Comparison of de-skin pretreatment and oil extraction on aflatoxins, phthalate esters, and polycyclic aromatic hydrocarbons in peanut oil

Rapid identification of peanut oil adulteration by near infrared spectroscopy and chemometrics

Peanut oil, prized for its unique taste and nutritional value, grapples with the pressing issue of adulteration by cost-cutting vendors seeking higher profits. In response, we introduce a novel approach using near-infrared spectroscopy to non-invasively and cost-effectively identify adulteration in peanut oil. Our study, analyzing spectral data of both authentic and intentionally adulterated peanut oil, successfully distinguished high-quality pure peanut oil (PPEO) from adulterated oil (AO) through rigorous analysis. By combining near-infrared spectroscopy with factor analysis (FA) and partial least squares regression (PLS), we achieved discriminant accuracies exceeding 92 % (S > 2) and 89 % (S > 1) for FA models 1 and 2, respectively. The PLS model demonstrated strong predictive capabilities, with a prediction coefficient (R2) surpassing 93.11 and a root mean square error (RMSECV) below 4.43. These results highlight the effectiveness of NIR spectroscopy in confirming the authenticity of peanut oil and detecting adulteration in its composition.

Pre-regulation of the water content impacts on the flavor and harmful substances of sesame paste

In this study, the influence of pre-regulation of the water content (5-25 %) on the harmful substances and aroma compounds of sesame paste (SP) was investigated. The results indicated that pre-regulation of the water content reduced the generation of harmful substances in SP. Notably, the total heterocyclic amine content in SP-15 was significantly lower than in other samples. SP-10 had the lowest total polycyclic aromatic hydrocarbon content, while SP-5 exhibited the lowest PAH4 content. Using solvent-assisted aroma evaporation and GC-O-MS, 50 aroma compounds were identified in SP. Pre-regulation of water content in SP led to an elevated concentration of heterocyclic compounds thereby imparting a diverse aromatic profile. It enhanced the perceived intensity of roasted sesame and salty pastry aromas while reducing the perceived intensity of fermentation and burnt aromas. The findings suggested the pre-regulation of the water content played a crucial role in aroma modulation and harmful substances control in SP.

Moisture content in dehulled sesame seeds: A key factor affecting the aroma and safety quality of sesame paste (tahini)

This study aimed to investigate the influence of the moisture content of dehulled sesame seeds on the aroma formation and harmful substances in sesame paste (SP). The SP samples were made of dehulled sesame seeds with moisture contents of 5%, 10%, 15%, 20%, and 25% and denoted as T5, T10, T15, T20, and T25, respectively. The results revealed that adjusting the moisture content had a significant impact on aroma compounds, color intensity, and sensory properties. SP pre-adjusted to a moisture content of 10% exhibited the smallest L* value and the highest browning strength. Using gas chromatography-olfactometry-mass spectrometry analysis, the researchers identified 38 aroma-active compounds in the SP, with pyrazines being the most abundant, contributing to roasted sesame and nutty aromas. Additionally, the presence of pyrrole and furan derivatives led to enhanced caramel and almond aromas, positively influencing the overall sensory properties. T10 demonstrated the highest levels of roasted sesame and nutty odors. Furthermore, the regulation of moisture content also affected the formation of harmful compounds, such as heterocyclic amines and polycyclic aromatic hydrocarbons (PAHs). Notably, the sample made of the sesame seeds with 10% and 15% moisture content exhibited the lowest total PAHs content (18.21-28.91 ng/g) and PAH4 content (non-detectable-0.15 ng/g). The carcinogen benzo[a]pyrene was not detected in any of the samples, ensuring a safer product. The pre-adjustment of moisture content in SP appears to be a promising approach to improve both its flavor and safety qualities.

Comparison of microwave and hot-air roasting on microstructure of sesame seed, aroma-active, hazardous components, and sensory perception of sesame oil

The unclear effects of microwaves, as a greener alternative to hot air, on sensory perception, aroma, and hazardous components of sesame oil were investigated. Microwaves (900 W, 6-10 min) created more seed porosity and cell destruction and facilitated more γ-tocopherol release in sesame oil (349.30-408.50 mg/kg) than 200 °C, 20 min hot air (304.90 mg/kg). Microwaves (6-10 min) generated more aromatic heterocyclics (42.40-125.12 mg/kg) and aldehydes (5.15-2.08 mg/kg) in sesame oil than hot air (25.59 mg/kg and 1.34 mg/kg). Microwaves (6 min) produced sesame oil with a stronger roasted sesame flavour, and weaker bitter and burnt flavour than hot air. Microwaves reduced harman (≤775.19 ng/g), norharman (≤1,069.99 ng/g), and benzo(a)pyrene (≤1.59 μg/kg) in sesame oil than hot air (1,319.85 ng/g, 1,168.40 ng/g, and 1.83 μg/kg). Appropriate microwave is a promising alternative to hot air in producing sesame oil with a better sensory profile, more bioactive, and less carcinogenic components.

Single extraction and integrated non-target data acquisition with data mining workflow for analysis of hazardous substances in agricultural plant products

Identifying contaminants in agricultural plant food products (APFPs) is a major problem. In this study, we developed a single-step extraction and integrated non-target data acquisition (INDA) workflow for increasing hazardous substances coverage. D-optimal experimental designs were applied to optimize filter plate extraction (FPE) for one-single extraction of multipolar hazardous substances. The vDIA mode was used to collect all precursor ion fragments within the range to supplement data loss caused by DDA mode. The underlying principle of vDIA is to increase the utilization rate of MS2 spectra that are likely to identify a maximum number and minimum amounts of hazardous substances. Compared with traditional DDA mode alone, a combination of the two modes increased the rate of identification of hazardous substances by 18.5%. The molecular network of hazardous substance provided by GNPS could enable some metabolites and structure-related products to discover potentially hazardous substance.

A Novel Strategy for the Demulsification of Peanut Oil Body by Caproic Acid

The aqueous enzymatic method is a form of green oil extraction technology with limited industrial application, owing to the need for the demulsification of the oil body intermediate product. Existing demulsification methods have problems, including low demulsification rates and high costs, such that new methods are needed. The free fatty acids produced by lipid hydrolysis can affect the stability of peanut oil body (POB) at a certain concentration. After screening even-carbon fatty acids with carbon chain lengths below ten, caproic acid was selected for the demulsification of POB using response surface methodology and a Box-Behnken design. Under the optimal conditions (caproic acid concentration, 0.22%; solid-to-liquid ratio, 1:4.7 (w/v); time, 61 min; and temperature, 79 °C), a demulsification rate of 97.87% was achieved. Caproic acid not only adjusted the reaction system pH to cause the aggregation of the POB interfacial proteins, but also decreased the interfacial tension and viscoelasticity of the interfacial film with an increasing caproic acid concentration to realize POB demulsification. Compared to pressed oil and soxhlet-extracted oil, the acid value and peroxide value of the caproic acid demulsified oil were increased, while the unsaturated fatty acid content and oxidation induction time were decreased. However, the tocopherol and tocotrienol contents were higher than those of the soxhlet-extracted oil. This study provides a new method for the demulsification of POB.

Detecting Aflatoxin B1 in Peanuts by Fourier Transform Near-Infrared Transmission and Diffuse Reflection Spectroscopy

Aflatioxin B₁ (AFB₁) has been recognized by the International Agency of Research on Cancer as a group 1 carcinogen in animals and humans. A fast, batch, and real-time control and no chemical pollution method was developed for the discrimination and quantification prediction of AFB₁-infected peanuts by applying Fourier transform near-infrared (FT-NIR) coupled with chemometrics. Initially, the near-infrared transmission (NIRT) and diffuse reflection (NIRR) modules were applied to collect spectra of the samples. The principal component analysis (PCA) method was employed to extract the characteristic wavelength, followed by different preprocessing methods (seven methods) to build an effective linear discriminant analysis (LDA) classification and partial least squares (PLS) quantification models. The results showed that, for both the NIRT or NIRR modules, the LDA classification models satisfactorily distinguished peanuts infected with AFB₁ or from those not infected, with external validation showing a 100% correct identification rate and a 0% misjudgment rate. In addition, combined with the concentration of AFB₁ in peanuts determined by enzyme-linked immunoassay assay, the best partial least squares (PLS) models were established, with a combination of the first derivative and the Norris derivative filter smoothing pretreatment (R_c² = 0.937 and 0.984, RMSECV = 3.92% and 2.22%, RPD = 3.98 and 7.91 for NIRR and NIRT, respectively). The correlation coefficient between the predicted value and the reference value in the external verification was 0.998 and 0.917, respectively. This study highlights that both spectral acquisition modules meet the requirements of online, rapid, and accurate identification of peanut AFB₁ infection in the early stages.

Determination of Five Phthalate Esters in Tea and Their Dynamic Characteristics during Black Tea Processing

A highly specific and high extraction-rate method for the analysis of dimethyl phthalate (DMP), diethyl phthalate (DEP), di-n-butyl phthalate (DBP), diisobutyl phthalate (DiBP), and di-(2-ethyl) hexyl phthalate (DEHP) in tea samples was developed. Based on three-factor Box-Behnken response surface design, solid-phase extraction (SPE) of five phthalate ester (PAE) residues in tea was optimized. Optimal extraction conditions were found for extraction temperature (40 °C), extraction time (12 h), and ratio of tea to n-hexane (1:20). The dynamic distribution of PAEs at each stage of black tea processing was also analyzed, and it was found that the baking process was the main stage of PAE emission, indicating that traditional processing of black tea significantly degrades PAEs. Further, principal component analysis of the physicochemical properties and processing factors of the five PAEs identified the main processing stages affecting the release of PAEs, and it was found that the degradation of PAEs during black tea processing is also related to its own physicochemical properties, especially the octanol-water partition coefficient. These results can provide important references for the detection, determination of processing losses, and control of maximum residue limits (MRLs) of PAEs to ensure the quality and safety of black tea.