Fruit economic characteristics and yields of 40 superior Camellia oleifera Abel plants in the low-hot valley area of Guizhou Province, China

High-yield hybrid breeding of Camellia oleifolia based on ISSR molecular markers

BACKGROUND

C. Oleifera is among the world's largest four woody plants known for their edible oil production, yet the contribution rate of improved varieties is less than 20%. The species traditional breeding is lengthy cycle (20-30 years), occupation of land resources, high labor cost, and low accuracy and efficiency, which can be enhanced by molecular marker-assisted selection. However, the lack of high-quality molecular markers hinders the species genetic analysis and molecular breeding.

RESULTS

Through quantitative traits characterization, genetic diversity assessment, and association studies, we generated a selection population with wide genetic diversity, and identified five excellent high-yield parental combinations associated with four reliable high-yield ISSR markers. Early selection criteria were determined based on kernel fresh weight and cultivated 1-year seedling height, aided by the identification of these 4 ISSR markers. Specific assignment of selected individuals as paternal and maternal parents was made to capitalize on their unique attributes.

CONCLUSIONS

Our results indicated that molecular markers-assisted breeding can effectively shorten, enhance selection accuracy and efficiency and facilitate the development of a new breeding system for C. oleifera.

Production of Camellia oleifera Abel Seed Oil for Injection: Extraction, Analysis, Deacidification, Decolorization, and Deodorization

Camellia seed oil (CSO), as a nutrient-rich edible oil, is widely used in foods, cosmetics, and other fields. In this work, the extraction, deacidification, decolorization, and deodorization processes of CSO were respectively optimized for meeting injectable oil standards. The results showed that the CSO extraction rate reached the highest level of 94% at optimized conditions (ultrasonic time, 31.2 min; reaction pH, 9.2; and reaction time, 3.5 h). The physicochemical indexes of CSO and 10 other vegetable oils were evaluated by the principal component analysis method, and the overall scores of vegetable oils were ranked as camellia seed oil > olive oil > rice oil > peanut oil > sesame oil > corn oil > soybean oil > sunflower oil > rapeseed oil > walnut oil > flaxseed oil. The physicochemical indicators of CSO were the most ideal among the 11 vegetable oils, which means that CSO is suitable as an injectable oil. Through the optimized processes of the deacidification, decolorization, and deodorization, the CSO acid value was reduced to 0.0515 mg KOH/g, the decolorization rate reached a maximum of 93.86%, and the OD430 was 0.015, meeting the requirement (≤0.045 of OD430) of injectable oil. After the deodorization process, these parameters of the refractive index, acid value, saponification value, iodine value, absorbance, unsaponifiable, moisture and volatiles, fatty acid composition, and heavy metal limits all met the pharmacopoeia standards of injectable oil in many countries and regions. The possibility of CSO as an injectable oil was first verified through refining-process optimization and nutritional index analysis, providing an important technical reference for the high-value utilization of vegetable oil.

Classification of Camellia oleifera Diseases in Complex Environments by Attention and Multi-Dimensional Feature Fusion Neural Network

The use of neural networks for plant disease identification is a hot topic of current research. However, unlike the classification of ordinary objects, the features of plant diseases frequently vary, resulting in substantial intra-class variation; in addition, the complex environmental noise makes it more challenging for the model to categorize the diseases. In this paper, an attention and multidimensional feature fusion neural network (AMDFNet) is proposed for Camellia oleifera disease classification network based on multidimensional feature fusion and attentional mechanism, which improves the classification ability of the model by fusing features to each layer of the Inception structure and enhancing the fused features with attentional enhancement. The model was compared with the classical convolutional neural networks GoogLeNet, Inception V3, ResNet50, and DenseNet121 and the latest disease image classification network DICNN in a self-built camellia disease dataset. The experimental results show that the recognition accuracy of the new model reaches 86.78% under the same experimental conditions, which is 2.3% higher than that of GoogLeNet with a simple Inception structure, and the number of parameters is reduced to one-fourth compared to large models such as ResNet50. The method proposed in this paper can be run on mobile with higher identification accuracy and a smaller model parameter number.

Characterization and comprehensive evaluation of phenotypic characters in wild Camellia oleifera germplasm for conservation and breeding

Camellia oleifera Abel. is an economically important woody oil plant native to China. To explore the genetic diversity of wild C. oleifera phenotypic traits and effectively protect these germplasm resources, this study provides a thorough evaluation of the phenotypic variability of a cluster of 143 wild C. oleifera germplasm resources. A total of 41 characters, including leaves, flowers, fruits, seeds, and oil quality characters, were investigated based on the quantization of physical and chemical descriptors and digital image analysis. The findings revealed significant variations among the 41 characters with a high range of Shannon-Wiener indexes (H') from 0.07 to 2.19. The coefficient of variation (CV) among 32 quantitative characters ranged from 5.34% to 81.31%, with an average of 27.14%. High genetic diversity was also detected among the 143 germplasm. Based on the analysis of hierarchical clustering, 143 accessions were separated into six categories. All the individuals can be clearly distinguished from each other according to the result of the principal component analysis (PCA). The M-TOPSIS exhaustive evaluation method based on correlation and PCA analyses of 32 quantitative characters was applied for the 143 wild C. oleifera accessions, and the top 10 varieties were identified as YA53, YA13, YA40, YA34, YA57, YA19, YA33, YA41, DZ8, and YA7. This research optimized the germplasm evaluation system and perfected the statistical phenotypic traits for distinctness, uniformity, and stability (DUS) testing. Some top-notch germplasm sources were also screened for oil-tea Camellia breeding.

Multi-omics joint analysis reveals how Streptomyces albidoflavus OsiLf-2 assists Camellia oleifera to resist drought stress and improve fruit quality

Camellia oleifera (C. oleifera) is a unique edible oil crop in China cultivated in the hilly southern mountains. Although C. oleifera is classified as a drought-tolerant tree species, drought remains the main factor limiting the growth of C. oleifera in summer and autumn. Using endophytes to improve crop drought tolerance is one effective strategy to meet our growing food crop demand. In this study, we showed that endophyte Streptomyces albidoflavus OsiLf-2 could mitigate the negative impact of drought stress on C. oleifera, thus improving seed, oil, and fruit quality. Microbiome analysis revealed that OsiLf-2 treatment significantly affected the microbial community structure in the rhizosphere soil of C. oleifera, decreasing both the diversity and abundance of the soil microbe. Likewise, transcriptome and metabolome analyses found that OsiLf-2 protected plant cells from drought stress by reducing root cell water loss and synthesizing osmoregulatory substances, polysaccharides, and sugar alcohols in roots. Moreover, we observed that OsiLf-2 could induce the host to resist drought stress by increasing its peroxidase activity and synthesizing antioxidants such as cysteine. A multi-omics joint analysis of microbiomes, transcriptomes, and metabolomes revealed OsiLf-2 assists C. oleifera in resisting drought stress. This study provides theoretical and technical support for future research on endophytes application to enhance the drought resistance, yield, and quality of C. oleifera.

Genetic Diversity Analysis and Core Germplasm Collection Construction of Camellia oleifera Based on Fruit Phenotype and SSR Data

Many Camellia oleifera germplasm resources were collected from Guizhou Province, but the fruit morphological variation and genetic diversity of C. oleifera germplasm resources remain unclear. The genetic diversity of C. oleifera germplasms resources in Guizhou was studied based on fruit traits and simple sequence repeat (SSR) molecular markers to build a core collection. This paper aims to provide a scientific basis for the collection, management, development, and utilization of C. oleifera resources in Guizhou province. The variation coefficients among and within varieties of seven fruit phenotypic traits of C. oleifera ranged from 11.79% to 61.76% and from 8.15% to 42.31%, respectively, showing rich phenotypic variation. Furthermore, 12 SSR markers were used to analyze the genetic diversity. These primers generated 214 polymorphic bands, and the average number was 17.833. The average number of effective alleles (Ne), Shannon's information index (I), observed heterozygosity (Ho), expected heterozygosity (He), polymorphic information content (PIC), and major allele frequency (MAF) were 8.999, 2.301, 0.965, 0.50, 0.836, and 0.238, respectively. The results showed that 12 SSR markers had high polymorphism, and the genetic diversity of 167 C. oleifera germplasm resources was high. Based on SSR molecular marker information and fruit traits clustering, 167 C. oleifera germplasm resources were divided into three groups. When constructing core collections based on fruit traits and molecular marker information, the PowerCore-25 of core collections greatly preserves fruit traits and improves genetic diversity. This paper can provide a reference for the genetic diversity and fruit traits variation of C. camellia germplasm resources in Guizhou Province. It is significant for establishing a core collection, thus promoting germplasm innovation and the development of the oil tea industry in Guizhou.