Journal of the American Oil Chemists Society最新文献

Bioparaffins, derived from soybean oil, hold significant potential as sustainable alternatives to mineral waxes in various industrial applications. However, to fully exploit their benefits, it is necessary to engineer their performance and properties. In this work, a non-linear partial least squares (PLS) algorithm was used to relate the melting profiles obtained via differential scanning calorimetry (DSC) to the chemical composition determined by gas chromatography (GC) of simple and binary mixtures of (partially) hydrogenated samples. This model was used to determine the composition of a bioparaffin to mimic the thermal and textural properties of commercial mineral paraffin. This innovative approach allows for broader adoption in industries seeking sustainable alternatives to petroleum-based waxes.

Soybean is one of the most economically important crops in the United States. Produced for its oil and protein concentration, it is readily utilized in food products for both human and livestock consumption. Since soybean was first cultivated in the United States, increased yield has been the driving factor in breeding efforts. Though yield and oil have been observed to be positively correlated, protein concentration is negatively correlated with both. An increased effort has been underway recently to produce high-yielding cultivars that have both elevated oil and protein concentration. This has been accomplished utilizing molecular markers associated with quantitative trait loci (QTL) for both traits. To assist in this effort, more information on QTL associated with quality traits is required. In this study, 180 F_4:6 recombinant inbred lines (RILs) segregating for protein, oil, and fatty acids were produced from a cross between TN12-4098 and TN13-4303. These lines were grown across three locations in Tennessee: Research and Education Center at Milan (RECM), Highland Rim Research and Education Center (HRREC), and East Tennessee Research and Education Center (ETREC) in 2018 and 2019. Sixteen QTL were found for protein, oil, linolenic acid, and meal protein concentration. Of these identified QTL, six were novel. Developing molecular markers associated with these QTL will assist in breeding efforts to produce high-quality elite soybean cultivars that meet the demands of both farmers and consumers.

The growing interest in the rapid measurement of seed ingredients using single-kernel NIR (SKNIR) spectroscopy as a nondestructive measurement technique allows fast analysis of sample seed variance that can have effects on breeding and end-use processing. Flax (Linum usitatissimum), an oilseed crop grown in the Northwest United States and worldwide, is highly beneficial for human health, food, and fiber. Its health benefits include its high protein and omega-3 fatty acids content. Therefore, seed composition profiles are an important aspect of breeding. The goals of this research were the development of single seed NIR calibration models for protein, oil, and weight of intact flax seeds. In this study, SKNIR spectroscopy was used on a diverse set of flax accessions comprising of 306 samples to create prediction models on a custom built SKNIR instrument. Spectra data and reference protein, oil, and weight were used to build partial least squares (PLS) models. Calibration models provided reasonable prediction of these traits and could be used for screening purposes. PLS statistics were oil (R² = 0.82, SEP = 1.72), weight (R² = 0.74, SEP = 0.71), and protein (R² = 0.62, SEP = 0.96) for validation data sets comprising of one-third of the total samples. In conclusion, prediction models showed that SKNIR spectroscopy could be a very beneficial nondestructive technique to determine oil and weight as well as rapid screening of protein in single flax seeds while not requiring extensive preparation as compared to traditional techniques.

The microencapsulation of vegetable drying oils is an established strategy to develop smart coatings with self-healing properties. The literature has mostly focused on evaluating linseed oil (LO) and tung oil (TO) as self-healing agents. There is a lack of studies regarding the application of other drying oils in smart coatings and a comparison between different vegetable oils as self-healing agents has yet to be carried out. In this work, the self-healing potential of different seed oils was assessed in terms of their drying and anticorrosive properties. The investigation was focused on chia oil (CO), dehydrated castor oil (DCO), LO, and TO. Drying times were assessed under different cobalt (Co) drier contents. Drying kinetics was carried out by monitoring changes in viscosity with time and following the evolution of infrared spectra during drying. Barrier properties of the polymerized oil-based coatings were assessed by electrochemical impedance spectroscopy of carbon steel coated samples during immersion in 0.1 mol/L NaCl solution. It was found that the type of oil and concentration of drier play an important role on favoring the self-healing effect. The concentration of 0.2 wt% Co was found optimum for encapsulation to accelerate self-healing, as oils dry up to three times faster in comparison with the lowest drier content studied (0.025 wt% Co). TO obtained the best drying properties, with set-to-touch times around 1 h and rapidly forming a tack-free film, however, TO coatings ended up being extremely cracked, which compromised its barrier properties. LO obtained the slowest drying, while CO and DCO exhibited intermediate drying between TO and LO. DCO showed the best anticorrosive properties among investigated oils, as its coating was the only one that did not show any decrease in impedance with time, whereas TO and LO coatings presented a decrease in up to one order of magnitude in impedance. Overall, the good drying and barrier properties of DCO strongly stimulate its use as feedstock for self-healing coatings. Results are discussed in terms of fatty acid composition and oxidative polymerization mechanisms. Conclusions help with the selection of seed oils as self-healing agents that can further extend the lifetime of anticorrosive coatings.

Structured lipid diacylglycerol (DAG) synthesis employing bubble column reactor (BCR) is a recent and promising approach used to replace the conventional stirred tank reactor for upscaling purpose. BCR offers great economic benefits in the long run. In the present study, a screened Lecitasse® Ultra (LU) lipase was immobilized (LXTE-LU) and used repetitively in both BCR and stirring system reactor (STR) to catalyze the glycerolysis of flaxseed oil for the preparation of DAG. The BCR system was found to prolong the lipase shelf life, maintaining 69% of catalytic activity after 10 cycles. The reaction products were purified by molecular distillation to obtain DAG-40 and DAG-80. Monitoring of processing contaminants and phytonutrients during the heat treatment of flaxseed oil and flaxseed oil DAG products revealed that prolonged heat treatment significantly increased glycidyl esters levels while short-term stir-frying did not significantly affect the levels of processing contaminants levels. However, prolonged heat treatment destroyed phytonutrients. Meanwhile, the oxidation kinetic study showed that the DAG samples fitted well with the zero-order reaction kinetic model, and the oxidation rate of DAG was lower than that of flaxseed oil. Additionally, the antioxidant effect increased with higher DAG content, indicating that DAG could effectively retard lipid oxidation and improve the stability of the oxidation process. These stabilities suggest the potential application of polyunsaturated DAG in food processing systems.

Glycerol is produced on a large scale as a byproduct in the biodiesel market. In order to give an application to glycerol, this work uses diglycerol from synthesized polyglycerol and commercial triglycerol in the synthesis of long chain esters obtained from esterification and transesterification reactions with oleic acid, methyl oleate, and epoxidized methyl oleate. Diglycerol tetraoleate (DGMO), epoxidized diglycerol tetraoleate (DGEMO), and triglycerol pentaoleate (TGOA) were synthesized and characterized by ¹H and ¹³C Nuclear Magnetic Resonance (NMR) and infrared (IR) spectroscopy. Polyglycerol esters were evaluated for basic lubrication properties such as density, kinematic viscosity, viscosity index, melting point, and thermo-oxidative stability. The ester that showed best thermo-oxidative stability was DGEMO. In addition, the influence of esters synthesized as additives in a pure paraffinic oil lubricant was evaluated and the TGOA showed greater change in viscosity at 100 and 40°C and in melting point which was increased by 1.56°C.

This study investigated the effects of temperature and pressure on the yield and volatile compound contents of black cumin seed oil (BCO) extracted from black cumin seeds using supercritical carbon dioxide (SCCO₂). The solubility of BCO in SCCO₂ increased 2.5-fold as the pressure increased by 10 MPa. Major volatile compounds in BCO were identified using a static headspace gas chromatography–mass spectrometry (SH–GC–MS). Evidence indicated the main volatile components in SCCO₂-extracted BCO to be hexanal, p-cymene, and thymoquinone. BCO extracted from China-cultivated black cumin seed contained similar amounts of p-cymene and thymoquinone. This black cumin seed is classified as the cymene/thymoquinone chemotype and is also found in Indian, Iranian, and Algerian black cumin seeds. Thymoquinone contents in BCO were more sensitive to the extraction temperature than hexanal and p-cymene contents. The maximum oil yield of 36.28 ± 1.38 wt%, with approximately 2.0 mg of thymoquinone per milliliter of oil, was obtained at extraction temperatures of 50°C and pressures of 30 MPa. A SH–GC–MS could detect small molecules in black cumin seed oil such as hexanal. The results of this work reveal that temperature has more impact on the selectivity of volatile compounds than pressure in supercritical carbon dioxide extraction.

Washing crude epoxidized oil is an indispensable step for the removal of residual acetic acid and unreacted hydrogen peroxide after epoxidation. There are many studies on the epoxidation of vegetable oils but there are many discrepancies in the washing process which likely leads to water wastage, excess use of neutralizing agent, and additional processing time. Hence, this study aims to optimize the washing step by analyzing the quality of each washing step and developing a model that can predict the amount of acid removed. Soybean oil (1.5 kg) was epoxidized at 60°C for 5.5 h using Amberlite IR 120H as a heterogeneous catalyst. To determine the optimum water washing level, process parameters such as number of washing cycles (1–5), proportion of epoxidized oil to water volume (1:0.5, 1:1, 1:2, 1:3, 1:4, 1:5), and water temperature (20, 40, and 60°C) were examined. The main responses were the residual acid value and pH of the washed epoxidized oil. Results revealed that 64% of the acid was removed after 5 washing cycles irrespective of the washing water temperature and proportion. In contrast, approximately 57% of the acid was removed in the first two washing cycles. Increasing the temperature of the water affected acid removal; with approximately 54% of acid removed at 20°C compared to 60% at 60°C. Doubling or tripling the amount of water needed above a 1:0.5 ratio did not significantly affect the amount of acid removed. The model developed was significant with a predicted R² of 96% and a root mean square error (RMSE) of 1.1 when the model was validated at different washing scenarios. Therefore, this study shows that it is possible to significantly reduce the amount of water used and processing time while maintaining resin qualities.

The content of phenolic compounds in chocolate depends on the processing of the cocoa from bean to bar. The aim of this study was to determine the fate of phenolic compounds and theobromine in cocoa beans during roasting at different temperatures. Based on a screening of 12 cocoa bean sorts, three beans (NM, NCC, and NB) with initial high total phenolic content (TPC) were selected for the roasting trial (100 and 150°C up to 20 min). The concentration of three major flavonoids ((−)-catechin, (−)-epicatechin and procyanidin B2) and one methylxanthine (theobromine) were evaluated in both raw and roasted beans. Results showed changes in the concentration of flavonoids and theobromine during roasting. Roasting at 150°C for 15 min was optimal for maintaining high flavonoid levels while reducing theobromine levels. However, sensory evaluation on final product is needed to confirm whether the suggested roasting condition would also result in a final product with pleasant sensory properties.

Biodiesel (fatty acid methyl esters [FAME]) is a renewable biomass-based diesel (BBD) fuel made from plant oils, animal fats and waste greases. One of the main disadvantages of biodiesel is its poor oxidative stability, which is caused by the presence of high concentrations of unsaturated FAME. When stored in fuel terminals, vehicle tanks and fuel systems, biodiesel can react with oxygen in ambient air, causing it to degrade, which can adversely affect its viscosity and ignition quality. The shelf-life (SL) of biodiesel is an important property that defines how long it can be stored at low temperatures. The objective of this work is to develop reliable mathematical models to estimate the SL of biodiesel at T = 25°C (298.15 K). This was done by measuring oxidation induction period with a Rancimat instrument (IP_R) at variable temperatures. The data were analyzed by linear regression to determine ln(IP_R) as a function of T (Model A) and T⁻¹ (Model B) for canola, palm and soybean oil FAME (CaME, PME and SME), methyl oleate (MeC18:1) and methyl linoleate (MeC18:2). Statistical analysis of the Model A and Model B type equations showed that all inferred equations were good fits of the experimental data (adjusted coefficients of determination, R² ≥ 0.985). The most dependable results were obtained from extrapolation of Model B type equations to predict the SL^B values. For CaME, PME, SME and MeC18:1, SL^B = 559.0, 1135, 378.3 and 4515 d were inferred. However, the reliability of SL^A (extrapolated from its Model A type equation) and SL^B values calculated for MeC18:2 (3.1 and 4.8 d) were questionable as estimates of its SL at 298.15 K.