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  • Open Access

    ARTICLE

    Optimizing Cherry Tomato Growth under Heat Stress Using Semi-Enclosed Greenhouses and LED Spectra

    Nuttabodee Viriyawattana, Surachat Sinworn*

    Phyton-International Journal of Experimental Botany, Vol.95, No.8, 2026, DOI:10.32604/phyton.2026.086514 - 28 August 2026

    Abstract High solar radiation during the Thai summer raises greenhouse temperatures to 33–41°C, exceeding the optimal range for tomato cultivation (15–25°C) and reducing yield and fruit quality. This study aimed to evaluate the effectiveness of combining daytime shading with evening supplemental light-emitting diode (LED) lighting to improve the growth, yield, and fruit quality of cherry tomato grown under heat-stress conditions. To alleviate excessive heat accumulation, a semi-enclosed greenhouse equipped with an 80% shade net was applied from 11:00 to 14:00, while supplemental LED lighting was provided from 18:00 to 22:00. Plants were exposed to red, blue,… More >

  • Open Access

    ARTICLE

    Freshness Detection of Plasma Treated Tomato Using CFL-YOLOv8n

    Shaohuang Bian1,#, Qinxiu Gao1,#, Shan Su1, Weifeng Wang1, Feng Huang2,*

    CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.081818 - 23 July 2026

    Abstract Tomato, as a globally important crop, its freshness directly affects postharvest quality, market value, and consumer acceptance. Traditional tomato freshness evaluation mainly relies on manual inspection and experience-based judgment, which is time-consuming, labor-intensive, and inefficient. Meanwhile, plasma technology has shown promising potential in agricultural preservation due to its safety and effectiveness, making the evaluation of tomato freshness after plasma treatment particularly important. In recent years, with the rapid development of deep learning technology, non-destructive detection methods based on image analysis have become important tools for agricultural product quality assessment. This study proposes an improved YOLOv8n-based… More >

  • Open Access

    ARTICLE

    CENPF Promotes Gastric Cancer Proliferation through c-Myc-Mediated GLS1 Upregulation and Glutamine Metabolism

    Min Dong1,#, Zongchang Song2,#, Xiaohui Lu1,3,#, Minxue Lu4,*, Chen Zhong1,*

    Oncology Research, Vol.34, No.3, 2026, DOI:10.32604/or.2026.068508 - 24 February 2026

    Abstract Background: Gastric cancer (GC) remains highly lethal, with metabolic reprogramming as a key hallmark. This study explores Centromere Protein F (CENPF)’s role in GC pathogenesis, specifically its regulation of glutamine metabolism. Methods: The Cancer Genome Atlas–Stomach Adenocarcinoma (TCGA-STAD), GSE19826, and GSE27342 datasets were analyzed by bioinformatics to identify key candidate genes in GC. The function of CENPF was assessed by flow cytometry, colony formation assays, and Cell Counting Kit-8 (CCK-8). RNA sequencing, metabolic profiling, chromatin immunoprecipitation (ChIP), western blot (WB), and luciferase reporter assay were employed to investigate the fundamental mechanisms. Results: CENPF was upregulated in GC… More >

  • Open Access

    ARTICLE

    YOLO-SPDNet: Multi-Scale Sequence and Attention-Based Tomato Leaf Disease Detection Model

    Meng Wang1, Jinghan Cai1, Wenzheng Liu1, Xue Yang1, Jingjing Zhang1, Qiangmin Zhou1, Fanzhen Wang1, Hang Zhang1,*, Tonghai Liu2,*

    Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2025.075541 - 30 January 2026

    Abstract Tomato is a major economic crop worldwide, and diseases on tomato leaves can significantly reduce both yield and quality. Traditional manual inspection is inefficient and highly subjective, making it difficult to meet the requirements of early disease identification in complex natural environments. To address this issue, this study proposes an improved YOLO11-based model, YOLO-SPDNet (Scale Sequence Fusion, Position-Channel Attention, and Dual Enhancement Network). The model integrates the SEAM (Self-Ensembling Attention Mechanism) semantic enhancement module, the MLCA (Mixed Local Channel Attention) lightweight attention mechanism, and the SPA (Scale-Position-Detail Awareness) module composed of SSFF (Scale Sequence Feature… More >

  • Open Access

    ARTICLE

    Wavelet Transform-Based Bayesian Inference Learning with Conditional Variational Autoencoder for Mitigating Injection Attack in 6G Edge Network

    Binu Sudhakaran Pillai1, Raghavendra Kulkarni2, Venkata Satya Suresh kumar Kondeti2, Surendran Rajendran3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 1141-1166, 2025, DOI:10.32604/cmes.2025.070348 - 30 October 2025

    Abstract Future 6G communications will open up opportunities for innovative applications, including Cyber-Physical Systems, edge computing, supporting Industry 5.0, and digital agriculture. While automation is creating efficiencies, it can also create new cyber threats, such as vulnerabilities in trust and malicious node injection. Denial-of-Service (DoS) attacks can stop many forms of operations by overwhelming networks and systems with data noise. Current anomaly detection methods require extensive software changes and only detect static threats. Data collection is important for being accurate, but it is often a slow, tedious, and sometimes inefficient process. This paper proposes a new… More >

  • Open Access

    ARTICLE

    A Unified U-Net-Vision Mamba Model with Hierarchical Bottleneck Attention for Detection of Tomato Leaf Diseases

    Geoffry Mutiso*, John Ndia

    Journal on Artificial Intelligence, Vol.7, pp. 275-288, 2025, DOI:10.32604/jai.2025.069768 - 05 September 2025

    Abstract Tomato leaf diseases significantly reduce crop yield; therefore, early and accurate disease detection is required. Traditional detection methods are laborious and error-prone, particularly in large-scale farms, whereas existing hybrid deep learning models often face computational inefficiencies and poor generalization over diverse environmental and disease conditions. This study presents a unified U-Net-Vision Mamba Model with Hierarchical Bottleneck Attention Mechanism (U-net-Vim-HBAM), which integrates U-Net’s high-resolution segmentation, Vision Mamba’s efficient contextual processing, and a Hierarchical Bottleneck Attention Mechanism to address the challenges of disease detection accuracy, computational complexity, and efficiency in existing models. The model was trained on More >

  • Open Access

    ARTICLE

    Synergistic Effect of Zinc Oxide, Magnesium Oxide and Graphene Nanomaterials on Fusarium oxysporum-Inoculated Tomato Plants

    Alejandra Sánchez-Reyna1, Yolanda González-García2, Ángel Gabriel Alpuche-Solís3, Gregorio Cadenas-Pliego4, Adalberto Benavides-Mendoza5,6, Antonio Juárez-Maldonado6,7,*

    Phyton-International Journal of Experimental Botany, Vol.94, No.7, pp. 2097-2116, 2025, DOI:10.32604/phyton.2025.067092 - 31 July 2025

    Abstract Tomato is an economically important crop that is susceptible to biotic and abiotic stresses, situations that negatively affect the crop cycle. Biotic stress is caused by phytopathogens such as Fusarium oxysporum f. sp. lycopersici (FOL), responsible for vascular wilt, a disease that causes economic losses of up to 100% in crops of interest. Nanomaterials represent an area of opportunity for pathogen control through stimulations that modify the plant development program, achieving greater adaptation and tolerance to stress. The aim of this study was to evaluate the antimicrobial capacity of the nanoparticles and the concentrations used in tomato… More >

  • Open Access

    REVIEW

    Strengthening Tomato Resilience: Harnessing Microbial Consortia to Overcome Biotic and Abiotic Stress

    Oumaima Benaissa1,2,3, Mohammed Taoussi1,4, Ikram Legrifi1,2, Zineb Belabess3, Abderrahim Lazraq2, Rachid Lahlali1,*

    Phyton-International Journal of Experimental Botany, Vol.94, No.5, pp. 1453-1495, 2025, DOI:10.32604/phyton.2025.064598 - 29 May 2025

    Abstract Tomato cultivation faces formidable challenges from both biotic and abiotic stressors, necessitating innovative and sustainable strategies to ensure crop resilience and yield stability. This comprehensive review delves into the evolving landscape of employing microbial consortia as a dynamic tool for the integrated management of biotic and abiotic stresses in tomato plants. The microbial consortium, comprising an intricate network of bacteria, fungi, and other beneficial microorganisms, plays a pivotal role in promoting plant health and bolstering defense mechanisms. Against biotic stressors, the consortium exhibits multifaceted actions, including the suppression of pathogenic organisms through antagonistic interactions and… More >

  • Open Access

    ARTICLE

    Plant Disease Detection and Classification Using Hybrid Model Based on Convolutional Auto Encoder and Convolutional Neural Network

    Tajinder Kumar1, Sarbjit Kaur2, Purushottam Sharma3,*, Ankita Chhikara4, Xiaochun Cheng5,*, Sachin Lalar6, Vikram Verma7

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5219-5234, 2025, DOI:10.32604/cmc.2025.062010 - 19 May 2025

    Abstract During its growth stage, the plant is exposed to various diseases. Detection and early detection of crop diseases is a major challenge in the horticulture industry. Crop infections can harm total crop yield and reduce farmers’ income if not identified early. Today’s approved method involves a professional plant pathologist to diagnose the disease by visual inspection of the afflicted plant leaves. This is an excellent use case for Community Assessment and Treatment Services (CATS) due to the lengthy manual disease diagnosis process and the accuracy of identification is directly proportional to the skills of pathologists.… More >

  • Open Access

    ARTICLE

    Evaluating Dying Efficiency and Energy Performance of a Hybrid Solar Dryer with Natural, Forced, and Hybrid Convection Modes for Tomatoes

    Sadaf Gul Unar1, Shoaib Ahmed Khatri1,*, Nayyar Hussain Mirjat1, Muhammad Faraz Arain1, Syed Rafay Ahmed Zaidi1, Laveet Kumar2

    Frontiers in Heat and Mass Transfer, Vol.23, No.2, pp. 479-505, 2025, DOI:10.32604/fhmt.2025.063937 - 25 April 2025

    Abstract This research focuses on developing innovative hybrid solar dryers that combine solar Photovoltaic (PV) and solar thermal systems for sustainable food preservation in Pakistan, addressing the country’s pressing issues of high post-harvest losses and unreliable energy sources. The proposed active hybrid solar dryer features a drying cabinet, two Direct Current (DC) fans for forced convection, and a resistive heating element powered by a 180 W solar PV panel. An energy-storing battery ensures continuous supply to the auxiliaries during periods of low solar irradiance, poor weather conditions, or nighttime. Tomatoes, a delicate and in-demand crop, were… More >

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