New Technologies to Implement Precise Management of Farming in a City

  • Tadashi ChosaEmail author
  • Hitoshi Kato
  • Rei Kikuchi


Robotics is a key technology to innovate various industries such as manufacturing, medical care, nursing care, transportation, and agriculture. The robot that can talk and communicate with people is currently available on the market. Robot tractors have been studied for a long time since the 1990s. The accumulation of technology has assisted recent ICT agricultural and robotic technology. Applications of drones to monitor crop growth, the growth environment, and application of materials, among the many others, have increased, and the deployment of flying robots is expected to expand. The situation that miniaturization of sensors, progress of AI, and dissemination of communication technology, etc. are progressing daily favors the development of small robots. The use of compact robots in housework, logistics, medical care, and the like that are close to our daily living just starts. Application of small-sized robots in actual agricultural work and contribution to agricultural production is discussed in the first section.

The Global Navigation Satellite System (GNSS) is a generic term for the generally recognized GPS, QZSS, and other satellite positioning systems. Calculation algorithm of positioning system is described in the second section to realize a driving support system for a farming guidance system based on GNSS and automatic driving assistance.

Producing fruits around urban regions is popular in Japan. However, the fruit production around a city has some issues that need to be addressed. When the farmers spray pesticides and apply chemical fertilizers in the field that is close to houses, the residents will complain about the work. Managing work on fruit production should be done precisely and carefully in urban region. The various information from a plant body such as leaves, branches, flowers, etc. provides management solutions on irrigation timing, amount of water to farmers, etc. The information includes changes in photosynthetic capacity, transpiration, and water transport inside a plant body, among the many others. An attempt monitoring the stem diameter displacement of blueberry plant by using a small load cell with high precision is explained for obtaining biological information in the third section.


  1. Blackmore S (2016a) Robotic agriculture: smarter machines using minimum energy, presented on April 21, 2016. Accessed 3 Dec 2018
  2. Chosa T (2017) Why do we try to do agriculture with a small robot? In: Proceedings of the 76th annual meeting of The Japanese Society of Agricultural Machinery and Food Engineers 193. (Presentation No. 7–8) (in Japanese)Google Scholar
  3. Chosa T (2018) Lets’s start small farming? In: Proceedings of the 21st Techno-Festa, Symposium of the Japanese Society of Agricultural Machinery and Food, (in press). (in Japanese).Google Scholar
  4. Chosa T, Furuhata M, Omine M, Matsumura O (2009) Development of air-assisted strip seeding for direct seeding in flooded paddy fields seeding machine and effect of air assistance. Jpn J Farm Work Res 44(4):211–218. in Japanese with English summaryCrossRefGoogle Scholar
  5. Chosa T, Tojo S, Rojas J L P (2015) An attempt of the air-assisted strip seeding for direct seeding using a knapsack power applicator, Proceedings of Joint Conference on Environmental Engineering in Agriculture 2015 (on CD-ROM). (Presentation No. B204)Google Scholar
  6. Faulkner EH (1943) Plowman’s folly, the University of Oklahoma Press, Publishing Division of the University. Manufactured in the USAGoogle Scholar
  7. Fujimori K, Chosa T, Tojo S (2017a) Evaluation by simulated seeding distribution envisioning random traveling of small field robot. Proceedings of the 53rd annual meeting of Kanto branch, The Japanese Society of Agricultural Machinery and Food Engineers, 32–33. (Presentation No. A13) (in Japanese)Google Scholar
  8. Fujimori K, Chosa T, Tojo S (2017b) Seeding simulation by small field robot. In: Proceedings of the 76th annual meeting of The Japanese Society of Agricultural Machinery and Food Engineers, 186. (Presentation No. 7–1) (in Japanese)Google Scholar
  9. Fujita A, Nakamura M, Kameoka T (2011) Soil moisture measurement to support production of high-quality oranges for information and communication technology (ICT) application in production orchards. Agric Inf Res 20:86–94. Scholar
  10. GNSS Technologies Inc. (2016) Fundamental knowledge of GNSS (in Japanese). Accessed 10 Feb 2019
  11. Goldhamer DA, Fereres E (2001) Irrigation scheduling protocols using continuously recorded trunk diameter measurements. Irrig Sci 20:115–125. Scholar
  12. Haman DZ, Smajstrla AG, Pritchard RT, Lyrene PM (1997) Response of young blueberry plants to irrigation in Florida. HortScience 32:1194–1196CrossRefGoogle Scholar
  13. Imai S, Iwao K, Fujiwara T (1990) Measurements of plant physiological information of vine tree and indexation of soil moisture control (1). Environ Control Biol 28:103–108CrossRefGoogle Scholar
  14. Iwao K, Takano T (1988) Studies on measurements of plant physiological informations and their agricultural applications (1). Environ Control Biol 26:139–145CrossRefGoogle Scholar
  15. Kato T, Chosa T, Tojo S, Yoshikawa M, Mochimaru T (2016) Influence of mowing using robot lawn mower on vegetation in weeds. Japn J Farm Work Res 51(1):23–24CrossRefGoogle Scholar
  16. Kawai K, Ito J, Ohkura K, Fujita K (2003) Measurement of changes in stem diameter under different temperature by an unbonded type gauge device. Environ Control Biol 41:289–294CrossRefGoogle Scholar
  17. Kikuchi R, Chosa T, Tojo S (2012) Root temperature influences growth of blueberry stems. CIGR-AgEng2012, International conference of agricultural engineering, Val Spain, JulyGoogle Scholar
  18. Kikuchi R, Chosa T, Tojo S (2014a) Relation between changes in stem diameter of blueberry and water balance of absorptions and evapotranspiration. International conference on agricultural engineering, AgEng 2014, Zurich, 6–10 JulyGoogle Scholar
  19. Kikuchi R, Chosa T, Tojo S (2014b) Development of continuous water supply system for measurements of water balance of absorptions and evapotranspiration of blueberries. International conference on agricultural engineering, AgEng 2014, Zurich, 6–10 JulyGoogle Scholar
  20. Kikuchi R, Chosa T, Tojo S (2017) Continuous measurement for stem diameter of blueberry plant with small load cell. J Jpn Soc Agric Mach Food Eng 79:365–373Google Scholar
  21. Komatsuzaki M (2007) Ecological significance of cover crop and no tillage practices for ensuring sustainablity of agriculture and eco-system service. In: Chen J, Guo C (eds) Ecosystem ecology research trends. Nova Science Publishers, New York, pp 177–207Google Scholar
  22. Kuroda H (2017) Verification of power supply to lawn mowing robot by independent power supply (solar + storage battery). In: Proceeding of the 76th annual meeting of the Japanese Society of Agricultural Machinery and Food Engineers, 187. (No. 7–2) (in Japanese)Google Scholar
  23. MAFF (2015) Ministry of Agriculture, Forestry and Fisheries of Japan, 2002–2015. The statistics of production dynamics of locally produced fruit tree.
  24. Miralles-Crespo J, Sanchez-Blanco MJ, AN G et al (2010) Comparison of stem diameter variations in three small ornamental shrubs under water stress. HortScience 45:1681–1689CrossRefGoogle Scholar
  25. Muramatsu N (2007) Recent measurement of moisture content in body of fruit tree. Agric Hortic 82:947–955. (in Japanese)Google Scholar
  26. Nagasaka Y, Taniwaki K, Otani R, Shigeta K (1999) The development of autonomous rice transplanter (Part 1) − The location of the rice transplanter by a real-time kinematic GPS −. Journal of Japanese Society of Agricultural Machinery 61(6):179–186. (in Japanese with English abstractGoogle Scholar
  27. Nakahara M, Inoue Y (1997) Detecting water stress in differentially-irrigated tomato plants with infrared thermometry for cultivation of high-Brix fruits. J Agric Meteorol 53:191–199. Scholar
  28. Noguchi N (1996) An over view of the global positioning system (GPS) and application for agriculture – Advanced technology in the near future. J Jpn Soc Agric Mach 58(4):130–134Google Scholar
  29. Nortes PA, Perez-Pastor A, Egea G et al (2005) Comparison of changes in stem diameter and water potential values for detecting water stress in young almond trees. Agric Water Manag 77:296–307. Scholar
  30. Oda M, Li Z, Tsuji K et al (1993) Effects of humidity and soil moisture content on chlorophyll fluorescence of cucumber seedlings exposed to high air temperature. J Japn Soc Hortic Sci 62:399–405. Scholar
  31. Oishi N (2002) Development of irrigation control system in response to plant water stress in tomato hydroponics (1). Environ Control Biol 40:81–89CrossRefGoogle Scholar
  32. Pedersen SM, Fountas S, Have H, Blackmore BS (2006) Agricultural robots—system analysis and economic feasibility. Precis Agric 7(4):295–308CrossRefGoogle Scholar
  33. Saito M, Tamaki K, Nishiwaki K, Nagasaka Y (2012) Development of an autonomous rice combined harvester using CAN bus network. J Japn Soc Agricult Mach 74(4):312–317. (in Japanese with English abstractGoogle Scholar
  34. Sakai T (2016) Status of the Japanese QZSS Program. Munich Satellite Navigation Summit, Munich, Germany, March 2016. Accessed 10 Feb 2019
  35. Simonneau T, Habib R, Goutouly J-P, Huguet J-G (1993) Diurnal changes in stem diameter depend upon variations in water content: Direct evidence in peach trees. J Exp Bot 44:615–621. Scholar
  36. Spiers JM (1996) Established “Tifblue” rabbiteye blueberries respond to irrigation and fertilization. HortScience 31:1167–1168CrossRefGoogle Scholar
  37. Spiers JM (1998) Establishment and early growth and yield of “Gulfcoast” southern highbush blueberry. HortScience 33:1138–1140CrossRefGoogle Scholar
  38. Tokyo Metropolitan Central Wholesale Market (2017). Market statisticsGoogle Scholar
  39. Tokyo Metropolitan Government, Bureau of Industrial and Labor Affairs (2018) Fruit tree agriculture promotion plan of TokyoGoogle Scholar
  40. Ueda M, Shibata E (2001) Diurnal changes in branch diameter as indicator of water status of Hinoki cypress Chamaecyparis obtusa. Trees - Struct Funct 15:315–318. Scholar
  41. Ueda M, Shibata E (2002) Water status of the trees estimated from diurnal changes in stem and branch diameters using strain gauges. J tree Heal 6:75–84Google Scholar
  42. Yukumoto O, Matsuo Y, Noguchi N, Suzuki M (1998) Development of tilling robot (Part 1) − concept of control algorithm and task planning using position sensing system and geomagnetic direction sensor. J Jpn Soc Agric Mach 60(3):37–44. (in Japanese with English abstractGoogle Scholar

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© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Institute of AgricultureTokyo University of Agriculture and TechnologyFuchuJapan
  2. 2.Division of Lowland Farming, Central Region Agricultural Research CenterNational Agriculture and Food Research OrganizationTsukubaJapan
  3. 3.Division of Farming Systems Research, Western Region Agricultural Research CenterNational Agriculture and Food Research OrganizationFukuyamaJapan

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