Aroma and quality of breads baked from old and modern wheat varieties and their prediction from genomic and flour-based metabolite profiles

Impact of Tagatose on Physicochemical, Nutritional, and In Vitro Digestive Properties of Toast Bread

It is more attractive to develop effective strategies to reduce sugar intake without compromising food quality with the rising prevalence of obesity and diabetes around the world. Due to its high cost, tagatose has not been widely adopted as a sucrose substitute in toast bread. In the present research, five types of toast containing different proportions (0%, 4%, 8%, 12%, and 16%) of tagatose with sweetness similar to that of sucrose were prepared. The effects of tagatose on microstructural, textural, physicochemical, nutritional, and sensory properties and in vitro digestion were evaluated using techniques such as Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), rheological test, textural profile assay (TPA), and gas chromatography-mass spectrometry (GC-MS) analysis. The results indicated that after the substitution of tagatose for sucrose, the water-holding capacities of the dough were increased, whereas the specific volume of toast was decreased from 4.74 to 3.01 mL/g (p < 0.05), and the acidity of toast was increased from 1.92 to 2.69°T (p < 0.05). The content of flavor substances, especially alcohols, in the toast was significantly increased by the addition of tagatose. However, the glycemic index (GI) of toast was decreased from 94.39 to 67.96 (p < 0.05). Overall, the addition of 12% or more tagatose will significantly reduce the GI of toasted bread and enrich the flavor, but it will lead to a decrease in specific volume and an increase in acidity. Tagatose is a promising alternative sweetener with low calorie.

Comprehensive review of sweetpotato flavor compounds: Opportunities for developing consumer-preferred varieties

Flavor contributes significantly to consumer preferences of cooked sweetpotato. Sugars largely drive the sweet taste, while the volatile organic compounds (VOCs), mainly classified as alcohols, aldehydes, ketones, and terpenes, provide characteristic aromas and influence the overall perception of flavor. In this paper, we review sweetpotato VOCs identified in the literature from 1980 to 2024 and discuss the efforts to understand how these compounds influence sensory perception and consumer preferences. Over 400 VOCs have been identified in cooked sweetpotato with 76 known to be aroma-active. Most of these aroma-active compounds are generated from Maillard reactions, Strecker, lipid and carotenoid degradation, or thermal release of terpenes from glycosidic bonds during cooking. Suggested mechanisms of formation of these aroma-active compounds are described. However, specific VOCs that are responsible for different aromas and flavors in cooked sweetpotatoes are yet to be fully characterized. There are significant opportunities to further identify the key predictors of aroma and flavor attributes in sweetpotato, which can be used to enhance the quality of existing varieties and develop new ones using a wide range of genetic tools. This review summarizes 44 years of research aimed at identifying key aroma compounds in cooked sweetpotato and provides a roadmap for future studies to guide breeders in developing high-quality, consumer-preferred varieties.

Impact of conventional and emerging processing methods on alternative breads- a comprehensive review and meta-analysis

An increasing consumer demand for plant-based and high-protein options, motivated by health and sustainability, has resulted in a surge of food innovation in this area. Incorporating alternative plant sources, such as pulses and pseudocereals, has been proven to enhance the nutritional profile of baked products. However, these can also negatively impact the yeasted bread acceptability. In the bakery sector, it is crucial to consider how incorporating non-wheat ingredients influences product quality. Consequently, exploring effective treatments/processing methods becomes essential to minimize the impact of alternative plant ingredient additions. This review explores conventional and emerging processing approaches for alternative plant materials and discusses the nutritional value may be enhanced while maintaining high acceptability. A meta-analysis was undertaken to visualize the influence of plant processing technologies on product quality, specifically on loaf-specific volume and crumb texture. This review highlighted the importance of conventional processing methods when applied to bread. Additionally revealed the potential of emerging processing which can positively affect a loaf volume and texture when compared with non-processed plant ingredients. Such studies enabled the production of acceptable bakery products with higher levels of alternative ingredient incorporation. However, increased use of emerging technologies is dependent on further research and overcoming scaling-up difficulties.

Maintenance of UK bread baking quality: Trends in wheat quality traits over 50 years of breeding and potential for future application of genomic-assisted selection

Improved selection of wheat varieties with high end-use quality contributes to sustainable food systems by ensuring productive crops are suitable for human consumption end-uses. Here, we investigated the genetic control and genomic prediction of milling and baking quality traits in a panel of 379 historic and elite, high-quality UK bread wheat (Triticum eastivum L.) varieties and breeding lines. Analysis of the panel showed that genetic diversity has not declined over recent decades of selective breeding while phenotypic analysis found a clear trend of increased loaf baking quality of modern milling wheats despite declining grain protein content. Genome-wide association analysis identified 24 quantitative trait loci (QTL) across all quality traits, many of which had pleiotropic effects. Changes in the frequency of positive alleles of QTL over recent decades reflected trends in trait variation and reveal where progress has historically been made for improved baking quality traits. It also demonstrates opportunities for marker-assisted selection for traits such as Hagberg falling number and specific weight that do not appear to have been improved by recent decades of phenotypic selection. We demonstrate that applying genomic prediction in a commercial wheat breeding program for expensive late-stage loaf baking quality traits outperforms phenotypic selection based on early-stage predictive quality traits. Finally, trait-assisted genomic prediction combining both phenotypic and genomic selection enabled slightly higher prediction accuracy, but genomic prediction alone was the most cost-effective selection strategy considering genotyping and phenotyping costs per sample.

Genetic Variation and Heritability of Sensory and Artisan Bread Traits in a Set of SRW Wheat Breeding Lines

Focus on local food production and supply chains has heightened in recent years, as evidenced and amplified by the COVID-19 pandemic. This study aimed to assess the suitability of soft red winter (SRW) wheat breeding lines for local artisan bakers interested in locally sourced, strong gluten wheat for bread. Seventy-six genotyped SRW wheat breeding lines were milled into whole wheat flour and baked into small loaves. Bread aroma, flavor, and texture were evaluated by a sensory panel, and bread quality traits, including sedimentation volume, dough extensibility, and loaf volume, were measured to estimate heritability. SE-HPLC was performed on white flour, and breeding lines were characterized for different protein fraction ratios. Heritability of loaf volume was moderately high (h² = 0.68), while heritability of sedimentation volume, a much easier trait to measure, was slightly lower (h² = 0.55). Certain protein fraction ratios strongly related to loaf volume had high heritability (h² = 0.7). Even though only a moderate heritability estimate of dough extensibility was found in our study, high positive correlations were found between this parameter and sedimentation volume (r = 0.6) and loaf volume (r = 0.53). This low-input and highly repeatable parameter could be useful to estimate dough functionality characteristics. Flavor and texture heritability estimates ranged from 0.16 to 0.37, and the heritability estimate of aroma was not significantly different from zero. However, the sensorial characteristics were significantly correlated with each other, suggesting that we might be able to select indirectly for aroma by selecting for flavor or texture characteristics. From a genome-wide association study (GWAS), we identified six SNPs (single nucleotide polymorphisms) associated with loaf volume that could be useful in breeding for this trait. Producing high-quality strong gluten flour in our high rainfall environment is a challenge, but it provides local growers and end users with a value-added opportunity.

Metabolic Profiling Identifies Changes in the Winter Wheat Grains Following Fusarium Treatment at Two Locations in Croatia

Fusarium head blight (FHB) is one of the most dangerous diseases of winter wheat, resulting in reduced grain yield and quality, and production of mycotoxins by the Fusarium fungi. In the present study, changes in the grain metabolomics of winter wheat samples infected with Fusarium spp. and corresponding non-infected samples from two locations in Croatia were investigated by GC-MS. A Mann-Whitney test revealed that 24 metabolites detected were significantly separated between Fusarium-inoculated and non-infected samples during the variety by treatment interactions. The results confirmed that in grains of six FHB-resistant varieties, ten metabolites were identified as possible resistance-related metabolites. These metabolites included heptadecanoic acid, 9-(Z)-hexadecenoic acid, sophorose, and secolaganin in grains of FHB-resistant varieties at the Osijek location, as well as 2-methylaminomethyltartronic acid, maleamic acid, 4-hydroxyphenylacetonitrile, 1,4-lactonearabinonic acid, secolaganin, and alanine in grains of FHB-resistant varieties at the Tovarnik location. Moreover, on the PCA bi-plot, FHB-susceptible wheat varieties were closer to glycyl proline, decanoic acid, and lactic acid dimer that could have affected other metabolites, and thus, suppressed resistance to FHB. Although defense reactions were genetically conditioned and variety specific, resulting metabolomics changes may give insight into defense-related pathways that could be manipulated to engineer plants with improved resistance to the pathogen.

Mineral and Phytic Acid Content as Well as Phytase Activity in Flours and Breads Made from Different Wheat Species

Wheat is of high importance for a healthy and sustainable diet for the growing world population, partly due to its high mineral content. However, several minerals are bound in a phytate complex in the grain and unavailable to humans. We performed a series of trials to compare the contents of minerals and phytic acid as well as phytase activity in several varieties from alternative wheat species spelt, emmer and einkorn with common wheat. Additionally, we investigated the potential of recent popular bread making recipes in German bakeries to reduce phytic acid content, and thus increase mineral bioavailability in bread. For all studied ingredients, we found considerable variance both between varieties within a species and across wheat species. For example, whole grain flours, particularly from emmer and einkorn, appear to have higher mineral content than common wheat, but also a higher phytic acid content with similar phytase activity. Bread making recipes had a greater effect on phytic acid content in the final bread than the choice of species for whole grain flour production. Recipes with long yeast proofing or sourdough and the use of whole grain rye flour in a mixed wheat bread minimized the phytic acid content in the bread. Consequently, optimizing food to better nourish a growing world requires close collaboration between research organizations and practical stakeholders ensuring a streamlined sustainable process from farm to fork.

Technology characteristics and flavor changes of traditional green wheat product nian zhuan in Northern China

Nian zhuan has its aroma as one of the perceived principal characteristics. The current study was aimed mainly to investigate the potential to include the aroma of nian zhuan as a new target criterion into the green wheat product chain. By improving the conditions for the traditional processing of nian zhuan, the optimal processing conditions were determined as green wheat (GW) 14 d, steaming the green wheat with the skin (SGWS) 26 min and cooked green wheat peeled (CGWP) 280 min, to evaluate the feasibility of using electronic nose (E-nose) and gas chromatography mass spectrometry (GC-MS) to discriminate nian zhuan in different stages. E-nose was used to recognize nian zhuan odors in different processing stages, and GC-MS to identify the individual volatile compounds. A total of 139 volatile compounds were detected by GC-MS, of which 71 key were screened by t-test (P &lt; 0.01). The W1W, W1S, W2W and W2S sensors of E-nose gave higher responses to all samples, and effectively discriminated the samples. The most volatile compounds were produced in the millstone milling (MSM) stage of nian zhuan, and millstone could promote the release of volatile compounds from cooked green wheat by milling.

Research progress on the formation mechanism and detection technology of bread flavor

With a long history of fermentation technology and rich flavors, bread is widely consumed by people all around the world. The consumer market is huge and the demand is wide. However, the formation mechanism of bread baking flavor has not been completely defined. In order to improve the breadmaking process and the quality of bread, the main flavor substances produced in bread baking, the formation mechanism, and the detection technology of bread baking flavor are carefully summarized in this paper. The generation conditions and formation mechanism of flavor substances during the bread baking process are expounded, and the limitations of some current bread flavor detection technologies are proposed, which will provide theoretical basis for effectively regulating the generation of flavor substances in the bread baking process and making bread with good flavor and rich nutrition in the future.

Marker-assisted introgression of genes into rye translocation leads to the improvement in bread making quality of wheat (Triticum aestivum L.)

Introgression of genes from related species can be a powerful way to genetically improve crop yields, but selection for one trait can come at the cost to others. Wheat varieties with translocation of the short arm of chromosome 1 from the B genome of wheat (1BS) with the short arm of chromosome 1 from rye (1RS) are popular globally for their positive effect on yield and stress resistance. Unfortunately, this translocation (1BL.1RS) is also associated with poor bread making quality, mainly due to the presence of Sec-1 on its proximal end, encoding secalin proteins, and the absence of Glu-B3/Gli-B1-linked loci on its distal end, encoding low molecular weight glutenin subunits (LMW-GS). The present study aims to replace these two important loci on the 1RS arm with the wheat 1BS loci, in two popular Indian wheat varieties, PBW550 and DBW17, to improve their bread-making quality. Two donor lines in the cultivar Pavon background with absence of the Sec-1 locus and presence of the Glu-B3/Gli-B1 locus, respectively, were crossed and backcrossed with these two selected wheat varieties. In the advancing generations, marker assisted foreground selection was done for Sec-1^- and Glu-B3/Gli-B1⁺ loci while recurrent parent recovery was done with the help of SSR markers. BC₂F₅ and BC₂F₆ near isosgenic lines (NILs) with absence of Sec-1 and presence of Glu-B3/Gli-B1 loci were evaluated for two years in replicated yield trials. As a result of this selection, thirty promising lines were generated that demonstrated improved bread making quality but also balanced with improved yield-related traits compared to the parental strains. The study demonstrates the benefits of using marker-assisted selection to replace a few loci with negative effects within larger alien translocations for crop improvement.

Improvement of prediction ability by integrating multi-omic datasets in barley

Background

Genomic prediction (GP) based on single nucleotide polymorphisms (SNP) has become a broadly used tool to increase the gain of selection in plant breeding. However, using predictors that are biologically closer to the phenotypes such as transcriptome and metabolome may increase the prediction ability in GP. The objectives of this study were to (i) assess the prediction ability for three yield-related phenotypic traits using different omic datasets as single predictors compared to a SNP array, where these omic datasets included different types of sequence variants (full-SV, deleterious-dSV, and tolerant-tSV), different types of transcriptome (expression presence/absence variation-ePAV, gene expression-GE, and transcript expression-TE) sampled from two tissues, leaf and seedling, and metabolites (M); (ii) investigate the improvement in prediction ability when combining multiple omic datasets information to predict phenotypic variation in barley breeding programs; (iii) explore the predictive performance when using SV, GE, and ePAV from simulated 3’end mRNA sequencing of different lengths as predictors.

Results

The prediction ability from genomic best linear unbiased prediction (GBLUP) for the three traits using dSV information was higher than when using tSV, all SV information, or the SNP array. Any predictors from the transcriptome (GE, TE, as well as ePAV) and metabolome provided higher prediction abilities compared to the SNP array and SV on average across the three traits. In addition, some (di)-similarity existed between different omic datasets, and therefore provided complementary biological perspectives to phenotypic variation. Optimal combining the information of dSV, TE, ePAV, as well as metabolites into GP models could improve the prediction ability over that of the single predictors alone.

Conclusions

The use of integrated omic datasets in GP model is highly recommended. Furthermore, we evaluated a cost-effective approach generating 3’end mRNA sequencing with transcriptome data extracted from seedling without losing prediction ability in comparison to the full-length mRNA sequencing, paving the path for the use of such prediction methods in commercial breeding programs.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08337-7).

Metabolomic selection for enhanced fruit flavor

Consumers often regard heirloom fruit varieties grown in the garden as more flavorful than commercial varieties purchased at the grocery store. While plant breeders have historically focused on improving producer-orientated traits such as yield, consumer-oriented traits such as flavor have regularly been neglected. This is, in part, due to the difficulty associated with measuring the sensory perceptions of flavor. Here, we combine fruit chemical and consumer sensory panel information to train machine learning models that can predict how flavorful a fruit will be from its chemistry. By increasing the throughput of flavor evaluations, these models will help plant breeders to integrate flavor earlier in the breeding pipeline and aid in the design of varieties with exceptional flavor profiles.

Although they are staple foods in cuisines globally, many commercial fruit varieties have become progressively less flavorful over time. Due to the cost and difficulty associated with flavor phenotyping, breeding programs have long been challenged in selecting for this complex trait. To address this issue, we leveraged targeted metabolomics of diverse tomato and blueberry accessions and their corresponding consumer panel ratings to create statistical and machine learning models that can predict sensory perceptions of fruit flavor. Using these models, a breeding program can assess flavor ratings for a large number of genotypes, previously limited by the low throughput of consumer sensory panels. The ability to predict consumer ratings of liking, sweet, sour, umami, and flavor intensity was evaluated by a 10-fold cross-validation, and the accuracies of 18 different models were assessed. The prediction accuracies were high for most attributes and ranged from 0.87 for sourness intensity in blueberry using XGBoost to 0.46 for overall liking in tomato using linear regression. Further, the best-performing models were used to infer the flavor compounds (sugars, acids, and volatiles) that contribute most to each flavor attribute. We found that the variance decomposition of overall liking score estimates that 42% and 56% of the variance was explained by volatile organic compounds in tomato and blueberry, respectively. We expect that these models will enable an earlier incorporation of flavor as breeding targets and encourage selection and release of more flavorful fruit varieties.

Metabolomics as a Tool to Elucidate the Sensory, Nutritional and Safety Quality of Wheat Bread-A Review

Wheat (Triticum aestivum) is one of the most extensively cultivated and used staple crops in human nutrition, while wheat bread is annually consumed in more than nine billion kilograms over the world. Consumers’ purchase decisions on wheat bread are largely influenced by its nutritional and sensorial characteristics. In the last decades, metabolomics is considered an effective tool for elucidating the information on metabolites; however, the deep investigations on metabolites still remain a difficult and longtime action. This review gives emphasis on the achievements in wheat bread metabolomics by highlighting targeted and untargeted analyses used in this field. The metabolomics approaches are discussed in terms of quality, processing and safety of wheat and bread, while the molecular mechanisms involved in the sensorial and nutritional characteristics of wheat bread are pointed out. These aspects are of crucial importance in the context of new consumers’ demands on healthy bakery products rich in bioactive compounds but, equally, with good sensorial acceptance. Moreover, metabolomics is a potential tool for assessing the changes in nutrient composition from breeding to processing, while monitoring and understanding the transformations of metabolites with bioactive properties, as well as the formation of compounds like toxins during wheat storage.