Effect of fruit moving speed on predicting soluble solids content of 'Cuiguan' pears (Pomaceae pyrifolia Nakai cv. Cuiguan) using PLS and LS-SVM regression

Tong Sun, Hongjian Lin, Huirong Xu, Yibin Ying

Research output: Contribution to journalArticlepeer-review

86 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)86-90
Number of pages5
JournalPostharvest Biology and Technology
Volume51
Issue number1
DOIs
StatePublished - Jan 1 2009

Keywords

  • Fruit moving speed
  • Least squares support vector machines
  • Partial least squares
  • Pear
  • Soluble solids content
  • Visible/near infrared spectroscopy

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