The Benefits of near Infrared Analysis for Food Product Quality

1998 ◽  
Vol 6 (A) ◽  
pp. A343-A348 ◽  
Author(s):  
Christel Kurowski ◽  
Dagmar Timm ◽  
Uwe Grummisch ◽  
Ulrich Meyhack ◽  
Horst Grunewald
Keyword(s):  
Near Infrared ◽  
Raw Materials ◽  
Nir Spectroscopy ◽  
Food Product ◽  
Infrared Analysis ◽  
Full Spectrum ◽  
Process Measurements ◽  
Selection Of

This is a poster presentation. Raw materials have a decisive influence on the quality of a product. Therefore it is important to check raw materials not only for quality and composition but also for identity. It is also essential to check material during the production process to prevent defective products and to save costs resulting from any out of specification batch. Such in-process measurements are also used for process control. The power of NIR spectroscopy includes both qualitative and quantitative analysis. Results can be obtained within a few seconds. Since no chemicals or time consuming sample preparation is necessary NIR spectroscopy is an ideal analytical method for at-line and in-line measurements. NIR spectroscopy is well established to measure moisture, protein, and fat – the three major constituents in food processing. For these three and a few other constituents a selection of 19 specific wavelengh filters can give all necessary information. But NIR spectroscopy is not only an appropriate tool to analyze these “standard parameters” it can also be very helpful when determining less conventional or minor parameters. Therefore often a higher flexibility regarding the wavelength selection is required which makes the collection of a full spectrum necessary. Some of these less common applications are the determination of caffeine in coffee, theobromine in chocolate or trans fatty acids in margarine. Other product specific parameters which have a strong influence on processing behaviour like the tenderness of peas or the degree of substitution in modified starch can also be measured by NIR.

scholarly journals Assessment of pesticide coating on cereal seeds by near infrared hyperspectral imaging

2017 ◽  
Author(s):  
Ph. Vermeulen ◽  
P. Flémal ◽  
O. Pigeon ◽  
P. Dardenne ◽  
J. Fernández Pierna ◽  
...  
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Seed Quality ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Ultra Performance Liquid Chromatography

Classical chromatographic methods, such as ultra performance liquid chromatography (UPLC), are used as reference methods to assess seed quality and homogeneous pesticide coating of seeds. These methods have some important drawbacks since they are time consuming, expensive, destructive and require a substantial amount of solvent, among others. Near infrared (NIR) spectroscopy seems to be an interesting alternative technique for the determination of the quality of seed treatment and avoids most of these drawbacks. The objective of this study was to assess the quality of pesticide coating treatment by near infrared hyperspectral imaging (NIR-HSI) by analysing, on a seed-by-seed basis, several seeds simultaneously in comparison to NIR spectroscopy and UPLC as the reference method. To achieve this goal, discrimination—partial least squares discriminant analysis (PLS-DA)—models and regression—partial least squares (PLS)—models were developed. The results obtained by NIR-HSI are compared to the results obtained with NIR spectroscopy and UPLC instruments. This study has shown the potential of NIR hyperspectral imaging to assess the quality/homogeneity of the pesticide coating on seeds.

scholarly journals Simultaneous Determination of Several Fiber Contents in Blended Fabrics by Near-Infrared Spectroscopy and Multivariate Calibration

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Hui Chen ◽  
Zan Lin ◽  
Chao Tan
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Nir Spectroscopy ◽  
Nondestructive Method ◽  
Full Spectrum ◽  
Lattice Design ◽  
The Mean

The qualitative and quantitative determination of the components of textile fibers takes an important position in quality control. A fast and nondestructive method of simultaneously analyzing four fiber components in blended fabrics was studied by near-infrared (NIR) spectroscopy combined with multivariate calibration. Two sample sets including 39 and 25 samples were designed by simplex mixture lattice design methods and used for experiment. Four components include wool, polyester, polyacrylonitrile, and nylon and their mixture is one of the most popular formulas of textiles. Uninformative variable elimination-partial least squares (UVEPLS) and the full-spectrum partial least squares (PLS) were used as the tool. On the test set, the mean standard error of prediction (SEP) and the mean ratio of the standard deviation of the response variable and SEP (RPD) of the full-spectrum PLS model and UVEPLS model were 0.38, 0.32 and 7.6, 8.3, respectively. This result reveals that the UVEPLS can construct local models with acceptable and better performance than the full-spectrum PLS. It indicates that this method is valuable for nondestructive analysis in the field of wool content detection since it can avoid time-consuming, costly, and laborious wet chemical analysis.

scholarly journals Determination of selected parameters of quality of the dairy products by NIR spectroscopy

2011 ◽  
Vol 24 (No. 6) ◽  
pp. 255-260 ◽  
Author(s):  
J. Růžičková ◽  
K. Šustová
Keyword(s):  
Dairy Products ◽  
Near Infrared ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Integrating Sphere ◽  
Calibration Model ◽  
Titrable Acidity ◽  
Non Destructive

The possibility of the application of near-infrared spectroscopy to the analysis of the selected parameters of quality of the dairy products was followed. The contents of solids and fat, as well as pH in yoghurts (also the titrable acidity), milk semolina, and milk rice were determined. The samples were analysed by reference methods and by FT NIR spectroscope at integrating sphere within reflectance mode in the wavelength range of 10 000&ndash;4&nbsp;000 cm<sup>&ndash;1 </sup>with 100&nbsp;scans. To develop the calibration model for the components examined, the partial least squares (PLS) was used and this model was validated by full cross validation. The highest correlation coefficients were found with yoghurt: 0.998 (solids), 0.989 (fat), 0.875 (pH) and 0.989 (titrable acidity), with milk semolina: 0.967 (solids), 0.983 (fat) and 0.992 (pH), and with milk rice: 0.987 (solids), 0.990 (fat) and 0.852 (pH). The results of this study showed the availability of NIR spectroscopy for a quick and non-destructive analysis of the dairy products. &nbsp;

Near-Infrared Spectroscopic Measurement of Organic Matter in Soil

2012 ◽  
Vol 499 ◽  
pp. 414-418
Author(s):  
Tao Pan ◽  
Zhen Tao Wu ◽  
Jie Mei Chen
Keyword(s):  
Organic Matter ◽  
Near Infrared ◽  
Rapid Determination ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Modeling Prediction ◽  
Validation Set ◽  
Selection Of

Near-infrared (NIR) spectroscopy was successfully applied to chemical free and rapid determination of the organic matter in soil, and moving window partial least square (MWPLS) combining with Savitzky-Golay (SG) smoothing was used to the selection of NIR waveband. Thirty-five samples were randomly selected from all 97 collected soil samples as the validation set. The remaining 62 samples were divided into similar modeling calibration set (37 samples) and modeling prediction set (25 samples) based on partial least square cross-validation predictive bias (PLSPB). The selected waveband was 1896 nm to 2138 nm; the SG smoothing parameters and PLS factor OD, DP, NSP and F were 2, 6, 71 and 15, respectively; the modeling effect M-SEP and M-RPwere 0.219% and 0.944, respectively; the validating effect V-SEP and V-RPwere 0.243% and 0.878, respectively. The result provided a reliable NIR model and valuable references for designing specialized NIR instruments.

scholarly journals La importancia de las denominaciones de origen protegidas como indicadores de calidad para el comportamiento del consumidor. El caso del aceite de oliva del Bajo Aragón

2011 ◽  
Vol 7 (14) ◽  
pp. 3 ◽  
Author(s):  
Joel Espejel ◽  
Carmina Fandos ◽  
Carlos Flavián
Keyword(s):  
Olive Oil ◽  
Raw Materials ◽  
Food Product ◽  
Food Products ◽  
Perceived Quality ◽  
Know How

In this paper we analyze the influence of satisfaction towards a food product with Protected Denomination of Origin (PDO) on loyalty and consumers’ buying intention. The results show the importance that the consumers allowance towards the links as the origin, territory, raw materials, know how, and the strict controls by the PDO Regulatory Council. All these aspects, concern in the determination of the perceived quality of the above mentioned PDO food products. In fact, these findings suppose a major feelings satisfaction and loyalty as well as of a major predisposition to continue buying the olive oil from Bajo Aragon (Spain).

scholarly journals Textile Recognition and Sorting for Recycling at an Automated Line Using Near Infrared Spectroscopy

Recycling ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 11
Author(s):  
Kirsti Cura ◽  
Niko Rintala ◽  
Taina Kamppuri ◽  
Eetta Saarimäki ◽  
Pirjo Heikkilä
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Automated Recognition ◽  
Textile Materials ◽  
Input Material ◽  
Adequate Quality ◽  
Automated Line

In order to add value to recycled textile material and to guarantee that the input material for recycling processes is of adequate quality, it is essential to be able to accurately recognise and sort items according to their material content. Therefore, there is a need for an economically viable and effective way to recognise and sort textile materials. Automated recognition and sorting lines provide a method for ensuring better quality of the fractions being recycled and thus enhance the availability of such fractions for recycling. The aim of this study was to deepen the understanding of NIR spectroscopy technology in the recognition of textile materials by studying the effects of structural fabric properties on the recognition. The identified properties of fabrics that led non-matching recognition were coating and finishing that lead different recognition of the material depending on the side facing the NIR analyser. In addition, very thin fabrics allowed NIRS to penetrate through the fabric and resulted in the non-matching recognition. Additionally, ageing was found to cause such chemical changes, especially in the spectra of cotton, that hampered the recognition.

New active learning algorithms for near-infrared spectroscopy in agricultural applications

2021 ◽  
Vol 69 (4) ◽  
pp. 297-306
Author(s):  
Julius Krause ◽  
Maurice Günder ◽  
Daniel Schulz ◽  
Robin Gruna
Keyword(s):  
Active Learning ◽  
Near Infrared ◽  
Agricultural Products ◽  
Training Data ◽  
Calibration Model ◽  
Learning Approaches ◽  
Training Samples ◽  
Agricultural Applications ◽  
Selection Of

Abstract The selection of training data determines the quality of a chemometric calibration model. In order to cover the entire parameter space of known influencing parameters, an experimental design is usually created. Nevertheless, even with a carefully prepared Design of Experiment (DoE), redundant reference analyses are often performed during the analysis of agricultural products. Because the number of possible reference analyses is usually very limited, the presented active learning approaches are intended to provide a tool for better selection of training samples.

scholarly journals Wine preferences based on intrinsic attributes: A tasting experiment in Alto Adige/Südtirol province

2021 ◽  
pp. 129-134
Author(s):  
Luigi Fabbris ◽  
Alfonso Piscitelli
Keyword(s):  
Food Product ◽  
Fractional Factorial ◽  
Region Of Origin ◽  
Double Blind ◽  
White Wines ◽  
Grape Varieties ◽  
The Impact ◽  
Administration Procedure ◽  
Selection Of

Different methods have been developed by researchers in modelling wine consumers purchase behaviour. The quality of a food product is described by a set of characteristics ascribable to the intrinsic and extrinsic product attributes (Olson and Jacoby, 1972). Price, brand, region of origin, grapes and gained awards are the key extrinsic attributes and physical characteristics of the wine such as taste and flavour are intrinsic attributes. This paper addresses the problem of measuring the intrinsic attributes that characterise the wine, based on specific characteristics and the impact on consumers in terms of preferences. To this end, a fractional factorial experiment held on a selection of white wines of the Alto Adige/Südtirol province in Italy. The sensorial experiment involved a voluntary sample of 33 mild wine consumers and concerned 6 grape varieties typical of that territory. For each variety, two producing cellars were selected for a total of 12 evaluated wines. The experiment followed a double-blind administration procedure to the sample and a paper questionnaire was used to elicit the consumers’ opinions on the tasted wines. The results show that intrinsic attributes, such as taste-olfactory intensity, harmony and olfactory complexity, are the drivers used in combination by consumers to rank wines in order of preference.

scholarly journals Determination of the composition of multilayer plastic packaging with NIR spectroscopy

Detritus ◽  
2020 ◽  
pp. 62-66
Author(s):  
Xiaozheng Chen ◽  
Nils Kroell ◽  
Alexander Feil ◽  
Thomas Pretz
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared ◽  
State Of The Art ◽  
Nir Spectroscopy ◽  
Waste Recycling ◽  
Point Of View ◽  
Plastic Packaging ◽  
Post Industrial ◽  
Detection And Separation

In food and medical packaging, multiple layers of different polymers are combined in order to achieve optimal functional properties for various applications. Flexible multilayer plastic packaging achieves a reduction in weight compared to other packaging products with the same function, saving material and in transportation costs. Recycling of post-industrial multilayer packaging was achieved by some companies, but the available technologies are limited to specific polymer types. For post-consumer waste, recycling of multilayer packaging has not been achieved yet. One of the main challenges in plastic sorting is that the detection and separation of multilayer packaging from other materials is not possible yet. In this study, the possibility to detect and sort flexible multilayer plastic packaging was investigated with near-infrared spectroscopy, which is the state-of-the-art technology for plastic sorting. The results show that from a detection and classification point of view, sorting of monolayer, two- and three-layers samples under laboratory conditions is possible. According to the captured data, the sequence of layers has little influence on the spectra. In case of glossy samples, the spectra are influenced by printed surfaces. With an increase in thickness, the spectra get more characteristic, which makes the classification easier. Our results indicate that the sorting of post-consumer multilayer plastic packaging by main composition is theoretically achievable.

Prediction of Stilbene Content from Heartwood Increment Cores of Scots Pine Using near Infrared Spectroscopy Methodology

2016 ◽  
Vol 24 (6) ◽  
pp. 517-528 ◽  
Author(s):  
Susanna Pulkka ◽  
Vincent Segura ◽  
Anni Harju ◽  
Tarja Tapanila ◽  
Johanna Tanner ◽  
...  
Keyword(s):  
Scots Pine ◽  
High Throughput ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Tree Breeding ◽  
Decay Resistance ◽  
Increment Core ◽  
Automatic Selection ◽  
Non Destructive ◽  
Selection Of

High-throughput and non-destructive methods for quantifying the content of the stilbene compounds of Scots pine ( Pinus sylvestris L.) heartwood are needed in the breeding for decay resistance of heartwood timber. In this study, near infrared (NIR) spectroscopy calibrations were developed for a large collection of solid heartwood increment core samples in order to predict the amount of the stilbene pinosylvin (PS), its monomethyl ether (PSM) and their sum (STB). The resulting models presented quite accurate predictions in an independent validation set with R2V values ranging between 0.79 and 0.91. The accuracy of the models strongly depended on the chemical being calibrated, with the lowest accuracy for PS, intermediate accuracy for PSM and highest accuracy for STB. The effect of collecting one, two or more (up to five) spectra per sample on the calibration models was studied and it was found that averaging multiple spectra yielded better accuracy as it may account for the heterogeneity of wood along the increment core within and between rings. Several statistical pretreatments of the spectra were tested and an automatic selection of wavenumbers prior to calibration. Without the automatic selection of wavenumbers, a first derivative of normalised spectra yielded the best accuracies, whereas after the automatic selection of wavenumbers, no particular statistical pretreatment appeared to yield better results than any other. Finally, the automatic selection of wavenumbers slightly improved the accuracy of the models for all traits. These results demonstrate the potential of NIR spectroscopy as a high-throughput and non-destructive phenotyping technique in tree breeding for the improvement of decay resistance in heartwood timber.

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