Application of NIR Spectroscopy and Multivariate Analysis for Non-destructive Evaluation of Apple Moisture Content during Ultrasonic Drying

2021 ◽  
pp. 120733
Author(s):  
Amir Malvandi ◽  
Hao Feng ◽  
Mohammed Kamruzzaman
Keyword(s):  
Multivariate Analysis ◽  
Moisture Content ◽  
Nir Spectroscopy ◽  
Non Destructive Evaluation ◽  
Non Destructive

Identification prediction moisture content of Thai coconut sugar (Cocos nucifera L.) using FT-NIR spectroscopy

Food Research ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 382-385
Author(s):  
D. Thumrongchote
Keyword(s):  
Moisture Content ◽  
Cocos Nucifera ◽  
Nir Spectroscopy ◽  
Grocery Stores ◽  
Absorbance Spectrum ◽  
Coconut Tree ◽  
Cocos Nucifera L ◽  
The Cost ◽  
Non Destructive ◽  
Low Glycemic Index

Coconut sugar is a local sugar from the blossoms of a coconut tree. It has been considered a healthy sugar due to its low glycemic index. There is an attempt to add other sugar to it to lower the cost. Thus, this research aimed to identify Thai coconut sugar and to establish models for predicting the moisture content of coconut sugar by using FT-NIR spectroscopy. Thai coconut sugar samples were purchased from local grocery stores in four provinces, online, and the community market. Their moisture contents were varied and equilibrated for 24 hrs prior to the measurements of moisture and FT-NIR spectra. The results showed that FT-NIR spectra of Thai coconut sugar differ from sucrose, glucose and fructose at the absorbance spectrum of 5379-5011 cm-1 . FT-NIR spectroscopy of 54 known moisture samples of Thai coconut sugar was used to obtain a model to predict moisture content. The predicted equation, using the PLS technique with the Spectrum Quant program, was found to give a standard error of prediction (SEP) 0.077% (less than 0.10%), indicating a non-destructive method of accurately and precisely predicting moisture levels in the coconut sugar. The results obtained suggested that FTNIR spectroscopy has the potential to be used as a tool to identify Thai coconut sugar accurately. It can rapidly predict the moisture content in the sample which will be useful in quality control standards.

Non-destructive evaluation of grain angle, moisture content and density of spruce with microwaves

2013 ◽  
Vol 71 (6) ◽  
pp. 779-786 ◽  
Author(s):  
Andreas Aichholzer ◽  
Holger Arthaber ◽  
Christian Schuberth ◽  
Herwig Mayer
Keyword(s):  
Moisture Content ◽  
Grain Angle ◽  
Non Destructive Evaluation ◽  
Non Destructive

Non-destructive evaluation of moisture content of wood material at GPR frequency

2015 ◽  
Vol 77 ◽  
pp. 213-217 ◽  
Author(s):  
Tien Chinh Mai ◽  
Stephen Razafindratsima ◽  
Zoubir Mehdi Sbartaï ◽  
François Demontoux ◽  
Frédéric Bos
Keyword(s):  
Moisture Content ◽  
Wood Material ◽  
Non Destructive Evaluation ◽  
Non Destructive
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