Empirical rheology and pasting properties of soft-textured durum wheat ( Triticum turgidum ssp. durum ) and hard-textured common wheat ( T. aestivum )

A null allele of granule bound starch synthase (Wx-B1) may be one of the major genes controlling chapatti softness

Chapatti (unleavened flatbread) is a staple food in northern India and neighboring countries but the genetics behind its processing quality are poorly understood. To understand the genes determining chapatti quality, differentially expressed genes were selected from microarray data of contrasting chapatti cultivars. From the gene and trait association studies, a null allele of granule bound starch synthase (GBSS; Wx-B1) was found to be associated with low amylose content and good chapatti quality. For validation, near-isogenic lines (NILs) of this allele were created by marker assisted backcross (MAB) breeding. Background screening indicated 88.2 to 96.7% background recovery in 16 selected BC3F5 NILs. Processing quality and sensory evaluation of selected NILs indicated improvement in chapatti making quality. Traits that showed improvement were mouthfeel, tearing strength and softness indicating that the Wx-B1 may be one of the major genes controlling chapatti softness.

Toward the Genetic Basis and Multiple QTLs of Kernel Hardness in Wheat

Kernel hardness is one of the most important single traits of wheat seed. It classifies wheat cultivars, determines milling quality and affects many end-use qualities. Starch granule surfaces, polar lipids, storage protein matrices and Puroindolines potentially form a four-way interaction that controls wheat kernel hardness. As a genetic factor, Puroindoline polymorphism explains over 60% of the variation in kernel hardness. However, genetic factors other than Puroindolines remain to be exploited. Over the past two decades, efforts using population genetics have been increasing, and numerous kernel hardness-associated quantitative trait loci (QTLs) have been identified on almost every chromosome in wheat. Here, we summarize the state of the art for mapping kernel hardness. We emphasize that these steps in progress have benefitted from (1) the standardized methods for measuring kernel hardness, (2) the use of the appropriate germplasm and mapping population, and (3) the improvements in genotyping methods. Recently, abundant genomic resources have become available in wheat and related Triticeae species, including the high-quality reference genomes and advanced genotyping technologies. Finally, we provide perspectives on future research directions that will enhance our understanding of kernel hardness through the identification of multiple QTLs and will address challenges involved in fine-tuning kernel hardness and, consequently, food properties.

Relationships between puroindoline A-prolamin interactions and wheat grain hardness

Grain hardness is an important quality trait of cereal crops. In wheat, it is mainly determined by the Hardness locus that harbors genes encoding puroindoline A (PINA) and puroindoline B (PINB). Any deletion or mutation of these genes leading to the absence of PINA or to single amino acid changes in PINB leads to hard endosperms. Although it is generally acknowledged that hardness is controlled by adhesion strength between the protein matrix and starch granules, the physicochemical mechanisms connecting puroindolines and the starch-protein interactions are unknown as of this time. To explore these mechanisms, we focused on PINA. The overexpression in a hard wheat cultivar (cv. Courtot with the Pina-D1a and Pinb-D1d alleles) decreased grain hardness in a dose-related effect, suggesting an interactive process. When PINA was added to gliadins in solution, large aggregates of up to 13 μm in diameter were formed. Turbidimetry measurements showed that the PINA-gliadin interaction displayed a high cooperativity that increased with a decrease in pH from neutral to acid (pH 4) media, mimicking the pH change during endosperm development. No turbidity was observed in the presence of isolated α– and γ-gliadins, but non-cooperative interactions of PINA with these proteins could be confirmed by surface plasmon resonance. A significant higher interaction of PINA with γ-gliadins than with α–gliadins was observed. Similar binding behavior was observed with a recombinant repeated polypeptide that mimics the repeat domain of gliadins, i.e., (Pro-Gln-Gln-Pro-Tyr)₈. Taken together, these results suggest that the interaction of PINA with a monomeric gliadin creates a nucleation point leading to the aggregation of other gliadins, a phenomenon that could prevent further interaction of the storage prolamins with starch granules. Consequently, the role of puroindoline-prolamin interactions on grain hardness should be addressed on the basis of previous observations that highlight the similar subcellular routing of storage prolamins and puroindolines.

Electric Drive Supervisor for Milling Process 4.0 Automation: A Process Analytical Approach with IIoT NIR Devices for Common Wheat

The milling industry envisions solutions to become fully compatible with the industry 4.0 technology where sensors interconnect devices, machines and processes. In this contest, the work presents an integrated solution merging a deeper understanding and control of the process due to real-time data collection by MicroNIR sensors (VIAVI, Santa Rosa, CA)—directly from the manufacturing process—and data analysis by Chemometrics. To the aim the sensors were positioned at wheat cleaning and at the flour blends phase and near infrared spectra (951–1608 nm) were collected online. Regression models were developed merging the spectra information with the results obtained by reference analyses, i.e., chemical composition and rheological properties of dough by Farinograph^® (Brabender GmbH and Co., Duisburg, Germany), Alveograph^® (Chopin, NG Villeneuve-la-Garenne Cedex, France) and Extensograph^®.(Brabender GmbH and Co., Duisburg, Germany) The model performance was tested by an external dataset obtaining, for most of the parameters, R_PRED higher than 0.80 and Root Mean Squares Errors in prediction lower than two-fold the value of the reference method errors. The real-time implementation resulted in optimal (100% of samples) or really good (99.9%–80% of samples) prediction ability. The proposed work succeeded in the implementation of a process analytical approach with Industrial Internet of Things near infrared (IIoT NIR) devices for the prediction of relevant grain and flour characteristics of common wheat at the industrial level.

Expression of Puroindoline a in Durum Wheat Affects Milling and Pasting Properties

Durum wheat has limited culinary utilizations partly due to its extremely hard kernel texture. Previously, we developed transgenic durum wheat lines with expression of the wildtype Puroindoline a (Pina) and characterized PINA's effects on kernel hardness, total flour yield and dough mixing properties in durum wheat. The medium-hard kernel texture is potentially useful for exploring culinary applications of durum wheat. In the present study, we examined the milling parameters and flour attributes of the transgenic lines, including particle size distribution, damaged starch and water binding capacity. PINA expression results in increased break and reduction flour yield but decreased shorts. PINA expression also leads to finer flour particles and decreased starch damage. Interestingly, PINA transgenic lines showed increased peak viscosity and breakdown viscosity but leave other flour pasting parameters generally unaltered. PINA transgenic lines were associated with increased small monomeric proteins, appearing to affect gluten aggregation. Our data together with several previous results highlight distinct effects of PINs on pasting properties depending on species and variety. The medium-hard kernel texture together with improved pasting parameters may be valuable for producing a broader range of end-products from durum wheat.

Co-expression of high-molecular-weight glutenin subunit 1Ax1 and Puroindoline a (Pina) genes in transgenic durum wheat (Triticum turgidum ssp. durum) improves milling and pasting quality

BACKGROUND

Durum wheat is considered not suitable for making many food products that bread wheat can. This limitation is largely due to: (i) lack of grain-hardness controlling genes (Puroindoline a and b) and consequently extremely-hard kernel; (ii) lack of high- and low-molecular-weight glutenin subunit loci (Glu-D1 and Glu-D3) that contribute to gluten strength. To improve food processing quality of durum wheat, we stacked transgenic Pina and HMW-glutenin subunit 1Ax1 in durum wheat and developed lines with medium-hard kernel texture.

RESULTS

Here, we demonstrated that co-expression of Pina + 1Ax1 in durum wheat did not affect the milling performance that was enhanced by Pina expression. While stacking of Pina + 1Ax1 led to increased flour yield, finer flour particles and decreased starch damage compared to the control lines. Interestingly, Pina and 1Ax1 co-expression showed synergistic effects on the pasting attribute peak viscosity. Moreover, Pina and 1Ax1 co-expression suggests that PINA impacts gluten aggregation via interaction with gluten protein matrix.

CONCLUSIONS

The results herein may fill the gap of grain hardness between extremely-hard durum wheat and the soft kernel durum wheat, the latter of which has been developed recently. Our results may also serve as a proof of concept that stacking Puroindolines and other genes contributing to wheat end-use quality from the A and/or D genomes could improve the above-mentioned bottleneck traits of durum wheat and help to expand its culinary uses.

Interspecific and intergeneric hybridization as a source of variation for wheat grain quality improvement

The hybridization events with wild relatives and old varieties are an alternative source for enlarging the wheat quality variability. This review describes these process and their effects on the technological and nutritional quality. Wheat quality and its end-uses are mainly based on variation in three traits: grain hardness, gluten quality and starch. In recent times, the importance of nutritional quality and health-related aspects has increased the range of these traits with the inclusion of other grain components such as vitamins, fibre and micronutrients. One option to enlarge the genetic variability in wheat for all these components has been the use of wild relatives, together with underutilised or neglected wheat varieties or species. In the current review, we summarise the role of each grain component in relation to grain quality, their variation in modern wheat and the alternative sources in which wheat breeders have found novel variation.

Improving the baking quality of bread wheat by genomic selection in early generations

Genomic selection shows great promise for pre-selecting lines with superior bread baking quality in early generations, 3 years ahead of labour-intensive, time-consuming, and costly quality analysis. The genetic improvement of baking quality is one of the grand challenges in wheat breeding as the assessment of the associated traits often involves time-consuming, labour-intensive, and costly testing forcing breeders to postpone sophisticated quality tests to the very last phases of variety development. The prospect of genomic selection for complex traits like grain yield has been shown in numerous studies, and might thus be also an interesting method to select for baking quality traits. Hence, we focused in this study on the accuracy of genomic selection for laborious and expensive to phenotype quality traits as well as its selection response in comparison with phenotypic selection. More than 400 genotyped wheat lines were, therefore, phenotyped for protein content, dough viscoelastic and mixing properties related to baking quality in multi-environment trials 2009-2016. The average prediction accuracy across three independent validation populations was r = 0.39 and could be increased to r = 0.47 by modelling major QTL as fixed effects as well as employing multi-trait prediction models, which resulted in an acceptable prediction accuracy for all dough rheological traits (r = 0.38-0.63). Genomic selection can furthermore be applied 2-3 years earlier than direct phenotypic selection, and the estimated selection response was nearly twice as high in comparison with indirect selection by protein content for baking quality related traits. This considerable advantage of genomic selection could accordingly support breeders in their selection decisions and aid in efficiently combining superior baking quality with grain yield in newly developed wheat varieties.

Structural consequences of the interaction of puroindolines with gluten proteins

The effect of puroindolines (PINs) on structural characteristics of wheat proteins was investigated in Triticum turgidum ssp. durum (cv. Svevo) and Triticum aestivum (cv. Alpowa) and in their respective derivatives in which PIN genes were expressed (Soft Svevo) or the distal end of the short arm of chromosome 5D was deleted and PINs were not expressed (Hard Alpowa). The presence of PINs decreased the amount of cold-SDS extractable proteins and the accessibility of protein thiols to specific reagents, but resulted in facilitated solvation of gluten proteins, as detected by tryptophan fluorescence measurements carried out on minimally mixed flour/water mixtures. We propose that PINs and gluten proteins are interacting in the grain or flour prior to mixing. Hydrophobic interactions between PINs and some of the gluten proteins modify the pattern of interactions among gluten proteins, thus providing an additional mechanistic rationale for the effects of PINs on kernel hardness.