DEVELOPMENT OF AN AUTOMATIC TOMATO PASTE PRODUCTION MACHINE
Olanrewaju, T. O., Durojaiye, L., Sunusi, I.I., Tenuche, S. S. and Baba Dahiru
National Agricultural Extension and Research Liaison Services (NAERLS),
Ahmadu Bello University, Zaria, Nigeria.
taofiqolanrewaju13@yahoo.com
+2348181079742
Abstract
Agriculture is a vast field that has been undergoing some level of evolution with the use of
mechanization and precision technologies. Inventions as a result of precise and qualitative
technology has contributed to large scale modern agriculture industry, that experiences
qualitative and quantitative produce through the engagement of precision smart agriculture. In
order to contribute to smart agriculture, especially, processing agricultural produce, an
automatic tomato paste machine was developed using electronic devices for its operation. The
tomato paste machine was developed from locally sourced materials which are mild steel angle
iron, stainless steel and PVC pipes. The automatic electronic components were made from series
of Integrated Circuits (IC), timers, relays, diodes, thermostats, blenders, heaters and plug. These
materials were soldiered to a board in conformity with the design of the circuit diagram. Tests
carried out revealed that as steam time increases, blending becomes easier and quality of paste
was also observed to improve. The more time used to blend, a corresponding paste volume was
sieved. A maximum volume of paste was received through the 1.2 mm sieve at blending time of
10 minutes. A volume of 2.7 kg and 2.8 kg paste were collected at 4 minutes and 6 minutes
steaming time. The timed heater and blender work as programmed, an indication that the
automation as preset is effective for the operation of the tomato paste machine. The machine is
easy to use, maintain and does not require supervision during use.
Keywords: Automatic, electronic, tomato paste, processing machine.
Introduction
Agricultural productivity, quality and economic growth of a country can be increased through
automation and smart agriculture. Studies has revealed that agricultural practices as practiced in
the mid-1990s has experienced some major changes, especially in areas like domestication of
crops and animals, weed control techniques, water management, fertilizer/pesticides application,
genetic engineering and mechanization through long term and low-tech alternatives in
agricultural mechanization and automation. Also, several systems of soil monitoring and irrigation control have been developed, with the aim of improving water use efficiency. The
speed of information processing of data collected in fields can assist to rapidly grow the
agriculture sector using precision technologies discovered by innovations that result in various
revolutions worldwide (Koprda and Magdin, 2015; Bachche, 2015; Seema, et al., 2015).
Numerous researches have been conducted on automation in agriculture, few among them are the
study of Nouri-Ahmadabadi et al. (2017) who developed an intelligent system that works with
Machine Vision (MV) and Support Vector Machine (SVM) that sorts peeled pistachio kernels
and shells. Images were taken and digitized using a colour CCD and capture card before they are
transferred to a computer for further analysis. The SVM achieved the best accuracy at 99.17%,
overall sorter accuracy of 94.33% and capacity of 22.74 kg/h. Momin et al. (2017) developed an
image acquisition and processing system to automate the grading of mangoes considering
projected area, perimeter, and roundness developed in Bangladesh. Images were acquired with a
high-resolution camera, processed with algorithm capable of colour binarization that classified
mangoes into large, medium and small. It has an accuracy of 97% for the projected area, 79% for
perimeter and 36% for roundness. It can be adopted for other crops with slight modifications. It
was recommended that two different grading features be used in sequence to achieve finer
grading. Moreover, a digital technology (automation) was used to simplify and reduce manpower
in agricultural sector. A sensor that detects humidity, temperature, fertilizers and pesticides was
designed to work in wired and wireless environment. The sensor was designed to connect
mechanical (natural environment) into digital environment. Simulation was done using
intellisuite software with finite element method at various levels of observations on the sensor.
The designed sensor was reported to achieve its function (Kalaiyazhagan et al., 2018). An
algorithm for fruit sorting using computer vision was also developed by Seema et al. (2015).
Image processing in agriculture was reviewed to provide an insight into the use of vision-based
systems highlighting their advantages and disadvantages. Bachche (2015) conducted a study by
collating 30 years information on various design strategies in recognition and picking systems in
fruits harvesting robots.
The high-tech, precise and qualitative large-scale modern agriculture industry of today is a result
of evolutions in time and different inventions in agriculture. The present era of modern high-tech
and precision agriculture is producing quality produce. However, tomato fruits being a tender
sensitive fruit with high moisture content and great post-harvest losses, especially immediately
after harvest has received insignificant level of smart agriculture/automation. In order to
contribute to smart agriculture, especially, agricultural produce processing, an automatic tomato
paste production machine was produced.
Materials and Methods
The tomato paste machine was made of different components which were welded, bolted,
screwed and wired. The frame was made from mild steel angle iron. The steaming unit was
made from a stainless-steel pot with perforated base positioned above a water bath and a heater.
Blending unit was also fabricated from stainless steel material. A bought-out blender and the
steamer were connected by a 3 mm PVC pipe. The machine views are presented in figures 1 to 3.
Engineering properties of materials and relevant design considerations were all considered in the
machine fabrication.
Figure 1: Orthographic and Isometric views of the automatic tomato paste production machine
1 – Handle, 2 – Steaming pot, 3 – Connecting pipe, 4 – Frame, 5 – Blending pot, 6 – Blender,
Figure 2: Real life picture of the tomato paste machine
Figure 3: Pictorial views of the developed tomato paste machine
Operating procedure
Water was poured and heated to boiling point below the steamer. The steam from the boiled
water rises by convection to the tomato fruits to soften it in readiness for blending. A stirrer
positioned at the middle of the steamer is rotated intermittently to ensure uniform reception of
steam by the tomato fruits. After a preset time, the heater goes off and the blender start up
automatically. The steamed tomato moves through the PVC pipes into the blending unit.
The inside of the blending unit has a conically wrapped stainless steel that ensures propulsion during
blending to achieve uniform blending of the tomato fruits into a homogenous paste.
The automatic electronic unit
The automatic electronic unit was designed and fabricated from series of Integrated Circuits (IC),
timers, relays, diodes, thermostats, blenders, heaters and plug. These materials were soldiered to
a board following the design of the circuit diagram presented in figure 4. The outlook of the
automation unit after arranging, soldering, and coupling is shown in figure 5. The plug is
connected to a socket. V1 represent an alternating voltage source of 220V. This voltage is used
two ways in the entire circuit. Components including the Blender B1, Heater H1 and Contact
Relays RL1 and RL2 uses the entire 220V alternating voltage from V1 while other electronic
components use a 12V direct current (DC) derived from V1 via Voltage Step-down, rectification
and filtration processes. TX1 is transformer unit used for stepping down the voltage from 220V
(AC) to 12V (DC). The 12V output is fed into two Rectifier Diodes D1 and D2 to rectify to 12V
(DC). Capacitor C1 is used to remove ac ripples (filtering) from the rectifier diodes’ output. The
output of C1 is fed into Zener diode (7812). The 7812 diode is used to ensure that a constant DC
voltage of 12V is frequently supplied to the electronic components even if the values of V1
fluctuate. The 12V dc voltage is supplied to the remaining electronic components in the circuit.
Integrated Circuits IC1 and IC2 are 555 timers. They are used to time Blender B1 and Heater H1.
R1, C2 and R2, C3 are used to control the timing of IC1 and IC2 respectively. This timing (t) is
related to an associated resistor R and Capacitor C of a 555 timer by equation 1.
R = (1)
R1 and R3 are variable resistors which can be tuned to control the timing of Blender B1 and
Heater H1. D4 and D5 are Light Emitting Diodes (LED) used as indicators for the operation of
Heater H1 and Blender B1. Q1 and Q2 and other associated components (resistors and capacitors)
performs the task of switching the Contact Relays RL1 and RL2 respectively. These Contact
Relays RL1 and RL2 respectively switch ON/OFF of Blender B1 and Heater H1 based on the
timing of IC1 and IC2.
Test Procedure
The major components of the automatic units are the steamer and the blender; hence, time was
preset for the steamer and blender. Literatures consulted indicated that average steaming time for
tomato fruits are usually between 5 - 10 minutes while blending time mostly takes between 7 and
15 minutes which are variety dependent (Olanrewaju, 2012). To ensure that the timers for both
the steamer and blender perform optimally, preset time of 3, 4 and 6 minutes for steaming while
4, 6 and 10 minutes for blending were considered. Combination of steaming and blending time
(treatments) gave 9 replications for the tests conducted as presented in Figure 6.
Steaming time 3 4 6
Blending time 4 6 10
Figure 6: Factorial Design of the Machine Testing
Fresh Roma Vf tomato fruits variety at grape vine maturity were purchased from a local market
in Ilorin, Kwara state, Nigeria. They were washed and sorted to remove foreign materials, and
bad fruits that could contaminate the paste. The fruits were weighed to avoid choking the
steaming and blending chamber and also to ensure uniform reception of steam. Clean tomato
fruits of 3 kg were fed into the machine. The steaming and blending time were preset using the
factorial design in figure 6. Particle size analysis was conducted on the blended paste using sieve
shaker with sieve sizes of 1.2 mm, 0.8 mm and 0.4 mm.
Result and Discussion
Results of the tests carried out on the machine are presented below.
Figure 7: Paste volume sieved after blending
Discussion
Quality of tomato paste is correlated with the steaming and blending time. Figure 7 shows the
quantity of tomato paste sieved by 3 different sieves. It was observed that as the steam time
increases, blending becomes easier and rheology of paste (smoothness/coarseness, homogeneity)
was also observed to improve. Moreover, the blending time increases as the volume of paste
sieved also increases. Maximum volume of paste was received through the 1.2 mm sieve at
blending time of 10 minutes. A volume of 2.7 kg and 2.8 kg paste were collected at 4 minutes
and 6 minutes steaming time. These assertions are in consonance with the studies of Dogan et al.
(2003), Zhang et al. (2014) and Sheta et al. (2017).
Conclusion
The automatic tomato paste machine produced was novel among local technology and its
performance were observed to produce an average tomato paste of 2.8 kg at steaming and
blending time of 6 and 10 minutes respectively. The performance of the machine can actualize
possibilities of automation in food processing industries, especially at small and medium scale
levels in Nigeria. The machine is easy to operate, maintain and as the name implies; automatic –
no supervision required during operation.
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