Chemometric Analysis-Based Sustainable Use of Different Current Baking Wheat Lots from Romania and Hungary

Adrian Vasile Timar, Alin Cristian Teusdea (), Cornelia Purcarea, Adrian Nicolae Vuscan (), Adriana Ramona Memete and Simona Ioana Vicas
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Adrian Vasile Timar: Department of Food Engineering, Faculty of Environmental Protection, University of Oradea, 410048 Oradea, Romania
Alin Cristian Teusdea: Department of Food Engineering, Faculty of Environmental Protection, University of Oradea, 410048 Oradea, Romania
Cornelia Purcarea: Department of Food Engineering, Faculty of Environmental Protection, University of Oradea, 410048 Oradea, Romania
Adrian Nicolae Vuscan: Department of Food Engineering, Faculty of Environmental Protection, University of Oradea, 410048 Oradea, Romania
Adriana Ramona Memete: Department of Food Engineering, Faculty of Environmental Protection, University of Oradea, 410048 Oradea, Romania
Simona Ioana Vicas: Department of Food Engineering, Faculty of Environmental Protection, University of Oradea, 410048 Oradea, Romania

Sustainability, 2023, vol. 15, issue 17, 1-16

Abstract: Wheat is the most important raw material for bakery industries. Real-time grain quality assessment could increase bakery product quality and baking efficiency. The quality assessment of wheat grains can be conducted using modern and non-invasive techniques based on near-infrared spectrophotometry (NIRS) methods for the assessment of gluten content (WetGL), protein content, Zeleny index (ZelenyIdx), grain humidity (Ur), etc. The topic covered in the study is of current interest, is a part of sustainable research, and involves aspects of food quality, one of the concerns addressed by the University of Oradea’s Department of Food Engineering. The present study was carried out in 2020 on eleven wheat lots from Romania and Hungary. Following the NIRS analyses, the results show varied quality for the Romanian and Hungarians wheat lots. The Romanian variety Crisana recorded the highest values for quality parameters, being similar to the Hungarian variety Bekes from Hajdu Bihar County. The statistical analysis was carried out using multivariate analysis (multivariate analysis of variance (MANOVA), canonical variate analysis (CVA) and hierarchical cluster analysis (HCA)), which highlighted which of the batches of wheat grains can be mixed to obtain a raw material of high quality for the bakery industry.

Keywords: wheat grains; near-infrared spectrophotometry; quality chemical analysis; multivariate analysis of variance (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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