A Rapid and sensitive method for the evaluation of cereal grains in bioethanol production using near infrared reflectance spectroscopy

Pohl, Ferdinand; Senn, Thomas

doi:10.1016/j.biortech.2010.10.058

Cited by 21 publications

(7 citation statements)

References 19 publications

(18 reference statements)

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“…Wort target extract of 12.5°P was set based on an extract ratio of 80% (w/w) from barley malt (Weyermann Pilsner Malz, Weyermann GmbH, Germany) and 20% (w/w) from sorghum flakes (Altdorfer Mühle GmbH, Germany). Determination of fermentable substances was performed as described by Pohl and Senn [32]. The determination of the fermentable substance in grain is defined as the sum of glucose and maltose content released in the production process and converted to ethanol by S. cerevisiae.…”

Section: Wort Productionmentioning

confidence: 99%

Barley-sorghum craft beer production with Saccharomyces cerevisiae, Torulaspora delbrueckii and Metschnikowia pulcherrima yeast strains

Einfalt

2020

Eur Food Res Technol

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The use of different yeast strains contributes to obtain insights into beer products with diverse sensory characteristics. In this study, three yeast species of different genera were selected to evaluate their fermentation performance and sensory profile for barley-sorghum beer production. Baley-sorghum wort was produced with 12.5°P and fermented with Saccharomyces cerevisiae, Torulaspora delbrueckii and Metschnikowia pulcherrima yeast strains. Differences were observed in terms of fermentation time and ability to ferment maltose. S. cerevisiae attenuated initial maltose concentration within 72 h, while M. pulcherrima and T. delbrueckii performed fermentation within 120 and 192 h, respectively. Both yeast strains simultaneously produced 11% and 23% lower ethanol concentrations, compared to S. cerevisiae with 37.9 g/L. Wort fermented with T. delbrueckii showed residual maltose concentration of 19.7 ± 4.1 g/L, resulting in significantly enhanced beer sweetness. S. cerevisiae produced significantly increased levels of higher alcohols, and obtained the highest scores for the sensory attribute body perception. Beer produced with T. delbrueckii contained significantly lower fermentative 2,3-butanediol and 2-methyl-1-butanol volatiles; this beer also showed reduced body perception. Beer conditioned with T. delbrueckii was significantly preferred over M. pulcherrima. Besides S. cerevisiae with high fermentative power, T. delbrueckii and M. pulcherrima were found to have reduced maltose fermenting abilities and provide significantly different sensory attributes to barley-sorghum beers.

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Section: Wort Productionmentioning

confidence: 99%

Barley-sorghum craft beer production with Saccharomyces cerevisiae, Torulaspora delbrueckii and Metschnikowia pulcherrima yeast strains

Einfalt

2020

Eur Food Res Technol

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“…The best preprocessing method for an application must be selected through rigorous validation of the models being developed. Preprocessing spectral data with EMSC have been shown to improve performance in certain applications (Pohl & Senn, 2011; Vongsvivut et al., 2014) while in some applications EMSC preprocessing could not improve prediction performance of calibration models (Caporaso, Whitworth, & Fisk, 2018; Penchaiya, Bobelyn, Verlinden, Nicolai, & Saeys, 2009). This may hold true when developing NIR calibrations for other sorghum traits as well and thus warrants further research in developing calibrations for assessing other traits of weathered sorghum.…”

Section: Resultsmentioning

confidence: 99%

Extended multiplicative signal correction to improve prediction accuracy of protein content in weathered sorghum grain samples

2020

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Background and objectives Sorghum grains may be subjected to weathering damage in the field as naked grains on the panicle are exposed to adverse environmental conditions during grain development or dry down before harvest. A near infrared (NIR) protein calibration model did not work as expected for weathered grains. Extended multiplicative signal correction was tested as a preprocessing method for spectra to improve the prediction accuracy of the model when weathered grain samples are evaluated. Findings NIR spectra of weathered sorghum grain samples showed marked distortions with a higher apparent absorbance at lower wavelengths in the 950–1650 nm spectral range. A partial least squares calibration developed with sound grain samples using spectra preprocessed with multiplicative signal correction (MSC) predicted protein content of validation sample set of sound grains with a root mean square error of prediction (RMSEP) = 0.67% and coefficient of determination (r2) = 0.83. However, performance of this calibration model dropped with RMSEP = 13.14% and r2 = 0.04 when used to predict proteins in weathered grain samples. Introduction of weathered grain spectra to the calibration improved predictive performance with RMSEP = 0.92% and r2 = 0.69. Application of extended multiplicative scatter correction (EMSC) to preprocess the spectra of the calibration with weathered grain samples enhanced the prediction performance with RMSEP = 0.61% and r2 = 0.85. Conclusions Inclusion of weathered grain spectra in the calibration and preprocessing spectra with EMSC markedly improved the robustness of the sorghum protein calibration. Significance and novelty Sorghum breeders using NIR spectroscopy for evaluation of protein levels in sorghum breeding lines can get the weathered grain samples also analyzed for protein levels by using this method.

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“…3 Today, NIR spectroscopy is generally accepted as a technique for industrial applications and has been successfully used for the rapid analysis of moisture, protein, and fat content in many agricultural and food products. 4 In the bioethanol industry, the application of NIR technology is mainly focused on the following areas: direct compositional characterization of the incoming grains, 5 prediction of overall ethanol yield, 1 and determination of the geographical origin of grains. 6 The possibility of using NIR spectroscopy to predict nutritional components such as dietary fiber, crude protein, lipids, and moisture has been investigated, and predictive regression models have been developed.…”

Section: Introductionmentioning

confidence: 99%

“…Conventional analytical methods for determining dry solids, ethanol, starch, and carbohydrate content in samples require stepwise chemical or enzymatic procedures that are generally labor intensive, time-consuming, expensive, and involve the destruction of the samples tested. 1 Consequently, the sample turnaround rate is low and it is usually impossible to perform real-time process adjustments based on the availability of analytical results.…”

Section: Introductionmentioning

confidence: 99%

Using near infrared spectroscopy to determine moisture and starch content of corn processing products

Chen

Delaney

Johnson

et al. 2017

Journal of Near Infrared Spectroscopy

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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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A Rapid and sensitive method for the evaluation of cereal grains in bioethanol production using near infrared reflectance spectroscopy

Cited by 21 publications

References 19 publications

Barley-sorghum craft beer production with Saccharomyces cerevisiae, Torulaspora delbrueckii and Metschnikowia pulcherrima yeast strains

Barley-sorghum craft beer production with Saccharomyces cerevisiae, Torulaspora delbrueckii and Metschnikowia pulcherrima yeast strains

Extended multiplicative signal correction to improve prediction accuracy of protein content in weathered sorghum grain samples

Using near infrared spectroscopy to determine moisture and starch content of corn processing products

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