REFINING THE RELATIONSHIP BETWEEN CANOPY LIGHT ...walnutresearch.ucdavis.edu/2011/2011_143.pdf ·...

REFINING THE RELATIONSHIP BETWEEN CANOPY LIGHT

INTERCEPTION AND YIELD IN WALNUT

Bruce Lampinen, Shrini Upadhyaya, Vasu Udompetaikul, Greg Browne, David Slaughter,

Samuel Metcalf, Bill Stewart, Loreto Contador, Jedediah Roach, Bob Beede, Carolyn DeBuse,

Janet Caprile, Bill Coates, John Edstrom, Rachel Elkins, Joe Grant, Janine Hasey, Kathy Kelley,

and Bill Krueger

ABSTRACT

The existing mobile platform lightbar was redesigned in order to make it more robust and

adjustable to a wider range of tree spacings. In addition, more accurate soil temperature sensors

were added. This second generation mobile platform light bar was used during the 2011 season

and performed well. In addition to the second generation mobile platform light bar, a new

harvest supercart equipped with GPS, continuous yield monitoring capability, self contained

hydraulics and an auto-sampler were also built with partial funding from this project. Light

measurements continued on a large number of walnut orchards of varying ages and tree

densities. An upper limit of about 0.05 in-shell tons per acre for every one percent of light that

can be intercepted has continued to continued to be supported. When all of the walnut data from

the last three years was combined, it was found that midday canopy light interception increased

with orchard age until about 10-12 years when it tended to flatten and approach a value of near

93 percent. This results in a mature walnut orchard yield potential above 4 tons per acre. Work

was continued on the canopy sensor suite for assessing plant water status. The results were

promising and suggest the possibility of further developing this classification technique to assess

plant water stress for irrigation scheduling in walnut orchards. In particular, the results using

shaded rather than sunlit leaves were very encouraging and this should allow automating of the

process onto the mobile platform since it is not critical to assess leaf angle for shaded leaves.

PROBLEM AND ITS SIGNIFICANCE

Data collected by the authors over the past several years has provided a rough upper limit to

productivity in walnut and almond based on the percentage of the available midday canopy

photosynthetically active radiation (PAR) that is intercepted. However, most of the data that was

collected previously had limitations. The methods of measuring percent PAR interception using

a handheld light bar (Decagon Devices, Pullman, WA 99163) were relatively slow and labor

intensive. For this reason, much of the light bar data that was used to develop the relationship

was based on sampling of relatively small samples of trees. Often the area for the yield and PAR

interception data did not match (i.e. PAR data from 5 trees and yield data from either one tree or

from an entire row). In the 2009 and 2010 seasons, we began using the first generation light bar

for automated measurement of canopy PAR interception. In the winter of 2011, we completed

the second generation light bar which was mounted on the Kawasaki Mule in the spring of 2011

and used during the 2011 summer season. The new mobile platform light bar is continuously

adjustable from approximately 8-32 feet.

California Walnut Board 143 Walnut Research Reports 2011

The data generated with the mobile platform light bar are useful for any studies that aim to

quantify the impact of treatments on yield. By measuring canopy light interception on a large

scale, the impacts of differences in canopy development can be separated out from other

treatment impacts allowing more robust data interpretation.

OBJECTIVES

There were three objectives for this project in 2011. The first was to provide support to Shrini

Upadhyaya and David Slaughter to complete the light bar modifications to make it sturdier and

more adjustable as well as to work toward automating the data processing. The first generation

mobile platform light bar was developed with funding from the almond and walnut industries as

well as the USDA almond methyl bromide area wide project. An additional part of this objective

was added, which was to build a new supercart with load cells and GPS for more automated and

grower friendly yield data collection. The second objective was to find orchard sites, in

cooperation with farm advisors, throughout the walnut growing areas of California for testing the

light bar. These sites were chosen in orchards that have a variety of ages and light interception

levels. The goal was to find orchards that are well managed and as productive as possible to

attempt to place upper limits on the light interception/yield relationship. The third objective was

to develop technology for determining plant water status with sensor technology.

PROCEDURES

Objective 1. The plan was to use the funding from the California Walnut Board to improve the

design of the light bar for utilization in walnuts. This objective was designed to provide support

to Shrini Upadhyaya and David Slaughter to modify the existing light bar design to make it more

robust as well as user friendly and also to work toward automating the data processing. An

additional objective was added which was to purchase and equip a super cart with load cells and

global positioning satellite (GPS) equipment to allow continuous yield data to be gathered that

can be compared with the continuous light bar data.

Objective 2

Walnut orchard mapping- The plan was to obtain light bar data on individual rows in a variety of

walnut orchards and to then harvest these same rows to obtain yield data to compare to the light

bar data. During the 2011 season, a total of twenty eight different walnut orchards were mapped

with the mule light bar (Table 1). Several of the orchards were mapped multiple times during the

season to investigate the impact of time of year and environmental conditions on canopy light

interception (Table 1). Data was collected on 18 Chandler orchards, 4 Tulare orchards, 4 Howard

orchards, as well as a trial with Forde and Gillet (recent releases from the UC Davis Walnut

Improvement Program). In general, light bar measurements were either done in each replication

of a particular trial or in 5-10 row middles (depending on orchard size and variability) in

representative areas of grower orchards. These rows were then flagged and at harvest time, field

weights were taken from each row middle. Subsamples were taken from each row middle,

hulled, and dried to estimate in-shell crop weight for each row and samples were submitted for

quality analysis.


Table 1. Description of sites used for walnut light interception and yield mapping in the 2011 season. A total of 28

sites were mapped in 2011.

Objective 3

A pressure chamber or “pressure bomb” is often used to measure stem water potential of a plant

to determine plant water status. However, measuring plant water status using a pressure bomb is

tedious and time consuming, and is not suitable for measuring plant water status if a large

number of measurements need to be obtained for irrigation management purposes. The objective

of this portion of the project is to develop a sensing system that can determine the plant water

status quickly. Based on the energy balance model for a single leaf, the temperature difference

between the leaf and the surrounding air can be shown to depend on leaf conductance, net

radiation, vapor pressure deficit, and wind speed. Leaf conductance is a major plant parameter

limiting evapotranspiration rate that influences leaf temperature. Leaf conductance depends

upon many factors. During the midday period, the time that plants experience maximum water

stress, stem water potential is the major factor that controls leaf conductance. The other factors

that influence leaf temperature are vapor pressure deficit, solar radiation, and wind speed. A

sensor suite, consisting of an infrared thermometer, quantum sensor, pyranometer, ultrasonic

anemometer, and air temperature and relative humidity probe, has been developed to measure

leaf temperature and microclimatic information in the vicinity of the leaf to determine plant

water stress. Experiments were conducted to test the validity of this sensor suite.

Work on objective 3 was carried out during the summer of 2011 in 2 walnut orchards in Colusa

County. Within each orchard three blocks of 5 to 6 trees were established. During a given test, a

block was selected at random and leaf temperature, photosynthetically active radiation (PAR),

solar radiation, air temperature, and wind speed were measured using the sensor suite on each


tree. Stem water potential (SWP) and leaf conductance (gL) were measured using a pressure

chamber and leaf porometer respectively. Five sunlit and five shaded leaves were measured per

tree. Each observation consisted of averages of 5 leaf-air temperature (TLeaf-Tair), 5 PAR, 5 solar

radiation (Rs), 5 VPD, and 5 wind speed measurements. In addition, stomatal conductance

measurements were made on three each of the five sunlit and shaded leaves. One stem water

potential measurement was taken per tree. This experimental procedure was repeated between 5

to 12 times for a given orchard.

RESULTS AND DISCUSSION

Objective 1. Mule platform modification- The existing Mule mounted lightbar setup (Fig. 1a)

Fig. 1. (a). Design of Kawasaki Mule mounted lightbar as used during summer 2010. Modifications included adding a branch bumper on front designed to aid in pushing through orchards with many low overhanging branches. (b)-. Over the winter of 2010-11, the entire lightbar was redesigned and rebuilt and made much more protected, robust and adjustable.

a

b


has been modified in order to make it more robust and adjustable to a wider range of tree

spacings. This included rebuilding the entire light bar with a much more stable and more

adjustable base and a built in protective bumper to push low hanging branches up and over the

lightbar (Fig. 1b). A more accurate global positioning satellite (GPS) receiver and an encoder

that measures distances using the rotation of the axle were added to provide more accurate

positional information. In addition, three infrared thermometers with a much narrower angle of

view were added for measuring soil surface temperature under the tree canopy.

A load cell and GPS equipped supercart harvest trailer was also built with partial funding from

this project (Fig. 2). The trailer has self-contained hydraulics to operate the augers and rear

elevator as well as an autosampler. This allows the trailer to be used with almost any grower

harvesters since we do not need to match the hydraulic hookups to the growers equipment. The

trailer also allows our experimental harvest plots to be picked up and weighed on a continuous

basis with minimal disruption to grower harvest operations since we can offload the nuts into any

type of bank out system the grower uses. The yield data from the load cells on the trailer is

logged 10 times each second to the Trimble GPS unit which allows continuous yield data to be

compared to continuous light bar data.

Fig. 2. Load cell and GPS equipped supercart built with funding from this project.

This setup allows us to collect continuous yield data which is then logged to the

Trimble GPS unit.

Objective 2

A total of 28 orchards were mapped in 2011 (Table 1). Midday canopy light interception varied

from about 10 to 90 percent in the orchards studied in 2009-2011 (Fig. 3). Several of the

orchards were above the line in 2009 but in general, where these same orchards were measured

again in 2010 they tended to be below the line. Past data has suggested that alternate bearing may

allow orchards to rise above the line in one year but will then tend to be below the line in the


following year. Yield data was lost at several sites in all years due to problems with scheduling

harvests with growers and/or due to early fall rains making plot harvest difficult to fit within the

grower harvest schedule.

Measurements were also done throughout the season on an eight year old Howard pruning trial

in 2010 as well as a three year old Chandler/Tulare/Forde/Gillet pruning trial at Nickels Soil

Laboratory in Colusa County in 2010 and 2011. Midday canopy light interception was fairly

constant through the season for the more mature Howard pruning trial shown in Fig. 4. This

Midday canopy light interception (%)0 10 20 30 40 50 60 70 80 90 100

Yiel

d (d

ry to

ns/a

cre)

0

1

2

3

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6

R

R

R

RR

R

B BBB B

B

Y

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G

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G

Sutter Own-rooted trial Rio Oso OR Chandler/ParR

Sutter Own-rooted trial Rio Oso OR- Chandler/owB

Sutter Own-rooted trial Rio Oso OR- Vina/ParadoY

SutterOwn-rooted trial Rio Oso OR- Vina/own-rooG

Lake Walnut lightbar sites Lake County- Upper LSutter Walnut lightbar site Rio Oso #2Sutter Walnut lightbar site Rio Oso #1San Joaquin Tulare Farmington siteStanislaus Chandler site ModestoYolo County Chandler site MadisonYuba Tulare Surround trialColusa Nickels Howard pruning trial

2009

Midday canopy light interception (%)0 10 20 30 40 50 60 70 80 90 100

Yiel

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6Sutter Walnut lightbar site Rio Oso #2Sutter Walnut lightbar site Rio Oso #1San Joaquin Tulare Farmington siteYolo County Chandler site MadisonNickels Howard unprunedNickels Howard unpruned + nut removalNickels Howard prunedNickels Howard pruned + nut removalNickels Howard pruned 2006, hedged 2008Nickels Forde unpruned, unheadedNickels Forde moderately prunedNickels Forde heavily prunedNickels Gillet unpruned, unheadedNickels Gillet moderately prunedNickels Gillet heavily prunedNickels Tulare unpruned, unheadedNickels Tulare moderately prunedNickels Tulare heavily prunedRio Oso Orchard #3Solano Surround trial untreated controlSolano Surround trial Surround treated

2010

2011

Midday canopy light interception (%)

0 20 40 60 80 100

Yiel

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6 San Joaquin Tulare Farmington Site Yolo County Chandler site MadisonNickels Howard unhedgedNickels Howard skirtedNickels Howard hedgedNickels FordeNickels GilletNickels TulareNickels Chandler minimal prunedNickels Chandler untrained, unprunedNickels Chandler heavily prunedNickels Chandler minimal pruned plus deficitMature Chandler Lake CountyLake County 10 yr old ChandlerLake County 9 yr old ChandlerRio Oso Chandler #1Rio Oso Chandler #2Tehama mature Chandler #1Tehama mature Chandler #2Tehama 5 year old ChandlerTehama 6 year old ChandlerColusa 14 yr old Howard Orchard #1Colusa 14 yr old Howard Orchard #2

Fig.3. Midday canopy light interception versus yield relationship from various walnut trials

from throughout state measured with the Mule mounted light bar in 2009, 2010, and 2011.


Nickels Howard pruning trial 2010

Date, 2010

2010-4-1 2010-5-1 2010-6-1 2010-7-1 2010-8-1 2010-9-1 2010-10-1 2010-11-1

Mid

day

cano

py li

ght i

nter

cept

ion

(%)

0

20

40

60

80

100

T1 (unpruned)T2 (unpruned w/fruit removal)T3 (pruned)T4 (pruned w/fruit removal)T5 (pruned 2004 and hedged 2008)Mechanically hedged

Fig. 4. Midday canopy light interception for the Nickels Howard pruning trial over

the 2010 season by pruning treatment.

suggests that measurements on mature orchards can probably be done from early June to late

August with similar results. Seasonal midday canopy light interception through the 2011 season

for the Chandler pruning trial is shown in Fig. 5. There were no significant treatment difference

at any point during the season. However, the large seasonal change in midday canopy light

interception in the younger Chandler orchard (Fig. 5) compared to the older Howard orchard

(Fig. 4) suggests that the seasonal timing of measurements in young orchards is much more

critical. For instance, the minimal pruned treatment increased from about 25 to 45 percent

midday canopy PAR interception from late May to October in 2011 (Fig. 5).

Fig. 5. Midday canopy light interception over the 2011 season for Nickels Chandler

pruning trial. There were no significant treatment differences on any date in 2011.

Date, 2011

Apr May Jun Jul Aug Sep Oct Nov

Mid

day

cano

py P

AR

inte

rcep

tion

(%)

0

10

20

30

40

50

Heavily pruned (T1)Minimally pruned plus deficit (T2)Minimally pruned (T3)Untrained, unpruned (T4)


Fig. 6 shows the yield per unit PAR intercepted (expressed as in-shell pounds per 1% PAR

intercepted) for the 2009 through 2011 seasons. The line at 100 is the maximum sustained level

Fig. 6. Yield per unit PAR intercepted by treatment and year for Chandler pruning trial at Nickels

Soil Laboratory. Solid line indicates yield per unit PAR intercepted for the highest yielding

orchard in our light bar study, a 10 year old Tulare orchard in San Joaquin County. Dotted line

shows our current estimate of the highest sustained production level for walnut.

of production that might be expected in a mature orchard and we have had one mature Tulare

orchard in our trial for three years that has produced very close to the maximum level for all 3

years (solid line in Fig. 6). It is interesting that the average for the Chandler pruning trial

treatments for the 2010 and 2011 seasons is close to the maximum level since this orchard is still

filling in the space allotted (Fig. 6).

Midday canopy PAR interception increased with orchard age until about 10-12 years when it

tended to flatten and approach a value of near 93 percent (Fig. 7). The potential rate of increase

in years 1 to 10 is about 8-9% per year. The rate is dependent on tree spacing, variety, rootstock,

water management, etc. These data give growers a tool to evaluate their orchard performance

relative to others.

Orchard floor temperature- The impact of midday canopy light interception on soil surface

temperature is shown in Figure 8. There is a clear relationship between midday canopy light

interception on the left side of the light bar and soil surface temperature with the high soil

temperatures (approximately 60°C) occurring when midday canopy light interception is low.

Even though this orchard is only three years of age, the cool temperatures that are associated

with shaded orchards are beginning to show up underneath the tree canopy as shown by the 30°C

Year

2008.5 2009.0 2009.5 2010.0 2010.5 2011.0 2011.5

Yiel

d pe

r uni

t PA

R in

terc

epte

d (in

she

ll pou

nds/

per 1

%P

AR

)

0

20

40

60

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100

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Heavily prunedMinimal pruned plus deficit in 2011Minimal prunedUntrained, unprunedHighest yielding mature Tulare orchard


Fig. 7 shows the midday canopy light interception versus orchard age for walnut sites (each point is the

average for an orchard) measured with the Mule light bar during the 2009-2011 seasons. The upper

boundary to the relationship appears to be about an 8- 9% rate of increase from years 1-10 and then a

leveling off eventually approaching a level of interception of about 93%. The low points for age 22-24

are for orchards that were mechanically hedged.

temperature reached under the tree on the right as it reaches about 90% light interception (Fig.

8). Figure 9 shows similar data for a mature Tulare planting that has produced 4 tons per acre for

Fig. 8. The top graph shows fractional midday PAR interception (multiply by 100 to get percent midday PAR

interception) while the bottom graph shows orchard floor temperature (in degrees Centigrade) for the corresponding

drive row center for a methyl bromide alternatives trial in Kings County, California measured on Aug. 30, 2011.


the past three years. Note that the high temperatures coincide with the lowest PAR interception

and the low temperatures with the highest PAR interception. These data will be useful in

assessing impacts of different canopy management regimes on soil surface temperature which

can relate to food safety risk since ideal temperature for Salmonella survival in the soil is in the

range of 30-35 deg C which is what the shaded areas in walnut orchards generally reach in the

Central Valley of California during mid-summer. Because mature walnut orchards tend to be

heavily shaded, the potential for food safety risk cannot be ignored.

Fig. 9. The top graph shows fractional midday PAR interception (multiply by 100 to get percent midday PAR

interception) while the bottom graph shows orchard floor temperature (in degrees Centigrade) for the corresponding

drive row center for a mature Tulare walnut orchard in San Joaquin County that has produced an average of 4 tons per

acre for the past three years. Data collected on 7/30/2011.

Objective 3

Determining plant water stress using an IR thermal sensor- Based on the energy balance model

for a single leaf, the temperature difference between the leaf and surrounding air can be shown to

depend on leaf conductance, net radiation, vapor pressure deficit, and wind speed. Leaf

conductance is a major plant parameter limiting the rate of evapotranspiration which influences

leaf temperature. Leaf conductance depends upon many factors. During the midday period,

when plants experience maximum water stress, stem water potential is the major factor that

controls leaf conductance. The other factors that influence leaf temperature are vapor pressure

deficit, solar radiation, and wind speed. A sensor suite, consisting of an infrared thermometer,

quantum sensor, pyranometer, ultrasonic anemometer, and an air temperature/relative humidity

probe, has been developed to measure leaf temperature and microclimatic information in the

vicinity of the leaf to attempt to relate these factors to plant water stress. Experiments were

conducted in two walnut orchards in 2010 to test the validity of this sensor suite. In the models

presented in Table 2, the response variable is the temperature difference between the leaf and the

surrounding air and plant water status or its surrogate, stomatal conductance, is the independent

or predictor variable. The approach was to use a threshold value of temperature differences

corresponding to critical values of SWP. A walnut tree at -8 bars was considered to be stressed

(i.e. in need of irrigation).


The approach predicted correct plant water status in 95% to 100% of the cases for walnuts (using

validation data sets). In terms of rating trees which are stressed as unstressed, which is

designated as a “ critically wrong decision” as this has implications for plant growth and yield,

the results varied between 0% to 5% for walnuts. A less serious error that would lead to over-

irrigation (i.e., detecting unstressed trees as stressed) also occurred in 0% to 5% of validation

datasets for walnut.

These results are promising and suggest the possibility of further developing this classification

technique to assess plant water stress for irrigation scheduling in walnut orchards. Improvements

such as use of a newer, more sensitive IR sensor and more advanced analysis techniques may

further improve plant water status prediction in walnuts. The success of the shaded leaf method

allows the possibility of automating the process onto the mobile platform since it is not critical to

assess leaf angle for shaded leaves.

Table 2. Results for a multiple regression model using data from the sensor suite to

predict plant water status. The percent correct prediction for each leaf type and

regression method is shown in the right hand column. Results for walnuts were very

promising with both shaded and sunlit leaves showing good results (above 94% correct

prediction).

Walnuts All leavesStepwise -All Predicted %Correct prediction 93.7%

Measured Total Stress Non-Stress %Wrong prediction 6.3%

Stress 50 47 3 %Critically wrong prediction 3.2%

Non-Stress 45 3 42 %Potential over-irrigation 3.2%

Stepwise -Va lida tion Predicted %Correct prediction 94.7%




Walnuts Shaded leavesStepwise -All Predicted %Correct prediction 95.7%




Stepwise -Va lida tion 0.76 Predicted %Correct prediction 100.0%




Walnuts Sunlit leavesStepwise -All Predicted %Correct prediction 95.9%




Stepwise -Va lida tion Predicted %Correct prediction 100.0%





Plans for 2012- The first objective will be to further refine the relationship between midday

canopy light interception and yield as well as the impact that alternate bearing has on the

relationship. With a better estimate of the maximum productivity per unit light interception,

these data can be used to assess potential orchard yield and will allow separating out canopy light

interception as a variable in other research projects. For example, if a pruning study is being

conducted, this tool will allow the separation of the effect of the pruning treatment on overall

canopy light interception as opposed to the effect of the pruning treatment on productivity per

unit canopy. It will also allow block to block variability to be assessed before or after a research

trial in initiated. 2012 will be the first season where the 2nd

generation mobile platform will be

fully functional from the beginning of the season (last year soil temperature sensors were not

fully functional until mid to late summer). The second objective will be to continue to refine

using the sensor suite to assess plant stress in walnut.


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