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The study compares the effects of: timer ('Timer') and soil moisture sensor-controlled irrigation on soilless lettuce; two volumetric water content (Θ) thresholds for irrigation (0.30 ('Θ = 0.3') and 0.40 m3/m3 ('Θ = 0.4')). The most nutrient solution (NS) was applied in 'Timer' where the lowest water use efficiency was observed, with 17 and 42% less NS used in 'Θ = 0.4' and 'Θ = 0.3', respectively. Irrigation volumes followed the plant water needs in the sensor-controlled treatments, with little or no leaching, while 18% of leaching was recorded in 'Timer'. Plants in 'Timer' and 'Θ = 0.4' had higher fresh weights (24%) and leaf area (13%) than plants in 'Θ = 0.3'. Similar dry weight was observed among treatments but percentage of dry matter was 20% higher in 'Θ = 0.3'. Gas exchanges and leaf tissues chemical composition were similar in all treatments, but nitrate concentration was lower in the 'Θ = 0.3' plants. Precision sensor-controlled irrigation based on Θ measurements is an effective tool to increase the overall water use efficiency and to improve the quality of soilless-grown lettuce by acting on the substrate moisture level. © 2016, Czech Academy of Agricultural Sciences. All rights reserved.
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Timer versus moisture sensor-based irrigation control
of soilless lettuce: Effects on yield, quality and water
use efficiency
F.F. M1, M.W.  I2, A. P1
1Institute of Sciences of Food Production, National Research Council, Bari, Italy
2Department of Horticulture, University of Georgia, Athens (GA), USA
Abstract
M F.F.,  I M.W., P A. (2016): Timer versus moisture sensor-based irrigation control
of soilless lettuce: Effects on yield, quality and water use efficiency. Hort. Sci. (Prague), 43: 67–75.
e study compares the effects of: timer (‘Timer’) and soil moisture sensor-controlled irrigation on soilless lettuce;
two volumetric water content (Θ) thresholds for irrigation (0.30 (‘Θ = 0.3’) and 0.40 m3/m3 (‘Θ = 0.4’)). e most nutri-
ent solution (NS) was applied in ‘Timer’ where the lowest water use efficiency was observed, with 17 and 42% less NS
used in ‘Θ = 0.4’ and ‘Θ = 0.3’, respectively. Irrigation volumes followed the plant water needs in the sensor-controlled
treatments, with little or no leaching, while 18% of leaching was recorded in ‘Timer’. Plants in ‘Timer’ and ‘Θ = 0.4’ had
higher fresh weights (24%) and leaf area (13%) than plants in ‘Θ = 0.3’. Similar dry weight was observed among treat-
ments but percentage of dry matter was 20% higher in ‘Θ = 0.3’. Gas exchanges and leaf tissues chemical composition
were similar in all treatments, but nitrate concentration was lower in the ‘Θ = 0.3’ plants. Precision sensor-controlled
irrigation based on Θ measurements is an effective tool to increase the overall water use efficiency and to improve the
quality of soilless-grown lettuce by acting on the substrate moisture level.
Keywords: Lactuca sativa L. var. capitata; greenhouse; volumetric water content; leaching; easily available water
Minimally processed or fresh-cut leaf y vegetables,
such as lettuce (Lactuca sativa L.), have been gain-
ing importance in the worldwide vegetable market.
Leafy lettuce was traditionally cultivated in soil, but
recently soilless cultivation techniques have been
considered. ere can be large differences between
soil and soilless systems in terms of inputs, size, lo-
cation, environmental conditions and productivity
(S et al. 2012). Although greenhouse soilless
cultivation could be impaired in some regions of
the world by the generally high capital investments
and energy requirements, greenhouse production
of leafy vegetables using soilless culture permits
precise control of plant nutrition, and allows for
more efficient water and nutrient use and higher
sanitary quality than conventional, soil-based cul-
ture. Soilless culture can also simplify post-harvest
handling and waste-water treatment (V
et al. 2008; F at al. 2009; M et al.
2011). Several recent studies focused on the effects
of nutrient solution (NS) mineral composition on
lettuce yield and quality in soilless cultivation sys-
tems (F et al. 2009; S et al. 2011).
However, there is a general lack of information on
Supported by project “Efficient Irrigation Management Tools for Agricultural Cultivations and Urban Landscapes” (IRMA) –
European Territorial Cooperation Programmes (ETCP), Greece-Italy 2007–2013.
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Hort. Sci. (Prague) Vol. 43, 2016 (2): 67–75
doi: 10.17221/312/2014-HORTSCI
the influence of irrigation management on soilless
lettuce yield and quality.
Irrigation management directly affects crop per-
formance, and efficient irrigation practices can lead
to qualitative and quantitative improvements in veg-
etable production (D et al. 2010). Efficient irri-
gation management also contributes to the sustain-
able use of water. Increasing competition for water
resources (J, V   2005) has raised consumer
and government interest in the environmental im-
pact of food production. As a result of the increasing
pressure on limited water resources, member states
of the European Union implemented the Water
Framework Directive, which aims to assure the good
ecological status of all water bodies (A
2000). Since agriculture is an important source of
nonpoint source water pollution, it may be neces-
sary to adopt agricultural practices which minimize
the release of pollutants to meet societal goals and
satisfy government regulations (B et al.
2010). For the greenhouse industry, this means that
irrigation management will become increasingly
important, since excessive irrigation results in low
water use efficiency, leaching, and runoff of water,
fertilizer, and other agrochemicals.
Irrigation management using timers or the visual
assessment of plants and substrate is generally in-
efficient (N et al. 2007). An alternative ap-
proach is to monitor the water status of the soil
or substrate and make objective irrigation deci-
sions based on real-time measurements (J
2007). Soilless substrates generally hold most of
the water in a matric potential range from –1 to
–10 kPa, with matric potentials of –1 to –5 kPa
accounting for easily available water (EAW) and
water occurring between –5 and –10 kPa be-
ing considered “water buffering capacity” (WBC)
( B, V 1972; A 1998). Knowl-
edge of water availability in the growing media
can be used to determine appropriate thresholds
for automated irrigation. Still, little work has been
done to correlate the commonly defined EAW or
WBC with plant growth (A et al. 2010).
Irrigation has been automated using water ten-
sion measurements for decades (S, W
2011), but few growers currently do so, because
even ’’micro’’- tensiometers are bulky and require
frequent maintenance and refilling. Tensiometers
can easily become dislodged from the substrate,
breaking capillarity and leading to faulty readings
( I et al. 2013). Substrate volumetric wa-
ter content (Θ) has recently become a more feasible
parameter for determining substrate water status
and automating irrigation due to the development
of low-cost sensors (J 2007; N, 
I 2006). By using media-specific water re-
tention curves, it is possible to correlate substrate
Θ with matric potential, and use Θ to determine
thresholds for precision irrigation.
is study compares the effects of timer- and soil
moisture sensor-controlled irrigation on the water
use, yield and quality of lettuce grown in soilless
substrate. It also compares two different Θ thresh-
olds, which were determined based on the substrate
EAW. It was hypothesized that using Θ thresholds
to control irrigation would reduce water use, with-
out affecting lettuce yield and quality.
MATERIAL AND METHODS
Plant material and growing conditions. e
experiment was carried out in a greenhouse at the
experimental farm ‘‘La Noria’’ of the Institute of
Sciences of Food Production (CNR - ISPA) in Mola
di Bari (Southern Italy). Seedlings of Lactuca sativa
L. var. capitata cv. Mortarella d’Inverno (S.A.I.S.
Sementi, Cesena, Italy) were obtained from a com-
mercial nursery and transplanted into 5 l plastic
containers (one plant per container) filled with a
soilless substrate (peat-perlite, 1:1 v/v). e sub-
strate was saturated with water before transplant-
ing. Initial substrate solution electrical conductiv-
ity (EC) was 0.8 dS/m as measured with an in situ
EC sensor (WET sensor; Delta T Devices, Burwell,
U.K.). After transplanting, the seedlings were wa-
tered with a nutrient solution (NS) prepared with
pre-collected rain water and containing 8mM
N-NO3, 2mM N-NH4, 5.1mM K, 1.6mM P, 1.2mM
Mg, 2.5mM Ca, 2.8mM S, with micronutrients ap-
plied according to J et al. (1957). e NS
had an EC of 1.5 dS/m and a pH of 6.0. All plants
were well-watered using the NS for 8 days after
transplanting (DAT) to allow the seedlings to es-
tablish. e experiment was terminated at 50 DAT,
when plants reached the commercial size typical
for the cultivar. Mean temperature and relative
humidity inside the greenhouse were 15.6°C and
84.7%, respectively. e mean daily light integral
was 7.84 mol/m2/d during the experiment.
Determination of substrate EAW and irriga-
tion thresholds. Substrate volumetric water con-
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doi: 10.17221/312/2014-HORTSCI
tent at –5 kPa (water potential limit for EAW) was
measured using a sand-box (Eijkelkamp Agrisearch
Equipment, Giesbeek, e Netherlands) in accord-
ance with the European Standards EN 13041:1999
(Soil improvers and growing media – Determina-
tion of physical properties – Dry bulk density, air
volume, shrinkage value and total pore space). e
substrate was equilibrated in water, transferred into
tubes made of two overlapping PVC rings (100 ±
1mm diameter and 50 ± 1 mm height each), and
saturated with water for 48 hours. e PVC tubes
with substrate were then moved to the sandbox and
kept at a pressure of –5 kPa at room temperature
until they reached a constant weight. e PVC rings
were removed from the sandbox and separated, af-
ter which the substrate from the lower rings was
weighed and dried at 105°C to a constant weight.
Based on these measurements, it was determined
that the Θ value limit of the EAW was 0.38 m3/m3
for this substrate. Two irrigation thresholds were
chosen accordingly in order to control substrate
Θ at slightly above (0.40 m3/m3) and well below
(0.30m3/m3) the EAW limit.
Treatments and experimental design. e
treatments were: (i) timer-controlled irrigation
(‘Timer’); (ii) irrigation controlled with soil mois-
ture sensors with a Θ thresholds of 0.40 m3/m3
(above the threshold for EAW) (‘Θ = 0.4’), and (iii)
irrigation controlled with soil moisture sensors
with a Θ threshold of 0.30 m3/m3 (value lower than
the EAW limit) (‘Θ = 0.3’). Plants were arranged
in a randomized complete block design with three
replications. e experimental unit was a set of two
plants and containers (subsamples), with one of the
two used to monitor Θ and control irrigation, for a
total of 18 plants used in this experiment (3 treat-
ments × 3 replications × 2 subsamples).
e control system used to irrigate based on Θ
thresholds was similar to that described by N-
 and  I (2006). EC-5 sensors were
used rather than EC-10 sensors (Decagon De-
vices, Pullman, USA), because EC-5 sensors are
less sensitive to substrate electrical conductivity
(EC) and temperature (N et al. 2007). One
sensor was inserted at a ≈ 45° angle into the sub-
strate in each of the 9 measured containers. Sensor
voltage output was measured every 20 min using
a CR1000 datalogger (Campbell Scientific, Logan,
USA) which converted voltage measurements to
Θ using a substrate-specific calibration equation
(Θ = voltage × 3.3007 – 0.2555, r2 = 0.99, 2,500mV
sensor excitation voltage). Each replication of the
‘Θ = 0.3’ and ‘Θ = 0.4’ treatments had a dedicat-
ed pump (Shott 12.10/1400; Shott International,
Cittadella, Italy) and EC-5 sensor. Whenever the
measured Θ dropped below the threshold value
(0.30 or 0.40m3/m3), the datalogger sent a signal to
a relay driver (SDM16AC/DC controller; Campbell
Scientific, Logan, USA) which turned on the pump
to irrigate the 2 containers for 3 minutes. Wa-
ter was allowed to equilibrate in the substrate for
17min before the next measurement and potential
irrigation event. Pumps were submerged in a 500 l
tank filled with NS, and delivered 30 ml/min (90 ml
of NS/irrigation event) to each container through
two pressure-compensated emitters. In the ‘Timer’
treatment, Θ was measured but not used for irriga-
tion control. ese plants were irrigated once daily
(90 ml NS) for 26 DAT and twice a day (180 ml NS)
thereafter using a single submerged pump for the
3replications. is irrigation frequency maintained
a leaching fraction of approximately 20%. Leachate
from each container in all treatments was collected
in buckets, and the volume was measured weekly.
Measurements, calculations and statistical
analysis. e data logger stored the Θ readings from
all sensors every 20 min, the average of the sensor
readings for each measured container every hour,
and the daily number of irrigation events for each
replication of the sensor-controlled treatments.
Daily and total irrigation volumes were calculated
based on the number of irrigations recorded and
the known volume per irrigation event. Leaf chlo-
rophyll content was measured non-destructively us-
ing a handheld leaf chlorophyll meter (SPAD-502;
Minolta, Ramsey, USA) at 42 DAT. Measurements
were taken on ten well-expanded young leaves per
plant, and the averages were recorded for each plant.
Leaf net CO2 assimilation rate (An), stomatal con-
ductance to water vapour (gsw) and transpiration (T)
were measured at 40 DAT using a portable photo-
synthesis system (LI-6400; LI-COR Biosciences,
Lincoln, USA) which provided a photosynthetic
photon flux (PPF) of 1,000 µmol/m2s and a CO2
concentration of 400 µmol/mol. Measured leaves
were allowed to adjust to the measurement condi-
tions for at least 20 min before the values were re-
corded. Plants were harvested, and substrate EC in
each container was measured using a WET sensor
at 50 DAT. e number of leaves was recorded and
the shoot fresh weight of each plant was determined.
Total leaf area was measured using a leaf area me-
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Hort. Sci. (Prague) Vol. 43, 2016 (2): 67–75
doi: 10.17221/312/2014-HORTSCI
ter (Li-3100; LI-COR Biosciences, Lincoln, USA).
e leaves and stems of each plant were dried in a
thermo-ventilated oven at 65°C until they reached a
constant weight. Percent dry matter was calculated
as [(dry weight/fresh weight) × 100]. Water use ef-
ficiency (WUE) was calculated as a function of the
applied irrigation water (WUEa = total dry weight
of shoots/irrigation volume applied) and irrigation
water without leaching [WUEr = total dry weight of
shoots/(irrigation volume applied – leachate)]. In-
stantaneous WUE (WUEi) was calculated from the
leaf gas exchange measurements (WUEi = An/T).
Dried leaves were finely ground through a mill
(IKA; Labortechnik, Staufen, Germany) with a
1.0 mm sieve. Leaf nutrient concentrations were
determined using ion chromatography (Dionex
DX120; Dionex Corporation, Sunnyvale, USA)
and a conductivity detector with the IonPackAG14
pre-column and the IonPack AS14 separation col-
umn for anions, and IonPack CG12A pre-column
and IonPack CS12A separation column for cati-
ons. Inorganic anions were measured using 0.5 g of
ground leaf tissue with 50 ml solution containing
3.5mM sodium-carbonate and 1.0mM sodium-bi-
carbonate. Inorganic cations were measured using
1 g of ground leaf tissue, ashed in a muffle furnace
at 550°C and digested with 20 ml 1M HCl in boiling
water for 30 min (E et al. 1996).
Data were subjected to ANOVA using the general
linear model procedure (SAS Institute, Cary, USA);
means were separated by LSD test with P ≤ 0.05
considered to be statistically significant.
RESULTS AND DISCUSSION
Substrate water content, irrigation volume
and water use efficiency, substrate EC
Substrate Θ was different in the three treatments. In
the ‘Timer’ treatment, Θ was higher than 0.45 m3/m3
for the most of the growing cycle and dropped
below this value only during the last part of the
cycle (Fig. 1). e sensor-controlled system gen-
erally maintained Θ close to the irrigation thresh-
olds despite increases in plant size. e average Θ
measured by sensors was 0.461 ± 0.011, 0.412 ±
0.007 and 0.320 ± 0.009 m3/m3 (mean ± sd) in the
‘Timer’, ‘‘Θ = 0.4’’ and ‘‘Θ = 0.3’’ treatments, respec-
tively (for the two sensor controlled treatments, the
reported Θ values are calculated starting from the
beginning of irrigation controlled by the automat-
ed system, after Θ dropped for the first time below
the respective irrigation threshold). e ‘Θ = 0.3’
treatment resulted in greater Θ fluctuations than
did the ‘Θ = 0.4’ treatment (Fig. 1). is is consist-
ent with previous findings (N,  I
2006;  I et al. 2010) and may be because
the hydraulic conductivity of peat-based substrates
decreases at lower water contents (N et al.
2005), resulting in slower water movement, less
uniform water distribution, and increased Θ vari-
ability. It took an average of 9 d for the substrate
of the ‘Θ = 0.4’ treatments to reach the irrigation
threshold (0.40m3/m3) and 23 days for the ‘Θ = 0.3’
treatments to reach the 0.30 m3/m3 threshold.
e most irrigation water was applied in the ‘Tim-
er’ treatment, with 17% less NS used in the ‘Θ = 0.4’
treatment, and 42% less in the ‘Θ = 0.3’ treatment
(Table 1). Approximately 18% of applied NS leached
out from the containers when the timer was used
for irrigation control, while little or no leaching
occurred in the sensor-controlled treatments (Ta-
ble1). Irrigation volumes fluctuated daily in the sen-
sor-controlled treatments due to variability in plant
water consumption and the corresponding changes
in the rate of substrate water depletion (Fig.2). Sen-
sor-controlled irrigation reduces the amount of NS
applied and effectively eliminates leaching. Using Θ
to automate irrigation ensures that NS is provided to
the plant only when water is lost from the substrate
due to plant consumption or evaporation. Limit-
ing the duration and volume of irrigation events
based on container size and substrate water reten-
Fig. 1. Average volumetric water content (Θ) readings
of soil moisture sensors in pots irrigated with a timer or
with an automatic irrigation system based on Θ threshold
(0.30 for ‘Θ = 0.3’ and 0.40 m3/m3 for ‘Θ = 0.4’) measured
by substrate moisture sensors
0.25
0.30
0.35
0.40
0.45
0.50
0.55
10 20 30 40 50
Θ(m3/m3)
Days after transplant
Timer Θ = 0.4 Θ = 0.3
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doi: 10.17221/312/2014-HORTSCI
tion properties maximizes the efficiency of sensor-
controlled irrigation systems. Leaching from soilless
substrates can generally be minimized by reducing
the duration of each irrigation event, thereby ap-
plying less water at one time (Y et al. 1997;
B,  I 2008). In our experiment, the
leaching fraction in the ‘Timer’ treatment was lower
than is typical for soilless production systems, since
it is common in substrate systems to apply 30–50%
more water than is used by the crop (K
2001), suggesting that the water saving obtained us-
ing moisture sensors could even be higher in com-
mercial growing conditions.
Water use efficiency calculated based on the ap-
plied irrigation water is a measure of whole system
(irrigation and cultivation system combined) ef-
ficiency, which takes into account both the actual
plant water use and the water lost through leach-
ing. In the ‘Timer’ treatment, WUEa was the low-
est because of the large volume of NS that was ap-
plied, and WUEa was the highest in the ‘Θ = 0.3’
treatment, which used the least NS (Table 1). e
substantial leaching that generally occurs with tim-
er-based irrigation decreases its WUEa. Reducing
leaching during production by growing plants at
the optimal substrate water content and growing
species with high water-use efficiency have been
recognized as crucial approaches to efficient wa-
ter use (N,  I 2008). e water use
efficiency of the plants can be estimated from the
biomass and the amount of NS that was retained
by the substrate (i.e., NS applied – leached). e
‘Θ = 0.3’ treatment resulted in the highest WUEr,
and there was no difference in WUEr between the
‘Timer’ and ‘Θ = 0.4’ treatments (Table 1).
However, when calculating water use efficiency,
it is also important to account for the change in the
amount of water present in the substrate over the
course of the growing cycle. e Θ did not change
much in the ‘Timer’ and ‘Θ = 0.4’ treatments, but
decreased from 0.48 to 0.30 m3/m3 (approximately
900 ml/container) in the ‘Θ = 0.3’ treatment. Tak-
ing into account this additional amount of water
used by the plants in the ‘Θ=0.3’ treatment reduces
the WUEr to approximately 3.1 g/l, similar to that
in the other treatments.
Table 1. Applied nutrient solution (NS), volume of leachate, water use efficiency (WUE), and substrate electrical
conductivity (EC) in soilless cultivation of lettuce where irrigation management was performed with a timer or with
an automatic irrigation system based on Θ threshold (0.30 for ‘Θ = 0.3’ and 0.40 m3/m3 for ‘Θ = 0.4’) measured by
substrate moisture sensors
Treatment Applied NS (ml/plant) Leachate (ml/plant) WUEa
2 (g/l) WUEr
3 (g/l) Substrate EC (dS/m)
Timer 5,310a 933a2.36c2.86b1.1b
Θ = 0.4 4,410b 59b2.95b2.99b1.1b
Θ = 0.3 3,060c 0b4.02a4.02a1.4a
Significance1*** *** *** ** ***
1mean separation within columns by LSD0.05; **, *** – significant at P ≤ 0.01 and P ≤ 0.001, respectively; 2calculated as a
function of the applied irrigation water; 3calculated as a function of the irrigation water retained in the substrate; within
columns, values followed by the same letters are not significantly different
Fig. 2. Daily irrigation volume
for lettuce plants irrigated with
a timer or with an automatic
irrigation system based on Θ
threshold (0.30 for ‘Θ=0.3’ and
0.40 m3/m3 for ‘Θ=0.4’) meas-
ured by substrate moisture
sensors
0.25
0.30
0.35
0.40
0.45
0.50
0.55
10 20 30 40 50
Θ(m3/m3)
Days after transplant
Timer Θ = 0.4 Θ = 0.3
0
50
100
150
200
250
300
350
400
515253
54
5
Daily irrigation volume
(ml/plant)
Days after transplant
Timer Θ=0.4 Θ=0.3
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doi: 10.17221/312/2014-HORTSCI
Electrical conductivity was slightly higher in the
‘Θ = 0.3’ treatment (Table 1), likely because of the
absence of leaching and accumulation of fertilizer
salts. Similar results were observed by B
and  I (2008). High substrate EC may
negatively affect plant growth by imposing osmotic
stress. is is a potential problem that should be
taken into account when using sensor-controlled
irrigation, especially with salt-sensitive species or
low quality (high EC) irrigation water.
Plant growth, photosynthetic activity
and tissue analysis
At the end of the growing cycle, plants had a
similar number of leaves in all treatments, but the
plants irrigated at the lowest Θ showed, on aver-
age, a 11.7% decrease in leaf area (Table 2). Plants
in the ‘Timer’ and ‘Θ = 0.4’ treatments had higher
fresh weights (24%) than plants irrigated at the
lowest Θ threshold (Table 2). No differences in dry
weight were observed among treatments. us, the
irrigation treatments had little or no effect on bio-
mass production, and differences in fresh weight
resulted from differences in plant water content.
Percent dry matter was 20% higher in the ‘Θ = 0.3’
treatment than in the treatments with higher fresh
weights. In minimally-processed greens, a high
dry matter percentage is desirable because low dry
matter content can decrease shelf life (M
et al. 2011). Our results suggest that precision irri-
gation can be used to increase dry matter content,
thereby improving the quality of lettuce in soilless
cultivation. e ‘Θ = 0.3’ plants irrigated at the low-
est Θ, showed, on average, an 11.7% decrease in leaf
area (Table 2). Reduced water availability leads to
decreased leaf size because even mild drought can
reduce the turgor needed for cell expansion during
leaf development (B 1970). Water availability
in soilless substrates is reduced rapidly when Θ ap-
proaches a substrate-specific threshold (W
2008) and the ‘Θ = 0.3’ treatment apparently im-
posed enough of drought stress to reduce leaf elon-
gation. e reduced leaf area in this experiment
was consistent with the lower tissue water con-
tent observed in the ‘Θ = 0.3’ treatment, in which
Θ was maintained below the generally recognized
limit for EAW in soilless substrates ( B,
V 1972; A 1998). However, no visual
symptoms of water stress were observed in any of
the plants, indicating that the drought stress in the
Θ=0.3’ treatment was not severe. is was consist-
ent with the lack of an effect on shoot biomass.
Leaf chlorophyll content, net CO2 assimilation
rate, stomatal conductance and leaf transpiration
were similar in all treatments (Table 3). Since gas
exchange parameters were similar, WUEi was also
similar for all treatments. However, WUEa was
higher in the sensor-controlled treatments (Table
1). Leaf gas exchange measurements are limited to
a particular leaf and specific time, and may not ac-
curately represent long-term or whole-plant pro-
cesses. When calculated using leaf gas exchange
measurements, WUE is not always consistent with
the final WUE based on biomass and yield (G
et al. 2012; T et al. 2012; W et al. 2013).
In this study, it was demonstrated that, although
WUEi was unaffected, the overall water use effi-
ciency (WUEa) of an irrigation system can be im-
proved by adopting sensor-control.
Leaf tissue chemical composition was not affect-
ed by the treatments, with the exception of nitrate
concentration, which was lowest in the ‘‘Θ = 0.3’
treatment (Table 4). is may be because less NS,
and thus less nitrate, was applied in the ‘Θ = 0.3’
Table 2. Leaf area and number, total fresh and dry weight, and total dry matter of lettuce plants grown in soilless
conditions and with irrigation management performed with a timer or with an automatic irrigation system based on
Θ threshold (0.30 m3/m3 for ‘Θ = 0.3’ and 0.40 m3/m3 for ‘Θ = 0.4’) measured by substrate moisture sensors
Treatment Leaf area
(cm2/plant)
Leaf number
per plant
Total fresh weight
(g/plant)
Total dry weight
(g/plant)
Dry matter
(%)
Timer 3,914a36 273.3a12.5 4.58b
Θ = 0.4 3,889a33 267.0a13.0 4.87b
Θ = 0.3 3,446b33 217.1b12.3 5.67a
Significance1*ns *ns **
1mean separation within columns by LSD0.05; ns, *, ** – non-significant or significant at P ≤ 0.05 and
P ≤ 0.01, respectively; within columns, values followed by the same letters are not significantly different
72
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doi: 10.17221/312/2014-HORTSCI
treatment (Table 1). Moreover, a strong negative
correlation between nitrate and dry matter content
has been demonstrated in butterhead lettuce culti-
vars (R et al. 1987), similar to our findings.
is relationship between nitrate and dry matter
content is explained by the fact that a high dry mat-
ter content is normally associated with high organic
solutes in the cell vacuole (R, B-Z-
 1989), thus reducing the plant accumulation
of nitrates to compensate for a lower concentration
of organic solutes (R 1993). However, none
of the plants showed any visual symptom of nitro-
gen deficiency and leaf chlorophyll readings were
similar in all treatments, suggesting that nutritional
needs were met in all treatments. High nitrate con-
centrations in leafy greens can be a health hazard,
and in some cases (i.e., European countries), regu-
lations limit the acceptable nitrate concentration
of vegetables. Precision irrigation could be used
to improve lettuce quality by reducing leaf nitrate
concentrations.
Potential economic impact
Sensor-controlled irrigation can have a positive
economic impact on greenhouses through a variety
of ways: reducing water cost, less energy required to
pump water, labour savings resulting from automa-
tion, improved crop quality and/or shorter produc-
tion cycles. Some of these potential benefits will differ
based on locations, since the cost of water, energy, and
labour varies. In one case study in the South-eastern
United States, it was shown that precision irrigation
using wireless sensor networks increased annualized
profits of the production of Gardenia jasminoides
by 156% (L et al. 2013). is increase
in profits resulted largely from better growth and a
shorter production cycle, and to a lesser extent from a
reduction in plants lost due to damage by root patho-
gens. No similar economic analysis has yet been con-
ducted for lettuce production.
A survey of US greenhouse and nursery growers
showed widespread interest in adoption of wireless
sensor networks for sensor-controlled irrigation.
L et al. (2015) suggested that the ini-
tial adoption rate of wireless sensor networks may
be high, based on the expected cost of such sys-
tems and the growers’ willingness to pay for them.
Whether this holds true in other parts of the world
is not yet clear.
In conclusion, sensor-controlled irrigation with
a set-point above the EAW limit (‘Θ = 0.4’ treat-
ment) had similar plant fresh weight and quality
as timer-controlled irrigation, but used less irriga-
tion volume. Maintaining a substrate moisture lev-
Table 3. Chlorophyll content, net CO2 assimilation rate (An), stomatal conductance to water vapour (gsw), leaf tran-
spiration (T) and instantaneous water use efficiency (An/T, WUEi) of lettuce plants grown in soilless conditions and
with irrigation management performed with a timer or with an automatic irrigation system based on Θ threshold
(0.30 m3/m3 for ‘Θ = 0.3’ and 0.40 m3/m3 for ‘Θ = 0.4’) measured by substrate moisture sensors
Treatment Chlorophyll content
(SPAD units)
An
(µmol/m2s)
gsw
(mol/m2s)
T
(mmol/m2s)
WUEi
(µmol/mmol)
Timer 33.9 18.8 0.94 4.74 3.98
Θ = 0.4 33.6 18.8 0.81 4.80 3.94
Θ = 0.3 34.5 19.4 0.78 4.46 4.40
Significance1ns ns ns ns ns
1mean separation within columns by LSD0.05; ns – non-significant
Table 4. NO3, K, Mg and Ca content (g/kg dry weight) in
leaf tissues of lettuce plants grown in soilless conditions
and with irrigation management performed with a timer
or with an automatic irrigation system based on Θ thresh-
old (0.30 for ‘Θ = 0.3’ and 0.40 m3/m3 for ‘Θ = 0.4’) meas-
ured by substrate moisture sensors
Treatment NO3KMg Ca
Timer 55.0a89.2 5.6 13.4
Θ = 0.4 49.5a90.9 5.1 11.0
Θ = 0.3 33.4b74.8 5.7 13.7
Significance1*** ns ns ns
1mean separation within columns by LSD0.05; ns, *** – non-
significant and significant at P ≤ 0.001, respectively; within
columns, values followed by the same letters are not sig-
nificantly different
73
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doi: 10.17221/312/2014-HORTSCI
el slightly below the conventionally defined EAW
(‘Θ = 0.3’ treatment) range reduced the water con-
tent and nitrate concentration of lettuce grown in
soilless substrate but did not reduce overall biomass
production. Sensor-controlled irrigation resulted
in higher overall water and nutrient use efficiency
than timer-controlled irrigation. Precision irrigation
based on Θ measurements eliminated leaching while
improving the quality of soilless-grown lettuce.
Acknowledgement
We thank Gerolmina Florio and Nicola Gentile
for their technical assistance and Geoffrey Weaver
for editing this manuscript.
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Received for publication November 19, 2014
Accepted after corrections September 7, 2015
Corresponding author:
Dr. A P, Institute of Sciences of Food Production, National Research Council, Via G. Amendola, 122/O,
70126 Bari, Italy; e-mail: angelo.parente@ispa.cnr.it
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doi: 10.17221/312/2014-HORTSCI
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