Study of Galactooligosaccharides production from dairy waste by FTIR and chemometrics as Process Analytical Technology

Rico-Rodriguez, Fabián; Strani, Lorenzo; Grassi, Silvia; Lancheros, Ruth; Serrato, Juan Carlos Fernández; Casiraghi, E.

doi:10.1016/j.fbp.2020.12.009

Cited by 14 publications

(4 citation statements)

References 30 publications

(43 reference statements)

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“…The spectrum obtained for the Vivinal ® GOS syrup, which corresponds to a mixture of β-GOS, Lac, Glu, and Gal, was also similar to those of the extracts. The bands shared between the samples and the Vivinal ® GOS syrup included the broad one at 3500–3000 cm −1 (OH stretching) and those in the fingerprint region (1200–800 cm −1 ), arising from the C-O-C glycosidic linkage, the COH bending, and the C-C stretching vibrational modes, that collectively provide a characteristic pattern for each carbohydrate [ 26 , 27 ]. The differences observed between the Vivinal ® GOS syrup and the extracts in this region may be related to the fact that the former does not contain polysaccharides.…”

Section: Resultsmentioning

confidence: 99%

Chickpeas’ and Lentils’ Soaking and Cooking Wastewaters Repurposed for Growing Lactic Acid Bacteria

Martins

Carboni

Hugo

et al. 2023

Foods

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Legumes processing involves large amounts of water to remove anti-nutrients, reduce uncomfortable effects, and improve organoleptic characteristics. This procedure generates waste and high levels of environmental pollution. This work aims to evaluate the galacto-oligosaccharide (GOS) and general carbohydrate composition of legume wastewaters and assess their potential for growing lactic acid bacteria. Legume wastewater extracts were produced by soaking and/or cooking the dry seeds of chickpeas and lentils in distilled water and analysed using high-performance liquid chromatography with refractive index detection. GOS were present in all extracts, which was also confirmed by Fourier transform infrared spectroscopy (FTIR). C-BW extract, produced by cooking chickpeas without soaking, provided the highest extraction yield of 3% (g/100 g dry seeds). Lentil extracts were the richest source of GOS with degree of polymerization ≥ 5 (0.4%). Lactiplantibacillus plantarum CIDCA 83114 was able to grow in de Man, Rogosa, and Sharpe (MRS) broth prepared by replacing the glucose naturally present in the medium with chickpeas’ and lentils’ extracts. Bacteria were able to consume the mono and disaccharides present in the media with extracts, as demonstrated by HPLC and FTIR. These results provide support for the revalorisation of chickpeas’ and lentils’ wastewater, being also a sustainable way to purify GOS by removing mono and disaccharides from the mixtures.

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Section: Resultsmentioning

confidence: 99%

Chickpeas’ and Lentils’ Soaking and Cooking Wastewaters Repurposed for Growing Lactic Acid Bacteria

Martins

Carboni

Hugo

et al. 2023

Foods

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“…Zhong [49] 2020-2023 Prediction of key process parameters Bai [50] 2023 Fault monitoring of chemical process equipment Ye [51], Zeng [52], Gatlan [53], Rico-Rodriguez [54] 2020-2022 Emission and utilization of pollutants Zhu [55], Rau [56], Zang [57] 2021-2023 Prediction of energy efficiency Chen [58], Furrer [59], Han [60] 2020-2023 Prediction of chemical production Liu [61], Liu [62], Chai [63], Mamudu [64], Tariq [65],…”

Section: Review Of Dynamic Problems In Complex Industrial Processesmentioning

confidence: 99%

Dynamic Operation Optimization of Complex Industries Based on a Data-Driven Strategy

Tian,

Zhao,

Xie

et al. 2024

Processes

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As industrial practices continue to evolve, complex process industries often exhibit characteristics such as multivariate correlation, dynamism, and nonlinearity, making traditional mechanism modeling inadequate in terms of addressing the intricacies of complex industrial problems. In recent years, with advancements in control theory and industrial practices, there has been a substantial increase in the volume of industrial data. Data-driven dynamic operation optimization techniques have emerged as effective solutions for handling complex industrial processes. By responding to dynamic environmental changes and utilizing advanced optimization algorithms, it is possible to achieve dynamic operational optimization in industrial processes, thereby reducing costs and emissions, improving efficiency, and increasing productivity. This correlates nicely with the goals set forth by conventional process operation optimization theories. Nowadays, this dynamic, data-driven strategy has shown significant potential in complex process industries characterized by multivariate correlations and nonlinear behavior. This paper approaches the subject from a data-driven perspective by establishing dynamic optimization models for complex industries and reviewing the state-of-the-art time series forecasting models to cope with changing objective functions over time. Meanwhile, aiming at the problem of concept drift in time series, this paper summarizes new concept drift detection methods and introduces model update methods to solve this challenge. In addressing the problem of solving dynamic multi-objective optimization problems, the paper reviews recent developments in dynamic change detection and response methods while summarizing commonly used as well as the latest performance measures for dynamic multi-objective optimization problems. In conclusion, a discussion of the research progress and challenges in the relevant domains is undertaken, followed by the proposal of potential directions for future research. This review will help to deeply understand the importance and application prospects of data-driven dynamic operation optimization in complex industrial fields.

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“…Moreover, if in addition to the data coming from process sensors controlling the machinery settings (such as the temperature, mixing rate, pressure, etc.) fused with NIR, it could become feasible to achieving a better understanding of processes, which could aid in designing more efficient and environmentally friendly processes [ 12 , 13 ]. However, it is still not so common in food production to have implemented systems for the data storage of retrieval process sensors.…”

Section: Introductionmentioning

confidence: 99%

A Feasibility Study towards the On-Line Quality Assessment of Pesto Sauce Production by NIR and Chemometrics

Tanzilli

D’Alessandro

Tamelli

et al. 2023

Foods

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The food industry needs tools to improve the efficiency of their production processes by minimizing waste, detecting timely potential process issues, as well as reducing the efforts and workforce devoted to laboratory analysis while, at the same time, maintaining high-quality standards of products. This can be achieved by developing on-line monitoring systems and models. The present work presents a feasibility study toward establishing the on-line monitoring of a pesto sauce production process by means of NIR spectroscopy and chemometric tools. The spectra of an intermediate product were acquired on-line and continuously by a NIR probe installed directly on the process line. Principal Component Analysis (PCA) was used both to perform an exploratory data analysis and to build Multivariate Statistical Process Control (MSPC) charts. Moreover, Partial Least Squares (PLS) regression was employed to compute real time prediction models for two different pesto quality parameters, namely, consistency and total lipids content. PCA highlighted some differences related to the origin of basil plants, the main pesto ingredient, such as plant age and supplier. MSPC charts were able to detect production stops/restarts. Finally, it was possible to obtain a rough estimation of the quality of some properties in the early production stage through PLS.

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Study of Galactooligosaccharides production from dairy waste by FTIR and chemometrics as Process Analytical Technology

Cited by 14 publications

References 30 publications

Chickpeas’ and Lentils’ Soaking and Cooking Wastewaters Repurposed for Growing Lactic Acid Bacteria

Chickpeas’ and Lentils’ Soaking and Cooking Wastewaters Repurposed for Growing Lactic Acid Bacteria

Dynamic Operation Optimization of Complex Industries Based on a Data-Driven Strategy

A Feasibility Study towards the On-Line Quality Assessment of Pesto Sauce Production by NIR and Chemometrics

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