Prediction of Some Quality Properties of Grape Fruit (cv. Bidaneh Ghermez) Using Non- Destructive Near Infrared Spectroscopy

Document Type : Research Paper


1 Ph. D. Student, Department of Horticultural Science, Tehran University

2 Assistant Professor, Department of Horticultural Science, Tehran University

3 Professor, Department of Horticultural Science, Tehran University

4 Assistant Professor, Agricultural Engineering Research Institute

5 Professor, Laser and Plasma Research Institute, Shahid Beheshti University

6 Ph. D. Student, Laser and Plasma Research Institute, Shahid Beheshti University


Various destructive and non-destructive methods are used to measure the maturity and internal quality parameters of fruits. Destructive methods often consume time and are costly. In this study, the ability of near infrared spectroscopy for prediction of the quality properties such as soluble solids content, titratable acid, pH, total phenol and extract anthocyanin of 'Bidaneh Ghermez' grape was evaluated. For this purpose, after the spectroscopy of ten berries samples in the range of 900-1700 nm, reference and chemical experiments were performed and calibration models were developed using pre-processed spectra and reference measurements. Preprocessing of data was done as combination of many preprocessing. The results of validation of the best models indicated that soluble solids content can be predicted with high accuracy (Rcv= 0.949, SDR=2.838) and pH can be predicted with acceptable accuracy (Rcv= 0.906, SDR=1.993) by near infrared. Titratable acid and total phenol were predicted with fair accuracy by rcv equal to 0.772 and 0.822 and SDR equal to 1.60 and 1.718 respectively. Also, extract anthocyanin of 'Bidaneh Ghermez' grape was not predictable by using near infrared spectroscopy in this experiment.


Abbot, J. A. (1999). Quality measurement of fruits and vegetables.  Postharvest Biology and Technology, 15, 207-225.
Bobelyn, E., Serban, A. S., Nicu, M., Lammertyn, J., Nicoli, B. M. & Saeys, W. (2010).  Postharvest quality predicted by NIR-spectroscopy: Study of the effect of biological variability on spectra and model performance. Postharvest Biology and Technology, 55, 133–143.
Cao, F., Wu, D. & He, Y. (2010). Soluble solids content and pH prediction and varieties discrimination of grapes based on visible–near infrared spectroscopy. Computers and Electronics in Agriculture, 71, 15–18.
Cen, H. & He, Y. (2007). Theory and application of near inferared reflectance spectroscopy in determination of food quality. Trends in Food science and Technology, 18, 72-83.
Chen, P. & Nattuvetty, V. R. (1980). Light transmittance through a region of an intact fruit. Transactions of the ASAE, 23(2), 519–522.
Ebadi, A. & Hadadninejad, M. (2014). Physiology, breeding and production of grapevine. University of Tehran Press. 383pp. (In Farsi).
Fadock, M. (2011). Non-destructive vis-NIR reflectance spectrometry for red wine grape analysis.  M. A. Sc. Thesis. Faculty of Graduate Studies, University of Guelph, Ontario, Canada.
Rahemi, M. (2010). Postharvest: an introduction to the physiology and handling of fruit, vegetables & ornamentals. Shiraz University Press. 437pp. (In Farsi).
Tafazali, E., Hekmati, J. & Firoozeh, P. (1991). Grape. Shiraz University Press. 343pp. (In Farsi).
Jamshidi, B. (2012). None-destructive taste characterization and classification of oranges using Vis/NIR spectroscopy. Ph.D. Thesis. Faculty of Agriculture, University of Tarbiat Modares, Iran. (In Farsi).
Nazoori, F. (2013). Study of the effect of harvest time on quality and postharvest life of fresh and dry pistachio nut. Ph.D. Thesis. Faculty of Agriculture Science and Engineering, University of Tehran, Iran. (In Farsi).
Rabiei, V. (2004). Physiological and morphological responses of some grapevine cultivars to water stress. Ph.D. Thesis. Faculty of Agriculture Science and Engineering, University of Tehran, Iran. (In Farsi).
Geraudie, V., Roger, J. M., Ferrandis, J. L., Gialis, J. M., Barbe, P., Bellon Maurel, V. & Pellenc, R. ( 2009). A revolutionary device for predicting grape maturity based on NIR spectrometry. In: Proceedings of the 8th Fruit, Nut and Vegetable Production Engineering Symposium, 5 -9 Jan., University of Concepción, Concepción, Chile. pp. 1-8.
Giovenzana, V., Beghi, R., Mena, A., Civelli, R., Guidetti, R., Best, S. & Leon G, L. F. (2013). Quick quality evaluation of Chilean grape by a portable vis/NIR device. Acta Horticulture, 978, 93-100.
Golic, M. & Walsh, K. B. (2006). Robustness of calibration models based on near infrared spectroscopy to the in-line grading of stone fruit for total soluble solids. Analytica Chimica Acta, 555, 286-291.
Guidetti, R., Beghi, R. & Bodria, L. (2010). Evaluation of grape quality parameters by a simple VIS/NIR system. Transactions of the ASABE, 53(2), 477-484.
Jamshidi, B., Minaei, S., Mohajerani, E. & Ghassemian, H. (2012). Reflectance Vis/NIR spectroscopy for nondestructive taste characterization of Valencia oranges. Computers and Electronics in Agriculture, 85, 64-69.
 Jaren, C., Ortuno, J. C., Arazuri, S., Arana, J. I. & Salvadores, M. C. (2001). Sugar determination in grapes using NIR technology. International Journal of Infrared and Millimeter Waves, 22(10), 1513-1530.
Kader, A. A. (1999). Fruit maturity, ripening and quality relationships. Acta Horticulture, 458, 203-208.
Kader, A. A. (2003). Postharvest technology of horticultural crops. University of California, Agriculture and Natural Resources, UCD Press, 535pp.
Lee, J., Durst, R. W. & Wrolstad, R. E. (2005). Determination of total monomeric anthocyanin pigment content of fruit juices, beverages, natural colorants, and wines by the pH differential method: collaborative study. Journal of AOAC International, 88(5), 1269-1287.
Lu, R. (2001). Predicting firmness and sugar content of sweet cherries using near-infrared diffuse reflectance spectroscopy. Transactions of the ASAE, 44(5), 1265–1271.
Mitcham, B., Cantwell, M. & Kader, A. (1996). Methods for determining quality of fresh commodities. Perishable Handling Newsletter, 85, 1-5.
Nicolai, B. M., Beullens, K., Bobelyn, E., Peirs, A., Saeys, W., Theron, K. I., Karen, I. T. & Lammertyn, J. (2007). Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review. Postharvest Biology and Technology, 46, 99–118.
Nicolai, B. M., Defraeye, T., Ketelaere, B. D., Herremans, E., Hertog, M. L., Saeys, W., Torricelli, A., Vandendriessche, T. & Verboven, P. (2014). Nondestructive measurement of fruit and vegetable quality. Food Science Technology, 5, 285- 312.
Raja, H. N.,  Dara, N. E., Hobaika, Z., Boussetta, N., Vorobiev, E., Maroun, R. G. & Louka, N. (2014). Extraction of total phenolic compounds, flavonoids, anthocyanins and tannins from grape byproducts by response surface methodology. Influence of solid-liquid ratio, particle size, time, temperature and solvent mixtures on the optimization process. Food and Nutrition Sciences, 5, 397- 409.
Shao, Y., He, Y., Gomez, A. H., Pereir, A. G., Qiu, Z. &  Zhang, Y. (2007). Visible/near infrared spectrometric technique for nondestructive assessment of tomato ‘Heatwave’ (Lycopersicum esculentum) quality characteristics. Journal of Food Engineering, 81, 672-678.
 Wold, S., Sjostrom, M. and Erikson, L. (2007). PLS-regression: a basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems, 58, 109-130.28.
Volume 46, Issue 4 - Serial Number 4
January 2016
Pages 371-378
  • Receive Date: 04 April 2015
  • Revise Date: 03 May 2016
  • Accept Date: 21 April 2015
  • First Publish Date: 22 December 2015