Establishment of an Accurate Starch Content Analysis System for Fresh Cassava Roots Using Short-Wavelength Near Infrared Spectroscopy

Due to the rapid development of the corn-to-ethanol industry, the demand for process monitoring has led to the gradual substitution of traditional analytical techniques with fast and non-destructive methods such as near infrared spectroscopy. In this study, the feasibility of using Fourier transform–near infrared technology as an analytical tool to predict operational parameters (dry solids, starch, carbohydrate, and ethanol content) was investigated. Corn flour, liquefied mash, fermented mash, and distiller’s dried grains with solubles were selected to represent the feedstock, two intermediate products, and one primary co-product of corn-to-ethanol plants, respectively. Multivariate partial least square calibration models were developed to correlate near infrared spectra to the corresponding analytical values. The validation results indicate that near infrared models can be developed that will predict various parameters accurately (root mean square error of prediction: 0.16–1.14%, residual predictive deviation: 3.0–6.3). Measurement of starch or carbohydrate content in corn flour or distiller’s dried grains with solubles is challenging due to low accuracy of wet chemistry methods as well as sample complexity. The study demonstrated that near infrared spectroscopy, a high-throughput analytical technique, has the potential to replace the enzymatic assay.

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Comparative Study on Self-Monitoring of Blood Glucose and Non-invasive Blood Glucose Sensor Using Short-wavelength Near-infrared Spectroscopy in Glycemic Index Determination

Nippon Shokuhin Kagaku Kogaku Kaishi ◽

10.3136/nskkk.63.538 ◽

2016 ◽

Vol 63 (11) ◽

pp. 538-544

Author(s):

Akiko Momose ◽

Akifumi Ikehata ◽

Yasuhiro Uwadaira ◽

Masayo Miura

Keyword(s):

Infrared Spectroscopy ◽

Blood Glucose ◽

Comparative Study ◽

Near Infrared Spectroscopy ◽

Glycemic Index ◽

Short Wavelength ◽

Near Infrared ◽

Glucose Sensor ◽

Self Monitoring ◽

Non Invasive

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Noninvasive monitoring of bulk polymerization using short-wavelength near-infrared spectroscopy

Analytical Chemistry ◽

10.1021/ac00072a009 ◽

1993 ◽

Vol 65 (24) ◽

pp. 3581-3585 ◽

Cited By ~ 27

Author(s):

P. K. Aldridge ◽

J. J. Kelly ◽

James B. Callis ◽

D. H. Burns

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Short Wavelength ◽

Near Infrared ◽

Noninvasive Monitoring ◽

Bulk Polymerization

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Analisa Gula Kristal Putih Secara Cepat Menggunakan Near Infrared Spectroscopy

Indonesian Sugar Research Journal ◽

10.54256/isrj.v1i2.54 ◽

2021 ◽

Vol 1 (2) ◽

pp. 106-113

Author(s):

Opal Priya Wening

Keyword(s):

Content Analysis ◽

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Partial Least Square ◽

Least Square

Near infrared spectroscopy (NIRS) merupakan metode alternatif untuk menganalisa parameter sampel yang lebih cepat. Pada penelitian ini, NIRS akan digunakan sebagai penentuan kualitas gula kristal putih (GKP) dengan parameter penting seperti pol, warna, susut pengeringan, dan berat jenis butiran. Sampel gula yang digunakan berasal dari laboratorium P3GI. Instrumen NIRS menggunakan FOSS XDS rapid content analysis, kemudian model yang dibangun menggunakan metode kalibrasi partial least square (PLS). Hasil NIRS dievaluasi dengan standar: nilai korelasi R2 dan r2 yang mendekati 1, error SEC yang rendah, dan rasio RPD yang tinggi. Penelitian menghasilkan nilai untuk pol (%): R2 = 0,970, SEC = 0,023, r2 = 0,496, RPD = 1,152; warna (IU): R2 = 0,970, SEC = 12,305, r2 = 0,757, RPD = 1,529; susut pengeringan (%): R2 = 0,973, SEC = 0,004, r2 = 0,789, RPD = 1,601; dan berat jenis butiran (mm): R2 = 0,954, SEC = 0,038, r2 = 0,407, RPD = 0,997. Berdasarkan hasil evaluasi tersebut metode NIRS berpotensi sebagai analisa kualitas gula kristal putih dengan model yang dibangun tergolong sebagai pendahuluan.

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