Measurement of quality parameters of sugar beet juices using near-infrared spectroscopy and chemometrics

Bahrami, Mohammad Erfan; Honarvar, Masoud; Ansari, Keivan; Jamshidi, Bahareh

doi:10.1016/j.jfoodeng.2019.109775

Cited by 17 publications

(9 citation statements)

References 34 publications

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“…The main functional groups in the NIR spectrum were H‐containing groups, including C–H (methyl, methylene, methoxyl, carboxyl, aryl, etc. ), O–H, S–H, and N–H (primary amine, secondary amine, tertiary amine, and amine salt) (Bahrami, Honarvar, Ansari, & Jamshidi, 2020). A study found that the most prominent absorption bands in the NIR region were related to C–H and O–H bonds, and these bonds were common in water, sucrose, and cellulose in the samples (Cevoli et al., 2013).…”

Section: Resultsmentioning

confidence: 99%

Determination of sugar content in Lingwu jujube by NIR–hyperspectral imaging

Yang

Liu

et al. 2021

Journal of Food Science

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Near infrared hyperspectral imaging (NIR-HSI) with a spectral range of 900 to 1700 nm was for the first time used to predict the changes of sugar content in Lingwu jujube during storage. Monte Carlo method was adopted to detect outliers, and multiple scattering correction (MSC), standard normal variate transformation (SNV), and Baseline were used to optimize modeling. Competitive adaptive reweighted sampling (CARS), interval variable iterative space shrinkage approach (iVISSA), and interval random frog (IRF) were used to select optimal wavelengths. In addition, partial least square regression (PLSR) and support vector machine (SVM) modeling based on optimal wavelengths were compared. The results showed that 30, 30, and 24 wavelengths were selected by CARS; 106, 87, and 112 feature wavelengths were selected by iVISSA; and 96, 71, and 83 optimal wavelengths were selected by IRF for sucrose, fructose, and glucose, respectively. The CARS-PLSR models provided the best results for fructose and glucose, and iVISSA-SVM model was better for sucrose. The results indicated that NIR-HSI model may be used as a rapid and nondestructive method for the determination of sugar content in jujubes.

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Section: Resultsmentioning

confidence: 99%

Determination of sugar content in Lingwu jujube by NIR–hyperspectral imaging

Yang

Liu

et al. 2021

Journal of Food Science

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“…In accordance with the manufacturer's instruction for beet measurements, 2.50 Jo was subtracted from the measurements obtained (Bert et al, 1980). This methods for determine sucrose percentage is wildly used (Bahrami et al, 2020). The data was statistically analyzed by using the Statistical Analysis System (SAS Institute, 2005), the data was statistically analyzed for all of the studied traits.…”

Section: Methodsmentioning

confidence: 99%

Response of Some Sugar Beet Varieties to Different Sowing Dates Under Two Seasonal Conditions in Khabat

Mohammed

Hamed

2023

Polytechnic j.

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The research was conducted in the field of Khabat Technical Institute / Erbil Polytechnic University during winter season of 2019-2020 and summer season of 2020. It shows the effect of planting date, varieties on growth and yield component of sugar beet under two different seasonal conditions. A factorial experimental design was applied in randomized complete block design with three replication; the first factor represents three planting dates (1st October, 16th October and 31th October, 2019) in winter and (1st March, 16th March and 31th March, 2020) in summer season, the second factor was three varieties of sugar beet (Germany, Turkish and Iranian), had been applied in both seasons. The combined effect of planting in 1st October and the Turkish variety produced the highest value of all study traits; No. of leaf.plant-1, leaf area (cm2), leaf area index (LAI), root length cm, root diameter cm, root weight kg.plant-1, root yield t.ha-1, sugar % and sugar yield t.ha-1in winter season, but the Germany variety surpassed in length of root (cm) in summer season. The interaction between planting date from 1st October with Turkish variety recorded the highest value of all study traits, in winter season achieved the lowest value in number of leaf.plant-1, root length cm, root diameter cm, root weight kg.plant-1, root yield t.ha-1, sugar% and sugar yield, were recorded from the interaction between planting in 31th March and Iranian variety in summer season. On the other hand, the interaction treatment 31th March with Turkish variety recorded the lowest value in leaf area and leaf area index.

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“…Du et al [14] were used Norris derivative as a pre-processing method to detect adulteration of different oils in camellia oil. Also, meaning average filter was used as a pre-processing method in Bahrami et al and Udompetaikul et al [33,47].…”

Section: Savitzky-golay Filtermentioning

confidence: 99%

A Review of Data Analysis Techniques Used in Near-Infrared Spectroscopy

Cataltas¹,

Tutuncu²

2021

European Journal of Science and Technology

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Although the analysis of the structure of objects and the components that makeup them has been done for decades, it is one of today's research topics to do this analysis quickly and without damaging the sample. Near-infrared spectroscopy is used in many areas due to its non-contact measurement, fast analysis, and high accuracy features. Near-infrared spectroscopy is used in the classification or quality analysis of products, especially in the agriculture and food sector, due to the chemical bonds interacting in this region. The most critical part of achieving a successful result in near-infrared spectroscopy is pre-processing and analyzing the spectral data using the correct method. In this review, we perform a survey of recent studies that use near-infrared spectroscopy in food production and agriculture. Since there are many studies in this field in the literature, the survey is limited to cover works in the last five years. The review's main question is the pre-processing and data analysis methods used in these studies and the main features of these methods. Among the examined studies, the most frequently used pre-processing method was standard normal variate, and the most frequently used analysis method was partial least squares regression. In addition, the software tools and the spectrum range were also examined within the scope of the study.

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Measurement of quality parameters of sugar beet juices using near-infrared spectroscopy and chemometrics

Cited by 17 publications

References 34 publications

Determination of sugar content in Lingwu jujube by NIR–hyperspectral imaging

Determination of sugar content in Lingwu jujube by NIR–hyperspectral imaging

Response of Some Sugar Beet Varieties to Different Sowing Dates Under Two Seasonal Conditions in Khabat

A Review of Data Analysis Techniques Used in Near-Infrared Spectroscopy

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