Research Article
The Application of Near Infrared Reflectance Spectroscopy as A Fast and Non-Destructive Method to Determine Inner Quality Parameters of Intact Mango
@INPROCEEDINGS{10.4108/eai.3-10-2018.2284287, author={Agus Arip Munawar and Hesti Meilina and Zulfahrizal Zulfahrizal}, title={The Application of Near Infrared Reflectance Spectroscopy as A Fast and Non-Destructive Method to Determine Inner Quality Parameters of Intact Mango}, proceedings={Proceeding of the First International Graduate Conference (IGC) On Innovation, Creativity, Digital, \& Technopreneurship for Sustainable Development in Conjunction with The 6th Roundtable for Indonesian Entrepreneurship Educators 2018 Universitas Syiah Kuala October, 3-5, 2018 Banda Aceh, Indonesia}, publisher={EAI}, proceedings_a={IGC}, year={2019}, month={5}, keywords={soluble solids content (ssc) near infrared reflectance spectroscopy (nirs) mangos}, doi={10.4108/eai.3-10-2018.2284287} }
- Agus Arip Munawar
Hesti Meilina
Zulfahrizal Zulfahrizal
Year: 2019
The Application of Near Infrared Reflectance Spectroscopy as A Fast and Non-Destructive Method to Determine Inner Quality Parameters of Intact Mango
IGC
EAI
DOI: 10.4108/eai.3-10-2018.2284287
Abstract
Generally speaking, to determine inner quality parameters such as soluble solids content (SSC) and vitamin C of intact mango or other fruits, several methods were already employed. Yet, most of them are based on chemical analysis and fruit extraction followed by other laboratory analysis. These methods often require complicated sample processing, longer time consuming and destructive. In the last three decades, the application of near infrared reflectance spectroscopy (NIRS) as a fast, robust and non-destructive method in agricultural industries is gaining more attentions. Thus, the main purpose of this present study is to apply the NIRS method in determining SSC and vitamin C of intact whole mango by developing prediction models. Spectra data were corrected and enhanced using mean normalization (MN), standard normal variate (SNV) and the combination of them (MN+SNV). Prediction models used to predict SSC and vitamin C of intact mangos were developed using partial least square regression (PLSR). The results showed that SSC and vitamin C can be predicted rapidly and simultaneously using NIRS method with maximum correlation coefficient (r) were 0.85 for SSC and 0.96 for vitamin C, with residual predictive deviation (RPD) index were 1.92 and 3.53 for SSC and vitamin C respectively. Based on obtained results, we may conclude that the NIRS method can be applied as an alternative fast and non-destructive method in determining quality parameters of intact mango.