Abstract & References Vol 25 No 5 (2021)

Malaysian Journal of Analytical Sciences Vol 25 No 5 (2021): 751 - 765

QUALITY ASSESSMENT OF MANGOSTEEN IN DIFFERENT MATURITY STAGES BY HAND-HELD NEAR-INFRARED SPECTROSCOPY

(Penilaian Kualiti Manggis dalam Tahap Kematangan yang Berbeza dengan Genggam Spektroskopi Inframerah Dekat)

Low Shuang Yao¹, Mahmud Iwan Solihin², Pavalee Chompoorat³, Lim Lee Ying¹, Pui Liew Phing¹*

¹Department of Food Science and Nutrition, Faculty of Applied Sciences

²Department of Mechanical and Mechatronics Engineering, Faculty of Engineering, Technology and Built Environment

UCSI University, 56000 Kuala Lumpur, Malaysia

³Faculty of Engineering and Agro-Industry,

Maejo University, Chiang Mai 50290, Thailand.

*Corresponding author: puilp@ucsiuniversity.edu.my

Received: 11 August 2021 ; Accepted: 18 September 2021; Published: 25 October 2021

Abstract

Quality loss of mangosteen, a tropical fruit, is caused by improper post-harvest handling. A method that can evaluate mangosteen color along with its physical and chemical properties quickly and conveniently should be developed. In this study, 90 mangosteen samples were collected and scanned by the hand-held micro near-infrared (NIR) spectrometer in the wavelength from 900–1700 nm. The mangosteen samples were tested with destructive methods such as color, total soluble solids, reducing sugar content, titratable acidity, and pH to obtain the reference data for the predictive model. Spectral data collected has undergone several pre-processing techniques. The enhanced spectral data are regressed using the regression model. Partial least square (PLS) regression and Principal Component Regression are used as the regression method for predicting mangosteen attributes with the help of Orange data mining software. The results showed that color of the sample was not ideal and stage 5 maturity had the lowest L* (27.99), a* (9.03) and b* (7.22). Maturity of stage 6 mangosteen have the highest amount of reducing sugar (10.70 × 10^-6 g/100g) and total soluble solids (7.18%). Pearson’s correlation was used to determine the relationship between the chemical and physical properties of the mangosteen samples. The PLS and PCR predictive models for reducing sugars were obtained with accuracy as R²= 0.56 and R²= 0.50 for the training and testing data, respectively. This achieved accuracy may not be good, but it can be improved in the future by using nonlinear machine learning and ensemble methods such as PLS and PCR. Overall, this study indicated that the NIR spectroscopy technique combined with several pre-processing methods and the predictive model by PLS and PCR could be a rapid and non-destructive method for evaluating the quality and maturity of the mangosteen fruit.

Keywords: hand-held near-infrared spectroscopy, mangosteen, color analysis, total soluble solids, non-destructive quality assessment

Abstrak

Kehilangan kualiti manggis, buah tropika, disebabkan oleh pengendalian pasca tuai yang tidak betul. Kaedah yang dapat menilai warna manggis, sifat manggis fizikal dan kimia dengan kelajuan dan kemudahan yang pantas harus dikembangkan. Dalam kajian ini, 90 sampel manggis dikumpulkan dan diimbas oleh spektrometer mikro dekat inframerah (NIR) genggam. Sampel manggis diuji dengan kaedah yang merosakkan seperti warna, pepejal larut total, pengurangan kandungan gula, keasidan yang dapat ditetrasi dan pH untuk mendapatkan data rujukan untuk model ramalan. Data spektral yang dikumpulkan telah menjalani beberapa teknik pra-pemprosesan. Data spektrum yang ditingkatkan mundur menggunakan model latihan regresi. Regresi Separa Sekurang Persegi (PLS) dan Regresi Komponen Utama digunakan sebagai kaedah regresi untuk meramalkan atribut manggis dengan bantuan perisian perlombongan data Orange. Hasil kajian menunjukkan bahawa warna sampel tidak sesuai untuk kematangan tahap 5 yang mempunyai terendah L*(27.99), a* (9.03) dan b* (7.22). Kematangan manggis tahap 6 mempunyai jumlah gula pengurangan tertinggi (10.70 × 10-6 g/100g) dan jumlah perpejal larut (7.18%). Korelasi Pearson digunakan untuk menentukan hubungan antara sifat kimia dan fizikal sampel manggis. Model ramalan PLS dan PCR diperoleh dengan ketepatan masing-masing R²=0.56 dan R²=0.50. Secara kesuluruhan, kajian ini menunjukkan bahawa teknik spektroskopi transmisi NIR digabungkan dengan beberapa kaedah pra-pemprosesan dan model ramalan yang dibandingkan dengan PLS dan PCR dapat menjadi kaedah yang cepat dan tidak merosakkan untuk menilai kualiti dan kematangan buah manggis.

Kata kunci: genggam spektroskopi inframerah dekat, manggis, analisis warna, jumlah pepejal larut, penilaian kualiti yang tidak merosakkan

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