Early detection of oil-induced stress incrops using spectral and thermalresponses

Ebele Josephine EmenginiGeorge Alan BlackburnJulian Charles Theobald

Early detection of oil-induced stress in crops usingspectral and thermal responses

Ebele Josephine Emengini,a George Alan Blackburn,b andJulian Charles Theobaldc

aNnamdi Azikiwe University, Department of Surveying and Geoinformatics, Faculty ofEnvironmental Sciences, P.M.B. 5025, Awka, Anambra State, Nigeria

scholaphine@yahoo.combLancaster University, Lancaster Environment Centre, Lancaster. LA1 4YQ, United KingdomcMarlborough Winery, Pernod Ricard New Zealand, Blenheim, P.O. Box 331, New Zealand

Abstract. Oil pollution is a major source of environmental degradation, and requires accuratemonitoring and timely detection for an effective control of its occurrence. This paper examinesthe potential of a remote sensing approach using the spectral and thermal responses of crops forthe early detection of stress caused by oil pollution. In a glasshouse, pot-grown maize was treatedwith oil at sublethal and lethal applications. Thereafter, leaf thermal, spectral and physiologicalmeasurements were taken every two to three days to monitor the development of stressresponses. Our results indicate that absolute leaf temperature was a poor indicator of developingstress. However, a derived thermal index (IG) responded consistently in the early stages ofphysiological damage. Various spectral reflectance features were highly sensitive to oil-inducedstress. A narrow-band index using wavelengths in the near-infrared and red-edge region,ðR755 − R716Þ∕ðR755 þ R716Þ, was optimal for previsual detection of oil-induced stress. Thisindex had a strong linear relationship with photosynthetic rate. This indicates that by detectingvegetation stress, thermal and hyperspectral remote sensing has considerable potential for thetimely detection of oil pollution in the environment. © 2013 Society of Photo-Optical InstrumentationEngineers (SPIE). [DOI: 10.1117/1.JRS.7.073596]

Keywords: remote sensing; spectral reflectance; thermography; plant; crop; oil pollution.

Paper 12205 received Jul. 10, 2012; revised manuscript received Dec. 12, 2012; accepted forpublication Dec. 19, 2012; published online Jan. 17, 2013.

1 Introduction

Contamination of soils with petroleum products is becoming an ever-increasing problem, espe-cially in the light of several failures of pipelines and wells reported recently.1 This is a particularproblem in developing countries such as Nigeria, where oil pollution regularly affects subsistencecrops and natural vegetation. For safety and security reasons, pipelines and facilities are keptconstantly under surveillance using foot patrols by appointed officials and by intermittent manualobservations from aircraft. However, the effectiveness of such approaches is often limited. Oilleaks can develop into massive spills, polluting soils for decades and leading to fire outbreaks thatcan have severe and long-lasting environmental impacts if not detected and stopped early.

Previous investigations have found that stress caused by factors such as drought, herbicideapplication, and volatile hydrocarbon and heavy metal pollution cause changes to the reflectancespectra of leaves and canopies,2–5 and these can be detected before visual symptoms are observed.6

Indeed, numerous studies have found a significant increase in visible reflectance and decreases innear-infrared (NIR) reflectance in response to various stresses.3,5–14 Spectral parameters such asreflectance in individual narrow wavebands, characteristics of the red-edge and narrow-band ratioindices have been employed as a means of identifying stress in plants.3,15–18 However, there isa lack of evidence to indicate whether there are consistent and proportionate changes in leafreflectance in response to physiological stress induced by oil pollution.

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When plants are subjected to deficits of soil water, they act to control water loss by closingleaf stomata, therefore changes in the rate of transpiration by plants can be exploited as an indi-cator of developing water stress.19 If transpiration is restricted due to stomatal closure, latent heatloss by evaporation from the leaf surfaces decreases resulting in an increase in leaf temperature.20

As a consequence of this process, recent applications of thermal imaging techniques have shownthat plant water stress can be detected through an increase in leaf and canopy temperatures.21–23

Using such techniques, Olga et al. were able to distinguish between irrigated and nonirrigatedgrapevine canopies, and even between different deficit irrigation treatments.24 It is known that oilcontaminated soil can indirectly induce water stress in plants. De Jong observed that oil mark-edly decreased water uptake by wheat from contaminated soils,25 while Pezeshki and Delaunefound that oil pollution decreased plant transpiration.26 In studying the effects of soil contami-nation with diesel oil on yellow lupine, Wyszkowski et al. found that as oil penetrates soil itblocks air spaces and thereby decreases the fluxes of air and water, leading to a decrease incrop yield.1 This presumably is due to anoxia, decreased nutrient and water uptake, or a combi-nation of all three. Since oil contaminated soil can induce water stress in plants, which in turnincreases leaf temperatures, thermal remote sensing of plants is potentially of value as an indi-cator of oil pollution.

There is potential for the early detection of oil-induced stress in crops by using remotely-sensed spectral and thermal parameters. Thus, this paper analyses the physiological, spectral andthermal properties and responses of maize (Zea mays L.) as oil-induced stress develops. Maizewas chosen as a model species, since it is widely grown throughout the world (850 million tonnesin 2010) and demand, particularly in developing countries, is set to double and surpass that ofwheat and rice by 2020.27

The sensitivities of a range of spectral and thermal parameters were evaluated based on tim-ing and consistency of response in relation to the occurrence of visible stress symptoms. Therelationships between spectral and thermal parameters and oil-induced changes in photosynthe-sis, transpiration, and stomatal conductance were also examined. Hence, the objectives of thestudy were to first determine the efficacy of spectral and thermal properties of maize as indicatorsof oil pollution, and second, to identify an optimal remotely-sensed index for the early detectionof oil-induced stress in maize at sublethal and lethal applications.

2 Materials and Methods

2.1 Plant Material

The experiment was conducted in a glasshouse (5 by 3 m) at the Lancaster Environment Centre,Lancaster University, United Kingdom under seminatural conditions at day and night temper-atures of 26°C (�2°C) and 15°C (�1°C), respectively. A 12 h supplementary photoperiod(06:00 h to 18:00 h) provided by Osram Plantastar 600 W sodium lamps delivered a photosyn-thetic photon flux density (PPFD) of 400 μmolm−2 s−1 at bench height. Seeds of maize(Zea mays L. cv Earligold) were pregerminated for three days on damp tissue paper in darknessand then two seedlings were sown per 1.6 l pot containing a loam-based compost (John InnesNo.2, J Arthur Bowers, Lincoln, United Kingdom). Pots were placed on capillary matting andwatered daily and, after two weeks, thinned to one plant per pot. Throughout the experiment,liquid fertilizer (Tomorite, Levington, United Kingdom) was applied (at a rate of 40 ml diluted in9 l of water) at weekly intervals to avoid nutrient deficiency.

2.2 Plant Treatments

Thirty days after germination, plants were treated with 15 W∕40 diesel engine oil (Unipart,Crawley, United Kingdom). This type of oil was used due its reduced flammability and evapo-rability, which was important in the context of the enclosed glasshouse and the presence of highpower lighting providing potential ignition triggers. The oil was applied to the surface of thecompost as a percentage volume of the water holding capacity (WHC) of the pot and soil (fieldcapacity minus oven dry), previously determined as 0.63 g H2O g compost at a density of

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0.8 g cm−3. Application rates were 0%, 10%, 30%, and 50% of WHC, being equivalent to 0 and∼48, 144, and 241 g oil∕kg soil, respectively and hereafter referred to as control, low, mediumand high treatments. These treatments were chosen to ensure that plants were subjected to bothsublethal and lethal doses of oil pollution, these levels of treatment having previously beendefined in preliminary dosing experiments.28 There were eight replicate plants per treatment.

2.3 Physiological, Thermal and Spectral Measurements

The sixth just-fully-emerged leaf on each plant was chosen for all measurements, which com-menced on day zero immediately prior to the application of oil and then every two to three daysthereafter. Rates of photosynthesis, transpiration, and stomatal conductance were determinedusing a portable infrared gas analyser (CIRAS-2, PP Systems, Hitchin, United Kingdom),with leaf cuvette conditions set to track ambient glasshouse temperature, humidity and CO2

concentration (38.5 Pa), with a PPFD of 600 μmolm−2 s−1, and a leaf equilibration time ofthree minutes within the cuvette prior to recording data. At the same time plants were scoredfor any visual signs of stress.

Thermographs for individual leaves were acquired in the glasshouse using an SC2000 ther-mal imager (FLIR Systems, West Malling, United Kingdom), operating in a waveband from 7.5to 13 μm with a thermal sensitivity of 0.07°C at 30°C. The field of view (FOV) was 24-deg. by18-deg. at the minimum focal distance of 0.3 m, with the spatial resolution 1.3 mrad, and with anemissivity of 0.95. Measurements were made following the procedures of Grant et al.,21 and eachcaptured frame included wet (sprayed with water) and dry (coated in petroleum jelly) referenceleaf surfaces alongside the target leaf of interest. The temperature of these references (Tdry andTwet) were used with the leaf of interest (T leaf) to calculate the thermal index (IG), where IG ¼ðTdry − T leafÞ∕ðT leaf − TwetÞ and under any given environmental conditions, is theoretically pro-portional to stomatal conductance.22

Leaf spectral reflectance data were collected in a dark room directly opposite the glasshouseand immediately after physiological and thermal measurements, using a GER 1500Spectroradiometer (Geophysical & Environmental Research Corp., Millbrook, New York). Thisinstrument covers the spectral range 350 to 1050 nm using 512 bands with a nominal width of1.5 nm. Leaves were gently clipped and held against a flat low-reflectance surface in order tominimize the effects of background on the sample spectrum. The sensor was mounted in a fixedposition, at nadir, 12 cm above each leaf blade to be measured. An 8-deg. fore-optic was usedwhich covered an instantaneous FOV approximately 7 cm diameter centred upon the midrib ofthe leaf. To fully illuminate the target, a 500 W halogen lamp was mounted in a fixed position, ata zenith angle of 45-deg. and at a distance of 70 cm from the leaf. Ten spectral measurementswere taken per leaf, with the GER FOV covering different areas along the length of the leaf eachtime. Subsequently, a measurement of the irradiance incident upon the leaf was obtained bytaking a reference spectrum of a white Spectralon panel (Labsphere, North Sutton, NewHampshire) placed in the same position as the leaf.

2.4 Data Analysis

To account for daily glasshouse variability in ambient temperature and humidity at the time ofmeasurement, results for photosynthesis, transpiration, and stomatal conductance are expressedas a percentage of the control on each sampling occasion. The software package ThermaCAMResearcher (FLIR Systems, West Malling, United Kingdom) was used to extract data from ther-mographs, by manually selecting the target leaf and wet and dry reference areas of interest fromeach frame. The average leaf temperatures were extracted for each sample and IG calculated.

Each GER leaf spectrum was divided by the corresponding reference spectrum in order tocalculate a percentage reflectance spectrum, and a correction for the reflectance properties of theSpectralon panel was then applied. The spectral reflectance data were imported into MicrosoftExcel for further processing. A range of different spectral parameters were extracted from theleaf reflectance spectra and used for subsequent analysis. These included individual narrowwavebands and band ratios selected to systematically incorporate the major areas of variabilityacross the wavelength range and to incorporate wavebands with a high variation in reflectance

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between oil-treated and control plants. In addition, several band ratios found to be valuable forplant stress detection in previous studies were also investigated. From the large number of wave-bands and ratios tested, the ones included in Table 1 were selected for report in this paper (forconciseness) as they incorporate and demonstrate the range of levels of response to oil treatment.

The red-edge position (REP) was determined using the linear extrapolation method of Choand Skidmore,29 which recognizes that double peaks can occur in the first derivative of leafreflectance spectra in the region of the red-edge, and which may have physiological significance.In addition, the wavelength positions of the first and second peaks in the first derivative wereextracted and the spectral distance between these peaks was calculated. Prior to calculatingderivatives, reflectance spectra were smoothed using a three-band window moving average,to reduce the effects of noise (which is amplified in derivatives) and at the same time minimizeloss of fine spectral detail.

Sensitivity analysis was performed in order to ascertain which of the remote stress indicatorswas optimal for early detection, prediction and quantification of oil-induced stress. The bestindices are those that perform consistently well in diverse situations,30 thus the criteria usedfor sensitivity analysis were the statistical significance of a change in the thermal or spectralmeasure, the consistency of response and the timing of the response at sublethal and lethaldoses. Timing of response was considered to be particularly important in order to determinewhether oil-induced stress could be detected spectrally and/or thermally before symptomsbecame apparent to an unaided eye. The hypothesis tested using analysis of variance(ANOVA) was that there is no significant effect of refined oil pollution on plant physiological,spectral and thermal properties. Post hoc test analyses using Tukey HSD were performed on theANOVA to determine significant treatment differences by a mean square multiple comparisonprocedure. This helps to ascertain the sensitivity of an indicator to lethal and sublethal levels ofpollution. All significant differences were at the 0.05 level of confidence. Correlation analysiswas conducted to determine relationships between remotely-sensed stress indicators and physio-logical parameters.

3 Results

3.1 Photosynthesis, Transpiration, and Stomatal Conductance

Treatment with oil significantly decreased rates of photosynthesis, transpiration, and stomatalconductance of maize in a dose-dependent manner [see Fig. 1(a) through 1(c)]. Net photosyn-thesis was not affected at the low dose level until six days after treatment (20% decrease) whilethe medium and high levels showed a response after two days (38% and 70% decreases, respec-tively). The rate of transpiration for the low dose level was briefly stimulated at two and fourdays, but then gradually declined as stress progressed. In contrast, at day two, transpiration forthe medium and high dose plants had already decreased by 38% and 40%, respectively. Stomatalconductance followed a similar dose-dependant pattern of response, decreasing by 38% and

Table 1 Selected spectral parameters tested for sensitivity to oil-induced stress in maize.

Individual narrow wavebands (nm) Ratios of narrow wavebands (nm) Red-edge features

450, 550, 650 530∕440, 685∕440, 740∕440 Red-edge position (REP)

705, 706, 708 685∕530, 740∕530 First of the double peaks (FDP)

710–712, 714, 716, 717, 750,850, 950

760∕695, 740∕685 Second of the double peaks (SDP)

750∕700, 715∕705, 755∕716 Distance between FDP & SDP

ð920 − 655Þ∕ð920þ 655Þ

ð755 − 716Þ∕ð755þ 716Þ

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Fig. 1 Effects at low, medium and high doses of oil pollution on rates of (a) net photosynthesis,(b) transpiration, and (c) stomatal conductance in maize over the course of the experiment.Treatments as denoted by the key. Error bars ¼ 1 × SE, n ¼ 8.

Fig. 2 (a) Mean reflectance spectra, 14 days after treatment. (b) Differences between meanreflectance spectra of treated and control leaves, 14 days after treatment (n ¼ 80).

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Table 2 Sensitivity of selected spectral parameters across varied dose levels of oil pollution overthe course of the experiment. Unshaded ¼ inconsistency or no significant difference; Shaded ¼significant difference between the oil-treated plants and controls. h, m, l ¼ time when visiblestress symptoms were observed in the high, medium and low treatments, respectively.

Spectral measure (nm) Treatments

Time (Days)

0 2 4 6h 9m 11 14l

ðR755 − R716Þ∕ðR755 þ R716Þ Low

Medium

High

R755∕R716 Low

Medium

High

R740∕R530 Low

Medium

High

R760∕R695 Low

Medium

High

REP Low

Medium

High

R750∕R700 Low

Medium

High

R715∕R705 Low

Medium

High

R740∕R685 Low

Medium

High

R705 Low

Medium

High

R685∕R440 Low

Medium

High

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58%, respectively in medium and high dose plants at day two, and by 21% in low dose plantsat day 11.

3.2 Visual Observations

Slight chlorosis was visually observed on some of the leaves of the high dose plants after six daysof treatment. By day nine, the medium and high dose plants showed symptoms of severe stress,with chlorosis on both leaves and stems, thinner canopies and a decrease in growth. By day 14,low dose plants were exhibiting moderate leaf chlorosis, while medium and high dose plantswere severely wilted and dying. Control plants exhibited no visual symptoms of stress.

3.3 Spectral Reflectance

In response to oil pollution, there was a dose-dependant increase in leaf reflectance in the visibleregion and a dose-dependant decrease in the NIR, as indicated by leaf spectra after 14 days oftreatment [Fig. 2(a)]. Differences between the mean spectral reflectance of controls and treatedleaves were highest in the red and far-red region of the spectrum with the greatest difference at

Table 2 (Continued).

Spectral measure (nm) Treatments

Time (Days)

0 2 4 6h 9m 11 14l

R650 Low

Medium

High

ðR920 − R655Þ∕ðR920 þ R655Þ Low

Medium

High

R685∕R530 Low

Medium

High

R740∕R440 Low

Medium

High

R550 Low

Medium

High

R530∕R440 Low

Medium

High

R450 Low

Medium

High

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approximately 705 nm [Fig. 2(b)]. The green and NIR regions showed moderate responses whilethe blue region was invariant.

Table 2 demonstrates that there was considerable variation in the sensitivity of different spec-tral parameters, with the shaded areas representing the period when there was a significant differ-ence between oil-treated and control plants. Those parameters that were not sensitive by the ninthday after treatment for any dose level are not presented.

Importantly, some spectral parameters showed significant differences between the oil-treatedplants and controls at all dose levels, before stress symptoms could be detected visually. Whenthese parameters were compared based on the timing, consistency and magnitude of response,the normalized difference ratio ðR755 − R716Þ∕ðR755 þ R716Þ was found to be the most sensitiveindex. Furthermore, this ratio had a strong linear relationship with photosynthesis (Fig. 3).

Figure 4(a) demonstrates how the ratio ðR755 − R716Þ∕ðR755 þ R716Þ decreased as stressadvanced through the experiment and how the timing and magnitude of the response corre-sponded with dose level. Figure 4(b) shows that REP had a similar response to oil-induced stress

y = 53.618x - 4.3299R² = 0.92

-5

0

5

10

15

20

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

Pho

tosy

nthe

sis

(µm

ol/m

2 /s)

(R755-R716)/(R755+R716)

Fig. 3 Relationships between spectral narrow-band normalized difference ratioðR755 − R716Þ∕ðR755 þ R716Þ and photosynthesis (P < 0.01) (n.b. the data refer to net photosyn-thesis so negative values indicate that respiration exceeds photosynthesis). Error bars ¼ 1 × SE,n ¼ 8.

-10

10

30

50

70

90

110

0 2 4 6 8 10 12 14

(R75

5-R

716)

/(R75

5+R

716)

(% o

f co

ntro

l)

Time (days)

-40-35-30-25-20-15-10

-505

0 2 4 6 8 10 12 14

Red

-edg

e po

sitio

n (n

m)

(rel

ativ

e to

con

trol

)

Time (days)

(b)

(a)

Control

Low

Medium

High

20

40

60

80

100

120

0 2 4 6 8 10 12 14

I G(%

of

cont

rol)

Time (days)

(c)

Fig. 4 Change in leaf spectral and thermal properties of controls and oil-treated maize plants overthe course of the experiment. (a) The normalized difference ratio ðR755 − R716Þ∕ðR755 þ R716Þ.(b) The red-edge position (REP). (c) The thermal index (IG). Treatments as denoted by thekey. Error bars ¼ 1 × SE, n ¼ 8.

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to that of the ratio ðR755 − R716Þ∕ðR755 þ R716Þ, with shifts to shorter wavelengths according todose level. The REP had a slightly weaker performance than the ratio ðR755 − R716Þ∕ðR755 þ R716Þ, in that it failed to show a significant response by day two for the low doselevel (see Table 2), but it did display an equally rapid response to the medium and highdose treatments.

3.4 Thermal Responses

The average absolute leaf temperature of the treated plants fluctuated above and below the con-trol plants and showed no statistically significant response to oil pollution throughout the experi-ment. However, the IG was consistently lower for the treated plants than controls, apart fromduring the early stage of the experiment for the low dose level plants. Figure 4(c) demonstratesthat the timing and the magnitude of response of IG was dose-dependant, but there was a lack ofconsistency in the significance of the differences between controls and treatments through theexperiment. Furthermore, there was a linear relationship between IG and stomatal conductance(Fig. 5) for all treatments prior to any visual stress symptoms, but thereafter the relationshipbroke down.

4 Discussion

Many studies have shown that pollution-induced stress has a negative effect on the physiologicalfunctioning of plants.31,32 Such effects have been found in relation to oil pollution within soil33

but low levels of contamination may not inhibit plant growth.34 In this study, we have observedthis breadth of response, having seen rapid and substantial changes in physiological properties ofplants treated with high and medium doses of oil, but slower and smaller responses at a low dose.

In the present work variations in the onset of visible stress symptoms of pollution indicatethat plant damage by oil is a function of intensity and duration. Rosso et al.5 found similar tem-poral variations in the occurrence of visible stress symptoms in Salicornia virginica after apply-ing a range of dose levels of heavy metals and petroleum. Indeed, a range of studies have foundthat the first visual signs of stress can range from five to 30 days after inducement dependingupon the type and magnitude of applied stress and plant species.15,32,35–39 In our study, symptomsat all dose levels started mildly by affecting only a few leaves and gradually became severespreading throughout the canopy. This development is similar to that observed in oilseedrape plants affected by natural gas elevation in the soil and by other stresses.15

Significant changes in leaf spectral reflectance as a result of oil pollution were found mainlyin the red-edge region of the spectrum, between 650 and 720 nm. This is consistent with a studyby Carter10 who found that reflectance in the red-edge increased in response to a range of stressagents for a range of plant species, with the region 685 to 700 nm being particularly sensitive.Reflectance in this region is strongly controlled by foliar pigment concentrations which typically

y = 370.19x + 61.94R² = 0.58

0

20

40

60

80

100

120

140

160

-0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2

Stom

atal

con

duct

ance

(m

ol/m

2 /s)

IG

Fig. 5 Relationships between IG and stomatal conductance (P < 0.05) (for sample days beforevisual signs of stress were apparent). Error bars ¼ 1 × SE, n ¼ 8.

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decrease in response to physiological stress.6 In particular, relatively small variations in the con-centrations of the chlorophylls, which have absorption maxima in the red wavelengths, can sub-stantially influence reflectance along the wings of the absorption features in the red-edge.40

Consequently, in the present experiment, individual narrow wavebands in the red-edge weremore consistent in their sensitivity to oil pollution than those in other regions of the reflectancespectrum. By the same token, wavebands in the visible (and ratios of these bands), positionedaround the centres of pigment absorption maxima in the red (R650) and blue (R450) and eventhose between the two pigment absorption maxima in the green region (R550) only respondedsignificantly to higher dose levels of pollution causing substantial pigment reductions in the laterstages of the experiment. Hence, a ratio of red and green reflectance that was found by Smithet al.15 to be indicative of gas pollution and herbicide stress in plants was only sensitive tomedium and high oil dose levels at later stages of the present experiment.

The overall decrease in NIR reflectance resulting from oil pollution in the present study issimilar to the results of Pickerill and Malthus41 who found lower leaf NIR reflectance in wheatcrops growing in anaerobic soils over leaks from aqueducts. Changes in the cellular structure anda decrease in intercellular spaces in stressed leaves both produce less light scattering and lessreflectance in the NIR.5 This effect appears to operate in response to oil pollution in this experi-ment. Oil stress appears to have inhibited the cellular development and expansion of intercellularspaces of the treated plants leading to lower NIR reflectances, compared to the controls.Furthermore, since oil markedly reduces water uptake by plants,25 cellular turgor and thereforeleaf structure may have deteriorated due to the indirect effects of oil on the plant water relations.

A consistent and high sensitivity to oil-induced stress was shown by ratios of wavebands inthe regions R715 to 760 and R695 to 716. This concurs with the findings of Tarpley et al.,

30 who notedthat a combination of a red-edge waveband with a waveband of high reflectance in the NIRregion produced a sensitive spectral indicator of leaf stress, in that case in response to nitrogendeficiency. In the present study the normalized difference ratio ðR755 − R716Þ∕ðR755 þ R716Þ thatcombined the red-edge and NIR regions was highly sensitive to oil pollution in terms of time-liness and consistency. For the high and medium dose treated plants this ratio showed significantchange after just two days, whereas a further four and seven days, respectively elapsed beforestress symptoms were visually observed upon leaves. Likewise, this ratio showed significantchanges after four days for the low dose treated plants, while stress symptoms were not visuallyobserved for a further 10 days. A number of recent studies have demonstrated the effectivenessof such narrow-band ratios for the characterization of stress-related variations in the biochemicaland biophysical properties of particular crop types and plant species.42–45

A consistent and significant shift of the REP to shorter wavelengths in treated plants showedthat this was a reliable spectral parameter for early detection of oil-induced stress. The shift of theREP was strongly related to a decrease in photosynthesis and thus, chlorophyll contents but, asrecognized by Horler et al.,8 REP is responsive to leaf developmental stage and leaf water con-tent, both of which can be influenced by oil pollution. Indeed, our results concur with severalstudies that have demonstrated REP shifts to shorter wavelengths in leaves of plants exposed to arange of different stress factors (e.g., Smith et al.15 and Rock et al.16).

Regarding thermal responses of leaves to oil pollution, it was found that absolute leaf temper-atures fluctuated as stress progressed, irrespective of dose level and did not differ significantly orconsistently between treated and control plants. Similar results were found in an experimentalfield study of herbicide-induced stress in a mixed stand of five year old loblolly pine (Pinus taedaL.) and slash pine (Pinus elliottii Engelm), where there was no significant difference in absolutecanopy temperature between treated and control plots.6 The authors attributed this to coupling ofleaf temperature with air temperature, and equalization of temperature among treatments due towind and environmental moisture. Likewise, Grant et al.21 detected no significant differencesbetween absolute leaf temperature of grapevine either well watered or subjected to a water defi-cit. This was related to greater environmental variation inevitable in an experiment with rela-tively large plants across a glasshouse. Such environmental variation may well explain theinconsistency in responses of absolute leaf temperature observed in this study.

In contrast to absolute leaf temperature, the IG, which corrects for variations in local ambienttemperature, showed a consistent and dose-dependent response to oil pollution. Theoretically, itis expected that IG should be related to stomatal conductance.22 In the present experiment this

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was indeed the case, but only for leaves that were not displaying any visual symptoms of stress(i.e., nonchlorotic). For latter occasions where stress symptoms were visually observed, the pro-portionality of the relationship between IG and stomatal conductance broke down. This indicatesthat prior to visual symptoms appearing, leaves are capable of regulating their water and energybalances via stomatal control, but by the time leaves exhibit visual symptoms this capability hasbeen substantially restricted due to the direct and indirect effects of oil pollution. Hence, IG ispotentially a valuable early previsual indicator of oil pollution but is less reliable as an indicatorfor later stages of physiological damage.

The species of plant examined in the present study was maize, which is a rapidly growingcrop that uses C4 carbon fixation and is considerably more water-efficient than other C3 cropssuch as alfalfa and soybean and is capable of surviving under a range of different environmentalregimes. Due to differences in environmental tolerance the direct and indirect effects of oil pol-lution may vary between species. Thus, while the findings of this study provide a general indi-cation of the relative merits of different spectral measures and the differences between spectraland thermal responses to oil-induced stress, such responses may differ between crop species.Likewise, while diesel engine oil was used to treat the plants in this experiment, environmentalpollution may result from releases of crude oil and other refined oil products which are typicallystored and transported through pipelines. Due to their differences in toxicity and interactionswith soil water and other physical and chemical constituents, different oil types may inducedifferent physiological, spectral and thermal responses in plants. Hence, it is important that fur-ther work is undertaken to investigate the sensitivity and transferability of the remote sensingtechniques developed here across a range of plant species and oil types.

While the findings of this study are based on proximal sensing in a laboratory context, thisresearch does provide valuable evidence that operational remote sensing, using airborne andspaceborne sensors, has the potential to detect oil pollution via plant stress responses. Thepresent laboratory-based approach supports the evidence from field-based spectroscopy46

and airborne hyperspectral imagery47 of the capabilities of remote sensing in this contextand further demonstrates the important contribution that remote sensing can make in oilspill detection and monitoring (see review by Fingas and Brown48). The present study indicatesthat remotely-sensed hyperspectral data, with sufficiently high spectral resolution particularly inthe red-edge region, and thermal data, with adequate radiometric sensitivity, have a role to play infuture monitoring efforts. The findings also demonstrate that remotely-sensed data with suffi-ciently high temporal resolution will enable the detection of oil pollution soon after a releaseevent and this is important for implementing effective control measures. Research is now neededin order to test the robustness of the spectral and thermal remote sensing techniques identified inthis research as we move from leaf to canopy and landscape scales, and towards operationalscenarios with variable atmospheric conditions and sensor capabilities.

5 Conclusions

Our results demonstrate that while absolute leaf temperature is unsuitable for detecting oil pollu-tion in crops, the IG, as a surrogate for stomatal conductance has some potential, although theresponse on its own is not unique to oil-induced stress. However, spectral reflectance has the great-est capability in this regard. In terms of timeliness and consistency, the application of normalized-difference spectral indices that combine a waveband in the red-edge with one in the NIR regioncould enhance the early detection of oil pollution via a plant stress response. In particular, a strongpositive linear relationship between the ratio ðR755 − R716Þ∕ðR755 þ R716Þ and photosynthetic ratesuggests that this can be a sensitive indicator irrespective of pollution intensity, but high spectralresolution input data is needed to maximize the sensitivity of this index. Further work is requiredto examine the potential of combining spectral parameters and thermal measures such as IG fordiscriminating oil-induced stress from other factors, such as soil water or nutrient deficiency.

Acknowledgments

We gratefully acknowledge the Petroleum Technology Development Fund (PTDF), Nigeria forfunding this research. We also wish to thank the Lancaster Environment Centre, Lancaster

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University, UK, for providing funds for the purchase of equipment and for access to glasshousespace. We are grateful to Professor Bill Davies (Lancaster Environment Centre) for use of thethermal imager and for allowing JCT time to support research in this area.

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Ebele Josephine Emengini obtained a BSc in surveying and photogram-metry from the Enugu State University of Science and Technology and anMSc from the Nnamdi Azikiwe University, Awka, both in Nigeria. She alsoreceived a PhD in remote sensing from Lancaster University, UK. She is alecturer in the Department of Surveying and Geoinformatics, NnamdiAzikiwe University, Awka. Her research interest focuses on applyingremote sensing and GIS techniques to solving various environmentalproblems faced by developing countries.

George Alan Blackburn received a BSc in geography from the Universityof Bristol and a PhD in remote sensing from the University ofSouthampton. He is a senior lecturer with the Lancaster EnvironmentCentre, Lancaster University. His research focuses on developing remotesensing and GIS techniques for environmental applications, particularly invegetation ecophysiology and ecology.

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