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Optimised computer vision system for automatic pre-grading of citrus fruit in the field using a mobile platform

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Abstract

The mechanisation and automation of citrus harvesting is considered to be one of the best options to reduce production costs. Computer vision technology has been shown to be a useful tool for fresh fruit and vegetable inspection, and is currently used in post-harvest fruit and vegetable automated grading systems in packing houses. Although computer vision technology has been used in some harvesting robots, it is not commonly utilised in fruit grading during harvesting due to the difficulties involved in adapting it to field conditions. Carrying out fruit inspection before arrival at the packing lines could offer many advantages, such as having an accurate fruit assessment in order to decide among different fruit treatments or savings in the cost of transport and marketing non-commercial fruit. This work presents a computer vision system, mounted on a mobile platform where workers place the harvested fruits, that was specially designed for sorting fruit in the field. Due to the specific field conditions, an efficient and robust lighting system, very low-power image acquisition and processing hardware, and a reduced inspection chamber had to be developed. The equipment is capable of analysing fruit colour and size at a speed of eight fruits per second. The algorithms developed achieved prediction accuracy with an R2 coefficient of 0.993 for size estimation and an R2 coefficient of 0.918 for the colour index.

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References

  • Baeten, J., Donné, K., Boedrij, S., Beckers, W., & Claesen, E. (2008). Autonomous fruit picking machine: A robotic apple harvester. Springer Tracts in Advanced Robotics, 42, 531–539.

    Article  Google Scholar 

  • Blasco, J., Aleixos, N., Gómez-Sanchis, J., & Moltó, E. (2009a). Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features. Biosystems Engineering, 103, 137–145.

    Article  Google Scholar 

  • Blasco, J., Aleixos, N., Roger, J. M., Rabatel, G., & Moltó, E. (2002). Robotic weed control using machine vision. Biosystems Engineering, 83(2), 149–157.

    Article  Google Scholar 

  • Blasco, J., Cubero, S., Gómez-Sanchis, J., Mira, P., & Moltó, E. (2009b). Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision. Journal of Food Engineering, 90, 27–34.

    Article  Google Scholar 

  • Chong, V. K., Monta, M., Ninomiya, K., Kondo, N., Namba, K., Terasaki, E., et al. (2008). Development of mobile eggplant grading robot for dynamic in-field variability sensing––manufacture of robot and performance test. Engineering in Agriculture, Environment and Food, 1(2), 68–76.

    Google Scholar 

  • Coppock, G. E., & Jutras, P. J. (1960). Mechanizing citrus fruit harvesting. Transactions of the ASAE, 3(2), 130–132.

    Article  Google Scholar 

  • Cubero, S., Aleixos, N., Moltó, E., Gómez-Sanchis, J., & Blasco, J. (2011). Advances in machine vision applications for automatic inspection and quality evaluation of fruits and vegetables. Food and Bioprocess Technology, 4(4), 487–504.

    Article  Google Scholar 

  • Cubero, S., Moltó, E., Gutiérrez, A., Aleixos, N., García-Navarrete, O. L., Juste, F., et al. (2010). Real-time inspection of fruit on a mobile harvesting platform in field conditions using computer vision. Progress in Agricultural Engineering Science, 6, 1–16.

    Article  Google Scholar 

  • DOGV. (2006). Diari Oficial de la Comunitat Valenciana, 5346, 30321–30328.

  • Edan, Y., Rogozin, D., Flash, T., & Miles, G. E. (2000). Robotic melon harvesting. IEEE Transactions on Robotics and Automation, 16(6), 831–834.

    Article  Google Scholar 

  • Ehsani, M. R., Grift, T. E., Maja, J. M., & Zhong, D. (2009). Two fruit counting techniques for citrus mechanical harvesting machinery. Computers and Electronics in Agriculture, 65(2), 186–191.

    Article  Google Scholar 

  • Feng, G., Qixin, C., & Masateru, N. (2008). Fruit detachment and classification method for strawberry harvesting robot. International Journal of Advanced Robotic Systems, 5(1), 41–48.

    Google Scholar 

  • Gómez-Sanchis, J., Gómez-Chova, L., Aleixos, N., Camps-Valls, G., Montesinos-Herrero, C., Moltó, E., et al. (2008). Hyperspectral system for early detection of rottenness caused by Penicillium digitatum in mandarins. Journal of Food Engineering, 89(1), 80–86.

    Article  Google Scholar 

  • HunterLab. (2008). Applications note, 8(9) http://www.hunterlab.com/appnotes/an08_96a.pdf. Accessed Nov 2012.

  • Jiménez-Cuesta, M.J., Cuquerella, J., & Martínez-Jávega, J.M. (1981). Determination of a color index for citrus fruit degreening. In: Proceedings of the International Society of Citriculture, Tokyo (Japan), vol. 2 (pp. 750–753).

  • Jutras, P.J., & Coppock, G.E. (1958). Mechanization of citrus fruit picking. Florida State Horticultural Society, 71, 201,204.

    Google Scholar 

  • Kohno, Y., Kondo, N., Iida, M., Kurita, M., Shiigi, T., Ogawa, Y., et al. (2011). Development of a mobile grading machine for citrus fruit. Engineering in Agriculture, Environment and Food, 4(1), 7–11.

    Google Scholar 

  • Kondo, N. (2009). Robotization in fruit grading system. Sensors and Instrumentation for Food Quality, 3, 81–87.

    Article  Google Scholar 

  • Lee, W. S., & Slaughter, D. C. (2004). Recognition of partially occluded plant leaves using a modified Watershed algorithm. Transactions of the ASAE, 47, 1269–1280.

    Article  Google Scholar 

  • Lee, W. S., Slaughter, D. C., & Giles, D. K. (1999). Robotic weed control system for tomatoes. Precision Agriculture, 1(1), 95–113.

    Article  Google Scholar 

  • Li, Z., Li, P., & Liu, J. (2011). Physical and mechanical properties of tomato fruits as related to robot harvesting. Journal of Food Engineering, 103(2), 170–178.

    Article  Google Scholar 

  • Lorente, D., Aleixos, N., Gómez-Sanchis, J., Cubero, S., García-Navarrete, O. L., & Blasco, J. (2012). Recent advances and applications of hyperspectral imaging for fruit and vegetable quality assessment. Food and Bioprocess Technology, 5(4), 1121–1142.

    Article  Google Scholar 

  • Mazzetto, F., Calcante, A., Mena, A., & Vercesi, A. (2010). Integration of optical and analogue sensors for monitoring canopy health and vigour in precision viticulture. Precision Agriculture, 11(6), 636–649.

    Article  Google Scholar 

  • McBratney, A., Whelan, B., Ancev, T., & Bouma, J. (2005). Future directions of precision agriculture. Precision Agriculture, 6(1), 7–23.

    Article  Google Scholar 

  • Mizushima, A., & Lu, R. (2011). Cost benefits analysis of in-field presorting for the apple industry. Applied Engineering in Agriculture, 27(1), 33–40.

    Article  Google Scholar 

  • Muscato, G., Prestifilippo, M., Abbate, N., & Rizzuto, I. (2005). A prototype of an orange picking robot: Past history and experimental results. Industrial Robot, 32(2), 128–138.

    Article  Google Scholar 

  • Nieuwenhuizen, A. T., Hofstee, J. W., & van Henten, E. J. (2010). Adaptive detection of volunteer potato plants in sugar beet fields. Precision Agriculture, 11, 433–447.

    Article  Google Scholar 

  • Official Journal of European Communities. (2001). 14.09.2001. pp. L244/12–L244/18. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2001:244:0012:0018:EN:PDF. Accessed May 2013.

  • Ortiz, C., Blasco, J., Balasch, S., & Torregrosa, A. (2011). Shock absorbing surfaces for collecting fruit during the mechanical harvesting of citrus. Biosystems Engineering, 110, 2–9.

    Article  Google Scholar 

  • Qiao, J., Sasao, A., Shibusawa, S., Kondo, N., & Morimoto, E. (2004). Mobile fruit grading robot (part1)––Development of a robotic system for grading sweet peppers. Journal of the Japanese Society of Agricultural Machinery (JSAM), 66(2), 113–122.

    Google Scholar 

  • Qiao, J., Sasao, A., Shibusawa, S., Kondo, N., & Morimoto, E. (2005). Mapping yield and quality using the mobile fruit grading robot. Biosystems Engineering, 90(2), 135–142.

    Article  Google Scholar 

  • Ruiz-Altisent, M., Ortiz-Cañavate, J., & Valero, C. (2004). Fruit and vegetables harvesting systems. In: R. Dris and S. M. Jain (Eds.), Production practices and quality assessment of food crops, vol. 1: Preharvest practice (pp. 261–285). Dordrecht: Kluwer.

  • Torregrosa, A., Gil, J., Ortiz, C., Ortí, E., & Martín, B. (2009). Mechanical harvesting of oranges and mandarins in Spain. Biosystems Engineering, 104(1), 18–24.

    Article  Google Scholar 

  • Vidal, A., Talens, P., Prats-Montalbán, J. M., Cubero, S., Albert, F., & Blasco, J. (2012). In-line estimation of the standard colour index of citrus fruits using a computer vision system developed for a mobile platform. Food and Bioprocess Technology,. doi:10.1007/s11947-012-1015-2.

    Google Scholar 

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Acknowledgments

This research work has been funded by the Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria de España (INIA) and the European FEDER funds (projects RTA2009-00118-C02-01 and RTA2009-00118-C02-02). The authors wish to thank the collaboration of the company Argilés Diseny i Fabricació, S.L.

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Correspondence to J. Blasco.

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Cubero, S., Aleixos, N., Albert, F. et al. Optimised computer vision system for automatic pre-grading of citrus fruit in the field using a mobile platform. Precision Agric 15, 80–94 (2014). https://doi.org/10.1007/s11119-013-9324-7

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  • DOI: https://doi.org/10.1007/s11119-013-9324-7

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