QTL Mapping Combined With Bulked Segregant Analysis Identify SNP Markers Linked to Leaf Shape Traits in Pisum sativum Using SLAF Sequencing

Leaf shape is an important trait that influences the utilization rate of light, and affects quality and yield of pea (Pisum sativum). In the present study, a joint method of high-density genetic mapping using specific locus amplified fragment sequencing (SLAF-seq) and bulked segregant analysis (BSA) was applied to rapidly detect loci with leaf shape traits. A total of 7,146 polymorphic SLAFs containing 12,213 SNP markers were employed to construct a high-density genetic map for pea. We conducted quantitative trait locus (QTL) mapping on an F2 population to identify QTLs associated with leaf shape traits. Moreover, SLAF-BSA was conducted on the same F2 population to identify the single nucleotide polymorphism (SNP) markers linked to leaf shape in pea. Two QTLs (qLeaf_or-1, qLeaf_or-2) were mapped on linkage group 7 (LG7) for pea leaf shape. Through alignment of SLAF markers with Cicer arietinum, Medicago truncatula, and Glycine max, the pea LGs were assigned to their corresponding homologous chromosomal groups. The comparative genetic analysis showed that pea is more closely related to M. truncatula. Based on the sequencing results of two pools with different leaf shape, 179 associated markers were obtained after association analysis. The joint analysis of SLAF-seq and BSA showed that the QTLs obtained from mapping on a high-density genetic map are convincing due to the closely associated map region with the BSA results, which provided more potential markers related to leaf shape. Thus, the identified QTLs could be used in marker-assisted selection for pea breeding in the future. Our study revealed that joint analysis of QTL mapping on a high-density genetic map and BSA-seq is a cost-effective and accurate method to reveal genetic architecture of target traits in plant species without a reference genome

Safety Index, Evaluation Model, and Comprehensive Evaluation Method of Power Information System under Classified Protection 2.0

Aiming at the problems of the low integration of the current power information system security assessment method with classified protection 2.0, strong subjectivity, and the vague quantification of objective indexes, this article proposes to establish a safety index system suitable for the electric power information system with the existing safety inspection standards for power systems on the basis of the classified protection 2.0 evaluation system. Additionally, it quantifies each index through a quantitative method combining subjective and objective methods and uses the analytic hierarchy process entropy method to obtain the combined weight of the evaluation index system. Finally, this paper summarizes the expert scores and the graded protection evaluation reports of the six systems into the original data for comprehensive weight calculation and analyzes the rationality of the weight change. The comparison and analysis of the closeness of the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) and the evaluation score of the equal guarantee have confirmed the scientificity and rationality of the evaluation model. It provides a reasonable logical idea for the implementation of the classified protection 2.0 system in the power information system

Electric Power System Operation Mechanism with Energy Routers Based on QoS Index under Blockchain Architecture

With the integration of highly permeable renewable energy to the grid at different levels (transmission, distribution and grid-connected), the volatility on both sides (source side and load side) leading to bidirectional power flow in the power grid complicates the control mechanism. In order to ensure the real-time power balance, energy exchange, higher energy utilization efficiency and stability maintenance in the electric power system, this paper proposes an integrated application of blockchain technology on energy routers at transmission and distribution networks with increased renewable energy penetration. This paper focuses on the safe and stable operation of a highly penetrated renewable energy grid-connected power system and its operation. It also demonstrates a blockchain-based negotiation model with weakly centralized scenarios for “source-network-load” collaborative scheduling operations; secondly, the QoS (quality of service) index of energy flow control and energy router node doubly-fed stability control model were designed. Further, it also introduces the MOPSO (multi-objective particle swarm optimization) algorithm for power output optimization of multienergy power generation; Thirdly, based on the blockchain underlying architecture and load prediction value constraints, this paper puts forward the optimization mechanism and control flow of autonomous energy coordination of b2u (bottom-up) between router nodes of transmission and distribution network based on blockchain

A New Power System Source-End Low Carbonization Evaluation System Considering Carbon Control Model

Under the global goal of “carbon peaking and carbon neutrality”, new power system is facing a new energy development trend of increasing the capacity of new energy and reducing the capacity and quantity of coal power. Furthermore, new power systems are also moving towards new models such as the Energy Internet and energy storage diversification. This paper combines the needs of new power systems’ “source-load interaction” and a differentiated analysis of the specific carbon emission characteristics of each subject of the Energy Internet “source-network-load-storage”. This paper analyzes the energy efficiency coefficient and carbon emission factors of each link of “source-grid-load-storage”. Therefore, the paper proposes a carbon control model for the Energy Internet. This paper focuses on the characteristics of coal power with the largest carbon reduction. Therefore, this article constructs a multi-dimensional low-carbonization evaluation index system for coal-fired power plants. In addition, this article designs a fusion weight calculation method for subjective and objective indicators based on CRITIC-G1. Additionally, this paper uses the ideal solution–gray relational method to evaluate the specified samples. Finally, this article verifies the effectiveness and feasibility of the implementation of the low-carbonization evaluation index system for coal-fired power plants

An Ecological, Power Lean, Comprehensive Marketing Evaluation System Based on DEMATEL–CRITIC and VIKOR: A Case Study of Power Users in Northeast China

The reduction of carbon emissions in the power industry will play a vital role in global decarbonization. The power industry has three main strategies to achieve this reduction in emissions: to implement lean marketing strategies that effectively target users of power and encourage them to adopt decarbonizing technologies and services; to optimize the efficiency of these users of power; and to improve the efficiency of renewable energy sources. This paper establishes a comprehensive evaluation system of indexed data from power industry customers for the development of lean marketing strategies. This system evaluates indexes derived from customer data on renewable energy sources, carbon emissions, energy efficiency, and customer credit. It adopts the DEMATEL–CRITIC combination weight assignment and VIKOR method for system evaluation and conducts simulation experiments on customer data in a region of Northeastern China to give an example of how this method could be applied in practice to lean marketing. The results show that the evaluation system proposed in this paper can govern the lean marketing decision-making of power sales enterprises

Coupled Model and Node Importance Evaluation of Electric Power Cyber-Physical Systems Considering Carbon Power Flow

To improve the distributed carbon emission optimization control capability of the smart distribution network system, thereby reducing the carbon emissions in the distribution process, it is a very important issue to comprehensively analyze the importance of the node carbon emission flow of the smart distribution network. This paper transforms the power grid into a carbon emission flow network through power flow calculations: Based on the complex network theory, it determines the coupling scale of the two networks by means of the correlation coefficient method and the correlation matrix method, and establishes a coupling network model based on the carbon emission flow network; Combining the different business characteristics of carbon emission flow and information flow, an evaluation index system considering the dual-network coupling scale is established, and a multi-indicator comprehensive evaluation method that combines the Topsis and grey relational analysis method, that can objectively evaluate indicators that contain subjective components was proposed; The obtained node importance values can be used to determine the relative key line, greater sum node importance values represent a greater carbon emission impact of the line, providing a sequential basis for the carbon reduction and restructuring of the distribution network; Taking the 3-machine 9-node system as an example, the carbon flow distribution in the corresponding network is calculated, and the comprehensive importance value of the coupling node is calculated to analyze the rationality of this method

Volatiles and Transcriptome Profiling Revealed the Formation of ‘Taro-like’ Aroma in the Leaf of Pumpkin (Cucurbita moschata)

‘Taro-like’ odor is an important economic trait of pumpkin species. The metabolic and molecular bases of this aromatic trait remain largely unexplored. Therefore, in this study, gas chromatography-mass spectrometry, GC-Olfactometry, and RNA-seq technology were used to illuminate the differential volatile compounds, the key volatile compounds, and differentially expressed genes (DEGs) in leaves from two pumpkin samples. Eight volatile compounds, including (E)-2-nonenal, 3-octanol, 2-ethyl-1-hexanol, 1-nonanol, α-terpineol, 2,3-pentanedione, caryophyllene, and 2-acetyl-1-pyrroline, were only detected in the sample with ‘taro-like’ aroma. Moreover, the variable importance in projection scores of all the above eight volatile compounds were >1.0 using PLS-DA analysis. The compounds 2-acetyl-1-pyrroline, 3-octanol, 1-nonanol, and (E)-3,7-dimethyl-2,6-octadienal were identified as the key contributors using GC-Olfactometry analysis. It was determined that 2-acetyl-1-pyrroline might play a significant role in ‘taro-like’ aroma. Furthermore, most of the differential volatile compounds were derived from fatty acids, and the DEGs were also involved in the pathways related to degradation, metabolism, and biosynthesis of fatty acids. Moreover, five genes involved in the accumulation of 2-acetyl-1-pyrroline showed differential expression, and their expression trends were consistent with 2-acetyl-1-pyrroline. This study offers the basis for further studies on the mechanism of ‘taro-like’ aroma in pumpkins