Prediction of the intramuscular connective tissue components of fresh and freeze-dried samples by near infrared spectroscopy

The Role of Near-Infrared Spectroscopy in Food Quality Assurance: A Review of the Past Two Decades

During food quality control, NIR technology enables the rapid and non-destructive determination of the typical quality characteristics of food categories, their origin, and the detection of potential counterfeits. Over the past 20 years, the NIR results for a variety of food groups-including meat and meat products, milk and milk products, baked goods, pasta, honey, vegetables, fruits, and luxury items like coffee, tea, and chocolate-have been compiled. This review aims to give a broad overview of the NIRS processes that have been used thus far to assist researchers employing non-destructive techniques in comparing their findings with earlier data and determining new research directions.

Development and validation of a near-infrared spectroscopy model for the prediction of muscle protein in Chinese native chickens

This study investigated the ability of the near-infrared spectroscopy (NIRS) model to predict the protein of freeze-dried muscle samples in Chinese native chickens and to determine the accuracy of the models for other native chicken breeds. Spectral pretreatment, wavelength selection, and outlier sample elimination were used to optimize the calibration models. The results showed that the best model was obtained by using a combination of standard normal variable transformation and gap-segment first-derivative pretreatment spectra after removing 48 outliers in the wavelength range of 1,439 to 1,900 nm, with coefficient of determination for the calibration (R2C) of 0.95, standard error of cross-validation (SECV) of 1.18, coefficient of determination for the prediction (R2P) of 0.95, the ratio of the standard deviation of the validation to the standard deviation of the calibration (RPDP) of 4.62. The findings indicated that NIRS can be used to predict the protein of freeze-dried muscle in Chinese native chickens.

Aquaphotomics monitoring of strawberry fruit during cold storage - A comparison of two cooling systems

The objective of this study was to use aquaphotomics and near-infrared (NIR) spectroscopy to follow the changes in strawberries during cold storage in the refrigerator with an electric field generator (supercooling fridge, SCF) and without it (control fridge, CF). The NIR spectra of strawberries stored in these refrigerators were collected over the course of 15 days using a portable mini spectrometer and their weight was measured daily. The spectral data in the region of the first overtone of water (1,300-1,600 nm) were analyzed using aquaphotomics multivariate analysis. The results showed a decrease in weight loss of strawberries, but the loss of weight was significantly lower in SCF, compared to the CF. The reduction of weight loss due to exposure to an electric field was comparable to the use of coatings. The aquaphotomics analysis showed that the NIR spectra adequately captured changes in the fruit over the storage period, and that it is possible to predict how long the fruit spent in storage, regardless of the storage type. During aquaphotomics analysis, 19 water absorbance bands were found to be consistently repeating and to have importance for the description of changes in strawberries during cold storage. These bands defined the water spectral pattern (WASP), multidimensional biomarker that was used for the description of the state and dynamics of water in strawberries during time spent in storage. Comparison of WASPs of strawberries in CF and SCF showed that exposure to an electric field leads to a delay in ripening by around 3 days. This was evidenced by the increased amount of structural, strongly bound water and vapor-like trapped water in the strawberries stored in SCF. This particular state of water in strawberries stored in SCF was related to the hardening of the strawberry skin and prevention of moisture loss, in agreement with the results of significantly decreased weight loss.

Next Generation Sequencing of Single Nucleotide Polymorphic DNA-Markers in Selecting for Intramuscular Fat, Fat Melting Point, Omega-3 Long-Chain Polyunsaturated Fatty Acids and Meat Eating Quality in Tattykeel Australian White MARGRA Lamb

Meat quality data can only be obtained after slaughter when selection decisions about the live animal are already too late. Carcass estimated breeding values present major precision problems due to low accuracy, and by the time an informed decision on the genetic merit for meat quality is made, the animal is already dead. We report for the first time, a targeted next-generation sequencing (NGS) of single nucleotide polymorphisms (SNP) of lipid metabolism genes in Tattykeel Australian White (TAW) sheep of the MARGRA lamb brand, utilizing an innovative and minimally invasive muscle biopsy sampling technique for directly quantifying the genetic worth of live lambs for health-beneficial omega-3 long-chain polyunsaturated fatty acids (n-3 LC-PUFA), intramuscular fat (IMF), and fat melting point (FMP). NGS of stearoyl-CoA desaturase (SCD), fatty acid binding protein-4 (FABP4), and fatty acid synthase (FASN) genes identified functional SNP with unique DNA marker signatures for TAW genetics. The SCD g.23881050T>C locus was significantly associated with IMF, C22:6n-3, and C22:5n-3; FASN g.12323864A>G locus with FMP, C18:3n-3, C18:1n-9, C18:0, C16:0, MUFA, and FABP4 g.62829478A>T locus with IMF. These add new knowledge, precision, and reliability in directly making early and informed decisions on live sheep selection and breeding for health-beneficial n-3 LC-PUFA, FMP, IMF and superior meat-eating quality at the farmgate level. The findings provide evidence that significant associations exist between SNP of lipid metabolism genes and n-3 LC-PUFA, IMF, and FMP, thus underpinning potential marker-assisted selection for meat-eating quality traits in TAW lambs.