Oil Palm and Machine Learning: Reviewing One Decade of Ideas, Innovations, Applications, and Gaps

Nuzhat Khan, Mohamad Anuar Kamaruddin, Usman Ullah Sheikh, Yusri Yusup and Muhammad Paend Bakht
Additional contact information
Nuzhat Khan: School of Industrial Technology, Universiti Sains Malaysia, Gelugor 11800, Malaysia
Mohamad Anuar Kamaruddin: School of Industrial Technology, Universiti Sains Malaysia, Gelugor 11800, Malaysia
Usman Ullah Sheikh: School of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
Yusri Yusup: School of Industrial Technology, Universiti Sains Malaysia, Gelugor 11800, Malaysia
Muhammad Paend Bakht: School of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia

Agriculture, 2021, vol. 11, issue 9, 1-26

Abstract: Machine learning (ML) offers new technologies in the precision agriculture domain with its intelligent algorithms and strong computation. Oil palm is one of the rich crops that is also emerging with modern technologies to meet global sustainability standards. This article presents a comprehensive review of research dedicated to the application of ML in the oil palm agricultural industry over the last decade (2011–2020). A systematic review was structured to answer seven predefined research questions by analysing 61 papers after applying exclusion criteria. The works analysed were categorized into two main groups: (1) regression analysis used to predict fruit yield, harvest time, oil yield, and seasonal impacts and (2) classification techniques to classify trees, fruit, disease levels, canopy, and land. Based on defined research questions, investigation of the reviewed literature included yearly distribution and geographical distribution of articles, highly adopted algorithms, input data, used features, and model performance evaluation criteria. Detailed quantitative–qualitative investigations have revealed that ML is still underutilised for predictive analysis of oil palm. However, smart systems integrated with machine vision and artificial intelligence are evolving to reform oil palm agri-business. This article offers an opportunity to understand the significance of ML in the oil palm agricultural industry and provides a roadmap for future research in this domain.

Keywords: oil palm; machine learning; systematic review; agriculture; sustainability (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://www.mdpi.com/2077-0472/11/9/832/pdf (application/pdf)
https://www.mdpi.com/2077-0472/11/9/832/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:11:y:2021:i:9:p:832-:d:625945

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().