Oumaima Benaissa^1,2,3, Mohammed Taoussi^1,4, Ikram Legrifi^1,2, Zineb Belabess³, Abderrahim Lazraq², Rachid Lahlali^1,*

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 >

Sajid Ali^*, Yong-Sun Moon^*

Phyton-International Journal of Experimental Botany, Vol.94, No.5, pp. 1419-1451, 2025, DOI:10.32604/phyton.2025.064284 - 29 May 2025

Abstract This review focused on the role of plant growth-promoting rhizobacteria (PGPR) in enhancing plant growth and protecting against pathogens, highlighting their mechanisms of action, ecological benefits, and challenges. PGPR mediate plant growth through several mechanisms, including nutrient acquisition, production of antimicrobial compounds and induction of systemic resistance. These mechanisms are critical in improving crop yields, especially under stressful conditions. This review examines the molecular mechanisms of PGPR-mediated plant pathogen control, cellular mechanisms of PGPR in plant pathogen control, ecological and environmental benefits of PGPR application. Despite their potential, PGPR application is limited by environmental variability,… More >

Vicky Anand¹, Priyadarshani Rajput¹, Tatiana Minkina¹, Saglara Mandzhieva¹, Santosh Kumar², Avnish Chauhan³, Vishnu D. Rajput^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.5, pp. 1339-1365, 2025, DOI:10.32604/phyton.2025.063927 - 29 May 2025

Abstract The digital revolution in agriculture has introduced data-driven decision-making, where artificial intelligence, especially machine learning (ML), helps analyze large and varied data sources to improve soil quality and crop growth indices. Thus, a thorough evaluation of scientific publications from 2007 to 2024 was conducted via the Scopus and Web of Science databases with the PRISMA guidelines to determine the realistic role of ML in soil health and crop improvement under the SDGs. In addition, the present review focused to identify and analyze the trends, challenges, and opportunities associated with the successful implementation of ML in… More >

Muhammad Qasim^1,2, Syed M. Adnan Shah¹, Qamas Gul Khan Safi¹, Danish Mahmood², Adeel Iqbal^3,*, Ali Nauman³, Sung Won Kim^3,*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4429-4445, 2025, DOI:10.32604/cmc.2025.065060 - 19 May 2025

Abstract Grains are the most important food consumed globally, yet their yield can be severely impacted by pest infestations. Addressing this issue, scientists and researchers strive to enhance the yield-to-seed ratio through effective pest detection methods. Traditional approaches often rely on preprocessed datasets, but there is a growing need for solutions that utilize real-time images of pests in their natural habitat. Our study introduces a novel two-step approach to tackle this challenge. Initially, raw images with complex backgrounds are captured. In the subsequent step, feature extraction is performed using both hand-crafted algorithms (Haralick, LBP, and Color… More >

Shahin Imran^1,2,#,*, Mousumi Jahan Sumi^3,#, Israt Jahan Harine⁴, Newton Chandra Paul¹, Md. Asif Mahamud⁵, Rakibul Hasan Md. Rabbi⁵, Marian Brestic⁶, Mohammad Saidur Rhaman^7,*

Phyton-International Journal of Experimental Botany, Vol.94, No.4, pp. 1073-1109, 2025, DOI:10.32604/phyton.2025.064046 - 30 April 2025

Abstract Heavy metal (HM) accumulation in soil poses a major hazard to both ecological health and plant growth progressions. Cadmium (Cd), lead (Pb), copper (Cu), chromium (Cr), arsenic (As), zinc (Zn), and nickel (Ni) are examples of HMs that negatively impact the growth and development of plants, resulting in lower agricultural output and food safety concerns. Biochar (BC), a substance rich in carbon that is formed by pyrolyzing natural biomass, has demonstrated remarkable promise in reducing HM stress in polluted soils. Research has shown that BC effectively lowers plant uptake of metals, and enhances soil qualities,… More >

Arpita Rani Roy¹, Israt Jahan², Sharah Jabeen Mou², Md. Farhan Hasin³, Prodipto Bishnu Angon^1,*, Rebeka Sultana², Badhon Mazumder⁴, Md. Arif Sakil^5,*

Phyton-International Journal of Experimental Botany, Vol.94, No.4, pp. 1177-1210, 2025, DOI:10.32604/phyton.2025.063675 - 30 April 2025

Abstract Global warming is making plants more susceptible to heat stress. Hence, adjustments to crop production systems are required for global food security. Heat stress (HS) poses a threat to the quality of ecosystems and global food security due to its adverse effects on plant development. The degree to which HS affects physiological disruptions, physical harm, and biochemical changes at various growth stages directly correlates with its effects on physiological functions, plant growth, and crop production. One promising approach is soil modification using biochar, which enhances soil health and promotes the development of microbial communities, ultimately… More >

Wafaa H. Alwan^1,*, Sabah M. Alturfi²

Computer Systems Science and Engineering, Vol.49, pp. 419-434, 2025, DOI:10.32604/csse.2025.064195 - 30 April 2025

Abstract Plant diseases pose a significant challenge to global agricultural productivity, necessitating efficient and precise diagnostic systems for early intervention and mitigation. In this study, we propose a novel hybrid framework that integrates EfficientNet-B8, Vision Transformer (ViT), and Knowledge Graph Fusion (KGF) to enhance plant disease classification across 38 distinct disease categories. The proposed framework leverages deep learning and semantic enrichment to improve classification accuracy and interpretability. EfficientNet-B8, a convolutional neural network (CNN) with optimized depth and width scaling, captures fine-grained spatial details in high-resolution plant images, aiding in the detection of subtle disease symptoms. In… More >

Maryam¹, Mohamed M. El-Mogy², Muhammad Faheem Jan³, Iram Naz¹, Ishtiaq Ahmad^4,*, Riaz Ahmad⁵, Muhammad Tanveer Altaf⁶

Phyton-International Journal of Experimental Botany, Vol.94, No.3, pp. 623-640, 2025, DOI:10.32604/phyton.2025.063763 - 31 March 2025

Abstract Various environmental stressors, such as salinity, heat, drought, and metals, present significant obstacles to crop productivity. This study delves into the adverse effects of metals, specifically focusing on cadmium (Cd), nickel (Ni), mercury (Hg), chromium (Cr), arsenic (As), lead (Pb), and copper (Cu) on plants. It explores the sources of these metals, examining both natural occurrences and human-induced activities, and investigates the mechanisms through which plants absorb them. Metal pollution, in particular, negatively affects plant and microbiome well-being, producing reactive oxygen species (ROS) that harm essential macromolecules. Traditional stress-resistant plant varieties necessitate substantial development, leading… More >

Faten S. Alamri¹, Tariq Sadad^2,*, Ahmed S. Almasoud³, Raja Atif Aurangzeb⁴, Amjad Khan³

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1023-1039, 2025, DOI:10.32604/cmc.2025.061890 - 26 March 2025

Abstract Mango farming significantly contributes to the economy, particularly in developing countries. However, mango trees are susceptible to various diseases caused by fungi, viruses, and bacteria, and diagnosing these diseases at an early stage is crucial to prevent their spread, which can lead to substantial losses. The development of deep learning models for detecting crop diseases is an active area of research in smart agriculture. This study focuses on mango plant diseases and employs the ConvNeXt and Vision Transformer (ViT) architectures. Two datasets were used. The first, MangoLeafBD, contains data for mango leaf diseases such as… More >

Muhammad Nazim^1,2,*, Abdul Ghafoor^3,*, Abida Hussain⁴, Mehwish Tabassum⁵, Aamir Nawaz⁶, Muhammad Ahmad⁷, Murad Muhammad^1,2, Muqarrab Ali⁴

Phyton-International Journal of Experimental Botany, Vol.94, No.1, pp. 65-99, 2025, DOI:10.32604/phyton.2025.058970 - 24 January 2025

Abstract In recent years, the world has faced rising global temperatures, accumulative pollution, and energy crises, stimulating scientists worldwide to strive for eco-friendly and cost-effective solutions. Biochar has materialized as a favorable tool for environmental remediation, indicating efficacy as an efficient sorbent substance for both inorganic and organic pollutants in environmental field. These unique properties exclude improved surface functionality, porous morphology, large specific surface area (SSA), cation exchange capacity (CEC), robust adsorption capabilities, environmental stability, and embedded micronutrients. Biochar exhibited potential characteristics for environmental oversight, greenhouse gas (GHG) emission reduction, and soil fertility improvement. This review… More >