Damaged starch and dietary fibre content in Swedish wheat flour : PLS-modelling to predict baking volume
SDmatic, SRC-CHOPIN 2 and Alveolab are used to evaluate flour, but not widely used in Sweden. This study aimed to evaluate the machines and see if they could be used to predict baking volume for bread baked on Swedish wheat flour. PLS-models were built with baking volume as the Y-variable. It was no...
| Autor principal: | |
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| Formato: | H2 |
| Lenguaje: | Inglés sueco |
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SLU/Department of Molecular Sciences
2021
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| Materias: |
| _version_ | 1855572743203848192 |
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| author | Nåbo, Edvin |
| author_browse | Nåbo, Edvin |
| author_facet | Nåbo, Edvin |
| author_sort | Nåbo, Edvin |
| collection | Epsilon Archive for Student Projects |
| description | SDmatic, SRC-CHOPIN 2 and Alveolab are used to evaluate flour, but not widely used in Sweden. This study aimed to evaluate the machines and see if they could be used to predict baking volume for bread baked on Swedish wheat flour. PLS-models were built with baking volume as the Y-variable. It was noticed that baking volume of breads made on winter wheats and spring wheats were explained by different parameters and as a result building separate PLS-models for these groups gave the best results. Damaged starch had negative impact on baking volume for spring wheats but not for bread baked on winter wheats. All PLS-models were optimised for Q2 by removal of X-variables. Variables from SDmatic, SRC-CHOPIN 2 or Alveolab were left in all PLS-models. The most promising model in this study was built on winter wheats and had a Root Mean Square Error of Prediction (RMSEP) at 75 ml, which can be compared to the average bread with a volume of 2032 ml. This model had only one parameter from these machines and it is thus unclear how useful these machines are when predicting baking volume of bread baked on Swedish wheat flour. Glucomannan was the most important parameter for this model based on Variable Importance in Projection (VIP)-scores and was positively correlated with baking volume. Baking volume was the only predicted quality parameter and future studies should analyse how these machines can predict other quality parameters, such as crumb structure, bread staling and consumer acceptability. |
| format | H2 |
| id | RepoSLU16423 |
| institution | Swedish University of Agricultural Sciences |
| language | Inglés swe |
| publishDate | 2021 |
| publishDateSort | 2021 |
| publisher | SLU/Department of Molecular Sciences |
| publisherStr | SLU/Department of Molecular Sciences |
| record_format | eprints |
| spelling | RepoSLU164232021-02-16T02:02:40Z Damaged starch and dietary fibre content in Swedish wheat flour : PLS-modelling to predict baking volume Skadad stärkelse och kostfibrer i svenskt vetemjöl : PLS-modellering för att förutse brödvolym Nåbo, Edvin damaged starch dietary fibre bread volume PLS SDmatic, SRC-CHOPIN 2 and Alveolab are used to evaluate flour, but not widely used in Sweden. This study aimed to evaluate the machines and see if they could be used to predict baking volume for bread baked on Swedish wheat flour. PLS-models were built with baking volume as the Y-variable. It was noticed that baking volume of breads made on winter wheats and spring wheats were explained by different parameters and as a result building separate PLS-models for these groups gave the best results. Damaged starch had negative impact on baking volume for spring wheats but not for bread baked on winter wheats. All PLS-models were optimised for Q2 by removal of X-variables. Variables from SDmatic, SRC-CHOPIN 2 or Alveolab were left in all PLS-models. The most promising model in this study was built on winter wheats and had a Root Mean Square Error of Prediction (RMSEP) at 75 ml, which can be compared to the average bread with a volume of 2032 ml. This model had only one parameter from these machines and it is thus unclear how useful these machines are when predicting baking volume of bread baked on Swedish wheat flour. Glucomannan was the most important parameter for this model based on Variable Importance in Projection (VIP)-scores and was positively correlated with baking volume. Baking volume was the only predicted quality parameter and future studies should analyse how these machines can predict other quality parameters, such as crumb structure, bread staling and consumer acceptability. SDmatic, SRC-CHOPIN 2 och Alveolab används ofta för att bestämma egenskaper hos vetemjöl, men inte i Sverige. I den här studien undersöktes om maskinerna kunde användas i modeller för att förutse bakvolym av bröd bakat på svenskt vetemjöl. PLS-modeller gjordes med bakvolym som Y-faktor. Olika parametrar förklarade bakvolymen för bröd bakat på vårvete och höstvete, och därför gjordes separata PLS-modeller för vårvete och höstvete. Skadad stärkelse hade en negativ inverkan på bakvolymen för bröd bakat vårvete men inte för bröd bakat på höstvete. Parametrar i PLS-modellerna togs bort för att optimera Q2. Minst en variabel från SDmatic, SRC-CHOPIN 2 eller Alveolab var kvar i alla PLS-modeller efter optimeringen. Den mest lovande modellen var byggd på höstvete och hade Root Mean Square Error of Prediction (RMSEP) på 75 ml vilket kan jämföras med den genomsnittliga bakvolymen på 2032 ml för bröd bakat på höstvete. Denna modell hade enbart en parameter från Alveolab och inga från SDmatic eller SRC-CHOPIN 2. Det är därför svårt att säga om dessa maskiner är användbara i PLS-modeller som ska förutse bakvolym av bröd bakat på svenskt vetemjöl. Glucomannan var den viktigaste parametern för denna modell baserat på Variable Importance in Projection (VIP) och var dessutom positivt korrelerat med bakvolym. Bakvolym var den enda kvalitativa parametern i den här studien. Framtida studier skulle kunna se om dessa maskiner kan användas för att förutse parametrar som strukturen av inkråmet, brödets hållbarhet och konsumentacceptans. SLU/Department of Molecular Sciences 2021 H2 eng swe https://stud.epsilon.slu.se/16423/ |
| spellingShingle | damaged starch dietary fibre bread volume PLS Nåbo, Edvin Damaged starch and dietary fibre content in Swedish wheat flour : PLS-modelling to predict baking volume |
| title | Damaged starch and dietary fibre content in Swedish wheat flour : PLS-modelling to predict baking volume |
| title_full | Damaged starch and dietary fibre content in Swedish wheat flour : PLS-modelling to predict baking volume |
| title_fullStr | Damaged starch and dietary fibre content in Swedish wheat flour : PLS-modelling to predict baking volume |
| title_full_unstemmed | Damaged starch and dietary fibre content in Swedish wheat flour : PLS-modelling to predict baking volume |
| title_short | Damaged starch and dietary fibre content in Swedish wheat flour : PLS-modelling to predict baking volume |
| title_sort | damaged starch and dietary fibre content in swedish wheat flour : pls-modelling to predict baking volume |
| topic | damaged starch dietary fibre bread volume PLS |