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Environmental and Experimental Botany 68 (2010) 165174

Contents lists available at ScienceDirect

Environmental and Experimental Botany

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / e n v e x p b o t

Strawberry plant fruiting efficiency and its correlation with solar irradiance,

temperature and reflectance water index variation

Hong Li a,b,, Tingxian Li c, Robert J. Gordon d, Samuel K. Asiedu a, Kelin Hu b

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

a r t i c l e i n f o

Article history:

Received 7 July 2009

Received in revised form 4 November 2009

Accepted 1 December 2009

Keywords:

Light

Planting design

Strawberry fruit

Topographic features

Water

a b s t r a c t

Uneven light distribution and low water holding capacity are two constraints limiting strawberry (Fra-

gariaananassa Duch.) production in coastal northern Atlantic areas. A study was conducted in a

commercial strawberry production field characterized by rapid internal soil drainage and undulating

land features in Nova Scotia. The objectives were to examine the uneven distribution patterns of solar

irradiance (IRR), temperature and soil water content (SWC) and quantify correlations of these physical

variables with strawberry fruit yield, plant reflectance water index(WI) and leaf chlorophyll. Strawberry

row orientation was along the field aspect in the northsouth (NS) direction for maximizing plant sun-

light exposure and spring rainfall drainage. The measurement design consisted of a nested grid with

five transects. Results showed that solar radiation incident upon the canopy was significantly higher

(mean IRR 779820 W m2) in the shoulder and slope areas compared to the mean IRR of 709W m2

in downslope area (P< 0.001), where higher SWC and lower temperature stimulated strawberry fruit

bearing. Significantly higher reflectance WI was related to low strawberry yield (R2 =0.55, P< 0.05).

Strawberry fruit yieldwas positivelycorrelated to normalizeddifference vegetationindex, ratio nitrogen

vegetative index and leaf chlorophyll (0.46< R2


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166 H. Li et al. / Environmental and Experimental Botany 68 (2010) 165174

Soil water is recognized as the greatest hazard affecting sys-

tems productivity and sustainability (Blum, 1996; Griffiths and

Parry, 2002; Sperry et al., 2002; Li et al., 2001a, 2002, 2004,

2008). Reduced water availability induces numerous physio-

logical and biochemical changes in plant organs (Hetherington

and Woodward, 2003). Drought and NaCl stress in strawberry

plant can retard the development of its reproductive organs,

leading to fewer flowers and fruit (Blanke and Cooke, 2004;

Klamkowski and Treder, 2008; Keutgen and Pawelzik, 2009).

Irrigation is often practiced following the onset of plant water

stress, however, this is often too late to avoid a partial reduc-

tion in yield (El-farhan and Pritts, 1997; Li et al., 2002). Plant

responses in canopy spectral reflectance, transmittance or absorp-

tance are real-time eco physiological indicators of plant water

stress (Jackson, 1982; Carter and Knapp, 2001). Crop yield differ-

ence can be explained by spectral index such as relative nitrogen

vegetative index (RNVI), normalized difference vegetation index

(NDVI) (Jackson, 1982; Li et al., 2001a,b). Reflectance water index

(WI) is a spectral indicator for real-time management of plant

water stress (Jackson, 1982; Penuelas et al., 1997; Claudio et al.,

2006).

Light, solar radiation and temperature distribution can vary sig-

nificantly under different topographic features such as elevation,

aspect and slope (Rorison et al., 1986; Florinsky et al., 1994; Li etal., 2001b). Temperature is oneof themostimportant factors affect-

ing strawberry plant nutrient uptake (Ganmore-Neumann and

Kafkafi, 1985) and wheat photosynthesis and grain-filling (Shah

and Paulsen, 2003). High temperature (2432 C) reduces straw-

berry flower formation and fruit quality (Heide, 1977; Klamkowski

and Treder, 2008). Temperature is associated with strawberry

flower bud induction (Ito & Saito, 1962; Heide, 1977), runner,

meristem-tip and leaf variegation (Watkins et al., 1990), dormancy

induction (Robert et al., 1999), fruit flavors (Watson et al., 2002),

and membrane phospholipids (Wang and Lin, 2006).

Planting orientation of rows is usefulfor maximizing light inter-

ception by plant canopies to achieve high yield and fruit quality

(Rieger, 2005). Light andwatermanagement forsoilshaving rolling

and coarse-textured gravel characteristics that can lead to unevendistributionof light andwateris a challenge forgrowers. Currently,

no information is available for light and water management under

the influence of rolling landforms and rapid internal drainage.

Therewas a needfor understanding the relationships between solar

radiation, temperature, soil water and strawberry fruit yields. In

addition, plant and soil functions are often encountered for under-

lying environmental variables, which should be measured as a

function of space in systematic grid sampling scheme ( Marriott et

al., 1997; Cole et al., 2001; Li et al., 2002).

Several studies have addressed strawberry plant and supra-

optimal temperature (or photoperiod) problemsonly (Ito and Saito,

1962; Heide, 1977; Ganmore-Neumann and Kafkafi, 1985; Watkins

et al., 1990; Robert et al., 1999; Watson et al., 2002; Wang and

Lin, 2006), or strawberry plant water (or salinity) problems only(Blanke and Cooke, 2004; Klamkowski and Treder, 2008; Keutgen

and Pawelzik, 2009). We conducted a 2-year study in a strawberry

field in the coastal areas of Nova Scotia to quantify simultaneously

the roles of solar irradiance, temperature and soil water variation

in strawberry fruit setting on lands with natural rolling charac-

ters and drainage constraints. It was hypothesized that undulating

landforms and natural drainage constraints can create difference

in solar radiation capture, temperature and soil water distribution

patterns. This can then impact strawberry plant development and

fruit yield. The objectives of the study were to (i) examine the dis-

tribution patterns of solar irradiance (IRR), temperatures and SWC,

and (ii) quantify strawberry plant fruiting efficiency and its cor-

relations with these physical variables and plant reflectance WI,

canopy spectral index and leaf chlorophyll across the landscape.

The information would be useful for understanding light, temper-

ature, water and plant relations for growing high-value fruit crops

in soils with natural constraints.

2. Materials and methods

2.1. Study site and strawberry planting description

The study was conductedin an irrigated, commercial strawberry

production field (454001N, 635415W) near Glenholme in the

Cobequid Bay, Nova Scotia during 20062007. The site was 1.2-ha

in size with a 3-crop, 6-year rotation regime, which was 2-year

grass, 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% and

an aspect in the northsouth (NS) direction. The field landforms

consisted of a 30-m long shoulder area, a 28-m slope and a 28-

m downslope flat terrain along the aspect. The previous crop was

2-year perennial ryegrass (Lolium perenne L.) to improve soil qual-

ity including suppressing pests and disease fungi. In May 2005, the

strawberry cv Annapolis, a lateJune-early Julybearing variety,was

transplanted in raised beds (1.2 m in dimension) for soil warming,rainfall evacuating and sunlight capture. The orientation of rows

was following the aspect in the NS direction, an usual planting

practice of orientation of rows for maximum plant sunlight expo-

sure forfruitbearing andalso forfacilitating drainage when rainfall

was more frequent in the spring.

The strawberry plant spacing was 1.5m between rows and

0.50m apart between plants in the row. After transplanting the

plants were mulched with wheat straw to conserve soil water and

control weeds. The strawberry plants were fertilized based on soil

tests performed in the spring and utilized regional recommenda-

tions. Irrigation was done on a rainfall compensation basis using

sprinkler system with pipes installed 24 m apart across the field.

The useof sprinkle irrigation washelpful forfrostprotection.At the

critical stage of transplant establishment, the irrigation rates were4 L m2 per day because the newly set transplants were suscepti-

ble to even mild water stress (El-farhan and Pritts, 1997). The total

irrigation water was on average 260 L m2 per season, which was

in the range of irrigation recommendation for mulching strawberry

(El-farhan and Pritts, 1997).

For better fruit bearing, strawberry plant runners were thinned

duringthe first growing season. Floweringstemson theplants were

consistentlyremoved as they appeared throughout the season. The

flower thinning strengthened the mother plants and main runner

plants. Nutrientswere applied basedon soiltest results and disease,

insect and weed control was done according to the regional rec-

ommendation. The plants were mulched for winter protection and

irrigation at the rate of 5 L m2 was done prior to mulch covering

to reduce risk of cold-temperature injury.In 2006, the strawberry plants were allowed to attain a large

size at full vegetative stage then allowed flowers for fruit bearing

from June through harvest in mid July. Irrigation was done at the

rate of 4 L m2 per day (dry days) during the periods of flowering,

initiation of berry setthrough thefinal enlargement of thefruit. The

strawberry plants were cared for crop protection, fertilization and

irrigation for fruit bearing for 2007. However, the plants were hit

by an unexpected hail storm during the fruit bearing period (mid

June 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


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H. Li et al. / Environmental and Experimental Botany 68 (2010) 165174 167

Fig. 1. Spatial interpolated patterns of site elevation (A), solar irradiance (B), soil water content (C), strawberry plant reflectance water index (D), leaf chlorophyll SPAD

readings (E) and strawberry marketable fruit yield (F).

apart, along the aspect (NS) direction, and three other transects

(three strawberry rows), 24m apart, in the westeast (WE) direc-

tion across the field. The two NS transects were five rows apart,

covering along the shoulder, slope and downslope areas where it

presented the greatest variability in elevation following the aspect.

The three WE transects were parallel, with each transect in the

shoulder, slope and downslope area, respectively. All measure-

ments were taken in the 7.56 m grid in the NS transects, and

2412m gridalongtheWEtransects. The gridarea was 72m long

in the aspect (NS) direction and 72m in the WE direction (Fig. 1).This nested grid design had an advantage of emphasis on exam-

ining the spatial variability in the areas presenting the greatest

variability, as shown in Marriott et al. (1997) and Cole et al. (2001).

The field measurements were initiated in 2006 because of the

plant runner and flower thinning in the first year (2005). The mea-

surement points were geo-referenced using a Garmin handheld

GPS system (Garmin International, Olathe, KS). There were a total

of 42 GPS points with 12 measurements in each NS transect and

6 measurements in each WE transect.

Soil temperature, strawberry leaf and fruit temperatures were

measured using an infrared thermal sensor (Spectrum Technolo-

gies, Plainfield, IL). The temperature measurements were taken at

full vegetative stage, at flowering andat fruit bearing stage. At each

stage temperatures were measured two times in a 10-day interval.

Temperature measurements were taken simultaneously on three

fruits, leavesand soils at each measurement point.Fruits andleaves

for the measurements were selected at the same levels of plant

heights each time.

Leaf chlorophyll content was measured on the same leaves as

for temperature measurements using a Minolta SPAD 502 meter

(Markwell et al., 1995). Three chlorophyll measurements were

taken on separate leaves at each GPS point three times at full vege-

tative stage,at flowering andat fruit bearing stage. Airtemperature

data 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 1752nm using a portable multispectral

radiometer (MSRSYS5, CropScan, Rochester, MN), a rapid assess-

ment taken directly on plant canopies across the field (Li et al.,

2001a). The MSRSYS5 consistedof five up-sensorsto detect incident

energyand fivedown-sensorsto detectoutgoingenergy. Theplant-

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 of

theGPS pointswithin thegrids. Thespectralreadings were taken at

14:00 within a time of 1530 solar zenith angle at full vegetative

stage, at flowering and at fruit harvest. Sensor outputs consisted of

the reflectance readings at the center wavelength of 485, 560, 660,


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830 and 1650 nm, respectively. The blue, green, red, near infrared

(NIR) andmidinfrared(MIR) bandswere acrossa wavelength width

between 452518 nm,524596nm, 631689 nm,757903 nm and

15531748nm, respectively. As a result, thewavelength width was

similarly narrow, comparable within the blue, green and red bands

(5772 nm) and also within the NIR and MIR bands (146195 nm).

Solar irradiance (IRR), the power of electromagnetic radiation

incident upon the canopy surface per unit area, was detected

simultaneously with the plant reflectance measurements, using

the MSRSYS5 radiometer up-facing sensor at the center 560nm

(wavelength width 524596 nm). This green band was the near-

est band to the peak of the solar spectrum (480nm). The up-sensor

estimated the total hemispherical irradiance or received on 1-m2

canopy surface. This green band was a narrowband (72nm) and

provided estimations with uncertainty within 5% of total solar

incident radiation in clear sky conditions or in lightly cloudy con-

ditions, verified using solar pyranometer readings. It was to note

although the blue band (485nm)was closer to the peak of the solar

spectrum than the green band, the blue sensor was not chose for

the solar irradiance measurements because the hemispherical blue

light could drop more quickly than the green light when it was

slightly cloudy (Jackson, 1982; Carter and Knapp, 2001; Claudio et

al., 2006).

The soil water content was measured at the depth of 00.15musing a TDR probe (Spectrum Technologies, Plainfield, IL). A com-

posite soil sample with three soil cores was taken at the depth

of 00.15m. Soil samples were air-dried. Soil pH was measured

using pHH2O (m/v1:1)ratio(Liet al.,2002). Soil wateravailability

expressed on a gravimetrical basis was also determined by drying

soil 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-m

long on the rows at each GPS point in 2006. The fruit yields were

assessed neither in thefirst year in 2005 (due to plant thinning) nor

in 2007 (because of the hail damage). The strawberry marketable

yield was obtained from marketable-size (2.5cm) fruits with red,

free of defects for each GPS point. Damaged or diseased fruits were

discarded. Elevation data taken using the Garmin unit were then

calibrated with the soil map unit elevation (Webb et al., 1991) toobtain the estimated elevation data for each sampling site.

2.3. Plant, water and soil data analysis and mapping

Strawberry plant spectral reflectance readings were calibrated

with a reflectance correction factor, and then converted to

reflectance percentage, a ratio from thedown andup sensor output

in mV, asdescribed in Li et al.(2001a). Soil reflectance was discrim-

inated in the red band (center 660 nm), and plant reflectance was

discriminated in theNIR band (center 830nm). Plant water holding

status was estimated using the reflectance data in the water band,

which was the MIR band (center 1650nm), as shown in Li et al.

(2001b) and Claudio et al. (2006).

The ratio vegetative index (RVI) was the ratio of NIR to redreflectance (NIR/red). The NIR and green (G) reflectance (NIR/G)

ratio was defined as relative nitrogen vegetative index (RNVI). The

normalized difference vegetative index (NDVI), a spectral vege-

tative index widely used in termination of plant N status, was

determined by the ratio of differencing and combining reflectance

measured in NIR and red bands as NDVI= (NIR red)/(NIR+ red), as

shown in Li et al. (2001a,b).

Reflectance water index (WI) was estimated using the ratio of

thereflectance withinthe water band wavelength, center1650nm,

to the nearby reflectance wavelength where there was no water

absorption, which wasthe NIRband830 nm.The wavelength width

of this 1650-nm water band (width 15531748 nm) was very close

tothe twomostprominentwaterbands (1400and 1900nm). Water

adsorption was strong in the MIR bands and plant reflectance at

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 grouped

by landform for analysis of variance and comparison of means

between the shoulder, slope and downslope landform groups.

Descriptive statistics and correlation of data were done using PROC

UNIVARIATE and PROC CORR procedures (SAS Institute, 1990). The

analysis of variance between the landform groups was done using

General Linear Models (GLM) procedure. The Honestly Significant

Difference (HSD) was used for comparison of means between the

landform groups (SAS Institute, 1990). Variance homogeneity of

datasets was verified using the Bartlett test, and normality and

residual 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 Systems

Research Institute Inc., Redlands, CA).

3. Results

3.1. Distribution patterns of solar irradiance, soil water and

strawberry water index

The descriptive statistics showed that physical properties (site

elevation, IRR and SWC), soil pH, and strawberry plant physio-

logical variables (reflectance WI, leaf chlorophyll SPAD readings

and NDVI) were highly variable (Table 1). The field topography

featured a lineardecline from theshoulder, slope to downslopeter-

rain (Table 1) and the interpolated topographic patterns showed

the aspect direction and the landform zones (Fig. 1A). The site

elevation had a range of 6.3m with a mean of 2 m difference

between the sequent landforms (n = 14 each landform group) and

the difference was significant (P< 0.001, Table 1). The IRR showed

the similar patterns as the elevation (Fig. 1B) with values being

the highest (830840W m2) in the shoulder area (Table 1), and

the 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 were0.9m for the elevation and 18W m2 for

the IRR variable ( = 0.05).

Soil water content (SWC) varied between 0.06 and 0.20 g g1

and the difference in SWC was significant between the landforms

(F=4.13, P< 0.05, df= 2). The HSD value was 0.03g g1 for the SWC

variable ( = 0.05). The interpolated SWC patterns were spatially

dividing by landform (Fig. 1C). Soil pH (mean 6.626.84) was with

in the optimal range for strawberry growth. Slightly higher soil pH

values were measured in the high radiation shoulder area but the

difference was not significant between the landforms (Table 1).

Strawberry plantwater indexwas significantly higher(WI range

0.640.80) in the slope area than in the shoulder and downslope

areas (Table 1). Significantly higher WI values were situated in theshoulder and slope areas (Fig. 1D). Higher WI indicated a higher

plant water stress. As a result, the SPAD readings and the NDVI

index values were significantly lower in the slope areas than in

the shoulder and downslope areas. Overall, the datasets were not

skewed(kurtosis < 3)except thesoilpH inthe slope(kurtosis = 3.76)

and downslope areas (kurtosis= 4.68) and the sample variances

were proportional to the means of variables (Table 1). The HSD

valueswere0.05for theWI and0.04forthe 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 high

IRR and high elevation, indicating a water loss possibly from runoff

in high elevation shoulder and slope areas.


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Table 1

Descriptive statistics andcomparison of siteelevation,solar irradiance (IRR), soilwater content (SWC), soilpH, strawberry plant reflectance water index(WI), leafchlorophyll

concentration (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

Shoulder

Mean 21.5 820 0.13 6.84 0.66 34.5 0.69

Standard deviation 0.6 16.4 0.04 0.50 0.10 4.28 0.12

Sample variance 0.3 270 0.11 0.25 0.21 18.4 0.17

Kurtosis 0.5 0.04 0.06 1.32 1.35 1.44 0.86

Skewness 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 0.65

Maximum 22.6 844 0.20 7.55 0.70 40.0 0.75

Slope

Mean 19.5 779 0.12 6.71 0.71 30.8 0.64


Sample variance 1.4 657.0 0.13 0.17 0.36 5.90 0.20

Kurtosis 0.8 1.4 0.39 3.76 0.15 1.08 0.25

Skewness 0.2 0.1 0.40 1.63 0.07 1.32 0.26

Minimum 17.3 738 0.06 5.58 0.64 27.8 0.56

Maximum 21.3 816 0.18 7.25 0.80 35.9 0.71

Downslope

Mean 17.6 709 0.16 6.62 0.52 38.6 0.81


Sample variance 0.7 701 0.09 0.22 0.17 20.4 0.14

Kurtosis 0.3 0.1 0.98 4.68 1.19 0.89 1.44

Skewness 0.4 0.5 0.36 1.72 0.10 0.03 0.11

Minimum 16.3 669 0.09 5.30 0.48 32.0 0.75

Maximum 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**

Slope vs. downslope 33.39** 31.67** 3.76* 1.44 ns 91.68** 25.84** 74**

a Elevation in m, IRR in W m2 and SWC in gg1.b ns, * and **: not significant and significant at P< 0.05 and at P< 0.001, respectively.

3.2. Trends of strawberry fruit, leaf and soil temperatures

Meanday-timeair and surface soiltemperatures ranged922 C

during the growing season. Maximum air temperatures varied

between 26 and32.4C duringthe firsttwo weeks ofJulyeach year.

The surface soil temperatures measured in the warmest month

(July) were significantly higher (35.60.7 C, range 35.637.4 C)in the shoulder area than in the downslope areas (31.3 0.8 C,

range 31.233.0 C). The landform had a significant effect on the

surface soil temperatures (F= 94.75, P< 0.001, df= 2). Soil tempera-

tures were significantly different between the shoulder, slope and

downslope (P< 0.001) and their HSD value ( = 0.05) was 0.98 C

(Fig. 2).

Fig. 2. Comparison of surface soil temperatures in shoulder, slope and downslope

areas. Each bar was the mean and standard deviation of 42 readings at each GPS

point, measured during early July 2006 and early 2007. The honestly significant

difference (HSD, Tukey test) value was 0.98

C ( = 0.05).

The temperatures in July were important because it was the

time during the strawberry fruit bulking and maturity period.

The temperatures measured on the strawberry fruits and leaves

were significantly different with the HSD value ( = 0.05) of 1.09C

(Fig. 3). Across the nested grid, strawberry surface fruit temper-

atures varied between 32.91.3 C, which was on average 5.8 C

higher than leaf temperatures (27.10.5 C). The landform had asignificant effecton the fruit,leaf andsoil temperatures (F= 135.97,

P


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Table 2

Descriptive statistics of strawberry plant reflectance in different bands, the ratio vegetative index (RVI), relative nitrogen vegetative index (RNVI), normalized difference

vegetative index (NDVI) and reflectance water index (WI). n =42.

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

Mean 4.89 9.77 8.62 51.3 31.9 6.45 5.36 0.71 0.63

Standard deviation 1.06 1.24 2.23 3.19 2.55 2.07 0.90 0.07 0.07

Sample variance 1.13 1.53 4.97 10.2 6.50 4.28 0.82 0.01 0.01

Kurtosis 0.16 0.07 0.28 0.01 0.23 0.93 0.56 0.45 0.57

Skewness 0.43 0.23 0.35 0.07 0.23 1.02 0.72 0.20 0.17

Minimum 2.67 6.83 4.10 43.3 26.3 3.18 3.55 0.52 0.48Maximum 8.05 13.62 15.13 60.9 39.9 13.9 8.32 0.87 0.80

CV (%) 22 13 26 6 8 32 17 10 12

a Reflectance data are in %.

ing the water band (center 1650 nm) (Table 2), as plants absorbed

strongly visible energy and reflected NIR energy. The descriptive

statistics showed that all the reflectance data and spectral index

values were not skewed (small kurtosis values 0.071.02, Table 2).

The NIR reflectance was significantly lower in the slope area (mean

46%) compared to in the downslope flat terrain (mean 54%). The

green band reflectance was slightly higher than the red band. As

a result, the ratio vegetative index (RVI) was higher than the rela-

tive nitrogen vegetative index (RNVI). The NDVI andreflectance WI

values were compatible (Table 2). Similar to the NDVI distributions

pattern (Table 1), the high RVI (12.113.9) and high RNVI values

(7.18.3) were measured in the downslope areas.

The landform had the significant effects on the blue (F= 61.9,

P


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Table 3

Pearson correlation coefficients (r) of strawberry marketable fruit yield plant reflectance in different bands, the ratio vegetative index (RVI), relative nitrogen vegetative

index (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 1

SPAD 0.78** 1

485nm 0.69* 0.58* 1

560nm 0.62* 0.48 ns 0.97** 1

660nm 0.68* 0.56* 0.99** 0.97** 1

830 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* 1

RVI 0.69* 0.51* 0.95** 0.94** 0.95** 0.86** 0.87** 1

RNVI 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.

Fig. 4. Comparison of strawberry total fruit yield (A)and marketable fruit yield (B)measured in theshoulder, slope anddownflat areas,respectively.Each bar wasthe mean

and standard deviation of 14 measurements in a 1-m2 area. The honestly significant difference (HSD, Tukey test) values were 0.40 kg m2 for the total yield and 0.47 kg m2

for the marketable yield variables ( =0.05).

vation because of high radiation and water runoff in high position

areas (Fig. 5).

Supra-optimal temperature (2426 C) exerted a modifying

influence on the response of strawberry and at 30 C the plants

failed to form the flower buds (Ito and Saito, 1962; Heide, 1977).

High temperatures associated with drought could also induce the

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

perature or soil water status associated with topographic features

could 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) and

its correlation with the plant nitrogen status (NDVI and RNVI) and

Fig. 5. Regression relationships of strawberry marketable fruit yield and solar irradiance (IRR in W m2, (A); strawberry marketable fruit yield and reflectance water index

(WI, B); strawberry marketable fruit yield and site elevation (SE in m, C); and strawberry marketable fruit yield and soil water content (SWC in g g1

, D).


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Fig. 6. Regression relationships of strawberry marketable fruit yield vs. normalized difference vegetative index (NDVI, A); strawberry marketable fruit yield vs. relative

nitrogen vegetative index (RNVI, B); strawberry marketable fruit yield vs. ratio vegetative index (RVI, C); and strawberry marketable fruit yield vs. leaf chlorophyll SPAD

readings (D).

leafchlorophyll content (Fig.6). Thesimilarapproachhas been used

for quantifying plant abiotic stress (Carter and Knapp, 2001).

Strawberry fruit surface temperatures were slightly higher than

leaves (Fig. 3), which would be due to the heat accumulation in

the fruits. The lack of correlation between soil pH and strawberry

yield and other measured variables would be because there was

no difference in soil pH within the field (Table 1). The decline in

strawberry fruit yieldsin slope andshoulderareascouldalso be theconsequence of high IRRand water deficitstress leading to reduced

leaf stomatal activity, water channel activity in stolons and dis-

tribution of photoassimilates within strawberry plants associated

with drought stress, as comparable to the consequences reported

in other studies (Blanke and Cooke, 2004; Klamkowski and Treder,

2008).

The water deficit in the shoulder and slope areas was shown by

theirsignificantly higherWI (0.750.82) compared to the WI values

(0.480.65) in the downslope terrain. Plant water stress occurred

when the plant demand for water exceeded the available amount

during a certain period and water stress was among the princi-

pal causes of reduced plant development and reduction in crop

yield (Griffiths and Parry, 2002; Claudio et al., 2006; Li et al., 2008).

Plantwater stress couldlead to stunted growth, and water-stressedstrawberry plants might not enable for vigorous fruit bearing. The

ability to recognize early symptoms of plant water stress was cru-

cial without significant economic reduction of crop yield (Blum,

1996; Griffiths and Parry, 2002). The WI index and canopy infrared

temperature could be a real-time indicator of plant water stress

minimizing negative impacts of water deficit on plant growth and

development (Jackson, 1982; Penuelas et al., 1997; Claudio et al.,

2006).

4.2. Strawberry plant water holding and plant vigor related to

reflectance and spectral index

Strawberry plant water holding status could also be explained

using the reflectance WI, estimated using the water band MIR

reflectance to the NIR reflectance. High WI value meant low water

holding in theplants.The WIwas a usefulestimate ofyieldlossfrom

plant water stress as its regression relation with the strawberry

fruit yield was significant (Fig. 5B). The MIR band (center 1650nm)

was within the two major water bands (1400 and 1900 nm), the

NIR (center 830 nm) was away the water bands, and therefore the

correlation 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 shown

in 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 the

strawberry plant reflected more visible and MIR energy, the plants

were more water stressed. High MIR reflectance meant low water

content in the plants. Plants containing less water would reflect

more MIRbandenergythanplants containing higherwatercontent

(Jackson, 1982; Li et al., 2001a). When the SWC was low, plants had

to use more energy to uptake available water and nutrients, and

plants might develop stress symptoms (Sperry et al., 2002; Li et al.,

2008). Low NIR reflectance would mean a small leaf area and small

plant ground cover (Jackson, 1982; Carter and Knapp, 2001; Li et

al., 2001a).The high reflection of NIR energy corresponding to the high

absorption of MIR energy and high leaf chlorophyll of strawberry

plants (Table 3) would mean a strong plant vigor. Leaf chloro-

phyll molecule was vital for photosynthesis that could absorb the

sunlight to help plants get energy from lights, and leaf chloro-

phyll was commonly considered as indicatorof plant growth status

(Markwell et al., 1995). Plant water stress status and plant eco-

physiological processes could be detected from color, vigor, and

morphology of stressed plants (Li et al., 2001a;Claudio et al., 2006).

Also, a physiological approach to understand how plants could

adapt to water deficit in the soil would be measuring their multi-

spectral reflectance, i.e., a ratio of incoming to outgoing radiation

in the visible and near infrared bands and its canopy infrared tem-

perature (Jackson, 1982; Li et al., 2001b).


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4.3. Planting design and orientation of rows for light and water

management

Full sunlight exposure through the canopies is a key factor

for maximizing fruit bearing (Heide, 1977; Watson et al., 2002;

Rieger, 2005). The consequences of uneven landforms and inter-

nal drainage constraints from the current study included uneven

distribution of light spectrum (Table 1), temperatures (Fig. 1) and

soil water (Table 1) and insufficient strawberry plant water hold-

ing (high WI) and low fruit bearing in slope areas (Fig. 4). As most

fields commonly characterize by uneven landforms, each crop has

a specific minimum threshold growth and water requirement for

economic production in a given environment. Evaluation of whole

plant responses to a given water shortage is difficult because of

many other factors also affecting the production system (Blum,

1996; Griffiths and Parry, 2002; Sperry et al., 2002).

New planting designs which consider an alternative orientation

ofrows canbe anoption forimprovinglightand watermanagement

in this soil having natural rolling and internal drainage constraints.

The current orientation of rowsfollowingthe aspect direction(NS)

is useful for sunlight exposure to the strawberry plants and water

drainage in case of heavy rainfall.Being in thehumidAtlanticcoast,

there is excess precipitation in the region (mean annual rainfall

1200mm and high rainfall frequency in the spring). Therefore infarming practices row orientation for fruit crop planting is usu-

ally along the aspect to support drainage in the spring and to help

increase soil temperature during that time of year. However, as

rainfall is reduced in the summer and strawberry plants requires

more water during the full vegetative stage for flower bud forma-

tion and fruit bearing, the row orientation along the aspect seems

notto help forreducing water runoffand internaldrainage. Itis sug-

gested that alternative orientation of row in the NESW direction

or theWE directionwould help reducebothwaterlosses from sur-

face runoff and internal drainage during the important strawberry

flowering and fruiting period. Also, as the strawberry is planted on

the raised beds, the soil can warm up sooner in the spring and the

canopies can still be fully exposed to sunlight with the NESW or

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

runoff and internal drainage constraints would be introducing drip

irrigation. Sprinkle irrigation is useful for frost protection but drip

irrigationis moreefficientthan overhead irrigationin termsof plant

water use. Drip irrigation reduces water runoff and requires 50%

less water (El-farhan and Pritts, 1997). Also, water management

couldinclude establishing runoff control systems by adding organic

matter which can be mixed into the soil for sealing the surface to

reduce infiltration (Li et al., 2004).

Future study on light and water management for naturally

undulating conditions with rapid internal drainage constraints

would be evaluatedusing newplantingdesign with alternative ori-

entation of rows for capturing maximum sunlight interception and

reducing waterrunoff, especiallyduring fruitbearing period. In thiscoast area, growers have practiced strawberry rotations with rye-

grass for reducing tillage for soil and water conservation. Other

practices have included keeping soil in place by planning a cover

crop for soil protection. More information such as adding organic

matter into the soil to reduce infiltration and strawberry flowering

and budding capacity in relation to early season temperature, irra-

diance andwater availability is needed for developingmanagement

strategies for enhancing high-value horticultural crop production

in the soils with these natural constraints.

5. Conclusions

Lights and water were not evenly distributed in the field

with topographic features and rapid internal drainage constraints.

Solar radiation, temperature and mainly water availability were

factors associated with site elevation to influence strawberry fruit-

ing efficiency. Strawberry fruit yield were negatively correlated

with solar irradiance, which suggested that high solar radiation

and high temperature associated with water loss would exert a

signal negative influence on the responses of cool-weather straw-

berryplantsand consequently reducing fruitformation. Strawberry

plants in the slope areas were more water stressed with a higher

reflectance WI, and therefore reduced fruiting rates. Strawberry

plant vigor, expressed by leaf temperature, whole plant multi-

spectral reflectance, and WI, NDVI, RNVI and RVI determined from

whole plant multispectral signals could be real-time indicators of

plant light and water conditions. It is suggested that NS orienta-

tionof rowsfollowingthe aspect maycreate waterstress conditions

during fruit bearing period. A new planting design for alternative

orientation of rows and drip irrigation would be tested for captur-

ing maximum sunlight and reducing water loss in the fields with

natural constraints.

Acknowledgements

We thank Nova Scotia Department of Agriculture (NSDA) Tech-

nology Development Program, Advancing Canadian Agriculture

and Agri-Food Council Agri-Futures Program, Horticulture Nova

Scotia, Millen Farms, and National Natural Science Foundation of

China (NSFC, Project 40671110/D0115) for support for this study.

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