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Increased nitrogen deposition is a key feature of global climate change, however, its effects on the structure and assembling mechanisms of the nitrogen-fixing bacteria present at the root surface remain to be elucidated. In this pursuit, we used NH4NO3 to simulate nitrogen deposition in a 10-year-old Camellia oleifera plantation, and set up four deposition treatments, including control N0 (0 kg N hm−2 a−1), low nitrogen N20 (20 kg N hm−2 a−1), medium nitrogen N40 (40 kg N hm−2 a−1) and high nitrogen N160 (160 kg N hm−2 a−1). The results showed that nitrogen deposition affected the soil nitrogen content and the structure of the nitrogen-fixing bacterial community. Low nitrogen deposition was conducive for nitrogen fixation in mature C. oleifera plantation. With increasing nitrogen deposition, the dominant soil nitrogen-fixing bacterial community shifted from Desulfobulbaceae to Bradyrhizobium. When nitrogen deposition was below 160 kg N hm−2 a−1, the soil organic matter content, total nitrogen content, nitrate nitrogen content, ammonium nitrogen content, urease activity, soil pH and nitrate reductase activity influenced the composition of the nitrogen-fixing bacterial community, but the stochastic process remained the dominant factor. The results indicate that the strains of Bradyrhizobium japonicum and Bradyrhizobium sp. ORS 285 can be used as indicator species for excessive nitrogen deposition.

Drought stress is a critical environmental factor that significantly impacts plant growth and productivity. However, the transcriptome analysis of differentially expressed genes in response to drought stress in Camellia oleifera Abel. is still unclear. This study analyzed the transcriptome sequencing data of C. oleifera under drought treatments. A total of 20,674 differentially expressed genes (DEGs) were identified under drought stress, with the number of DEGs increasing with the duration of drought. Specifically, 11,793 and 18,046 DEGs were detected after 8 and 15 days of drought treatment, respectively, including numerous upregulated and downregulated genes. Gene Ontology (GO) enrichment analysis showed that the DEGs were primarily involved in various biological processes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that carbon metabolism, glyoxylate and dicarboxylate metabolism, proteasome, glycine, serine, and threonine metabolism were the main affected pathways. Among the DEGs, 376 protein kinases, 42 proteases, 168 transcription factor (TF) genes, and 152 other potential functional genes were identified, which may play significant roles in the drought response of C. oleifera. The expression of relevant functional genes was further validated using quantitative real-time PCR (qRT-PCR). These findings contribute to the comprehension of drought tolerance mechanisms in C. oleifera and bolster the identification of drought-resistant genes for molecular breeding purposes.

Soil nutrient transformation and the microbial metabolism are primarily regulated by soil microorganisms, including fungi and bacteria, which exhibit distinct growth patterns, energy substrate utilization, and survival strategies. Despite their significance, our understanding of the key microorganisms governing the soil microbial metabolism and multifunctionality in subtropical woodlands remains limited. To address this knowledge gap, we conducted a large-scale investigation and assessment of the soil microbial metabolic limitation and soil multifunctionality in Camellia oleifera Abel and Pinus massoniana Lamb. woodlands in subtropical China. Our results reveal that the microbial phosphorus limitation was more severe in C. oleifera compared to P. massoniana woodlands. Nonetheless, the pattern of carbon metabolic limitation for microbes and soil multifunctionality was similar in both types of woodland. Specifically, the microbial carbon limitation was positively associated with both bacterial and fungal richness, while the microbial phosphorus limitation was significantly correlated with fungi including the richness and community structure in the P. massoniana woodland. By contrast, we did not observe significant correlations between microbial metabolic limitation indices and microbial parameters in C. oleifera woodlands. Regarding soil multifunctionality, the results reveal a strong positive correlation between the soil multifunctionality and fungal community in both P. massoniana and C. oleifera woodlands. Furthermore, our structural equation modeling revealed that the soil fungal community, rather than the bacterial community, had a significant effect on the microbial metabolic limitation and soil multifunctionality. Overall, our study provides profound insights into the relative importance of bacterial and fungal communities in shaping the soil microbial metabolic limitation and soil multifunctionality in subtropical woodlands. The findings of our study have important implications for the management and conservation of subtropical woodlands.

In this paper, a distributed cooperative control problem for a class of high-order multi-input and multi-output (MIMO) nonlinear multiagent systems (MASs) in the presence of uncertain nonlinearities and external disturbances is addressed. A coupled design is developed to collaboratively approximate unknown nonlinearities and compounded disturbances by combining neural networks (NNs) with high-order disturbance observers (HODOs). To further simplify the controller structure, relationships among the Laplace matrix, adjacency matrix and consensus tracking errors are analyzed based on undirected communication graphs. Then, a distributed adaptive NN anti-disturbance control protocol is proposed for high-order MIMO nonlinear MASs based on the outputs of NNs and HODOs, where dynamic surface control (DSC) is introduced to eliminate the “computational explosion” problem of the conventional backstepping method. The semiglobally uniformly ultimate boundedness of closed-loop system signals is proven through Lyapunov theory. Finally, simulations of a quadrotor UAV formation are performed to demonstrate the effectiveness of the proposed control scheme.

A new species, Polygonatum praecox Y.F.Hu & J.W.Shao (Asparagaceae), is described and illustrated. This species is similar to P. cyrtonema, P. odoratum and P. caulialatum, but can be distinguished from P. cyrtonema by its racemose inflorescence, cylindrical hairless filaments and apex without a retrorse spur; from P. odoratum by its stout moniliform rhizome, straight stem and longer (1.7–2.2 cm long) floral tube; and from P. caulialatum by its upper part straight stem, yellowish-green corolla, lobes excurved and earlier flowering. The complete chloroplast genome of this new species is 155,115–155,256 bp in length. Phylogenetic analysis revealed that P. praecox is not genetically related to the above three morphological similar species, but is closely related to the two European species (P. multiforum and P. latifolium). This species is relatively common in mid-eastern China and has previously been confused with P. cyrtonema. As its wild resources have decreased in recent years due to over-exploitation for medicinal or edible purposes, we classify it as Near Threatened (NT) according to the IUCN Red List Criteria.

High temperature and drought are the main factors restricting the increase in Camellia oleifera Abel production that can seriously harm its physiological and biochemical functions. This study aimed to explore the effect by which Ca2+ enhances the drought resistance of C. oleifera. Four-year-old potted plants of the ‘Xianglin 210’ variety were treated with four levels of CaCl2 solution (0, 10, 20, and 40 mmol/L) and subjected to natural drought stress. The drought levels were categorized as CS (non-drought), LD (light drought), MD (moderate drought), and SD (severe drought). The effects of drought stress on the growth and physiological-biochemical characteristics of C. oleifera were measured. Under drought stress, spraying CaCl2 solution on leaves could significantly increase the net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), endogenous hormone indoleacetic acid (IAA) content, abscisic acid (ABA) content, and gibberellic acid (GA) content in organs and tissues; enhance the superoxide dismutase (SOD) activity; and decrease the concentration of intercellular carbon dioxide (Ci) and number of dehiscence fruits. Spraying 10 mmol/L CaCl2 effectively alleviates the damage of drought stress to tung oil trees. The study provides references for alleviating drought stress and increasing economic benefits in C. oleifera production.

Plant polysaccharides, a type of important bioactive compound, are involved in multiple plant defense mechanisms, and in particular polysaccharide-alleviated abiotic stress has been well studied. Polygonatum cyrtonema Hua (P. cyrtonema Hua) is a medicinal and edible perennial plant that is used in traditional Chinese medicine and is rich in polysaccharides. Previous studies suggested that sucrose might act as a precursor for polysaccharide biosynthesis. However, the role of sucrose metabolism and transport in mediating polysaccharide biosynthesis remains largely unknown in P. cyrtonema Hua. In this study, we investigated the contents of polysaccharides, sucrose, glucose, and fructose in the rhizome, stem, leaf, and flower tissues of P. cyrtonema Hua, and systemically identified the genes associated with the sucrose metabolism and transport and polysaccharide biosynthesis pathways. Our results showed that polysaccharides were mainly accumulated in rhizomes, leaves, and flowers. Besides, there was a positive correlation between sucrose and polysaccharide content, and a negative correlation between glucose and polysaccharide content in rhizome, stem, leaf, and flower tissues. Then, the transcriptomic analyses of different tissues were performed, and differentially expressed genes related to sucrose metabolism and transport, polysaccharide biosynthesis, and transcription factors were identified. The analyses of the gene expression patterns provided novel regulatory networks for the molecular basis of high accumulation of polysaccharides, especially in the rhizome tissue. Furthermore, our findings explored that polysaccharide accumulation was highly correlated with the expression levels of SUS, INV, SWEET, and PLST, which are mediated by bHLH, bZIP, ERF, ARF, C2H2, and other genes in different tissues of P. cyrtonema Hua. Herein, this study contributes to a comprehensive understanding of the transcriptional regulation of polysaccharide accumulation and provides information regarding valuable genes involved in the tolerance to abiotic stresses in P. cyrtonema Hua.

Arbuscular mycorrhizal fungi (AMF) symbiosis has been shown to improve the ability to obtain nutrients and resist adverse environmental conditions. However, there are few studies on the functions of AMF in the absorption and accumulation of boron (B). Moreover, it is still unclear whether the root colonization rates of AMF are limited by B deficiency. In this study, Camellia oleifera seedlings were planted in normal and boron-deficient substrates, and the seedlings were inoculated with Funneliformis mosseae or left uninoculated. The growth and physiological indices of C. oleifera seedlings were determined. The results of this experiment indicate that AMF inoculation increased the plant biomass, B content, B accumulation, and antioxidant enzyme activity in both normal and boron-deficient C. oleifera seedlings. Furthermore, boron deficiency resulted in a decrease in the AMF root colonization efficiency and the inhibition of C. oleifera seedlings’ growth and physiological activity. These findings suggest that AMF inoculation could improve the resistance to B-deficiency stress. Additionally, the colonization efficiency of AMF was adversely affected by B deficiency; thus, AMF play a cooperative role with B in the growth and physiological functions of plants. The results provide a theoretical basis for taking measures to solve B-deficiency stress in C. oleifera and other plants’ cultivation.

Understanding soil microbial element limitation and its relation with the microbial community can help in elucidating the soil fertility status and improving nutrient management of planted forest ecosystems. The stand age of a planted forest determines the aboveground forest biomass and structure and underground microbial function and diversity. In this study, we investigated 30 plantations of Camellia oleifera distributed across the subtropical region of China that we classified into four stand ages (planted 60 years age). Enzymatic stoichiometry analysis showed that microbial metabolism in the forests was mainly limited by C and P. P limitation significantly decreased and C limitation slightly increased along the stand age gradient. The alpha diversity of the soil microbiota remained steady along stand age, while microbial communities gradually converged from scattered to clustered, which was accompanied by a decrease in network complexity. The soil bacterial community assembly shifted from stochastic to deterministic processes, which probably contributed to a decrease in soil pH along stand age. Our findings emphasize that the stand age regulated the soil microbial metabolism limitation and community assembly, which provides new insight into the improvement of C and P management in subtropical planted forest.

A low-complexity adaptive tracking control strategy for a class of pure feedback nonlinear systems is developed in the presence of completely unknown non-affine nonlinearities, prescribed tracking performance constraints, full states constraints, and input saturation constraint. To handle the input saturation nonlinearity and the constrained states without pre-calculating the bound of virtual controllers, a new coordinate transformation approach is presented with an arc-tangent function and an auxiliary first-order dynamics. Subsequently, to deal with the completely unknown non-affine nonlinearities and the problem of prescribed performance, an inverse hyperbolic tangent function and a Nussbaum function are introduced at each step of back-stepping design, which can guarantee the control errors to vary with prescribed performance functions in time and avoid the “explosion of complexity” issue simultaneously. Then, an adaptive controller is derived from the recursive design procedure without the use of any approximators. The semi-globally uniformly ultimate boundedness of all signals in the closed-loop system and the satisfaction of all constraints are rigorously proved through Lyapunov stability analysis. Finally, the simulation studies on a hypersonic flight vehicle system are worked out to demonstrate the effectiveness and the applicability of the investigated approach.

Abstract Background Sutherlandia frutescens is one of the most promising commercialized, indigenous and medicinal plants of South Africa that is used as an immune-booster, and a traditional treatment for cancer. However, few studies report on its toxicology and dosage in vivo. There is still room to better understand its cytotoxicity effects in animal systems. Methods We prepared two extracts, one with 80% (v/v) ethanol, and the other, with water. Both were studied to determine the maximum tolerable concentration when extracts were applied at 0 to 200 μg/ml to a Tuebingen zebrafish embryo line. The development of zebrafish embryos after 24 h post fertilization (hpf) was studied. A concentration range of 5 μg/ml to 50 μg/ml was then chosen to monitor the ontological development of cultured embryos. A liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) method was used to study the differences of the two experimental extracts. Chemical variation between the extracts was illustrated using chemometrics. Results Both extracts led to bleeding and pericardial cyst formation when applied at high concentrations to the zebrafish embryo culture. Chronic teratogenic toxicities, leading to pericardial edema, yolk sac swelling, and other abnormal developmental characteristics, were detected. The aqueous extracts of S. frutescens were less toxic to the larvae than the ethanol extracts, validating preference for aqueous preparations when used in traditional medicine. Chemical differences between the water extracts and alcoholic extracts were analysed using LC-MS/MS. A supervised metabolomics approach, targeting the sutherlandiosides and sutherlandins using orthogonal partial least squares-discriminant analysis (OPLS-DA), illustrated that sutherlandiosides were the main chemical features that can be used to distinguish between the two extracts, despite the extracts being highly similar in their chemical constituents. Conclusion The water extract caused less cytotoxic and abnormal developmental effects compared to the ethanolic extract, and, this is likely due to differences in concentrations of extracted chemicals rather than the chemical profile per se. This study provides more evidence of cytotoxicity effects linked to S. frutescens using the zebrafish embryo bioassay as a study tool.

Camellia oleifera Abel. is one of the world’s four famous woody oil trees and has drawn increasing attention because of its high commercial value. Endophytes are microorganisms inhabiting inside plant tissues, and their functions vary with the change of host status and environmental parameters. To deepen our understanding of the interactions between C. oleifera and their endophytic actinobacteria, the present study investigated the four endophytic actinobacterial composition-residing high-yield C. oleifera trees. A total of 156 endophytic actinobacterial isolates were obtained distributed in 17 genera. Among them, Streptomyces was the dominant endophytic actinobacteria, followed by Nocardia, Amycolatopsis, Microbiospora, Micromonospora and other rare actinobacteria genera. Soil characteristics including soil pH and organic matter were found to play crucial roles in shaping the endophytic actinobacterial community composition. Furthermore, all isolates were studied to determine their plant growth-promotion traits, 86.54% could produce Indole 3-Acetic Acid, 16.03% showed nitrogen-fixing, 21.15% showed phosphorus solubilizing, and 35.26% produced siderophore. Under the glasshouse condition, some isolates exhibited growth promotion effects on C. oleifera seedlings with significant increase in spring shoot length and ground diameter. Altogether, this study demonstrated that C. oleifera plants harbored a high diversity and novelty of culturable endophytic actinobacteria, which represent important potential as natural biofertilizers for the high production of C. oleifera.

Camellia oleifera Abel., is an important woody plant, and its fruit contains high-quality edible oil. Production of C. oleifera has significantly expanded over the last 20 years in China. Due to the lack of appropriate information on nutrient management, its production has encountered low yield and low oil quality problems. As nitrogen (N) is an essential nutrient and the most abundant in C. oleifera tissues, the present study investigated effects of different ratios of nitrate (NO3−) and ammonium (NH4+) on the growth of a cultivar Xianglin 27 at the seedling stage. Uniform seedlings were grown in a soil-based substrate in containers and fertigated with solutions composed of six ratios of NO3− and NH4+, respectively for five months. Results showed that C. oleifera prefers both NO3− and NH4+ at a ratio of 1:1. Seedlings receiving this solution had the highest total N in leaves and total dry weight; elevated chrolophyll, soluble saccharide and protein contents as well as higher activities of peroxidase (POD), superoxide dismutase (SOD), nitrate reductase (NR), glutamine synthetase (GS), and glutamate synthase (GOGAT). Our study shows for the first time that N supply for producing C. oleifera should be an equal ratio of NO3− and NH4+.

Oil tea Camellia, as a major cash and oil crop, has a high status in the forestry cultivation systems in China. To meet the current market demand for oil tea Camellia, its potential distribution and suitable soil condition was researched, to instruct its cultivation and popularization. The potential distribution of oil tea Camellia in China was predicted by the maximum entropy model, using global environmental and soil databases. Then, we collected 10-year literature data about oil tea Camellia soil and applied multiple imputation and factor modeling for an in-depth analysis of soil suitability for growing of oil tea Camellia. The prediction indicated that oil tea Camellia was mainly distributed in Hunan, Jiangxi, Zhejiang, Hainan, East Hubei, Southwest Anhui and most of Guangdong. Climatic factors were more influential than soil factors. The minimum temperature of the coldest month, mean temperature of the coldest quarter and annual precipitation were the most significant contributors to the habitat suitability distribution. In the cultivated area of oil tea Camellia, soil fertility was poor, organic matter was the most significant factor for the soil conditions. Based on climatic and soil factor analyses, our data suggest there is a great potential to spread the oil tea Camellia cultivation industry.

Abstract Janus nanoparticles have aroused the interest of scholars because of their highly efficient emulsification of spilled oils in wastewater. In this work, interfacially active Janus hollow glass microparticles (J-HGMPs) of asymmetric wettability were designed and synthesized in order to achieve more efficient separation of emulsified oil droplets from oily wastewater. Surface characteristic techniques such as FTIR, SEM, zeta potential and contact angle measurements had been employed to assess the amphiphilic surface properties of J-HGMPs. The oil removal/recovery performance of J-HGMPs in different oil–water systems and their interfacial activities were studied. As a particulate emulsifier, J-HGMPs could remove/recover > 96% oil from oil–water mixed phase. The results showed that J-HGMPs had strong interfacial activities and anchored firmly at oil/water interfaces. This high adsorption energy was also evaluated and verified via the calculation of Gibbs free energy. Overall, this study provided a novel and low-cost oil recovery method via a convenient buoyancy force that could be effectively applied in the treatment of oil spills while achieving the goal of benign and green environmental protection.

Entropy measures the randomness or uncertainty of a stochastic process, and the entropy rate refers to the limit of the time average of entropy. The generalized entropy rate in the form of delayed averages can overcome the redundancy of initial information while ensuring stationarity. Therefore, it has better practical value. A Hidden Markov Model (HMM) contains two stochastic processes, a stochastic process in which all states can be observed and a Markov chain in which all states cannot be observed. The entropy rate is an important characteristic of HMMs. The transition matrix of a homogeneous HMM is unique, while a Nonhomogeneous Hidden Markov Model (NHMM) requires the transition matrices to be dependent on time variables. From the perspective of model structure, NHMMs are novel extensions of homogeneous HMMs. In this paper, the concepts of the generalized entropy rate and NHMMs are defined and fully explained, a strong limit theorem and limit properties of a norm are presented, and then generalized entropy ergodic theorems with an almost surely convergence for NHMMs are obtained. These results provide concise formulas for the computation and estimation of the generalized entropy rate for NHMMs.

Wind farms are usually located in plateau mountains and northern coastal areas, bringing a high probability of blade icing. Blade icing even leads to blade cracks and turbine collapse. Traditional methods of blade icing diagnosis increase operating costs and have the potential risk of damaging the original mechanical structure. A data-driven model based on a novel convolutional recurrent neural network is proposed in this article. The method can effectively extract hidden features for accurate icing diagnosis. The hyperparameters of the proposed model are optimized by the improved African vultures optimization algorithm (IAVOA). To alleviate the critical data imbalance, the adaptive synthetic (ADASYN) is used to oversample the minority classes of icing status. In comparison to the state-of-the-art classification methods, the proposed method illustrates the outstanding effectiveness in blade icing diagnosis using the sensor data from supervisory control and data acquisition (SCADA) systems. The effectiveness analysis of variables, ablation study, and sensitivity analysis validates the performance of the proposed method.

Although machine learning for quality prediction of manufacturing processes has attracted attention in the literature, there is a significant lack of case studies from industry, especially in medical sector. This paper proposes a data-driven approach to infer the batch quality of blood glucose test strips. Once the low quality of work in process is detected, unnecessary process waste could be eliminated. Starting from data pre-processing, which consists of Synthetic Minority Over-sampling TEchnique and Random Over-Sampling Example, this project tries to balance the ill-distributed data first. Followed by machine learning aims to classify and predict the quality of blood glucose test strips. Different models are evaluated by the Receiver Operating Characteristic curve and Area Under Curve. Computational results show that the decision tree and random forest after SMOTE perform better than the counterpart of ROSE method. Ensemble learning, such as random forest, out-wins base learner decision tree. To sum up, random forest with SMOTE is the suggested model for accurately predicting the quality of blood glucose test strips. There is a 30% improvement in error rate under random forest and SMOTE for NG class that could be of top concern for prognosis. Several factors, including the direction of applying test reagent onto test strips and the position where the strips are located, that affect quality of test strips have been identified. Explanations in terms of inspection and manufacturing are discussed subsequently. Finally, the prognosis of quality can be attained through big data and statistical machine learning.