Prediction of Soluble Solids Content During Storage of Apples with Different Maturity Based on VIS / NIR Spectroscopy

2020 ◽  
Author(s):  
Bo Zhang ◽  
Mengsheng Zhang ◽  
Maosheng Shen ◽  
Hao Li ◽  
Haihui Zhang ◽  
...  
Keyword(s):  
Nir Spectroscopy ◽  
Soluble Solids ◽  
Soluble Solids Content ◽  
Solids Content

Non-destructive measurement of firmness and soluble solids content in bell pepper using NIR spectroscopy

2009 ◽  
Vol 94 (3-4) ◽  
pp. 267-273 ◽  
Author(s):  
Pathompong Penchaiya ◽  
Els Bobelyn ◽  
Bert E. Verlinden ◽  
Bart M. Nicolaï ◽  
Wouter Saeys
Keyword(s):  
Nir Spectroscopy ◽  
Bell Pepper ◽  
Soluble Solids ◽  
Soluble Solids Content ◽  
Solids Content ◽  
Destructive Measurement ◽  
Non Destructive

Comparison of Multivariate Calibrations for the Determination of Soluble Solids Content of Tea Beverage Using UV-VIS-NIR Spectroscopy

2012 ◽  
Vol 236-237 ◽  
pp. 83-88 ◽  
Author(s):  
Wei Qiang Luo ◽  
Hai Qing Yang ◽  
Wei Cheng Dai
Keyword(s):  
Least Squares ◽  
Multivariate Calibration ◽  
Fiber Type ◽  
Nir Spectroscopy ◽  
Soluble Solids ◽  
Coefficient Of Determination ◽  
Support Vector ◽  
Soluble Solids Content ◽  
Solids Content

Ultra-violet, visible and near infrared (UV-VIS-NIR) spectroscopy combined with chemometrics was investigated for fast determination of soluble solids content (SSC) of tea beverage. In this study, a total of 120 tea samples with SSC range of 4.0-9.5 ºBrix were tested. Samples were randomly divided for calibration (n=90) and independent validation (n=30). Spectra were collected by a mobile fiber-type UV-VIS-NIR spectrophotometer in transmission mode with recorded wavelength range of 203.64-1128.05 nm. Various calibration approaches, i.e., principal components analysis (PCA), partial least squares (PLS) regression, least squares support vector machine (LSSVM) and back propagation artificial neural network (BPANN), were investigated. The combinations of PCA-BPANN, PCA-LSSVM, PLS-BPANN and PLS-LSSVM were also investigated to build calibration models. Validation results indicated that all these investigated models achieved high prediction accuracy. Especially, PLS-LSSVM achieved best performance with mean coefficient of determination (R2) of 0.99, root-mean-square error of prediction (RMSEP) of 0.12 and residual prediction deviation (RPD) of 15.16. This experiment suggests that it is feasible to measure SSC of tea beverage using UV-VIS-NIR spectroscopy coupled with appropriate multivariate calibration, which may allow using the proposed method for off-line and on-line quality supervision in the production of soft drink.

Nondestructive Detection of Soluble Solids Content in Navel Orange Based on GEP Algorithm

2014 ◽  
Vol 988 ◽  
pp. 552-556
Author(s):  
Long Sheng Huang ◽  
Wen Xia Yang ◽  
Yu Bo Liao ◽  
Qi Zhong
Keyword(s):  
Genetic Algorithm ◽  
Gene Expression Programming ◽  
Nir Spectroscopy ◽  
Soluble Solids ◽  
Navel Orange ◽  
Soluble Solids Content ◽  
Fiber Optic Probe ◽  
Data Points ◽  
Optic Probe ◽  
Solids Content

A rapid quantification technique was developed and validated for nondestructively quantifying the soluble solids content of navel orange using NIR spectroscopy in conjunction with Gene expression programming (GEP) algorithm and genetic algorithm (GA).The spectra were recorded in the NIR region using the fiber optic probe method. Four data points of the navel orange NIR spectra were selected by GEP algorithm and genetic algorithm by cross validation. In our experiment, the mean standard error Ribetween the prediction values and the real values in the train group is 0.0256, and the validation group is 0.0194, the results show that the proposed method can be built to a concise easily computed model, which has higher accuracy.

Non-Destructive Measurement of Soluble Solids Content and Vitamin C in Gannan Navel Oranges by Vis-NIR Spectroscopy

2011 ◽  
Vol 9 (3) ◽  
pp. 1133-1139 ◽  
Author(s):  
Yande Liu ◽  
Xudong Sun ◽  
Xiaoling Dong ◽  
Aiguo Ouyang ◽  
Rongjie Gao ◽  
...  
Keyword(s):  
Vitamin C ◽  
Nir Spectroscopy ◽  
Soluble Solids ◽  
Soluble Solids Content ◽  
Solids Content ◽  
Destructive Measurement ◽  
Non Destructive

scholarly journals Determination of soluble solids content in Prunus avium by Vis/NIR equipment using linear and non-linear regression methods

2020 ◽  
Vol 17 (4) ◽  
pp. e0207
Author(s):  
Victoria Lafuente ◽  
Luis J. Herrera ◽  
Jesús Val ◽  
Razvan Ghinea ◽  
Angel I. Negueruela
Keyword(s):  
Prunus Avium ◽  
Nir Spectroscopy ◽  
Soluble Solids ◽  
Soluble Solids Content ◽  
Regression Methods ◽  
Variable Selection Method ◽  
Different Seasons ◽  
Solids Content ◽  
Calibration Equations

Aim of study: Developing models to determine soluble solids content (SSC) in cherry trees by means of Vis/NIR spectroscopy.Area of study: The Spanish Autonomous Community of Aragón (Spain).Material and methods: Vis/NIR spectroscopy was applied to Prunus avium fruit ‘Chelan’ (n=360) to predict total SSC using a range 400-2420 nm. Linear (PLS) and nonlinear (LSSVM) regression methods were applied to establish prediction models.Main results: The two regression methods applied obtained similar results (Rcv2=0.97 and Rcv2=0.98 respectively). The range 700-1060 nm attained better results to predict SSC in different seasons. Forty variables selected according to the variable selection method achieved Rcv2 value, 0.97 similar than full range.Research highlights: The development of this methodology is of great interest to the fruit sector in the area, facilitating the harvest for future seasons. Further work is needed on the development of the NIRS methodology and on new calibration equations for other varieties of cherry and other species.

scholarly journals Prediction of Soluble Solids Content of Chestnut using VIS/NIR Spectroscopy

2013 ◽  
Vol 38 (3) ◽  
pp. 185-191 ◽  
Author(s):  
Soo Hyun Park ◽  
Ki Taek Lim ◽  
Hoyoung Lee ◽  
Soo Hee Lee ◽  
Sang Ha Noh
Keyword(s):  
Nir Spectroscopy ◽  
Soluble Solids ◽  
Soluble Solids Content ◽  
Solids Content
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