Characterization, antioxidant activity and potential application fractionalized Szechuan pepper on fresh beef meat as natural preservative.

The pericarp of Szechuan pepper is rich in phenols and alkylamides, making it a potential source of antioxidant compounds. Despite being recognized as the primary antioxidants in Szechuan pepper, there is still limited knowledge about their application in real food systems. This study aims to identify, separate, and apply polyphenol and alkylamide fractions derived from Szechuan extracts to beef meat. Using HPLC-MS2, we identified 5 phenols and 11 alkylamides in Szechuan extracts. The quality of the minced meat was evaluated based on color, thiobarbituric acid reactive substances (TBARS), conjugated dienes, carbonyl content, Sulfhydryl content, microbiological content, and total volatile basic nitrogen content (TVB-N). Compared to the polyphenol fraction (1.25 mg/mL), alkylamide fraction (25 mg/mL), and control samples, beef samples incorporated with the polyphenol fraction (6.25 mg/mL) significantly reduced carbonyl content, TBARS, and TVB-N values at the end of storage. Furthermore, they exhibited a significant slowdown in microbial development, improved meat color stability, and preserved pH. Therefore, the use of Szechuan pepper fractions as natural preservatives in meat and meat products is an important area of research and has the potential to enhance the safety and quality of meat products.

Au-Ag OHCs-based SERS sensor coupled with deep learning CNN algorithm to quantify thiram and pymetrozine in tea.

Pesticide residue detection in food has become increasingly important. Herein, surface-enhanced Raman scattering (SERS) coupled with an intelligent algorithm was developed for the rapid and sensitive detection of pesticide residues in tea. By employing octahedral Cu2O templates, Au-Ag octahedral hollow cages (Au-Ag OHCs) were developed, which improved the surface plasma effect via rough edges and hollow inner structure, amplifying the Raman signals of pesticide molecules. Afterward, convolutional neural network (CNN), partial least squares (PLS), and extreme learning machine (ELM) algorithms were applied for the quantitative prediction of thiram and pymetrozine. CNN algorithms performed optimally for thiram and pymetrozine, with correlation values of 0.995 and 0.977 and detection limits (LOD) of 0.286 and 29 ppb, respectively. Accordingly, no significant difference (P greater than 0.05) was observed between the developed approach and HPLC in detecting tea samples. Hence, the proposed Au-Ag OHCs-based SERS technique could be utilized for quantifying thiram and pymetrozine in tea.

The anti-oxidative potential of ginger extract and its constituent on meat protein isolate under induced Fenton oxidation.

Ginger extract has been reported to possess antioxidant properties. However, components isolated from ginger have been rarely reported to inhibit oxidation. Herein, the antioxidant properties of ginger and purified components derived from it (6-gingerol, zingerone, rutin, quercetin, and kaempferol) were confirmed by using HPLC and were further used to investigate its effect on lamb meat. Myofibrillar proteins isolated (MPI) from lamb meat were incubated with ginger and its constituents under induced Fenton oxidation (1.0 mmol/L FeCl3, 0.1 mmol/L Asc, and 20 mmol/L H2O2) for 1, 3,5, and 7 h. Incubating meat protein isolate in the absence of ginger extract or its components resulted in a substantial drop in sulfhydryl groups, an increase in protein carbonyl content, and a corresponding increase in TBARS content. However, ginger extract and its constituents demonstrated antioxidant properties, which might be attributed to their hydroxyl groups and suitable solubilizing side chains. Overall, ginger extract exhibited the highest antioxidant capabilities of all treated samples, suggesting that ginger extracts may be used as a natural antioxidant in meat and lipid/protein-containing processed products. SIGNIFICANCE OF THE STUDY: Ginger extract is also frequently used as a herbal medicine due to its anti-inflammatory, anti-cancer, and antibacterial qualities. Nonvolatile pungent chemicals found in ginger, such as gingerol, shogaols, paradols, and zingerone, as well as kaempferol, rutin, and other phenolic compounds, have been confirmed in ginger extract and have been shown to have antioxidant action driven by free radical elimination. Despite these findings, ginger extract and its pure constituent components have seldom been shown to have the ability to slow protein and lipid oxidation in meat and meat-related products. The effect of ginger extracts on the oxidative stability of myofibriller protein isolate has never been investigated. Exploiting the phenolic content of ginger extract may result in a discovery that would have a huge influence on both the ginger and meat industries as well as other food processing sectors. The first aim of our study was to confirm the presence of six selected phenolic compounds (rutin, kaempferol, 6-gingerol, zingerone, naringenin, and quercetin) in ginger as reported by literature, and the second objective was to determine the efficacy of ginger extracts and its purified constituents on myofibrillar protein isolate treated under induced Fenton oxidation.

Recent trends in the micro-encapsulation of plant-derived compounds and their specific application in meat as antioxidants and antimicrobials.

The controversy around synthetic antioxidants and antimicrobials, which have been linked to major health problems, has driven both consumers and producers toward the usage of natural preservatives. Plants are excellent sources of bioactive compounds that can be used as part of raw materials during meat processing. Therefore, exploitation of plant-derived antioxidants is necessary to protect against microbial growth and to extend the self-life of meat. However, certain limitations, such as a strong organoleptic effect owing to the bitterness and acerbic taste, instability, and short shelf life of some plant bioactive compounds, limit their use in the meat system. Encapsulation is a novel and promising technique for overcoming these limitations. It protects bioactive compounds by strengthening their oxidative stability and by controlling the release of targeted compounds. Indeed, this review article provides recent advancements in the encapsulation of plant-derived compounds and their specific application in meat preservation.

Fraud detection in crude palm oil using SERS combined with chemometrics.

Edible crude palm oil (CPO) is a vital oil utilized in various industries, including food, pharmaceuticals, and domestic cooking. Unfortunately, reports of CPO adulteration with harmful Sudan dyes have surfaced over the years. Surface-enhanced Raman spectroscopy (SERS) and chemometrics were employed to detect Sudan dyes adulteration in CPO within 900 - 1800 cm- 1 Raman peak. The concentration of Sudan dyes detected in CPO samples ranged between 0.005 and 4 ppm. The principal component analysis (PCA) model detected Sudan II and Sudan IV in CPO with 99.88 and 99.90% accuracy. Linear discriminant analysis (LDA) and K-Nearest Neighbors (KNN) also recorded high detection rates of Sudan II and IV dyes in CPO. Sudan II and IV dyes could be detected at 0.0028 ppm and 0.0019 ppm by this sensor. The performance of the Au@Ag SERS sensor was comparable to that of HPLC. This study proved SERS and chemometrics can be used to authenticate edible CPO.

Application of NIR spectroscopy for rapid quantification of acid and peroxide in crude peanut oil coupled multivariate analysis.

Two key parameters (acidity and peroxide content) for evaluation of the oxidation level in crude peanut oil have been studied. The titrimetric analysis was carried out for reference data collection. Then, near-infrared spectroscopy in combination with chemometric algorithms such as partial least square (PLS); bootstrapping soft shrinkage-PLS (BOSS-PLS); uninformative variable elimination-PLS (UVE-PLS), and competitive-adaptive reweighted sampling-PLS (CARS-PLS) were attempted and assessed. The correlation coefficients of prediction (Rp), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) were used to individually evaluate the performance of the models. Optimum results were noticed with CARS-PLS, 0.9517 ≤ Rc ≤ 0.9670, 0.9503 ≤ Rp ≤ 0.9637, 0.0874 ≤ RMSEP ≤ 0.5650, and 3.14 ≤ RPD ≤ 3.64. Therefore, this affirmed that the near-infrared spectroscopy coupled with CARS-PLS could be used as a simple, fast, and non-invasive technique for quantifying acid value and peroxide value in crude peanut oil.