TY - JOUR
T1 - Effect of fruit moving speed on predicting soluble solids content of 'Cuiguan' pears (Pomaceae pyrifolia Nakai cv. Cuiguan) using PLS and LS-SVM regression
AU - Sun, Tong
AU - Lin, Hongjian
AU - Xu, Huirong
AU - Ying, Yibin
PY - 2009/1/1
Y1 - 2009/1/1
N2 - Visible (Vis)/near infrared (NIR) spectroscopy is an excellent technique for non-destructive fruit quality assessment. This research was focused on evaluating the use of Vis/NIR spectroscopy for measuring soluble solids content (SSC) of intact 'Cuiguan' pears (Pomaceae pyrifolia Nakai cv. Cuiguan) on-line. Also, the effect of fruit moving speed on SSC measurements was investigated. Diffuse transmission spectra were collected using a fiber spectrometer equipped with a 3648-element linear silicon CCD array detector in the wavelength range of 345-1040 nm, and all sample spectra were collected three times at different fruit moving speeds of 0.3 m s-1, 0.5 m s-1 and 0.7 m s-1. Spectral pre-processing such as derivative, standard normal variate transformation (SNV) and multiplicative scatter correction (MSC) was used before calibration. Partial least squares (PLS) and least squares support vector machines (LS-SVM) were used to develop calibration models for SSC. The results show that fruit moving speed has few effects on spectra and model performance at a fruit moving speed of 0.3-0.7 m s-1. At 0.5 m s-1, the best model for SSC was PLS regression coupled with original spectra, its coefficient of determination (R2) and root mean square error of prediction (RMSEP) being 0.916% and 0.530%, respectively.
AB - Visible (Vis)/near infrared (NIR) spectroscopy is an excellent technique for non-destructive fruit quality assessment. This research was focused on evaluating the use of Vis/NIR spectroscopy for measuring soluble solids content (SSC) of intact 'Cuiguan' pears (Pomaceae pyrifolia Nakai cv. Cuiguan) on-line. Also, the effect of fruit moving speed on SSC measurements was investigated. Diffuse transmission spectra were collected using a fiber spectrometer equipped with a 3648-element linear silicon CCD array detector in the wavelength range of 345-1040 nm, and all sample spectra were collected three times at different fruit moving speeds of 0.3 m s-1, 0.5 m s-1 and 0.7 m s-1. Spectral pre-processing such as derivative, standard normal variate transformation (SNV) and multiplicative scatter correction (MSC) was used before calibration. Partial least squares (PLS) and least squares support vector machines (LS-SVM) were used to develop calibration models for SSC. The results show that fruit moving speed has few effects on spectra and model performance at a fruit moving speed of 0.3-0.7 m s-1. At 0.5 m s-1, the best model for SSC was PLS regression coupled with original spectra, its coefficient of determination (R2) and root mean square error of prediction (RMSEP) being 0.916% and 0.530%, respectively.
KW - Fruit moving speed
KW - Least squares support vector machines
KW - Partial least squares
KW - Pear
KW - Soluble solids content
KW - Visible/near infrared spectroscopy
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U2 - 10.1016/j.postharvbio.2008.06.003
DO - 10.1016/j.postharvbio.2008.06.003
M3 - Article
AN - SCOPUS:56249116922
VL - 51
SP - 86
EP - 90
JO - Postharvest Biology and Technology
JF - Postharvest Biology and Technology
SN - 0925-5214
IS - 1
ER -