato
0
380 a
371 c
320 b
0+ surfact.
10
20
417 a
405 b
459 a
25
30
416 a
414 ab 448 a
30 (20+10) 418 a
40
419 a
443 a
474 a
40 (20+20) 414 a
441 a
40 (30+10)
435 ab
50
60
417 a
447 a
440 a
60 (20+40) 417 a
427 ab
100
2011
2012
2012
Skeena Sweetheart Lapins
316 b
298 b
261 b
336 b
305 b
250 b
370 a
373 a
331 a
297 a
377 a
390 a
383 a
345 a
281 a
352 a
262 b
394 a
373 a
– Firmness was the most consistently affected attribute
– Response saturated at low concentrations (10 to 25 ppm)
– Response was not influenced by cultivar
GA Effects on Color
0 GA
10 ppm
20 ppm
30 ppm
40 ppm
60 ppm
• GA delays color
– inconsistent rate response (i.e., >25ppm did not
always result in further impairment)
• Delay in color allows fruit more time on tree
potentially resulting in greater size and SS
‘Kordia’ in Tasmania
Collaboration with Dugald Close, Sally Bound; UTas
Treatment
Fruit set (%) Fruit wt (g) Cracked fruit
(%)
Control
9.7 a
14.5 b
25.1 b
AVG 500 g/ha
15.3 b
12.9 a
14.0 a
Rate of AVG
ns
ns
ns
Time of
application
ns
ns
ns
(ca. ¾ pouch/ac)
Rate and timing studies
Pacific Northwest, 2013
• Rates:
– 0, 0.5, 1.0, 1.5 pouches/acre
– 0, 166, 333, 500 g/acre
• Timings:
– Popcorn, 10% FB, 50% FB, ca. FB
‘Regina’ in Zillah
Control
0.5 AVG
1.0 AVG 1.0 AVG
10% full bloom
full bloom
50% full bloom
10% full bloom
10% full bloom
50%
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
popcorn
Fruit set - % available flowers
1.5 AVG
ReTain  Regina Fruit Set
35
Fruit Set (%)
30
25
20
15
10
5
0
Control
Retain: 30 % Retain: 65 % Retain: 30 &
FB
FB
65 % FB
• Surfactant 0.1% v:v
• Rate 1 pouch (333 g) per acre
• Timing between 10 to 80% of full bloom
ReTain  Regina Fruit Set
Treatments
2011 Limb Trials
Control
Retain @ 30 % FB
Retain @ 65 % FB
Retain @ 30 & 65 % FB
Treatment
2013 Orchard Trials
Control
ReTain (1 pouch/a)
P>F
4 reps (RCBD), n=19
Yield per limb
(lbs)
1.6 b
3.1 a
3.0 a
3.0 a
Fruit per limb
(no.)
48 b
81 a
85 a
92 a
Avg. fruit weight
(g)
11.8
12.0
11.3
12.0
Yield
Projected based on actual tree density
(lbs/tree)
(tons/a)
51.9 b
6.3
69.2 a
8.4
0.022
• Product cost ~ $285/acre
‘Regina’ in The Dalles
Fruit set - % available flowers
10% Full bloom
70
- Natural set very high
+ 4 kg/tree
60
- Improved with AVG
50
40
30
20
Full bloom
10
0
Control
0.5 AVG
1 AVG
1.5 AVG
60
50
40
30
20
10
0
+ 0.5 kg/tree
Control
1 AVG
Mode of action – ‘Regina’
Percentage of Ovule Areas Lost Viabilities (%)
AVG treatment reduced ovule senescence
50
45
Popcorn
A
40
35
Full Open
AB
a
BC
30
C
25
b
20
b
b
15
10
5
0
Control
166g/acreAVG 333g/acreAVG
Treatments
499g/acreAVG
Recommendations:
• ReTain® applied at 10 +% full bloom
• 1 to 1.5 pouches per acre
• Particularly during warm weather
Picker reimbursement
• Current system for paying pickers is
inaccurate (piece-rate) and inefficient
– Growers over-paying
– Much conflict
– Payroll data entry is tedious/inaccurate
Mobile measurement system
1 – AccuPAR LP-80
2 – LI-COR quantum sensor
3 – I-O interface control box
4 – Deere E-Gator
5 – TRD-S encoder
PAR interception of vertical and
angled fruiting walls
Upright fruiting offshoots (UFO)
Y-trellis
PAR interception of vertical and angled fruiting walls
Diurnal trends of PAR interception of UFO and Y-trellis architecture. July 5th, 2011.
• Diurnal trend was nearly symmetric around solar noon
• Diurnal trend of Y-trellis was more moderate than UFO,
• higher relative to the UFO system
Pruning severity
Prepruning
Light
Postpruning
Medium
Heavy
Pruning severity levels:
• Light pruning: thinning cuts
and few heading cuts.
• Medium pruning: optimum
thinning cuts and few heading
cuts.
• Heavy pruning: many thinning
cuts and heading cuts.
Experiment
Samples: 45 trees, 15 blocks with
5 trees of each, 3 blocks for each
pruning level.
Data collection:
• PAR interception of pre- and
post-pruning.
• Length and diameters of both
ends of all branches in each
tree pre-pruning.
• Length and diameters of both
ends of all prunings from each
tree.
• Total weight of all prunings
from each tree.
Light interception vs. VCA
relative reduction of light
interception/tree (%)
30
Significantly different
(P<0.05)
25
27,2 c
Relative reduction of light interception =
(light interception (pre-pruning) – light
interception (post-pruning))/light
interception (pre-pruning) * 100%
20,2 b
20
15
12,3 a
10
Relative reduction of VCA = (VCA
(pre-pruning) – VCA (postpruning))/VCA (pre-pruning) * 100%
5
0
50
45
40
35
30
25
20
15
10
5
0
medium
pruning level
high
y = 1,0692x
R² = 0,4547
0
10
20
30
40
relative reduction of light interception/tree (%)
relative reduction of VCA/block (%)
relative reduction of VCA/tree (%)
light
40
y = 1,1032x
R² = 0,8393
35
30
25
20
15
10
5
0
0
10
20
30
40
relative reduction of light interception/block (%)
Conclusion
• Adoption of innovation has been slow in
cherry industry
• Market pressures will force innovation
• Research at WSU at leading edge
Muchas gracias
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