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  • Open Access

    ARTICLE

    Mycorrhiza improves plant growth and photosynthetic characteristics of tea plants in response to drought stress

    FENGJUN DAI1, ZIYI RONG1, QIANGSHENG WU1, ELSAYED FATHI ABD_ALLAH3, CHUNYAN LIU1,2,*, SHENGRUI LIU2,*

    BIOCELL, Vol.46, No.5, pp. 1339-1346, 2022, DOI:10.32604/biocell.2022.018909

    Abstract Tea plants are sensitive to soil moisture deficit, with the level of soil water being a critical factor affecting their growth and quality. Arbuscular mycorrhizal fungi (AMF) can improve water and nutrient absorption, but it is not clear whether AMF can improve the photosynthetic characteristics of tea plants. A potted study was conducted to determine the effects of Claroideoglomus etunicatum on plant growth, leaf water status, pigment content, gas exchange, and chlorophyll fluorescence parameters in Camellia sinensis cv. Fuding Dabaicha under well-watered (WW) and drought stress (DS) conditions. Root mycorrhizal colonization and soil hyphal length were significantly reduced by the… More >

  • Open Access

    ARTICLE

    Deep Learning-Based Algorithm for Multi-Type Defects Detection in Solar Cells with Aerial EL Images for Photovoltaic Plants

    Wuqin Tang, Qiang Yang, Wenjun Yan*

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1423-1439, 2022, DOI:10.32604/cmes.2022.018313

    Abstract Defects detection with Electroluminescence (EL) image for photovoltaic (PV) module has become a standard test procedure during the process of production, installation, and operation of solar modules. There are some typical defects types, such as crack, finger interruption, that can be recognized with high accuracy. However, due to the complexity of EL images and the limitation of the dataset, it is hard to label all types of defects during the inspection process. The unknown or unlabeled create significant difficulties in the practical application of the automatic defects detection technique. To address the problem, we proposed an evolutionary algorithm combined with… More >

  • Open Access

    VIEWPOINT

    Associative learning in plants: light quality history may matter

    FATIMA CVRČKOVÁ*, HANA KONRÁDOVÁ

    BIOCELL, Vol.46, No.3, pp. 645-649, 2022, DOI:10.32604/biocell.2022.018114

    Abstract The possibility of associative learning in plants is a topic of ongoing controversy. In one published study, growing pea plants were reported to associate two stimuli (airflow and light) and thereafter use one (airflow) as an indicator for the other (light), similar to dogs in Pavlov’s famous experiments. However, this observation could not be independently repeated. Here we examine a possible reason for the failure of a published reproduction attempt, which used substantially different light quality during plant cultivation prior to experimental treatments than in the original study. This could have resulted in dramatically different growth characteristics. While the relevance… More >

  • Open Access

    VIEWPOINT

    Impact of nanomaterials on plants: What other implications do they have?

    ANTONIO JUÁREZ-MALDONADO*

    BIOCELL, Vol.46, No.3, pp. 651-654, 2022, DOI:10.32604/biocell.2022.017350

    Abstract The use of nanomaterials has spread and has been applied in different industries, including agriculture. Here, the possibilities presented by NMs are very varied, from the biostimulation of favorable responses, or the control of pests and diseases, to the monitoring of characteristics of interest with the use of nanosensors. Particularly the biostimulation of agricultural crops with the use of nanomaterials is very relevant, since from this process stress tolerance, higher content of biocompounds, etc., can be induced. Although the positive impacts on crops are clear, there is not enough information to determine the long-term impacts, both on ecosystems and on… More >

  • Open Access

    ARTICLE

    Intelligent Integrated Model for Improving Performance in Power Plants

    Ahmed Ali Ajmi1,2, Noor Shakir Mahmood1,2, Khairur Rijal Jamaludin1,*, Hayati Habibah Abdul Talib1, Shamsul Sarip1, Hazilah Mad Kaidi1

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5783-5801, 2022, DOI:10.32604/cmc.2022.021885

    Abstract Industry 4.0 is expected to play a crucial role in improving energy management and personnel performance in power plants. Poor performance problem in maintaining power plants is the result of both human errors, human factors and the poor implementation of automation in energy management. This problem can potentially be solved using artificial intelligence (AI) and an integrated management system (IMS). This article investigates the current challenges to improving personnel and energy management performance in power plants, identifies the critical success factors (CSFs) for an integrated intelligent framework, and develops an intelligent framework that enables power plants to improve performance. The… More >

  • Open Access

    ARTICLE

    Process Modelling and Experimental Analysis of Optimal Specimen Selection in Organic CMCs

    P. V. Rajesh1, Kanak Kalita2,*, Xiao-Zhi Gao3

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2415-2433, 2022, DOI:10.32604/cmc.2022.018247

    Abstract Bone grafting is a surgical restructuring procedure of replacing broken bones and reconstructing missing bone pieces so that complex bone fractures can be repaired to avoid any serious health risk as well as permanent bone disfiguration. Normally, human bones tend to regenerate and heal completely from fracture. But it needs a small scaffold to provide the necessary space to grow. Bone implants allow a broken bone to grow seamlessly. Traditionally, non-corrosive metal alloys are used for fixing broken bones. A metal plate is fastened between two ends of broken bones to join them. However, issues like high weight, high cost,… More >

  • Open Access

    REVIEW

    Delineating the role of phytocompounds against anti-bacterial drug resistance–An update

    REKHA GAHTORI1,#, MOSLEH MOHAMMAD ABOMUGHAID2,#, NIDHI NEGI3, SARAVANAN KRISHNAN4, SUGAPRIYA DHANASEKARAN5, SOUMYA PANDIT6, KANU PRIYA6, DILLIP KUMAR BISHI7,*, RAM PRASAD8, PIYUSH KUMAR GUPTA6,*

    BIOCELL, Vol.45, No.6, pp. 1465-1477, 2021, DOI:10.32604/biocell.2021.016484

    Abstract Antibacterial resistance developed by bacteria due to the unlimited use of antibiotics has posed a challenge for human civilization. This kind of problem is not limited to India only, but it is a global concern. Nowadays, many treatments and medicines for bacterial diseases have been developed. However, they possess some drawbacks. Therefore, the alternative medicine has been used to target the drug resistant mechanisms and such medicines have less side effects which is becoming necessary. Natural products have traditionally or historically been of importance for the development of antibacterial agents and are also known to overcome bacterial drug resistance by… More >

  • Open Access

    ARTICLE

    Cotton Leaf Diseases Recognition Using Deep Learning and Genetic Algorithm

    Muhammad Rizwan Latif1, Muhamamd Attique Khan1, Muhammad Younus Javed1, Haris Masood2, Usman Tariq3, Yunyoung Nam4,*, Seifedine Kadry5

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2917-2932, 2021, DOI:10.32604/cmc.2021.017364

    Abstract Globally, Pakistan ranks 4 in cotton production, 6 as an importer of raw cotton, and 3 in cotton consumption. Nearly 10% of GDP and 55% of the country's foreign exchange earnings depend on cotton products. Approximately 1.5 million people in Pakistan are engaged in the cotton value chain. However, several diseases such as Mildew, Leaf Spot, and Soreshine affect cotton production. Manual diagnosis is not a good solution due to several factors such as high cost and unavailability of an expert. Therefore, it is essential to develop an automated technique that can accurately detect and recognize these diseases at their… More >

  • Open Access

    ARTICLE

    Robust Optimal Proportional–Integral Controller for an Uncertain Unstable Delay System: Wind Process Application

    Rihem Farkh1,2, Yasser Fouad1,*, Haykel Marouani1

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 837-851, 2021, DOI:10.32604/iasc.2021.018214

    Abstract In industrial practice, certain processes are unstable, such as different types of reactors, distillation columns, and combustion systems. To ensure greater maneuverability and improve the speed of response command, certain systems in the military and aviation fields are purposely configured to be unstable. These systems are often more difficult to control than stable systems and are of particular interest to designers and control engineers. Despite all advances in process control over the past six decades, the proportional–integral–derivative (PID) controller is still the most common. The main reasons are the simplicity, robustness, and successful applications provided by PID-based control structures. The… More >

  • Open Access

    ARTICLE

    Effects of Region and Elevation on Adaptation of Leaf Functional Traits of an Invasive Plant Erigeron annuus in China

    Yuanyuan Liu, Zhen Li, Lie Xu, Qiang Fu*, Yongjian Wang

    Phyton-International Journal of Experimental Botany, Vol.91, No.1, pp. 115-128, 2022, DOI:10.32604/phyton.2022.015395

    Abstract A key scientific challenge relating to the threat of invasive plants on agriculture at the region level is to understand their adaptation and evolution in functional traits. Leaf functional traits, related to growth and resource utilization, might lead to adaptation of invasive plants to the geographical barriers (region or elevation). In the field experiment, we discussed the effects of region and elevation on leaf functional traits on invasive plant Erigeron annuus in farmland habitats in China. We compared leaf size, coefficient of variation (CV) of leaf traits, and fluctuating asymmetry (FA) of E. annuus from three regions (east vs. center… More >

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