Pineapple Maturity Recognition Using RGB Extraction
Pineapples can be classified using an index with seven
levels of maturity based on the green and yellow color of the skin. As
the pineapple ripens, the skin will change from pale green to a golden
or yellowish color. The issues that occur in agriculture nowadays are
to do with farmers being unable to distinguish between the indexes of
pineapple maturity correctly and effectively. There are several
reasons for why farmers cannot properly follow the guideline provide
by Federal Agriculture Marketing Authority (FAMA) and one of
reason is that due to manual inspection done by experts, there are no
specific and universal guidelines to be adopted by farmers due to the
different points of view of the experts when sorting the pineapples
based on their knowledge and experience. Therefore, an automatic
system will help farmers to identify pineapple maturity effectively
and will become a universal indicator to farmers.
[1] P. B. Van, J. Ceusters, M.P. Proft , Determination of Pineapple
(Ananas comosus, MD-2 hybrid cultivar) Plant Maturity, the Efficiency
of Flowering Induction Agents and the Use of Activated Carbon.
Scientia Horticulturae vol. 120, 2009 , pp. 58-63.
[2] S. Rosnah, R. W. D. Wan, S. T. Mohammad, H. Osman, Chemical
Compositions And Thermal Properties Of The Josapine Variety Of
Pineapple Fruit (Ananas Comosus L.) in Different Storage Systems.
Journal of Food Process Engineering Vol. 34, Issue 5,2009, pp. 1558-
1572.
[3] E. Blotta ,A. Bouchet, V. Ballarin, J. Pastore , Enhancement of Medical
Images In HSI Color Space. Journal of Physics : Conference Series 332,
2011 , pp. 1-4.
[4] H. Keqian, X. Hanbing, W. Junning, Z. Lubin, H. Huigang, J. Zhiwei ,
G. Hui, H. Quanguang, G. Deqiang, Quality Changes And Internal
Browning Developments of Summer Pineapple Fruit During Storage at
Different Temperature. Scientia Horticulturae 151, 2013.
[5] F. S. Ramon, C. G. Antonio, P. F. F. Hugo, L. D. V. Lírio, A. S.
Douglas, P. G. Miguel, Nodule Cluster Cultures and Temporary
Immersion Bioreactors as a High Performance Micropropagation
Strategy in Pineapple (Ananas Comosus Var. Comosus). Scientia
Horticulturae 151, 2013.
[6] A. N. F. Fabiano, E. L. Jr. Francisco, R. Sueli, Ultrasound as Pre-
Treatment for Drying of Pineapple. Ultrasonics Sonochemistry vol. 15,
2008.
[7] L.A. Ramallo , R.H. Mascheroni, Quality Evaluation of Pineapple Fruit
During Drying Process. Food And Bioproducts Processing vol. 90,2012.
[8] J. A. T. Pennington, R. A. Fisher, Classification of Fruits and
Vegetables. Journal of Food Composition and Analysis 22S,2009.
[9] M.Z. Abdullah, L.C. Guan, K.C. Lim, A.A. Karim ,The Applications of
Computer Vision System and Tomographic Radar Imaging for Assessing
Physical Properties of Food. Journal of Food Engineering vol. 61, 2004.
[10] H.D. Cheng, X.H. Jiang, Y. Sun, Jingli Wang, Color Image
Segmentation: Advances and Prospects. Pattern Recognition vol.
34,2001.
[11] M.Z. Abdullah, L.C. Guan, B.M.N. Mohd Azemi, Stepwise
Discriminant Analysis for Colour Grading of Oil Palm Using Machine
Vision System. Institution of Chemical Engineers vol. 79 2001.
[1] P. B. Van, J. Ceusters, M.P. Proft , Determination of Pineapple
(Ananas comosus, MD-2 hybrid cultivar) Plant Maturity, the Efficiency
of Flowering Induction Agents and the Use of Activated Carbon.
Scientia Horticulturae vol. 120, 2009 , pp. 58-63.
[2] S. Rosnah, R. W. D. Wan, S. T. Mohammad, H. Osman, Chemical
Compositions And Thermal Properties Of The Josapine Variety Of
Pineapple Fruit (Ananas Comosus L.) in Different Storage Systems.
Journal of Food Process Engineering Vol. 34, Issue 5,2009, pp. 1558-
1572.
[3] E. Blotta ,A. Bouchet, V. Ballarin, J. Pastore , Enhancement of Medical
Images In HSI Color Space. Journal of Physics : Conference Series 332,
2011 , pp. 1-4.
[4] H. Keqian, X. Hanbing, W. Junning, Z. Lubin, H. Huigang, J. Zhiwei ,
G. Hui, H. Quanguang, G. Deqiang, Quality Changes And Internal
Browning Developments of Summer Pineapple Fruit During Storage at
Different Temperature. Scientia Horticulturae 151, 2013.
[5] F. S. Ramon, C. G. Antonio, P. F. F. Hugo, L. D. V. Lírio, A. S.
Douglas, P. G. Miguel, Nodule Cluster Cultures and Temporary
Immersion Bioreactors as a High Performance Micropropagation
Strategy in Pineapple (Ananas Comosus Var. Comosus). Scientia
Horticulturae 151, 2013.
[6] A. N. F. Fabiano, E. L. Jr. Francisco, R. Sueli, Ultrasound as Pre-
Treatment for Drying of Pineapple. Ultrasonics Sonochemistry vol. 15,
2008.
[7] L.A. Ramallo , R.H. Mascheroni, Quality Evaluation of Pineapple Fruit
During Drying Process. Food And Bioproducts Processing vol. 90,2012.
[8] J. A. T. Pennington, R. A. Fisher, Classification of Fruits and
Vegetables. Journal of Food Composition and Analysis 22S,2009.
[9] M.Z. Abdullah, L.C. Guan, K.C. Lim, A.A. Karim ,The Applications of
Computer Vision System and Tomographic Radar Imaging for Assessing
Physical Properties of Food. Journal of Food Engineering vol. 61, 2004.
[10] H.D. Cheng, X.H. Jiang, Y. Sun, Jingli Wang, Color Image
Segmentation: Advances and Prospects. Pattern Recognition vol.
34,2001.
[11] M.Z. Abdullah, L.C. Guan, B.M.N. Mohd Azemi, Stepwise
Discriminant Analysis for Colour Grading of Oil Palm Using Machine
Vision System. Institution of Chemical Engineers vol. 79 2001.
@article{"International Journal of Electrical, Electronic and Communication Sciences:60775", author = "J. I. Asnor and S. Rosnah and Z. W. H. Wan and H. A. B. Badrul", title = "Pineapple Maturity Recognition Using RGB Extraction", abstract = "Pineapples can be classified using an index with seven
levels of maturity based on the green and yellow color of the skin. As
the pineapple ripens, the skin will change from pale green to a golden
or yellowish color. The issues that occur in agriculture nowadays are
to do with farmers being unable to distinguish between the indexes of
pineapple maturity correctly and effectively. There are several
reasons for why farmers cannot properly follow the guideline provide
by Federal Agriculture Marketing Authority (FAMA) and one of
reason is that due to manual inspection done by experts, there are no
specific and universal guidelines to be adopted by farmers due to the
different points of view of the experts when sorting the pineapples
based on their knowledge and experience. Therefore, an automatic
system will help farmers to identify pineapple maturity effectively
and will become a universal indicator to farmers.", keywords = "Artificial Neural Network, Image Processing, Index of Maturity, Pineapple", volume = "7", number = "6", pages = "731-4", }