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Temperature fluctuation commonly occurs in the cold chain leading to complete or partial thawing and refreezing of frozen products resulting in a multifrozen product. Such oscillation of temperature could cause significant quality reduction compared to single frozen products. This study was designed to differentiate frozen Atlantic salmon fillets based on the level of temperature fluctuation. Near‐infrared spectroscopy (NIRS) coupled with chemometrics was used to classify the frozen fillets stored at no fluctuation (NF), low fluctuation (LF), high fluctuation (HF), and very high fluctuation (VF) temperature. Using spectral profiles obtained at both frozen and thawed states, fillets were classified based on the level of temperature fluctuation by partial least squares discriminant analysis (PLS‐DA). The thawed samples showed better classification accuracy (71%) than frozen samples (66%) in a four‐class model. Considering the small variation within the first two (NF, LF) and the last two (HF, VF) groups, a two‐class classification model was developed using thawed samples, and the obtained model correctly classified the two groups ([NF, LF] and [HF, VF]) with 100 % classification accuracy. Protein‐ and water‐related changes were found important to distinguish the fillets. Based on these findings, the four‐class prediction model is found insufficient to be used for nondestructive determination of temperature history of frozen fillets. However, the two‐class prediction model with further external validation can be applied to determine the level of temperature fluctuation particularly using fillets scanned at thawed state. Practical Application: NIR spectroscopy can be used to evaluate the degree of temperature fluctuation and thus related quality loss throughout the logistics of frozen Atlantic salmon fillets. Researchers, food control authorities, and the retail industry could be the primary beneficiaries of this research output. [ABSTRACT FROM AUTHOR]

The sugar profile of a syrup determines its suitability for use in different food applications. The traditional wet chemical method for sugar profile analysis is time-consuming, destructive, and requires several chemical reagents. Therefore, this study aimed to develop a rapid method for determining the concentration of the main sugars (glucose, maltose, maltotriose, and fructose) in tapioca syrups using NIR spectroscopy in the 12000–4000 cm−1 wavenumber region or 800–2500 nm wavelength range. As large spectral variation due to water and liquid glucose was observed, orthogonal projection (OP) was evaluated to reduce those effects. Results showed that for all sugars studied, orthogonal projection prior to partial least squares regression (PLSR) improved the prediction performance in terms of the root mean square error of prediction (RMSEP) by 5–47% and the coefficient of determination for prediction (R p 2) by 3–7%. The developed models had high R p 2 and low RMSEP values, which provides opportunities for industrial monitoring of the sugar profiles of tapioca syrup products. • NIR spectroscopy allows quantifying many sugars in tapioca syrups. • Interference removal by orthogonal projection enhances prediction of syrup sugars. • High-accuracy prediction models for the individual sugars were built by using PLSR. • Identification of important wavelengths for syrup sugar profiling was established. [ABSTRACT FROM AUTHOR]

Spectroscopy in the visible near-infrared spectral (Vis-NIRS) range combined with imaging techniques (hyperspectral imaging, HSI) allows assessment of chemical composition, texture, and meat structure. The use of HSI in the meat and food industry has observed a significant growth in the last decade, yet its use for assessment of meat it is not optimal yet. The application of HSI for assessment of meat is reviewed with focus on its ability to capture meat unique chemical and structural characteristics. While HSI is widely used for assessment of chemical composition, a limited number of evidences on its ability to handle the effect of different sources of variation on the assessment is found. The use of spatially resolved spectroscopy has been able to detect structural information related to animal background, muscle type, rigor process and ageing. Similarly the use of texture features seem to capture unique characteristics of meat. [ABSTRACT FROM AUTHOR]

Diabetes, a disorder in the control of blood-glucose levels, is one of the most serious metabolic diseases worldwide. Among the investigated technologies for continuous glucose monitoring (CGM), near-infrared spectroscopy (NIR) has received the most attention. There have been many attempts to develop NIR-based CGM systems with promising in-vitro results, but they lacked robustness for in-vivo use. We critically review the application of chemometrics for CGM and the research needed. Pre-processing and multivariate-calibration techniques, which allow exploiting expert knowledge on the potential interferences, are possible solutions. The combination and first overtone bands in the ranges 2050–2300 nm and 1500–1800 nm, respectively, are the most informative regions. We therefore recommended selecting the most informative variables and exploiting the available expert knowledge on known interferences in pre-processing or multivariate calibration to develop an NIR-based CGM sensor for in-vivo use. [ABSTRACT FROM AUTHOR]

The global citrus industry is continually confronted by new technological challenges to meet the ever-increasing consumer awareness and demand for quality-assured fruit. To face these challenges, recent trend in agribusiness is declining reliance on subjective assessment of quality and increasing adoption of objective, quantitative and non-destructive techniques of quality assessment. Non-destructive instrument-based methods are preferred to destructive techniques because they allow the measurement and analysis of individual fruit, reduce waste and permit repeated measures on the same item over time. A wide range of objective instruments for sensing and measuring the quality attributes of fresh produce have been reported. Among non-destructive quality assessment techniques, near-infrared (NIR) spectroscopy (NIRS) is arguably the most advanced with regard to instrumentation, applications, accessories and chemometric software packages. This paper reviews research progress on NIRS applications in internal and external quality measurement of citrus fruit, including the selection of NIR characteristics for spectra capture, analysis and interpretation. A brief overview on the fundamental theory, history, chemometrics of NIRS including spectral pre-processing methods, model calibration, validation and robustness is included. Finally, future prospects for NIRS-based imaging systems such as multispectral and hyperspectral imaging as well as optical coherence tomography as potential non-destructive techniques for citrus quality assessment are explored. [ABSTRACT FROM AUTHOR]

Abstract: An overview is given of near infrared (NIR) spectroscopy for use in measuring quality attributes of horticultural produce. Different spectrophotometer designs and measurement principles are compared, and novel techniques, such as time and spatially resolved spectroscopy for the estimation of light absorption and scattering properties of vegetable tissue, as well as NIR multi- and hyperspectral imaging techniques are reviewed. Special attention is paid to recent developments in portable systems. Chemometrics is an essential part of NIR spectroscopy, and the available preprocessing and regression techniques, including nonlinear ones, such as kernel-based methods, are discussed. Robustness issues due to orchard and species effects and fluctuating temperatures are addressed. The problem of calibration transfer from one spectrophotometer to another is introduced, as well as techniques for calibration transfer. Most applications of NIR spectroscopy have focussed on the nondestructive measurement of soluble solids content of fruit where typically a root mean square error of prediction of 1° Brix can be achieved, but also other applications involving texture, dry matter, acidity or disorders of fruit and vegetables have been reported. Areas where more research is required are identified. [Copyright &y& Elsevier]