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  • Open Access

    REVIEW

    Plant Extracts as Biostimulant Agents: A Promising Strategy for Managing Environmental Stress in Sustainable Agriculture

    Mingzhao Han1, Susilawati Kasim1,*, Zhongming Yang2, Xi Deng2, Noor Baity Saidi3, Md Kamal Uddin1, Effyanti Mohd Shuib1

    Phyton-International Journal of Experimental Botany, Vol.93, No.9, pp. 2149-2166, 2024, DOI:10.32604/phyton.2024.054009 - 30 September 2024

    Abstract It is imperative to enhance crop yield to meet the demands of a burgeoning global population while simultaneously safeguarding the environment from adverse impacts, which is one of the dominant challenges confronting humanity in this phase of global climate change. To overcome this problem and reduce dependency on chemical fertilizer, scientists now view the implementation of biostimulant strategies as a cost-effective and environmentally friendly approach to achieving sustainable agriculture. Plant extracts are rich in bioactive phytocompounds, which can enhance plant resistance to disease, pest, and abiotic stresses (e.g., drought, salinity, and extreme temperature), and promote… More >

  • Open Access

    ARTICLE

    Human Stress Recognition by Correlating Vision and EEG Data

    S. Praveenkumar*, T. Karthick

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2417-2433, 2023, DOI:10.32604/csse.2023.032480 - 21 December 2022

    Abstract Because stress has such a powerful impact on human health, we must be able to identify it automatically in our everyday lives. The human activity recognition (HAR) system use data from several kinds of sensors to try to recognize and evaluate human actions automatically recognize and evaluate human actions. Using the multimodal dataset DEAP (Database for Emotion Analysis using Physiological Signals), this paper presents deep learning (DL) technique for effectively detecting human stress. The combination of vision-based and sensor-based approaches for recognizing human stress will help us achieve the increased efficiency of current stress recognition… More >

  • Open Access

    ARTICLE

    Forecasting Mental Stress Using Machine Learning Algorithms

    Elias Hossain1, Abdulwahab Alazeb2,*, Naif Al Mudawi2, Sultan Almakdi2, Mohammed Alshehri2, M. Gazi Golam Faruque3, Wahidur Rahman3

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4945-4966, 2022, DOI:10.32604/cmc.2022.027058 - 21 April 2022

    Abstract Depression is a crippling affliction and affects millions of individuals around the world. In general, the physicians screen patients for mental health disorders on a regular basis and treat patients in collaboration with psychologists and other mental health experts, which results in lower costs and improved patient outcomes. However, this strategy can necessitate a lot of buy-in from a large number of people, as well as additional training and logistical considerations. Thus, utilizing the machine learning algorithms, patients with depression based on information generally present in a medical file were analyzed and predicted. The methodology… More >

  • Open Access

    ARTICLE

    Diversity of Saxicolous Lichens along an Aridity Gradient in Central México

    José Carmen Soto-Correa1, Abraham Saldaña-Vega1, Víctor Hugo Cambrón-Sandoval1, Laura Concostrina-Zubiri2, Mariela Gómez-Romero3,*

    Phyton-International Journal of Experimental Botany, Vol.91, No.4, pp. 827-840, 2022, DOI:10.32604/phyton.2022.017929 - 09 December 2021

    Abstract Lichens are symbiotic organisms that comprise a fungus and a photosynthetic partner wich are recognized as a good indicator of climate change. However, our understanding of how aridity affects the diversity of saxicolous lichens in drylands is still limited. To evaluate the relationship between saxicolous lichen diversity and aridity in a central México dryland, a geographical transect was established of 100 km to build an aridity gradient in the semiarid zone of the State of Querétaro, Mexico, comprising ten sampling sites with a 10 km separation. Species richness, abundance and diversity of soil lichen species were recorded… More >

  • Open Access

    REVIEW

    Emerging environmental stressors and oxidative pathways in marine organisms: Current knowledge on regulation mechanisms and functional effects

    MAURA BENEDETTI, MARIA ELISA GIULIANI, MARICA MEZZELANI, ALESSANDRO NARDI, LUCIA PITTURA, STEFANIA GORBI, FRANCESCO REGOLI

    BIOCELL, Vol.46, No.1, pp. 37-49, 2022, DOI:10.32604/biocell.2022.017507 - 28 September 2021

    Abstract Oxidative stress is a critical condition derived from the imbalance between the generation of reactive oxygen species and the sophisticated network of antioxidant mechanisms. Several pollutants and environmental factors can affect this system through connected mechanisms, indirect relationships, and cascade effects from pre-transcriptional to catalytic level, by either enhancing intracellular ROS formation or impairing antioxidant defenses. This review summarizes the current knowledge on the pro-oxidant challenges from emerging environmental stressors threatening marine organisms, such as pharmaceuticals, microplastics and climate-related ocean changes. Emphasis will be placed on oxidative pathways, including signaling proteins and transcription factors involved More >

  • Open Access

    ARTICLE

    Responses of Conocarpus lancifolius to environmental stress: a case study in the semi-arid land of Kuwait

    Redha A, P Suleman, R Al-Hasan, M Afzal

    Phyton-International Journal of Experimental Botany, Vol.81, pp. 181-190, 2012, DOI:10.32604/phyton.2012.81.181

    Abstract Cococarpus lancifolius Engl. grows wild in Djibouti, Somalia and East Africa, and South Asia. The species was introduced into Kuwait, where it is exposed to several stresses: oil pollution, salinity, high temperature and harsh climatic conditions. These conditions are prevalent in its semi-arid environment. In this study, the impact of salinity (2, 6 and 10%), temperature (20, 30 and 40 °C), polyethylene glycol (10, 30 and 60%) and drought has been investigated on C. lancifolius. Proline (Pro) accumulation (5.5 ± 0.03 µg/g dry weight; p≤0.05-0.005), protein (16.47 ± 0.052 mg/g; p≤0.001), free amino acids (10.92 ± 0.082… More >

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