Estimation of Moisture and Protein Content in Pumpkin Seeds Using NIRS with Partial Least Square (PLS) Method

- Ifmalinda, - Andasuryani, - Santosa, Iriwad Putri

Abstract


Most people do not use pumpkin seeds and only fruit for food production. Meanwhile, pumpkin seeds contain antioxidants, protein, carbohydrates, and other vitamins. Measurement of the chemical content of a material is usually carried out destructively (conventional methods) in the laboratory. This method is expensive, takes a long time to repair samples, and creates chemical waste. One method that is currently being developed to detect the chemical content of a material is the near-infrared spectroscopy (NIRS) method. Near-infrared spectroscopy (NIRS) is a non-destructive method used to quickly analyze and obtain information on a material's chemical content without using chemicals. The NIRS data calibration technique using partial least squares (PLS) is a step carried out to build a model that relates the response spectra of each sample at each wavelength to chemical concentrations known from laboratory analysis and protein content in pumpkin seeds with NIRS using PLS calibration. Spectrum data pre-treatment was carried out with GapDerivarive and Derivative Savitzky-Golay. The results showed that the best calibration model for moisture and protein content was obtained using DerivativeGap data processing with values of r = 0.92, R2 = 0.84, SEC = 0.11%, and RMSEC = 0.11%. RPD = 2.66 and using Latent Variable (LV) factor 2, while for protein content r = 0.95, R2 = 0.89, SEC = 0.71%, and RMSEC = 0.70%. RPD value = 3.33 and using Latent Variable (LV) factor 3.

Keywords


Pumpkin seeds; NIRS; PLS; protein; moisture content.

Full Text:

PDF

References


E. Puspaningdyah and D. Herawati, “Kombinasi Bilakupu (Biji Labu Kuning Dan Kunyit Putih) dalam Menurunkan Hiperkolesterolemia,†J. Sains Heal., vol. 4, no. 1, 2020.

Y. Deng, Y. Wang, G. Zhong, and X. Yu, "Simultaneous quantitative analysis of protein, carbohydrate and fat in nutritionally complete formulas of medical foods by near-infrared spectroscopy," Infrared Phys. Technol., vol. 93, pp. 124–129, 2018, doi: 10.1016/j.infrared.2018.07.027.

Rachmawati, E. Rohaeti, and M. Rafi, "Combination of near infrared spectroscopy and chemometrics for authentication of taro flour from wheat and sago flour," J. Phys. Conf. Ser., vol. 835, no. 1, 2017, doi: 10.1088/1742-6596/835/1/012011.

C. Gardana, A. Scialpi, C. Fachechi, and P. Simonetti, "Near-infrared spectroscopy and chemometrics for the routine detection of bilberry extract adulteration and quantitative determination of the anthocyanins," J. Spectrosc., vol. 2018, 2018, doi: 10.1155/2018/4751247.

H. Cen and Y. He, "Theory and application of near infrared reflectance spectroscopy in determination of food quality," Trends Food Sci. Technol., vol. 18, no. 2, pp. 72–83, 2007, doi: 10.1016/j.tifs.2006.09.003.

C. D. Iskandar, Zainuddin, and A. A. Munawar, "Rapid assessment of frozen beef quality using near infrared technology," Int. J. Sci. Technol. Res., vol. 9, no. 5, pp. 156–160, 2020.

A. A. Munawar, Kusumiyati, and D. Wahyuni, "Near infrared spectroscopic data for rapid and simultaneous prediction of quality attributes in intact mango fruits," Data Br., vol. 27, p. 104789, 2019, doi: 10.1016/j.dib.2019.104789.

Kusumiyati et al., "Non-Destructive Method for Predicting Sapodilla Fruit Quality Using Near Infrared Spectroscopy," IOP Conf. Ser. Earth Environ. Sci., vol. 334, no. 1, 2019, doi: 10.1088/1755-1315/334/1/012045.

G. Ibáñez, J. Cebolla-Cornejo, R. Martí, S. Roselló, and M. Valcárcel, “Non-destructive determination of taste-related compounds in tomato using NIR spectra,†J. Food Eng., vol. 263, no. April, pp. 237–242, 2019, doi: 10.1016/j.jfoodeng.2019.07.004.

A. Biancolillo, P. Firmani, R. Bucci, A. Magrì, and F. Marini, "Determination of insect infestation on stored rice by near infrared (NIR) spectroscopy," Microchem. J., vol. 145, no. August 2018, pp. 252–258, 2019, doi: 10.1016/j.microc.2018.10.049.

S. Bureau, D. Cozzolino, and C. J. Clark, "Contributions of Fourier-transform mid infrared (FT-MIR) spectroscopy to the study of fruit and vegetables: A review," Postharvest Biol. Technol., vol. 148, no. September 2018, pp. 1–14, 2019, doi: 10.1016/j.postharvbio.2018.10.003.

N. P. Sari and W. D. R. Putri, “Pengaruh Lama Penyimpanan dan Metode Pemasakan Terhadap Karakteristik Fisikokimia Labu Kuning (Cucurbita moschata),†J. Pangan dan Agroindustri, vol. 6, no. 1, pp. 17–27, 2018, doi: 10.21776/ub.jpa.2018.006.01.3.

J.S.H., "Association of official agricultural chemists," J. Franklin Inst., vol. 219, no. 2, p. 236, 1935, doi: 10.1016/s0016-0032(35)91522-8.

A. Biancolillo et al., "Authentication of an Italian PDO hazelnut ('Nocciola Romana') by NIR spectroscopy," Environ. Sci. Pollut. Res., vol. 25, no. 29, pp. 28780–28786, 2018, doi: 10.1007/s11356-018-1755-2.

M. Mathian et al., "Identifying the phyllosilicate minerals of hypogene ore deposits in lateritic saprolites using the near-IR spectroscopy second derivative methodology," J. Geochemical Explor., vol. 186, pp. 298–314, 2018, doi: 10.1016/j.gexplo.2017.11.019.

A. A. Munawar, Kusumiyati, Hafidh, R. Hayati, and D. Wahyuni, "The application of near infrared technology as a rapid and non-destructive method to determine vitamin C content of intact mango fruit," INMATEH - Agric. Eng., vol. 58, no. 2, pp. 1–12, 2019, doi: 10.35633/INMATEH-58-31.

I. W. Budiastra, S. Sutrisno, S. Widyotomo, and P. C. Ayu, "Prediction of Caffeine Content in Java Preanger Coffee Beans by NIR Spectroscopy Using PLS and MLR Method," IOP Conf. Ser. Earth Environ. Sci., vol. 147, no. 1, 2018, doi: 10.1088/1755-1315/147/1/012004.

Ifmalinda, M. Makky, and F. Y. S, “Uji Non Destruktif Kandungan Kafein Biji Kopi Arabika Solok Rajo dengan Menggunakan Near Infrared Spectroscopy,†2017.

A. A. Munawar, D. von Hörsten, J. K. Wegener, E. Pawelzik, and D. Mörlein, "Rapid and non-destructive prediction of mango quality attributes using Fourier transform near infrared spectroscopy and chemometrics," Eng. Agric. Environ. Food, vol. 9, no. 3, pp. 208–215, 2016, doi: 10.1016/j.eaef.2015.12.004.

Sudarjat, Kusumiyati, Hasanuddin, and A. A. Munawar, "Rapid and non-destructive detection of insect infestations on intact mango by means of near infrared spectroscopy," IOP Conf. Ser. Earth Environ. Sci., vol. 365, no. 1, 2019, doi: 10.1088/1755-1315/365/1/012037.

Y. Ma et al., "Characteristics of groundwater pollution in a vegetable cultivation area of typical facility agriculture in a developed city," Ecol. Indic., vol. 105, no. November 2018, pp. 709–716, 2019, doi: 10.1016/j.ecolind.2018.10.056.

R. Xu et al., "Use of near-infrared spectroscopy for the rapid evaluation of soybean [Glycine max (L.) Merri.] water soluble protein content," Spectrochim. Acta - Part A Mol. Biomol. Spectrosc., vol. 224, p. 117400, 2020, doi: 10.1016/j.saa.2019.117400.

Samadi, S. Wajizah, and A. A. Munawar, "Rapid and simultaneous determination of feed nutritive values by means of near infrared spectroscopy," Trop. Anim. Sci. J., vol. 41, no. 2, pp. 121–127, 2018, doi: 10.5398/tasj.2018.41.2.121.

J. B. Jianwen Luo, Kui Ying, "Savitzky–Golay smoothing and differentiation ï¬lter.pdf," no. January, 2020.

A. A. Munawar, Y. Yunus, Devianti, and P. Satriyo, "Calibration models database of near infrared spectroscopy to predict agricultural soil fertility properties," Data Br., vol. 30, p. 105469, 2020, doi: 10.1016/j.dib.2020.105469.

X. Zhao, W. Wang, X. Ni, X. Chu, Y. F. Li, and C. Sun, "Evaluation of near-infrared hyperspectral imaging for detection of peanut and walnut powders in whole wheat flour," Appl. Sci., vol. 8, no. 7, 2018, doi: 10.3390/app8071076.

H. Chen, C. Tan, and Z. Lin, "Authenticity Detection of Black Rice by Near-Infrared Spectroscopy and Support Vector Data Description," Int. J. Anal. Chem., vol. 2018, 2018, doi: 10.1155/2018/8032831.

S. N. Athfiyah, I. W. Budiastra, Sutrisno, and Y. A. Purwanto, "Prediction of Piperine content in white pepper by NIR spectroscopy using Partial Least Square (PLS) method," IOP Conf. Ser. Earth Environ. Sci., vol. 542, no. 1, 2020, doi: 10.1088/1755-1315/542/1/012020.

J. Y. Chen, Y. Miao, S. Sato, and H. Zhang, "Near infrared spectroscopy for determination of the protein composition of rice flour," Food Sci. Technol. Res., vol. 14, no. 2, pp. 132–138, 2008, doi: 10.3136/fstr.14.132.

P. S. Sampaio, A. Soares, A. Castanho, A. S. Almeida, J. Oliveira, and C. Brites, "Optimization of rice amylose determination by NIR-spectroscopy using PLS chemometrics algorithms," Food Chem., vol. 242, no. February 2017, pp. 196–204, 2018, doi: 10.1016/j.foodchem.2017.09.058.

C. Chen, H. Li, X. Lv, J. Tang, C. Chen, and X. Zheng, "Application of near infrared spectroscopy combined with SVR algorithm in rapid detection of cAMP content in red jujube," Optik (Stuttg)., vol. 194, no. April, p. 163063, 2019, doi: 10.1016/j.ijleo.2019.163063.

C. Pasquini, "Near infrared spectroscopy: A mature analytical technique with new perspectives – A review," Anal. Chim. Acta, vol. 1026, pp. 8–36, 2018, doi: 10.1016/j.aca.2018.04.004.

A. Andasuryani, Y. A. Purwanto, I. W. Budiastra, and K. Syamsu, "Determination of Catechin Content in Gambir Powder from Dried Gambir Leaves Quickly using FT NIR PLS Model," Int. J. Adv. Sci. Eng. Inf. Technol., vol. 4, no. 5, p. 303, 2014, doi: 10.18517/ijaseit.4.5.423.

Z. Zhu, S. Chen, X. Wu, C. Xing, and J. Yuan, "Determination of soybean routine quality parameters using near-infrared spectroscopy," Food Sci. Nutr., vol. 6, no. 4, pp. 1109–1118, 2018, doi: 10.1002/fsn3.652.

Z. Genisheva, C. Quintelas, D. P. Mesquita, E. C. Ferreira, J. M. Oliveira, and A. L. Amaral, "New PLS analysis approach to wine volatile compounds characterization by near infrared spectroscopy (NIR)," Food Chem., vol. 246, no. November 2017, pp. 172–178, 2018, doi: 10.1016/j.foodchem.2017.11.015.

M. Bezara and S. Taibi, "An approach of PLS method applied to model the rice self-sufficiency of peasant households in Atsinanana Madagascar," 19th Int. Sci. Conf. “Economic Sci. Rural Dev. 2018â€. Integr. Sustain. Reg. Dev. Mark. Sustain. Consum., vol. 48, no. 48, pp. 321–327, 2018, doi: 10.22616/esrd.2018.101.




DOI: http://dx.doi.org/10.18517/ijaseit.12.4.16089

Refbacks

  • There are currently no refbacks.


Published by INSIGHT - Indonesian Society for Knowledge and Human Development