Investigating the impact of spectral data pre-processing to assess honey botanical origin through Fourier transform infrared spectroscopy (FTIR)

Tsagkaris, Aristeidis S.; Bechyňská, Kamila; Ntakoulas, D.D.; Pasias, Ioannis N.; Weller, Philipp; Proestos, Charalampos; Hajšlová, Jana

doi:10.1016/j.jfca.2023.105276

Cited by 19 publications

(4 citation statements)

References 37 publications

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“…The 12 methods included Savitzky-Golay convolutional smoothing (SG), multiple scattering correction (MSC), standard normal variety (SNV), logarithmic transformation (LG), first derivative (FD), and second derivative (SD). Combinations of two single preprocessing algorithms (SG + SNV and SG + MSC) and combinations of three single preprocessing methods (SG + MSC + SD, SG + MSC + FD, SG + SNV + FD, SG + SNV + SD, and SG + SNV + SD) were used to preprocess the original spectral data [40]. Next, partial least squares regression (PLSR) [41] and gradient boosting regression tree (GBRT) algorithms were used to establish a prediction model for mineral element content, establish a full-band prediction model, and preliminarily screen out two models that meet the criteria for predicting the iron content in pear peel and two models that meet the criteria for predicting the iron content in pear pulp.…”

Section: Discussionmentioning

confidence: 99%

Quantitatively Determine the Iron Content in the Fruit of ‘Huangguan’ Pear Using Near-Infrared Spectroscopy

Fang

et al. 2023

Horticulturae

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‘Huangguan’ pear has excellent quality, strong adaptability, and good socioeconomic value. Iron is one of the important trace elements in plants, and iron imbalance seriously affects the growth and development of pear trees and reduces their economic benefits. If the iron content in pear fruit can be easily and non-destructively detected using modern technology during the critical period of fruit development, it will undoubtedly help guide actual production. In this study, ‘Huangguan’ pear fruit was used as the research object, and the possibility of using the more convenient near-infrared spectroscopy (900~1700 nm) technology for nondestructive detection of the iron content in the peel and pulp of ‘Huangguan’ pear was explored. First, 12 algorithms were used to preprocess the original spectral data, and based on the original and the preprocessed spectral data, partial least squares regression and gradient boosting regression tree algorithms were used. A full-band prediction model of the iron content in the peel and pulp of ‘Huangguan’ pear was established, and the genetic algorithm was used to extract characteristic wavelengths, establish a characteristic wavelength prediction model, and evaluate the prediction effect of each model according to the coefficient of determination R² and the relative analysis error RPD. After comparison, we found that the prediction model with the best prediction of the iron content in the peel and pulp of ‘Huangguan’ pear reaches class A, and the prediction effect is good and meets expectations. This experiment shows that the use of near-infrared spectroscopy can achieve better prediction of the iron content in the peel and pulp of ‘Huangguan’ pear.

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Section: Discussionmentioning

confidence: 99%

Quantitatively Determine the Iron Content in the Fruit of ‘Huangguan’ Pear Using Near-Infrared Spectroscopy

Fang

et al. 2023

Horticulturae

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“…This method can reduce big-sized data to its principal component (PC), representing the structure and variance in the data (Granato et al, 2018). In PCA, FTIR spectra is pre-treated with an objection to avoid any problems raised by the baseline shift, and increase the resolution of overlapping spectra (Tsagkaris et al, 2023).…”

Section: Ftir Spectra Grouping With Pcamentioning

confidence: 99%

Antioxidant activity and metabolite changes in Centella asiatica with different drying methods using FTIR- and quantitative HPLC-based metabolomics

Nomi,

Handayani,

Khuluk

et al. 2024

IFRJ

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Centella asiatica, known as Indian or Asiatic pennywort, is consumed raw as salad or used as a brain tonic, treatment of Alzheimer’s disease, and memory improvement. Differences in the drying method will lead to different levels of phytochemical profile and biological activity. Therefore, the present work aimed to investigate the Fourier transforms infrared (FTIR) spectra fingerprint profiles, HPLC analysis of four bioactive compounds, and antioxidant activity of C. asiatica samples exposed to various drying methods, including air-, oven-, and sun-drying. Results showed that all samples had identical FTIR spectra patterns, but there were differences in the absorbance intensities at 1692 and 1634 cm-1, showing the effect of drying methods on the content of extracts’ bioactive compounds. These differences were analysed by chemometrics namely principal components analysis (PCA), and groupings were shown for the three samples. Based on the IC50 values, oven-drying (OD) had the highest antioxidant activity, followed by sun-drying (SD) and air-drying (AD), with IC50 values of 52.25, 94.18, and 99.29 μg/mL, respectively. HPLC analysis showed that OD had a higher percentage for madecassoside and asiaticoside with values of 0.86 and 0.96%, respectively, compared to SD and AD. Meanwhile, AD had the highest content of madecassic and asiatic acids, with values of 0.50 and 0.48%. The absorbance and antioxidant activity data for the three C. asiatica extracts were analysed for the correlation using an orthogonal partial least square. Results showed that at 1006 - 989 cm-1, it positively correlated with antioxidant activity, and could be identified as the C–O functional group of alcohol and phenol.

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“…All preprocessing methods aim to reduce random noise and systematic variations in the resulting data to improve their analysis. For this reason, preprocessing of data is an important and relevant step, especially when reasonable results are to be obtained [18].…”

Section: Data Preprocessingmentioning

confidence: 99%

Application of Common Components Analysis to Mid-Infrared Spectra for the Authentication of Lebanese Honey

El Hajj,

Skaff,

Estephan

2024

Journal of Spectroscopy

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Honey is considered as a premium food produced by honeybees. It is highly appreciated by consumers around the world and raises a major concern nowadays which is ensuring its authenticity in respect to its production and its botanical origin. In Lebanon, honey is mainly multifloral which makes its authentication rather difficult. While mid-infrared (MIR) spectroscopy combined with multivariate analysis has proven to be successful in authenticating unifloral honey, the challenge with Lebanese honey lies in assessing its performance with multifloral honey. Therefore, this work aims to test the performance of common components analysis (CCA) applied on mid-infrared spectra in the authentication of multifloral Lebanese honey. For this purpose, 96 multifloral Lebanese honey samples of different floral sources were collected from different regions of the Lebanese territory and analyzed using MIR spectroscopy. CCA applied to the spectral data, allowed a separation between honeydew honey samples and floral honey samples. In addition, honey samples collected from the Bekaa plain region were differentiated from the other honey samples collected from all the other Lebanese geographical regions. This discrimination between the groups of honey samples is based essentially on their sugar composition.

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Investigating the impact of spectral data pre-processing to assess honey botanical origin through Fourier transform infrared spectroscopy (FTIR)

Cited by 19 publications

References 37 publications

Quantitatively Determine the Iron Content in the Fruit of ‘Huangguan’ Pear Using Near-Infrared Spectroscopy

Quantitatively Determine the Iron Content in the Fruit of ‘Huangguan’ Pear Using Near-Infrared Spectroscopy

Antioxidant activity and metabolite changes in Centella asiatica with different drying methods using FTIR- and quantitative HPLC-based metabolomics

Application of Common Components Analysis to Mid-Infrared Spectra for the Authentication of Lebanese Honey

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