Foliar Nitrogen Estimation with Artificial Intelligence and Technological Tools: State of the Art and Future Challenges

被引:0
|
作者
Gallegos, Angeles [1 ]
Gavito, Mayra E. [1 ]
Ferreira-Medina, Heberto [1 ]
机构
[1] Univ Nacl Autonoma Mexico, Inst Invest Ecosistemas & Sustentabil, Antigua Carretera Patzcuaro 8701, Morelia 58190, Michoacan, Mexico
关键词
Digital images; spectral data; estimation models; technological tools; nitrogen; DIGITAL CAMERA; LEAF NITROGEN; PLANT; NUTRITION; FERTILIZATION; SEGMENTATION; IMAGES; YIELD; CORN; MAP;
D O I
10.14569/IJACSA.2024.0150640
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Nitrogen plays a fundamental role in plant growth, but its high application has significant negative impacts for the farmers and the environment. This nutrient is often provided in excess to prevent plant growth limitations when it ought to be administered in the exact quantities because many farmers do not have access to technology or affordable soil and plant chemical analyses. Precision agriculture through monitoring of crop nutrition may be possible with quantitative, non-destructive methods and technological tools that allow farmers to conduct a rapid and representative verification of their fertilizer applications. In this sense, we carried out a systematic review and bibliometric analysis of recent scientific research to answer the questions: 1) Can artificial intelligence-based, nondestructive analysis of plant nutrition provide relevant information for decision-making in agricultural systems?, 2) Have recent studies reached the stage of developing technological tools to be applied in agricultural systems and field conditions?, and 3) What is the way forward to achieve popularization of the application and development of technological tools in agricultural systems? We found that non-destructive analyses of foliar nutrition need to provide more supportive information for decision-making given the challenge of interpreting and replicating results in agricultural systems operating under uncontrolled conditions, such as field conditions. To address this issue, we propose developing accessible technological tools, such as mobile applications, tailored to farmers' needs. However, most studies had not yet considered developing a technological tool as part of their objectives. Therefore, it is critical to develop accessible and affordable technologies and monitoring systems that approach precision agriculture since the conservation and sustainable management of natural resources demands translating scientific knowledge into supporting tools that reach farmers and decision-makers worldwide. The way forward is innovation through technological developments that enhance current agricultural systems.
引用
收藏
页码:375 / 386
页数:12
相关论文
共 50 条
  • [1] Artificial intelligence for climate prediction of extremes: State of the art, challenges, and future perspectives
    Materia, Stefano
    Garcia, Lluis Palma
    van Straaten, Chiem
    Sungmin, O.
    Mamalakis, Antonios
    Cavicchia, Leone
    Coumou, Dim
    de Luca, Paolo
    Kretschmer, Marlene
    Donat, Markus
    WILEY INTERDISCIPLINARY REVIEWS-CLIMATE CHANGE, 2024, 15 (06)
  • [2] Application of Artificial Intelligence in Predicting Earthquakes: State-of-the-Art and Future Challenges
    Al Banna, Md. Hasan
    Abu Taher, Kazi
    Kaiser, M. Shamim
    Mahmud, Mufti
    Rahman, Md. Sazzadur
    Hosen, A. S. M. Sanwar
    Cho, Gi Hwan
    IEEE ACCESS, 2020, 8 : 192880 - 192923
  • [3] Artificial Intelligence Approaches for Energetic Materials by Design: State of the Art, Challenges, and Future Directions
    Choi, Joseph B.
    Nguyen, Phong C. H.
    Sen, Oishik
    Udaykumar, H. S.
    Baek, Stephen
    PROPELLANTS EXPLOSIVES PYROTECHNICS, 2023, 48 (04)
  • [4] Robotics in neurosurgery: state of the art and future technological challenges
    Zamorano, L
    Li, Q
    Jain, S
    Kaur, G
    INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY, 2004, 1 (01): : 7 - 22
  • [5] Study on artificial intelligence: The state of the art and future prospects
    Zhang, Caiming
    Lu, Yang
    JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION, 2021, 23
  • [6] Artificial Intelligence in radiotherapy: state of the art and future directions
    Francolini, Giulio
    Desideri, Isacco
    Stocchi, Giulia
    Salvestrini, Viola
    Ciccone, Lucia Pia
    Garlatti, Pietro
    Loi, Mauro
    Livi, Lorenzo
    MEDICAL ONCOLOGY, 2020, 37 (06)
  • [7] Artificial Intelligence in radiotherapy: state of the art and future directions
    Giulio Francolini
    Isacco Desideri
    Giulia Stocchi
    Viola Salvestrini
    Lucia Pia Ciccone
    Pietro Garlatti
    Mauro Loi
    Lorenzo Livi
    Medical Oncology, 2020, 37
  • [8] Artificial intelligence for glaucoma: state of the art and future perspectives
    Correia Barao, Rafael
    Hemelings, Ruben
    Abegao Pinto, Luis
    Pazos, Marta
    Stalmans, Ingeborg
    CURRENT OPINION IN OPHTHALMOLOGY, 2024, 35 (02) : 104 - 110
  • [9] Artificial Intelligence for Cognitive Health Assessment: State-of-the-Art, Open Challenges and Future Directions
    Javed, Abdul Rehman
    Saadia, Ayesha
    Mughal, Huma
    Gadekallu, Thippa Reddy
    Rizwan, Muhammad
    Maddikunta, Praveen Kumar Reddy
    Mahmud, Mufti
    Liyanage, Madhusanka
    Hussain, Amir
    COGNITIVE COMPUTATION, 2023, 15 (06) : 1767 - 1812
  • [10] Artificial Intelligence for Cognitive Health Assessment: State-of-the-Art, Open Challenges and Future Directions
    Abdul Rehman Javed
    Ayesha Saadia
    Huma Mughal
    Thippa Reddy Gadekallu
    Muhammad Rizwan
    Praveen Kumar Reddy Maddikunta
    Mufti Mahmud
    Madhusanka Liyanage
    Amir Hussain
    Cognitive Computation, 2023, 15 : 1767 - 1812