Estimating numbers of oil palm (Elaeis guineensis) pollen grains using image analysis and processing

Putra Ramadhani Eka, . and Permana Budi, . and Kinasih Ida, . and Permana Agus Dana, . and Sahari Bandung, . Estimating numbers of oil palm (Elaeis guineensis) pollen grains using image analysis and processing. pp. 311-317. ISSN 1511-2780

Elaeidobius kamerunicus is the most important oil palm pollinator in Indonesia and Malaysia. However the mechanism and efficiency of pollen transfer by this weevil are clearly not understood. The lack of study on pollination process in oil palm (Elaeis guineensis) is mostly caused by difficulties in pollen counting due to their small size. Most of the counting was conducted manually which is prone to mistakes required extensive training and time-consuming. The aim of this study is to provide a novel technique for counting pollen that is rapid consistent and efficient with a comparable accuracy to manual counting. Male and female of E. kamerunicus were collected from male and female oil palm inflorescences (N60). Extracted pollen were placed and distributed in a flat microscope slide separated by designated observation chambers. Images of each chamber were captured as a JPEG format and analysed by ImageJ. Multiple macros were constructed for image processing steps to obtain the pollen numbers. Comparison with manual counting using paired T-test Pearsons correlation and linear regression showed a high similarity between both methods.

Full text available from: Official URL: http://jopr.mpob.gov.my/estimating-numbers-of-oil-...

Abstract

Elaeidobius kamerunicus is the most important oil palm pollinator in Indonesia and Malaysia. However the mechanism and efficiency of pollen transfer by this weevil are clearly not understood. The lack of study on pollination process in oil palm (Elaeis guineensis) is mostly caused by difficulties in pollen counting due to their small size. Most of the counting was conducted manually which is prone to mistakes required extensive training and time-consuming. The aim of this study is to provide a novel technique for counting pollen that is rapid consistent and efficient with a comparable accuracy to manual counting. Male and female of E. kamerunicus were collected from male and female oil palm inflorescences (N60). Extracted pollen were placed and distributed in a flat microscope slide separated by designated observation chambers. Images of each chamber were captured as a JPEG format and analysed by ImageJ. Multiple macros were constructed for image processing steps to obtain the pollen numbers. Comparison with manual counting using paired T-test Pearsons correlation and linear regression showed a high similarity between both methods.

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Item Type:	Article
AGROVOC Term:	Elaeis guineensis
AGROVOC Term:	Elaeidobius kamerunicus
AGROVOC Term:	Image analysis
AGROVOC Term:	Image processing
AGROVOC Term:	Inflorescences
AGROVOC Term:	Oil palms
AGROVOC Term:	Oil plants
AGROVOC Term:	Pollen
AGROVOC Term:	Pollination
Depositing User:	Ms. Suzila Mohamad Kasim
Last Modified:	24 Apr 2025 06:28
URI:	http://webagris.upm.edu.my/id/eprint/24152

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