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  • Open Access

    ARTICLE

    Participatory Rice Breeding in Rainfed Land to Sustainable Agriculture

    Vina Eka Aristya1, Sri Minarsih1, Kristamtini1, I Gusti Komang Dana Arsana1, Samijan1, Setyorini Widyayanti1, Sodiq Jauhari1, Arif Susila1, Ni Wayan Trisnawati1, I Ketut Mahaputra1, I Nyoman Suyasa1, Opik Mahendra2, Supriyanta3, Gilang Wirakusuma3, Taufan Alam3, Taryono3,*

    Phyton-International Journal of Experimental Botany, Vol.94, No.7, pp. 2055-2073, 2025, DOI:10.32604/phyton.2025.065227 - 31 July 2025

    Abstract Rice, as a primary commodity, needs to be increased in production while facing the sustainability challenges of limited land, water resources, and climate change. The demand for rice productivity was not enough to rely only on the fertile fields’ ability; it is necessary to consider the rainfed land potential. Cultivation in rainfed land involves biophysical pressure, low production, and limited access to superior varieties. Participatory rice breeding aimed to identify farmers’ trait preferences and develop acceptable lines. A bottom-up approach involved 203 farmers from four rainfed fields in Indonesia, i.e., Semarang-Central Java, Kulon Progo-Yogyakarta, Tabanan-Bali,… More >

  • Open Access

    ARTICLE

    Coordinated Charging Scheduling Strategy for Electric Vehicles Considering Vehicle Urgency

    Zhenhao Wang1, Hongwei Li1,*, Dan Pang2, Jinming Ge1

    Energy Engineering, Vol.122, No.8, pp. 3223-3242, 2025, DOI:10.32604/ee.2025.063615 - 24 July 2025

    Abstract Aiming at the problem of increasing the peak-to-valley difference of grid load and the rising cost of user charging caused by the disorderly charging of large-scale electric vehicles, this paper proposes a coordinated charging scheduling strategy for multiple types of electric vehicles based on the degree of urgency of vehicle use. First, considering the range loss characteristics, dynamic time-sharing tariff mechanism, and user incentive policy in the low-temperature environment of northern winter, a differentiated charging model is constructed for four types of vehicles: family cars, official cars, buses, and cabs. Then, we innovatively introduce the… More >

  • Open Access

    ARTICLE

    Rice Spike Identification and Number Prediction in Different Periods Based on UAV Imagery and Improved YOLOv8

    Fuheng Qu1, Hailong Li1,*, Ping Wang2, Sike Guo2, Lu Wang2, Xiaofeng Li3,*

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3911-3925, 2025, DOI:10.32604/cmc.2025.063820 - 03 July 2025

    Abstract Rice spike detection and counting play a crucial role in rice yield research. Automatic detection technology based on Unmanned Aerial Vehicle (UAV) imagery has the advantages of flexibility, efficiency, low cost, safety, and reliability. However, due to the complex field environment and the small target morphology of some rice spikes, the accuracy of detection and counting is relatively low, and the differences in phenotypic characteristics of rice spikes at different growth stages have a significant impact on detection results. To solve the above problems, this paper improves the You Only Look Once v8 (YOLOv8) model,… More >

  • Open Access

    ARTICLE

    Design a Computer Vision Approach to Localize, Detect and Count Rice Seedlings Captured by a UAV-Mounted Camera

    Trong Hieu Luu1, Phan Nguyen Ky Phuc2, Quang Hieu Ngo1,*, Thanh Tam Nguyen3, Huu Cuong Nguyen1

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5643-5656, 2025, DOI:10.32604/cmc.2025.064007 - 19 May 2025

    Abstract This study presents a drone-based aerial imaging method for automated rice seedling detection and counting in paddy fields. Utilizing a drone equipped with a high-resolution camera, images are captured 14 days post-sowing at a consistent altitude of six meters, employing autonomous flight for uniform data acquisition. The approach effectively addresses the distinct growth patterns of both single and clustered rice seedlings at this early stage. The methodology follows a two-step process: first, the GoogleNet deep learning network identifies the location and center points of rice plants. Then, the U-Net deep learning network performs classification and… More >

  • Open Access

    ARTICLE

    Stackelberg Game for Bilateral Transactions between Energy Storage and Wind Farms Considering the Day-Ahead Electricity Market

    Xingxu Zhu1, Guiqing Zhao1, Gangui Yan1, Junhui Li1,*, Hongda Dong2, Chenggang Li2

    Energy Engineering, Vol.122, No.5, pp. 1645-1668, 2025, DOI:10.32604/ee.2025.063192 - 25 April 2025

    Abstract The participation of wind farms in the former energy market faces challenges such as power fluctuations and energy storage construction costs. To this end, this paper proposes a joint energy storage operation scheme for multiple wind farms based on a leasing model, which assists wind farms in bidding for participation in the former energy market through leasing services, thereby enhancing energy storage efficiency and maximizing economic benefits. In this paper, based on the Weibull probability distribution to portray the uncertainty of wind power, and considering the lifetime capacity loss caused by charging and discharging of… More > Graphic Abstract

    Stackelberg Game for Bilateral Transactions between Energy Storage and Wind Farms Considering the Day-Ahead Electricity Market

  • Open Access

    ARTICLE

    Assessing Stress Tolerance of SUBI and DRO1 Introgression Lines under Flooding and Drought Conditions at Different Growth Stages

    Ibrahim Soe1,2, Emmanuel Odama3, Alex Tamu1,2, Aquilino Lado Legge Wani1,4, Taiichiro Ookawa5, Abdelbagi M. Ismail6, Jun-Ichi Sakagami1,7,*

    Phyton-International Journal of Experimental Botany, Vol.94, No.2, pp. 303-316, 2025, DOI:10.32604/phyton.2025.060016 - 06 March 2025

    Abstract Rice varieties tolerant to submergence regulate shoot elongation during short-term submergence by expressing the SUB1A gene. In contrast, the deep-rooted DRO1 is effectively expressed under drought conditions to enhance water and nutrient uptake. This study investigates the growth and yield of rice with both SUB1A and DRO1 in the background of IR64, under early-season flooding, and mid-season drought. The study used a randomized complete design with two factors: soil moisture treatments (submergence, drought, and their combination) and genotypes. The genotypes included IR64, and three near-isogenic lines (NILs): NIL-SUB1DRO1, NIL-SUB1, and NIL-DRO1. Complete submergence was imposed for 7… More >

  • Open Access

    ARTICLE

    Determination of Fungal Species to Investigate the Aflatoxin Contamination in Rice (Oryza sativa L.)

    Eman Alhomaidi1, Aisha Umar2,*, Mustansar Mubeen3, Laurent Dufossé4, Yasir Iftikhar3,*, Arpita Das5, Soumya Ghosh6, Muhammad Sibt-e-Abbas7

    Phyton-International Journal of Experimental Botany, Vol.94, No.2, pp. 407-420, 2025, DOI:10.32604/phyton.2025.058035 - 06 March 2025

    Abstract Aspergillus species produce aflatoxins and raise concerns about food safety in departmental stores and manufacturing mills. To address the risks posed by aflatoxins, and to advise the public on the highest quality rice that serves as a nutritious food source, an inquiry following the guidelines outlined in both local and international standards of food safety for the presence of aflatoxins is an essential requirement. Therefore, 16 white rice samples were selected randomly from low/high socio-economic departmental stores from 16 different localities. Grind powdered rice filtrate was extracted using chloroform. The filtrate applied on TLC plates and… More > Graphic Abstract

    Determination of Fungal Species to Investigate the Aflatoxin Contamination in Rice (<i>Oryza sativa</i> L.<i></i>)

  • Open Access

    ARTICLE

    Influences of Financial Development and Energy Price on Renewable Energy: An Italian Case

    Asif Raihan1,*, Mohammad Ridwan2, Mahdi Salehi3, Grzegorz Zimon4,*

    Energy Engineering, Vol.122, No.2, pp. 493-514, 2025, DOI:10.32604/ee.2025.059016 - 31 January 2025

    Abstract Global climate change has created substantial difficulties in the areas of sustainability, development, and environmental conservation due to the widespread dependence on fossil fuels for energy production. Nevertheless, the promotion of renewable energy programs has the potential to significantly expedite endeavors aimed at tackling climate change. Thus, it is essential to conduct a thorough analysis that considers the financial aspects to fully understand the main hurdles that are preventing the advancement of renewable energy initiatives. Italy is a leading country in the worldwide deployment of renewable energy. The objective of this research is to assess… More > Graphic Abstract

    Influences of Financial Development and Energy Price on Renewable Energy: An Italian Case

  • Open Access

    ARTICLE

    Effects of Paclobutrazol Seed Soaking on Non-Structural Carbohydrate and Grain Enrichment in Direct-Seeded Rice

    Qiang Zhang1,#, Dongsheng Gai1,#, Yong Liu1, Weiyang Liu1, Pengcheng Fu1, Xiwen Shao1, Xuanhe Liang2, Yanqiu Geng1,*, Liying Guo1,*

    Phyton-International Journal of Experimental Botany, Vol.94, No.1, pp. 269-279, 2025, DOI:10.32604/phyton.2025.060551 - 24 January 2025

    Abstract The yield of direct-seeded rice (DSR) was constrained by inadequate grain filling. Recent studies have indicated that paclobutrazol application plays a significant role in enhancing crop agronomic traits and increasing yield. This study aimed to examine the effects of paclobutrazol seed soaking (PSS) on non-structural carbohydrate accumulation and grain enrichment in DSR, potentially providing a theoretical foundation for achieving high-yield DSR cultivation. The experiment utilized two rice varieties, Jiyujing (JYJ) and Jijing305 (JJ305), with seeds soaked in paclobutrazol concentrations of 0 mg L−1 and 100 mg L−1. PSS demonstrated increased chlorophyll content, net photosynthetic rate, and… More >

  • Open Access

    ARTICLE

    Research on Stock Price Prediction Method Based on the GAN-LSTM-Attention Model

    Peng Li, Yanrui Wei, Lili Yin*

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 609-625, 2025, DOI:10.32604/cmc.2024.056651 - 03 January 2025

    Abstract Stock price prediction is a typical complex time series prediction problem characterized by dynamics, nonlinearity, and complexity. This paper introduces a generative adversarial network model that incorporates an attention mechanism (GAN-LSTM-Attention) to improve the accuracy of stock price prediction. Firstly, the generator of this model combines the Long and Short-Term Memory Network (LSTM), the Attention Mechanism and, the Fully-Connected Layer, focusing on generating the predicted stock price. The discriminator combines the Convolutional Neural Network (CNN) and the Fully-Connected Layer to discriminate between real stock prices and generated stock prices. Secondly, to evaluate the practical application… More >

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