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Environmental and Experimental Botany 68 (2010) 165–174

Contents lists available at ScienceDirect

Environmental and Experimental Botany

journa l homepage: www.e lsev ier .com/ locate /envexpbot

trawberry plant fruiting efficiency and its correlation with solar irradiance,emperature and reflectance water index variation

ong Lia,b,∗, Tingxian Li c, Robert J. Gordond, Samuel K. Asiedua, Kelin Hub

Nova Scotia Agricultural College, Department of Plant and Animal Sciences, Truro, Nova Scotia, B2N 5E3, CanadaChina Agricultural University, Department of Soil and Water Sciences, Beijin 100094, ChinaMinistry of Sustainable Development, Environment and Parks of Quebec, Sustainable Development and Ecological Inheritance Services, Quebec City, Quebec, G1R 5V7, CanadaUniversity of Guelph, School of Environmental Sciences, Guelph, Ontario, N1G 2W1, Canada

r t i c l e i n f o

rticle history:eceived 7 July 2009eceived in revised form 4 November 2009ccepted 1 December 2009

eywords:ightlanting designtrawberry fruitopographic featuresater

a b s t r a c t

Uneven light distribution and low water holding capacity are two constraints limiting strawberry (Fra-garia × ananassa Duch.) production in coastal northern Atlantic areas. A study was conducted in acommercial strawberry production field characterized by rapid internal soil drainage and undulatingland features in Nova Scotia. The objectives were to examine the uneven distribution patterns of solarirradiance (IRR), temperature and soil water content (SWC) and quantify correlations of these physicalvariables with strawberry fruit yield, plant reflectance water index (WI) and leaf chlorophyll. Strawberryrow orientation was along the field aspect in the north–south (N–S) direction for maximizing plant sun-light exposure and spring rainfall drainage. The measurement design consisted of a nested grid withfive transects. Results showed that solar radiation incident upon the canopy was significantly higher(mean IRR 779–820 W m−2) in the shoulder and slope areas compared to the mean IRR of 709 W m−2

in downslope area (P < 0.001), where higher SWC and lower temperature stimulated strawberry fruitbearing. Significantly higher reflectance WI was related to low strawberry yield (R2 = 0.55, P < 0.05).Strawberry fruit yield was positively correlated to normalized difference vegetation index, ratio nitrogen

2

vegetative index and leaf chlorophyll (0.46 < R < 0.61, P < 0.05). Distribution patterns and correlationsbetween strawberry fruit yield and physical variables suggested that IRR and water stress occurring withthe influence of high topographic features resulted in reduced strawberry fruit bearing ability. It wassuggested that the N–S row orientation along the aspect would help sunlight capture but not water hold-ing for strawberry plant fruit bearing needs. A new planting design for alternative orientation of rows(NE–SW or W–E) and drip irrigation should be tested for light and water management in soils with naturalconstraints.

. Introduction

Strawberry (Fragaria × ananasa Duch.), a small fruit crop andhybrid of two highly variable octoploid species, has adapted to

xtremely different environmental conditions (Heide, 1977; Rieger,005). In North America strawberries are grown extensively inool areas (e.g. Nova Scotia) and also in semi-tropical regions (e.g.lorida). Full sunlight and available water are key components forroducing high quality strawberry fruit (El-farhan and Pritts, 1997;

atson et al., 2002; Rieger, 2005; Klamkowski and Treder, 2008).

s strawberry fruit bearing and maturity occur in a short time20–40 days after pollination) and also strawberries have shallowoot systems (the plants are growing via stolons), light and water

∗ Corresponding author. Tel.: +1 902 893 7859; fax: +1 902 897 9762.E-mail address: hli@nsac.ca (H. Li).

098-8472/$ – see front matter © 2009 Elsevier B.V. All rights reserved.oi:10.1016/j.envexpbot.2009.12.001

© 2009 Elsevier B.V. All rights reserved.

management are critical for achieving high yield and fruit qualityof strawberries.

In the humid and temperate coastal areas in Nova Scotia, agri-cultural fields typically include rolling to hilly landforms and soilsare highly permeable resulting in rapid internal drainage and pre-cipitation is also lost by runoff (Webb et al., 1991). Rapid internaldrainage can be defined as water removed rapidly through thesoil profile due to a high hydraulic conductivity (between 10 and100 �m s−1) and unless irrigated only a restricted variety of cropscan be grown with a low yield (Webb et al., 1991). Traditional cropsare hay, oats, barley and potatoes in this coast area. In recent years,with the adoption of irrigation technology in the region, produc-

ers have grown high-value horticultural crops such as strawberriesand raspberries. However, maintaining appropriate water status inthese soils is critical because of the cost for irrigation and also thepotential loss of fertilizers leaching with the water through the soilprofile.

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66 H. Li et al. / Environmental and Ex

Soil water is recognized as the greatest hazard affecting sys-ems productivity and sustainability (Blum, 1996; Griffiths andarry, 2002; Sperry et al., 2002; Li et al., 2001a, 2002, 2004,008). Reduced water availability induces numerous physio-

ogical and biochemical changes in plant organs (Hetheringtonnd Woodward, 2003). Drought and NaCl stress in strawberrylant can retard the development of its reproductive organs,

eading to fewer flowers and fruit (Blanke and Cooke, 2004;lamkowski and Treder, 2008; Keutgen and Pawelzik, 2009).

rrigation is often practiced following the onset of plant watertress, however, this is often too late to avoid a partial reduc-ion in yield (El-farhan and Pritts, 1997; Li et al., 2002). Plantesponses in canopy spectral reflectance, transmittance or absorp-ance are real-time eco physiological indicators of plant watertress (Jackson, 1982; Carter and Knapp, 2001). Crop yield differ-nce can be explained by spectral index such as relative nitrogenegetative index (RNVI), normalized difference vegetation indexNDVI) (Jackson, 1982; Li et al., 2001a,b). Reflectance water indexWI) is a spectral indicator for real-time management of plantater stress (Jackson, 1982; Penuelas et al., 1997; Claudio et al.,

006).Light, solar radiation and temperature distribution can vary sig-

ificantly under different topographic features such as elevation,spect and slope (Rorison et al., 1986; Florinsky et al., 1994; Li etl., 2001b). Temperature is one of the most important factors affect-ng strawberry plant nutrient uptake (Ganmore-Neumann andafkafi, 1985) and wheat photosynthesis and grain-filling (Shahnd Paulsen, 2003). High temperature (24–32 ◦C) reduces straw-erry flower formation and fruit quality (Heide, 1977; Klamkowskind Treder, 2008). Temperature is associated with strawberryower bud induction (Ito & Saito, 1962; Heide, 1977), runner,eristem-tip and leaf variegation (Watkins et al., 1990), dormancy

nduction (Robert et al., 1999), fruit flavors (Watson et al., 2002),nd membrane phospholipids (Wang and Lin, 2006).

Planting orientation of rows is useful for maximizing light inter-eption by plant canopies to achieve high yield and fruit qualityRieger, 2005). Light and water management for soils having rollingnd coarse-textured gravel characteristics that can lead to unevenistribution of light and water is a challenge for growers. Currently,o information is available for light and water management underhe influence of rolling landforms and rapid internal drainage.here was a need for understanding the relationships between solaradiation, temperature, soil water and strawberry fruit yields. Inddition, plant and soil functions are often encountered for under-ying environmental variables, which should be measured as aunction of space in systematic grid sampling scheme (Marriott etl., 1997; Cole et al., 2001; Li et al., 2002).

Several studies have addressed strawberry plant and supra-ptimal temperature (or photoperiod) problems only (Ito and Saito,962; Heide, 1977; Ganmore-Neumann and Kafkafi, 1985; Watkinst al., 1990; Robert et al., 1999; Watson et al., 2002; Wang andin, 2006), or strawberry plant water (or salinity) problems onlyBlanke and Cooke, 2004; Klamkowski and Treder, 2008; Keutgennd Pawelzik, 2009). We conducted a 2-year study in a strawberryeld in the coastal areas of Nova Scotia to quantify simultaneouslyhe roles of solar irradiance, temperature and soil water variationn strawberry fruit setting on lands with natural rolling charac-ers and drainage constraints. It was hypothesized that undulatingandforms and natural drainage constraints can create differencen solar radiation capture, temperature and soil water distributionatterns. This can then impact strawberry plant development and

ruit yield. The objectives of the study were to (i) examine the dis-ribution patterns of solar irradiance (IRR), temperatures and SWC,nd (ii) quantify strawberry plant fruiting efficiency and its cor-elations with these physical variables and plant reflectance WI,anopy spectral index and leaf chlorophyll across the landscape.

ental Botany 68 (2010) 165–174

The information would be useful for understanding light, temper-ature, water and plant relations for growing high-value fruit cropsin soils with natural constraints.

2. Materials and methods

2.1. Study site and strawberry planting description

The study was conducted in an irrigated, commercial strawberryproduction field (45◦40′01′′N, 63◦54′15′′W) near Glenholme in theCobequid Bay, Nova Scotia during 2006–2007. The site was 1.2-hain size with a 3-crop, 6-year rotation regime, which was 2-yeargrass, 3-year strawberry and 1-year corn. The soil was a gravelly,rapidly drained sandy loam, classified as Hebert (map unit He2)loam, Orthic Humo-Ferric Podzols (Webb et al., 1991).

The field, typical for the area, was characterized by an undu-lating land surface with a slope varying between 5 and 10% andan aspect in the north–south (N–S) direction. The field landformsconsisted of a 30-m long shoulder area, a 28-m slope and a 28-m downslope flat terrain along the aspect. The previous crop was2-year perennial ryegrass (Lolium perenne L.) to improve soil qual-ity including suppressing pests and disease fungi. In May 2005, thestrawberry cv ‘Annapolis’, a late June-early July bearing variety, wastransplanted in raised beds (1.2 m in dimension) for soil warming,rainfall evacuating and sunlight capture. The orientation of rowswas following the aspect in the N–S direction, an usual plantingpractice of orientation of rows for maximum plant sunlight expo-sure for fruit bearing and also for facilitating drainage when rainfallwas more frequent in the spring.

The strawberry plant spacing was 1.5 m between rows and0.50 m apart between plants in the row. After transplanting theplants were mulched with wheat straw to conserve soil water andcontrol weeds. The strawberry plants were fertilized based on soiltests performed in the spring and utilized regional recommenda-tions. Irrigation was done on a rainfall compensation basis usingsprinkler system with pipes installed 24 m apart across the field.The use of sprinkle irrigation was helpful for frost protection. At thecritical stage of transplant establishment, the irrigation rates were4 L m−2 per day because the newly set transplants were suscepti-ble to even mild water stress (El-farhan and Pritts, 1997). The totalirrigation water was on average 260 L m−2 per season, which wasin the range of irrigation recommendation for mulching strawberry(El-farhan and Pritts, 1997).

For better fruit bearing, strawberry plant runners were thinnedduring the first growing season. Flowering stems on the plants wereconsistently removed as they appeared throughout the season. Theflower thinning strengthened the mother plants and main runnerplants. Nutrients were applied based on soil test results and disease,insect and weed control was done according to the regional rec-ommendation. The plants were mulched for winter protection andirrigation at the rate of 5 L m−2 was done prior to mulch coveringto reduce risk of cold-temperature injury.

In 2006, the strawberry plants were allowed to attain a largesize at full vegetative stage then allowed flowers for fruit bearingfrom June through harvest in mid July. Irrigation was done at therate of 4 L m−2 per day (dry days) during the periods of flowering,initiation of berry set through the final enlargement of the fruit. Thestrawberry plants were cared for crop protection, fertilization andirrigation for fruit bearing for 2007. However, the plants were hitby an unexpected hail storm during the fruit bearing period (midJune 2007), resulting in some damages on fruit formation.

2.2. The experimental design and field measurements

The experimental design was a nested grid sampling scheme,which consisted of two transects (two strawberry rows), 7.5 m

H. Li et al. / Environmental and Experimental Botany 68 (2010) 165–174 167

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ig. 1. Spatial interpolated patterns of site elevation (A), solar irradiance (B), soileadings (E) and strawberry marketable fruit yield (F).

part, along the aspect (N–S) direction, and three other transectsthree strawberry rows), 24 m apart, in the west–east (W–E) direc-ion across the field. The two N–S transects were five rows apart,overing along the shoulder, slope and downslope areas where itresented the greatest variability in elevation following the aspect.he three W–E transects were parallel, with each transect in thehoulder, slope and downslope area, respectively. All measure-ents were taken in the 7.5 × 6 m grid in the N–S transects, and

4 × 12 m grid along the W–E transects. The grid area was 72 m longn the aspect (N–S) direction and 72 m in the W–E direction (Fig. 1).his nested grid design had an advantage of emphasis on exam-ning the spatial variability in the areas presenting the greatestariability, as shown in Marriott et al. (1997) and Cole et al. (2001).

The field measurements were initiated in 2006 because of thelant runner and flower thinning in the first year (2005). The mea-urement points were geo-referenced using a Garmin handheldPS system (Garmin International, Olathe, KS). There were a totalf 42 GPS points with 12 measurements in each N–S transect andmeasurements in each W–E transect.

Soil temperature, strawberry leaf and fruit temperatures wereeasured using an infrared thermal sensor (Spectrum Technolo-

ies, Plainfield, IL). The temperature measurements were taken atull vegetative stage, at flowering and at fruit bearing stage. At eachtage temperatures were measured two times in a 10-day interval.

content (C), strawberry plant reflectance water index (D), leaf chlorophyll SPAD

Temperature measurements were taken simultaneously on threefruits, leaves and soils at each measurement point. Fruits and leavesfor the measurements were selected at the same levels of plantheights each time.

Leaf chlorophyll content was measured on the same leaves asfor temperature measurements using a Minolta SPAD 502 meter(Markwell et al., 1995). Three chlorophyll measurements weretaken on separate leaves at each GPS point three times at full vege-tative stage, at flowering and at fruit bearing stage. Air temperaturedata were obtained from a nearby weather station in Glenholme,3 km away from the study site.

Plant canopy multispectral reflectance was detected at a wave-length between 462 and 1752 nm using a portable multispectralradiometer (MSRSYS5, CropScan, Rochester, MN), a rapid assess-ment taken directly on plant canopies across the field (Li et al.,2001a). The MSRSYS5 consisted of five up-sensors to detect incidentenergy and five down-sensors to detect outgoing energy. The plant-soil target surface was sensed at 2 m distance from the sensors(looking straight down) with a 31.1◦ field of view yielding a ground

of 1-m2 area. The reflectance measurements were taken at each ofthe GPS points within the grids. The spectral readings were taken at14:00 within a time of 15–30◦ solar zenith angle at full vegetativestage, at flowering and at fruit harvest. Sensor outputs consisted ofthe reflectance readings at the center wavelength of 485, 560, 660,

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30 and 1650 nm, respectively. The blue, green, red, near infraredNIR) and mid infrared (MIR) bands were across a wavelength widthetween 452–518 nm, 524–596 nm, 631–689 nm, 757–903 nm and553–1748 nm, respectively. As a result, the wavelength width wasimilarly narrow, comparable within the blue, green and red bands57–72 nm) and also within the NIR and MIR bands (146–195 nm).

Solar irradiance (IRR), the power of electromagnetic radiationncident upon the canopy surface per unit area, was detectedimultaneously with the plant reflectance measurements, usinghe MSRSYS5 radiometer up-facing sensor at the center 560 nmwavelength width 524–596 nm). This green band was the near-st band to the peak of the solar spectrum (480 nm). The up-sensorstimated the total hemispherical irradiance or received on 1-m2

anopy surface. This green band was a narrowband (72 nm) androvided estimations with uncertainty within ±5% of total solar

ncident radiation in clear sky conditions or in lightly cloudy con-itions, verified using solar pyranometer readings. It was to notelthough the blue band (485 nm) was closer to the peak of the solarpectrum than the green band, the blue sensor was not chose forhe solar irradiance measurements because the hemispherical blueight could drop more quickly than the green light when it waslightly cloudy (Jackson, 1982; Carter and Knapp, 2001; Claudio etl., 2006).

The soil water content was measured at the depth of 0–0.15 msing a TDR probe (Spectrum Technologies, Plainfield, IL). A com-osite soil sample with three soil cores was taken at the depthf 0–0.15 m. Soil samples were air-dried. Soil pH was measuredsing pH–H2O (m/v 1:1) ratio (Li et al., 2002). Soil water availabilityxpressed on a gravimetrical basis was also determined by dryingoil samples in the oven at a temperature of 110 ◦C (Li et al., 2004).

Strawberry fruit yield was hand harvested in an area of 1-mong on the rows at each GPS point in 2006. The fruit yields weressessed neither in the first year in 2005 (due to plant thinning) norn 2007 (because of the hail damage). The strawberry marketableield was obtained from marketable-size (≥2.5 cm) fruits with red,ree of defects for each GPS point. Damaged or diseased fruits wereiscarded. Elevation data taken using the Garmin unit were thenalibrated with the soil map unit elevation (Webb et al., 1991) tobtain the estimated elevation data for each sampling site.

.3. Plant, water and soil data analysis and mapping

Strawberry plant spectral reflectance readings were calibratedith a reflectance correction factor, and then converted to

eflectance percentage, a ratio from the down and up sensor outputn mV, as described in Li et al. (2001a). Soil reflectance was discrim-nated in the red band (center 660 nm), and plant reflectance wasiscriminated in the NIR band (center 830 nm). Plant water holdingtatus was estimated using the reflectance data in the water band,hich was the MIR band (center 1650 nm), as shown in Li et al.

2001b) and Claudio et al. (2006).The ratio vegetative index (RVI) was the ratio of NIR to red

eflectance (NIR/red). The NIR and green (G) reflectance (NIR/G)atio was defined as relative nitrogen vegetative index (RNVI). Theormalized difference vegetative index (NDVI), a spectral vege-ative index widely used in termination of plant N status, wasetermined by the ratio of differencing and combining reflectanceeasured in NIR and red bands as NDVI = (NIR − red)/(NIR + red), as

hown in Li et al. (2001a,b).Reflectance water index (WI) was estimated using the ratio of

he reflectance within the water band wavelength, center 1650 nm,

o the nearby reflectance wavelength where there was no waterbsorption, which was the NIR band 830 nm. The wavelength widthf this 1650-nm water band (width 1553–1748 nm) was very closeo the two most prominent water bands (1400 and 1900 nm). Waterdsorption was strong in the MIR bands and plant reflectance at

ental Botany 68 (2010) 165–174

these wavelengths has been shown to be correlated to water hold-ing in plants (Jackson, 1982; Penuelas et al., 1997; Li et al., 2001b;Claudio et al., 2006).

The data collected within the measurement grid were groupedby landform for analysis of variance and comparison of meansbetween the shoulder, slope and downslope landform groups.Descriptive statistics and correlation of data were done using PROCUNIVARIATE and PROC CORR procedures (SAS Institute, 1990). Theanalysis of variance between the landform groups was done usingGeneral Linear Models (GLM) procedure. The Honestly SignificantDifference (HSD) was used for comparison of means between thelandform groups (SAS Institute, 1990). Variance homogeneity ofdatasets was verified using the Bartlett test, and normality andresidual distribution of data sets were confirmed using PROC UNI-VARIATE (SAS Institute, 1990).

All variables were mapped with Inverse Distance Weighting(IDW) interpolation using ArcMap 9.1 (Environmental SystemsResearch Institute Inc., Redlands, CA).

3. Results

3.1. Distribution patterns of solar irradiance, soil water andstrawberry water index

The descriptive statistics showed that physical properties (siteelevation, IRR and SWC), soil pH, and strawberry plant physio-logical variables (reflectance WI, leaf chlorophyll SPAD readingsand NDVI) were highly variable (Table 1). The field topographyfeatured a linear decline from the shoulder, slope to downslope ter-rain (Table 1) and the interpolated topographic patterns showedthe aspect direction and the landform zones (Fig. 1A). The siteelevation had a range of 6.3 m with a mean of 2 m differencebetween the sequent landforms (n = 14 each landform group) andthe difference was significant (P < 0.001, Table 1). The IRR showedthe similar patterns as the elevation (Fig. 1B) with values beingthe highest (830–840 W m−2) in the shoulder area (Table 1), andthe difference in IRR was significantly between the three land-forms (P < 0.001, Table 1). The landform had a significant effect onirradiance (F = 118.68, P < 0.001, df = 2). The honestly significant dif-ference (HSD) values were 0.9 m for the elevation and 18 W m−2 forthe IRR variable (˛ = 0.05).

Soil water content (SWC) varied between 0.06 and 0.20 g g−1

and the difference in SWC was significant between the landforms(F = 4.13, P < 0.05, df = 2). The HSD value was 0.03 g g−1 for the SWCvariable (˛ = 0.05). The interpolated SWC patterns were spatiallydividing by landform (Fig. 1C). Soil pH (mean 6.62–6.84) was within the optimal range for strawberry growth. Slightly higher soil pHvalues were measured in the high radiation shoulder area but thedifference was not significant between the landforms (Table 1).

Strawberry plant water index was significantly higher (WI range0.64–0.80) in the slope area than in the shoulder and downslopeareas (Table 1). Significantly higher WI values were situated in theshoulder and slope areas (Fig. 1D). Higher WI indicated a higherplant water stress. As a result, the SPAD readings and the NDVIindex values were significantly lower in the slope areas than inthe shoulder and downslope areas. Overall, the datasets were notskewed (kurtosis < 3) except the soil pH in the slope (kurtosis = 3.76)and downslope areas (kurtosis = 4.68) and the sample varianceswere proportional to the means of variables (Table 1). The HSDvalues were 0.05 for the WI and 0.04 for the NDVI variable (˛ = 0.05).

The correlations between these physical variables were signif-

icant (IRR vs. elevation, r = 0.83, P < 0.01; SWC vs. IRR, r = −0.38,P < 0.05; and SWC vs. elevation, r = −0.36, P < 0.05). These correla-tion relationships revealed that low SWC was associated with highIRR and high elevation, indicating a water loss possibly from runoffin high elevation shoulder and slope areas.

H. Li et al. / Environmental and Experimental Botany 68 (2010) 165–174 169

Table 1Descriptive statistics and comparison of site elevation, solar irradiance (IRR), soil water content (SWC), soil pH, strawberry plant reflectance water index (WI), leaf chlorophyllconcentration (SPAD readings) and plant normalized difference vegetative index (NDVI) in different landform groups at the study site (n = 14 in each landform group).

Landform groups Elevationa IRRa SWCa pH WI SPAD NDVI

ShoulderMean 21.5 820 0.13 6.84 0.66 34.5 0.69Standard deviation 0.6 16.4 0.04 0.50 0.10 4.28 0.12Sample variance 0.3 270 0.11 0.25 0.21 18.4 0.17Kurtosis −0.5 −0.04 0.06 1.32 −1.35 −1.44 −0.86Skewness 0.3 −0.43 −0.43 −0.86 −0.04 −0.15 0.36Minimum 20.6 785 0.06 5.62 0.61 27.5 0.65Maximum 22.6 844 0.20 7.55 0.70 40.0 0.75

SlopeMean 19.5 779 0.12 6.71 0.71 30.8 0.64Standard deviation 1.2 25.6 0.06 0.41 0.13 2.43 0.16Sample variance 1.4 657.0 0.13 0.17 0.36 5.90 0.20Kurtosis −0.8 −1.4 −0.39 3.76 −0.15 1.08 −0.25Skewness −0.2 −0.1 −0.40 −1.63 0.07 1.32 −0.26Minimum 17.3 738 0.06 5.58 0.64 27.8 0.56Maximum 21.3 816 0.18 7.25 0.80 35.9 0.71

DownslopeMean 17.6 709 0.16 6.62 0.52 38.6 0.81Standard deviation 0.9 26.5 0.03 0.47 0.09 4.52 0.11Sample variance 0.7 701 0.09 0.22 0.17 20.4 0.14Kurtosis −0.3 0.1 −0.98 4.68 −1.19 −0.89 −1.44Skewness 0.4 0.5 −0.36 −1.72 −0.10 0.03 −0.11Minimum 16.3 669 0.09 5.30 0.48 32.0 0.75Maximum 19.3 765 0.20 7.20 0.57 46.2 0.87

Contrasts (F-value inter landform)b

Shoulder vs. slope and downslope 118.01** 205.68** 3.92* 0.95 ns 185.61** 20.32** 146**

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Slope vs. downslope 33.39** 31.67**

a Elevation in m, IRR in W m−2 and SWC in g g−1.b ns, * and **: not significant and significant at P < 0.05 and at P < 0.001, respective

.2. Trends of strawberry fruit, leaf and soil temperatures

Mean day-time air and surface soil temperatures ranged 9–22 ◦Curing the growing season. Maximum air temperatures variedetween 26 and 32.4 ◦C during the first two weeks of July each year.he surface soil temperatures measured in the warmest monthJuly) were significantly higher (35.6 ± 0.7 ◦C, range 35.6–37.4 ◦C)n the shoulder area than in the downslope areas (31.3 ± 0.8 ◦C,ange 31.2–33.0 ◦C). The landform had a significant effect on the

urface soil temperatures (F = 94.75, P < 0.001, df = 2). Soil tempera-ures were significantly different between the shoulder, slope andownslope (P < 0.001) and their HSD value (˛ = 0.05) was 0.98 ◦CFig. 2).

ig. 2. Comparison of surface soil temperatures in shoulder, slope and downslopereas. Each bar was the mean and standard deviation of 42 readings at each GPSoint, measured during early July 2006 and early 2007. The honestly significantifference (HSD, Tukey test) value was 0.98 ◦C (˛ = 0.05).

3.76* 1.44 ns 91.68** 25.84** 74**

The temperatures in July were important because it was thetime during the strawberry fruit bulking and maturity period.The temperatures measured on the strawberry fruits and leaveswere significantly different with the HSD value (˛ = 0.05) of 1.09 ◦C(Fig. 3). Across the nested grid, strawberry surface fruit temper-atures varied between 32.9 ± 1.3 ◦C, which was on average 5.8 ◦Chigher than leaf temperatures (27.1 ± 0.5 ◦C). The landform had asignificant effect on the fruit, leaf and soil temperatures (F = 135.97,P < 0.001, df = 2).

3.3. Trends of strawberry plant canopy reflectance and spectralindex

During strawberry fruit bulking and maturity period, the canopyreflectance was the highest at the NIR band (center 830 nm) follow-

Fig. 3. Comparison of temperatures in soil, strawberry fruits and leaves. Each barwas the mean and standard deviation of 42 readings at each GPS point, measuredduring July 2006. The honestly significant difference (HSD, Tukey test) value was1.09 ◦C (˛ = 0.05).

170 H. Li et al. / Environmental and Experimental Botany 68 (2010) 165–174

Table 2Descriptive statistics of strawberry plant reflectance in different bands, the ratio vegetative index (RVI), relative nitrogen vegetative index (RNVI), normalized differencevegetative index (NDVI) and reflectance water index (WI). n = 42.

485 nma 560 nma 660 nma 830 nma 1650 nma RVI RNVI NDVI WI

Mean 4.89 9.77 8.62 51.3 31.9 6.45 5.36 0.71 0.63Standard deviation 1.06 1.24 2.23 3.19 2.55 2.07 0.90 0.07 0.07Sample variance 1.13 1.53 4.97 10.2 6.50 4.28 0.82 0.01 0.01Kurtosis −0.16 −0.07 −0.28 0.01 −0.23 0.93 0.56 −0.45 −0.57Skewness 0.43 0.23 0.35 0.07 0.23 1.02 0.72 −0.20 0.17

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Minimum 2.67 6.83 4.10Maximum 8.05 13.62 15.13CV (%) 22 13 26

a Reflectance data are in %.

ng the water band (center 1650 nm) (Table 2), as plants absorbedtrongly visible energy and reflected NIR energy. The descriptivetatistics showed that all the reflectance data and spectral indexalues were not skewed (small kurtosis values 0.07–1.02, Table 2).he NIR reflectance was significantly lower in the slope area (mean6%) compared to in the downslope flat terrain (mean 54%). Thereen band reflectance was slightly higher than the red band. Asresult, the ratio vegetative index (RVI) was higher than the rela-

ive nitrogen vegetative index (RNVI). The NDVI and reflectance WIalues were compatible (Table 2). Similar to the NDVI distributionsattern (Table 1), the high RVI (12.1–13.9) and high RNVI values7.1–8.3) were measured in the downslope areas.

The landform had the significant effects on the blue (F = 61.9,< 0.001, df = 2), green (F = 44.0, P < 0.001, df = 2), red (F = 62.07,< 0.001, df = 2), NIR (F = 52.32, P < 0.001, df = 2) and the MIR

eflectance (F = 55.8, P < 0.001, df = 2). There were also significantandform effects on the spectral index RVI (F = 56.9, P < 0.001, df = 2)nd RNVI (F = 62.3, P < 0.001, df = 2). The HSD values were 1.4 forhe RVI and 0.52 for the RNVI variable (˛ = 0.05). All reflectanceariables and spectral index were significantly correlated (Table 3).he NIR reflectance was negatively correlated with the visible andIR reflectance but positively correlated with the RVI and RNVI

Table 3).

.4. Relationships of strawberry fruit sets, canopy reflectance,olar irradiance and soil water

The strawberry fruit sets were tenser in the downslope areashan in the shoulder area and fruit sets and fruit sizes were reducedn the slope. As a result, strawberry total fruit yield were signif-cantly different between the three position areas (Fig. 4A). Thetrawberry total fruit yield decreased from 1.88 ± 0.37 kg m−2 inhe shoulder area to 1.36 ± 0.22 kg m−2 in the slope. With lowolar irradiance and high water content, the strawberry total fruitield increased to 2.65 ± 0.53 kg m−2 in the downslope area, whicheant that water and irradiance were critical for this small fruit

earing. The fruit sizes were also larger in the higher SWC soil in theown-flat area, as the marketable fruit yields (fruit sizes ≥2.5 cm)ere 81.5%, 72.9% and 69.1% of the total yields in the downslope,

lope and shoulder areas, respectively.The strawberry marketable fruit yields were significantly higher

2.16 ± 0.66 kg m−2) in the downslope area (Fig. 4B). The landformad the significant effects on the strawberry total yield (F = 32.34,< 0.001, df = 2) and marketable yield (F = 21.52, P < 0.001, df = 2).he HSD values were 0.4 kg m−2 for the total yield and 0.47 kg m−2

or the marketable yield variable (˛ = 0.05, Fig. 4). Strawberry fruitield also had the highest variations among the measured variables,

ith a high coefficient of variation (CV = 46%).

The interpolated patterns for the strawberry marketable yieldsere comparable to the leaf chlorophyll (Fig. 1EF). The strawberry

ruit yield was positively correlated with NIR reflectance and spec-ral index RVI and RNVI and negatively correlated to visible and MIR

26.3 3.18 3.55 0.52 0.4839.9 13.9 8.32 0.87 0.80

8 32 17 10 12

reflectance data (Table 3). There were similarly significant correla-tions for the SPAD and the spectral variables (Table 3), as a result ofthe comparable patterns for the leaf chlorophyll and yield variables.

Strawberry marketable yield was negatively related to IRR(R2 = 0.32, P < 0.05, Fig. 5A), reflectance WI (R2 = 0.41, P < 0.05,Fig. 5B), and site elevation (R2 = 0.45, P < 0.05, Fig. 5C) but positivelycorrelated with SWC (R2 = 0.45, P < 0.05, Fig. 5D). In contrast, straw-berry marketable yield was positively related to the canopy spectralreflectance indexes and leaf chlorophyll including NDVI, RNVI, RVIand SPAD leaf chlorophyll readings (0.46 < R2 < 0.68, P < 0.05, Fig. 6).

The distribution patterns of strawberry leaf chlorophyll SPADreadings against the physical variables (solar irradiance, reflectancewater index, soil water content (SWC), and site elevation (SE)and the strawberry canopy spectral reflectance indexes (NDVI andRNVI) were similar to the strawberry yield patterns (Figs. 5 and 6).The correlations between these variables (n = 42) could bedescribed by the linearly regression equations as follows:

SPAD = 78.56SWC + 24.26, R2 = 0.40, P < 0.05

SPAD = − 1.7408SE + 59.84, R2 = 0.47, P < 0.05

NDVI = 0.0097SPAD + 0.3767, R2 = 0.38, P < 0.05

RNVI = 2.2215SPAD + 22.68, R2 = 0.35, P < 0.05

4. Discussion

4.1. Strawberry plant irradiance, temperature and water stress

Strawberry plants are perennial, growing in the field duringhot and cold seasons and strawberry is adapted to the environ-ment with temperature variations (Heide, 1977). Grown in theshallow, gravel soil, the variation in strawberry fruit yield andplant physiological variables (chlorophyll and reflectance measure-ments) revealed that in landscapes with topographic influences,solar irradiance, temperatures and SWC had significant effects onstrawberry fruiting ability, as shown their relationships with thestrawberry fruit yield (Figs. 5 and 6). It was reported that thecorrelations between solar irradiance, temperature and elevationwere positively significant (Rorison et al., 1986; Florinsky et al.,1994). The role of topography was attributed to its influence on thethermal and hydrologic processes influencing the strawberry plantvigor and its fruit bearing efficiency (yield).

Strawberry plant water stress (WI values > 0.6) occurred on theslope and shoulder areas, where there was high irradiance (Table 1)

and temperature (Fig. 2) and low SWC values (Table 1), resultingin significantly lower fruit yield (Fig. 4). The negative regressionrelationship between strawberry yield and solar irradiance (Fig. 5)further suggested that the influence of soil water in strawberrygrowth seemed to be complicated by solar irradiance and site ele-

H. Li et al. / Environmental and Experimental Botany 68 (2010) 165–174 171

Table 3Pearson correlation coefficients (r) of strawberry marketable fruit yield plant reflectance in different bands, the ratio vegetative index (RVI), relative nitrogen vegetativeindex (RNVI), normalized difference vegetative index (NDVI) and reflectance water index (WI). n = 42.

Yield SPAD 485 nm 560 nm 660 nm 830 nm 1650 nm RVI RNVI

Yield 1SPAD 0.78** 1485 nm −0.69* −0.58* 1560 nm −0.62* −0.48 ns 0.97** 1660 nm −0.68* −0.56* 0.99** 0.97** 1830 nm 0.71** 0.57* −0.82** −0.74** −0.81** 11650 nm −0.66* −0.59* 0.93** 0.91** 0.93** −0.69* 1RVI 0.69* 0.51* −0.95** −0.94** −0.95** 0.86** −0.87** 1RNVI 0.68* 0.50* −0.95** −0.95** −0.95** 0.88** −0.86** 0.99** 1

†: ns, * and **: not significant and significant at P < 0.05 and at P < 0.01, respectively.

F easua t diffef

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ig. 4. Comparison of strawberry total fruit yield (A) and marketable fruit yield (B) mnd standard deviation of 14 measurements in a 1-m2 area. The honestly significanor the marketable yield variables (˛ = 0.05).

ation because of high radiation and water runoff in high position

reas (Fig. 5).

Supra-optimal temperature (24–26 ◦C) exerted a modifyingnfluence on the response of strawberry and at 30 ◦C the plantsailed to form the flower buds (Ito and Saito, 1962; Heide, 1977).igh temperatures associated with drought could also induce the

ig. 5. Regression relationships of strawberry marketable fruit yield and solar irradianceWI, B); strawberry marketable fruit yield and site elevation (SE in m, C); and strawberry

red in the shoulder, slope and down flat areas, respectively. Each bar was the meanrence (HSD, Tukey test) values were 0.40 kg m−2 for the total yield and 0.47 kg m−2

earlier flower bud formation (Klamkowski and Treder, 2008). Tem-

perature or soil water status associated with topographic featurescould further affect soil nutrient distribution, and thus crop nutri-ent uptake and yields (Rorison et al., 1986; Li et al., 2001b, 2002),which would explain the variation of strawberry yield (Fig. 4) andits correlation with the plant nitrogen status (NDVI and RNVI) and

(IRR in W m−2, (A); strawberry marketable fruit yield and reflectance water indexmarketable fruit yield and soil water content (SWC in g g−1, D).

172 H. Li et al. / Environmental and Experimental Botany 68 (2010) 165–174

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ig. 6. Regression relationships of strawberry marketable fruit yield vs. normalizitrogen vegetative index (RNVI, B); strawberry marketable fruit yield vs. ratio veeadings (D).

eaf chlorophyll content (Fig. 6). The similar approach has been usedor quantifying plant abiotic stress (Carter and Knapp, 2001).

Strawberry fruit surface temperatures were slightly higher thaneaves (Fig. 3), which would be due to the heat accumulation inhe fruits. The lack of correlation between soil pH and strawberryield and other measured variables would be because there waso difference in soil pH within the field (Table 1). The decline intrawberry fruit yields in slope and shoulder areas could also be theonsequence of high IRR and water deficit stress leading to reducedeaf stomatal activity, water channel activity in stolons and dis-ribution of photoassimilates within strawberry plants associatedith drought stress, as comparable to the consequences reported

n other studies (Blanke and Cooke, 2004; Klamkowski and Treder,008).

The water deficit in the shoulder and slope areas was shown byheir significantly higher WI (0.75–0.82) compared to the WI values0.48–0.65) in the downslope terrain. Plant water stress occurredhen the plant demand for water exceeded the available amounturing a certain period and water stress was among the princi-al causes of reduced plant development and reduction in cropield (Griffiths and Parry, 2002; Claudio et al., 2006; Li et al., 2008).lant water stress could lead to stunted growth, and water-stressedtrawberry plants might not enable for vigorous fruit bearing. Thebility to recognize early symptoms of plant water stress was cru-ial without significant economic reduction of crop yield (Blum,996; Griffiths and Parry, 2002). The WI index and canopy infraredemperature could be a real-time indicator of plant water stress

inimizing negative impacts of water deficit on plant growth andevelopment (Jackson, 1982; Penuelas et al., 1997; Claudio et al.,006).

.2. Strawberry plant water holding and plant vigor related toeflectance and spectral index

Strawberry plant water holding status could also be explainedsing the reflectance WI, estimated using the water band MIR

ference vegetative index (NDVI, A); strawberry marketable fruit yield vs. relativeve index (RVI, C); and strawberry marketable fruit yield vs. leaf chlorophyll SPAD

reflectance to the NIR reflectance. High WI value meant low waterholding in the plants. The WI was a useful estimate of yield loss fromplant water stress as its regression relation with the strawberryfruit yield was significant (Fig. 5B). The MIR band (center 1650 nm)was within the two major water bands (1400 and 1900 nm), theNIR (center 830 nm) was away the water bands, and therefore thecorrelation between NIR and MIR reflectance was significantly neg-ative (Table 3). This relation confirmed that the use of NIR bandwas adequate for determination of plant water holding, as shownin Claudio et al. (2006).

As the MIR reflectance was positively correlated with the blue,green and red bands (0.91 < r < 0.93, Table 3), it indicated when thestrawberry plant reflected more visible and MIR energy, the plantswere more water stressed. High MIR reflectance meant low watercontent in the plants. Plants containing less water would reflectmore MIR band energy than plants containing higher water content(Jackson, 1982; Li et al., 2001a). When the SWC was low, plants hadto use more energy to uptake available water and nutrients, andplants might develop stress symptoms (Sperry et al., 2002; Li et al.,2008). Low NIR reflectance would mean a small leaf area and smallplant ground cover (Jackson, 1982; Carter and Knapp, 2001; Li etal., 2001a).

The high reflection of NIR energy corresponding to the highabsorption of MIR energy and high leaf chlorophyll of strawberryplants (Table 3) would mean a strong plant vigor. Leaf chloro-phyll molecule was vital for photosynthesis that could absorb thesunlight to help plants get energy from lights, and leaf chloro-phyll was commonly considered as indicator of plant growth status(Markwell et al., 1995). Plant water stress status and plant eco-physiological processes could be detected from color, vigor, andmorphology of stressed plants (Li et al., 2001a; Claudio et al., 2006).

Also, a physiological approach to understand how plants couldadapt to water deficit in the soil would be measuring their multi-spectral reflectance, i.e., a ratio of incoming to outgoing radiationin the visible and near infrared bands and its canopy infrared tem-perature (Jackson, 1982; Li et al., 2001b).

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.3. Planting design and orientation of rows for light and wateranagement

Full sunlight exposure through the canopies is a key factoror maximizing fruit bearing (Heide, 1977; Watson et al., 2002;ieger, 2005). The consequences of uneven landforms and inter-al drainage constraints from the current study included unevenistribution of light spectrum (Table 1), temperatures (Fig. 1) andoil water (Table 1) and insufficient strawberry plant water hold-ng (high WI) and low fruit bearing in slope areas (Fig. 4). As mostelds commonly characterize by uneven landforms, each crop hasspecific minimum threshold growth and water requirement for

conomic production in a given environment. Evaluation of wholelant responses to a given water shortage is difficult because ofany other factors also affecting the production system (Blum,

996; Griffiths and Parry, 2002; Sperry et al., 2002).New planting designs which consider an alternative orientation

f rows can be an option for improving light and water managementn this soil having natural rolling and internal drainage constraints.he current orientation of rows following the aspect direction (N–S)s useful for sunlight exposure to the strawberry plants and waterrainage in case of heavy rainfall. Being in the humid Atlantic coast,here is excess precipitation in the region (mean annual rainfall200 mm and high rainfall frequency in the spring). Therefore inarming practices row orientation for fruit crop planting is usu-lly along the aspect to support drainage in the spring and to helpncrease soil temperature during that time of year. However, asainfall is reduced in the summer and strawberry plants requiresore water during the full vegetative stage for flower bud forma-

ion and fruit bearing, the row orientation along the aspect seemsot to help for reducing water runoff and internal drainage. It is sug-ested that alternative orientation of row in the NE–SW directionr the W–E direction would help reduce both water losses from sur-ace runoff and internal drainage during the important strawberryowering and fruiting period. Also, as the strawberry is planted onhe raised beds, the soil can warm up sooner in the spring and theanopies can still be fully exposed to sunlight with the NE–SW or

–E orientation of rows.Other options for water management in this soil with natural

unoff and internal drainage constraints would be introducing driprrigation. Sprinkle irrigation is useful for frost protection but driprrigation is more efficient than overhead irrigation in terms of plant

ater use. Drip irrigation reduces water runoff and requires 50%ess water (El-farhan and Pritts, 1997). Also, water managementould include establishing runoff control systems by adding organicatter which can be mixed into the soil for sealing the surface to

educe infiltration (Li et al., 2004).Future study on light and water management for naturally

ndulating conditions with rapid internal drainage constraintsould be evaluated using new planting design with alternative ori-

ntation of rows for capturing maximum sunlight interception andeducing water runoff, especially during fruit bearing period. In thisoast area, growers have practiced strawberry rotations with rye-rass for reducing tillage for soil and water conservation. Otherractices have included keeping soil in place by planning a coverrop for soil protection. More information such as adding organicatter into the soil to reduce infiltration and strawberry flowering

nd budding capacity in relation to early season temperature, irra-iance and water availability is needed for developing managementtrategies for enhancing high-value horticultural crop productionn the soils with these natural constraints.

. Conclusions

Lights and water were not evenly distributed in the fieldith topographic features and rapid internal drainage constraints.

ental Botany 68 (2010) 165–174 173

Solar radiation, temperature and mainly water availability werefactors associated with site elevation to influence strawberry fruit-ing efficiency. Strawberry fruit yield were negatively correlatedwith solar irradiance, which suggested that high solar radiationand high temperature associated with water loss would exert asignal negative influence on the responses of cool-weather straw-berry plants and consequently reducing fruit formation. Strawberryplants in the slope areas were more water stressed with a higherreflectance WI, and therefore reduced fruiting rates. Strawberryplant vigor, expressed by leaf temperature, whole plant multi-spectral reflectance, and WI, NDVI, RNVI and RVI determined fromwhole plant multispectral signals could be real-time indicators ofplant light and water conditions. It is suggested that N–S orienta-tion of rows following the aspect may create water stress conditionsduring fruit bearing period. A new planting design for alternativeorientation of rows and drip irrigation would be tested for captur-ing maximum sunlight and reducing water loss in the fields withnatural constraints.

Acknowledgements

We thank Nova Scotia Department of Agriculture (NSDA) Tech-nology Development Program, Advancing Canadian Agricultureand Agri-Food Council Agri-Futures Program, Horticulture NovaScotia, Millen Farms, and National Natural Science Foundation ofChina (NSFC, Project 40671110/D0115) for support for this study.

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