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      Quality Traits of Sourdough Bread Obtained by Novel Digital Technologies and Machine Learning Modelling

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      Fermentation
      MDPI AG

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          Abstract

          Sourdough bread (SB) has increased popularity due to health benefits and higher interest in artisan breadmaking due to social isolation during the COVID-19 pandemic. However, quality traits and consumer assessment are still limited to complex laboratory analysis and sensory trials. In this research, new and emerging digital technologies were tested to assess quality traits of SB made from six different flour sources. The results showed that machine learning (ML) models developed to classify the type of wheat used for flours (targets) from near-infrared (NIR) spectroscopy data (Model 1) and a low-cost electronic nose (Model 2) as inputs rendered highly accurate and precise models (96.3% and 99.4%, respectively). Furthermore, ML regression models based on the same inputs for NIR (Model 3) and e-nose (Model 4) were developed to automatically assess 16 volatile aromatic compounds (targets) using GC-MS as ground-truth. To reiterate, models with high accuracy and performance were obtained with correlation (R), determination coefficients (R2), and slope (b) of R = 0.97; R2 = 0.94 and b = 0.99 for Model 3 and R = 0.99; R2 = 0.99 and b = 0.99 for Model 4. The development of low-cost instrumentation and sensors could make possible the accessibility of hardware and software to the industry and artisan breadmakers to assess quality traits and consistency of SB.

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          Most cited references52

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          Sourdough volatile compounds and their contribution to bread: A review

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            Lifestyles of sourdough lactobacilli – Do they matter for microbial ecology and bread quality?

            Sourdough is used in production of (steamed) bread as leavening agent (type I sourdoughs) or as baking improver to enhance flavour, texture, and shelf life of bread (type II sourdoughs). The long-term propagation of sourdoughs eliminates dispersal limitation and consistently leads to sourdough microbiota that are composed of host adapted lactobacilli. In contrast, community assembly in spontaneous cereal fermentations is limited by dispersal and nomadic or environmental lactic acid bacteria are the first colonizers of these sourdoughs. Propagation of sourdoughs for use as sole leavening agent (type I sourdoughs) dictates fermentation conditions that select for rapid growth. Type I wheat- and rye sourdoughs are consistently populated by insect-adapted lactobacilli, particularly Lactobacillus sanfranciscensis, which is characterized by a small genome size and a restricted metabolic potential. The diverse fermentation conditions employed in industrial or artisanal Type II sourdough fermentation processes also result in a more diverse microbiota. Nevertheless, type II sourdoughs are typically populated by vertebrate host adapted lactobacilli of the L. delbrueckii and L. reuteri groups. Metabolic traits of host-adapted lactobacilli that enhance competitiveness in intestinal ecosystems also provide technological functionality in bread making. Examples include formation of exopolysaccharides, arginine-, glutamine- and glutamate based mechanisms of acid resistance, and glycosyl hydrolases that reduce FODMAP levels in sourdough and sourdough bread. In conclusion, consideration of the lifestyle of sourdough lactobacilli facilitates the selection of competitive and functional sourdough starter cultures.
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              Development of a low-cost e-nose to assess aroma profiles: An artificial intelligence application to assess beer quality

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                Author and article information

                Contributors
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                Journal
                FERMC4
                Fermentation
                Fermentation
                MDPI AG
                2311-5637
                October 2022
                October 07 2022
                : 8
                : 10
                : 516
                Article
                10.3390/fermentation8100516
                5df86a30-3d62-480d-bcb9-7bc91baaf611
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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