Advertisement

Food and Bioprocess Technology

, Volume 4, Issue 5, pp 809–813 | Cite as

Non-destructive Estimation of Mandarin Maturity Status Through Portable VIS-NIR Spectrophotometer

  • Francesca Antonucci
  • Federico PallottinoEmail author
  • Graziella Paglia
  • Amedeo Palma
  • Salvatore D’Aquino
  • Paolo Menesatti
Communication

Abstract

Sugar content is one of the most important quality attributes of citrus fruit, either for fresh or for processing market. Since sugars in citrus juice are highly correlated with total soluble solids (TSS) content, which can be determined easily even by the means of a hand refractometer, TSS is one of the most frequently used quality index. Since TSS can be measured only destructively, the results are representative only if carried out on large samples and do not allow classifying marketable fruit one by one according to their specific sugar content. Objective of this experiment was to assess possibility and limits of a non-destructive estimation of citrus fruits internal quality parameters (TSS and titratable acidity) presenting thick peel by the use of a spectrophotometric portable VIS-NIR system. Four hundred fruit of “Miho” satsuma and 150 fruit of “Page” tangelo were used. Each fruit was first subjected to spectrophotometric acquisition and soon after was juiced and TSS and titratable acidity (TA) determined. Partial least squares (PLS) regression analysis was applied for constructing a predictive model based on the spectral normalized response, constructing the model on a sub-sample and verifying the model (prediction test) on independent ones. The TA relative to Page mandarin was predicted in the test with an r = 0.88 and a standard error of prevision (SEP) coefficient of variability of 3.8% while the TSS scored an r = 0.85 and a SEP coefficient of variability equal to 4%. The TA of Miho mandarin was predicted in the test with an r = 0.81 and a SEP coefficient of Variability of 8.3% while the TSS scored an r = 0.84 and a SEP coefficient of variability equal to 5.6%.

Keywords

Mandarin VIS-NIR Partial least squares Total soluble solids Titratable acidity 

References

  1. Cayuela, J. A. (2008). Vis/NIR soluble solids prediction in intact oranges (Citrus sinensis L.) cv. Valencia Late by reflectance. Postharvest Biology and Technology, 47(1), 75–80.CrossRefGoogle Scholar
  2. Gómez, A. H., Pereira, A. G., & He, Y. (2004) Non-destructive measurement of acidity, soluble solids and firmness of Satsuma Mandarin Using VIS/NIR-Spectroscopy Technique. In: Proc. Intl. Conf. Beijing of World Assoc. Agr. Engineering (CIGR 2004), paper no 20-159D.Google Scholar
  3. Kawano, S., Fujiwara, K., & Iwamoto, M. (1993). Nondestructive determination of sugar content in Satsuma mandarin using near infrared (NIR) transmittance. J Jpn Soc Hortic Sci, 62, 465–470.CrossRefGoogle Scholar
  4. Lammertyn, J., Nicolai, B., Ooms, K., De Smedt, V., & Baerdemaeker, J. (1998). Non-destructive measurement of acidity, soluble solids, and firmness of Jonagold apples using NIR spectroscopy. Transaction of the ASAE, 41(4), 1086–1094.Google Scholar
  5. Lu, H., Jiang, H., Fu, X., Yu, H., Xu, H., & Ying, Y. (2008). Non-invasive measurements of the internal quality of intact ‘Gannan’ navel orange by VIS/NIR spectroscopy. Transactions of the ASABE, 51(3), 1009–1014.Google Scholar
  6. McGlone, V. A., Fraser, D. G., Jordan, R. B., & Künnemeyer, R. (2003). Internal quality assessment of mandarin fruit by VIS/NIR spectroscopy. Journal of Near Infrared Spectroscopy, 11, 323–332.CrossRefGoogle Scholar
  7. Menesatti, P., Zanella, A., D’Andrea, S., Costa, C., Paglia, G., & Pallottino, F. (2009). Supervised multivariate analysis of hyperspectral NIR images to evaluate the starch index of apples. Food And Bioprocess Technology, 2(3), 308–314.CrossRefGoogle Scholar
  8. Miller, W. M., & Zude-Sasse, M. (2004). NIR-based sensing to measure soluble solids content of Florida citrus. Applied Engineering in Agriculture, 20(3), 321–327.Google Scholar
  9. Nicolaï, B. M., Beullens, K., Bobelyn, E., Peirs, A., Saeys, W., Theron, K. I., et al. (2007). Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: a review. Postharvest Biology and Technology, 46(2), 99–118.CrossRefGoogle Scholar
  10. Osborne, S. D., & Künnemeyer, R. (1999). A low-cost system for the grading of kiwifruit. Journal of Near Infrared Spectroscopy, 7, 9–15.CrossRefGoogle Scholar
  11. Pallottino, F., Menesatti, C., Costa, C., Paglia, G., De Salvador, F. R., & Lolletti, D. (2010). Image analysis techniques for automated hazelnut peeling determination. Food And Bioprocess Technology. doi: 10.1007/s11947-009-0211-1.Google Scholar
  12. Park, B., Abbott, J. A., Lee, K. J., Choi, C. H., & Choi, K. H. (2003). Near-infrared diffuse reflectance for quantitative and qualitative measurement of soluble solids and firmness of delicious and gala apples. Transactions of the ASAE, 46(6), 1721–1731.Google Scholar
  13. 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, 137–145.CrossRefGoogle Scholar
  14. Slaughter, D. C., Barrett, D., & Boersig, M. (1996). Non-destructive determination of soluble solids in tomatoes using near infrared spectroscopy. Journal of Food Science, 61, 695–697.CrossRefGoogle Scholar
  15. Steuer, B., Schulz, H., & Läger, E. (2001). Classification and analysis of citrus oils by NIR spectroscopy. Food Chemistry, 72, 113–117.CrossRefGoogle Scholar
  16. Zude, M., Pflanz, M., Kaprielian, C., & Aivazian, B. L. (2008). NIRS as a tool for precision horticulture in the Citrus industry. Journal Biosystems Engineering, 99(3), 455–459.CrossRefGoogle Scholar

Copyright information

© Springer Science + Business Media, LLC 2010

Authors and Affiliations

  • Francesca Antonucci
    • 1
  • Federico Pallottino
    • 1
    Email author
  • Graziella Paglia
    • 1
  • Amedeo Palma
    • 2
  • Salvatore D’Aquino
    • 2
  • Paolo Menesatti
    • 1
  1. 1.CRA-ING Agricultural Engineering Research Unit of the Agriculture Research CouncilMonterotondo scaloItaly
  2. 2.ISPA-CNR Istituto di Scienze delle Produzioni Alimentari-National Research CouncilLi PuntiItaly

Personalised recommendations