Jingcheng Zhang¹, Xingjian Zhou¹, Dong Shen¹, Qimeng Yu¹, Lin Yuan^2,*, Yingying Dong³

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 745-762, 2024, DOI:10.32604/phyton.2024.049734

Abstract As an important rice disease, rice bacterial leaf blight (RBLB, caused by the bacterium Xanthomonas oryzae pv. oryzae), has become widespread in east China in recent years. Significant losses in rice yield occurred as a result of the disease’s epidemic, making it imperative to monitor RBLB at a large scale. With the development of remote sensing technology, the broad-band sensors equipped with red-edge channels over multiple spatial resolutions offer numerous available data for large-scale monitoring of rice diseases. However, RBLB is characterized by rapid dispersal under suitable conditions, making it difficult to track the disease at a regional scale with… More >

Guangwei Sun^1,2,#, Xuanhao Zhang^3,#, Yi Liu³, Liguang Chai², Daisong Liu², Zhenguo Chen^1,*, Shiyou Lü^3,*

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 641-659, 2024, DOI:10.32604/phyton.2024.049285

Abstract The Nicotiana genus, commonly known as tobacco, holds significant importance as a crucial economic crop. Confronted with an abundance of herbivorous insects that pose a substantial threat to yield, tobacco has developed a diverse and sophisticated array of mechanisms, establishing itself as a model of plant ecological defense. This review provides a concise overview of the current understanding of tobacco’s defense strategies against herbivores. Direct defenses, exemplified by its well-known tactic of secreting the alkaloid nicotine, serve as a potent toxin against a broad spectrum of herbivorous pests. Moreover, in response to herbivore attacks, tobacco enhances the discharge of volatile… More >

Wissal Saadellaoui¹, Samiha Kahlaoui¹, Kheiria Hcini¹, Abir Haddada¹, Noomene Sleimi^2,*, Roberta Ascrizzi³, Guido Flamini³, Fethia Harzallah-Skhiri⁴, Sondes Stambouli-Essassi¹

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 725-744, 2024, DOI:10.32604/phyton.2024.048110

Abstract In this work, we investigated aroma volatiles emanated by dry roots, stems, leaves, flowers, and fruits of Cardaria draba (L.) Desv. growing wild in Tunisia and its aerial part essential oils (EOs) composition. A total of 37 volatile organic compounds (96.7%–98.9%) were identified; 4 esters, 4 alcohols, 7 hydrocarbons, 12 aldehydes, 5 ketones, 1 lactone, 1 organosulfur compound, 2 organonitrogen compounds, and 1 acid. The hydrocarbons form the main group, representing 49.5%–84.6% of the total detected volatiles. The main constituent was 2,2,4,6,6-pentamethylheptane (44.5%–76.2%) reaching the highest relative percentages. Forty-two compounds were determined in the two fractions of EOs, representing 98.8%… More >

Yong Zhao^1,#, Yaxuan Jiang^3,#, Li Wen¹, Rui Luo², Guorui Li², Jianjun Di², Mingda Yin², Zhiyan Wang², Fenglan Huang^2,4,5,6,7,*, Fanjuan Meng^3,*

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 713-723, 2024, DOI:10.32604/phyton.2024.047657

Abstract The yield of castor is influenced by the type of inflorescence and the proportion of female flowers. However, there are few studies on the genetic mechanism involved in the development and differentiation of castor inflorescences. In this study, we performed transcriptomic analyses of three different phenotypes of inflorescences at the five-leaf stage. In comparison to the MI (complete pistil without willow leaves), 290 and 89 differentially expressed genes (DEGs) were found in the SFI (complete pistil with willow leaves) and the BI (monoecious inflorescence), respectively. Among the DEGs, 104 and 88 were upregulated in the SFI and BI, respectively, compared… More >

Xiang Lin^1,*, Jian Fang¹, Ming Zhang¹, Kuang Yin¹, Yan Tian¹, Yingfei Guo², Qianggang Wang²

Energy Engineering, Vol.121, No.5, pp. 1127-1141, 2024, DOI:10.32604/ee.2024.046861

Abstract Efforts to protect electric power systems from faults have commonly relied on the use of ultra-high frequency (UHF) antennas for detecting partial discharge (PD) as a common precursor to faults. However, the effectiveness of existing UHF antennas suffers from a number of challenges such as limited bandwidth, relatively large physical size, and low detection sensitivity. The present study addresses these issues by proposing a compact microstrip patch antenna with fixed dimensions of 100 mm × 100 mm × 1.6 mm. The results of computations yield an optimized antenna design consisting of 2nd-order Hilbert fractal units positioned within a four-layer serpentine… More > Graphic Abstract

Yang Li^1,2, Jianjun Zhao², Xiaolong Yang², He Wang^1,*, Yuyan Wang¹

Energy Engineering, Vol.121, No.5, pp. 1263-1289, 2024, DOI:10.32604/ee.2024.046784

Abstract Distributed photovoltaic (PV) is one of the important power sources for building a new power system with new energy as the main body. The rapid development of distributed PV has brought new challenges to the operation of distribution networks. In order to improve the absorption ability of large-scale distributed PV access to the distribution network, the AC/DC hybrid distribution network is constructed based on flexible interconnection technology, and a coordinated scheduling strategy model of hydrogen energy storage (HS) and distributed PV is established. Firstly, the mathematical model of distributed PV and HS system is established, and a comprehensive energy storage… More >

Chenglian Ma¹, Rui Han¹, Zhao An^2,*, Tianyu Hu², Meizhu Jin²

Energy Engineering, Vol.121, No.5, pp. 1245-1261, 2024, DOI:10.32604/ee.2024.046644

Abstract Precise forecasting of solar power is crucial for the development of sustainable energy systems. Contemporary forecasting approaches often fail to adequately consider the crucial role of weather factors in photovoltaic (PV) power generation and encounter issues such as gradient explosion or disappearance when dealing with extensive time-series data. To overcome these challenges, this research presents a cutting-edge, multi-stage forecasting method called D-Informer. This method skillfully merges the differential transformation algorithm with the Informer model, leveraging a detailed array of meteorological variables and historical PV power generation records. The D-Informer model exhibits remarkable superiority over competing models across multiple performance metrics,… More > Graphic Abstract

Dong Pan¹, Xu Gui¹, Jiayin Xu¹, Yuming Shen¹, Haoran Xu², Yinghao Ma^2,*

Energy Engineering, Vol.121, No.5, pp. 1309-1328, 2024, DOI:10.32604/ee.2024.046464

Abstract With the increasing urgency of the carbon emission reduction task, the generation expansion planning process needs to add carbon emission risk constraints, in addition to considering the level of power adequacy. However, methods for quantifying and assessing carbon emissions and operational risks are lacking. It results in excessive carbon emissions and frequent load-shedding on some days, although meeting annual carbon emission reduction targets. First, in response to the above problems, carbon emission and power balance risk assessment indicators and assessment methods, were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios, considering power supply regulation… More >

Lifeng Li¹, Zaimin Yang¹, Xiongping Yang¹, Jiaming Li², Qianyufan Zhou^3,*, Ping Yang³

Energy Engineering, Vol.121, No.5, pp. 1329-1346, 2024, DOI:10.32604/ee.2023.046447

Abstract As the global demand for renewable energy grows, solar energy is gaining attention as a clean, sustainable energy source. Accurate assessment of solar energy resources is crucial for the siting and design of photovoltaic power plants. This study proposes an integrated deep learning-based photovoltaic resource assessment method. Ensemble learning and deep learning methods are fused for photovoltaic resource assessment for the first time. The proposed method combines the random forest, gated recurrent unit, and long short-term memory to effectively improve the accuracy and reliability of photovoltaic resource assessment. The proposed method has strong adaptability and high accuracy even in the… More >

Bin Chen¹, Ziyang Li¹, Shipeng Li¹, Qingzhou Zhao¹, Xingdou Liu^2,*

Energy Engineering, Vol.121, No.5, pp. 1291-1307, 2024, DOI:10.32604/ee.2024.046374

Abstract To reduce carbon emissions, clean energy is being integrated into the power system. Wind power is connected to the grid in a distributed form, but its high variability poses a challenge to grid stability. This article combines wind turbine monitoring data with numerical weather prediction (NWP) data to create a suitable wind power prediction framework for distributed grids. First, high-precision NWP of the turbine range is achieved using weather research and forecasting models (WRF), and Kriging interpolation locates predicted meteorological data at the turbine site. Then, a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion… More >