IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v15y2025i11p1154-d1665850.html
   My bibliography  Save this article

Towards Intelligent Pruning of Vineyards by Direct Detection of Cutting Areas

Author

Listed:
  • Elia Pacioni

    (Centro Universitario de Mérida, Universidad de Extremadura, Avda. Santa Teresa de Jornet, 38, 06800 Mérida, Spain
    HES-SO Valais/Wallis, 3960 Sierre, Switzerland)

  • Eugenio Abengózar

    (Facultad de Ciencias, Universidad de Extremadura, Avda. de Elvas, s/n, 06006 Badajoz, Spain)

  • Miguel Macías Macías

    (Centro Universitario de Mérida, Universidad de Extremadura, Avda. Santa Teresa de Jornet, 38, 06800 Mérida, Spain
    Instituto de Computación Científica Avanzada, Av. de la Investigación, s/n, 06006 Badajoz, Spain)

  • Carlos J. García-Orellana

    (Facultad de Ciencias, Universidad de Extremadura, Avda. de Elvas, s/n, 06006 Badajoz, Spain
    Instituto de Computación Científica Avanzada, Av. de la Investigación, s/n, 06006 Badajoz, Spain)

  • Ramón Gallardo

    (Instituto de Computación Científica Avanzada, Av. de la Investigación, s/n, 06006 Badajoz, Spain
    Escuela Politécnica, Universidad de Extremadura, Avda. Universidad s/n, 10003 Cáceres, Spain)

  • Horacio M. González Velasco

    (Instituto de Computación Científica Avanzada, Av. de la Investigación, s/n, 06006 Badajoz, Spain
    Escuela Politécnica, Universidad de Extremadura, Avda. Universidad s/n, 10003 Cáceres, Spain)

Abstract

The development of robots for automatic pruning of vineyards using deep learning techniques seems feasible in the medium term. In this context, it is essential to propose and study solutions that can be deployed on portable hardware, with artificial intelligence capabilities but reduced computing power. In this paper, we propose a novel approach to vineyard pruning by direct detection of cutting areas in real time by comparing Mask R-CNN and YOLOv8 performances. The studied object segmentation architectures are able to segment the image by locating the trunk, and pruned and not pruned vine shoots. Our study analyzes the performance of both frameworks in terms of segmentation efficiency and inference times on a Jetson AGX Orin GPU. To compare segmentation efficiency, we used the mAP50 and AP50 per category metrics. Our results show that YOLOv8 is superior both in segmentation efficiency and inference time. Specifically, YOLOv8-S exhibits the best tradeoff between efficiency and inference time, showing an mAP50 of 0.883 and an AP50 of 0.748 for the shoot class, with an inference time of around 55 ms on a Jetson AGX Orin.

Suggested Citation

  • Elia Pacioni & Eugenio Abengózar & Miguel Macías Macías & Carlos J. García-Orellana & Ramón Gallardo & Horacio M. González Velasco, 2025. "Towards Intelligent Pruning of Vineyards by Direct Detection of Cutting Areas," Agriculture, MDPI, vol. 15(11), pages 1-15, May.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:11:p:1154-:d:1665850
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/15/11/1154/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/15/11/1154/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ruzzante, Sacha & Labarta, Ricardo & Bilton, Amy, 2021. "Adoption of agricultural technology in the developing world: A meta-analysis of the empirical literature," World Development, Elsevier, vol. 146(C).
    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. Shrestha, Sujata & Shrestha, Uttam Babu & Shrestha, Bibek Raj & Maharjan, Shirish & Udas, Erica & Aryal, Kamal, 2024. "Determinants of adoption of climate resilient agricultural solutions," Agricultural Systems, Elsevier, vol. 221(C).
    2. Khumairoh, Uma & Teixeira, Heitor Mancini & Yadav, Sudhir & Schulte, Rogier P.O. & Batas, Mary Ann & Asmara, Degi Harja & Flor, Rica Joy & Agustina, Rohmatin & Setiawan, Adi & Nurlaelih, Euis E. & Pur, 2024. "Linking types of East Javanese rice farming systems to farmers' perceptions of complex rice systems," Agricultural Systems, Elsevier, vol. 218(C).
    3. Selvaggi, R. & Pappalardo, G. & Zarbà, C. & Lusk, J.L., 2024. "Driving factors behind precision livestock farming tools adoption: The case of the pedometer on dairy farms," Agricultural Systems, Elsevier, vol. 220(C).
    4. Dario Schulz & Jan Börner, 2023. "Innovation context and technology traits explain heterogeneity across studies of agricultural technology adoption: A meta‐analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 570-590, June.
    5. Das, Nandini & Gupta, Anubhab & Majumder, Binoy & Das, Mahamitra & Muniappan, Rangaswamy, 2024. "Does Training Farmers on Multiple Technologies Deter Adoption? Evidence from a Farm Management Training Program in Bangladesh," 2024 Annual Meeting, July 28-30, New Orleans, LA 344219, Agricultural and Applied Economics Association.
    6. Schwab, Benjamin & Yu, Jisang, 2022. "Guaranteed Storage? Risk and Credit Constraints in the Demand for Postharvest Technology and Rice Seed Storage Decisions in Bangladesh," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322475, Agricultural and Applied Economics Association.
    7. Dong, Fengxia & Mitchell, Paul D., 2023. "Economic and risk analysis of sustainable practice adoption among U.S. corn growers," Agricultural Systems, Elsevier, vol. 211(C).
    8. Mangole, Cool Dady & Maina, Charles Mbogo & Mulungu, Kelvin & Tschopp, Maurice & Harari, Nichole & Suresh, Roopa & Kassie, Menale, 2025. "Adoption of sustainable land and water management practices and their impact on crop productivity among smallholder farmers in sub-Saharan Africa," Land Use Policy, Elsevier, vol. 153(C).
    9. Zuberi, Mehwish & Spies, Michael & Nielsen, Jonas Ø., 2024. "Is there a future for smallholder farmers in bioeconomy? The case of ‘improved’ seeds in South Punjab, Pakistan," Forest Policy and Economics, Elsevier, vol. 158(C).
    10. Zor, Ummugulsum & Esen, Ayla & Canbulut, Murad & Karaca, Nevran & Karakaya, Gencay & Turker, Ipek, 2024. "A systems approach to understanding the interconnected factors affecting rural development: A case study from Türkiye," World Development Perspectives, Elsevier, vol. 34(C).
    11. Bridget Bwalya & Edward Mutandwa & Brian Chanda Chiluba, 2023. "Awareness and Use of Sustainable Land Management Practices in Smallholder Farming Systems," Sustainability, MDPI, vol. 15(20), pages 1-20, October.
    12. Magor Ors KOLLO & Vincentiu-Andrei VERES & Maria MORTAN, 2025. "From Perception to Practice: Drone Technology in Romanian Agriculture," Management and Economics Review, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 10(1), pages 5-21, February.
    13. Yeboah, Samuel, 2023. "Unlocking the Potential of Technological Innovations for Sustainable Agriculture in Developing Countries: Enhancing Resource Efficiency and Environmental Sustainability," MPRA Paper 118215, University Library of Munich, Germany, revised 26 Jul 2023.
    14. Passarelli, Mariacarmela & Bongiorno, Giuseppe & Cucino, Valentina & Cariola, Alfio, 2023. "Adopting new technologies during the crisis: An empirical analysis of agricultural sector," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    15. Winarno, Kodrad & Sustiyo, Joko & Aziz, Ammar Abdul & Permani, Risti, 2025. "Unlocking agricultural mechanisation potential in Indonesia: Barriers, drivers, and pathways for sustainable agri-food systems," Agricultural Systems, Elsevier, vol. 226(C).
    16. Pérez-Marulanda, Lisset & Jepsen, Martin Rudbeck & Castro-Nunez, Augusto, 2025. "Boosting the adoption of sustainable land-use systems for achieving Colombian land-based climate action and peacebuilding goals," World Development, Elsevier, vol. 188(C).
    17. Shah, Wasi Ul Hassan & Hao, Gang & Yan, Hong & Yasmeen, Rizwana & Xu, Xiaowei, 2024. "Natural resources utilization efficiency evaluation, determinant of productivity change, and production technology heterogeneity across developed and developing G20 economies," Technology in Society, Elsevier, vol. 77(C).
    18. Matavel, Custodio Efraim & Hoffmann, Harry & Kaechele, Harald & Löhr, Katharina & Bonatti, Michelle & Kipkulei, Harison K. & Njoya, Hamza Moluh & Massuque, Jonas & Sieber, Stefan & Rybak, Constance, 2024. "Does participatory research stimulate sustained adoption of energy technologies? Lessons from stove dissemination in Gurué district, rural Mozambique," Technology in Society, Elsevier, vol. 79(C).
    19. Adhikari, Lipy & Komarek, Adam M. & de Voil, Peter & Rodriguez, Daniel, 2023. "A framework for the assessment of farm diversification options in broadacre agriculture," Agricultural Systems, Elsevier, vol. 210(C).
    20. Aslihan Arslan & Kristin Floress & Christine Lamanna & Leslie Lipper & Todd S Rosenstock, 2022. "A meta-analysis of the adoption of agricultural technology in Sub-Saharan Africa," PLOS Sustainability and Transformation, Public Library of Science, vol. 1(7), pages 1-17, July.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jagris:v:15:y:2025:i:11:p:1154-:d:1665850. 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.