scholarly journals ATR-FTIR Spectroscopy Combined with Multivariate Analysis Successfully Discriminates Raw Doughs and Baked 3D-Printed Snacks Enriched with Edible Insect Powder

Foods ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1806
Author(s):  
Nerea García-Gutiérrez ◽  
Jorge Mellado-Carretero ◽  
Christophe Bengoa ◽  
Ana Salvador ◽  
Teresa Sanz ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Infrared Spectroscopy ◽  
Locusta Migratoria ◽  
Attenuated Total Reflection ◽  
Insect Species ◽  
Least Squares Regression ◽  
Alphitobius Diaperinus ◽  
Chickpea Flour ◽  
3D Printed ◽  
Preliminary Study

In a preliminary study, commercial insect powders were successfully identified using infrared spectroscopy combined with multivariate analysis. Nonetheless, it is necessary to check if this technology is capable of discriminating, predicting, and quantifying insect species once they are used as an ingredient in food products. The objective of this research was to study the potential of using attenuated total reflection Fourier transform mid-infrared spectroscopy (ATR-FTMIR) combined with multivariate analysis to discriminate doughs and 3D-printed baked snacks, enriched with Alphitobius diaperinus and Locusta migratoria powders. Several doughs were made with a variable amount of insect powder (0–13.9%) replacing the same amount of chickpea flour (46–32%). The spectral data were analyzed using soft independent modeling of class analogy (SIMCA) and partial least squares regression (PLSR) algorithms. SIMCA models successfully discriminated the insect species used to prepare the doughs and snacks. Discrimination was mainly associated with lipids, proteins, and chitin. PLSR models predicted the percentage of insect powder added to the dough and the snacks, with determination coefficients of 0.972, 0.979, and 0.994 and a standard error of prediction of 1.24, 1.08, and 1.90%, respectively. ATR-FTMIR combined with multivariate analysis has a high potential as a new tool in insect product authentication.

Rapid discrimination and classification of edible insect powders using ATR-FTIR spectroscopy combined with multivariate analysis

2020 ◽  
Vol 6 (2) ◽  
pp. 141-148
Author(s):  
J. Mellado-Carretero ◽  
N. García-Gutiérrez ◽  
M. Ferrando ◽  
C. Güell ◽  
D. García-Gonzalo ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Infrared Spectroscopy ◽  
Locusta Migratoria ◽  
Acheta Domesticus ◽  
Alphitobius Diaperinus ◽  
Edible Insect ◽  
Chemical Fingerprinting ◽  
Food And Feed ◽  
Rapid Discrimination

Insects are being proposed as an alternative way to ensure world’s food and feed security. Methods to determine edible insect powder’s origin and species will be needed for quality control purposes. Infrared spectroscopy has been extensively used in rapid chemical fingerprinting of food products. The present research explores a new approach to discriminate and classify commercial edible insect powders using attenuated total reflectance mid-infrared spectroscopy combined with multivariate analysis. Infrared spectra of seven commercial edible insect powders from different species (Tenebrio molitor, Alphitobius diaperinus, Gryllodes sigillatus, Acheta domesticus and Locusta migratoria) and origins (the Netherlands and New Zealand) were collected to build up soft independent modelling of class analogy (SIMCA) models. SIMCA models clearly discriminated insects by their species and origin linking their differences to lipids and chitin. SIMCA models performance was tested using five spectra of each class not used to build up the training set. 100% correct predictions were obtained for all the samples analysed with the exception of one sample of Alphitobius diaperinus. Infrared spectroscopy coupled to multivariate analysis provided a powerful method for the assurance of insect powder’s authenticity.

scholarly journals Comparison of Brain Activation Patterns during Olfactory Stimuli between Recovered COVID-19 Patients and Healthy Controls: A Functional Near-Infrared Spectroscopy (fNIRS) Study

2021 ◽  
Vol 11 (8) ◽  
pp. 968
Author(s):  
Roger C. Ho ◽  
Vijay K. Sharma ◽  
Benjamin Y. Q. Tan ◽  
Alison Y. Y. Ng ◽  
Yit-Shiang Lui ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Time Interval ◽  
Healthy Controls ◽  
Functional Near Infrared Spectroscopy ◽  
Activation Patterns ◽  
Identification Test ◽  
Olfactory Stimuli ◽  
Preliminary Study

Impaired sense of smell occurs in a fraction of patients with COVID-19 infection, but its effect on cerebral activity is unknown. Thus, this case report investigated the effect of COVID-19 infection on frontotemporal cortex activity during olfactory stimuli. In this preliminary study, patients who recovered from COVID-19 infection (n = 6) and healthy controls who never contracted COVID-19 (n = 6) were recruited. Relative changes in frontotemporal cortex oxy-hemoglobin during olfactory stimuli was acquired using functional near-infrared spectroscopy (fNIRS). The area under curve (AUC) of oxy-hemoglobin for the time interval 5 s before and 15 s after olfactory stimuli was derived. In addition, olfactory function was assessed using the Sniffin’ Sticks 12-identification test (SIT-12). Patients had lower SIT-12 scores than healthy controls (p = 0.026), but there were no differences in oxy-hemoglobin AUC between healthy controls and patients (p > 0.05). This suggests that past COVID-19 infection may not affect frontotemporal cortex function, and these preliminary results need to be verified in larger samples.

scholarly journals Quantification and Classification of Diclofenac Sodium Content in Dispersed Commercially Available Tablets by Attenuated Total Reflection Infrared Spectroscopy and Multivariate Data Analysis

2021 ◽  
Vol 14 (5) ◽  
pp. 440
Author(s):  
Eirini Siozou ◽  
Vasilios Sakkas ◽  
Nikolaos Kourkoumelis
Keyword(s):  
Infrared Spectroscopy ◽  
Low Cost ◽  
Diclofenac Sodium ◽  
Reference Method ◽  
Sodium Content ◽  
Attenuated Total Reflection ◽  
Accuracy And Precision ◽  
Significant Difference ◽  
Ft Ir

A new methodology, based on Fourier transform infrared spectroscopy equipped with an attenuated total reflectance accessory (ATR FT-IR), was developed for the determination of diclofenac sodium (DS) in dispersed commercially available tablets using chemometric tools such as partial least squares (PLS) coupled with discriminant analysis (PLS-DA). The results of PLS-DA depicted a perfect classification of the tablets into three different groups based on their DS concentrations, while the developed model with PLS had a sufficiently low root mean square error (RMSE) for the prediction of the samples’ concentration (~5%) and therefore can be practically used for any tablet with an unknown concentration of DS. Comparison with ultraviolet/visible (UV/Vis) spectrophotometry as the reference method revealed no significant difference between the two methods. The proposed methodology exhibited satisfactory results in terms of both accuracy and precision while being rapid, simple and of low cost.

scholarly journals Rapid tannin profiling of tree fodders using untargeted mid-infrared spectroscopy and partial least squares regression

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Jordi Ortuño ◽  
Sokratis Stergiadis ◽  
Anastasios Koidis ◽  
Jo Smith ◽  
Chris Humphrey ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Multivariate Calibration ◽  
Plant Ecology ◽  
Coefficient Of Determination ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Mid Infrared Spectroscopy

Abstract Background The presence of condensed tannins (CT) in tree fodders entails a series of productive, health and ecological benefits for ruminant nutrition. Current wet analytical methods employed for full CT characterisation are time and resource-consuming, thus limiting its applicability for silvopastoral systems. The development of quick, safe and robust analytical techniques to monitor CT’s full profile is crucial to suitably understand CT variability and biological activity, which would help to develop efficient evidence-based decision-making to maximise CT-derived benefits. The present study investigates the suitability of Fourier-transformed mid-infrared spectroscopy (MIR: 4000–550 cm−1) combined with multivariate analysis to determine CT concentration and structure (mean degree of polymerization—mDP, procyanidins:prodelphidins ratio—PC:PD and cis:trans ratio) in oak, field maple and goat willow foliage, using HCl:Butanol:Acetone:Iron (HBAI) and thiolysis-HPLC as reference methods. Results The MIR spectra obtained were explored firstly using Principal Component Analysis, whereas multivariate calibration models were developed based on partial least-squares regression. MIR showed an excellent prediction capacity for the determination of PC:PD [coefficient of determination for prediction (R2P) = 0.96; ratio of prediction to deviation (RPD) = 5.26, range error ratio (RER) = 14.1] and cis:trans ratio (R2P = 0.95; RPD = 4.24; RER = 13.3); modest for CT quantification (HBAI: R2P = 0.92; RPD = 3.71; RER = 13.1; Thiolysis: R2P = 0.88; RPD = 2.80; RER = 11.5); and weak for mDP (R2P = 0.66; RPD = 1.86; RER = 7.16). Conclusions MIR combined with chemometrics allowed to characterize the full CT profile of tree foliage rapidly, which would help to assess better plant ecology variability and to improve the nutritional management of ruminant livestock.

Occurrence of wooden breast and white striping in Brazilian slaughtering plants and use of near‐infrared spectroscopy and multivariate analysis to identify affected chicken breasts

2020 ◽  
Vol 85 (10) ◽  
pp. 3102-3112
Author(s):  
Leila Moreira Carvalho ◽  
Marta Suely Madruga ◽  
Mario Estévez ◽  
Amanda Teixeira Badaró ◽  
Douglas Fernandes Barbin
Keyword(s):  
Multivariate Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
White Striping ◽  
Wooden Breast
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