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Fourier transform infrared with attenuated total reflectance (FTIR-ATR) and Raman spectroscopy combined with partial least square regression (PLSR) were applied for the prediction of phenolic compounds and antioxidant activity in honey. Standards of catechin, syringic, vanillic, and chlorogenic acids were used for the identification and quantification of the individual phenolic compounds in six honey varieties using HPLC–DAD. Total antioxidant activity (TAC) and ferrous chelating capacity were measured spectrophotometrically. For the establishment of PLSR model, Raman spectra with Savitzky-Golay smoothing in wavenumber region 1500–400 cm −1 was used while for FTIR–ATR the wavenumber regions of 1800–700 and 3000–2800 cm −1 with multiplicative scattering correction (MSC) and Savitzky–Golay smoothing were used. The determination coefficients (R 2 ) were ranged from 0.9272 to 0.9992 for Raman while from 0.9461 to 0.9988 for FTIT-ART. The FTIR–ATR and Raman demonstrated to be simple, rapid and nondestructive methods to quantify phenolic compounds and antioxidant activities in honey. [ABSTRACT FROM AUTHOR]

This study optimizes the application of portable Near Infrared-Acousto Optically Tunable Filter (NIR) device to meet the increasing demand for cost-effective, non-invasive and easy-to-use methods for measuring physical and chemical properties during olive fruit development. Fruits from different phenotypically cultivars were sampled for firmness, total and specific phenols detection by HPLC, total anthocyanins, chlorophyll and carotenoids detection by spectrophotometry. On the same fruits, a portable NIR device in diffuse reflectance mode was employed for spectral detections. Predictive models for firmness, chlorophyll, anthocyanins, carotenoids and rutin were developed by Partial Least Square analysis. Oleuropein, verbascoside, 3,4-DHPEA-EDA, and total phenols were used to develop a validation model. Internal cross-validation was applied for calibration and predictive models. The standard errors for calibration, cross-validation, prediction, and RPD ratios (SD/SECV) were calculated as references for the model effectiveness. The determination of the optimal harvesting time facilitates the production of high quality extra virgin olive oil and table olives. [ABSTRACT FROM AUTHOR]

Highlights: [•] Hyperspectral imaging was used to determine drip loss and pH in salmon fillets. [•] The predictive abilities of PLSR models with two spectral ranges were compared. [•] Important wavelengths were selected to reduce redundancy of hyperspectral images. [•] Multivariate models were built for predicting drip loss and pH with good accuracy. [•] We developed image processing algorithm to obtain drip loss and pH distribution maps. [ABSTRACT FROM AUTHOR]