Predicting Heritability of Oil Palm Breeding Using Phenotypic Traits and Machine Learning Article Swipe
Najihah Ahmad Latif
,
Fatini Nadhirah Mohd Nain
,
Nurul Hashimah Ahamed Hassain Malim
,
Rosni Abdullah
,
Muhammad Rahim
,
Mohd Nasruddin Mohamad
,
Nurul Syafika Mohamad Fauzi
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/su132212613
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/su132212613
Oil palm is one of the main crops grown to help achieve sustainability in Malaysia. The selection of the best breeds will produce quality crops and increase crop yields. This study aimed to examine machine learning (ML) in oil palm breeding (OPB) using factors other than genetic data. A new conceptual framework to adopt the ML in OPB will be presented at the end of this paper. At first, data types, phenotype traits, current ML models, and evaluation technique will be identified through a literature survey. This study found that the phenotype and genotype data are widely used in oil palm breeding programs. The average bunch weight, bunch number, and fresh fruit bunch are the most important characteristics that can influence the genetic improvement of progenies. Although machine learning approaches have been applied to increase the productivity of the crop, most studies focus on molecular markers or genotypes for plant breeding, rather than on phenotype. Theoretically, the use of phenotypic data related to offspring should predict high breeding values by using ML. Therefore, a new ML conceptual framework to study the phenotype and progeny data of oil palm breeds will be discussed in relation to achieving the Sustainable Development Goals (SDGs).
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/su132212613
- https://www.mdpi.com/2071-1050/13/22/12613/pdf?version=1637053496
- OA Status
- gold
- Cited By
- 7
- References
- 78
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3214318038
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3214318038Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/su132212613Digital Object Identifier
- Title
-
Predicting Heritability of Oil Palm Breeding Using Phenotypic Traits and Machine LearningWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-11-15Full publication date if available
- Authors
-
Najihah Ahmad Latif, Fatini Nadhirah Mohd Nain, Nurul Hashimah Ahamed Hassain Malim, Rosni Abdullah, Muhammad Rahim, Mohd Nasruddin Mohamad, Nurul Syafika Mohamad FauziList of authors in order
- Landing page
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https://doi.org/10.3390/su132212613Publisher landing page
- PDF URL
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https://www.mdpi.com/2071-1050/13/22/12613/pdf?version=1637053496Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2071-1050/13/22/12613/pdf?version=1637053496Direct OA link when available
- Concepts
-
Heritability, Biology, Biotechnology, Palm oil, Crop, Palm, Elaeis guineensis, Selection (genetic algorithm), Phenotype, Sustainability, Plant breeding, Gene–environment interaction, Genotype, Agronomy, Machine learning, Genetics, Agricultural science, Computer science, Gene, Ecology, Physics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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7Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 2, 2023: 2, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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78Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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