Pendugaan Kandungan Kimia Mangga Gedong Gincu Menggunakan Spektroskopi Inframerah Dekat
Herna Permata Sari(1*), Yohanes Aris Purwanto(2), I Wayan Budiastra(3)
(1) Program Studi Teknologi Pascapanen, Sekolah Pasca Sarjana, Institut Pertanian Bogor, Kampus IPB Darmaga, Bogor 16680
(2) Pusat Kajian Hortikultura Tropika, Institut Pertanian Bogor, Kampus IPB Baranagsiang, Jl. Raya Pajajaran, Bogor 16144
(3) Program Studi Teknologi Pascapanen, Sekolah Pasca Sarjana, Institut Pertanian Bogor, Kampus IPB Darmaga, Bogor 16680
(*) Corresponding Author
Abstract
The objective of this work was to predict the soluble solid content, total acid, sugar acid ratio, and crude fiber of ‘Gedong Gincu’ mango non destructive using Near infrared Spectroscopy. Experiments were carried out using 182 samples of ‘Gedong Gincu’ mango. NIR reflectance spectra measurements were performed at wavelength of 1000-2500 nm using NIRFlex N-500 fiber optic solid. References data were collected from laboratory measurements. Five pre-processing treatments, smoothing 3 points (sa3), normalization (n01), first derivative Savitzky-Golay 9 points (dg1), combination (n01, dg1), and the Multiplicative Scatter Correction (MSC) were used to improve the accuracy of the calibration model. Partial Least Square (PLS) method was used to calibrate NIR data through references data. The results show that the best method for prediction of soluble non solid spectra were MSC and 12 factor of PLS with calibration value of Correlation Coefficient (r), Square Error Calibration (SEC), Square Error Prediction (SEP), Ratio of standard error prediction to deviation (RPD) were 0.91, 0.25 %, 0.39 %, 2.14 respectively. Sugar acid ratio content was predictd using MSC and 12 factor of PLS calibration with values of r, SEC, SEP, RPD were 0.81, 32.08 °Brix/%, 38.44 °Brix/%, 1.45. Soluble solid content was predicted using sa3 and 15 factor of PLS calibration with values of r, SEC, SEP, RPD were 0.82, 1.04 °Brix, 1.28 °Brix, 1.52 respectively. Total acid was predicted using dg1 and 3 with the value of r, SEC, SEP, RPD were 0.74, 0.01 %, 0.12 %, 1.33 respectively. It could be concluded that the developed model could be used to predict the chemical contents of ‘Gedong Gincu’ mango non destructively.
ABSTRAK
Tujuan dari penelitian ini adalah memprediksi kandungan total padatan terlarut (TPT), total asam, rasio gula asam, dan padatan tidak terlarut (serat kasar) mangga Gedong Gincu secara non destruktif menggunakan spektroskopi inframerah dekat (NIR). Bahan yang digunakan berupa mangga Gedong Gincu sebanyak 182 buah. Pengukuran spektra reflektan NIR dilakukan pada panjang gelombang 1000 – 2500 nm menggunakan NIRFlex N-500 fiber optik solid dilanjutkan pengukuran data referensi laboratorium. Lima pra-proses data spektra yaitu smoothing 3 points (sa3), normalisasi (n01), first derivative Savitzzky-golay (dg1), kombinasi (n01,dg1), dan Multiplicative Scatter Correction (MSC) dilakukan untuk meningkatkan akurasi model kalibrasi. Kalibrasi data NIR dan data kimia dilakukan menggunakan metode Partial Least Square (PLS). Metode terbaik untuk prediksi padatan tidak terlarut diperoleh dengan pra-proses MSC dan kalibrasi PLS dengan nilai Correlation Coefficient (r), Square Error Calibration (SEC), Square Error Prediction (SEP), Ratio of standard error prediction to deviation (RPD) adalah 0,91, 0,25 %, 0,39 %, 2,14, dan faktor PLS 12. Kandungan rasio gula asam diduga dengan pra-proses MSC serta kalibrasi PLS dengan nilai r, SEC, SEP, RPD adalah 0,81, 32,08 °Brix/%, 38,44 °Brix/%, 1,45 dan faktor PLS yang digunakan 12. TPT diduga menggunakan pra-proses sa3 dan kalibrasi PLS dengan nilai r, SEC, SEP, RPD adalah 0,82, 1,04 oBrix, 1,28 °Brix, 1,52. Model kalibrasi total asam diperoleh pra-proses dg1 dan kalibrasi PLS dengan nilai r, SEC, SEP, RPD adalah 0,74, 0,01 %, 0,12 %, 1,33. Hasil penelitian ini menunjukkan bahwa model yang dikembangkan dapat digunakan untuk menduga kandungan kimia mangga Gedong Gincu secara non destruktif.
Keywords
Full Text:
PDFDOI: https://doi.org/10.22146/agritech.16599
Article Metrics
Abstract views : 4575 | views : 5960Refbacks
- There are currently no refbacks.
Copyright (c) 2016 Herna Permata Sari, Yohanes Aris Purwanto, I Wayan Budiastra
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
agriTECH has been Indexed by:
agriTECH (print ISSN 0216-0455; online ISSN 2527-3825) is published by Faculty of Agricultural Technology, Universitas Gadjah Mada in colaboration with Indonesian Association of Food Technologies.