Bo Zhang

Background: The precise volatile compounds accountable for the characteristic scent of the wheat aroma were presently unidentified. Given the prominent manifestation of “wheat aroma” in wheat cultivated in saline-alkali (SA) soil, five wheat varieties planted in saline-alkali soil and control soil (low saline-alkali soil) to create “rich-aroma” and “bland-aroma” samples, respectively. Methods: The volatile profiles of these two groups of samples were analyzed using headspace solid-phase microextraction coupled with gas chromatographyed with gas chromathes-SPME-GC-MS), and differential characteristic volatile compounds between “rich-aroma” and “bland-aroma” samples were identified by combining paired t -tests, relative odor activity values (ROAVs), and molecular docking analysis. Results: A total of 75 volatile compounds were identified using HS-SPME-GC-MS. Paired t -test result revealed that a significant increase ( p < 0.05) in the peak areas and relative contents of limonene (>109.74% increase), β-pinene (> 474.09% increase) contrasted with reduced butanoic acid (>38.71% reduction) and (E,E)-3,5-octadien-2-one (>16.05% reduction) in saline-alkali soil-cultivated wheats. Molecular docking demonstrated high binding energies (<-4.25 kcal/mol) of limonene, β-pinene, and (E,E)-3,5-octadien-2-one to olfactory receptors, corroborated by relative odor activity values (ROAVs. > 1). Conclusion: Limonene, β-pinene and (E,E)-3,5-octadien-2-one are identified as possible saline-alkali soil-induced wheat aroma biomarkers, and offer theoretical insights for verificating wheat aroma. Identifying potential characteristic biomarkers in wheat under saline-alkali stress provides important theoretical insights for improving the flavor characteristics of wheat.

In recent decades, frozen dough has become an attractive means of preserving and offering the convenience of fresh‐tasting foods while retaining their nutritional benefits. However, the frozen dough industry still faces significant challenges related to processing, freezing, and storage that affect the dough's quality and stability during thawing. Understanding the complex interactions between proteins (gluten, glutenin, gliadin, and glutenin macropolymers), starch dynamics (gelatinization and retrogradation), and water distribution—particularly how ice crystals interact with the gluten–starch matrix—is essential for improving frozen dough quality. This review also delves into the rheological properties resulting from the interplay of these components, emphasizing their collective impact on dough texture and stability. Additionally, it explores various freezing mechanisms and innovative strategies to reduce freeze damage, as well as practical challenges in translating theoretical insights into industrial applications. Finally, it proposes future strategies for improving the shelf life and quality of frozen dough by optimizing freezing methods and water distribution. Through a comprehensive synthesis of current literature, this review underscores the critical importance of gluten–starch–water interactions in frozen dough and highlights promising strategies for enhancing product performance and quality.

The aim of this study was to compare the role of protein quantity and aggregate stretching degree in predicting dough stability and extensibility using the regression analysis, and to explore a more effective way of conducting the prediction. Flours from 28 milling streams of the wheat cultivar Shiluan 02-1 were collected as experimental material. Using the value of (ash content/L*) (L*-lightness), we sorted the milling streams flour from the inner layer to the outer layer of wheat kernel, which was divided into early reduction, later reduction, and break flours. Three regression models, quantity-based, stretching-degree-based and (quantity × stretching-degree)-based model for predicting dough stability and extensibility were evaluated in each category of milling streams through their coefficient of determination (R 2). Certain patterns were observed in physicochemical properties of flour from different categories of milling streams. Despite those considerable changes, the quantity-based model broadly produced greater R 2 values than the stretchingdegree-based model, and the (quantity × stretching-degree)-based model could in general provide higher R 2 values than the other two models on predicting dough stability and extensibility. The results suggest that measuring the protein quantity and aggregate stretching degree at the same time is of practical improvement in dough rheology evaluation, compared to focusing on either factor alone.