Online determination of quality parameters of dried soybean protein–lipid films (Fuzhu) by NIR spectroscopy combined with chemometrics

The use of near-infrared (NIR) spectroscopy for the prediction of the essential oil content and composition in various umbelliferae genotypes was investigated. Furthermore an NIR method was developed for the quantification of total carotenoids and sugars present in different carrot varieties. Applying partial least square algorithm very good calibration statistics ( SECV, R2) were obtained for the prediction of the essential oil content in fennel (0.47, 0.83), caraway (0.29, 0.93), dill (0.30, 0.96) and coriander (0.29, 0.93). Satisfactory calibration results were received for the NIR determination of total carotenoids (1.54, 0.80) and of saccharose(0.74, 0.76) in carrots. The performed study demonstrates that NIR can be used to rapidly and accurately predict secondary metabolites such as carotenoids, anethole, fenchone, estragole, limonene and carvone occurring in vegetables and in fruits of various essential oil plants.

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Development and comparison of regression models for the determination of quality parameters in margarine spread samples using NIR spectroscopy

Analytical Methods ◽

10.1039/c8ay01055b ◽

2018 ◽

Vol 10 (25) ◽

pp. 3089-3099 ◽

Cited By ~ 1

Author(s):

Anita Rácz ◽

Marietta Fodor ◽

Károly Héberger

Keyword(s):

Regression Models ◽

Nir Spectroscopy ◽

Quality Parameters ◽

Sum Of Ranking Differences

More than a hundred margarine samples and their FT-NIR spectra were used to develop regression models, and to compare them with sum of ranking differences and ANOVA.

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The Frequency of Occurrence of Handwriting Performance Features Used to Predict Whether Questioned Signatures are Simulated

Journal of Forensic Document Examination ◽

10.31974/jfde28-35-42 ◽

2018 ◽

Vol 28 ◽

pp. 35-42

Author(s):

David Black ◽

Bryan Found ◽

Doug Rogers

Keyword(s):

Large Population ◽

Quality Parameters ◽

Frequency Of Occurrence ◽

Relative Speed ◽

Simulation Process ◽

Spatial Features ◽

And Performance ◽

Document Examiners ◽

Line Trace

Forensic Document Examiners (FDEs) examine the physical morphology and performance attributes of a line trace when comparing questioned to specimen handwriting samples for the purpose of determining authorship. Along with spatial features, the elements of execution of the handwriting are thought to provide information as to whether or not a questioned sample is the product of a disguise or simulation process. Line features such as tremor, pen-lifts, blunt beginning and terminating strokes, indicators of relative speed, splicing and touch ups, are subjectively assessed and used in comparisons by FDEs and can contribute to the formation of an opinion as to the validity of a questioned sample of handwriting or signatures. In spite of the routine use of features such as these, there is little information available regarding the relative frequency of occurrence of these features in populations of disguised and simulated samples when compared to a large population of a single individual’s signature. This study describes a survey of the occurrence of these features in 46 disguised signatures, 620 simulated signatures (produced by 31 different amateur forgers) and 177 genuine signatures. It was found that the presence of splices and touch-ups were particularly good predictors of the simulation process and that all line quality parameters were potentially useful contributors in the determination of the authenticity of questioned signatures. Purchase Article - $10

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Plastics. Polyols for use in the production of polyurethanes. Determination of hydroxyl number by NIR spectroscopy

10.3403/30096724 ◽

2011 ◽

Keyword(s):

Nir Spectroscopy ◽

Hydroxyl Number

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Evaluation of Minimum Preparation Sampling Strategies for Sugarcane Quality Prediction by vis-NIR Spectroscopy

Sensors ◽

10.3390/s21062195 ◽

2021 ◽

Vol 21 (6) ◽

pp. 2195

Author(s):

Lucas de Paula Corrêdo ◽

Leonardo Felipe Maldaner ◽

Helizani Couto Bazame ◽

José Paulo Molin

Keyword(s):

Sample Preparation ◽

Prediction Models ◽

Spectral Response ◽

Nir Spectroscopy ◽

Quality Parameters ◽

Partial Least Square ◽

Least Square ◽

Sample Type ◽

Sampling Strategies ◽

Significant Difference

Proximal sensing for assessing sugarcane quality information during harvest can be affected by various factors, including the type of sample preparation. The objective of this study was to determine the best sugarcane sample type and analyze the spectral response for the prediction of quality parameters of sugarcane from visible and near-infrared (vis-NIR) spectroscopy. The sampling and spectral data acquisition were performed during the analysis of samples by conventional methods in a sugar mill laboratory. Samples of billets were collected and four modes of scanning and sample preparation were evaluated: outer-surface (‘skin’) (SS), cross-sectional scanning (CSS), defibrated cane (DF), and raw juice (RJ) to analyze the parameters soluble solids content (Brix), saccharose (Pol), fibre, pol of cane and total recoverable sugars (TRS). Predictive models based on Partial Least Square Regression (PLSR) were built with the vis-NIR spectral measurements. There was no significant difference (p-value > 0.05) between the accuracy SS and CSS samples compared to DF and RJ samples for all prediction models. However, DF samples presented the best predictive performance values for the main sugarcane quality parameters, and required only minimal sample preparation. The results contribute to advancing the development of on-board quality monitoring in sugarcane, indicating better sampling strategies.

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