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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

    Group Decision-Making Based on GIS and MultiCriteria Analysis for Assessing Land Suitability for Agriculture

    Abdelkader Mendas*, Abdellah Mebrek, Zohra Mekranfar

    Revue Internationale de Géomatique, Vol.33, pp. 383-398, 2024, DOI:10.32604/rig.2024.055321 - 25 September 2024

    Abstract The main purpose of this work is to propose a methodology that considers the multicriteria and multi-actor aspects for assessing land suitability for agriculture. This involves offering a group spatial decision-making approach. The members of a multidisciplinary team can decide on the relative importance of the criteria and the ranking of alternatives. Each member provides his judgment and contributes in a distinct and identifiable manner to find a compromise solution. Twelve criteria (easily available water reserve, cation exchange capacity, electric conductivity, potential of hydrogen (pH), drainage, permeability, active limestone, soil texture, soil useful depth, slopes,… More >

  • Open Access

    ARTICLE

    Performance of Deep Learning Techniques in Leaf Disease Detection

    Robertas Damasevicius1,*, Faheem Mahmood2, Yaseen Zaman3, Sobia Dastgeer2, Sajid Khan2

    Computer Systems Science and Engineering, Vol.48, No.5, pp. 1349-1366, 2024, DOI:10.32604/csse.2024.050359 - 13 September 2024

    Abstract Plant diseases must be identified as soon as possible since they have an impact on the growth of the corresponding species. Consequently, the identification of leaf diseases is essential in this field of agriculture. Diseases brought on by bacteria, viruses, and fungi are a significant factor in reduced crop yields. Numerous machine learning models have been applied in the identification of plant diseases, however, with the recent developments in deep learning, this field of study seems to hold huge potential for improved accuracy. This study presents an effective method that uses image processing and deep… More >

  • Open Access

    ARTICLE

    Cartographie Automatique et Comptage des Arbres Oliviers A Partir de L’Imagerie de Drone par Un Reseau de Neurones Covolutionnel

    Oumaima Ameslek1,*, Hafida Zahir2, Soukaina Mitro2, El Mostafa Bachaoui1

    Revue Internationale de Géomatique, Vol.33, pp. 321-340, 2024, DOI:10.32604/rig.2024.054838 - 03 September 2024

    Abstract L’agriculture de précision (AP) est une stratégie de gestion agricole fondée sur l’observation, la mesure et la réponse à la variabilité des cultures inter/intra-champ. Il comprend des avancées en matière de collecte, d’analyse et de gestion des données, ainsi que des développements technologiques en matière de stockage et de récupération de données, de positionnement précis, de surveillance des rendements et de télédétection. Cette dernière offre une résolution spatiale, spectrale et temporelle sans précédent, mais peut également fournir des informations détaillées sur la hauteur de la végétation et diverses observations. Aujourd’hui, le succès des nouvelles technologies… More >

  • Open Access

    ARTICLE

    Genome-Wide Analysis for Yield-Related Agronomic and Biochemical Traits of Chinese and Bangladeshi Grass Pea Genotypes Using SSR Markers

    Md. Mosiur Rahman1,2, Md. Ruhul Quddus3, Quanle Xu4, Muhammad Malek Hossain2, Rong Liu1, Mengwei Li1, Xin Yan1, Guan Li1, Yishan Ji1, Chenyu Wang1, Ashutosh Sarker5, Tao Yang1, Xuxiao Zong1, Md. Monoar Hossain6, Saleh Alfarraj7, Mohammad Javed Ansari8, Sagar Maitra9,*, Akbar Hossain10,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.8, pp. 1781-1804, 2024, DOI:10.32604/phyton.2024.048992 - 30 August 2024

    Abstract Grass pea (Lathyrus sativus L.) is an imperative food crop cultured in dryland agricultural ecology. It is a vital source of dietary protein to millions of populaces living in low-income countries in South-East Asia and Africa. This study highlights the improvement of genomic properties and their application in marker-trait relationships for 17 yield-related characters in 400 grass pea genotypes from China and Bangladesh. These characters were assessed via 56 polymorphic markers using general linear model (GLM) (P+G+Q) and mixed linear model (MLM) (P+G+Q+K) in the tassel software based on the linkage disequilibrium and population structure analysis.… More >

  • Open Access

    REVIEW

    Artificial Intelligence for Maximizing Agricultural Input Use Efficiency: Exploring Nutrient, Water and Weed Management Strategies

    Sumit Sow1,#, Shivani Ranjan1,#,*, Mahmoud F. Seleiman2,3, Hiba M. Alkharabsheh4,*, Mukesh Kumar1, Navnit Kumar1, Smruti Ranjan Padhan5, Dhirendra Kumar Roy1, Dibyajyoti Nath6, Harun Gitari7, Daniel O. Wasonga8

    Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1569-1598, 2024, DOI:10.32604/phyton.2024.052241 - 30 July 2024

    Abstract Agriculture plays a crucial role in the economy, and there is an increasing global emphasis on automating agricultural processes. With the tremendous increase in population, the demand for food and employment has also increased significantly. Agricultural methods traditionally used to meet these requirements are no longer adequate, requiring solutions to issues such as excessive herbicide use and the use of chemical fertilizers. Integration of technologies such as the Internet of Things, wireless communication, machine learning, artificial intelligence (AI), and deep learning shows promise in addressing these challenges. However, there is a lack of comprehensive documentation… More >

  • Open Access

    ARTICLE

    Security Analysis in Smart Agriculture: Insights from a Cyber-Physical System Application

    Ahmed Redha Mahlous*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4781-4803, 2024, DOI:10.32604/cmc.2024.050821 - 20 June 2024

    Abstract Smart agriculture modifies traditional farming practices, and offers innovative approaches to boost production and sustainability by leveraging contemporary technologies. In today’s world where technology is everything, these technologies are utilized to streamline regular tasks and procedures in agriculture, one of the largest and most significant industries in every nation. This research paper stands out from existing literature on smart agriculture security by providing a comprehensive analysis and examination of security issues within smart agriculture systems. Divided into three main sections—security analysis, system architecture and design and risk assessment of Cyber-Physical Systems (CPS) applications—the study delves… More >

  • Open Access

    ARTICLE

    Sorghum Productivity and Its Farming Feasibility in Dryland Agriculture: Genotypic and Planting Distance Insights

    Kristamtini1, Sugeng Widodo2, Heni Purwaningsih3, Arlyna Budi Pustika1, Setyorini Widyayanti1, Arif Muazam1, Arini Putri Hanifa1,*, Joko Triastono2, Dewi Sahara2, Heni Sulistyawati Purwaning Rahayu2, Pandu Laksono2, Diah Arina Fahmi2, Sutardi1, Joko Pramono4, Rachmiwati Yusuf1

    Phyton-International Journal of Experimental Botany, Vol.93, No.5, pp. 1007-1021, 2024, DOI:10.32604/phyton.2024.048770 - 28 May 2024

    Abstract Sorghum (Sorghum bicolor L. Moench) is an essential food crop for more than 750 million people in tropical and sub-tropical dry climates of Africa, India, and Latin America. The domestic sorghum market in Indonesia is still limited to the eastern region (East Nusa Tenggara, West Nusa Tenggara, Java, and South Sulawesi). Therefore, it is crucial to carry out sorghum research on drylands. This research aimed to investigate the effect of sorghum genotype and planting distance and their interaction toward growth and sorghum’s productivity in the Gunungkidul dryland, Yogyakarta, Indonesia. In addition, the farm business analysis, including… More >

  • Open Access

    REVIEW

    Plant Nitrogen Metabolism: Balancing Resilience to Nutritional Stress and Abiotic Challenges

    Muhammad Farhan1,#, Manda Sathish2, Rafia Kiran1, Aroosa Mushtaq3, Alaa Baazeem4, Ammarah Hasnain5, Fahad Hakim1, Syed Atif Hasan Naqvi1,#,*, Mustansar Mubeen6, Yasir Iftikhar6,*, Aqleem Abbas7, Muhammad Zeeshan Hassan1, Mahmoud Moustafa8

    Phyton-International Journal of Experimental Botany, Vol.93, No.3, pp. 581-609, 2024, DOI:10.32604/phyton.2024.046857 - 28 March 2024

    Abstract

    Plant growth and resilience to abiotic stresses, such as soil salinity and drought, depend intricately on nitrogen metabolism. This review explores nitrogen’s regulatory role in plant responses to these challenges, unveiling a dynamic interplay between nitrogen availability and abiotic stress. In the context of soil salinity, a nuanced relationship emerges, featuring both antagonistic and synergistic interactions between salinity and nitrogen levels. Salinity-induced chlorophyll depletion in plants can be alleviated by optimal nitrogen supplementation; however, excessive nitrogen can exacerbate salinity stress. We delve into the complexities of this interaction and its agricultural implications. Nitrogen, a vital element

    More >

  • Open Access

    ARTICLE

    A Lightweight Deep Learning-Based Model for Tomato Leaf Disease Classification

    Naeem Ullah1, Javed Ali Khan2,*, Sultan Almakdi3, Mohammed S. Alshehri3, Mimonah Al Qathrady4, Eman Abdullah Aldakheel5,*, Doaa Sami Khafaga5

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3969-3992, 2023, DOI:10.32604/cmc.2023.041819 - 26 December 2023

    Abstract Tomato leaf diseases significantly impact crop production, necessitating early detection for sustainable farming. Deep Learning (DL) has recently shown excellent results in identifying and classifying tomato leaf diseases. However, current DL methods often require substantial computational resources, hindering their application on resource-constrained devices. We propose the Deep Tomato Detection Network (DTomatoDNet), a lightweight DL-based framework comprising 19 learnable layers for efficient tomato leaf disease classification to overcome this. The Convn kernels used in the proposed (DTomatoDNet) framework is 1 × 1, which reduces the number of parameters and helps in more detailed and descriptive feature extraction for… More >

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