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At-line Prediction of Gelatinized Starch and Fiber Fractions in Extruded Dry Dog Food Using Different Near-Infrared Spectroscopy Technologies

SIMPLE SUMMARY: Starch is a non-fibrous carbohydrate that represents an important percentage of pet food composition. The degree of its gelatinization, due to the cooking process, can be a useful indicator of starch digestibility in the diet. Moreover, fiber fractions are important for animals’ heal...

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Autores principales: Goi, Arianna, Manuelian, Carmen L., Righi, Federico, De Marchi, Massimo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7278468/
https://www.ncbi.nlm.nih.gov/pubmed/32429392
http://dx.doi.org/10.3390/ani10050862
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author Goi, Arianna
Manuelian, Carmen L.
Righi, Federico
De Marchi, Massimo
author_facet Goi, Arianna
Manuelian, Carmen L.
Righi, Federico
De Marchi, Massimo
author_sort Goi, Arianna
collection PubMed
description SIMPLE SUMMARY: Starch is a non-fibrous carbohydrate that represents an important percentage of pet food composition. The degree of its gelatinization, due to the cooking process, can be a useful indicator of starch digestibility in the diet. Moreover, fiber fractions are important for animals’ health and nutritional status, so pet food industry is interested in the development of an easy and cost-effective method to measure these parameters. Results of this study revealed the applicability of visible/near-infrared spectroscopy to predict total and gelatinized starch, neutral detergent fiber, acid detergent fiber, and acid detergent lignin in pet food. On the other hand, near-infrared transmittance technology showed a scarce accuracy. The developed prediction models for total and gelatinized starch and fiber fractions using visible/near-infrared spectroscopy could be applied during the manufacturing process to perform quality controls. ABSTRACT: This study aimed to assess the feasibility of visible/near-infrared reflectance (Vis-NIR) and near-infrared transmittance (NIT) spectroscopy to predict total and gelatinized starch and fiber fractions in extruded dry dog food. Reference laboratory analyses were performed on 81 samples, and the spectrum of each ground sample was obtained through Vis-NIR and NIT spectrometers. Prediction equations for each instrument were developed by modified partial least squares regressions and validated by cross- (CrV) and external validation (ExV) procedures. All studied traits were better predicted by Vis-NIR than NIT spectroscopy. With Vis-NIR, excellent prediction models were obtained for total starch (residual predictive deviation; RPD(CrV) = 6.33; RPD(ExV) = 4.43), gelatinized starch (RPD(CrV) = 4.62; RPD(ExV) = 4.36), neutral detergent fiber (NDF; RPD(CrV) = 3.93; RPD(ExV) = 4.31), and acid detergent fiber (ADF; RPD(CrV) = 5.80; RPD(ExV) = 5.67). With NIT, RPD(CrV) ranged from 1.75 (ADF) to 2.61 (acid detergent lignin, ADL) and RPD(ExV) from 1.71 (ADL) to 2.16 (total starch). In conclusion, results of the present study demonstrated the feasibility of at-line Vis-NIR spectroscopy in predicting total and gelatinized starch, NDF, and ADF, with lower accuracy for ADL, whereas results do not support the applicability of NIT spectroscopy to predict those traits.
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spelling pubmed-72784682020-06-12 At-line Prediction of Gelatinized Starch and Fiber Fractions in Extruded Dry Dog Food Using Different Near-Infrared Spectroscopy Technologies Goi, Arianna Manuelian, Carmen L. Righi, Federico De Marchi, Massimo Animals (Basel) Article SIMPLE SUMMARY: Starch is a non-fibrous carbohydrate that represents an important percentage of pet food composition. The degree of its gelatinization, due to the cooking process, can be a useful indicator of starch digestibility in the diet. Moreover, fiber fractions are important for animals’ health and nutritional status, so pet food industry is interested in the development of an easy and cost-effective method to measure these parameters. Results of this study revealed the applicability of visible/near-infrared spectroscopy to predict total and gelatinized starch, neutral detergent fiber, acid detergent fiber, and acid detergent lignin in pet food. On the other hand, near-infrared transmittance technology showed a scarce accuracy. The developed prediction models for total and gelatinized starch and fiber fractions using visible/near-infrared spectroscopy could be applied during the manufacturing process to perform quality controls. ABSTRACT: This study aimed to assess the feasibility of visible/near-infrared reflectance (Vis-NIR) and near-infrared transmittance (NIT) spectroscopy to predict total and gelatinized starch and fiber fractions in extruded dry dog food. Reference laboratory analyses were performed on 81 samples, and the spectrum of each ground sample was obtained through Vis-NIR and NIT spectrometers. Prediction equations for each instrument were developed by modified partial least squares regressions and validated by cross- (CrV) and external validation (ExV) procedures. All studied traits were better predicted by Vis-NIR than NIT spectroscopy. With Vis-NIR, excellent prediction models were obtained for total starch (residual predictive deviation; RPD(CrV) = 6.33; RPD(ExV) = 4.43), gelatinized starch (RPD(CrV) = 4.62; RPD(ExV) = 4.36), neutral detergent fiber (NDF; RPD(CrV) = 3.93; RPD(ExV) = 4.31), and acid detergent fiber (ADF; RPD(CrV) = 5.80; RPD(ExV) = 5.67). With NIT, RPD(CrV) ranged from 1.75 (ADF) to 2.61 (acid detergent lignin, ADL) and RPD(ExV) from 1.71 (ADL) to 2.16 (total starch). In conclusion, results of the present study demonstrated the feasibility of at-line Vis-NIR spectroscopy in predicting total and gelatinized starch, NDF, and ADF, with lower accuracy for ADL, whereas results do not support the applicability of NIT spectroscopy to predict those traits. MDPI 2020-05-16 /pmc/articles/PMC7278468/ /pubmed/32429392 http://dx.doi.org/10.3390/ani10050862 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Goi, Arianna
Manuelian, Carmen L.
Righi, Federico
De Marchi, Massimo
At-line Prediction of Gelatinized Starch and Fiber Fractions in Extruded Dry Dog Food Using Different Near-Infrared Spectroscopy Technologies
title At-line Prediction of Gelatinized Starch and Fiber Fractions in Extruded Dry Dog Food Using Different Near-Infrared Spectroscopy Technologies
title_full At-line Prediction of Gelatinized Starch and Fiber Fractions in Extruded Dry Dog Food Using Different Near-Infrared Spectroscopy Technologies
title_fullStr At-line Prediction of Gelatinized Starch and Fiber Fractions in Extruded Dry Dog Food Using Different Near-Infrared Spectroscopy Technologies
title_full_unstemmed At-line Prediction of Gelatinized Starch and Fiber Fractions in Extruded Dry Dog Food Using Different Near-Infrared Spectroscopy Technologies
title_short At-line Prediction of Gelatinized Starch and Fiber Fractions in Extruded Dry Dog Food Using Different Near-Infrared Spectroscopy Technologies
title_sort at-line prediction of gelatinized starch and fiber fractions in extruded dry dog food using different near-infrared spectroscopy technologies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7278468/
https://www.ncbi.nlm.nih.gov/pubmed/32429392
http://dx.doi.org/10.3390/ani10050862
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