scholarly journals Total Anthocyanin Content in Intact Açaí (Euterpe oleracea Mart.) and Juçara (Euterpe edulis Mart.) Fruit Predicted by Near Infrared Spectroscopy

HortScience ◽  
2015 ◽  
Vol 50 (8) ◽  
pp. 1218-1223 ◽  
Author(s):  
Gustavo H. de A. Teixeira ◽  
Valquiria G. Lopes ◽  
Luís C. Cunha Júnior ◽  
José D.C. Pessoa
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Nondestructive Method ◽  
Data Sets ◽  
Anthocyanin Content ◽  
Euterpe Oleracea ◽  
Total Anthocyanin ◽  
Euterpe Edulis ◽  
On Line ◽  
Aoac Method

Açaí (Euterpe oleraceae Mart.) and juçara (Euterpe edulis Mart.) palms are native to Brazil and these species are rich in anthocynanins. The methods applied to determine anthocyanins are time-consuming, generate chemical residues, and do not fit in modern on-line grading machines. As near infrared (NIR) spectroscopy has been used as a nondestructive method to determine anthocyanin, the objective of this study was to use NIR spectroscopy to predict total anthocyanin (TA) in intact açaí and juçara fruits. Spectra were collected using a Fourier transform (FT)-NIR spectrophotometer in the diffuse reflectance (4,000–10,000 cm−1) and TA reference data were obtained using the Association of Official Analytical Chemists (AOAC) method. Different treatments were applied to spectra and spectral data sets were correlated with TA by using partial least squares (PLSs) regression algorithm. The global-PLS model obtained with açaí and juçara spectra resulted in a root mean standard error of prediction (RMSEP) of 10.05 g·kg−1. However, this model was not adequate for TA levels found in açaí fruits, therefore individual models were developed. The açaí-PLS model proved to be more adequate, as RMSEP was reduced to 3.56 g·kg−1. On the other hand, the RMSEP obtained with the juçara-PLS model (6.59 g·kg−1) was almost the same of the global model. NIR spectroscopy can be used to adequately predict TA content in intact açaí and juçara fruits and this method could be used as an analytical procedure to monitor their quality.

scholarly journals Near-Infrared Spectroscopy and Chemometrics for the Routine Detection of Bilberry Extract Adulteration and Quantitative Determination of the Anthocyanins

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Claudio Gardana ◽  
Antonio Scialpi ◽  
Christian Fachechi ◽  
Paolo Simonetti
Keyword(s):  
Near Infrared ◽  
Spectroscopic Method ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Good Prediction ◽  
Anthocyanin Content ◽  
Least Squares Regression ◽  
Nondestructive Technique ◽  
Total Anthocyanin ◽  
Bilberry Extract

Consumers must be assured that bought food supplements contain both bilberry extract and the anthocyanin amounts that match the declared levels. Therefore, a Fourier transform near-infrared (FT-NIR) spectroscopic method was validated based on principal component scores for the prediction of bilberry extract adulteration and partial least squares regression model for total anthocyanin evaluation. Anthocyanins have been quantified individually in 71 commercial bilberry extracts by HPLC-DAD, and 6 of them were counterfeit. The anthocyanin content in bilberry extracts was in the range 18–34%. Authentic bilberry extracts (n=65) were divided into two parts: one for calibration (n=38) and the other for the validation set (n=27). Spectra were recorded in the range of 4000–12500 cm−1, and a good prediction model was obtained in the range of 9400–6096 and 5456–4248 cm−1withr2of 99.5% and a root-mean-square error of 0.3%. The adulterated extracts subjected to NIR analysis were recognized as noncompliant, thus confirming the results obtained by chromatography. The FT-NIR spectroscopy is an economic, powerful, and fast methodology for the detection of adulteration and quantification of the total anthocyanin in bilberry extracts; above all, it is a rapid, low cost, and nondestructive technique for routine analysis.

Focusing near Infrared Spectroscopy on the Business Objectives of Modern Pharmaceutical Production

1998 ◽  
Vol 6 (A) ◽  
pp. A13-A19 ◽  
Author(s):  
T.G. Axon ◽  
R. Brown ◽  
S.V. Hammond ◽  
S.J. Maris ◽  
F. Ting
Keyword(s):  
High Performance ◽  
Near Infrared ◽  
Real Life ◽  
Nir Spectroscopy ◽  
Raw Material ◽  
Develop Model ◽  
Data Sets ◽  
Total Quality ◽  
Model Free ◽  
Pharmaceutical Production

The early use of near infrared (NIR) spectroscopy in the pharmaceutical industry was for raw material identification, later moving on to some conventional “calibrations” for various ingredients in a variety of sample types. The approach throughout this development process has always been “conventional” with one measurement by NIR directly replacing some other slower method, be it Mid-IR identification, or determinations by Karl Fischer, high performance liquid chromatography (HPLC)etc. A significant change in approach was demonstrated by Plugge and Van der Vlies1 in 1993, where a qualitative system was used to provide “quantitative like” answers for potency of a drug substance. Following on from that key paper, there has been a realisation that the qualitative analysis ability of NIR, has the potential to be a powerful tool for process investigation, control and validation. The final step has been to develop “model free” approaches, that consider individual data sets as unique systems, and present the opportunity for NIR to escape the shackles of “calibration” in one form or another. The use of qualitative, or model free, approaches to NIR spectroscopy provides an effective tool for satisfying many of the demands of modern pharmaceutical production. “Straight through production,” “right first time,” “short cycle time” and “total quality management” philosophies can be realised. Eventually the prospect of parametric release may be materialised with a strong contribution from NIR spectroscopy. This paper will illustrate the above points with some real life examles.

On-line application of visible and near infrared reflectance spectroscopy to predict physical and sensory characteristics of beef quality

2009 ◽  
Vol 2009 ◽  
pp. 135-135
Author(s):  
N Prieto ◽  
D W Ross ◽  
E A Navajas ◽  
G Nute ◽  
R I Richardson ◽  
...  
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Reflectance Spectroscopy ◽  
Sensory Characteristics ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Beef Quality ◽  
Near Infrared Reflectance ◽  
On Line ◽  
Meat Samples

Visible and near infrared reflectance spectroscopy (Vis-NIR) has been widely used by the industry research-base for large-scale meat quality evaluation to predict the chemical composition of meat quickly and accurately. Meat tenderness is measured by means of slow and destructive methods (e.g. Warner-Bratzler shear force). Similarly, sensory analysis, using trained panellists, requires large meat samples and is a complex, expensive and time-consuming technique. Nevertheless, these characteristics are important criteria that affect consumers’ evaluation of beef quality. Vis-NIR technique provides information about the molecular bonds (chemical constituents) and tissue ultra-structure in a scanned sample and thus can indirectly predict physical or sensory parameters of meat samples. Applications of Vis-NIR spectroscopy in an abattoir for prediction of physical and sensory characteristics have been less developed than in other fields. Therefore, the aim of this study was to test the on-line Vis-NIR spectroscopy for the prediction of beef quality characteristics such as colour, instrumental texture, water holding capacity (WHC) and sensory traits, by direct application of a fibre-optic probe to the M. longissimus thoracis with no prior sample treatment.

scholarly journals Single-Kernel FT-NIR Spectroscopy for Detecting Maturity of Cucumber Seeds Using a Multiclass Hierarchical Classification Strategy

2019 ◽  
Vol 9 (23) ◽  
pp. 5058 ◽  
Author(s):  
Zeng ◽  
Lü ◽  
Qiu ◽  
Lu ◽  
Jiang
Keyword(s):  
Near Infrared ◽  
Seed Quality ◽  
Hierarchical Classification ◽  
Nir Spectroscopy ◽  
Predictive Performance ◽  
Nondestructive Method ◽  
Maturation Stage ◽  
Seed Industry ◽  
Intrinsic Quality ◽  
Classification Strategy

The maturity of seeds at harvest determines their intrinsic quality characteristics such as longevity and vigor, and these characteristics are dominant factors for seed quality evaluation in the seed industry. However, little information is available on how to identify and further classify the maturation stage of seeds in a way that is nondestructive, precise, rapid, and inexpensive, while also exactly meeting the need for the uniform control of seed performance in the seed industry to improve crop yield. This study demonstrated a nondestructive method for detecting seed maturity by using the single-kernel near-infrared spectroscopy (SK-NIRS) technique. The results showed that five classes of cucumber seeds with different maturation levels can be distinguished successfully. A tree-structured hierarchical classification strategy consisting of one soft independent modeling of class analogy (SIMCA) model and three partial least squares discriminant analysis (PLS-DA) models were proposed ending up with 99.69% of the overall classification accuracy and 0.9961 of Cohen’s kappa in the test set, and its predictive performance was superior to both SIMCA and PLS-DA for direct multiclass classification. SK-NIRS in combination with a multiclass hierarchical classification strategy was proved to be both intuitive and efficient in classifying cucumber seeds according to maturation levels.

The Effect of Multiplicative Scatter Correction (MSC) and Linearity Improvement in NIR Spectroscopy

1988 ◽  
Vol 42 (7) ◽  
pp. 1273-1284 ◽  
Author(s):  
Tomas Isaksson ◽  
Tormod Næs
Keyword(s):  
Near Infrared ◽  
Scatter Correction ◽  
Principal Component Regression ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Data Sets ◽  
Prediction Errors ◽  
Regression Methods ◽  
Multiplicative Scatter Correction ◽  
Linearity Improvement

Near-infrared (NIR) reflectance spectra of five different food products were measured. The spectra were transformed by multiplicative scatter correction (MSC). Principal component regression (PCR) was performed, on both scatter-corrected and uncorrected spectra. Calibration and prediction were performed for four food constituents: protein, fat, water, and carbohydrates. All regressions gave lower prediction errors (7–68% improvement) by the use of MSC spectra than by the use of uncorrected absorbance spectra. One of these data sets was studied in more detail to clarify the effects of the MSC, by using PCR score, residual, and leverage plots. The improvement by using nonlinear regression methods is indicated.

scholarly journals Estimation of Secondary Soil Properties by Fusion of Laboratory and On-Line Measured Vis–NIR Spectra

2019 ◽  
Vol 11 (23) ◽  
pp. 2819 ◽  
Author(s):  
Muhammad Abdul Munnaf ◽  
Said Nawar ◽  
Abdul Mounem Mouazen
Keyword(s):  
Soil Properties ◽  
Real Time ◽  
Measurement Accuracy ◽  
Near Infrared ◽  
Diffuse Reflectance Spectroscopy ◽  
Spectral Response ◽  
Nir Spectroscopy ◽  
Accurate Estimation ◽  
Line Measurement ◽  
On Line

Visible and near infrared (vis–NIR) diffuse reflectance spectroscopy has made invaluable contributions to the accurate estimation of soil properties having direct and indirect spectral responses in NIR spectroscopy with measurements made in laboratory, in situ or using on-line (while the sensor is moving) platforms. Measurement accuracies vary with measurement type, for example, accuracy is higher for laboratory than on-line modes. On-line measurement accuracy deteriorates further for secondary (having indirect spectral response) soil properties. Therefore, the aim of this study is to improve on-line measurement accuracy of secondary properties by fusion of laboratory and on-line scanned spectra. Six arable fields were scanned using an on-line sensing platform coupled with a vis–NIR spectrophotometer (CompactSpec by Tec5 Technology for spectroscopy, Germany), with a spectral range of 305–1700 nm. A total of 138 soil samples were collected and used to develop five calibration models: (i) standard, using 100 laboratory scanned samples; (ii) hybrid-1, using 75 laboratory and 25 on-line samples; (iii) hybrid-2, using 50 laboratory and 50 on-line samples; (iv) hybrid-3, using 25 laboratory and 75 on-line samples, and (v) real-time using 100 on-line samples. Partial least squares regression (PLSR) models were developed for soil pH, available potassium (K), magnesium (Mg), calcium (Ca), and sodium (Na) and quality of models were validated using an independent prediction dataset (38 samples). Validation results showed that the standard models with laboratory scanned spectra provided poor to moderate accuracy for on-line prediction, and the hybrid-3 and real-time models provided the best prediction results, although hybrid-2 model with 50% on-line spectra provided equally good results for all properties except for pH and Na. These results suggest that either the real-time model with exclusively on-line spectra or the hybrid model with fusion up to 50% (except for pH and Na) and 75% on-line scanned spectra allows significant improvement of on-line prediction accuracy for secondary soil properties using vis–NIR spectroscopy.

On-Line Monitoring of Melt-Extrusion Transesterification of Ethylene Vinylacetate Copolymers by near Infrared Spectroscopy and Chemometrics

2002 ◽  
Vol 10 (3) ◽  
pp. 195-202 ◽  
Author(s):  
Tsuyoshi Furukawa ◽  
Yasuo Kita ◽  
Shigehiro Sasao ◽  
Kimihiro Matsukawa ◽  
Masahiro Watari ◽  
...  
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Intensity Change ◽  
Melt Extrusion ◽  
Peak Intensity ◽  
Fibre Optic Probe ◽  
On Line ◽  
Significant Intensity ◽  
Optic Probe

The melt-extrusion transesterification of ethylene/vinylacetate (EVA) copolymer to ethylene/vinylalcohol (EVAL) copolymers has been monitored by on-line near infrared (NIR) spectroscopy. A total of 60 NIR spectra were measured within 37 minutes after the initial addition of octanol (reagent) and catalyst (sodium methoxide) at the exit of the extruder by use of a fibre-optic probe. The most significant intensity change is observed for a band at 7089 cm−1 due to the first overtone of an OH stretching mode of the EVAL copolymers. We can monitor the progress of the reaction by plotting the peak intensity at 7089 cm−1 only. A principal component analysis (PCA) was carried out for the series of NIR spectra in the 7300–6900 cm−1 region. A score plot of PCA factor 1 is almost identical with the plot of the peak intensity at 7089 cm−1. Calibration models for predicting the vinyl acetate content in EVA copolymers have been developed by use of partial least squares (PLS) regression. The correlation coefficient and standard error of prediction are 0.96 and 0.85%, respectively, indicating that the described technique can be used to monitor the transesterification reaction.

Long-Length Fiber Optic Near-Infrared (NIR) Spectroscopy Probes for On-Line Quality Control of Processed Land Animal Proteins

2018 ◽  
Vol 72 (8) ◽  
pp. 1170-1182 ◽  
Author(s):  
Ana Garrido-Varo ◽  
Ana Sánchez-Bonilla ◽  
Francisco Maroto-Molina ◽  
Cecilia Riccioli ◽  
Dolores Pérez-Marín
Keyword(s):  
Near Infrared ◽  
Fiber Optic ◽  
Nir Spectroscopy ◽  
Conveyor Belt ◽  
Animal Origin ◽  
Processing Plant ◽  
Fiber Optic Cable ◽  
Operating Modes ◽  
On Line ◽  
Dynamic Operating

This research was conducted using a spectral database comprising 346 samples of processed animal proteins (PAPs) with a range of compositions, analyzed using a Fourier transform near-infrared spectroscopy multichannel instrument (Matrix-F, Bruker Optics) coupled to a 100 m fiber optic cable. Using both its static and dynamic operating modes (on a conveyor belt), simulating the movement of the product in the plant, the predictive capabilities of both modes of analysis were assessed and compared, for the purposes of predicting moisture, protein, and ashes. The results show that both exhibit highly similar degrees of precision and accuracy for predicting these parameters. This research provides a foundation of scientific-technical knowledge, hitherto unknown, regarding the “on-line” incorporation of an instrument (equipped with a 100 m fiber optic cable) into a processing plant of by-products of animal origin.

scholarly journals Soluble Solids and Simple Sugars Measurement in Intact Mango Using Near Infrared Spectroscopy

2008 ◽  
Vol 18 (3) ◽  
pp. 410-416 ◽  
Author(s):  
Stephen R. Delwiche ◽  
Weena Mekwatanakarn ◽  
Chien Y. Wang
Keyword(s):  
Standard Error ◽  
Quality Evaluation ◽  
Near Infrared ◽  
Wavelength Region ◽  
Nir Spectroscopy ◽  
Nondestructive Method ◽  
Soluble Solids ◽  
Least Squares Regression ◽  
Different Temperatures ◽  
The Individual

A rapid, reliable, and nondestructive method for quality evaluation of mango (Magnifera indica) fruit is important to the mango industry for international trade. The objective of this study was to determine the potential of near-infrared (NIR) spectroscopy to predict soluble solids content (SSC) and individual and combined concentrations of sucrose, glucose, and fructose nondestructively in mango. Mature mangoes at two different temperatures (15 °C and 20 °C) were measured by NIR interactance (750–1088 nm wavelength region analyzed) over an 11-day period, starting when the fruit were underripe and extending to a few days past optimal ripeness. Partial least squares regression was used to develop models for SSC, individual sugar concentration, and the sum of the concentrations of the three sugars. Such analyses yielded calibration equations with R2 = 0.77 to 0.88 (SSC), 0.75 (sucrose), 0.67 (glucose), 0.70 (fructose), and 0.82 (sum); standard error of calibration = 0.56 to 0.90 (SSC), 10.0 (sucrose), 0.9 (glucose), 4.5 (fructose), and 10.4 (sum); and standard error of cross-validation = 0.93 to 1.10 (SSC), 15.6 (sucrose), 1.4 (glucose), 6.9 (fructose), and 16.8 (sum). When the SSC calibration was applied to a separate validation set, the standard error of performance ranged from 0.94% to 1.72%. These results suggest that for assessment of mango ripeness, NIR SSC calibrations are superior to the NIR calibrations for any of the individual sugars. This nondestructive technology can be used in the screening and grading of mangoes and in quality evaluation at wholesale and retail levels.

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