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<p>This study presents a thorough investigation into identifying sugar beet pulp storage conditions by leveraging chemical composition analysis and infrared spectroscopy in tandem with advanced chemometric tools. Analysis of Neutral Detergent Fiber (NDF), Acid Detergent Fiber (ADF), Acid Detergent Lignin (ADL), Cellulose, and Hemicellulose across storage categories (T0, T3, and T6) revealed significant variations, particularly in ADF, ADL, Cellulose, and Hemicellulose contents. Concurrently, infrared spectroscopy provided detailed insights into the structural composition of sugar beet pulp, aiding in the differentiation of compositional nuances among samples. Employing Principal Component Analysis (PCA) highlighted distinct discrimination between immediately stored samples (T0) and those stored for longer durations (T3 and T6), with notable spectral alterations over time. Further, Partial Least Squares Discriminant Analysis (PLS-DA) demonstrated exceptional classification accuracy, effectively distinguishing samples based on storage conditions. The combined approach of chemical composition analysis and infrared spectroscopy, with PLS-DA exhibiting superior performance, underscores its efficacy as the method of choice for robust classification of sugar beet pulp storage conditions. This integrated methodology offers a comprehensive framework for quality assessment and monitoring of sugar beet pulp throughout the storage process, facilitating informed decision-making in industrial applications.</p>

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Identification of sugar beet pulp storage conditions: integrating fibrous fractions analysis and infrared spectroscopy with chemometric tools

  • 期刊论文

  • 发表日期：

    2025年4月4日

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  • Lamiae Alami,
  • Manar Otmani,
  • Abdennacer El Mrabet,
  • Abdelkhalek Oussama,
  • Souad Salmaoui,
  • Mohamed Mbarki,
  • Aimen El Orche

摘要

This study presents a thorough investigation into identifying sugar beet pulp storage conditions by leveraging chemical composition analysis and infrared spectroscopy in tandem with advanced chemometric tools. Analysis of Neutral Detergent Fiber (NDF), Acid Detergent Fiber (ADF), Acid Detergent Lignin (ADL), Cellulose, and Hemicellulose across storage categories (T0, T3, and T6) revealed significant variations, particularly in ADF, ADL, Cellulose, and Hemicellulose contents. Concurrently, infrared spectroscopy provided detailed insights into the structural composition of sugar beet pulp, aiding in the differentiation of compositional nuances among samples. Employing Principal Component Analysis (PCA) highlighted distinct discrimination between immediately stored samples (T0) and those stored for longer durations (T3 and T6), with notable spectral alterations over time. Further, Partial Least Squares Discriminant Analysis (PLS-DA) demonstrated exceptional classification accuracy, effectively distinguishing samples based on storage conditions. The combined approach of chemical composition analysis and infrared spectroscopy, with PLS-DA exhibiting superior performance, underscores its efficacy as the method of choice for robust classification of sugar beet pulp storage conditions. This integrated methodology offers a comprehensive framework for quality assessment and monitoring of sugar beet pulp throughout the storage process, facilitating informed decision-making in industrial applications.