NON-DESTRUCTIVE PREDICTION OF QUALITY PARAMETERS OF SWEET LEMON (CITRUS LIMETTA) THROUGH VIS/SWNIR SPECTROSCOPY

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MOOMKESH SHAHRAM; MIREEI SEYED AHMAD; SADEGHI MORTEZA; NAZERI MAJID

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Journal: Iranian Journal of Biosystems Engineering Year:2017 | Volume:47 | Issue:4 Page(s): 603-613

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Title

NON-DESTRUCTIVE PREDICTION OF QUALITY PARAMETERS OF SWEET LEMON (CITRUS LIMETTA) THROUGH VIS/SWNIR SPECTROSCOPY

Author(s)

MOOMKESH SHAHRAM | MIREEI SEYED AHMAD | SADEGHI MORTEZA | NAZERI MAJID | Issue Writer Certificate

Keywords

CORRELATION COEFFICIENTQ1

INTERACTANCEQ1

PARTIAL LEAST SQUARESQ1

PREPROCESSINGQ2

ROOT MEAN SQUARE ERRORQ2

TRANSMISSIONQ2

Abstract

Among different attributes for the distinction of maturity and quality evaluation of sweet lemon, Soluble Solids Content (SSC), Titratable Acidity (TA), and Moisture Content (MC) are considered as the most important ones. Throughout the present study, the potential of Visible and Short Wavelength Near-Infra Red (Vis/SWNIR) spectroscopy for nondestructive predicting of SSC, MC, and TA of sweet lemon was investigated. The spectra of 120 sweet lemon samples were acquired in the INTERACTANCE and TRANSMISSION modes and within the wavelength region of 400 to 1100 nm. Different PREPROCESSING methods, including Savitzky-Golay (SG) algorithm, Multiplicative Scatter Correction (MSC), Baseline Correction (BC), Standard Normal Variate (SNV), 1st derivative, and a combination of these methods were applied to the raw spectra. The most appropriate PREPROCESSING methods were then selected for building the predictive models using PARTIAL LEAST SQUARES (PLS) method. The results showed that the most appropriate SSC and MC predictive models were achieved in the INTERACTANCE mode while the most desirable TA predictive model was obtained in the TRANSMISSION mode. Among three quality parameters, the most suitable models resulted in the prediction of SSC, MC, and TA, respectively. The SSC with a CORRELATION COEFFICIENT (rp) of 0.87 and a Root Mean Squares Error of Prediction (RMSEP) of 0.5oBrix, MC with an rp of 0.88 and an RMSEP of 0.57%, as well as TA with a rp of 0.74 and an RMSEP of 0.0076% could be predicted.

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APA: Copy

MOOMKESH, SHAHRAM, MIREEI, SEYED AHMAD, SADEGHI, MORTEZA, & NAZERI, MAJID. (2017). NON-DESTRUCTIVE PREDICTION OF QUALITY PARAMETERS OF SWEET LEMON (CITRUS LIMETTA) THROUGH VIS/SWNIR SPECTROSCOPY. IRANIAN JOURNAL OF BIOSYSTEMS ENGINEERING (IRANIAN JOURNAL OF AGRICULTURAL SCIENCES), 47(4), 603-613. SID. https://sid.ir/paper/144381/en

Vancouver: Copy

MOOMKESH SHAHRAM, MIREEI SEYED AHMAD, SADEGHI MORTEZA, NAZERI MAJID. NON-DESTRUCTIVE PREDICTION OF QUALITY PARAMETERS OF SWEET LEMON (CITRUS LIMETTA) THROUGH VIS/SWNIR SPECTROSCOPY. IRANIAN JOURNAL OF BIOSYSTEMS ENGINEERING (IRANIAN JOURNAL OF AGRICULTURAL SCIENCES)[Internet]. 2017;47(4):603-613. Available from: https://sid.ir/paper/144381/en

IEEE: Copy

SHAHRAM MOOMKESH, SEYED AHMAD MIREEI, MORTEZA SADEGHI, and MAJID NAZERI, “NON-DESTRUCTIVE PREDICTION OF QUALITY PARAMETERS OF SWEET LEMON (CITRUS LIMETTA) THROUGH VIS/SWNIR SPECTROSCOPY,” IRANIAN JOURNAL OF BIOSYSTEMS ENGINEERING (IRANIAN JOURNAL OF AGRICULTURAL SCIENCES), vol. 47, no. 4, pp. 603–613, 2017, [Online]. Available: https://sid.ir/paper/144381/en

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