Volatile flavor of edible oils is an important quality index and factor affecting consumer choice. The purpose of this investigation was to characterize virgin Camellia oleifera seed oil (VCO) samples from different locations in southern China in terms of their volatile compounds to show the classification of VCO with respect to geography. Different samples from 20 producing VCO regions were collected in 2020 growing season, at almost the same maturity stage, and processed under the same conditions. Headspace solid-phase microextraction (HS-SPME) with a gas chromatography–mass spectrometer system (GC–MS) was used to analyze volatile compounds. A total of 348 volatiles were characterized, including aldehydes, ketones, alcohols, acids, esters, alkenes, alkanes, furans, phenols, and benzene; the relative contents ranged from 7.80–58.68%, 1.73–12.52%, 2.91–37.07%, 2.73–46.50%, 0.99–12.01%, 0.40–14.95%, 0.00–27.23%, 0.00–3.75%, 0.00–7.34%, and 0.00–1.55%, respectively. The VCO geographical origins with the largest number of volatile compounds was Xixiangtang of Guangxi (L17), and the least was Beireng of Hainan (L19). A total of 23 common and 98 unique volatile compounds were detected that reflected the basic and characteristic flavor of VCO, respectively. After PCA, heatmap and PLS-DA analysis, Longchuan of Guangdong (L8), Qingshanhu of Jiangxi (L16), and Panlong of Yunnan (L20) were in one group where the annual average temperatures are relatively low, where annual rainfalls are also low. Guangning of Guangdong (L6), Yunan of Guangdong (L7), Xingning of Guangdong (L9), Tianhe of Guangdong (L10), Xuwen of Guangdong (L11), and Xiuying of Hainan (L18) were in another group where the annual average temperatures are relatively high, and the altitudes are low. Hence, volatile compound distributions confirmed the differences among the VCO samples from these geographical areas, and the provenance difference evaluation can be carried out by flavor.

The study was carried out to evaluate the influence of polysaccharides from Camellia oleifera cake (CCP) in Lingnan yellow broilers diet from 1 to 50 days. Growth performance, carcass traits, meat quality, blood profile, and caecum microorganisms were characterized by three different levels of 0, 200 and 800 mg/kg CCP supplementation. Dietary treatment did not affect the productive trait from 1 to 50 days of age, except that average daily feed intake decreased at 42 days of age (p < 0.05). Additionally, the effects of CCP on various organs were different. The weight (p < 0.01) and index (p < 0.05) of bursa of Fabricius gradually decreased with the higher CCP supplementation at 21 days of the broilers diet. The gizzard weights were all higher when the broilers were fed with higher CCP concentration at 21, 42, and 50 days, respectively (p < 0.05). The weight and index of the spleen increased most with low CCP concentration (200 mg/kg) at 42 and 50 days. Moreover, CCP addition had no significant effect on meat quality except cooking loss (P < 0.05) and yellowness of meat color (p < 0.05). In the study of blood metabolism at 50 days of broilers, the concentration of calcium (p < 0.01), total cholesterol (p < 0.05) and uric acid (p < 0.01) decreased with higher CCP supplementation. CCP increased the albumin concentration (p < 0.001) that was highest at 200 mg/kg CCP supplementation. The addition of CCP increased the number of Lactobacillus and Enterococcus faecalis (p < 0.01) in the caecum of broilers, and had the potential to inhibit the growth of Escherichia coli (p = 0.11). Results showed that CCP played a role in improving intestinal flora and the immunity of yellow broilers.

A fast and effective determination method of different species of vegetable seeds oil is vital in the plant oil industry. The near-infrared reflectance spectroscopy (NIRS) method was developed in this study to analyze the oil and moisture contents of Camellia gauchowensis Chang and C. semiserrata Chi seeds kernels. Calibration and validation models were established using principal component analysis (PCA) and partial least squares (PLS) regression methods. In the prediction models of NIRS, the levels of accuracy obtained were sufficient for C. gauchowensis Chang and C. semiserrata Chi, the correlation coefficients of which for oil were 0.98 and 0.95, respectively, and those for moisture were 0.92 and 0.89, respectively. The near infrared spectrum of crush seeds kernels was more precise compared to intact kernels. Based on the calibration models of the two Camellia species, the NIRS predictive oil contents of C. gauchowensis Chang and C. semiserrata Chi seeds kernels were 48.71 ± 8.94% and 58.37 ± 7.39%, and the NIRS predictive moisture contents were 4.39 ± 1.08% and 3.49 ± 0.71%, respectively. The NIRS technique could determine successfully the oil and moisture contents of C. gauchowensis Chang and C. semiserrata Chi seeds kernels.

In this study, acrylic acid was used as a neutralizer to prepare bio-based WPU with an interpenetrating polymer network structure by thermally induced free radical emulsion polymerization. The effects of the content of acrylic acid on the properties of the resulting waterborne polyurethane-poly (acrylic acid) (WPU-PAA) dispersion and the films were systematically investigated. The results showed that the cross-linking density of the interpenetrating network polymers was increased and the interlocking structure of the soft and hard phase dislocations in the molecular segments of the double networks was tailored with increasing the content of acrylic acid, leading to enhancement of the mechanical properties and water resistance of WPU-PAA films. Notably, with the increase in content of acrylic acid, the tensile strength, Young’s modulus, and toughness of the WPU-PAA-110 film increased by 3 times, and 8 times, and 2.4 times compared with WPU-PAA-80, respectively. The WPU-PAA-100 film showed the best water resistance, and the water absorption rate at 96 h was only 3.27%. This work provided a new design scheme for constructing bio-based WPU materials with excellent properties.

Due to the strong polarity and volatility of organic acids, there is often a lack of effective quantitative methods for organic acids in vivo or in vitro. This study introduced a robust and scientifically validated LC-MS methodology for quantitatively analyzing six organic acids, encompassing five short-chain fatty acids and lactate, observed in in vitro fermentation and human fecal samples. This method was able to achieve precise quantification through the monitoring of mass-to-charge (m/z) ratios of the deprotonated negative ions. After optimization, a 2:1 (v/v) dichloromethane/acetonitrile mixture was utilized to extract the crude acid mix from fermentation or fecal samples. Subsequently, the organic acids were isolated using 3 mL of 3.5 M ammonium hydroxide solution from mixtures. The calibration curves for six organic acids demonstrated linearity with R² > 0.991 across the concentration ranges of 0.01–5.0 or 0.01–20 mM. The coefficient of variation and accuracy were 2–13% and 95–128%, respectively, which exhibited good precision and sensitivity. Accurate quantification of organic acids would aid in metabolic analysis in bacterial culture supernatants and human fecal matter.

A fast and effective determination method of different species of vegetable seeds oil is vital in the plant oil industry. The near-infrared reflectance spectroscopy (NIRS) method was developed in this study to massively analyze the oil and moisture contents of Camellia gauchowensis Chang and C. semiserrata Chi seeds kernels. In the prediction models of NIRS, the levels of accuracy obtained were sufficient for C. gauchowensis Chang and C. semiserrata Chi, the correlation coefficient of which oil were 0.983 and 0.962, respectively, while which of moisture were 0.937 and 0.907, respectively. The near infrared spectrum of crush seeds kernels was more precise compared to intact kernels. Based on the calibration models of the two Camellia species, the NIRS predictive oil contents of C. gauchowensis Chang and C. semiserrata Chi seeds kernels were 48.71 ± 8.94% and 31.71 ± 7.39%, respectively, and the NIRS predictive moisture contents were 4.39 ± 1.08% and 3.49 ± 0.71%, respectively. Compared with the traditional chemical measurement, the rapid, precise measurement of oil and moisture of C. gauchowensis Chang and C. semiserrata Chi seeds kernels can be actualized by NIRS method.