Oil Content and Free Fatty Acid Prediction of Oil Palm Fresh Fruit Bunches Using Multispectral Imaging and Partial Least Square Algorithm
- 10.2991/978-94-6463-228-6_17How to use a DOI?
- Multispectral Imaging; Oil Palm FFB; Oil Content; Free Fatty Acid; PLS algorithms
Multispectral imaging has many applications in agriculture, such as the prediction of the internal qualities of fruit and vegetables. Multispectral is preferable to Hyperspectral imaging for fast in-line sorting and grading machine vision due to fewer wavelength bands applied. Oil palm fresh fruit bunches (FFBs) are the source of crude palm oil (CPO) in Indonesia and Malaysia. However, the sorting and grading of FFBs are still done manually by experienced graders. Oil content and free fatty acid (FFA) are the main qualities of FFBs. Predicting the oil and FFA contents as part of the grading process is crucial. This study aimed to predict the oil content and FFA using a multispectral imaging system with a partial least square (PLS) algorithm. The system used three bandpass filters with wavelengths of 710 nm, 800 nm, and 830 nm, attached to a filter wheel in front of a monochrome camera. The acquisition and image processing used Python programming language. Mean Absolute Percentage Error (MAPE) was applied to calculate the accuracy of the prediction results. The MAPE values were 20.94% and 7.5% for the oil content and FFA prediction, respectively. These results show the potential use of multispectral imaging for predicting oil content and FFA of oil palm FFB.
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Cite this article
TY - CONF AU - Minarni Shiddiq AU - Roni Salambue AU - Zulfansyah Zulfansyah AU - Jahrizal Jahrizal AU - Ikhsan Rahman Husein AU - Sinta Afria Ningsih AU - Galef Alfahrezi PY - 2023 DA - 2023/08/22 TI - Oil Content and Free Fatty Acid Prediction of Oil Palm Fresh Fruit Bunches Using Multispectral Imaging and Partial Least Square Algorithm BT - Proceedings of the 4th International Seminar on Science and Technology (ISST 2022) PB - Atlantis Press SP - 143 EP - 154 SN - 2352-541X UR - https://doi.org/10.2991/978-94-6463-228-6_17 DO - 10.2991/978-94-6463-228-6_17 ID - Shiddiq2023 ER -