FOOD SCIENCE ›› 2010, Vol. 31 ›› Issue (14): 258-263.doi: 10.7506/spkx1002-6630-201014059

• Analysis & Detection • Previous Articles     Next Articles

Non-destructive Measurement of Soluble Solids, Vitamin C and Titratable Acidity of Hamlin Sweet Orange using Vis/NIR Spectrometry

MAO Sha-sha1，ZENG Ming1，HE Shao-lan2，ZHENG Yong-qiang2，YI Shi-lai2，WANG Liang1，ZHAO Xu-yang1，DENG Lie2,*   

  1. 1. College of Horticulture and Landscape Architecture, Southwest University, Chongqing 400716, China ；
    2. Citrus Research Institute, Chinese Academy of Agricultural Sciences, Chongqing 400712, China
  • Received:2010-03-05 Online:2010-07-15 Published:2010-12-29
  • Contact: DENG Lie2,* E-mail:liedeng@163.com

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Abstract:

The potential of reflectance visible/near infrared spectroscopy (VNIRS) was investigated for measuring total soluble solids (TSS), vitamin C (VC) and titratable acidity (TA) in Hamlin orange fruit (Citrus sinensis L.). VNIR spectra of Hamlin orange fruits harvested at different times were measured and related with the contents of TSS, VC and TA by partial least squares (PLS) method to establish nondestructive models for predicting the TSS, VC and TA in the fruit. Meanwhile, the effects of different spectral pretreatment methods and spectral waveband range on the performance of the established models were also investigated. The results showed that the PLS models of original spectra within the waveband range from 400 to 1000 nm gave optimal predictions for TSS, VC and TA. Through multiple scatter calibration and 5-point moving-average smoothing pretreatment, an optimal TSS prediction model was obtained, with a correlation coefficient of 0.995 and a root mean square error of calibration (RMSEC) of 0.026% for the calibration sample set and a correlation coefficient of 0.992 and a root mean square error of prediction (RMSEP) of 0.028% for the validation sample set. Multiple scatter calibration and 9-point moving-average smoothing pretreatment gave an optimal TA prediction model, with a correlation coefficient of 0.997 and a RMSEC of 0.012% for the calibration sample set and a correlation coefficient of 0.997 and a RMSEP of 0.013% for the validation sample set. An optimal VC prediction model was also obtained through multiple scatter calibration and 9-point moving-average smoothing pretreatment, with a correlation coefficient of 0.998 and a RMSEC of 0.009% for the calibration sample set and a correlation coefficient of 0.999 and a RMSEP of 0.009 for the validation sample set. These results suggest that the use of a sample set comprising Hamlin organe fruits collected at different harvesting times can improve the accuracy of a PLS prediction model.

Key words: Hamlin sweet orange, internal quality, Vis/NIR spectroscopy, non-destructive measurement

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