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Application of artificial neural network to predict copra conversion factor

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Abstract

Coconut (Cocos nucifera) is one of the major plantation crops in Sri Lanka. It has paved the way for establishing many industries due to versatility of the crop earning significant income to the country. One of the most important export products of coconut is “Copra” which earns a high export market income to the country (927.7 Rs/Mln in 2019). Literature reports that the copra conversion factor (CCF) is 0.19 kg, where approximately 5 nuts are required to produce 1 kg of copra. This study investigates the stability of this conversion factor and the dependency of it with various nut parameters (number of nuts in a harvest, fresh nut weight, husked nut weight (DW) and split nut weight (SW)) and meteorological parameters (rainfall, maximum and minimum air temperatures) to establish a relationship to estimate CCF of a nut. Results showed that CCF was temporally not stable and positively correlated with DW and SW. The study established a model to predict CCF using multilayer feed-forward neural network approach (MLFFNN). Performance of the model showed R  = 0.83  in training, 0.93 in testing and 0.93 in validation with MSE < 0.0002. Study further revealed that ~ 50% of the temporal variability of copra outturn was explained by temperature related parameters.

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Source: Coconut Research Institute, Sri Lanka

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Acknowledgements

Authors are grateful to the staff of the former biometry division at Coconut Research Institute (CRI) of Sri Lanka for assisting in the implementation of field study and the data collection. Coconut Processing Research Division of the same institute is also greatly acknowledged for preparing copra during the study period.

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Authors and Affiliations

  1. Plant Physiology Division, Coconut Research Institute, Bandirippuwa Estate, Lunuwila, Sri Lanka

    K. P. Waidyarathne, T. H. Chandrathilake & W. S. Wickramarachchi

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  1. K. P. Waidyarathne
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  2. T. H. Chandrathilake
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  3. W. S. Wickramarachchi
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Correspondence to K. P. Waidyarathne.

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Waidyarathne, K.P., Chandrathilake, T.H. & Wickramarachchi, W.S. Application of artificial neural network to predict copra conversion factor. Neural Comput & Applic 34, 7909–7918 (2022). https://doi.org/10.1007/s00521-022-06893-3

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