Robustness of the near infrared spectroscopy method determined using univariate and multivariate approach

Pojić, Milica; Mastilović, Jasna; Majcen, Nineta

doi:10.1016/j.foodchem.2012.03.104

Cited by 11 publications

(7 citation statements)

References 24 publications

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“…According to NIR analysis, the amount of starch was found to vary in the maize varieties from 60.2 to 63.1%. Considering the fact that the accuracy of such analysis is ±5%, 34 NIR analysis suggests that there is no significant difference in starch content among the maize varieties. According to the results of megazyme assay, starch content varies from 54.6 to 59.3% (±3%).…”

Section: ■ Results and Discussionmentioning

confidence: 99%

Rapid and Noninvasive Typing and Assessment of Nutrient Content of Maize Kernels Using a Handheld Raman Spectrometer

2019

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To thrive as a global civilization, food production must meet the demands of our ever-growing population. There are more than a billion people on the planet suffering from malnutrition through poor quality or lack of food. Nutrient content of food can be determined by a variety of methods, which have issues such as slow analysis or sample destruction. Near-infrared (NIR) spectroscopy is a long-standing alternative to these methods. In this work, we demonstrated that Raman spectroscopy (RS), another spectroscopic method, can also be used to assess the nutrient content of maize (Zea mays), one of the most widely cultivated grains in the world. Using a handheld Raman spectrometer, we predicted the content of carbohydrates, fibers, carotenoids, and proteins in six different varieties of maize. This analysis requires only a single maize kernel and is fast (1s), portable, noninvasive, and nondestructive. Moreover, we showed that RS in combination with chemometric methods can be used for highly accurate (approximately 90%) spectroscopic typing of maize, which is important for plant breeders and farmers. Finally, we demonstrate that Raman-based approach is as accurate as NIR analysis. These findings suggest that portable Raman systems can be used on combines and grain elevators for autonomous control of grain quality.

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Section: ■ Results and Discussionmentioning

confidence: 99%

Rapid and Noninvasive Typing and Assessment of Nutrient Content of Maize Kernels Using a Handheld Raman Spectrometer

2019

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“…The obtained results indicated that the NIRS method for determination of protein content appeared to be robust for its application in wheat quality control regardless the deliberate changes in operational conditions (Table 4) (Pojić et al, 2012). Fig.…”

Section: Robustnessmentioning

confidence: 75%

“…The robustness of a method is commonly examined in an experimental design, in the intervals that slightly exceed the variation that can be expected in a routine use of the method (Vander Heyden et al, 2001). Experimental design used to determine the robustness of an applied analytical method can be based on unvariate (one-variable-at-a-time, OVAT) or multivariate approaches (multi-variate-at-atime, MVAT) Pojić et al, 2012).…”

Section: Robustnessmentioning

confidence: 99%

“…It could be noticeable that the spectral differences were very small. The largest spectral variations were observed in the spectral region around 950 nm associated with OH band for water and around 968 nm, 982 nm and 1014 nm associated with overtone bands (Infrasoft International, 2000;Pojić et al, 2012 (Pojić et al, 2012). (Pojić et al, 2012).…”

Section: Robustnessmentioning

confidence: 99%

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The Application of Near Infrared Spectroscopy in Wheat Quality Control

Pojić¹,

Mastilović²,

Majcen³

2012

Infrared Spectroscopy - Life and Biomedical Sciences

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“…Finally, near-infrared spectroscopy (NIRS) showed considerable promise in analyzing the results of drying. Modelling studies based on univariate and multivariate approaches [55] validated the NIRS approach, and subsequent works provided a model for chemometric optimization of this technique [56].…”

Section: Modelling Dryingmentioning

confidence: 98%

Modelling Processes and Products in the Cereal Chain

Carvalho

Charalambides

Đjekić

et al. 2021

Foods

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In recent years, modelling techniques have become more frequently adopted in the field of food processing, especially for cereal-based products, which are among the most consumed foods in the world. Predictive models and simulations make it possible to explore new approaches and optimize proceedings, potentially helping companies reduce costs and limit carbon emissions. Nevertheless, as the different phases of the food processing chain are highly specialized, advances in modelling are often unknown outside of a single domain, and models rarely take into account more than one step. This paper introduces the first high-level overview of modelling techniques employed in different parts of the cereal supply chain, from farming to storage, from drying to milling, from processing to consumption. This review, issued from a networking project including researchers from over 30 different countries, aims at presenting the current state of the art in each domain, showing common trends and synergies, to finally suggest promising future venues for research.

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Robustness of the near infrared spectroscopy method determined using univariate and multivariate approach

Cited by 11 publications

References 24 publications

Rapid and Noninvasive Typing and Assessment of Nutrient Content of Maize Kernels Using a Handheld Raman Spectrometer

Rapid and Noninvasive Typing and Assessment of Nutrient Content of Maize Kernels Using a Handheld Raman Spectrometer

The Application of Near Infrared Spectroscopy in Wheat Quality Control

Modelling Processes and Products in the Cereal Chain

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