• Title of article

    Rapid determination of ethylene content in tomatoes using visible and short-wave near-infrared spectroscopy and wavelength selection

  • Author/Authors

    Xie، نويسنده , , Lijuan and Ying، نويسنده , , Yibin and Ying، نويسنده , , Tiejin، نويسنده ,

  • Issue Information
    دوفصلنامه با شماره پیاپی سال 2009
  • Pages
    5
  • From page
    141
  • To page
    145
  • Abstract
    The plant hormone ethylene controls many aspects of development. In tomato, ethylene is an essential component for fruit ripening. In this paper, the study was concentrated on the visible/short-wave near-infrared (Vis/SW NIR) spectroscopy technique for the quantitative analysis of ethylene content in three varieties of tomatoes: non-transgenic tomatoes, and transgenic tomatoes with antisense LeETR1 and LeETR2. The results indicate that the determination of ethylene content in tomatoes could be successfully performed through Vis/SW NIR spectroscopy combined with chemometrics methods including partial least square regression (PLSR) and stepwise multiple linear regression (SMLR). The performances of models using four spectral pretreatment methods – standard normal variate (SNV), multiplicative scatter correction (MSC), first and second derivation – were compared. Wavelengths for ethylene analysis in tomatoes were proposed using SMLR models. The models of ethylene in tomato using the assigned wavelengths show reliable results. The prediction precision of PLSR and SMLR using selected wavelengths was compared. The results show that the modeling of PLSR using the visible region needed less time than that using full region, although the prediction precisions were a little lower. The overall results indicate that Vis/SW NIR spectroscopy combined with wavelength selection could be applied as a nondestructive and rapid tool for the determination of ethylene content in tomatoes.
  • Keywords
    ethylene , Visible and short-wave near-infrared spectroscopy , Tomato , Wavelength selection , Partial Least Square Regression
  • Journal title
    Chemometrics and Intelligent Laboratory Systems
  • Serial Year
    2009
  • Journal title
    Chemometrics and Intelligent Laboratory Systems
  • Record number

    1489514