Prediction of hardness development in mangosteen peel using NIR spectroscopy during low temperature storage

Ahmad, Usman; Sutrisno, Sutrisno; Purwanto, Y. Aris; Budiastra, Wayan; Makino, Yoshio; Oshita, Seiichi; Kawagoe, Yoshinori; Kuroki, Shinichiro; Novita, Dwi Dian

doi:10.1016/j.eaef.2013.12.011

Cited by 4 publications

(3 citation statements)

References 4 publications

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“…One of the methods that can directly and nondestructively measure chemical content is NIR spectroscopy. NIR spectroscopy has been applied to determine chemical content of agricultural products such as major chemical content of dragon fruit peel flour [5], TSS of mango [6], hardness of mangosteen [7], TSS of papaya [8], trigonelline, chlorogenic acid, caffeine content of coffees [9][10], TSS and firmness of persimmon [11]. There is no report about NIR spectroscopy application on predicting TSS and hardness of dragon fruit.…”

Section: Introductionmentioning

confidence: 99%

Effect of chemometrics to accuracy of NIR spectroscopy in predicting total soluble solid and hardness of dragon fruit

Budiastra¹,

Dzikri²

2022

IOP Conf. Ser.: Earth Environ. Sci.

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NIR spectroscopy and chemometrics were assessed to determine the total soluble solids (TSS) and hardness of the dragon fruit nondestructively. Dragon fruit reflectance (n=117) were measured nondestructively by FT NIR spectrometer, and after that TSS and hardness of dragon fruit were measured destructively with digital refractometer and rheometer, respectively. Six spectra pretreatments and some number of PLS factors were applied to analyze the chemometrics effect to NIRS accuracy in predicting TSS and hardness of dragon fruit. The values of reflectance spectra of dragon fruit are high in 1000-1400 nm and after that decrease gradually. On the contrary, the values of absorption spectra are low in 1000-1400 nm, but in 1400-2500 nm the values are high with high variation. The hardness range of dragon fruit is 8.73-24.91 N and TSS of 9.20-17.60 brix. Reflectance spectra is better than absorption spectra in predicting TSS and hardness of dragon fruit. Only detrending spectra pretreatment increased the accuracy of NIR spectroscopy in predicting TSS of dragon fruit. However, there is no spectral pretreatment that can improve accuracy in predicting dragon fruit hardness. Increasing the number of PLS factors may increase the accuracy for a while but after that it decreases. The best chemometrics to determine TSS of dragon fruit is using detrending pretreatment of reflectance spectra and 16 PLS factors (r=0.93, SEP=0.66 brix, RPD=2.09). For hardness, the best chemometrics is using original reflectance spectra and 17 PLS factors (r=0.89, SEP=1.75 N, RPD=2.02). NIR Spectroscopy and chemometrics can be used to predict TSS and hardness of dragon fruit accurately and nondestructively.

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Section: Introductionmentioning

confidence: 99%

Effect of chemometrics to accuracy of NIR spectroscopy in predicting total soluble solid and hardness of dragon fruit

Budiastra¹,

Dzikri²

2022

IOP Conf. Ser.: Earth Environ. Sci.

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“…VIS/NIR spectroscopy is suitable for laboratory analysis. [24,25] E-tongue is fast, simple, and reliable, but it is limited in sensitivity. [23,26] The detecting objective of EN technique is the gases emitted by the samples.…”

Section: Introductionmentioning

confidence: 99%

Chinese Quince (Cydonia oblonga Miller) Freshness Rapid Determination Method Using Surface Acoustic Wave Resonator Combined with Electronic Nose

Liu

Gao

Zhang

et al. 2016

International Journal of Food Properties

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In this article, Chinese quince (Cydonia oblonga Miller) freshness determination method was investigated using surface acoustic wave resonator, electronic nose, and surface acoustic wave resonator combined with electronic nose. Human sensory evaluation and weight loss index were examined as freshness reference. Results indicated that quince freshness decreased during storage procedure. Surface acoustic wave resonator output frequency and electronic nose measurement data stochastic resonance signal-to-noise ratio Eigen values characterized quince quality under different storage time. Freshness predictive models were developed using surface acoustic wave resonator frequency, electronic nose signal-to-noise ratio spectrum Eigen values, and their hybrid model. Validating experiments results demonstrated that the hybrid predictive model presented higher predicting accuracy (R 2 = 0.987) than other two models. The proposed method is promising in fruit quality rapid analysis.

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“…Therefore, a rapid and more efficient method is required to cope with the problem, one of which is the near infrared spectroscopy (NIRS) method. NIR spectroscopy has been successfully applied to determine chemical content of agricultural products such as catechin in gambir powder [4], fat and free fatty acid in Jatropha [5], major chemical content of dragon fruit peel flour [6], total soluble solid (TSS) of mango [7], hardness of mangosteen [8], TSS of papaya [9], trigonelline, chlorogenic acid, caffeine content of coffees [10] [11], TSS and firmness of persimmon [12], TSS of dragon fruit [13], classification of coffee origin [14] and patchouli oil [15] as well. NIRS method has also been studied for determining the molecular composition of glucomannan yeast product (GYP) and glucomannan extracted from iles-iles or porang (Amorphophallus oncophylus) using NIRLab N-200 [16].…”

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confidence: 99%

Determination of Chemical Content of Porang Flour (Amorphophallus muelleri blume) by Near Infrared Spectroscopy

Budiastra

Noviyanti

2023

IOP Conf. Ser.: Earth Environ. Sci.

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Porang is well known with its high glucomannan content. Determination of the chemical content of porang flour is commonly carried out by chemical methods in the laboratory, which are known to take a long time and expensive. This study aims to determine the chemical content of porang flour using near infrared spectroscopy (NIRS). The reflectance of porang flour was measured using an FT NIR spectrometer at a wavelength of 1000 to 2500 nm. The chemical content (water and glucomannan content) of porang flour was determined by oven and spectrophotometry as the reference method. The reflectance was transformed to absorbance and several spectral pre-treatments such as normalisation, detrending, standard normal variate (SNV), orthogonal signal correction (OSC), and multiplicative scatter correction (MSC) with various PLS and PCR factors number were applied to obtain the best chemical content prediction of porang flour with NIRS. PLS and PCR were used for calibration of NIR spectra and chemical content of porang flour. The best calibration for determining the moisture content of porang flour was obtained using NIR spectra with normalisation pre-treatment and 8 PLS factor (r=0.92; SEC=0.15%; CV=2.13%; RPD=2.68). The best calibration for determining the glucomannan content of porang flour was NIR spectra with detrending pre-treatment at PLS factor 7 (r=0.86; SEC=0.54%; CV=0.90%; RPD=1.62). A lower accuracy was obtained for predicting water and glucomannan content using PCR calibration method. For water content, the best calibration was obtained by NIR spectra with normalisation pre-treatment and 12 PCR factors (r=0.91; SEC=0.16%; CV=2.21%; RPD=2.59). For glucomannan content, the best calibration was NIR spectra using detrending pre-treatment at 9 PCR factors (r=0.81; SEC=0.62%; CV=0.94%; RPD=1.55). This study shows that NIRS can be used to determine the chemical content of porang flour.

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Prediction of hardness development in mangosteen peel using NIR spectroscopy during low temperature storage

Cited by 4 publications

References 4 publications

Effect of chemometrics to accuracy of NIR spectroscopy in predicting total soluble solid and hardness of dragon fruit

Effect of chemometrics to accuracy of NIR spectroscopy in predicting total soluble solid and hardness of dragon fruit

Chinese Quince (Cydonia oblonga Miller) Freshness Rapid Determination Method Using Surface Acoustic Wave Resonator Combined with Electronic Nose

Determination of Chemical Content of Porang Flour (Amorphophallus muelleri blume) by Near Infrared Spectroscopy

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