IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i17p7651-d1470574.html
   My bibliography  Save this article

Integrative Approaches to Abiotic Stress Management in Crops: Combining Bioinformatics Educational Tools and Artificial Intelligence Applications

Author

Listed:
  • Xin Zhang

    (School of Marxism, Zhejiang University, Hangzhou 310058, China)

  • Zakir Ibrahim

    (Department of Agronomy, Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
    Faculty of Agriculture, Lasbela University of Agriculture, Water and Marine Sciences, Uthal 90150, Pakistan)

  • Muhammad Bilawal Khaskheli

    (School of Law, Dalian Maritime University, Dalian 116026, China)

  • Hamad Raza

    (Lyallpur Business School, Government College University, Faisalabad 38000, Pakistan)

  • Fanrui Zhou

    (Key Laboratory of State Forestry and Grassland Administration on Highly Efficient Utilization of Forestry Biomass Resources in Southwest China, College of Material and Chemical Engineering, Southwest Forestry University, Kunming 650224, China
    Department of Food Science and Nutrition, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China)

  • Imran Haider Shamsi

    (Department of Agronomy, Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China)

Abstract

Abiotic stresses, including drought, salinity, extreme temperatures and nutrient deficiencies, pose significant challenges to crop production and global food security. To combat these challenges, the integration of bioinformatics educational tools and AI applications provide a synergistic approach to identify and analyze stress-responsive genes, regulatory networks and molecular markers associated with stress tolerance. Bioinformatics educational tools offer a robust framework for data collection, storage and initial analysis, while AI applications enhance pattern recognition, predictive modeling and real-time data processing capabilities. This review uniquely integrates bioinformatics educational tools and AI applications, highlighting their combined role in managing abiotic stress in plants and crops. The novelty is demonstrated by the integration of multiomics data with AI algorithms, providing deeper insights into stress response pathways, biomarker discovery and pattern recognition. Key AI applications include predictive modeling of stress resistance genes, gene regulatory network inference, omics data integration and real-time plant monitoring through the fusion of remote sensing and AI-assisted phenomics. Challenges such as handling big omics data, model interpretability, overfitting and experimental validation remain there, but future prospects involve developing user-friendly bioinformatics educational platforms, establishing common data standards, interdisciplinary collaboration and harnessing AI for real-time stress mitigation strategies in plants and crops. Educational initiatives, interdisciplinary collaborations and trainings are essential to equip the next generation of researchers with the required skills to utilize these advanced tools effectively. The convergence of bioinformatics and AI holds vast prospects for accelerating the development of stress-resilient plants and crops, optimizing agricultural practices and ensuring global food security under increasing environmental pressures. Moreover, this integrated approach is crucial for advancing sustainable agriculture and ensuring global food security amidst growing environmental challenges.

Suggested Citation

  • Xin Zhang & Zakir Ibrahim & Muhammad Bilawal Khaskheli & Hamad Raza & Fanrui Zhou & Imran Haider Shamsi, 2024. "Integrative Approaches to Abiotic Stress Management in Crops: Combining Bioinformatics Educational Tools and Artificial Intelligence Applications," Sustainability, MDPI, vol. 16(17), pages 1-26, September.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:17:p:7651-:d:1470574
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/17/7651/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/17/7651/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Joseph L. Watson & David Juergens & Nathaniel R. Bennett & Brian L. Trippe & Jason Yim & Helen E. Eisenach & Woody Ahern & Andrew J. Borst & Robert J. Ragotte & Lukas F. Milles & Basile I. M. Wicky & , 2023. "De novo design of protein structure and function with RFdiffusion," Nature, Nature, vol. 620(7976), pages 1089-1100, August.
    2. Julian M Alston, 2018. "Reflections on Agricultural R&D, Productivity, and the Data Constraint: Unfinished Business, Unsettled Issues," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(2), pages 392-413.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hendricks, Nathan P. & Smith, Aaron D. & Villoria, Nelson B., 2018. "Global Agricultural Supply Response to Persistent Price Shocks," 2018 Annual Meeting, August 5-7, Washington, D.C. 274338, Agricultural and Applied Economics Association.
    2. Julian M. Alston & Philip G. Pardey, 2020. "Innovation, Growth, and Structural Change in American Agriculture," NBER Chapters, in: The Role of Innovation and Entrepreneurship in Economic Growth, pages 123-165, National Bureau of Economic Research, Inc.
    3. Eric Njuki & Boris E. Bravo-Ureta, 2019. "Examining irrigation productivity in U.S. agriculture using a single-factor approach," Journal of Productivity Analysis, Springer, vol. 51(2), pages 125-136, June.
    4. Michał Gazdecki & Grzegorz Leszczyński & Marek Zieliński, 2021. "Food Sector as an Interactive Business World: A Framework for Research on Innovations," Energies, MDPI, vol. 14(11), pages 1-19, June.
    5. Ying Huang & Chenyang Xue & Ruiqian Bu & Cang Wu & Jiachen Li & Jinqiu Zhang & Jinyu Chen & Zhaoying Shi & Yonglong Chen & Yong Wang & Zhongmin Liu, 2024. "Inhibition and transport mechanisms of the ABC transporter hMRP5," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    6. Konstantinos Metaxoglou & Aaron Smith, 2020. "Productivity Spillovers From Pollution Reduction: Reducing Coal Use Increases Crop Yields," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 259-280, January.
    7. Porteous, Obie, 2020. "Trade and agricultural technology adoption: Evidence from Africa," Journal of Development Economics, Elsevier, vol. 144(C).
    8. Xiaorui Wang & Xiaodan Yin & Dejun Jiang & Huifeng Zhao & Zhenxing Wu & Odin Zhang & Jike Wang & Yuquan Li & Yafeng Deng & Huanxiang Liu & Pei Luo & Yuqiang Han & Tingjun Hou & Xiaojun Yao & Chang-Yu , 2024. "Multi-modal deep learning enables efficient and accurate annotation of enzymatic active sites," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    9. Simeon D. Castle & Michiel Stock & Thomas E. Gorochowski, 2024. "Engineering is evolution: a perspective on design processes to engineer biology," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    10. Ryota Nakatani, 2024. "Food companies' productivity dynamics: Exploring the role of intangible assets," Agribusiness, John Wiley & Sons, Ltd., vol. 40(1), pages 185-226, January.
    11. Brenes, Esteban R. & Ciravegna, Luciano & Acuña, Joseph, 2020. "Differentiation strategies in agribusiness – A configurational approach," Journal of Business Research, Elsevier, vol. 119(C), pages 522-539.
    12. Mason-D'Croz, Daniel & Sulser, Timothy B. & Wiebe, Keith & Rosegrant, Mark W. & Lowder, Sarah K. & Nin-Pratt, Alejandro & Willenbockel, Dirk & Robinson, Sherman & Zhu, Tingju & Cenacchi, Nicola & Duns, 2019. "Agricultural investments and hunger in Africa modeling potential contributions to SDG2 – Zero Hunger," World Development, Elsevier, vol. 116(C), pages 38-53.
    13. Lana Awada & Peter W. B. Phillips, 2021. "The distribution of returns from land efficiency improvement in multistage production systems," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 69(1), pages 73-92, March.
    14. Aika Iwama & Ryoji Kise & Hiroaki Akasaka & Fumiya K. Sano & Hidetaka S. Oshima & Asuka Inoue & Wataru Shihoya & Osamu Nureki, 2024. "Structure and dynamics of the pyroglutamylated RF-amide peptide QRFP receptor GPR103," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    15. Nathan P. Hendricks & Aaron Smith & Nelson B. Villoria & Matthieu Stigler, 2023. "The effects of agricultural policy on supply and productivity: Evidence from differential changes in distortions," Agricultural Economics, International Association of Agricultural Economists, vol. 54(1), pages 44-61, January.
    16. Wei Lu & Jixian Zhang & Weifeng Huang & Ziqiao Zhang & Xiangyu Jia & Zhenyu Wang & Leilei Shi & Chengtao Li & Peter G. Wolynes & Shuangjia Zheng, 2024. "DynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    17. Diewert, Erwin & Fox, Kevin J., 2019. "Productivity Indexes and National Statistics: Theory, Methods and Challenges," Microeconomics.ca working papers erwin_diewert-2019-8, Vancouver School of Economics, revised 25 Apr 2019.
    18. Gheorghe Hurduzeu & Radu Lucian Pânzaru & Dragoș Mihai Medelete & Andi Ciobanu & Constanța Enea, 2022. "The Development of Sustainable Agriculture in EU Countries and the Potential Achievement of Sustainable Development Goals Specific Targets (SDG 2)," Sustainability, MDPI, vol. 14(23), pages 1-24, November.
    19. Chase R. Freschlin & Sarah A. Fahlberg & Pete Heinzelman & Philip A. Romero, 2024. "Neural network extrapolation to distant regions of the protein fitness landscape," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    20. Muhammad Usman & Gulnaz Hameed & Abdul Saboor & Lal K. Almas & Muhammad Hanif, 2021. "R&D Innovation Adoption, Climatic Sensitivity, and Absorptive Ability Contribution for Agriculture TFP Growth in Pakistan," Agriculture, MDPI, vol. 11(12), pages 1-18, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:17:p:7651-:d:1470574. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.