Directory UMM :Data Elmu:jurnal:A:Agricultural Water Management:Vol45.Issue2.Jul2000:
Agricultural Water Management 45 (2000) 145±157
Irrigation automation based on soil electrical
conductivity and leaf temperature
Noble Abraham*, P.S. Hema, E.K. Saritha,
Shinoj Subramannian
Kelappaji College of Agricultural Egnineering and Technology,
Kerala Agricultural University, Tavanur, Malappuram, Kerala 679573, India
Accepted 21 September 1999
Abstract
Two automated drip irrigation systems: one based on soil electrical conductivity and the other
based on leaf±air temperature differential were developed and tested for Okra (Abelmoschus
esculentus). Different sensors were evaluated for monitoring the soil moisture content based on
electrical resistance variation with moisture content. The sensor with washed sand as porous
medium was found to be the most ef®cient one for the study area. A low cost, commercially
available button type thermistor was used as the leaf and air temperature sensors. The amount of
water applied per day, leaf±air temperature and soil moisture content were monitored during the
study period. The systems maintained the designed soil moisture content and air±leaf temperature
differential through out the study period. # 2000 Elsevier Science B.V. All rights reserved.
Keywords: Irrigation automation; Moisture sensor; Leaf±air temperature differential
1. Introduction
Where rainfall is inadequate, farmers have always sought ways to supply crops with
the water necessary for its development. The recent irrigation techniques introduce
automated irrigation using sophisticated equipments to supply water to the plant as soon
as they need it. Automated irrigation systems can increase crop yields, save water usage,
energy and labour costs as compared with manual systems (Mulas, 1986). Automated
irrigation has a number of advantages including greater precision, more efficient use of
water and reduction in human error (Castanon, 1992). It is very useful, particularly in
*
Corresponding author. Tel.: 91-494686090.
0378-3774/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved.
PII: S 0 3 7 8 - 3 7 7 4 ( 9 9 ) 0 0 0 7 8 - 5
146
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
humid areas where unpredictable and unevenly distributed summer rainfall disrupts fixed
irrigation schedules. Automated irrigation system also facilitates high frequency and low
volume irrigation.
Automatic irrigation systems presently available are costly and are not adopted by most
of the Indian farmers. Therefore, appropriate low cost technology has to be developed to
facilitate high water use efficiency. A study was therefore conducted to evaluate the soil
electrical conductivity and leaf±air temperature differential as indicators for irrigation
automation. Relationships between soil moisture content and electrical resistance, and
soil moisture content and leaf±air temperature differential were established. Based on
these observations, two automated irrigation systems: one with soil electrical conductivity
and the other with leaf±air temperature as indicators for irrigation automation were
developed. Testing and performance evaluations of these automated systems were
conducted.
For irrigation scheduling, there is always a need for reliable methods for measuring soil
and plant water status. The most important and basic component of a measurement
system is the sensor. The efficiency of various management decisions depends on
accurate measurements, which in turn depends on the accuracy of the sensor.
Shull and Dylla (1980) suggested the use of gypsum resistance blocks as soil moisture
sensor. On larger fields for extending the soil moisture sensing area, a network of gypsum
resistance blocks was made by connecting them in series and in parallel with a resistance
range the same as that provided by one block. Usually in border irrigation automation, the
pneumatic sensors are being superseded by electronic water sensors due to the blocking
of air transmission line by debris. Alharthi and Lanje (1987) suggested a method of
assessing the water saturation by the measurements of composite dielectric constant.
Tension measurements by tensiometers are generally limited to matric suction values of
below one atmosphere. They do not satisfactorily measure the entire range of available
moisture in all soil types. (Michael, 1995). The resistance based sensors are simple and
the signal output can be directly fed to the control systems.
Cuming (1990) developed an irrigation control system, which includes a soil moisture
sensor that controls the common lines of various irrigation systems. A timer is activated
whenever the soil moisture sensor placed in the root zone allows it to be watered.
Frankovitch and Sarich (1991) developed an automatic plant watering system consisted
of an electronic switching system that controls pumping time. The flow rate of water is
controlled by a valve system.
Plant temperature may be a valuable qualitative index of water availability (Tanner,
1963 and Gates, 1964). The status of water in the plant represents an integration of the
atmospheric demand, soil water potential, rooting density and distribution as well as other
plant characteristics (Kramer, 1969). Therefore, to obtain a true measure of the plant
water deficit, the measurement should be made on the plant and not on the soil or
atmosphere. Clark and Hiler (1973) correlated the leaf±air temperature differential with
crop water deficit. They found that in almost every case the leaves were cooler than the
air above the canopy, when the crop was well watered. Once a water deficit occurred in
the stressed treatment, leaf±air temperature differential became positive and the leaf was
usually 2±38C warmer than that in the non-stressed treatment. Jackson et al. (1977)
reported that water stress causes partial stomatal closure, thus, reducing transpiration and
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
147
allowing sunlit leaves to warm above ambient air temperature. Irrigation scheduling
based on the canopy air temperature differential has been suggested by Walker and
Hatfield (1979). Jackson (1982) found that an ideal irrigation scheduling technique
should use the plant as the indicator of water stress, since the plant response to both the
aerial and soil environments. The use of canopy temperature to detect water stress is
based on the principle that water lost through transpiration cools the leaves below the
temperature of the surrounding air under well-watered conditions. Throssell et al. (1987)
reported that the plant canopyambient air temperature difference is a good indicator of the
water status of a plant. According to Kadam and Magan (1994), the canopy air
temperature difference is related to leaf water potential. Also, Bhosale et al. (1996)
reported that the canopy air temperature differential is a good indicator of water status of
the plants.
Different types of sensors are used for measuring canopy temperature. Ehrler (1973)
used thermocouple embedded in cotton leaves to determine leaf temperatures. Saha
(1984) used infrared radiation thermometer for measuring canopy temperature for
monitoring plant stress from aircraft. Ahmed and Misra (1990) described the method of
measuring leaf temperature with thermocouple.
Jackson et al. (1977) suggested the possibility of development of a totally automated
irrigation system in which instruments monitor the canopy temperature of plants for signs
of water stress and signal devices that automatically provide required amounts of
irrigation water. Wanjura et al. (1995) developed an automated drip irrigation system
based on threshold canopy temperature. Irrigation was applied only when average canopy
temperature exceeded pre-determined threshold values. The length of irrigation cycles
was shortest and amount per irrigation event was highest for all threshold temperatures
during the early growth stage as canopies were small, and warm bare soil contributed to
measured canopy temperature.
The experiments conducted and materials used in this study are described below.
2. Materials and methods
The experiment was conducted at Malappuram district of Kerala, India, situated at
108520 3000 North Latitude and 768 East Longitude. The soil at the site was sandy loam.
Two experimental plots (Plot 1 and Plot 2) were selected, each with an area of 2 m 2 m.
The crop planted was Okra (Abelmoschus esculentus) of variety Arca Anamika for which
one of the main planting season is February±March. It has an excellent rooting pattern
and good canopy, with moderately strong and thick leaves. The automated irrigation
system based on electrical conductivity of soil was installed in Plot 1 and the other system
based on leaf±air temperature differential was installed in Plot 2. The system consisted of
sensors, controller and solenoid valve to regulate the irrigation input. The layout of the
plot is shown in Fig. 1.
The soil moisture sensor used for the study consisted of two rectangular electrodes
with a porous medium in between. The soil moisture content was sensed by measuring
the resistance between the electrodes, which is a function of soil moisture content. To find
the suitability of porous medium, five soil moisture sensors with different porous medium
148
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
Fig. 1. Layout of experiment setup.
in between electrode plates were evaluated. Among the five sensors, four of them had
brass plate of size 30 mm 25 mm as electrodes with a gap of 10 mm between them.
Brass was selected as electrode after comparing the performance of stainless steel, copper
and brass. The porous media used were soil at the site, washed sand, sponge and nylon for
first, second, third and fourth sensors, respectively. A gypsum block was the fifth sensor
used for evaluation. All the five sensors were embedded in the soil at a depth of 50 mm
and the soil was irrigated to saturation. The soil moisture content and corresponding soil
electrical resistance were then monitored till a nearly constant moisture content was
reached. Four trials were done leaving a gap of 4 days. The selection of appropriate
sensor was made on the basis of the uniformity of soil moisture content electrical
resistance relationship in all the four trials. The resistance corresponding to the field
capacity of soil was also determined.
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
149
Fig. 2. Switching circuit for the automation system based on soil electrical conductivity.
The relationship of leaf±air temperature differential with soil moisture content was
established and was accepted as an indicator for irrigation scheduling. In order to sense
the leaf and air temperature and for converting it into a signal acceptable to the switching
circuit, a commercially available button type thermistor was used. Thermistors are
extremely delicate components whose effective surface area in contact with the leaf is
very small. For easy and quick flow of heat, thermistor was attached in between the leaf
and an aluminium foil of 20 mm 10 mm size. In order to revent the effect of direct solar
radiation, the sensor was placed on the underside of the leaf. Small holes were provided on
the aluminium foil in order to aid smooth transpiration. A similar button type thermistor was
used as air temperature sensor, which was hung freely within the microclimate of the plant.
The circuit used for automation based on electrical conductivity of soil is shown in
Fig. 2. The electrode for sensing the soil moisture was placed at a depth of 50 mm from
the surface within the root zone of a plant at the centre of the plot. Variation of moisture
in soil causes variation in electrical resistance across the electrode of the sensor. The
electrical signal obtained by variation in electrical resistance is processed by the circuit
and operates the relay contacts connected to a 12 V dc operated normally closed solenoid
valve. When the soil gets dry and its resistivity increases, the circuit open the valve and
water flows to the plants. As water content in soil reaches the required level set by the
variable resister VR1, the solenoid valve is closed. A 9 V dc supply powers the circuit.
The field capacity of the soil at the site was found to be 15%. The electrical resistance
corresponding to this moisture content was 33 kO for the selected sensor. This resistance
was set in the switching circuit, so that, when moisture content decreased below field
capacity, the system switched on and when the field capacity of the soil was reached
during wetting up, it switched off. Thus, the moisture content was always maintained
around field capacity level. To prevent the vibration of the relay contacts at the switching
point, a time delay for switching on the circuit was given.
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N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
2.1. Automation based on leaf±air temperature differential
When the temperature of the leaf changes with the soil moisture content, the resistance
of the thermistor RTH1, (attached to the leaf) varies. Thermistor RTH1, along with the
variable resistance VR1, constitutes a potential divider across the supply, resulting in a
voltage at pin 2 of the Op-amp IC1 741. This voltage rises as the temperature decreases.
Thermistor RTH2, (exposed to atmosphere) along with the variable resistance VR2,
provides a reference voltage at pin 3 of IC1. When the voltage at pin 2 rises above that at
pin 3, IC1 switches on and voltage appears at the output pin 6. The temperature at which
this happens is pre-set by adjusting variable resistances VR1 and VR2. In order to make
the sensors more sensitive to temperature changes, thermistors having different resistance
values were used. When the required temperature differential set by VR1 and VR2 is
reached, the output from IC2 turns transistor T1 CL100 on, and thus, it drives the relay.
IC3, an NE555 is used to have a time delay for operating the relay even after the pre-set
temperature difference is reached. Otherwise, sudden fluctuations in the temperature of
either atmosphere or leaf due to wind may affect the operation of the system. Adjustment
of VR3 can vary the time delay, if needed.
The relay contacts were connected to a 230 V ac operated normally closed solenoid
valve whose input was connected to an overhead tank and output to the drip irrigation
system installed at the field. Thus, when the plant is stressed, the temperature of leaf
increases with respect to atmosphere, the valve is opened and water flows to the plants.
Then the plant leaves begin to cool and when the temperature reaches the pre-set value,
the valve stops the flow of water. The circuit was powered by 9 V dc supply. The
switching circuit used for automation based on leaf ±air temperature differential is shown
in Fig. 3.
Fig. 3. Switching circuit for the automation system based on leaf±air temperature.
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
151
In the humid climatic conditions of Kerala, Okra showed a leaf temperature around
48C below that of atmosphere under well watered conditions. It was found to be going
upto 68C in certain days. This differential became 08C at extremely dry conditions. When
the leaves stared drooping, an air±leaf temperature differential of 28C or less was
observed. So the control circuit was adjusted such that it keeps on at an air±leaf
temperature differential of 38C. The selection of this air±leaf temperature differential was
also based on the sensitivity of the sensor used in this study.
To evaluate the performance of the two automated systems, the soil moisture content
was measured from each automated plot, three times a day, i.e. at 8.30 am, 12.30 and
3.30 pm. At the same time, air temperature and leaf temperature were also measured from
the Plot 2. The amount of water applied was also noted using two water meters. Moisture
contents from the two plots were determined by the gravimetric method. The yield and
dry matter content obtained from each plot were determined.
3. Results and discussion
The measurement of resistance in the field using gypsum block showed that when the
polarity across the electrodes changed, the resistance readings had considerable
variations. The performance curves of gypsum block for the four replications are shown
in Fig. 4. The sensor having soil in the field itself as the porous medium showed the same
relationship between moisture content and electrical resistance in the first and second
trials. During the third trial, it showed a slight variation from the trend. The fourth trial
showed considerable variation. This may be due to the presence of chemicals in the soil.
The performance curves for four trials are shown in Fig. 5. For the sensors having sponge
Fig. 4. Performance of gypsum block.
152
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
Fig. 5. Performance of soil in the plot as porous medium.
and nylon as porous medium, four trials showed different trends in the relationship
between soil moisture content and electrical resistance. The variation may be due to the
moisture retention properties of these materials are different from that of the soil. The
performance curves for sponge and nylon are shown in Figs. 6 and 7, respectively. In all
the four replications, the sensor having washed sand as porous medium showed a constant
trend in the relationship between soil moisture content and electrical resistance. This is
Fig. 6. Performance of sponge as porous medium.
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
153
Fig. 7. Performance of nylon as porous medium.
due to washed sand is less susceptible to chemical changes and the soil moisture
properties of the washed sand are probably similar to that of field soil. The performance
curves for washed sand are shown in Fig. 8. Based on the above results, the sensor with
washed sand as porous medium was selected and used as the soil moisture sensor in the
present study.
Fig. 8. Performance of washed sand as porous medium.
154
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
Fig. 9. Soil moisture status in Plot 1 (automation based on soil electrical conductivity).
The system based on electrical conductivity was tested during the month of February±
April 1998. A plot of soil moisture content verses time for 12 days during the matured
stage of the crop is shown in Fig. 9. During the matured stage, maximum fluctuation in
soil moisture content of the root zone is expected due to increased evapotranspiration. It
can be seen that the moisture content was maintained nearly constant throughout the
period within the range 14±17%, that is around field capacity of the soil. On 9th day, a
moisture content of 19% is observed as the moisture content was happened to be taken
during the time of irrigation.
About 1 week after the installation of the sensor, some deposits were found to form on
the electrode plates that reduced the electrical conductivity between the electrode plates.
These deposits may be due to the polarisation of certain ions present in the soil. The same
trend was found immediately after the addition of fertilisers to the soil.
The system based on leaf±air temperature differential was also tested in the same
period. The soil moisture in this case was maintained between 10% and 13% throughout
the study period. The moisture content for 12 days during the matured stage of the crop is
shown in Fig. 10. Here upto a moisture content of 10%, the differential was less than 28C,
upto 14% moisture content, the differential was about 38C and beyond that it was above
48C. This shows that there is a distinct variation in leaf±air temperature differential
corresponding to soil moisture content for the crop Okra.
The system was found to maintain the pre-set value of leaf±air temperature differential
and the leaf temperature was maintained 38C below the atmospheric temperature. At this
level the moisture content was less than field capacity and the plant was subjected to
certain level of moisture stress. The relationship of soil moisture content with the leaf ±air
temperature differential is shown in Fig. 11. It shows that leaf±air temperature differential
has a direct relationship with soil moisture content.
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
155
Fig. 10. Soil moisture status in Plot 2 (automation based on leaf±air temperature differential).
The volume of water applied during this period as irrigation is shown in Fig. 12. It can
be seen that more amount of water was applied in the first plot where system based on
soil resistivity was installed and a higher moisture content was maintained. The yield and
the drymatter content was also more in the first plot. On days 3, 5, and 9, there was
rainfall and the irrigation applied was less. The performance of both the systems were
Fig. 11. Variation in leaf±air temperature differential with soil moisture content.
156
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
Fig. 12. Volume of irrigation during a 10-day period.
satisfactory and can be adopted for irrigation scheduling. The systems are simple and can
be easily maintained by farmers.
Application of fertilizer or chemical change, the resistance moisture content
relationship and therefore calibration of sensor is required after adding fertilizers or
chemicals. Such variations are not required for the system based on leaf±air temperature
differential. However, the sensor need to be changed to new leaves as the plant canopy
develops.
4. Conclusions
The sensor with brass plate as electrode and washed sand as porous medium showed
nearly a constant trend in the relationship between resistance and soil moisture content in
all trials.
The automated systems based on soil resistance was found to be working efficiently
without frequent supervision and maintained the pre-set moisture content in the root zone.
The automated system based on leaf±air temperature differential maintained the pre-set
leaf±air temperature differential throughout the study period.
References
Ahmed, M., Misra, R.D. (Eds.), 1990. Manual on Irrigation Agronomy. Oxford and IBH Publishing Co. Pvt.
Ltd., New Delhi, pp. 121±122, 272±282.
Alharthi, A., Lanje, J., 1987. Soil water saturation: dielectric determination. Water Resour. Res. 23 (4), 591±595.
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Bhosale, A.M., Jadhav, A.S., Bote, N.L., Varsheya, M.C., 1996. Canopy temperature as an indicator for
scheduling irrigation for wheat. J. Maharashtra Agric. Univ. 21 (1), 106±109.
Castanon, G., 1992. The automation irrigation. Maquinas of Tractors Agricolas 3 (2), 45±49.
Clark, R.N., Hiler, E.A., 1973. Plant measurements as indicators of crop water de®cit. Crop Sci. 13, 466±469.
Cuming, K.D., 1990. Irrigation control system, United States Patent US4, 934, 400, 5 pp.
Ehrler, William L., 1973. Cotton leaf temperatures as related to soil water depletion and meteorological factors.
Agron. J. 65, 404±409.
Frankovitch, D.J., Sarich, J.I., 1991. Automatic plant watering system, Canadian Patent application, 16 pp.
Gates, D.M., 1964. Leaf temperature and transpiration. Agron. J. 56, 273±277.
Jackson, R.D., 1982. Canopy Temperature and Crop Water Stress, Advances in Irrigation, vol. I, Academic
Press, New York.
Jackson, R.D., Reginato, R.J., Idso, B.B., 1977. Wheat canopy temperature: a practical tool for evaluating water
requirements. Water Resour. Res. 13 (3), 651±656.
Kadam, J.R., Magan, S.S., 1994. Irrigation scheduling with thermal infrared remote sensing inputs: a review. J.
Maharashtra Agric. Univ. 19 (2), 273±276.
Kramer, P.J. (Ed.), 1969. Plant and Soil Water Relationships. McGraw-Hill, New York.
Michael, A.M. (Ed.), 1995. Irrigation Theory and Practice. Vikas Publishing House Pvt. Ltd., NewDelhi,
pp. 490±501.
Mulas, P., 1986. Developments in the automation of irrigation. Colture Protelte 15 (6), 17±19.
Saha, S.K., 1984. Remote sensing of crop evapo transpiration using plant canopy temperature. Saha et al. (Eds.),
Proceedings of the Seminar on Growth Condition and Remote Sensing. IARI, New Delhi, India.
Shull, H., Dylla, A.S., 1980. Irrigation automation with a soil moisture sensing system, Trans. ASAE, Vol. 23
pp. 649±652.
Tanner, C.B., 1963. Plant temperatures. Agron. J. 55, 210±211.
Throssell, C.S., Carrow, R.N., Milliken, G.A., 1987. Canopy temperature based irrigation scheduling indices for
Kentucky Bluegrass Turf. Crop Sci. 22, 126±131.
Walker, G.K., Hat®eld, J.L., 1979. Test of the stress degree day concept using multiple planting dates of red
kidney beans. Agron. J. 71, 967±971.
Wanjura, D.F., Upchurch, D.R., Mahan, J.R., 1995. Control of irrigation scheduling using temperature±time
thresholds. Trans. ASAE 38 (2), 403±409.
Irrigation automation based on soil electrical
conductivity and leaf temperature
Noble Abraham*, P.S. Hema, E.K. Saritha,
Shinoj Subramannian
Kelappaji College of Agricultural Egnineering and Technology,
Kerala Agricultural University, Tavanur, Malappuram, Kerala 679573, India
Accepted 21 September 1999
Abstract
Two automated drip irrigation systems: one based on soil electrical conductivity and the other
based on leaf±air temperature differential were developed and tested for Okra (Abelmoschus
esculentus). Different sensors were evaluated for monitoring the soil moisture content based on
electrical resistance variation with moisture content. The sensor with washed sand as porous
medium was found to be the most ef®cient one for the study area. A low cost, commercially
available button type thermistor was used as the leaf and air temperature sensors. The amount of
water applied per day, leaf±air temperature and soil moisture content were monitored during the
study period. The systems maintained the designed soil moisture content and air±leaf temperature
differential through out the study period. # 2000 Elsevier Science B.V. All rights reserved.
Keywords: Irrigation automation; Moisture sensor; Leaf±air temperature differential
1. Introduction
Where rainfall is inadequate, farmers have always sought ways to supply crops with
the water necessary for its development. The recent irrigation techniques introduce
automated irrigation using sophisticated equipments to supply water to the plant as soon
as they need it. Automated irrigation systems can increase crop yields, save water usage,
energy and labour costs as compared with manual systems (Mulas, 1986). Automated
irrigation has a number of advantages including greater precision, more efficient use of
water and reduction in human error (Castanon, 1992). It is very useful, particularly in
*
Corresponding author. Tel.: 91-494686090.
0378-3774/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved.
PII: S 0 3 7 8 - 3 7 7 4 ( 9 9 ) 0 0 0 7 8 - 5
146
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
humid areas where unpredictable and unevenly distributed summer rainfall disrupts fixed
irrigation schedules. Automated irrigation system also facilitates high frequency and low
volume irrigation.
Automatic irrigation systems presently available are costly and are not adopted by most
of the Indian farmers. Therefore, appropriate low cost technology has to be developed to
facilitate high water use efficiency. A study was therefore conducted to evaluate the soil
electrical conductivity and leaf±air temperature differential as indicators for irrigation
automation. Relationships between soil moisture content and electrical resistance, and
soil moisture content and leaf±air temperature differential were established. Based on
these observations, two automated irrigation systems: one with soil electrical conductivity
and the other with leaf±air temperature as indicators for irrigation automation were
developed. Testing and performance evaluations of these automated systems were
conducted.
For irrigation scheduling, there is always a need for reliable methods for measuring soil
and plant water status. The most important and basic component of a measurement
system is the sensor. The efficiency of various management decisions depends on
accurate measurements, which in turn depends on the accuracy of the sensor.
Shull and Dylla (1980) suggested the use of gypsum resistance blocks as soil moisture
sensor. On larger fields for extending the soil moisture sensing area, a network of gypsum
resistance blocks was made by connecting them in series and in parallel with a resistance
range the same as that provided by one block. Usually in border irrigation automation, the
pneumatic sensors are being superseded by electronic water sensors due to the blocking
of air transmission line by debris. Alharthi and Lanje (1987) suggested a method of
assessing the water saturation by the measurements of composite dielectric constant.
Tension measurements by tensiometers are generally limited to matric suction values of
below one atmosphere. They do not satisfactorily measure the entire range of available
moisture in all soil types. (Michael, 1995). The resistance based sensors are simple and
the signal output can be directly fed to the control systems.
Cuming (1990) developed an irrigation control system, which includes a soil moisture
sensor that controls the common lines of various irrigation systems. A timer is activated
whenever the soil moisture sensor placed in the root zone allows it to be watered.
Frankovitch and Sarich (1991) developed an automatic plant watering system consisted
of an electronic switching system that controls pumping time. The flow rate of water is
controlled by a valve system.
Plant temperature may be a valuable qualitative index of water availability (Tanner,
1963 and Gates, 1964). The status of water in the plant represents an integration of the
atmospheric demand, soil water potential, rooting density and distribution as well as other
plant characteristics (Kramer, 1969). Therefore, to obtain a true measure of the plant
water deficit, the measurement should be made on the plant and not on the soil or
atmosphere. Clark and Hiler (1973) correlated the leaf±air temperature differential with
crop water deficit. They found that in almost every case the leaves were cooler than the
air above the canopy, when the crop was well watered. Once a water deficit occurred in
the stressed treatment, leaf±air temperature differential became positive and the leaf was
usually 2±38C warmer than that in the non-stressed treatment. Jackson et al. (1977)
reported that water stress causes partial stomatal closure, thus, reducing transpiration and
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
147
allowing sunlit leaves to warm above ambient air temperature. Irrigation scheduling
based on the canopy air temperature differential has been suggested by Walker and
Hatfield (1979). Jackson (1982) found that an ideal irrigation scheduling technique
should use the plant as the indicator of water stress, since the plant response to both the
aerial and soil environments. The use of canopy temperature to detect water stress is
based on the principle that water lost through transpiration cools the leaves below the
temperature of the surrounding air under well-watered conditions. Throssell et al. (1987)
reported that the plant canopyambient air temperature difference is a good indicator of the
water status of a plant. According to Kadam and Magan (1994), the canopy air
temperature difference is related to leaf water potential. Also, Bhosale et al. (1996)
reported that the canopy air temperature differential is a good indicator of water status of
the plants.
Different types of sensors are used for measuring canopy temperature. Ehrler (1973)
used thermocouple embedded in cotton leaves to determine leaf temperatures. Saha
(1984) used infrared radiation thermometer for measuring canopy temperature for
monitoring plant stress from aircraft. Ahmed and Misra (1990) described the method of
measuring leaf temperature with thermocouple.
Jackson et al. (1977) suggested the possibility of development of a totally automated
irrigation system in which instruments monitor the canopy temperature of plants for signs
of water stress and signal devices that automatically provide required amounts of
irrigation water. Wanjura et al. (1995) developed an automated drip irrigation system
based on threshold canopy temperature. Irrigation was applied only when average canopy
temperature exceeded pre-determined threshold values. The length of irrigation cycles
was shortest and amount per irrigation event was highest for all threshold temperatures
during the early growth stage as canopies were small, and warm bare soil contributed to
measured canopy temperature.
The experiments conducted and materials used in this study are described below.
2. Materials and methods
The experiment was conducted at Malappuram district of Kerala, India, situated at
108520 3000 North Latitude and 768 East Longitude. The soil at the site was sandy loam.
Two experimental plots (Plot 1 and Plot 2) were selected, each with an area of 2 m 2 m.
The crop planted was Okra (Abelmoschus esculentus) of variety Arca Anamika for which
one of the main planting season is February±March. It has an excellent rooting pattern
and good canopy, with moderately strong and thick leaves. The automated irrigation
system based on electrical conductivity of soil was installed in Plot 1 and the other system
based on leaf±air temperature differential was installed in Plot 2. The system consisted of
sensors, controller and solenoid valve to regulate the irrigation input. The layout of the
plot is shown in Fig. 1.
The soil moisture sensor used for the study consisted of two rectangular electrodes
with a porous medium in between. The soil moisture content was sensed by measuring
the resistance between the electrodes, which is a function of soil moisture content. To find
the suitability of porous medium, five soil moisture sensors with different porous medium
148
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
Fig. 1. Layout of experiment setup.
in between electrode plates were evaluated. Among the five sensors, four of them had
brass plate of size 30 mm 25 mm as electrodes with a gap of 10 mm between them.
Brass was selected as electrode after comparing the performance of stainless steel, copper
and brass. The porous media used were soil at the site, washed sand, sponge and nylon for
first, second, third and fourth sensors, respectively. A gypsum block was the fifth sensor
used for evaluation. All the five sensors were embedded in the soil at a depth of 50 mm
and the soil was irrigated to saturation. The soil moisture content and corresponding soil
electrical resistance were then monitored till a nearly constant moisture content was
reached. Four trials were done leaving a gap of 4 days. The selection of appropriate
sensor was made on the basis of the uniformity of soil moisture content electrical
resistance relationship in all the four trials. The resistance corresponding to the field
capacity of soil was also determined.
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
149
Fig. 2. Switching circuit for the automation system based on soil electrical conductivity.
The relationship of leaf±air temperature differential with soil moisture content was
established and was accepted as an indicator for irrigation scheduling. In order to sense
the leaf and air temperature and for converting it into a signal acceptable to the switching
circuit, a commercially available button type thermistor was used. Thermistors are
extremely delicate components whose effective surface area in contact with the leaf is
very small. For easy and quick flow of heat, thermistor was attached in between the leaf
and an aluminium foil of 20 mm 10 mm size. In order to revent the effect of direct solar
radiation, the sensor was placed on the underside of the leaf. Small holes were provided on
the aluminium foil in order to aid smooth transpiration. A similar button type thermistor was
used as air temperature sensor, which was hung freely within the microclimate of the plant.
The circuit used for automation based on electrical conductivity of soil is shown in
Fig. 2. The electrode for sensing the soil moisture was placed at a depth of 50 mm from
the surface within the root zone of a plant at the centre of the plot. Variation of moisture
in soil causes variation in electrical resistance across the electrode of the sensor. The
electrical signal obtained by variation in electrical resistance is processed by the circuit
and operates the relay contacts connected to a 12 V dc operated normally closed solenoid
valve. When the soil gets dry and its resistivity increases, the circuit open the valve and
water flows to the plants. As water content in soil reaches the required level set by the
variable resister VR1, the solenoid valve is closed. A 9 V dc supply powers the circuit.
The field capacity of the soil at the site was found to be 15%. The electrical resistance
corresponding to this moisture content was 33 kO for the selected sensor. This resistance
was set in the switching circuit, so that, when moisture content decreased below field
capacity, the system switched on and when the field capacity of the soil was reached
during wetting up, it switched off. Thus, the moisture content was always maintained
around field capacity level. To prevent the vibration of the relay contacts at the switching
point, a time delay for switching on the circuit was given.
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2.1. Automation based on leaf±air temperature differential
When the temperature of the leaf changes with the soil moisture content, the resistance
of the thermistor RTH1, (attached to the leaf) varies. Thermistor RTH1, along with the
variable resistance VR1, constitutes a potential divider across the supply, resulting in a
voltage at pin 2 of the Op-amp IC1 741. This voltage rises as the temperature decreases.
Thermistor RTH2, (exposed to atmosphere) along with the variable resistance VR2,
provides a reference voltage at pin 3 of IC1. When the voltage at pin 2 rises above that at
pin 3, IC1 switches on and voltage appears at the output pin 6. The temperature at which
this happens is pre-set by adjusting variable resistances VR1 and VR2. In order to make
the sensors more sensitive to temperature changes, thermistors having different resistance
values were used. When the required temperature differential set by VR1 and VR2 is
reached, the output from IC2 turns transistor T1 CL100 on, and thus, it drives the relay.
IC3, an NE555 is used to have a time delay for operating the relay even after the pre-set
temperature difference is reached. Otherwise, sudden fluctuations in the temperature of
either atmosphere or leaf due to wind may affect the operation of the system. Adjustment
of VR3 can vary the time delay, if needed.
The relay contacts were connected to a 230 V ac operated normally closed solenoid
valve whose input was connected to an overhead tank and output to the drip irrigation
system installed at the field. Thus, when the plant is stressed, the temperature of leaf
increases with respect to atmosphere, the valve is opened and water flows to the plants.
Then the plant leaves begin to cool and when the temperature reaches the pre-set value,
the valve stops the flow of water. The circuit was powered by 9 V dc supply. The
switching circuit used for automation based on leaf ±air temperature differential is shown
in Fig. 3.
Fig. 3. Switching circuit for the automation system based on leaf±air temperature.
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151
In the humid climatic conditions of Kerala, Okra showed a leaf temperature around
48C below that of atmosphere under well watered conditions. It was found to be going
upto 68C in certain days. This differential became 08C at extremely dry conditions. When
the leaves stared drooping, an air±leaf temperature differential of 28C or less was
observed. So the control circuit was adjusted such that it keeps on at an air±leaf
temperature differential of 38C. The selection of this air±leaf temperature differential was
also based on the sensitivity of the sensor used in this study.
To evaluate the performance of the two automated systems, the soil moisture content
was measured from each automated plot, three times a day, i.e. at 8.30 am, 12.30 and
3.30 pm. At the same time, air temperature and leaf temperature were also measured from
the Plot 2. The amount of water applied was also noted using two water meters. Moisture
contents from the two plots were determined by the gravimetric method. The yield and
dry matter content obtained from each plot were determined.
3. Results and discussion
The measurement of resistance in the field using gypsum block showed that when the
polarity across the electrodes changed, the resistance readings had considerable
variations. The performance curves of gypsum block for the four replications are shown
in Fig. 4. The sensor having soil in the field itself as the porous medium showed the same
relationship between moisture content and electrical resistance in the first and second
trials. During the third trial, it showed a slight variation from the trend. The fourth trial
showed considerable variation. This may be due to the presence of chemicals in the soil.
The performance curves for four trials are shown in Fig. 5. For the sensors having sponge
Fig. 4. Performance of gypsum block.
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Fig. 5. Performance of soil in the plot as porous medium.
and nylon as porous medium, four trials showed different trends in the relationship
between soil moisture content and electrical resistance. The variation may be due to the
moisture retention properties of these materials are different from that of the soil. The
performance curves for sponge and nylon are shown in Figs. 6 and 7, respectively. In all
the four replications, the sensor having washed sand as porous medium showed a constant
trend in the relationship between soil moisture content and electrical resistance. This is
Fig. 6. Performance of sponge as porous medium.
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153
Fig. 7. Performance of nylon as porous medium.
due to washed sand is less susceptible to chemical changes and the soil moisture
properties of the washed sand are probably similar to that of field soil. The performance
curves for washed sand are shown in Fig. 8. Based on the above results, the sensor with
washed sand as porous medium was selected and used as the soil moisture sensor in the
present study.
Fig. 8. Performance of washed sand as porous medium.
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Fig. 9. Soil moisture status in Plot 1 (automation based on soil electrical conductivity).
The system based on electrical conductivity was tested during the month of February±
April 1998. A plot of soil moisture content verses time for 12 days during the matured
stage of the crop is shown in Fig. 9. During the matured stage, maximum fluctuation in
soil moisture content of the root zone is expected due to increased evapotranspiration. It
can be seen that the moisture content was maintained nearly constant throughout the
period within the range 14±17%, that is around field capacity of the soil. On 9th day, a
moisture content of 19% is observed as the moisture content was happened to be taken
during the time of irrigation.
About 1 week after the installation of the sensor, some deposits were found to form on
the electrode plates that reduced the electrical conductivity between the electrode plates.
These deposits may be due to the polarisation of certain ions present in the soil. The same
trend was found immediately after the addition of fertilisers to the soil.
The system based on leaf±air temperature differential was also tested in the same
period. The soil moisture in this case was maintained between 10% and 13% throughout
the study period. The moisture content for 12 days during the matured stage of the crop is
shown in Fig. 10. Here upto a moisture content of 10%, the differential was less than 28C,
upto 14% moisture content, the differential was about 38C and beyond that it was above
48C. This shows that there is a distinct variation in leaf±air temperature differential
corresponding to soil moisture content for the crop Okra.
The system was found to maintain the pre-set value of leaf±air temperature differential
and the leaf temperature was maintained 38C below the atmospheric temperature. At this
level the moisture content was less than field capacity and the plant was subjected to
certain level of moisture stress. The relationship of soil moisture content with the leaf ±air
temperature differential is shown in Fig. 11. It shows that leaf±air temperature differential
has a direct relationship with soil moisture content.
N. Abraham et al. / Agricultural Water Management 45 (2000) 145±157
155
Fig. 10. Soil moisture status in Plot 2 (automation based on leaf±air temperature differential).
The volume of water applied during this period as irrigation is shown in Fig. 12. It can
be seen that more amount of water was applied in the first plot where system based on
soil resistivity was installed and a higher moisture content was maintained. The yield and
the drymatter content was also more in the first plot. On days 3, 5, and 9, there was
rainfall and the irrigation applied was less. The performance of both the systems were
Fig. 11. Variation in leaf±air temperature differential with soil moisture content.
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Fig. 12. Volume of irrigation during a 10-day period.
satisfactory and can be adopted for irrigation scheduling. The systems are simple and can
be easily maintained by farmers.
Application of fertilizer or chemical change, the resistance moisture content
relationship and therefore calibration of sensor is required after adding fertilizers or
chemicals. Such variations are not required for the system based on leaf±air temperature
differential. However, the sensor need to be changed to new leaves as the plant canopy
develops.
4. Conclusions
The sensor with brass plate as electrode and washed sand as porous medium showed
nearly a constant trend in the relationship between resistance and soil moisture content in
all trials.
The automated systems based on soil resistance was found to be working efficiently
without frequent supervision and maintained the pre-set moisture content in the root zone.
The automated system based on leaf±air temperature differential maintained the pre-set
leaf±air temperature differential throughout the study period.
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