Soil moisture monitoring using near-infrared sensing technique and the Internet in a coffee plantation field

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1 Soil moisture monitoring using near-infrared sensing technique and the Internet in a coffee plantation field Ryoei Ito 1, Masaki Harada 2, Ayako Michida 2, Masaru Mizoguchi 3, Takashi Mishima 1, Takaharu Kameoka 1, Atsushi Hashimoto 1, Kenichi Nakanishi 1, Hiroshi Shono 4, Masaaki Oka 5, Hirokazu Taki 6, Fumitaka Uchio 6, Yasunori Saito 7, Hiroaki Ishizawa 8, Yoshitaka Motonaga 9, Takehiko Hoshi 10, Nobukazu Iguchi 11, Eiji Goto 3, Seishi Ninomiya 12, Masayuki Hirafuji 11, Tokihiro Fukatsu 11 Abstract We have developed two types of soil moisture monitoring system and performed long-term test employment of these systems in the coffee plantation in Hawaii. One is a lower cost and smaller size near-infrared moisture sensor developed by the SANYO Electric (Co., Ltd.), the other is a modified system for monitoring soil information, called SIMS(Soil Information Monitoring System). We settled them in the UCC (Ueshima Coffee Company) (Co., Ltd.) coffee farm in Hawaii and tried to retrieve the observed data through the Internet. After the multiple sensors were installed in a coffee field, their performance was evaluated for about a year. Throughout these experiments, it is proved that both "Simplified Optical Moisture Sensor system and modified SIMS can measure soil moisture precisely and continuously. Consequently, we could provide useful information to the GIS based coffee farm map. On the basis of BIX (BioInformation exchange), individual information can be integrated. Keywords: Near-infrared, Soil moisture, Coffee plantation field, Internet Introduction Some factors, such as the temperature, rainfall, soil permeability and so on, decide the suitable place for coffee production. Soil moisture is also an important factor for a coffee plant. KONA of the Hawaii Island (so called Big Island) is one of the famous coffee-producing areas. As the island is mostly made of volcanic rocks, farmers have to bring the fertile soil from other places for coffee production. We can only find the very thin soil layer (typically dozens of cm) in a coffee field. If there is a rainfall, it penetrates very quickly and most quantity of water is lost into the ground. The farmers have to provide additional irrigational water and manage the soil moisture condition adequate for good production. The aim of this paper is to 1 Faculty of Bioresources, Mie University, itou-r@bio.mie-u.ac.jp 2 SANYO Electric Co., Ltd., hara@mech.rd.sanyo.co.jp 3 University of Tokyo, mizo@soil.en.a.u-tokyo.ac.jp 4 Faculty of Agriculture, Iwate University, shono@iwate-u.ac.jp 5 Miyagi University of Education, maoka@staff.miyakyo-u.ac.jp 6 Faculty of Systems Engineering, Wakayama University, taki@sys.wakayama-u.ac.jp 7 Faculty of Engineering, Shinshu University, saitoh@cs.shinshu.ac.jp 8 Faculty of Textile Science & Technology, Shinshu University, zawa@giptc.shinshu-u.ac.jp 9 Faculty of Agriculture, Niigata University, motonaga@agr.niigata-u.ac.jp 10 School of High-Technology for Human Welfare, Tokai University, hoshi@fb.u-tokai.ac.jp 11 School of Science and Engineering, Kinki University, iguchi@is.kindai.ac.jp 12 National Agriculture Research Center, snino@affrc.go.jp

2 develop a low-cost soil moisture monitoring system and offer the useful information used as reduction of water management cost to the farmers. Many people know that moisture measurement using near-infrared rays has many advantages, but incorporating it into household electric appliances or applying it extensively was difficult up until now because of cost and size. We have developed a lower cost and smaller size near-infrared moisture sensor "Simplified Optical Moisture Sensor", which was realized through simplification of the mechanism and optimization of data processing. For comparison, we also use a dielectric aquameter, which is a commonly used sensor for measuring volumetric water content of soil and other porous material. We performed long-term test employment of these systems in the coffee plantation in Hawaii. We settled them in the UCC (Ueshima Coffee Company) (Co., Ltd.) coffee farm in Hawaii and tried to retrieve the observed data through the Internet. Moisture measurement using near-infrared rays The basic principle of measurement Water has the properties that absorb well the light of specific wavelength, such as 1450nm, 1950nm, and 3000nm, in the near-infrared region, because it contains O-H group. We can measure the amount of moisture contained in a subject by measuring the absorption (or penetration) rate of these specific wavelengths. Moreover, the absorption rate of the light is also measured simultaneously in the region where water does not absorb as a reference light, and the compensation is performed to remove the influence of substances other than water. This moisture measurement using near-infrared rays has the following advantages as compared with other systems, such as a resistance method and a heat capacity method. a) A measurement is not influenced by the electrical properties of the subject, such as ph. b) Non-distructive measurement is possible. c) It takes only a short time (few seconds) for the measurement. d) Measurement does not influence the subjects. If we want to make the optical moisture sensor adapting the principles described above, the following two devices are surely required. One is the light source which can output the light of the wavelength of near-infrared region, and the other is the optical detector which has high sensitivity in near-infrared region. But these devices are usually very expensive, and the mechanism of such a moisture sensor becomes complicated. We have developed a lower cost and smaller size near-infrared moisture sensor Simplified Optical Moisture Sensor, which was realized through simplification of the mechanism and optimization of data processing. Simplified optical moisture sensor Composition Fig. 1 shows the composition of the simplified optical moisture sensor. This sensor consists of a head unit and an operation unit. Head unit is composed of the incandescence light source and two light-receiving elements; one is a pyroelectric element, the other is a Si photodiode. An operation unit outputs the amount of

3 moisture using the calibration curve, which computes the amount of moisture from the light-receiving element output, created beforehand. The price of an incandescence light source is several dozens of yen per piece. Also, the each price of the two light-receiving elements is about hundreds of yen, the price of a new sensor drops from 1/10 to 1/15 with a low price far, compared with the parts used by the conventional optical moisture sensor mentioned above. The principle of measurement An incandescence light source outputs the light of a broad range, from a near-infrared region (800nm) where the absorption belt of water exists, to an infrared region (3000nm), as shown in the spectral power distribution map (Fig. 2(a)). And the two light-receiving elements have such a spectrum sensitivity characteristic as shown in Fig. 2(b). Si photodiode has sensitivity in the light of a 500 to 1000nm wavelength belt that is not absorbed by water; pyroelectric element has sensitivity in the light, wavelength of which is longer than 1000nm containing the absorption belt of water. When a light that is emitted from the incandescence light source reflects by the measurement subject containing water, absorption of light occurs with the water in a subject according to the spectral transmittance of water. For this reason, the reflection light detected by two light-receiving elements is fluctuated with the amount of moisture. The properties of optical detection P n, Q n (n =0,40,80) are shown in Fig. 2(e), where n is the moisture content (%) of a substance. The size of the amount of optical detection by a Si photodiode and a pyroelectric element is proportional to the area of the domain surrounded in the graph showing each properties of optical detection. Since the transmissivity of water is about 1.0 in a visible light region, we can see from Fig.2(d) that the amount of optical detection of Si photo-diode hardly changes, even if the amount of moisture changes. By contrast, because the rate of light absorption changes according to change of the amount of moisture in a near-infrared region, the amount of optical detection of a pyroelectric element changes according to moisture content. The amount of moisture is computed from these output change. The formula, which transformed the Lambert-Beer s law, is used for calculation of the amount of moisture. When the size of the amount of optical detection of Si photodiode and a pyroelectric element is set to Ps and Q s respectively, the amount of moisture can be computed from the following equation, W = a + a1 log( Ps ) + a2 log( Q 0 s ) where W is the amount of moisture, or the density of moisture in a substance, and a i are experimental constants. We use this equation as a calibration curve of the simplified optical moisture sensor. Soil moisture monitoring using the Internet Soil moisture is one of the important factors in agricultural production. In order to grasp and control the growth state of agricultural products, it is necessary to measure soil moisture over a long period of time. We applied the simplified optical moisture

4 sensor to a soil moisture monitoring and performed the test that carries out the soil moisture monitoring from a remote place. Fig. 3 shows the whole soil moisture monitoring system composition. A sensor head unit is installed under the ground in the depth where we want to measure soil moisture. A microcomputer BOX equivalent to the operation unit of Fig. 2 is installed on the ground, and is connected between the sensor head unit by the 1m length dedicated cable. RS-232C interface (maximum length is 20m) is used to communicate between microcomputer BOX and the sensor server PC. Along this communication line, there also exists a line that supplies a DC power to both sensors and a microcomputer BOX. The data server PC mainly offers the management function of acquired data, and the user interface to it. By the test performed in Japan, measurement data was transmitted using a cellular phone; we exchanged the cellular phone to the Internet, in order to enable a system to operate in many countries. Data is sent to the data server PC of a remote place by the from the sensor server PC. Discussion We performed long-term test employment of this system in the coffee plantation in Hawaii. For comparison, we also used a dielectric aquameter, which is a commonly used sensor for measuring volumetric water content of soil and other porous material. We settled them in the UCC (Ueshima Coffee Company) (Co., Ltd.) coffee farm in Hawaii and tried to retrieve the observed data through the Internet for about a year. The installation situation of each system is shown in Table 1, Fig. 4. At first, we designed the SOMS system so that observation data might be transmitted by the to the data server PC, but it did not work well since the SMTP server of the local ISP was out of condition. Then, we decided to retrieve data from the sensor server PC directly via VPN between Hawaii and NARC. Several months after an experiment start, we have noticed that the observed data of soil moisture near a surface of the ground was abnormal. Web camera, which was placed there by other members of our project, took pictures, which showed that the pipe for laying a cable from office to a coffee field was dug by someone. It was supposed that a wild animal might have dug the sensors to drink water. When an experiment was completed and we collected apparatus, we were able to check the situation. (Fig.5) Fig. 6 is an example of measuring result. Since it was not able to perform a calibration test of soil moisture on the experimental site unfortunately, raw observed values are plotted on the graph. Both SOMS and ECHO system show that the soil moisture was decreasing with periodical vibration. Throughout these experiments, it is proved that SOMS system and can measure soil moisture precisely and continuously.

5 Acknowledgement Authors would like to thank UCC Hawaii for offering the installations of their Coffee farm and for working together with us in this experiment. Synergetic information systems with distributed databases and models" project supported part of this work. References Ito R. et al., 2003, VPN Based Soil Environment Monitoring System for Remote Filed, Annual Conf. of JSIDRE, pp (in Japanese) Kameoka T. et al.2002.sensing and Information System for Cultivation Traceability in the Farm, AFITA, pp Michida A. et al, 2003, Simplified Optical Moisture Sensor For Application to Environmental Field and Agriculture -, SANYO Technical Review, Vol. 35, No. 2, pp (in Japanese) Tables Table 1: Experimental condition in the field Soil moisture Temperature SOMS 10, 30cm below ground 10, 30cm below ground ECHO 10,20,30 cm below ground 5,10,20,30 cm below ground

6 Figures Figure 1. Composition figure and appearance of SOMS Figure 2. Principle of measurement of SOMS Figure 3. Soil moisture monitoring system Figure 4. Settlement of the two soil moisture sensors

Figure 5. Wild animal dug the sensors out 900-0.6 850 ECHO SOMS -0.7-0.8-0.

7 Figure 5. Wild animal dug the sensors out ECHO SOMS Voltage(mV) /5/1 2003/5/3 2003/5/5 2003/5/7 2003/5/9 2003/5/ /5/13 Date Log(Qs) Figure 6. Example of measuring result

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