- -

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

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

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

Mostrar el registro completo del ítem

Blanes Campos, C.; Cortés López, V.; Ortiz Sánchez, MC.; Mellado Arteche, M.; Talens Oliag, P. (2015). Non-Destructive Assessment of Mango Firmness and Ripeness Using a Robotic Gripper. Food and Bioprocess Technology. 8(9):1914-1924. https://doi.org/10.1007/s11947-015-1548-2

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/63047

Ficheros en el ítem

Thumbnail
Nombre: versión autor.pdf
Tamaño: 3.651Mb
Formato: PDF
Descripción: Versión del Autor.
Abrir/Preview
[Cerrado]
Nombre: Non-Destructive ...
Tamaño: 1.102Mb
Formato: PDF
Descripción: Versión editorial
Solicitar una copia al autor

Metadatos del ítem

Título: Non-Destructive Assessment of Mango Firmness and Ripeness Using a Robotic Gripper
Autor: Blanes Campos, Carlos Cortés López, Victoria Ortiz Sánchez, María Coral Mellado Arteche, Martín Talens Oliag, Pau
Entidad UPV: Universitat Politècnica de València. Departamento de Ingeniería Rural y Agroalimentaria - Departament d'Enginyeria Rural i Agroalimentària
Fecha difusión:
Resumen:
[EN] The objective of the study was to evaluate the use of a robot gripper in the assessment of mango (cv. BOsteen^) firmness as well as to establish relationships between the nondestructive robot gripper measurements ...[+]
Palabras clave: Robot gripper , Non-destructive , Firmness , Ripening index , Mango
Derechos de uso: Reserva de todos los derechos
Fuente:
Food and Bioprocess Technology. (issn: 1935-5130 ) (eissn: 1935-5149 )
DOI: 10.1007/s11947-015-1548-2
Editorial:
Springer Verlag (Germany)
Versión del editor: http://dx.doi.org/10.1007/s11947-015-1548-2
Código del Proyecto:
info:eu-repo/grantAgreement/MINECO//RTA2012-00062-C04-02/ES/Nuevas técnicas de manipulación usando sensorización integrada para la estimación de propiedades y determinación automática de la calidad y sanidad de la producción agroalimentaria en líneas de inspección y manipulación (MANI-DACSA)/
info:eu-repo/grantAgreement/MINECO//RTA2012-00062-C04-03/ES/Nuevas técnicas de inspección basadas en visión por computador multiespectral para la estimación de propiedades y determinación automática de la calidad y sanidad de la producción agroalimentaria en líneas de inspección y manipulación (VIS-DACSA)/
info:eu-repo/grantAgreement/GVA//AICO%2F2015%2F122/
info:eu-repo/grantAgreement/UPV//PAID-05-11-2745/
info:eu-repo/grantAgreement/MECD//FPU13%2F04202/ES/FPU13%2F04202/
Descripción: The final publication is available at link.springer.com
Agradecimientos:
The authors thanks MANI-DACSA projects (ref. RTA2012-00062-C04-02 and RTA2012-00062-C04-03), Spanish Government (Ministerio de Economia y Competitividad), AICO/2015/122 project, Conselleria de Educacion, Cultura y Deporte, ...[+]
Tipo: Artículo

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.

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

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 .

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 .

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 .

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 .

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 .

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 .

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

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 .

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 .

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 .

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

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 .

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.

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 .

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 .

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 .

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 .

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 .

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

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 .

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 .

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem