TRABAJO FIN DE MASTER

Application of thermography for the assessment ofvineyard water status

Helga Ochagavía Orbegozo

PROGRAMA DE DOCTORADO ECOSISTEMAS AGRÍCOLAS SOSTENIBLES

Tutor: Javier Tardáguila LasoFacultad de Ciencias, Estudios Agroalimentarios e Informática

Curso 2010-2011

© El autor© Universidad de La Rioja, Servicio de Publicaciones, 2012

publicaciones.unirioja.esE-mail: publicaciones@unirioja.es

Application of thermography for the assessment of vineyard water status,trabajo final de estudios

de Helga Ochagavía Orbegozo, dirigido por Javier Tardáguila Laso (publicado por laUniversidad de La Rioja), se difunde bajo una Licencia

Creative Commons Reconocimiento-NoComercial-SinObraDerivada 3.0 Unported.Permisos que vayan más allá de lo cubierto por esta licencia pueden solicitarse a los

titulares del copyright.

Trabajo de investigación del Programa de Doctorado: “Ecosistemas Agrícolas Sostenibles”, Universidad de La Rioja

Author: Helga Ochagavía Orbegozo

Led by: Dr. Javier Tardáguila Laso

Curso académico: 2010-2011

Application of thermography for the assessment of vineyard water status

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Contents

Acknowledgments…………………………………………………………………………………..2

Abstract……………………………………………………………………………………………….3-4

1. Introduction……………………………………………………….…………………….…...5-9

2. Objectives…………………………………………………………………….……....…..10-11

3. Material and methods…………………………………................................12-17

3.1 Experimental layout………………………….…………..13-14 3.2 Thermal imaging…………………………………………...14-15 3.3 Stress indices and references surface temperatures………………………………………………..…...15-16 3.4 Stomatal conductance and stem water potential measurements…………………………………………………..…….16 3.5 Statistical analysis……………..……………..……..….……..17

4. Results……………………………………………………………………………………....18-30

4.1 Methods of extraction of thermal data: Temperatures of several sun exposed leaves versus Temperatures of regions of interest of the canopy ………………………………………………………………………19-20

4.2 Relationship between temperature, stomatal conductance and stem water potential: Timing effect…………..……………………………………..21-24 4.3 Relationship between stress indices, stomatal conductance and stem water potential: …………………..…………..……………………………..……...25-28 4.4 Frequency distributions of temperatures….....29-30

5. Discussion…………………………………………………………………………..….....31-35

6. Conclusions………………………………………………………………………………..36-37

7. References………………………………………………………………………………...38-41

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Acknowledgments

First, thanks to Televitis group (Dr. Javier Tardáguila, Dra. Maria Paz Diago, Javier

Baluja and Juan Antonio Blanco) which gave me the opportunity to work under their

guidance.

Thanks to Dr. Javier Tardáguila to lead this work.

Thanks to Dr. Olga Grant of University of Maynooth, Ireland, to welcome me in her lab.

I feel truly fortunate to work with her during three months. I really appreciate her help

and her infinite patience.

This project was supported by MoDeM_IVM Project: A web-based system for real-time

Monitoring and Decision Making for Integrated Vineyard Management.

My parents who I admire because they always are with me and support me in all my

decisions: Mª Pilar y Jesus.

My relatives which only with their presence make me happy, Lara, Sergio, Imanol,

Mamen, Abel, Eduardo, Naiara y Gonzalo.

My friends who do my life as enjoyable experience: Andrea, Raquel, Clara, Diana,

Daniel, Alberto, Ainhoa, Sonia y Esteban.

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Abstract

The applicability of thermography to assessment of vineyard water status was

determined in grapevines subjected to different water availability. Thermal images of

the sunlit side of canopies (lateral thermography) were compared with images taken

above the vine (zenithal thermography). Canopy temperature was determined either

by averaging the temperature of several individually selected sun-exposed leaves or by

extracting the average temperature of a region of canopy. Wet and dry artificial

‘leaves’ were included in images as references for calculation of the stomatal

conductance index (IG) and the crop water stress index (CWSI). Thermal data were

compared with stem water potential and stomatal conductance of the same vines.

Similar relationships between these physiological measurements and either method of

temperature extraction indicate the two methods are equally useful. Lateral

thermography in the afternoon was more useful than in the morning. Zenithal

temperatures were similarly indicative of vine water status compared to lateral

imaging.

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Abstract

Se determinó la aplicabilidad de la termografía para evaluar el estado hídrico del

viñedo en cepas sujetas a diferente disponibilidad hídrica. Las imágenes térmicas de la

parte iluminada de la canopy (termografía lateral) fueron comparadas con las

imágenes tomadas en la parte superior de la canopy (termografía cenital). Se

determinó la temperatura de la canopy mediante la temperatura media de diversas

hojas iluminadas seleccionadas individualmente y a partir de la temperatura media de

una región de la canopy. En cada imagen se incluyeron como referencias `hojas´

artificiales húmedas y secas con el fin de calcular el índice de conductancia estomática

(IG) y el índice de estrés hídrico del cultivo (CWSI). Se compararon los datos térmicos

con el potencial hídrico del tallo y con la conductancia estomática de las mismas cepas.

Las relaciones similares entre estas dos medidas fisiológicas con cualquiera de los dos

métodos de extracción de temperatura indican que los dos métodos son igualmente

útiles. La termografía lateral de la tarde fue más óptima que la de la mañana. La

termografía cenital fue similarmente indicativa del estado hídrico del viñedo al

compararla con las imágenes laterales.

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1. INTRODUCTION

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The most important wine regions in the world are located in areas which are

seasonally dry with high evaporative demand and low water availability. In recent

decades, these characteristics are being aggravated by climate change. Alterations in

precipitation patterns and air temperature induce changes in runoff and water

availability. At the regional level, irrigation demand will be increased due to those

climate changes, with water becoming the main factor limiting production (IPCC 2007).

Both grape yield and quality are influenced by water availability (Chaves et al. 2007;

Matthews and Anderson 1988).

Viticulturists are demanding solutions to the changing environmental situation and the

most widespread strategy to deal with these changes is based on more irrigation to

stabilize yield and improve subsequent wine quality (Chaves et al. 2007). Excess

irrigation may result in high canopy density causing shade in grape clusters. This may

lead to lower grape quality, affecting colour and reducing sugar content. Severe

drought, on other hand, may lead to leaf stomatal closure with lowered

photosynthetic rate, which negatively affects some berry quality characteristics

(Chaves et al. 2007). An intermediate solution between the two situations described

above is deficit irrigation, where the crop is given sufficient irrigation to maintain

quality but less than 100% evapotranspiration either throughout the growing season or

in a specific phenological stage. With this irrigation management strategy, a balance

between vegetative and reproductive development needed to improve grape quality is

achieved (Dry et al. 2001).

The measurement of stem water potential is one of the most used methods for

monitoring water stress in the vineyard, as it was an early indicator of water limitation

(Choné et al. 2001). The procedure, however, is destructive and time-consuming and

therefore unsuited to detecting spatial variation in water status within a large

vineyard. Sap flow meters are another tool to determine water stress, but have the

disadvantage of possibly interfering with plant performance (Fernandez et al. 2001).

Dendrometers also allow evaluation of the amount of available water through

continuous measurement of the stem diameter variations (Intrigliolo and Castel 2007),

but they require a complicated installation and they need maintenance. Imaging

techniques, such as thermal and fluorescence imaging can be used to non-

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destructively assess spatial and temporal changes when the plant is stressed (Chaerle

and Van Der Straeten 2000).

Fig. 1 Different strategies to evaluate vineyard water stress. Water potential measurement (a), sap flow

(b), dendrometers (c) and thermography (d).

Thermography allows the visualization of differences in surface temperature from

emitted infrared radiation. This technique relies on the fact that when water is lost

through the stomata, leaf temperature decreases, but when stomata close, leaf

temperature increases (Costa et al. 2010). Thus, leaf or canopy temperatures can be

considered as an indicator of stomatal conductance and hence canopy stress (Jones et

al. 2002). Leaf or canopy temperatures are sensitive to environmental factors. Stress

indices have been developed to remove the impact of environmental variation. The

“Crop Water Stress Index” (CWSI) which was elaborated by Idso et al. (1981) involves

normalization of both the effects of atmospheric humidity and the expected

temperature of a well-watered crop. It was adjusted to use wet and dry reference

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surfaces by Jones et al. (1999). Alternatively, the stomatal conductance index (IG) was

firstly proposed by Jones et al. (1999), and it is proportional to stomatal conductance.

The choice of appropriate references to calculate these stress indices is important.

Vine leaves used as references have similar radiometric and aerodynamic properties to

the canopy studied and therefore are more suitable than wet and dry white filter

paper references (Jones et al. 2002). However, Grant et al. (2007) showed that the use

of individual wet and dry leaves as references to calculate stress indices might not be

suitable for whole canopies and differences of time between spraying the wet leaves

and taking the image may cause errors. For these reasons, it was decided to explore an

alternative to the use of wet and dry reference leaves. A new approach to the use of

references surfaces is presented in this paper. This alternative approach uses two

artificial leaves composed of platinum, one of which is covered in a black cotton which

continually absorbs water from a small reservoir. This prevents drying out of the

artificial wet leaf and removes the need to keep spraying the wet reference. The

references are placed under the same environmental conditions as the plant canopy of

interest and thus are exposed to the same solar radiation, air temperature, relative

humidity and air movements.

Recently, thermography is being used from mobile or aerial platforms in order to

expand the area of view and to remotely assess the water stress of several crops. In

cotton, a thermal camera was mounted at a height of a 5 m above the ground,

increasing the field of view at canopy level (Cohen et al. 2005). In olives trees, Ben-Gal

et al. (2009) used two cameras (thermal and visible cameras) mounted on a truck-

crane about 15 m above the canopy. A similar approach was applied by Möller et al.

(2007) in grapevine. The resolution obtained permitted differentiating between leaves

and soil, and distinguishing sun-exposed leaves from shaded leaves.

In another vineyard, Jones et al. (2009) made thermal and visible images from a

balloon at a height of 80 m.

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Fig. 2 Thermal and digital images of vineyard taken from a balloon (Jones et al. unpubl. data)

A vineyard is not a continuous crop, vines are planted in rows, and canopy width is

usually within the range 30-50 centimeters for VSP trellis system (vertically shoot

positioned vines). Generally, leaves face into the row rather than upwards. Most

published data from thermal imaging of grapevine relates to images taken facing the

rows (lateral thermography) (Grant et al. 2007; Jones et al. 2002; Loveys et al. 1999),

but whether images taken from above the canopy can capture information of vine

status and crop stress equally well still needs to be explored. Thus, it is important to

compare thermal images from above the canopy (zenithal thermography) and thermal

images taken facing the vine row (lateral thermography) for the determination of

vineyard water status.

One of the problems that thermometry presents is the separation of temperatures of

leaves of interest from non- leaf temperatures (temperatures of soil, sky, trunk…).

With the development of thermal imaging along with increasingly sophisticated image

analysis software this is no longer a problem. Different approaches have been

employed to exclude non-leaf temperatures (Giuliani and Flore 2002; Leinonen and

Jones 2004).

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2. OBJECTIVES

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The main goal of this study was to explore zenithal and lateral thermography for

determining vine (Vitis vinifera L.) water status under field conditions. Therefore, the

relationships between canopy temperatures, or indices derived from these

temperatures and stomatal conductance and water potential were determined. In

addition:

i. The time of the day for acquisition thermal images were explored.

ii. The extraction of canopy temperatures in image analysis, were compared from

several sun exposed leaves and from a region of interest of the canopy which

contain an area of vine leaves.

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3. MATERIALS AND METHODS

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Experimental layout

The field experiments were carried out in 2010 in a commercial vineyard, located in

Tudelilla, La Rioja, Spain. An experimental plot (42° 18' 21.00''N, 2° 7' 18.58'' W) of

Tempranillo grapevine (Vitis vinifera L.) grafted in 2002 onto 110R rootstock and

trained to vertically shoot positioned (VSP) system and spur-pruned to 12 nodes per

vine was studied. The vines had a between-row and within-row spacing of 2.6 1.2 m

respectively. The orientation of rows was NE-SW. Shoot trimming was performed once

in June.

The shallow soil at the site had a light clay texture and low fertility. The climate of this

area was Mediterranean and semiarid, with hot summers and average annual rainfall

of 400 mm, with very scarce precipitation during the summer.

Fig. 3 Commercial vineyard where the field experiments were carried out, located in Tudelilla, La Rioja,

Spain

Four different irrigation regimes were applied to develop a large range of water status

in the vineyard: Rain-fed (non-irrigated) (RF), standard irrigation (SI), moderate

irrigation (MI) and full irrigation (FI). Irrigation was applied every day from 1 July until

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15 September and frequency varied from 1, 2 and 3 hours per day for standard

irrigation, moderate irrigated and full irrigation, respectively. Drip irrigation was

applied with pressure-compensated emitters of 2.0 l h-1, separated 0.80 m in the vine

rows. Each irrigation regime was tested in four experimental rows. Five vines per

irrigation regime were selected randomly within two central rows, marked and used as

experimental plants for measurements.

Thermal imaging

Thermal images were taken with a thermal camera (ThermaCAM P640, FLIR Systems,

Sweden) that operates in the wavebands 7.5-13 µm, has a thermal resolution of 0.06°C

and accuracy of ± 2°C and produces pictures with spatial resolution of 640 × 480 pixels.

The thermal camera also provided digital colour images (RGB). Lateral images in the

morning were obtained at 10:00 h and lateral images in the afternoon at 16:30 h on 4

and 5 September 2010. Zenithal images were taken at 14:30 on 4 September 2010.

Lateral images were taken from the sun-exposed side of the canopies at 1.5 m from

the canopies, and zenithal images of the top of the canopies were captured from a

truck-crane at 1.5 m above the canopies.

Fig. 4 Lateral photograph (a) and thermal image (b) of non-irrigated grapevine canopies.

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Fig. 5 Zenithal photograph (a) and thermal image (b) of non-irrigated grapevine canopies.

Five replicate plants were imaged per irrigation regime. All images were analyzed with

ThermaCAM Researcher Pro 2.9 software (FLIR Systems, Sweden). For each image

analyzed, the background reflectance temperature required for the calculation of

object temperatures was estimated as the radiative temperature of a crumpled

aluminum foil sheet placed in the same position as the object being viewed, with

emissivity set at 1.0. Emissivity for measurements of leaves and plant canopies was set

at 0.96 according to Jones (2004). By comparison of the thermal and RGB images of

each vine, four fully exposed leaves per vine were selected to obtain average

temperatures. In addition, in each image, a region of interest (ROI) of the canopy of

213 × 160 pixels approximately that included an area of vine leaves was selected and

average temperatures and frequency distributions of pixels in that ROI of the canopy

were calculated.

Stress indices and references surface temperatures

Wet and dry references temperatures were used for the derivation of stress indices,

which do not required environmental information. An evaporimeter (EvapoSensor,

Skye Instruments Ltd, Powys, UK) was used to provide artificial leaves which act as wet

and dry references. Wet and dry references were used to simulate leaves with open

and fully closed stomata, respectively. The artificial leaves were composed of black

metal (platinum), 5 cm long × 1 cm wide and 0.5 cm thick. The wet artificial leaf was

maintained wet by means of a wick of black cotton which continuously absorbs water

from a small reservoir, which was filled with distilled water. The evaporimeter was

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placed on handmade holders with the artificial leaves facing the same direction as the

canopy of interest.

The temperatures of these references were obtained from the thermal images and

were used in conjunction with canopy temperature to calculate the thermal indices.

The crop water stress index (CWSI) was calculated as:

CWSI= (Tcanopy─Twet) / (Tdry─Twet) (Idso et al. 1981)

and the stomatal conductance index (IG) was calculated as

IG= (Tdry─Tcanopy) / (Tcanopy─Twet) (Jones et al. 1999),

where Tcanopy was the mean temperature of the leaf area of the experimental plant, Tdry

was the temperature of the dry reference and Twet was the temperature of the wet

reference.

Stomatal conductance and stem water potential measurements

Stomatal conductance (gs) of two leaves per vine located within the area captured in

the thermal image on five vines per irrigation regime, was measured immediately after

each lateral thermal infrared image using a gas-exchange system (LC pro+, ADC, USA),

at 10:00 in the morning and 16:30 in the afternoon.

Stem water potential (Ψstem) was measured at midday (14:00, solar noon) using a

Scholander-type pressure chamber (model 600, PMS Instrument Company, USA) on

two leaves per vine, on five vines per irrigation regime. These physiological parameters

were measured on sun-exposed fully mature main leaves.

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Statistical analyses

The coefficient of determination (R2) and the significance of the correlations was

tested, using InfoStat software (Professional Edition 2010, Córdoba, Argentina), to

determine the relationship between canopy temperatures, stress indices and the

different physiological parameters.

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4. RESULTS

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Methods of extraction of thermal data: Temperatures of several sun exposed leaves

versus Temperatures of regions of interest of the canopy

The different methods of extraction of thermal data in the image analysis were

compared for lateral images in the morning, lateral images in the afternoon and for

zenithal images on 4 September (Fig. 6).

Strong relationships were found between the two methods of extraction (Fig. 6), but

average temperatures of regions of interest of the canopy were cooler than average

temperatures of several sun exposed leaves, indicating that selection of regions of

interest of the canopy might contain shaded leaves, which decrease average

temperatures, whilst that selection of several sun-exposed leaves presented higher

temperatures than shaded leaves.

The relationships between canopy temperatures extracted from both methods of

extraction, both stress indices (IG and CWSI) calculated from those canopy

temperatures and both physiological parameters (stomatal conductance and water

potential) will be described in the next sections.

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Fig. 6 Correlation between average canopy temperatures of several leaves and average canopy temperatures of an area of vine leaves on 4 September (A, B, C) (n=17-20) for lateral canopy in the morning (A), lateral canopy in the afternoon (B) and zenithal canopy (C)

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Relationship between temperature, stomatal conductance and stem water potential:

Timing effect

Average canopy temperatures of the region of interest of the canopy were not

significantly correlated with either stomatal conductance (Fig. 7A) or stem water

potential (Fig. 7B) for the lateral canopy in the morning on 4 September. However, in

the thermal data measured on 5 September, average canopy temperatures of the

regions of interest of the canopy were highly significantly correlated with stomatal

conductance (Fig. 7E) and water potential (Fig. 7F) for this time of thermal image

acquisition.

When the extraction of average canopy temperatures was carried out from selection

of several sun- exposed leaves, canopy temperature again was not significantly

correlated with stomatal conductance or stem water potential on 4 September during

the morning (Fig. 7C and 7D, respectively). Nevertheless, on 5 September during the

morning, the correlations between average canopy temperatures (extracted from a

selection of several leaves) and both physiological parameters (stomatal conductance

and stem water potential) were strongly significant (Fig. 7G and 7H, respectively). In

this date, the relationships between average canopy temperatures of a ROI of lateral

canopy in the morning with both physiological parameters was stronger than the

correlations obtained when average canopy temperatures of several sun exposed

leaves was used.

Average canopy temperatures of a region of interest of the canopy and stomatal

conductance were highly significant for both lateral canopies in the afternoon and for

zenithal canopy on 4 September (Fig. 7A). Moreover, both lateral temperature in the

afternoon and zenithal temperature were negatively correlated with stem water

potential (Fig. 7B). Stem water potential exhibited values between ─0.7 MPa and ─1.7

MPa, indicating that some vines were not under water deficit (≥─1.0 MPa) and other

vines showed intense water deficit (≤─1.6 MPa). Strong correlations between average

canopy temperatures of ROI of the canopy and both physiological parameters (gs and

Ψstem) were also found on 5 September in the afternoon (Fig. 7E and 7F, respectively).

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Fig. 7 Correlations between stomatal conductance, gs (A, C ,E , G) or stem water potential, Ψstem (B, D, F, H) measured on 4 (A, B, C, D) and 5 (E, F, G, H) September 2010 and canopy temperatures (n=17-20). Canopy temperatures represent the average temperature of a region of interest (ROI) of the canopy of 213 × 160 pixels, approximately (A, B, E, F) and of several sun exposed leaves (C, D, G, H). In each graph, R

2 values from top to bottom respectively correspond to lateral canopy temperature in the afternoon (

open circles), zenithal canopy temperature ( triangles) and lateral canopy temperature in the morning ( filled circles).

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Stronger coefficients of determination were found between canopy temperature and

stomatal conductance/water potential from lateral canopy in the afternoon than

zenithal canopies (Fig. 7A and 7B). Lateral canopy temperatures in the afternoon were

higher than both lateral canopy temperatures in the morning and zenithal canopy

temperatures. In the afternoon, lateral canopy temperatures reached 38°C, whereas

lateral canopy temperatures in the morning and zenithal canopy temperatures peaked

at 28°C and 33°C, respectively. The relationship between canopy temperature and

stomatal conductance and stem water potential was similar for lateral canopy in the

afternoon and zenithal images (Fig. 7A and 7B):

Canopy temperature = ─0.03 gs + 36.2 (lateral in the afternoon)

and

Canopy temperature = ─0.03 gs + 32.7 (zenithal)

and

Canopy temperature = ─5.51stem + 26.7 (lateral in the afternoon)

and

Canopy temperature = ─4.50stem + 24.7 (zenithal) (Fig. 7A and 7B),

where canopy temperature is measured in °C and gs in mmol m-2 s-1 and stem in MPa.

Average canopy temperatures in lateral canopies in the afternoon obtained from

several sun exposed leaves were significantly correlated with stomatal conductance

and with stem water potential on 4 September (Fig. 7C and 7D, respectively). During

the afternoon, higher coefficients of determination were found in the regressions that

employed average canopy temperatures of several sun exposed leaves on 4

September.

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However, no significant correlation was presented between the average canopy

temperatures of several leaves and either stomatal conductance or stem water

potential on 5 September during the afternoon (Fig. 7G and 7H, respectively). For this

date, the correlations were higher when average temperatures of a region of interest

of the canopy were used.

Average canopy temperatures extracted of several leaves corresponding zenithal

canopy on 4 September presented high correlations with stomatal conductance and

with stem water potential (Fig. 7C and 7D, respectively). Similar coefficients of

determination (R2) were found for the two methods of extraction. Overall, neither

method of extraction appears to be preferable to the other.

As expected from these results, average temperatures of lateral canopy in the

afternoon and average temperatures of zenithal canopy were significantly correlated

for both methods of extraction of canopy temperatures, showing similar coefficients of

determination (R2) (Fig. 8).

Fig. 8 Correlation between zenithal canopy temperature and lateral canopy temperature in the afternoon on 4 September (n=15-19) obtained from two different methods of extraction: average canopy temperatures of several sun exposed leaves ( filled circles) and average canopy temperatures of a region of interest of canopy ( open circles).

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Relationship between stress indices, stomatal conductance and stem water potential

In the morning of 4 September IG and CWSI were not significantly correlated either

with stomatal conductance (Fig. 9A and 9C, respectively) or stem water potential (Fig.

9B and 9D, respectively). However, statistically significant correlations between both

stress indices and both physiological parameters were found on 5 September with the

extraction of temperature from a region of interest of the canopy (Fig. 10A, 10B and

10C), with the exception of the relationship between CWSI and water potential (Fig.

10D). IG and CWSI obtained from several sun exposed leaves which were within the

lateral canopy in the morning were not significantly correlated either with stomatal

conductance (Fig. 9E and 9G, respectively) or stem water potential on 4 September

(Fig. 9F and 9H, respectively). However, IG and CWSI indices from the average

temperature of several sun exposed were significantly correlated with both

physiological parameters (gs and Ψstem) on 5 September in the morning (Fig. 10E, 10F,

10G and 10H, respectively). For this date, generally, the correlations were higher when

average temperatures of region of interest of canopy were used, compared to the

average temperature of several sun exposed leaves.

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Fig. 9 Correlations between stomatal conductance, gs (A, C, E, G) or stem water potential, Ψstem (B, D, F, H) and IG (A, B, E, F) and CWSI (C, D, G, H) on 4 September 2010 (n=15-19). Canopy temperatures represent the average temperature of a region of interest (ROI) of the canopy of 213 × 160 pixels, approximately (A, B, C, D) and of several sun exposed leaves (E, F, G, H). In each graph, R2 values from top to bottom respectively correspond to lateral canopy temperature in the afternoon ( open circles), zenithal canopy temperature ( triangles) and lateral canopy temperature in the morning ( filled circles).

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IG obtained from lateral temperatures in the afternoon from a ROI of the canopy

showed a significant correlation with stomatal conductance on 4 September (Fig. 9A).

For the same day, significant correlation was exhibited between IG obtained from

zenithal temperatures and stomatal conductance (Fig. 9A). Furthermore, IG indices

calculated from both lateral and zenithal temperatures in the afternoon presented a

significant correlation with stem water potential (Fig. 9B). CWSI indices calculated with

both lateral and zenithal temperatures in the afternoon from a region of interest of the

canopy showed strong correlations with stomatal conductance and with stem water

potential (Fig. 9C and 9D, respectively). The relationship between both thermal indices

(IG and CWSI) and both physiological parameters (gs and Ψstem) was strongly significant

during the afternoon on 5 September (Fig. 10A, 10B, 10C and 10D) when a region of

interest of canopy was extracted.

During the afternoon, for both dates, significant correlations were found between both

thermal indices (IG and CWSI) derived from the temperature of several sun exposed

leaves and both physiological parameters (gs and Ψstem) (Fig. 9 and 10 respectively). It

was not clear that either method of temperature extraction from the images was

preferable to evaluate vine water status in the image analysis on 4 September during

the afternoon. However, the correlations were higher when average temperatures

were obtained from a ROI of canopy on 5 September.

The stress indices (IG and CWSI) obtained from zenithal canopy temperatures with

average temperatures of several sun exposed leaves presented significant correlations

with stomatal conductance and with water potential on 4 September (Fig. 9). Neither

extraction method appeared preferable for detection of vine water status using the

stress indices.

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Fig. 10 Correlations between stomatal conductance, gs (A, C, E, G) or stem water potential, Ψstem (B, D, F, H) measured, IG (A, B, E, F) and CWSI (C, D, G, H) on 5 September 2010 (n=17-18). Canopy temperatures represent the average temperature of a region of interest (ROI) of the canopy of 213 × 160 pixels, approximately (A, B, C, D) and of several sun exposed leaves (E, F, G, H). In each graph, R

2 values from

top to bottom respectively correspond to lateral canopy temperature in the afternoon ( open circles) and lateral canopy temperature in the morning ( filled circles).

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Frequency distributions of temperatures

Selecting a ROI of canopy allowed analyzing the frequency distribution of

temperatures in the selected area. In all irrigation regimes, lateral canopy

temperatures in the morning were cooler than lateral canopy temperatures in the

afternoon and zenithal canopy temperatures. Highest temperatures were presented in

lateral canopies in the afternoon. As expected, there was a variation between

irrigation regimes, with rain-fed (RF) showing the highest temperatures while full

irrigation (FI) showing the lowest temperatures. These differences of temperature

between irrigation regimes were not clearly observed in lateral canopies in the

morning, which showed similar mean and variability (Fig. 11).

Frequency distributions of pixel temperatures within canopy showed different patterns

in different irrigation regimes. Generally, a higher range of distribution of pixel

temperatures within canopies was found for lateral canopy temperatures in the

morning (CV=9.49-11.58%), indicating more variation. For all irrigation regimes, the

lowest ranges of distribution of pixels temperature within canopies were presented in

zenithal canopy temperatures. Negative kurtosis was found for all irrigation regimes of

the lateral part of the canopy in the morning and in the afternoon, with the exception

of non irrigated (RF) regime in the afternoon i.e. the distribution was flattened

(platykurtic) in comparison with a normal distribution; all irrigation regimes in the

zenithal canopy and in the non irrigated (RF) regime for the lateral canopy in the

afternoon showed above 0 values of kurtosis i.e. the distribution is leptokurtic (higher

peak in comparison with normal distribution) (Fig. 11). The skewness values for all

irrigation regimes showed slight asymmetry, with higher values in the zenithal part of

the canopy.

When the distribution of pixel temperatures was compared between irrigation

regimes, it was observed that full irrigation (FI) presented smaller variation of thermal

distribution than other irrigation regimes.

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Fig. 11 Frequency of pixel temperatures obtained within a region of interest (ROI) of the canopy in five vines in each water regime (rain-fed, non-irrigated -RF-, standard irrigation -SI-, moderate irrigated -MI- and fully irrigated -FI-) for lateral canopy in the morning (lateral AM), lateral canopy in the afternoon (lateral PM) and zenithal canopy (zenithal) on 4 September.

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5. DISCUSSION

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Extraction of temperatures

The main problem generated in the extraction of thermal data from images is the need

to separate non-leaf material and background soil from leaf material. Different

approaches to the elimination of background temperatures have been explored.

Giuliani and Flore (2000) used a custom-written program based on thermal histograms

to process the digital images and exclude background temperatures. Jones et al. (2002)

discussed the use of reference surfaces (dry and wet) as limits to remove non-leaf

material from histograms. Other approaches required the analysis of individual pixels

in each image, such us the addition of the mean temperature of the reference image

to each pixel in the analyzed image, the transformation of each pixel in 8-bit gray-scale

image from an equation, the separation of canopy pixel from soil pixel by thresholds

related with air temperature (Alchanatis et al. 2010; Leinonen and Jones 2004; Meron

et al. 2010).

In our case, two approaches were explored, the use of average temperatures of

several sun exposed leaves and average temperatures of a ROI of the canopy. The use

of average temperatures of several sun exposed leaves involved checking the visible

image corresponding to each thermal image in order to select different leaves

manually.

Generally, analysis of the thermal data obtained on two measurement dates on

different parts (lateral and zenithal) of the canopy suggested that stronger correlations

with physiological data were presented when thermal data were obtained from a ROI

of the canopy. Average temperatures of a ROI were lower than average temperatures

of several leaves, supporting the idea that selection of a ROI of the canopy might

contain shaded leaves that decrease the average temperature of the area. The higher

correlations with stomatal conductance/water potential for a ROI of the canopy than

several sun exposed leaves might be explained by the sensitivity of canopy

temperature to stomatal conductance for sunlit canopy. There was less variability of

temperatures between shaded leaves than between sun-exposed leaves (Jones et al.

2002). However, Leinonen and Jones (2004) in a later study showed that the

temperature variance of the sunlit leaves was lower than shaded leaves. These results

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were obtained from a method that requires the manipulation of individual pixels,

allowing the calculation of temperature distribution of sun exposed leaves and shaded

leaves separately. This could explain the contradictory results obtained by Jones et al.

(2002), where temperature distribution were extracted manually from large areas of

the canopy.

The use of a ROI of the canopy to extract thermal data might present limitations, as

the stomata tend to be more closed in shaded leaves, hence smaller ranges of

stomatal conductances and temperature can be expected (Jones et al. 2002), but also

might present advantages for automated image processing (Jimenez-Bello et al. 2011).

Also, ROI analysis appeared to be a more objective method than to manually select

several sun exposed leaves. Furthermore, the ROI method can provide the frequency

distribution of temperatures of this selected ROI.

Time of imaging

During the morning, the relationships between thermal data obtained and both

physiological parameters were not significant on 4 September. However, they were

highly significant on 5 September. These contradictory results indicate that morning

measurement might not be accurate to detect vineyard water status. This might be

caused by great changes in the climatic conditions when thermal images were taken in

the morning hours (data not shown). When thermal images were obtained in the

afternoon hours, climate conditions were more stable. On the two dates (4 and 5

September) high correlations were found between thermal data in the afternoon and

stomatal conductance and stem water potential. These results demonstrate that time

of imaging affects the utility of thermal imaging for evaluation of water stress in the

field. In this study, afternoon imaging was more reliable to assess vineyard water

status.

Stronger correlations with physiological data were always found with thermal data

obtained from lateral canopies in the afternoon, compared to lateral canopies in the

morning or zenithal canopies. Furthermore, higher temperatures were found for the

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lateral canopies in the afternoon. This may be because in the zenithal part of the

canopy, most leaves were not facing the sun at the time of measurement, whilst leaf

angle in the lateral canopy was directed towards the sun, resulting in higher leaf

temperatures. Fuchs (1990) pointed out that water stress is better monitored if

thermal images are taken in the same direction as the sun and an angle similar to the

solar zenith angle. In order to decrease the effect of individual leaf angle in the canopy

temperature, average temperatures of several leaves were taken. Average

temperatures of several leaves have previously been observed to be more useful to

note the effects caused by different water regimes (Grant et al. 2007).

When the correlations between physiological parameters and average temperatures of

lateral canopy in the afternoon and zenithal canopy were compared, zenithal

thermography appeared to be as effective as lateral thermography in the detection of

water stress. This demonstrates that aerial thermal imaging could be a feasible tool to

assess vineyard water status.

Temperature distribution

The distribution of thermal data differed between different times of thermal imaging

and between irrigation regimes. Temperature distribution of ROI of the canopy might

be a good indicator of water stress. Smaller variation of thermal distribution within in

canopies of fully irrigated vines (FI) was found compared to canopies of stressed vines.

This findings support the idea of Fuchs (1990) that temperature variation increased as

stomata close. Hence, temperature variation was higher in a stressed plant than in a

non-stressed plant. Similarly, Clawson and Blad (1982) found that the variation of

thermal distribution is less in non-stressed corn plants compared to stressed plants.

On the other hand, Grant et al. (2007) observed that there were not greater variation

of grapevine leaves’ temperature within stressed vines as compared to non-stressed

vines. These contradictory results with respect to Fuchs´ idea could be explained by

the non-random distribution of leaf angles within grapevine canopies. Where stomata

are open, stomatal conductance is the predominant determinant of leaf temperature,

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but when stomata are closed, leaf angle has the biggest impact on the temperature of

individual leaves in a canopy: hence as stomata close, variation in leaf angle has an

increasingly important impact on variation in temperature within a canopy (Fuch

1990). The present results, however, particularly for lateral canopies in the afternoon,

suggest that even in grapevine canopies there can be sufficient variation in leaf angle

to result in increased variation in temperature distribution within a canopy when

stomatal conductance is low.

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6. CONCLUSIONS

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The main conclusions from this work are:

a) Two different methods of extraction of temperature from the images

were suitable for detection of vine water status: averaging the

temperature of several individually selected sun-exposed leaves or by

extracting the average temperature of a region of canopy. However, the

use of the average temperature of a region of canopy presents great

advantages as image processing could be automated, and it allows the

frequency distribution of canopy temperature to be obtained.

Additionally, extracting the average temperature of a region of canopy

is less subjective than averaging the temperature of several individually

selected sun-exposed leaves.

b) Strong correlations between canopy temperatures (or thermal indices)

and stomatal conductance and stem water potential were observed.

These results indicate that thermal imaging can be used as a non-

invasive technique to determine grapevine water status under field

conditions and therefore it could be applied for irrigation scheduling.

The most favourable time to acquire thermal images in this study was

during the afternoon.

c) Zenithal temperatures were similarly indicative of vine water status

compared to lateral imaging. These results suggest that aerial imaging

may be suitable for monitoring water status in grapevines.

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