scholarly journals Evaluation of Quality Parameters of Apple Juices Using Near-Infrared Spectroscopy and Chemometrics

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Katarzyna Włodarska ◽  
Igor Khmelinskii ◽  
Ewa Sikorska
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Nir Spectroscopy ◽  
Titratable Acidity ◽  
Quality Parameters ◽  
Soluble Solids ◽  
Soluble Solids Content ◽  
Model Optimization ◽  
Important Quality ◽  
Solids Content

Near-infrared (NIR) spectra were recorded for commercial apple juices. Analysis of these spectra using partial least squares (PLS) regression revealed quantitative relations between the spectra and quality- and taste-related properties of juices: soluble solids content (SSC), titratable acidity (TA), and the ratio of soluble solids content to titratable acidity (SSC/TA). Various spectral preprocessing methods were used for model optimization. The optimal spectral variables were chosen using the jack-knife-based method and different variants of the interval PLS (iPLS) method. The models were cross-validated and evaluated based on the determination coefficients (R2), root-mean-square error of cross-validation (RMSECV), and relative error (RE). The best model for the prediction of SSC (R2 = 0.881, RMSECV = 0.277 °Brix, and RE = 2.37%) was obtained for the first-derivative preprocessed spectra and jack-knife variable selection. The optimal model for TA (R2 = 0.761, RMSECV = 0.239 g/L, and RE = 4.55%) was obtained for smoothed spectra in the range of 6224–5350 cm−1. The best model for the SSC/TA (R2 = 0.843, RMSECV = 0.113, and RE = 5.04%) was obtained for the spectra without preprocessing in the range of 6224–5350 cm−1. The present results show the potential of the NIR spectroscopy for screening the important quality parameters of apple juices.

scholarly journals Nondestructive Quality Screening of Green Tomatoes Using Ethylene Gas

HortScience ◽  
1996 ◽  
Vol 31 (4) ◽  
pp. 641b-641
Author(s):  
F. Maul ◽  
S.A. Sargent
Keyword(s):  
Ascorbic Acid Content ◽  
Titratable Acidity ◽  
Quality Parameters ◽  
Soluble Solids ◽  
Short Exposure ◽  
Internal Quality ◽  
Soluble Solids Content ◽  
Nondestructive Technique ◽  
Total Sugars ◽  
Solids Content

The effects of prolonged ethylene exposure on external and internal quality parameters of tomato fruits were studied in order to explore the feasibility of its use as a nondestructive technique for screening immature and inferior quality fruit. `Agriset' and `CPT-5' tomatoes were hand harvested at Stage 1 (green) and held at 20°C and 50 ppm ethylene for 1-7 days. Each 24 hours, fruits reaching Stage 2 (breaker) were removed from C2H4 and transferred to 20°C air for subsequent ripening. Tomatoes were considered at edible maturity upon reaching full red-ripe stage and 4 mm deformation and final quality parameters were determined. For both cultivars, fruits which required prolonged C2H4 exposure to reach Stage 2 had lower overall visual appearance. `Agriset' tomatoes which required short exposure times to C2H4 (1 to 3 days) had somewhat higher quality than those requiring prolonged times (4 or 5 days). Days to reach edible maturity were 9.5 and 7.7, respectively. For the short exposure times, peel color was more intense (higher chroma value), while soluble solids content and total sugars were significantly higher (P = 0.05). Quality of `CPT-5' tomatoes was not adversely affected until requiring 6 or 7 days exposure to C2H4. Days to reach edible maturity decreased from an average of 12.5 to 11.0 for 1 to 5 or for 6 to 7 days exposure, respectively. For fruits requiring 7 days exposure, soluble solids content, total sugars and pH were significantly higher than for those reaching Stage 2 in fewer days. There were no significant differences in titratable acidity or ascorbic acid content for either cultivar.

Nondestructive Detection of Soluble Solids Content of Nanfeng Mandarin Orange Using VIS-NIR Spectroscopy

2011 ◽  
Vol 361-363 ◽  
pp. 1634-1637 ◽  
Author(s):  
Lu Zhang ◽  
Long Xue ◽  
Mu Hua Liu ◽  
Jing Li
Keyword(s):  
Near Infrared ◽  
Scatter Correction ◽  
Nir Spectroscopy ◽  
Rapid Analysis ◽  
Partial Least Square ◽  
Least Square ◽  
Soluble Solids ◽  
Soluble Solids Content ◽  
Solids Content ◽  
Mandarin Orange

This study demonstrated how VIS-NIR spectroscopy can be used in the quantitative, noninvasive probing of soluble solids content (SSC) of mandarin orange. Total 197 mandarin oranges were divided into calibration set (133 samples) and prediction set (64 samples). Multiple scatter correction (MSC) was used to preprocess the collected visible and near infrared (Vis-NIR) spectra (350-1800nm) of mandarin orange. Partial least square (PLS), interval partial least square (IPLS) and synergy interval partial least square (SIPLS) methods were applied for constructing predictive models of SSC. Experimental results showed that the optimal SIPLS model obtained with 10 PLS components and the optimal combinations of intervals were number 5,7,8,9. The correlation coefficient (r) between the predicted and actual SSC was 0.9265 and 0.8577 for calibration and prediction set, respectively. The root mean square error of calibration (RMSEC) and prediction (RMSEP) set was 0.4890 and 0.7113, respectively. In conclusion, the combination of Vis-NIR spectroscopy and SIPLS methods can be used to provide a technique of noninvasive, convenient and rapid analysis for SSC in fruit.

scholarly journals Application of the Non-Destructive NIR Technique for the Evaluation of Strawberry Fruits Quality Parameters

Foods ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 441 ◽  
Author(s):  
Manuela Mancini ◽  
Luca Mazzoni ◽  
Francesco Gagliardi ◽  
Francesca Balducci ◽  
Daniele Duca ◽  
...  
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Infrared Region ◽  
Quality Parameters ◽  
Soluble Solids ◽  
Electromagnetic Spectrum ◽  
Least Squares Regression ◽  
Solids Content ◽  
Non Destructive

The determination of strawberry fruit quality through the traditional destructive lab techniques has some limitations related to the amplitude of the samples, the timing and the applicability along all phases of the supply chain. The aim of this study was to determine the main qualitative characteristics through traditional lab destructive techniques and Near Infrared Spectroscopy (NIR) in fruits of five strawberry genotypes. Principal Component Analysis (PCA) was applied to search for spectral differences among all the collected samples. A Partial Least Squares regression (PLS) technique was computed in order to predict the quality parameters of interest. The PLS model for the soluble solids content prediction was the best performing—in fact, it is a robust and reliable model and the validation values suggested possibilities for its use in quality applications. A suitable PLS model is also obtained for the firmness prediction—the validation values tend to worsen slightly but can still be accepted in screening applications. NIR spectroscopy represents an important alternative to destructive techniques, using the infrared region of the electromagnetic spectrum to investigate in a non-destructive way the chemical–physical properties of the samples, finding remarkable applications in the agro-food market.

scholarly journals Online quantitative analysis of soluble solids content in navel oranges using visible-near infrared spectroscopy and variable selection methods

2014 ◽  
Vol 07 (06) ◽  
pp. 1350065 ◽  
Author(s):  
Yande Liu ◽  
Yanrui Zhou ◽  
Yuanyuan Pan
Keyword(s):  
Quantitative Analysis ◽  
Variable Selection ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Soluble Solids ◽  
Internal Quality ◽  
Soluble Solids Content ◽  
Selection Methods ◽  
Calibration Models ◽  
Solids Content

Variable selection is applied widely for visible-near infrared (Vis-NIR) spectroscopy analysis of internal quality in fruits. Different spectral variable selection methods were compared for online quantitative analysis of soluble solids content (SSC) in navel oranges. Moving window partial least squares (MW-PLS), Monte Carlo uninformative variables elimination (MC-UVE) and wavelet transform (WT) combined with the MC-UVE method were used to select the spectral variables and develop the calibration models of online analysis of SSC in navel oranges. The performances of these methods were compared for modeling the Vis-NIR data sets of navel orange samples. Results show that the WT-MC-UVE methods gave better calibration models with the higher correlation coefficient (r) of 0.89 and lower root mean square error of prediction (RMSEP) of 0.54 at 5 fruits per second. It concluded that Vis-NIR spectroscopy coupled with WT-MC-UVE may be a fast and effective tool for online quantitative analysis of SSC in navel oranges.

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