Solar Powered Automated Fertigation Control System ... - Science Direct

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APCBEE Procedia 4 (2012) 79 – 87

ICAAA 2012: July 23-24, 2012, Singapore

Solar Powered Automated Fertigation Control System for Cucumis Melo L. Cultivation in Green House J. E Mohd Salih∗, A. H Adom and A.Y Md Shaakaf School Of Mechatronic Engineering,Universiti Malaysia Perlis,Arau 02600,Perlis,Malaysia

Abstract Production of vegetables and fruits in Malaysia using fertigation methods been experiencing accelerated growth. Fertigation allow farmers to automatically deliver adequate nutrient quantity and concentration through drip irrigation to plants active root area throughout the growing season. Conventionally, three separate preset digital timers are used to turn ON/OFF injector and irrigation pumps for fertilizer mixing and setting daily frequency of irrigation. The quality of nutrients solution level is manually checked using Electrical Conductivity (EC) meter to determine quality of the nutrient solution. This project was developed and tested to provide low cost solution for precise control of fertilizer mixing and irrigation to local farmers. A predefined EC value will be used as single input that control all automated processes in cucumis melo L. cultivation using fertigation system. The developed system powered totally by solar power system and tested on its effectiveness to control the nutrient mixing process and injecting nutrient solutions according to plants growth rate and in the same time monitor all key parameters in fertigation system. © byby Elsevier B.V.B.V. Selection and/orand/or peer review under responsibility of Asia-Pacifi c Chemical, © 2012 2012Published Published Elsevier Selection peer review under responsibility of Asia-Pacific Biological Environmental Engineering Society Open access under CC BY-NC-ND license. Chemical,&Biological & Environmental Engineering Society Keywords: FERTIGATION, ELECTRICAL CONDUCTIVITY (EC), TIME BASED IRRIGATION

1. Introduction Fertilizers injected through drip irrigation systems in a process called fertigation are one type of microirrigation system [1]. Fertigation allows the delivery of nutrients to plants in the correct quantities and at the appropriate time for a specific stage of plant growth. Irrigators wishing to inject chemicals have a variety of

∗ Corresponding author. Tel.:+604-9885210; fax:+604-9885167. E-mail address: [email protected].

2212-6708 © 2012 Published by Elsevier B.V. Selection and/or peer review under responsibility of Asia-Pacific Chemical, Biological & Environmental Engineering Society Open access under CC BY-NC-ND license. doi:10.1016/j.apcbee.2012.11.014

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J. E Mohd Salih et al. / APCBEE Procedia 4 (2012) 79 – 87

injection equipment from which to choose, including differential pressure or batch tanks, bladder tanks, devices, and positive displacement pumps [2]. The major factor in the irrigation process is the time and the key in fertigation is striking to correct balance for optimal plant life with optimal use of water [3,4]. Fertigation controllers are divided roughly into two main classes, open loop and closed-loop controller. The open loop controller is based on a predefined control concept, with no feedback from the controlled object. Therefore, the open-loop controller uses a periodic irrigation policy [5]. In this policy, the irrigation is based on the relevant amounts of water that must be given periodically, normally fractions of total volume daily. These types of controllers, though relatively cheap, do not provide the optimal solution to the irrigation problem. Mean while the close loop controller is based on a combination of pre-defined control concept (feed forward) and feedback of the necessary data to determine the amount of water needed for irrigation [6]. The commercial fertigation controller normally used pH, electrical conductivity (EC) sensor to determine the correct ratio of fertilizers and water in nutrient solutions. Flow sensor combines with solenoid valves will give feedback signal to control irrigation process by controlling the ON/OFF periods for pump. Commercial fertigation controller is not affordable to majority of local farmers due to high set-up and maintenance costs. Another important factor that affects fertigation of micro-irrigation systems is the performance of the injecting device. Fertilizer uniformity could be greatly influenced by injection method and management during the injection process [5]. Commonly there are three types of injection method namely proportional pump, venturi injector and differential pressure tank. The venturi injector systems utilize a venturi restriction in the water line to suck the fertilizer solution into the water stream and therefore the system does not require electrical power. With venturi systems, the concentration of fertilizer in the water stream remains constant throughout the irrigation cycle, but pressure loss in main irrigation line required a booster pump and the quantitative aspect of fertigation is difficult to obtain [2]. So, it was preferred that fertilizer be prepared through mixing rather than to be directly injected to the mainline of the fertigation system in the irrigation cycle. The positive displacement pumps accurately measure and supply a constant amount of fertilizer into the irrigation water stream thus maintaining a constant concentration of fertilizer in the water stream throughout the irrigation cycle. Any crop must receive all of the nutrients at a specific EC. Therefore, the fertigation must be carried out according to the EC of the irrigation water. Another advantage of irrigation according to EC control is the ability to maintain the desired concentration of the fertilizer in the water regardless of preparation error, material chemistry and construction [7]. This project was developed to provide low cost solution for precise control of fertilizer mixing and irrigation to local farmers. A predefined EC value will be used as single input that control all automated processes in cucumis melo L. cultivation using fertigation system. The developed systems was powered totally by solar power system and were tested on its effectiveness to control the nutrient mixing process and injecting nutrient solutions according to plants growth rate and in the same time monitor all keys parameter in fertigation process. 2. Methods and Materials Cucumis melo L. or Rock Melon is one of suitable plants largely planted using fertigation system due to high return and short period of growth. For rock melon grown in closed fertigation systems, desired EC is between 1.5 dS/m to 2.5 dS/m with growth period between 70 to 80 days. The amount of daily consumption of nutrient ranges from 500 ml/daily to 2000 ml/daily according to plant growth stage. Table 1 shows the recommended nutrient delivery for rock melon suggested by Agriculture Department of Perak for the whole planting season. Small amounts of fertilizer used in the early crop’s season. Dosage is increased as fruit load and nutrient demands grow as plants approach the end of the crop's cycle.

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2.1. Mechanical Design The system was developed using three cylindrical polyethylene tanks. The stocks of fertilizers were placed in two 30 litre tanks, and another 60 litre tank was used for mixing. Fig. 1 shows the developed architecture of mixing and irrigation system. The fertilizer injectors (pump A & pump B) used are water pumps with a flow rate of 55 litre/hour rated at 6 V and irrigation pump had a flow rate of 250 litre/hour rated at 12 V. Three units of 12 V solenoid valve used in this system to control water flow to the mixing tank and to control nutrient flow to the irrigation piping system. An ultrasonic sensor used as level sensor to monitor nutrient level in the mixing tank. Table 1. Schedule for Nutrient Delivery for Rock Melon

Age (week)

EC Level (dS/m)

Daily Nutrient Volume (ml)

Daily Irrigation frequency

1 2 3 4 5 6 7 8 9 10 11

1.5 1.6 1.7 1.8 1.9 2.0 2.2 2.4 2.4 2.5 2.5

500 750 1000 1000 1500 1500 2000 2000 2000 2000 2000

5 x 100ml 5 x 125ml 5 x 200ml 5 x 200ml 5 x 300ml 5 x 300ml 5 x 400ml 5 x 400ml 5 x 400ml 5 x 400ml 5 x 400ml

Time Morning 8.00 am 8.00 am 8.00 am 8.00 am 8.00 am 8.00 am 8.00 am 8.00 am 8.00 am 8.00 am 8.00 am

10.00 am 10.00 am 10.00 am 10.00 am 10.00 am 10.00 am 10.00 am 10.00 am 10.00 am 10.00 am 10.00 am

Evening 12.00 pm 12.00 pm 12.00 pm 12.00 pm 12.00 pm 12.00 pm 12.00 pm 12.00 pm 12.00 pm 12.00 pm 12.00 pm

2.00 pm 2.00 pm 2.00 pm 2.00 pm 2.00 pm 2.00 pm 2.00 pm 2.00 pm 2.00 pm 2.00 pm 2.00 pm

5.00 pm 5.00 pm 5.00 pm 5.00 pm 5.00 pm 5.00 pm 5.00 pm 5.00 pm 5.00 pm 5.00 pm 5.00 pm

Fig. 1. The developed architecture of nutrient mixing and irrigation system

2.2. Solar Power and Controller System Design The solar power supply used consists of a 20 watts mono-crystalline photovoltaic (PV) solar panel, solar charge controller and a battery. The specifications of the solar panel are shown in Table 2. In Table 2, Vpp is the voltage at peak power, Ipp is the current at peak power, Vcc is open circuit voltage, Isc is short circuit

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current, and L, W, T, are the length, width, and thickness of the PV panel, respectively. Solar charge controller from Morningstar Corporation rated at maximum 6 A for solar panel and load. The controller will maximize the amount of solar energy into the battery and avoid it drying out. The charge controller has regulation voltage at 14.3 V, low voltage disconnects at 11.5 V and 12.6 V reconnected voltage respectively [8]. It also has LEDs display status information and battery level helps the user to better operate the solar power system. The 12 V and 6 Amp/hour battery which are used as backup supply in the absence of sunlight due to overcast skies or rain, are rechargeable, sealed, and lead–acid type. Table 2. Solar panel specifications Vpp [V]

Ipp [mA]

Vcc [V]

Icc [mA]

L

Dimensions (mm) W

T

Weight [kg]

17.82

1140

21.96

1270

662

299

34

2.7

A BasicStamp 2 microcontroller based system (Fig. 2) was developed to control all electrical components to perform nutrients mixing and irrigation process. The developed control board consists of the main components such as multiple voltage regulator (9V, 6V and 5V) circuitry, wireless communication and control modules integrated onto a single Printed Circuit Board (PCB).

Fig. 2. Schematic diagram showing various parts of the system

Nutrient mixing and irrigation process in the control module uses five inputs and six outputs. Table 3 shows the connections between input/output and BasicStamp 2 microcontroller for overall developed system. For EC measurements, EC stamp and EC probe from Atlas Scientific are used in this project. The EC Stamp design configuration allows the user to accurately monitor EC range of 10 s/cm to 65,000 s/cm [9].

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Table 3. List of input/output pins connections to BasicStamp 2 microcontroller Pin P0,P1 P2 P3 P4 P5 P6,P7 P8,P9 P10 P11 P12 P13 P14 P15

Connection X-bee module – serial in , serial out Start Button Potential meter Ultrasonic sensor LCD EC stamp – serial in , serial out pH stamp – serial out , serial in Relay circuit 1 Relay circuit 2 Relay circuit 3 Relay circuit 4 Relay circuit 5 Relay circuit 6

Functions Wireless communication with field sensors To start mixing and irrigation process Weekly EC setting level measurement Display nutrients and process parameters Communication with EC stamp for EC measurement Communication with pH stamp for pH measurement ON/OFF solenoid valve 3 ON/OFF solenoid valve 2 ON/OFF solenoid valve 1 ON/OFF irrigation pump ON/OFF injector pump A ON/OFF injector pump B

2.3. Nutrient Mixing and Irrigation Process In this study, two separate nutrient solution formulations namely stock A and B were used. This nutrients solution contains approximately nine substances. These stocks were prepared separately in a concentrated form to avoid low solubility and chemical reaction that will produce unwanted salt crystal in the nutrients stock. The insoluble precipitate can clog the drip tube and lead to nutrient deficiency. When various amounts of a certain concentrated solutions are added to the water, the changes that occur in the total salt concentration C in mEq/l and in the electrical conductivity EC in dS/m, may be approximately related to each other through the equation (1), where a is a factor depending on the composition of the particular concentrated solution, C = a (EC)

(1)

During nutrient solution preparation, addition of stock solutions increases the electrical conductivity by equation (2); EC =ECd – ECw

(2)

Since the fertilizer concentration in each of the stock solutions is identical, regardless of recycling application or not, the respective dilution ratios of the stock solutions Ai are related with C through the equation (3); C =Ai

(3)

Thus, the desired electrical conductivity ECd for stock solution are derived by substituting equations (2) and (3) into equation (1); ECd = Ai /a + ECw

(4)

If fertilizer dispensers that give a constant injection rate are used, the amount of each stock solution added when a fresh solution is prepared, has a linear relationship to injection time. For each stock solution, the injection time T in sec, is related to Ai by the equation (5), where f is the injection rate of the stock solution dispensers in 1/s. T = Vn / f

(5)

The irrigation process is mainly controlled by irrigation pump. The total volume of nutrient solution injected to each plant, Vi are proportional to pump flow rate. Equation (6) shows the relationship between

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pump flow rate, Q and nutrient volume for every plant, Vi. Timer, Tpump is ON period for pump in seconds and n total number of plant in irrigation pipeline. Vi = QTpump / n

(6)

2.4. Control Algorithm The BasicStamp 2 microcontroller was programmed to execute the nutrient mixing and irrigation process based on EC level set by user using a potential meter according to planting period in Table 1. The EC level selected by user will determine the ON period for both injector pumps. The total volume inside mixing tanks was set at 40 liters and measured by ultrasonic level sensor. A subroutine inside the program will convert the distances in centimeter receive by ultrasonic sensor into nutrient volume inside the mixing tank. Fig.4 shows the program flow for the system. The process parameters such planting periods in number of weeks, days and hours will be displayed by LCD. User also can monitor other process parameter status such as current EC level of nutrients solution, nutrient volume and irrigation counter on the LCD.

Fig. 3. Program flow for nutrient mixing, monitoring and irrigating process

2.5. Experimental Set-up In order to verify the fertilization, irrigation system and algorithm developed in this project, a fertigation system for rock melon cultivation was set-up in naturally ventilated tropical green house located in School of Mechatronics, Universiti Malaysia Perlis from January 2012 to Mac 2012. Seedlings of rock melon were planted inside 39 units of plastic pots filled with coco pet. The irrigation piping system was constructed using poly pipe and micro tubing divided into 4 rows and each row contains 10 plants. The nutrient solution was injected via 2 liter/hour dripper installed at every 39 pots plus one extra dripper installed for daily volume measurement. EC level and total volume of nutrient injected to the plants are measured daily. Fig.4 shows the details of physical system set-up inside the greenhouse.

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Fig. 4. (a) Actual prototype system installed inside the greenhouse; (b) system connection to solar panel; (c) rock melon plant inside planting pod in 2nd week of planting period

3. Results and Discussions 3.1. Solar Power Performance Hourly voltage level were measured during sunny day and cloudy conditions. During sunny days the solar panel will produce an average voltage level at 19.3 V and 16.4 V during cloudy days. Average power generated by solar panel was around 140 watt-hours/day. Power consumption for the system only required an average of 10 watt-hours/day. The reserved energy stored inside the battery can hold up to 72 watt-hours/day, and hence the system can operate up to 7 days without sunshine. 3.2. Relationship between EC, fertilizer volume and injector pump rate Prior to this development, relationship between EC and ratio between nutrient volume and water volume need to be measured. The system was programmed to fill up the mixing tank at maximum volume of 40 liters. Fertilizer stock A and B were then manually added into the water with volume increments of 100 ml each. Fig. 5 show the linearity relationship between 40 liters water volume and fertilizer volume that give the increment measurement of EC. Equation (8) show the relationship between EC value of and fertilizer volume, where is differential factor of nutrient concentration in (ds/m)/ml, Vn is total volume of fertilizer A and B and EC0 is initial EC value for the water measured at 0.05. EC = Vn+ EC0

(8)

The value calculated was 0.0019. The injector pump produced an average flow rate, Qi of 14.9 ml/s at 5.98 V regulated voltage level produced by controller board. The total volume of fertilizer injected is given by equation (9) where T is ON period of for each pump. Vn = Qi (2T)

(9)

By substituting all of the values of and Qi in equation (9) into equation (8), to achieve desired EC level set by user, each pump are programmed to turn ON for T period of times in seconds based on equation (10). For example, to achieve EC value of 2.0 ds/m during 6th week of planting season both pumps will automatically calculated to turn ON for 34.4 seconds. T = (EC – 0.05)/0.05662

(10)

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Fig.6. Relationship between EC and fertilizer volume mix with 40 liters of water.

3.3. Overall System performance The developed system was installed and tested inside a greenhouse. Observed values of daily EC were obtained via EC probe and displayed on LCD panel. The daily volume of discharge were obtained via volume measurement station. The daily EC and daily discharge volume were recorded for 28 days (4 weeks) and weekly average of EC and daily nutrient volume were calculated. Table 4 shows the comparison between measured weekly EC and daily nutrient volume compared to desired EC and daily nutrient intake for 4 weeks of planting season. Based on results obtained from the experiment (Fig. 7) the developed prototype is proven reliably to be to be installed in large size fertigation plantations. Table 4. Results weekly average of EC and nutrient volume

Week

Date

1

3-9 Jan 2012

Weekly Average EC Value (ds/m)

Daily Average Nutrient Volume, V (ml)

ECset

ECmeasure

Error (%)

Vcalculate

Vmeasure

Error (%)

1.5

1.52

1.33

500

508

1.6 1.73

2

10-16 Jan 2012

1.6

1.63

1.87

750

763

3

17-23 Jan 2012

1.7

1.72

1.18

1000

1022

2.2

4

24-39 Jan 2012

1.8

1.83

1.67

1000

1018

1.8

Fig. 7. Results between desired EC and volume and measured EC and volume by days


4. Conclusions Evaluation of the developed system has established that system was able to maintain nutrients EC level and daily nutrient to each plants accordingly. Hopefully this system can be used as a prototype for Malaysian farmers to automatically control and monitor nutrients deliver system. By being fully operated with solar energy the system can be installed at rural and remote locations to achieve reductions in costs and produce better yield for rock melon or other crops cultivated using fertigation systems. Acknowledgements The authors wish to express their appreciation to Universiti Malaysia Perlis for funding this project under Short Term Grant Scheme (Grant number: STG 9001-00355). Thank also to all contributors, local farmers and agriculture agency for advises to successfully develop the system. References [1] Saiful Farhan M. Samsuri, Robiah Ahamd, Mohd Hussien. Development of Nutrient Solution Mixing on Time Based Drip Fertigation System. Proceedings of the 4th Asia International Conference on Mathematical /Analytical Modelling and Computer Simulation 2010:615-619. [2] T. L. Robinson and W. C. Stiles, Fertigation effects on apple tree growth, cropping, and dry matter partitioning, New York FruitQuarterly, Horticultural Society of N.Y, vol. 12, 2004. [3] Evans, R., R.E. Sneed and D.K. Cassel, 2006.Irrigation scheduling to improve water and energy use efficiencies, North Carolina Cooperative extension Service (AG 452-4). [4] Reuter, D.C. and R.S. Everett, 2000. Control theory and applications: Neural-fuzzy controller for lawn irrigation. [5] Burman, R. and L.O. Pochop, 2004. Evaporation evapotranspiration and climatic data. Elsevier,Amsterdam. [6] P. Javadi Kia, et al. Intelligent Control Based Fuzzy Logic for Automation of Greenhouse Irrigation System and Evaluation in Relation to Conventional Systems, World Applied Science Journal 6 (1): 16-23,2009. [7] Noble Abraham, et al. Irrigation automation based on soil electrical conductivity and leaf temperature, Journal of Agricultural Water Management 45 (2000) 145-157 [8] MorningStar. The SHS 6A solar charge controller manual.2008 [9] Atlas Scientific. EC Stamp micro footprint electrical conductivity manual. Version 1.32. 2011

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