Effects of Cultivars and Geography in China on the Lipid Characteristics of Camellia oleifera Seeds

The complex hexaploid oil-Camellia genome traces back its phylogenomic history and multi-omics analysis of Camellia oil biosynthesis

Oil-Camellia (Camellia oleifera), belonging to the Theaceae family Camellia, is an important woody edible oil tree species. The Camellia oil in its mature seed kernels, mainly consists of more than 90% unsaturated fatty acids, tea polyphenols, flavonoids, squalene and other active substances, which is one of the best quality edible vegetable oils in the world. However, genetic research and molecular breeding on oil-Camellia are challenging due to its complex genetic background. Here, we successfully report a chromosome-scale genome assembly for a hexaploid oil-Camellia cultivar Changlin40. This assembly contains 8.80 Gb genomic sequences with scaffold N50 of 180.0 Mb and 45 pseudochromosomes comprising 15 homologous groups with three members each, which contain 135 868 genes with an average length of 3936 bp. Referring to the diploid genome, intragenomic and intergenomic comparisons of synteny indicate homologous chromosomal similarity and changes. Moreover, comparative and evolutionary analyses reveal three rounds of whole-genome duplication (WGD) events, as well as the possible diversification of hexaploid Changlin40 with diploid occurred approximately 9.06 million years ago (MYA). Furthermore, through the combination of genomics, transcriptomics and metabolomics approaches, a complex regulatory network was constructed and allows to identify potential key structural genes (SAD, FAD2 and FAD3) and transcription factors (AP2 and C2H2) that regulate the metabolism of Camellia oil, especially for unsaturated fatty acids biosynthesis. Overall, the genomic resource generated from this study has great potential to accelerate the research for the molecular biology and genetic improvement of hexaploid oil-Camellia, as well as to understand polyploid genome evolution.

A critical review of the bioactive ingredients and biological functions of camellia oleifera oil

Camellia oleifera oil is a pure and natural high-grade oil prevalent in South China. Camellia oleifera oil is known for its richness in unsaturated fatty acids and high nutritional value. There is increasing evidence indicating that a diet rich in unsaturated fatty acids is beneficial to health. Despite the widespread production of Camellia oleifera oil and its bioactive components, reports on its nutritional components are scarce, especially regarding systematic reviews of extraction methods and biological functions. This review systematically summarized the latest research on the bioactive components and biological functions of Camellia oleifera oil reported over the past decade. In addition to unsaturated fatty acids, Camellia oleifera oil contains six main functional components contributing to its antioxidant, antibacterial, anti-inflammatory, antidiabetic, anticancer, neuroprotective, and cardiovascular protective properties. These functional components are vitamin E, saponins, polyphenols, sterols, squalene, and flavonoids. This paper reviewed the biological activity of Camellia oleifera oil and its extraction methods, laying a foundation for further development of its bioactive components.

Quality Evaluation of the Oil of Camellia spp

The oil of Camellia spp. has become a well-known high-quality edible oil because of its rich nutrition. It is of great significance to breed fine varieties of Camellia spp. for the sustainable growth of the Camellia spp. industry. This study mainly evaluated the quality and antioxidant capacity of the camellia seed from several sources. The fatty acid composition and main active components of 40 kinds of C. oleifera, C. vietnamensis, C. osmantha, and C. gigantocarpa seeds, and so on, from different regions, were tested using GC-MS and HPLC. The quality of different Camellia spp. germplasm resources was comprehensively evaluated using multiple indices. The unsaturated fatty acid content and the antioxidant capacity of C. vietnamensis from Hainan were higher than those of C. oleifera Abel. In addition, there were a few differences in the fatty acid compositions of Camellia spp. oil from different species. Correlation analysis confirmed that rutin, total saponin, total flavonoids, squalene, and vitamin E were strongly correlated to the antioxidant capacity of Camellia spp. In the comprehensive evaluation, the best quality and strongest antioxidant activity were found for Chengmai Dafeng (C. vietnamensis). These methods in the study were applied for the first time for the quality evaluation of the Camellia spp. species. This study provided new insights into the quality evaluation of the Camellia spp. species, thus facilitating further development of variety breeding along with quality evaluation.

Applications of Chinese Camellia oleifera and its By-Products: A Review

Camellia oleifera is a woody oil tree species unique to China that has been cultivated and used in China for more than 2,300 years. Most biological research on C. oleifera in recent years has focused on the development of new varieties and breeding. Novel genomic information has been generated for C. oleifera, including a high-quality reference genome at the chromosome level. Camellia seeds are used to process high-quality edible oil; they are also often used in medicine, health foods, and daily chemical products and have shown promise for the treatment and prevention of diseases. C. oleifera by-products, such as camellia seed cake, saponin, and fruit shell are widely used in the daily chemical, dyeing, papermaking, chemical fibre, textile, and pesticide industries. C. oleifera shell can also be used to prepare activated carbon electrodes, which have high electrochemical performance when used as the negative electrode of lithium-ion batteries. C. oleifera is an economically valuable plant with diverse uses, and accelerating the utilization of its by-products will greatly enhance its industrial value.

Evaluation of the economic characteristics of the fruit of 45 superior Camellia weiningensis Y.K. Li. trees

Reports related to Camellia weiningensis Y.K. Li. are rare. We evaluated the economic characteristics of the mature fruit of 45 superior C. weiningensis trees using principal component analysis (PCA) and gray correlation analysis, and identified excellent germplasms according to performance. PCA was employed to reduce the dimensions. PCA was performed for the original 15 indices of fruit diameter, fruit length, fruit shape, single-fruit weight, pericarp thickness, oil yield, fresh seed rate, dry seed rate, dry kernel rate and palmitic acid, stearic acid, linolenic acid, oleic acid, linoleic acid and arachidonic acid contents. According to the requirements of a cumulative contribution rate ≥ 80% and an eigenvector value > 1, six principle components were selected. These indices underwent weighted summation to establish a function model for comprehensive evaluation. Finally, the comprehensive rankings of the cultivars according to PCA were compared with those according to gray correlation analysis. The genetic variation coefficients of the 15 parameters ranged from 2.24% (oleic acid content) to 22.70% (single-fruit weight, with a range of 21.34 g). The top ten excellent cultivars with the highest comprehensive scores according to PCA and those according to gray correlation analysis were compared. According to PCA, oleic acid content, fruit diameter, fruit length, pericarp thickness, arachidonic acid content and dry seed rate can serve as representative evaluation indicators of C. weiningensis. The outcomes obtained based on PCA were basically consistent with those obtained based on gray correlation analysis. Finally, nine excellent cultivars were finally determined, i.e., WY-1, WY-6, WY-8, WY-25, WY-27, WY-30, WY-33, WY-35, WY-38 and WY-44. The results obtained in terms of crown yield were basically consistent with the outcomes of the comprehensive assessments, which indicates the reliability of the assessment methods used in this study.

Characterization of the Volatile Compounds in Camellia oleifera Seed Oil from Different Geographic Origins

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.

Identification of Oil Tea (Camellia oleifera C.Abel) Cultivars Using EfficientNet-B4 CNN Model with Attention Mechanism

Cultivar identification is a basic task in oil tea (Camellia oleifera C.Abel) breeding, quality analysis, and an adjustment in the industrial structure. However, because the differences in texture, shape, and color under different cultivars of oil tea are usually inconspicuous and subtle, the identification of oil tea cultivars can be a significant challenge. The main goal of this study is to propose an automatic and accurate method for identifying oil tea cultivars. In this study, a new deep learning model is built, called EfficientNet-B4-CBAM, to identify oil tea cultivars. First, 4725 images containing four cultivars were collected to build an oil tea cultivar identification dataset. EfficientNet-B4 was selected as the basic model of oil tea cultivar identification, and the Convolutional Block Attention Module (CBAM) was integrated into EfficientNet-B4 to build EfficientNet-B4-CBAM, thereby improving the focusing ability of the fruit areas and the information expression capability of the fruit areas. Finally, the cultivar identification capability of EfficientNet-B4-CBAM was tested on the testing dataset and compared with InceptionV3, VGG16, ResNet50, EfficientNet-B4, and EfficientNet-B4-SE. The experiment results showed that the EfficientNet-B4-CBAM model achieves an overall accuracy of 97.02% and a kappa coefficient of 0.96, which is higher than that of other methods used in comparative experiments. In addition, gradient-weighted class activation mapping network visualization also showed that EfficientNet-B4-CBAM can pay more attention to the fruit areas that play a key role in cultivar identification. This study provides new effective strategies and a theoretical basis for the application of deep learning technology in the identification of oil tea cultivars and provides technical support for the automatic identification and non-destructive testing of oil tea cultivars.