Nondestructive detection of frying times for soybean oil by NIR-spectroscopy technology with Adaboost-SVM (RBF)

Optik ◽  
2020 ◽  
Vol 206 ◽  
pp. 164248
Author(s):  
Jinlong Li ◽  
Laijun Sun ◽  
Ruonan Li
Keyword(s):  
Soybean Oil ◽  
Nir Spectroscopy ◽  
Nondestructive Detection

Nondestructive detection of insect infested chestnuts based on NIR spectroscopy

2014 ◽  
Vol 87 ◽  
pp. 88-94 ◽  
Author(s):  
Roberto Moscetti ◽  
Ron P. Haff ◽  
Sirinnapa Saranwong ◽  
Danilo Monarca ◽  
Massimo Cecchini ◽  
...  
Keyword(s):  
Nir Spectroscopy ◽  
Nondestructive Detection

Improvement of Prediction Models for Nondestructive Detection of TVB-N Using Dual-Band Vis/NIR Spectroscopic Technique

2017 ◽  
Vol 60 (4) ◽  
pp. 1075-1082 ◽  
Author(s):  
Wenxiu Wang ◽  
Yankun Peng
Keyword(s):  
Light Source ◽  
Spectral Region ◽  
Near Infrared ◽  
Prediction Models ◽  
Great Influence ◽  
Nir Spectroscopy ◽  
Dual Band ◽  
Coefficient Of Determination ◽  
Band Selection ◽  
Nondestructive Detection

Abstract. This article discusses the influence of light source and band selection on prediction model performance. Two spectra acquisition systems for visible (Vis) and near-infrared (NIR) spectroscopy with a ring light source and a point light source were set up and compared based on the coefficient of variation (CV), signal-to-noise ratio (SNR), spectrum area change rate (ACR), and model results. Reflectance spectra of 61 pork samples were collected, and anomalous samples were eliminated by Monte Carlo method based on model cluster analysis. Partial least squares (PLS) models for total volatile basic nitrogen (TVB-N) based on a single spectral region (350-1100 nm or 1000-2500 nm) and a dual spectral region (350-2500 nm) were built to compare the influence of band choice. Based on the optimal chosen band, characteristic wavelengths were selected by competitive adaptive reweighted sampling (CARS), and a new PLS model was established. The results showed that spectra acquired with the ring light source had better stability and achieved optimal prediction models. The dual spectral region, which contained more comprehensive information on TVB-N, yielded better results than any single spectral region. Based on the dual-band spectra, a simplified PLS model using feature variables achieved a coefficient of determination in the prediction set (Rp2) of 0.8767 and standard error of prediction (SEP) of 2.8354 mg per 100 g. The results demonstrated that the choice of light source and modeling band had great influence on prediction results, and improvement of models would promote the application of Vis/NIR spectroscopy in on-line or portable detection. Keywords: Band selection, Light source, Nondestructive detection, Pork, TVB-N, Vis/NIR spectroscopy.

scholarly journals Determination of Free Fatty Acid by FT-NIR Spectroscopy in Esterification Reaction for Biodiesel Production

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Djéssica Tatiana Raspe ◽  
Camila da Silva
Keyword(s):  
Oleic Acid ◽  
Soybean Oil ◽  
Multivariate Calibration ◽  
Reaction Medium ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Biodiesel Production ◽  
Esterification Reaction ◽  
Experimental Conditions ◽  
Batch Mode

This work reports the use of FT-NIR spectroscopy coupled with multivariate calibration to determine the percentage of free fatty acids (FFA) in samples obtained by the esterification of FFA in vegetable oils. The analytical method used as calibration matrix samples of the reaction medium of esterification of oleic acid in soybean oil in proportions of 0.3 to 40 wt% (by weight) of oleic acid obtained under different experimental conditions and utilized the partial least squares (PLS) regression. The efficiency of the method was tested to predict the content of FFA in reactions of esterification of oleic acid in soybean oil catalysed by KSF clay and Amberlyst 15 commercial resin, both in a batch mode. Good Correlations were observed between the FT-NIR/PLS method and the reference method (AOCS). The results confirm that FT-NIR spectroscopy, in combination with multivariate calibration, is a promising technique for monitoring esterification reaction for biodiesel production.

Nondestructive Detection of Water Stress in Tomato Plants by NIR Spectroscopy.

2001 ◽  
Vol 39 (2) ◽  
pp. 75-85 ◽  
Author(s):  
Nancy K. OKAMURA ◽  
Takashi SHIMOMACHI ◽  
Takehiro TAKEMASA ◽  
Tadashi TAKAKURA
Keyword(s):  
Water Stress ◽  
Nir Spectroscopy ◽  
Nondestructive Detection ◽  
Tomato Plants

Rapid and nondestructive detection of multiple adulterants in kudzu starch by near infrared (NIR) spectroscopy and chemometrics

LWT ◽  
2015 ◽  
Vol 61 (2) ◽  
pp. 590-595 ◽  
Author(s):  
Lu Xu ◽  
Wei Shi ◽  
Chen-Bo Cai ◽  
Wei Zhong ◽  
Kang Tu
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Nondestructive Detection

scholarly journals DETERMINAÇÃO DE ÉSTERES ETÍLICOS DE ÁCIDOS GRAXOS POR ESPECTROSCOPIA FT-NIR E CALIBRAÇÃO MULTIVARIADA EM REAÇÕES DE TRANSESTERIFICAÇÃO

e-xacta ◽  
2013 ◽  
Vol 6 (1) ◽  
pp. 27 ◽  
Author(s):  
Djéssica Tatiane Raspe ◽  
Vitor Augusto Garcia ◽  
Camila Da Silva
Keyword(s):  
Soybean Oil ◽  
Multivariate Calibration ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Predictive Ability ◽  
Ethyl Esters ◽  
Biodiesel Production ◽  
Molar Ratio ◽  
Calibration And Validation ◽  
Flame Ionization

<p align="justify">O presente trabalho teve como objetivo estimar a O presente trabalho teve como objetivo estimar a concentração de ésteres etílicos de ácidos graxos (EEAG) em amostras da alcoólise de óleo de soja pela aplicação da espectroscopia FT-NIR associada à calibração multivariada. A amostra estudada foi obtida utilizando hidróxido de sódio como catalisador, em diferentes condições reacionais (temperatura, razão molar óleo, etanol, percentual de catalisador e tempo de reação), com o objetivo de obter amostras em diferentes concentrações de EEAG, a serem utilizadas nas etapas de calibração e validação da metodologia. Este trabalho utilizou a cromatografia gasosa com detector de ionização de chama (CG/DIC) como metodologia de referência e o método de mínimos quadrados parciais (PLS) no tratamento quimiométrico dos dados. Reporta uma alta correlação (r&gt;0,99) entre os dados obtidos pelo método FT-NIR/PLS e reportados pelo método CG/DIC. O modelo quimiométrico desenvolvido apresentou erro médio quadrático de 2,11 e 3,26 para as etapas de calibração e validação da metodologia. Além disso a capacidade de predição da metodologia FT-NIR/PLS foi testada com grupo independente de amostras, obtidas da alcoólise de óleo de soja. Os resultados obtidos demonstram que o método proposto apresenta-se como uma promissora técnica para avaliar o rendimento de reações de alcoólise de óleos vegetais, o que possibilitará o monitoramento de reações para produção de biodiesel.</p><p align="justify">Abstract</p><p align="justify">This study aimed to estimate the concentration of fatty acid ethyl esters (FAEE) in samples from the alcoholysis of soybean oil using FT-NIR spectroscopy associated with multivariate calibration. The samples were obtained using sodium hydroxide as a catalyst at different reaction conditions (temperature, molar ratio oil:ethanol percentage of catalyst and reaction time), in order to obtain samples at different concentrations of FAEE, to be used in steps calibration and validation of the methodology. Gas chromatography with flame ionization detector (GC / FID) was used as the reference method and the method of partial least squares (PLS) used for treatment of chemometric data. It was reported a high correlation (r&gt; 0.99) between the data obtained by the method reported by FT-NIR/PLS and method GC / FID. The chemometric model developed showed mean square error of 2.11 and 3.26 for the steps of calibration and validation of the methodology. The predictive ability of the FT-NIR/PLS method was tested with independent group of samples obtained from the alcoholysis of soybean oil. The results show that the proposed method is presented as a promising technique for evaluating the performance of reactions of alcoholysis of vegetable oils, which will allow the monitoring of reactions for biodiesel production.</p>

Nondestructive detection of pork quality based on dual-band VIS/NIR spectroscopy

2015 ◽  
Author(s):  
Wenxiu Wang ◽  
Yankun Peng ◽  
Yongyu Li ◽  
Xiuying Tang ◽  
Yuanyuan Liu
Keyword(s):  
Nir Spectroscopy ◽  
Dual Band ◽  
Pork Quality ◽  
Nondestructive Detection
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