scholarly journals Feasibility Study of the Use of Handheld NIR Spectrometer for Simultaneous Authentication and Quantification of Quality Parameters in Intact Pineapple Fruits

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Charles L. Y. Amuah ◽  
Ernest Teye ◽  
Francis Padi Lamptey ◽  
Kwasi Nyandey ◽  
Jerry Opoku-Ansah ◽  
...  
Keyword(s):  
Near Infrared ◽  
Nearest Neighbor ◽  
Multivariate Calibration ◽  
Principal Component ◽  
Quality Parameters ◽  
Soluble Solids ◽  
Least Squares Regression ◽  
Total Soluble Solids ◽  
Linear Discriminant ◽  
Identification Rate

The potential of predicting maturity using total soluble solids (TSS) and identifying organic from inorganic pineapple fruits based on near-infrared (NIR) spectra fingerprints would be beneficial to farmers and consumers alike. In this study, a portable NIR spectrometer and chemometric techniques were combined to simultaneously identify organically produced pineapple fruits from conventionally produced ones (thus organic and inorganic) and also predict total soluble solids. A total of 90 intact pineapple fruits were scanned with the NIR spectrometer while a digital refractometer was used to measure TSS from extracted pineapple juice. After attempting several preprocessing techniques, multivariate calibration models were built using principal component analysis (PCA), K-nearest neighbor (KNN), and linear discriminant analysis (LDA) to identify the classes (organic and conventional pineapple fruits) while partial least squares regression (PLSR) method was used to determine TSS of the fruits. Among the identification techniques, the MSC-PCA-LDA model accurately identified organic from conventionally produced fruits at 100% identification rate. For quantification of TSS, the MSC-PLSR model gave Rp = 0.851 and RMSEC = 0.950 °Brix, and Rc = 0.854 and RMSEP = 0.842 °Brix at 5 principal components in the calibration set and prediction set, respectively. The results generally indicated that portable NIR spectrometer coupled with the appropriate chemometric tools could be employed for rapid nondestructive examination of pineapple quality and also to detect pineapple fraud due to mislabeling of conventionally produced fruits as organic ones. This would be helpful to farmers, consumers, and quality control officers.

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 Application of visible-near infrared spectroscopy to evaluate the quality of button mushrooms

2018 ◽  
Vol 27 (1) ◽  
pp. 38-45 ◽  
Author(s):  
Valentina Giovenzana ◽  
Alessio Tugnolo ◽  
Andrea Casson ◽  
Riccardo Guidetti ◽  
Roberto Beghi
Keyword(s):  
Moisture Content ◽  
Near Infrared ◽  
Distribution Channel ◽  
Nir Spectroscopy ◽  
Quality Standard ◽  
Quality Parameters ◽  
Soluble Solids ◽  
Least Squares Regression ◽  
Physical Damage ◽  
Reference Quality

The Agaricus bisporus mushroom is one of the most cultivated and consumed mushrooms in the world, thanks to its delicacy, nutritional value and flavour. The quality evaluation of the A. bisporus during the harvest is generally established by a visual check by trained operators. This method complies with the request of the Distribution Channel (DC) to retailers and guarantees very low physical damage to the mushrooms; nevertheless, it is subjective and it does not guarantee the highest quality standard for the consumer. The aim of this study was to test the use of visible/near infrared (vis/NIR) reflectance spectroscopy (400–1000 nm) to objectively evaluate the quality parameters of A. bisporus mushrooms. A total of 167 samples of A. bisporus mushrooms were harvested according to the main DC purchasing standards. The vis/NIR analyses were performed the day of sampling just before the physico-chemical analyses (sizes, firmness, soluble solids content and moisture content) used as reference quality parameters. The vis/NIR spectra were correlated to reference measures in order to build predictive models using the partial least squares regression method. Calculated models gave positive results regarding the prediction of the moisture content (r2(pred) = 0.78) and firmness (r2(pred) = 0.78). Results of this explorative study could be considered encouraging and demonstrate the applicability of vis/NIR spectroscopy on A. bisporus as a rapid technique (i) to monitor the productive process directly at the company, (ii) to standardize the harvest moment, and (iii) to support DC’s buyers’ choices, nowadays exclusively based on product external characteristics.

Use of NIR Spectroscopy Combined with Recognition Methods for the Identification of Black Teas from Different Regions

2012 ◽  
Vol 503-504 ◽  
pp. 1601-1604 ◽  
Author(s):  
Jing Ming Ning ◽  
Sheng Peng Wang ◽  
Zheng Zhu Zhang ◽  
Xiao Chun Wan
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Nearest Neighbor ◽  
Recognition Rate ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Black Tea ◽  
Rapid Identification ◽  
K Nearest Neighbor ◽  
Identification Rate

Near-infrared (NIR) spectroscopy, combined with pattern recognition, was applied in this study for the rapid identification of Black tea from different origins.The K-Nearest Neighbor model recognition method was used for the establishment of a tea origin recognition model, which involved optimization of the principal component factors (PCs) and the identification rate using a cross-validation method. The experimental results showed that, after standard normal variant spectral preprocessing, an optimized model was obtained when the PCs were equal to three, with the cross-validation recognition rate and the predicted recognition rate reaching 98.1% and 93.3%, respectively.

scholarly journals NIR model development and robustness in prediction of melon fruit total soluble solids

2006 ◽  
Vol 57 (4) ◽  
pp. 411 ◽  
Author(s):  
J. A. Guthrie ◽  
C. J. Liebenberg ◽  
K. B. Walsh
Keyword(s):  
Near Infrared ◽  
Multivariate Calibration ◽  
Mean Squared Error ◽  
Scatter Correction ◽  
Model Development ◽  
Equatorial Region ◽  
Soluble Solids ◽  
Eating Quality ◽  
Spectral Window ◽  
Total Soluble Solids

Near infrared spectroscopy (NIRS) can be used for the on-line, non-invasive assessment of fruit for eating quality attributes such as total soluble solids (TSS). The robustness of multivariate calibration models, based on NIRS in a partial transmittance optical geometry, for the assessment of TSS of intact rockmelons (Cucumis melo) was assessed. The mesocarp TSS was highest around the fruit equator and increased towards the seed cavity. Inner mesocarp TSS levels decreased towards both the proximal and distal ends of the fruit, but more so towards the proximal end. The equatorial region of the fruit was chosen as representative of the fruit for near infrared assessment of TSS. The spectral window for model development was optimised at 695–1045 nm, and the data pre-treatment procedure was optimised to second-derivative absorbance without scatter correction. The ‘global’ modified partial least squares (MPLS) regression modelling procedure of WINISI (ver. 1.04) was found to be superior with respect to root mean squared error of prediction (RMSEP) and bias for model predictions of TSS across seasons, compared with the ‘local’ MPLS regression procedure. Updating of the model with samples selected randomly from the independent validation population demonstrated improvement in both RMSEP and bias with addition of approximately 15 samples.

scholarly journals Non-Destructive Quality Measurement for Three Varieties of Tomato Using VIS/NIR Spectroscopy

2021 ◽  
Vol 13 (19) ◽  
pp. 10747
Author(s):  
Khadija Najjar ◽  
Nawaf Abu-Khalaf
Keyword(s):  
Near Infrared ◽  
Quality Measurement ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Titratable Acidity ◽  
Quality Parameters ◽  
Partial Least Square ◽  
Least Square ◽  
Soluble Solids ◽  
Non Destructive

The non-destructive visible/near-infrared (VIS/NIR) spectroscopy is a promising technique in determining the quality of agricultural commodities. Therefore, this study aimed to examine the ability of VIS/NIR spectroscopy (550–1100 nm) to distinguish between three different varieties of tomato (i.e., Ekram, Harver and Izmer), as well as to predict the quality parameters of tomato, such as soluble solids content (SSC), titratable acidity (TA), taste (SSC/TA) and firmness. Ninety intact samples from three tomato varieties were used. These samples were examined using VIS/NIR spectroscopy and quality parameters were also measured using traditional methods. Principal component analysis (PCA) and partial least square (PLS) were carried out. The results of PCA showed the ability of VIS/NIR spectroscopy to distinguish between the three varieties, where two PCs explained about 99% of the total variance in both calibration and validation sets. Moreover, PLS showed the possibility of modelling quality parameters. The correlation coefficient (R2) and the ratio of performance deviation (RPD) for all quality parameters (except for firmness) were found to be higher than 0.85 and 2.5, respectively. Thus, these results indicate that the VIS/NIR spectroscopy can be used to discriminate between different varieties of tomato and predict their quality parameters.

Effect of Both Homogenisation and Storage on the Spectra of Red Grapes and on the Measurement of Total Anthocyanins, Total Soluble Solids and pH by Visual near Infrared Spectroscopy

2005 ◽  
Vol 13 (4) ◽  
pp. 213-223 ◽  
Author(s):  
D. Cozzolino ◽  
W.U. Cynkar ◽  
R.G. Dambergs ◽  
L. Janik ◽  
M. Gishen
Keyword(s):  
Near Infrared ◽  
Analytical Data ◽  
Frozen Storage ◽  
Principal Component ◽  
Soluble Solids ◽  
Fresh Sample ◽  
Total Soluble Solids ◽  
Red Grapes ◽  
Total Anthocyanins ◽  
And Storage

The effect of homogenisation and storage on both the visible (Vis) and near infrared (NIR) spectra as well as on the calibration performance for the measurement of total anthocyanins (colour), total soluble solids (TSS) and pH in red grapes were investigated. Homogenates obtained from fresh and previously frozen red grapes (overnight freezing for 24 hours, and after one, three, six and 12 months frozen storage) were scanned in reflectance mode (400–2500 nm) using a monochromator instrument (Foss NIRSystems 6500). Principal component analysis was used to examine the influence of homogeniser type and frozen storage on the spectra. Neither the homogeniser type used nor overnight freezing had visual effects on the spectra. Spectra and analytical data were used to develop partial least squares calibrations to quantify the influence of storage on the measurement of total anthocyanins (colour), TSS and pH. When cross-predicting between fresh and frozen samples, the standard error of prediction was slightly increased when compared with calibrations developed on fresh samples alone. On the other, hand frozen samples were predicted well with the fresh sample calibration for the chemical parameters evaluated. However, although there may be some increases in error, these results suggest that it might be possible to use Vis-NIR calibrations developed on frozen samples alone to measure the concentration of total anthocyanins, TSS and pH in either fresh or frozen samples after appropriate slope and bias correction.

scholarly journals Monitoring of water spectral patterns of lactobacilli development as a tool for rapid selection of probiotic candidates

2017 ◽  
Vol 25 (6) ◽  
pp. 423-431 ◽  
Author(s):  
Aleksandar Slavchev ◽  
Zoltan Kovacs ◽  
Haruki Koshiba ◽  
Gyorgy Bazar ◽  
Bernhard Pollner ◽  
...  
Keyword(s):  
Spectral Data ◽  
Near Infrared ◽  
Wavelength Region ◽  
Principal Component ◽  
Lactobacillus Bulgaricus ◽  
Probiotic Bacteria ◽  
Least Squares Regression ◽  
Linear Discriminant ◽  
Spectral Patterns

Nowadays a quick and inexpensive method, which allows rapid, in vivo comprehensive probiotic bacteria identification, is needed. To elucidate a new concept to evaluate probiotic bacteria, near infrared spectroscopy with aquaphotomics were applied to monitor the growth of eight Lactobacillus bulgaricus and one Lactobacillus gasseri bacteria strains. Their resistance to low pH (1.8) in the presence of pepsin and bile were measured and further used as reference data for analysis of the simultaneously acquired spectral data. The acquired spectral data in the region of 1100–1300 nm were subjected to various methods for multivariate data analyses—principal component analysis, linear discriminant analysis, soft independent modeling of class analogy, and partial least squares regression. The results showed high accuracy of bacteria strains classification according to their resistance and the potential of the tested wavelength region for rapid selection and prediction of some basic phenotypic characteristics of probiotic candidates. Results of the current study also revealed different suitability of each growth stage when using near infrared spectra for the classification of bacteria strains.

scholarly journals Potential of fourier transformed near-infrared (FT-NIR) spectroscopy for rapid analysis of elderberry (Sambucus nigra L.) fruits

2019 ◽  
Vol 37 (No. 1) ◽  
pp. 21-28 ◽  
Author(s):  
Virág Csorba ◽  
Marietta Fodor ◽  
Szilvia Kovács ◽  
Magdolna Tóth
Keyword(s):  
Near Infrared ◽  
Reference Data ◽  
Scatter Correction ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Titratable Acidity ◽  
Soluble Solids ◽  
Breeding Method ◽  
Linear Discriminant ◽  
Fruit Samples

Fruit samples were analysed to investigate the suitability of Fourier transform near infrared spectroscopy (FT-NIR) for the rapid discrimination of elderberry genotypes. Parallel analysis with classical chemical techniques and spectral measurements was performed on 11 cultivars originating from various European countries. The titratable acidity (TA) and soluble solids content (SSC) of the fruit, and the geographical origin and breeding method of the cultivar were used as reference data. Three spectrum transformation methods (standard normal variation, multiplicative scatter correction and first derivative) were applied in the calibration process. The statistical analysis and comparison of the samples was carried out using principal component analysis (PCA) and linear discriminant analysis (LDA). In all cases the analysis demonstrated a correlation between the spectra and both the chemical traits (TA and SSC) of the fruit and the other reference data, indicating that pattern recognition was not a chance occurrence. This work provides the first evidence that the NIR technique can be successfully applied to distinguish between elderberry genotypes on the basis of fruit quality, thus opening up new possibilities in breeding cultivars for food industry purposes.

scholarly journals Preliminary Insights in Sensory Profile of Sweet Cherries

Foods ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 612
Author(s):  
Vânia Silva ◽  
Sandra Pereira ◽  
Alice Vilela ◽  
Eunice Bacelar ◽  
Francisco Guedes ◽  
...  
Keyword(s):  
Sweet Cherry ◽  
Prunus Avium ◽  
Sugar Content ◽  
Principal Component ◽  
Titratable Acidity ◽  
Physicochemical Characteristics ◽  
Quality Parameters ◽  
Sensory Profile ◽  
Soluble Solids ◽  
Sensory Data

Sweet cherry (Prunus avium L.) is a fruit appreciated by consumers for its well-known physical and sensory characteristics and its health benefits. Being an extremely perishable fruit, it is important to know the unique attributes of the cultivars to develop cultivation or postharvest strategies that can enhance their quality. This study aimed to understand the influence of physicochemical characteristics of two sweet cherry cultivars, Burlat and Van, on the food quality perception. Several parameters (weight, dimensions, soluble solids content (SSC), pH, titratable acidity (TA), colour, and texture) were measured and correlated with sensory data. Results showed that cv. Van presented heavier and firmer fruits with high sugar content. In turn, cv. Burlat showed higher pH, lower TA, and presented redder and brightest fruits. The principal component analysis revealed an evident separation between cultivars. Van cherries stood out for their sensory parameters and were classified as more acidic, bitter, and astringent, and presented a firmer texture. Contrarily, Burlat cherries were distinguished as being more flavourful, succulent, sweeter, and more uniform in terms of visual and colour parameters. The results of the sensory analysis suggested that perceived quality does not always depend on and/or recognize the quality parameters inherent to the physicochemical characteristics of each cultivar.

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