Volume 13, Issue 4 (2011)                   JAST 2011, 13(4): 517-526 | Back to browse issues page

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Nikbakht A, Tavakkoli Hashjin T, Malekfar R, Ghobadian B. Nondestructive Determination of Tomato Fruit Quality Parameters Using Raman Spectroscopy. JAST. 13 (4) :517-526
URL: http://journals.modares.ac.ir/article-23-4685-en.html
1- Department of Mechanical Engineering in Agricultural Machinery, Faculty of Agriculture, Urmia University, Urmia, Islamic Republic of Iran.
2- Department of Agricultural Machinery Engineering, Faculty of Agriculture, Tarbiat Modares University, P. O. Box: 14115-336, Tehran, Islamic Republic of Iran.
3- Department of Molecular and Atomic Physics, Faculty of Sciences, Tarbiat Modares University, Tehran, Islamic Republic of Iran.
Abstract:   (4429 Views)
Tomato is a major fruit, as well as a major food science product. There is a need of determining the quality attributes of this fruit (nondestructively) due to the increasing demand of the in agro-industrially controlled areas. Most of the commonly employed techniques are time consuming and involve a considerable degree of manual work. Sample preparation, juice making, and laboratory tests are among the limitations. Raman spectroscopy was applied in this study to measure such important quality parameters of tomato as SSC, pH and color. A dispersive Raman instrument was employed and reference analyses were carried out to make calibration models regarding the spectral features and target attributes. Analysis of the spectra revealed that all the three characteristic bands of cartenoids, lycopene, and carotene, were significantly recognizable. Also there were several strong to medium bands recognized as related to carbohydrates. Principal Component Regression (PCR) and Partial Least Square (PLS) were selected as the multivariate calibration models. The prediction models proved to be robust resulting in a desirable mapping between the spectra and output attributes. The Root Mean Square Error of Predictions (RMSEP) through PLS and PCR for modeling the color index using the whole spectrum was obtained as 0.33 and 0.38, respectively. RMSEP for mapping the SSC using PLS and PCR models was resulted in respective figures of 0.30 and 0.38. PCA interpretation depicted that Raman spectra could make a favorable distinction among the samples based on their maturity stages. As a result, there is a great potential to use Raman spectroscopy in industrial approach and in line control.
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Received: 2011/02/5 | Accepted: 2011/02/5 | Published: 2011/02/5

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