Skip to main content
SpringerLink
Log in

Non-Destructive Assessment of Mango Firmness and Ripeness Using a Robotic Gripper

  • Original Paper
  • Published:
Food and Bioprocess Technology Aims and scope Submit manuscript

Abstract

The objective of the study was to evaluate the use of a robot gripper in the assessment of mango (cv. “Osteen”) firmness as well as to establish relationships between the non-destructive robot gripper measurements with embedded accelerometers in the fingers and the ripeness of mango fruit. Intact mango fruit was handled and manipulated by the robot gripper, and the major physicochemical properties related with their ripening index were analyzed. Partial least square regression models (PLS) were developed to explain these properties according to the variables extracted from the accelerometer signals. Correlation coefficients of 0.925, 0.892, 0.893, and 0.937 with a root-mean-square error of prediction of 2.524 N/mm, 1.579 °Brix, 3.187, and 0.517, were obtained for the prediction of fruit mechanical firmness, total soluble solids, flesh luminosity, and ripening index, respectively. This research showed that it is possible to assess mango firmness and ripeness during handling with a robot gripper.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Abdi, H. (2010). Partial least squares regression and projection on latent structure regression (PLS regression). Wiley Interdisciplinary Reviews: Computational Statistics, 2(1), 97–106.

    Article  Google Scholar 

  • Bandyopadhyaya I., Babu D., Bhattacharjee S., & Roychowdhury J. (2014). Vegetable grading using tactile sensing and machine learning. In: Anonymous (ed) Advanced Computing, Networking and Informatics-Volume 1. Smart Innovation, Systems and Technologies. Springer 27, 77-85. doi:10.1007/978-3-319-07353-8_10.

  • Blanes, C., Mellado, M., Ortiz, C., & Valera, A. (2011). Technologies for robot grippers in pick and place operations for fresh fruits and vegetables. Spanish Journal of Agricultural Research, 9(4), 1130–1141. doi:10.5424/sjar/20110904-501-10.

    Article  Google Scholar 

  • Blanes, C., Ortiz, C., Talens, P. & Mellado, M. (2014). Mango postharvest handling and firmness assessment with a robotic gripper. In Proceedings International Conference of Agricultural Engineer, Zurich, Switzerland.

  • Blanes, C., Ortiz, C., Mellado, M., & Beltrán, P. (2015). Assessment of eggplant firmness with accelerometers on a pneumatic robot gripper. Computers and Electronics in Agriculture, 113, 44–50. doi:10.1016/j.compag.2015.01.013.

    Article  Google Scholar 

  • Bouzayen M., Latché A., Nath P., & Pech J. (2010). Mechanism of fruit ripening. In Anonymous Plant Developmental Biology-Biotechnological Perspectives. (pp. 319–339). Springer. (ISBN 978-3-642-02300-2)

  • Brecht J., Sargent S., Kader A., Mitcham E., Maul F., Brecht P., & Menocal O. (2010). Mango Postharvest Best Management Practices Manual. Gainesville: Univ.of Fla.Horticultural Sciences Department, 78. Available at web page accessed 19 Jan 2015 http://edis.ifas.ufl.edu/pdffiles/HS/HS118500.pdf

  • Brown, E., Rodenberg, N., Amend, J., Mozeika, A., Steltz, E., Zakin, M. R., Lipson, H., & Jaeger, H. M. (2010). From the cover: universal robotic gripper based on the jamming of granular material. Proceedings of the National Academy of Sciences of the United States of America, 107(44), 18809–18814. doi:10.1073/pnas.1003250107.

    Article  CAS  Google Scholar 

  • Dobraszczyk B.J., Vincent J.F. (1999). Measurement of mechanical properties of food materials in relation to texture: the materials approach. Food Texture: Measurement and Perception, 99-151.

  • Esquerre, C., Gowen, A. A., O’Donnell, C. P., & Downey, G. (2009). Initial studies on the quantitation of bruise damage and freshness in mushrooms using visible-near-infrared spectroscopy. Journal of Agricultural and Food Chemistry, 57(5), 1903–1907. doi:10.1021/jf803090c.

    Article  CAS  Google Scholar 

  • FAOSTAT (2014). ProdSTAT. Food and Agriculture Organization of the United Nations. Available at web page accessed 19 Jan 2015 http://faostat.fao.org/site/339/default.aspx (Retrieved 10.03.14)

  • Girao, P. S., Ramos, P. M. P., Postolache, O., & Dias, J. M. (2013). Tactile sensors for robotic applications. Measurement, 46(3), 1257–1271. doi:10.1016/j.measurement.2012.11.015.

    Article  Google Scholar 

  • Gouado, I., Schweigert, F. J., Ejoh, R. A., Tchouanguep, M. F., & Camp, J. V. (2007). Systemic levels of carotenoids from mangoes and papaya consumed in three forms (juice, fresh and dry slice). European Journal of Clinical Nutrition, 61(10), 1180–1188. doi:10.1038/sj.ejcn.1602841.

    Article  CAS  Google Scholar 

  • Hahn, F. (2004). Mango firmness sorter. Biosystems Engineering, 89(3), 309–319. doi:10.1016/j.biosystemseng.2004.07.005.

    Article  Google Scholar 

  • http://www.lacquey.nl, available at web page accessed 19 Jan 2015.

  • Jaeger, H. (2014). Celebrating Soft Matter’s 10th Anniversary: toward jamming by design. Soft Matter, 11(1), 12–27. doi:10.1039/c4sm01923g.

    Article  Google Scholar 

  • Jha, S. K., Sethi, S., Srivastav, M., Dubey, A. K., Sharma, R. R., Samuel, D. V. K., & Singh, A. K. (2010). Firmness characteristics of mango hybrids under ambient storage. Journal of Food Engineering, 97(2), 208–212. doi:10.1016/j.jfoodeng.2009.10.011.

    Article  Google Scholar 

  • Lucena, Eliseu Marlônio Pereira de, Assis J.S.d., Alves R.E., Silva, Víctor César Macêdo da, & Enéias, Filho J. (2007). Alterações físicas e químicas durante o desenvolvimento de mangas ‘Tommy Atkins’ no vale de São Francisco, Petrolina-PE. Revista Brasileira de Fruticultura, 29, 96-101.

  • Meijneke, C., Kragten, G., & Wisse, M. (2011). Design and performance assessment of an under actuated hand for industrial applications. Mechanical Science, 2, 9–15. doi:10.5194/ms-2-9-2011.

    Article  Google Scholar 

  • Naghdy, F., & Esmaili, M. (1996). Soft fruit grading using a robotics gripper. International Journal of Robotics and Automation, 11, 93–101.

    Google Scholar 

  • Padda, M., Padda, M. S., Garcia, R., Slaughter, D., & Mitcham, E. (2011). Methods to analyze physico-chemical changes during mango ripening: a multivariate approach. Postharvest Biology and Technology, 62(3), 267–274. doi:10.1016/j.postharvbio.2011.06.002.

    Article  CAS  Google Scholar 

  • Peacock, B., Murray, C., Kosiyachinda, S., Kosittrakul, M., & Tansiriyakul, S. (1986). Influence of harvest maturity of mangoes on storage potential and ripe fruit quality. Asean Food Jorunal, 2, 99–101.

    Google Scholar 

  • Rungpichayapichet P., Rungpichayapichet B., Mahayothee P., Khuwijitjaru M., Nagle J., & Müller. (2015). Non-destructive determination of ß-carotene content in mango by near-infrared spectroscopy compared with colorimetric measurements. Journal of Food Composition and Analysis, 38, 32-41. (doi: 10.1016/j.jfca.2014.10.013)

  • Saranwong, S., Sornsrivichai, J., & Kawano, S. (2004). Prediction of ripe-stage eating quality of mango fruit from its harvest quality measured nondestructively by near infrared spectroscopy. Postharvest Biology and Technology, 31(2), 137–145. doi:10.1016/j.postharvbio.2003.08.007.

    Article  CAS  Google Scholar 

  • Singh, Z., Singh, R. K., Sane, V. A., & Nath, P. (2013). Mango—postharvest biology and biotechnology. Critical Reviews in Plant Sciences, 32(4), 217–236. doi:10.1080/07352689.2012.743399.

    Article  CAS  Google Scholar 

  • Talens, P., Mora, L., Morsy, N., Barbin, D. F., ElMasry, G., & Sun, D. (2013). Prediction of water and protein contents and quality classification of Spanish cooked ham using NIR hyperspectral imaging. Journal of Food Engineering, 117(3), 272–280. doi:10.1016/j.jfoodeng.2013.03.014.

    Article  CAS  Google Scholar 

  • Velez-Rivera, N., Blasco, J., Chanona-Perez, J., Calderon-Dominguez, G., de Jesus Perea-Flores, M., Arzate-Vazquez, I., Cubero, S., & Farrera-Rebollo, R. (2014). Computer vision system applied to classification of “Manila” mangoes during ripening process. Food and Bioprocess Technology, 7(4), 1183–1194. doi:10.1007/s11947-013-1142-4.

    Article  Google Scholar 

  • Vilela, C., Cordeiro, N., Silvestre, A. J. D., Oliveira, L., & Camacho, J. (2013). The ripe pulp of Mangifera indica L.: a rich source of phytosterols and other lipophilic phytochemicals. Food Research International, 54(2), 1535–1540. doi:10.1016/j.foodres.2013.09.017.

    Article  CAS  Google Scholar 

  • Wilson, M. (2010). Developments in robot applications for food manufacturing. Industrial Robot, 37(6), 498–502. doi:10.1108/01439911011081632.

    Article  Google Scholar 

  • Yashoda, H. M., Prabha, T. N., & Tharanathan, R. N. (2007). Mango ripening—role of carbohydrases in tissue softening. Food Chemistry, 102(3), 691–698. doi:10.1016/j.foodchem.2006.06.001.

    Article  CAS  Google Scholar 

  • Zaharah, S. S., Singh, Z., Symons, G. M., & Reid, J. B. (2012). Role of brassinosteroids, ethylene, abscisic acid, and indole-3-acetic acid in mango fruit ripening. Journal of Plant Growth Regulation, 31(3), 363–372. doi:10.1007/s00344-011-9245-5.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Instituto de Automática e Informática Industrial, Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain

    C. Blanes & M. Mellado

  2. Departamento de Tecnología de Alimentos, Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain

    V. Cortés & P. Talens

  3. Departamento de Ingeniería Rural y Agroalimentaria, Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain

    C. Ortiz

Authors
  1. C. Blanes
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. Cortés
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. C. Ortiz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M. Mellado
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. P. Talens
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to P. Talens.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Blanes, C., Cortés, V., Ortiz, C. et al. Non-Destructive Assessment of Mango Firmness and Ripeness Using a Robotic Gripper. Food Bioprocess Technol 8, 1914–1924 (2015). https://doi.org/10.1007/s11947-015-1548-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11947-015-1548-2

Keywords

Search

Navigation