On-line detection of orange soluble solid content using visible and near infrared transmission measurements

2012 ◽  
Author(s):  
Xiaping Fu ◽  
Yibin Ying ◽  
Huirong Xu ◽  
Bing Qi ◽  
Lijuan Xie
Keyword(s):  
Near Infrared ◽  
Solid Content ◽  
Line Detection ◽  
Soluble Solid Content ◽  
Infrared Transmission ◽  
Soluble Solid ◽  
On Line ◽  
Transmission Measurements

On-line detection of Brownheart in Braeburn apples using near infrared transmission measurements

2005 ◽  
Vol 37 (2) ◽  
pp. 142-151 ◽  
Author(s):  
V. Andrew McGlone ◽  
Paul J. Martinsen ◽  
Christopher J. Clark ◽  
Robert B. Jordan
Keyword(s):  
Near Infrared ◽  
Line Detection ◽  
Infrared Transmission ◽  
On Line ◽  
Transmission Measurements

Hyperspectral Imaging for Predicting Soluble Solid Content of Starfruit

2015 ◽  
Vol 73 (1) ◽  
Author(s):  
Feri Candra ◽  
Syed Abd. Rahman Abu Bakar
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Imaging System ◽  
Solid Content ◽  
Partial Least Square ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Soluble Solid Content ◽  
Calibration Model ◽  
Soluble Solid

Hyperspectral imaging technology is a powerful tool for non-destructive quality assessment of fruits. The objective of this research was to develop novel calibration model based on hyperspectral imaging to estimate soluble solid content (SSC) of starfruits. A hyperspectral imaging system, which consists of a near infrared  camera, a spectrograph V10, a halogen lighting and a conveyor belt system, was used in this study to acquire hyperspectral  images of the samples in visible and near infrared (500-1000 nm) regions. Partial least square (PLS) was used to build the model and to find the optimal wavelength. Two different masks were applied for obtaining the spectral data. The optimal wavelengths were evaluated using multi linear regression (MLR). The coefficient of determination (R2) for validation using the model with first mask (M1) and second mask (M2) were 0.82 and 0.80, respectively.

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