Physical Properties and Mass Modelling of Matoa Fruit (Pometia pinnata) at Different Varieties

dc.citation.epage192
dc.citation.issueS1
dc.citation.spage171
dc.citation.volume49
dc.contributor.authorMohd Hafizz Wondi
dc.contributor.authorNur Izzah Nabilah Haris
dc.contributor.authorMaimunah Mohd Ali
dc.contributor.authorSharifah Raina Manaf
dc.contributor.authorAbdul Rahman Saili
dc.contributor.authorAkmal Shafiq Badarul Azam
dc.contributor.authorBernard Maringgal
dc.contributor.authorMuhammad Hazwan Hamzah
dc.contributor.authorMuhammad Shahimi Ariffin
dc.contributor.departmentFaculty of Resource Science and Technology
dc.date.accessioned2026-04-06T07:24:07Z
dc.date.issued2026-03-17
dc.description.abstractMatoa fruit is a tropical fruit with a native background of Southeast Asia that is very promising in terms of specific flavour and nutrient properties, yet is under a poor usage by the groups because of the lack of post-harvest studies. There are two types of mass modelling discussed in this paper to facilitate post-harvest handling, sorting, and grading: purple and red Matoa. The average mass, primary diameter, Surface Area (SA), and sphericity of purple Matoa were 42.86 g, 54.22 mm, 7133 mm², and 0.85, in comparison to 17.55 g, 40.95 mm, 3610 mm², and 0.78 of red Matoa, respectively. It is worth noting that the dimensions, SA, and volume have been used as independent parameters to come up with regression models. The quadratic model proved to have the best predictive potential. The most suitable predictor of mass was the equivalent mean diameter (De) with a R² = 0.962 and Standard Error of Estimate (SEE) = 0.689. In line with this, the quadratic model was very good in explaining the case of SA, where R² = 0.960 and SEE = 0.714. Likewise, the model of the volume of an ellipsoid had a high predictive accuracy (R² = 0.960, SEE = 0.709). The results indicate that quadratic models are reliable in forecasting the mass of Matoa fruit, which can be used to design effective automated grading systems. This research would help to commercialise Matoa fruit in a sustainable way by removing the labour-intensive operations and increasing the value of the fruit in commercial and industrial use. Future research may focus on scalability and integration with machine vision systems.
dc.description.referencesUncontrolled Keywords: Mass modelling, mass prediction model, Matoa fruit, physical properties, post-harvest.
dc.description.statusPublished
dc.identifier.citationWondi, M. H., Haris, N. I. N., Ali, M. M., Manaf, S. R., Saili, A. R., Azam, A. S. B., Maringgal, B., Hamzah, M. H., & Ariffin, M. S. (2026). Physical properties and mass modelling of matoa fruit (Pometia pinnata) at different varieties. Pertanika Journal of Tropical Agricultural Science, 49(S1). https://doi.org/10.47836/pjtas.49.S1.08
dc.identifier.doihttps://doi.org/10.47836/pjtas.49.S1.08
dc.identifier.emailmbernard@unimas.my
dc.identifier.issn2231-8542
dc.identifier.urihttp://www.pertanika.upm.edu.my/pjtas/browse/special-issue?article=JTAS(S)-3571-2025
dc.identifier.urihttps://scholarhub.unimas.my/handle/123456789/296
dc.publisherUniversiti Putra Malaysia Press
dc.relation.ispartofPertanika Journal of Tropical Agricultural Science
dc.titlePhysical Properties and Mass Modelling of Matoa Fruit (Pometia pinnata) at Different Varieties
dc.typeArticles
dc.type.statusYes

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