Calibration Transfer from Micro NIR Spectrometer to Hyperspectral Imaging: a Case Study on Predicting Soluble Solids Content of Bananito Fruit (Musa acuminata)

2017 ◽  
Vol 11 (4) ◽  
pp. 1021-1033 ◽  
Author(s):  
Yuan-Yuan Pu ◽  
Da-Wen Sun ◽  
Cecilia Riccioli ◽  
Marina Buccheri ◽  
Maurizio Grassi ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Musa Acuminata ◽  
Soluble Solids ◽  
Soluble Solids Content ◽  
Calibration Transfer ◽  
Solids Content

Prediction of Soluble Solids Content of Jujube Fruit Using Hyperspectral Reflectance Imaging

2013 ◽  
Vol 706-708 ◽  
pp. 201-204
Author(s):  
Jian Guo He ◽  
Yang Luo ◽  
Gui Shan Liu ◽  
Shuang Xu ◽  
Zhen Hua Si ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Bp Neural Network ◽  
Imaging Technique ◽  
Principal Component ◽  
Regions Of Interest ◽  
Soluble Solids ◽  
Soluble Solids Content ◽  
Hyperspectral Reflectance ◽  
Jujube Fruit ◽  
Solids Content

To predict soluble solids content (SSC) of jujube fruits, a hyperspectral imaging technique has been used for acquiring reflectance images from 200 samples in the spectral regions of 900-1700nm. Hyperspectral images of jujubes were evaluated from the regions of interest using principal component analysis (PCA) with the goal of selecting five optimal wavelengths (1034, 1109，1231，1291 and 1461nm). Prediction model of SSC (Rp=0.9027, RMSEP=1.9845) were built based on BP neural network. This research has demonstrated the feasibility of implementing hyperspectral imaging technique for sorting jujube fruit for SSC to enhance the product quality and marketability.

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