Wheat Flour Milling Yield Estimation Based on Wheat Kernel Physical Properties Using Artificial Neural Networks

Sabancı, Kadir; Aydın, Nevzat; Sayaslan, Abdülvahit; Sönmez, Mesut Ersin; Aslan, Muhammet Fatih; Demir, Lutfu; Şermet, Cemal

doi:10.18201/ijisae.2020261588

Cited by 10 publications

(5 citation statements)

References 10 publications

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“…First, milling yield percentages were assessed as they are among the major milling quality features [33]. The total recovery of milling products (F + G fractions) along the micronizing and air classification processes reached values around 99%, thus ensuring a minimal loss of raw material.…”

Section: Discussionmentioning

confidence: 99%

Qualitative Characterization of Unrefined Durum Wheat Air-Classified Fractions

Cammerata

Laddomada

Milano

et al. 2021

Foods

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Durum wheat milling is a key process step to improve the quality and safety of final products. The aim of this study was to characterize three bran-enriched milling fractions (i.e., F250, G230 and G250), obtained from three durum wheat grain samples, by using an innovative micronization and air-classification technology. Milling fractions were characterized for main standard quality parameters and for alveographic properties, starch composition and content, phenolic acids, antioxidant activity and ATIs. Results showed that yield recovery, ash content and particle size distributions were influenced either by the operating conditions (230 or 250) or by the grain samples. While total starch content was lower in the micronized sample and air-classified fractions, the P/L ratio increased in air-classified fractions as compared to semolina. Six main individual phenolic acids were identified through HPLC-DAD analysis (i.e., ferulic acid, vanillic acid, p-coumaric acid, sinapic acid, syringic and p-hydroxybenzoic acids). Compared to semolina, higher contents of all individual phenolic components were found in all bran-enriched fractions. The highest rise of TPAs occurred in the F250 fraction, which was maintained in the derived pasta. Moreover, bran-enriched fractions showed significant reductions of ATIs content versus semolina. Overall, our data suggest the potential health benefits of F250, G230 and G250 and support their use to make durum-based foods.

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Section: Discussionmentioning

confidence: 99%

Qualitative Characterization of Unrefined Durum Wheat Air-Classified Fractions

Cammerata

Laddomada

Milano

et al. 2021

Foods

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“…The flour yield is one of the major quality criteria in wheat milling. The flour yield at each milling stage depends on the designed diagram, the number of main technological equipment (rollers, sifters and purifiers) and grinding modes [22].…”

Section: Results and Its Discussionmentioning

confidence: 99%

Formation of Water Absorption Capacity of Flour on Mills of Different Productivity

Zhygunov

Sots

Zhyhunova

et al. 2023

GPMF

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This article presents the results of a study of the quality indicators of flour streams, which affect the formation of the water absorption capacity of the final flour. The studies were carried out on five mills with a productivity of 60 to 300 tons per 24 hours. With the help of an original technique for removing the quantitative balance of the milling process, the yield of each individual flour stream and the yield of the final flour were determined, which depended on the productivity of the mill and varied from 75.9-76.1% – for mills with low productivity to 79.0-80.6% – for mills with productivity above 150 tones per 24 hours. Significant changes in the quality indicators of flour streams have been established. During milling at the mill plant with productivity of 150 t / 24 h ash content increased from 0.39% to 2.21%, protein content – from 11.0% to 17.4%, starch damage – from 17.6 UCD to 32.5 UCD. As result the water absorption capacity increases during the milling process from 54.0 to 69.6%. The variation in ash content, protein content, starch damage and other properties of the mill streams are due to the anatomical parts they come from, as result it influence the quality of the final flour. A simple correlation analysis carried out made it possible to evaluate the effect of ash content, protein content, and damaged starch content on the evolution of water absorption capacity. The variations of starch damage and ash content in the flour streams seems to be the principal factor of the increase in water absorption variation, while protein content has the least influence. Despite fluctuations in flour quality indicators on individual systems, it was found that strongly determines the overall quality of the final flour is the mill stream flour yield. That’s why optimization of grinding and sieving modes of systems (B1, B2, C1, C2, B3, Siz1) which have flour streams with the highest yield and the greatest impact on the grinding process is a fundamental step in achieving the set values for the final flour quality indicators. Knowledge and understanding of the patterns of change on individual systems of values of flour yield and their quality indicators that affect water absorption capacity will allow to more effectively manage the water absorption capacity. This will make it possible to optimize the properties of the dough according to the requirements of specific technological lines and to regulate the quality of the finished product at bakery and confectionery enterprises.

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“…Despite the advances in deep learning models in terms of performance (Goodfellow et al ., 2016) and their use in the field of wheat processing (Sabanci et al ., 2020; Assadzadeh et al ., 2022), models such as artificial neural network (ANN) are still difficult to interpret and require large amounts of data to be trained and to achieve good performance.…”

Section: Methodsmentioning

confidence: 99%

A decision support tool for the first stage of the tempering process of organic wheat grains in a mill

Parrenin

Danjou

Agard

et al. 2023

Int J of Food Sci Tech

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SummaryWheat tempering conditions grains before a milling process begins. Process adjustments must be made to reach a desired level of flour quality and yield, depending on multiple factors. This article aims to develop a decision support tool to help operators adjust the first‐stage tempering parameters. It is based on a regression model that predicts an increase in organic wheat moisture content according to the properties of the wheat (initial wheat moisture content, wheat protein content and wheat temperature), process parameters (targeted wheat moisture content, wheat flow rate, water flow rate, wheat quantity and resting time) and tempering conditions (water quantity, average day temperature and average day humidity). The increase in wheat moisture achieved during the first tempering stage varies between 0% and 5%. Five regression models were compared: OLS, LASSO, RIDGE, ElasticNet and XGBoost. The models have been developed and tested from a case study at an organic wheat mill. The results indicate that the LASSO model outperformed others, with an average prediction error of 0.428%. The model showed the importance of humidity and temperature factors during the tempering process. The flow of water and wheat were the most influential parameters for an increase in wheat moisture content.

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Wheat Flour Milling Yield Estimation Based on Wheat Kernel Physical Properties Using Artificial Neural Networks

Cited by 10 publications

References 10 publications

Qualitative Characterization of Unrefined Durum Wheat Air-Classified Fractions

Qualitative Characterization of Unrefined Durum Wheat Air-Classified Fractions

Formation of Water Absorption Capacity of Flour on Mills of Different Productivity

A decision support tool for the first stage of the tempering process of organic wheat grains in a mill

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