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Sweet Cherry Skin Colour Measurement as an Non-Destructive Indicator of Fruit Maturity Cover

Sweet Cherry Skin Colour Measurement as an Non-Destructive Indicator of Fruit Maturity

Open Access
|Dec 2019

References

  1. 1. Antal, T., Sikolya, L., & Kerekes, B. (2013). Assessment of Freezing Pre-Treatments for the Freeze Dried of Apple Slices. Acta Universitatis Cibiniensis. Series E: Food Technology, 17(2), 3–14.10.2478/aucft-2013-0006
  2. 2. Adamiak, A., Zdunek, A., Kurenda, A., & Kuczynski, A.P. (2011). Characteristics and application of biospeckle Phenomenon in the study of plant materials (a review). Acta Agrophysica, 18(2), 215–224.
  3. 3. Bauriegel, E., Giebel, A., & Herppich, W.B. (2011). Hyperspectral and chlorophyll fluorescence imaging to analyse the impact of Fusarium culmorum on the photosynthetic integrity of infected wheat ears. Sensors, 11, 3765–3779. doi:10.3390/s11040376510.3390/s110403765
  4. 4. Chełpiński, P. (2007). Wpływ wybranych podkładek na wzrost i plonowanie oraz skład chemiczny liści i owoców czereśni na Pomorzu Zachodnim. Wyd. Nauk. AR Szczecin ISSN 0239-6467.
  5. 5. Crisosto, C., Crisosto, G.M., & Metheney, P. (2003). Consumer acceptance of ‘Brooks’ and ‘Bing’ cherries is mainly dependent on fruit SSC and visual skin color. Postharvest Biol Tec, 28, 159–167.10.1016/S0925-5214(02)00173-4
  6. 6. Escribano, S., Biasi, W.V., Lerud, R., Slaughter, D.C., & Mitcham, E.J. (2017). Non-destructive prediction of soluble solids and dry matter content using NIR spectroscopy and its relationship with sensory quality in sweet cherries. Postharvest Biol. Tec, 128, 112–120. https://doi.org/10.1016/j.postharvbio.2017.01.01610.1016/j.postharvbio.2017.01.016
  7. 7. Ferrer, A., Remon, S., & Negueruela, A.I. (2005). Changes during ripening of the very late season Spanish peach cultivar Calanda Feasibility of using CIELab coordinates as maturity indices. Sci Hort, 105, 435–446. https://doi.org/10.1016/j.scienta.2005.02.00210.1016/j.scienta.2005.02.002
  8. 8. Forczmański, P., & Frejlichowski, D. (2012). Classification of elementary stamp shapes by means of reduced point distance histogram representation. Proceedings Machine Learning and Data Mining MLDM 2012, Lecture Notes in Artificial Intelligence, 7376, 603–616. https://doi.org/10.1007/978-3-642-31537-4_4710.1007/978-3-642-31537-4_47
  9. 9. Forczmański, P., & Maleika, W. (2015). Near-lossless PCA-based Compression of Seabed Surface with Prediction. Proceedings 12th International Conference on Image Analysis and Recognition ICIAR 2015, Lecture Notes in Computer Science, 9164, 119–128. https://doi.org/10.1007/978-3-319-20801-5_1310.1007/978-3-319-20801-5_13
  10. 10. Forczmański, P. (2016). Evaluation of Singer’s Voice Quality by Means of Visual Pattern Recognition. J Voice, 30(1), 127.e21-127.e3010.1016/j.jvoice.2015.03.00125935835
  11. 11. Goncalves, B., Silva, A.P., Moutinho-Pereira, J., Bacelar, E., Rosa, E., & Meyer, A.S. (2007). Effect of ripeness and postharvest storage on the evolution of colour and anthocyanins in cherries (Prunus avium L.). Food Chem, 103: 976–984. doi:10.1016/j.foodchem.2006.08.03910.1016/j.foodchem.2006.08.039
  12. 12. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I.H. (2009). The WEKA data mining software: an update. ACM SIGKDD explorations newsletter, 11(1), 10–18.10.1145/1656274.1656278
  13. 13. Hertog, M.L., Ben-Arie, R., Róth, E., & Nicolaï, B.M. (2004). Humidity and temperature effects on invasive and non-invasive firmness measures. Postharvest Biol Tec, 33(1), 79–91. https://doi.org/10.1016/j.postharvbio.2004.01.00510.1016/j.postharvbio.2004.01.005
  14. 14. Hunterlab. (2012). Measuring Color using Hunter L, a, b versus CIE 1976 L*a*b*. AN 1005.00: 1–4. (www.hunterlab.com/an-1005b.pdf).
  15. 15. Li, X., Wei, Y., Xu, J., Feng, X., Wu, F., Zhou, R., & He, Y. (2018). SSC and pH for sweet assessment and maturity classification of harvested cherry fruit based on NIR hyperspectral imaging technology. Postharvest Biol. Tec, 143, 112–118. https://doi.org/10.1016/j.postharvbio.2018.05.00310.1016/j.postharvbio.2018.05.003
  16. 16. Łysiak, G., Kurlus, R., Zydlik, Z., & Walkowiak-Tomczak, D. (2014). Apple skin colour changes during harvest as an indicator of maturity. Acta Sci Pol, Hortorum Cultus, 13(3), 71–83.
  17. 17. Łysiak, G. (2011). The determination of harvest index of ‘Šampion’ apples intended for long storage. Acta Sci Pol, Hortorum Cultus, 10(3), 273–282.
  18. 18. Łysiak, G. (2012). The base colour of fruit as an indicator of optimum harvest date for two apple cultivars (Malus domestica Borkh.). Folia Hort, 24(1), 81–89. doi:https://doi.org/10.2478/v10245-012-0012-210.2478/v10245-012-0012-2
  19. 19. Mireei, S.A., Mohtasebi, S.S., Massudi, R., Refiee, S., & Arabanian, A.S. (2010). Feasibility of near infrared spec-troscopy for analysis of date fruits. Int Agrophysics, 24, 351–356.
  20. 20. Nicolai, B.M., Lamertyn, E.A., Veraverbeke, M.A., Hertog, T.M., Roth, E., Berna, A., Alamar, M.C., Verlinden, B., & Jancsok, P. (2005). Non-destructive techniques for measuring quality of fruit and vegetables. Acta Hortic, 682, 1333–1339.10.17660/ActaHortic.2005.682.179
  21. 21. Nowakowska, M., Ochmian, I., & Mijowska, K. (2017). Assessment of the sea buckthorn growing in urban conditions–the quality of berries and leaves. J Elem, 22(2), 399–409. doi:10.5601/jelem.2016.21.2.116810.5601/jelem.2016.21.2.1168
  22. 22. Overbeck, V., Schmitz, M., & Blanke, M. (2017). Non-Destructive Sensor-Based Prediction of Maturity and Optimum Harvest Date of Sweet Cherry Fruit. Sensors, 17(2), 277.10.3390/s17020277533598928146114
  23. 23. Ochmian, I., Oszmiański, J., Lachowicz, S., & Krupa-Małkiewicz, M. (2019). Rootstock effect on physico-chemical properties and content of bioactive compounds of four cultivars Cornelian cherry fruits. Scientia Horticulturae, 256, 108588.10.1016/j.scienta.2019.108588
  24. 24. Ochmian, I., Yordanov, A., Mijowska, K., & Chełpiński, P. (2016). Effect of storing Persimmon (Diospyros kaki) fruits under shelf life conditions on selected physical parameters and chemical composition. Food Science Technology Quality, 1(104), 155–166. DOI: 10.15193/zntj/2016/104/10910.15193/zntj/2016/104/109
  25. 25. Overbeck, V., Schmitz, M., & Blanke, M. (2017). Non-Destructive Sensor-Based Prediction of Maturity and Optimum Harvest Date of Sweet Cherry Fruit. Sensors, 17(2), 277.10.3390/s17020277
  26. 26. Pappas, C.S., Takidelli, C., Tsantili, E., Tarantilis, P.A., & Polissiou, M.G. (2011). Quantitative determination of anthocyanins in three sweet cherry varieties using diffuse reflectance infrared Fourier transform spectroscopy. J Food Compos Anal, 24(1), 17–21. https://doi.org/10.1016/j.jfca.2010.07.00110.1016/j.jfca.2010.07.001
  27. 27. Paz, P., Sánchez, M.T., Pérez-Marín, D., Guerrero, J.E., & Garrido-Varo, A. (2008). Nondestructive determination of total soluble solid content and firmness in plums using near-infrared reflectance spectroscopy. J Agric Food Chem, 56(8), 2565–2570. doi:10.1021/jf073369h10.1021/jf073369h18363330
  28. 28. Peng, Y., & Lu, R.. (2008). Analysis of spatially resolved hyperspectral scattering images for assessing apple fruit firmness and soluble solids content. Postharvest Biol Technol, 48, 52–62. doi:10.1016/j.postharvbio.2007.09.01910.1016/j.postharvbio.2007.09.019
  29. 29. Royal Horticultural Society. (2007). Royal Horticultural Society colour chart. Royal Hort. Soc., London
  30. 30. Rutkowski, K.P., Michalczuk, B., & Konopacki, P. (2008). Nondestructive determination of ‘Golden Delicious’ apple quality and harvest maturity. J Fruit Ornam Plant Res, 16, 39–52.
  31. 31. Seifert, B., Zude, M., Spinelli, L., & Torricelli, A. (2015). Optical properties of developing pip and stone fruit reveal underlying structural changes. Physiol Plantarum, 153(2), 327–336. https://doi.org/10.1111/ppl.1223210.1111/ppl.1223224853358
  32. 32. Serrano, M., Diaz-Mula, H.M., Zapata, P.J., Castillo, S., Guillen, F., Martinez-Romero, D., Valverde, J.M., & Valero, D. (2009). Maturity stage at harvest determines the fruit quality and antioxidant potential after storage of sweet cherry cultivars. J Agric Food Chem, 57, 3240–3246. doi:10.1021/jf803949k10.1021/jf803949k19284725
  33. 33. Shmulevich, I. (2004). Mechanical techniques for non-destructive sorting of agricultural products. I Georgofili. Quaderni 2004 -III, 33–53.
  34. 34. Voss, D.H. (1992). Relating Colorimeter Measurment of Plant Color to the Royal Horticultural Society Colour Chart. HortSci, 27(12), 1256–1260.10.21273/HORTSCI.27.12.1256
  35. 35. Yusufe, M., Mohammed, A., & Satheesh, N. (2017). Effect of duration and drying temperature on characteristics of dried tomato (Lycopersicon esculentum L.) cochoro variety. Acta Universitatis Cibiniensis. Series E: Food Technology, 21(1), 41–50.10.1515/aucft-2017-0005
  36. 36. Zanella, A., Vanoli, M., Rizzolo, A., Grassi, M., Eccher Zerbini, P., Cubeddu, R., & Spinelli, L. (2012). Correlating optical maturity indices and firmness in stored ‘Braeburn’ and’ Cripps Pink’ apples. In VII International Postharvest Symposium. 1012 pp. 1173–1180.10.17660/ActaHortic.2013.1012.158
  37. 37. Zerbini, P.E., Grassi, M., Cubeddu, R., Pifferi, A., & Torricelli, A. (2003). Time-resolved reflectance spectroscopy can detect internal defects in pears. Acta Hort, 599, 359–365.10.17660/ActaHortic.2003.599.44
  38. 38. Zerbini, P.E. (2006). Emerging technologies for non-destructive quality evaluation of fruit. J Fruit Ornam Plant Res, 14(Suppl. 2), 13–23.
  39. 39. Zude, M., Pflanz, M., Spinelli, L., Dosche, C., & Torricelli, A. (2011). Non-destructive analysis of anthocyanins in cherries by means of Lambert-Beer and multivariate regression based on spectroscopy and scatter cor-rection using time-resolved analysis. J Food Eng, 103(1), 68–75. doi:10.1016/j.jfoodeng.2010.09.02110.1016/j.jfoodeng.2010.09.021
  40. 40. Zude, M., Sasse, J., & Schallnus, H. (2009). Non-Invasive Sensing of Fruit Development in Banana and Papaya by Means of a Spectroscopic Approach. International Symposium Postharvest Pacifica 2009-Pathways to Quality: V International Symposium on Managing Quality in 880, 2009, November, pp. 277–281. doi:10.17660/ActaHortic.2010.880.3210.17660/ActaHortic.2010.880.32
DOI: https://doi.org/10.2478/aucft-2019-0019 | Journal eISSN: 2344-150X | Journal ISSN: 2344-1496
Language: English
Page range: 157 - 166
Submitted on: Oct 19, 2019
Accepted on: Dec 4, 2019
Published on: Dec 30, 2019
Published by: Lucian Blaga University of Sibiu
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2019 Piotr Chełpiński, Ireneusz Ochmian, Paweł Forczmański, published by Lucian Blaga University of Sibiu
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.