This study evaluated the effects of conventional (CONV) and organic (ORG) management on grain yield, nutritional composition and quality traits of winter barley, winter spelt, spring oat and winter wheat over a three-year field experiment. The aim was to identify species-specific productivity-quality relationships and determine the relative contributions of management and seasonal variation to cereal performance. Across all species, CONV management consistently maximised grain yield, with winter barley reaching 7.03 t ha-1 under CONV compared with 3.33 t ha-1 under ORG, and winter wheat producing 6.43 versus 3.17 t ha-1, respectively. In contrast, ORG management enhanced grain nutritional quality by increasing micronutrient concentrations, particularly Zn, Cu, Fe and Mo; for example, winter wheat under ORG accumulated 39.54 mg kg-1 Zn compared with 26.98 mg kg-1 under CONV, while spring oat exceeded 79 mg kg-1 Fe under ORG conditions. Among the cereals studied, conventional hulled winter barley showed the highest β-glucan content, kernel width and thousand-kernel weight, whereas spring oat had higher fat, fibre and dry matter concentrations. Multivariate analyses showed that species identity was the main determinant of grain quality architecture, substantially outweighing management effects, while year significantly influenced most traits, reflecting strong genotype × environment × management interactions. The findings highlight the need to integrate cereal species selection, productivity and both concentration- and area-based nutritional indicators when designing sustainable cereal production systems.
The rapid digestibility of white rice (WR) poses metabolic burdens, whereas multigrain reconstituted rice (MRR) offers modulated digestive properties. This study employed a dynamic in vitro gastrointestinal system to investigate temporal variations in gastric pH, gastric emptying characteristics, starch hydrolysis rate, protein digestibility, microstructure and physicochemical properties of MRR and WR during gastrointestinal digestion. The results demonstrated that MRR contained ten times more dietary fiber than WR, exhibited significantly increased chyme viscosity, which physically impeded gastric mixing and peristaltic emptying, thereby prolonging gastric retention time. This delayed gastric emptying consequently limited the rate of starch transfer into the small intestine, leading to an 11.03% reduction in starch hydrolysis compared to WR. Meanwhile, the abundant dietary fiber in MRR formed a dense gel network that acted as a physical barrier, restricting enzyme accessibility to starch granules. Synergistically, the extrusion-induced V-type crystalline structure of MRR starch further enhanced its resistance to enzymatic attack. MRR showed delayed protein digestion but 4.15% higher final digestibility than WR. During digestion, the stable crystalline structure of MRR works synergistically with the physical barrier formed by its abundant dietary fiber, ultimately resulting in a slow and steady nutrient release pattern. The slow digestion behavior of MRR provided theoretical support for stabilized postprandial glucose response and prolonged satiety.
Zearalenone (ZEN) is a prevalent mycotoxin in cereal crops, particularly in corn and its derived products, posing significant health risks to humans and livestock due to its estrogen-mimicking structure. Consequently, effective mitigation of ZEN has become a critical food safety priority, driving the development of biodegradation, chemical, and physical mitigation strategies. Among these, physical methods are particularly favored for their simplicity, efficiency, and scalability, making them highly suitable for industrial applications. This review critically summarizes ZEN contamination levels and regulatory limits, with a focus on recent advances in physical detoxification technologies. Particular emphasis is placed on physical degradation methods such as thermal treatment, irradiation, and cold plasma, alongside adsorption-based strategies utilizing clay minerals, activated carbon, and metal-organic frameworks. Furthermore, the underlying mechanisms, detoxification efficacy, and practical limitations of these physical technologies are systematically evaluated. Although promising, the industrial application of these methods is often constrained by challenges in preserving food quality and maintaining efficacy within complex food matrices. This paper consolidates current insights to guide future research, emphasizing the development of selective adsorbents and process optimization under realistic food processing conditions.
Herein, functionalities of blue wheat starch modified by autoclaving heat-moisture treatment (AHT) were investigated on the basis of its multi-level structure. AHT with moisture content (MC) of 15-20 % enlarged crystalline lamellae and ameliorated packing order of double helices, and the thermal stability got enhanced. It induced debranching and moderate breakdown of long chains. Owing to the lower proportion of short chains in amylopectin, it yielded gels with higher springiness. AHT with MC of 25-30 % aggravated molecular disordering and chain depolymerization. The destruction of amylopectin was not confined to external short chains; internal long chains were also destructed. The severe structural destruction enhanced solubility, which contributes to higher paste clarity that is sensory-appealing for starch gel. Also, higher-MC AHT may induce more formation of starch-phenolics inclusion complexes and resulted in softer gels with anti-retrogradation capacity. Therefore, AHT-modified blue wheat starch is promising to serve as ingredients in novel starchy foods.
Common wheat near-isogenic lines carrying wild or mutated allele of the gene encoding Puroindoline B and displaying distinct hardness, soft or hard corresponding to the two main defined classes in relation to their uses in food making, were grown for two years under well-watered or water-deficit conditions. Grains produced under drought conditions were lighter and smaller with reduced levels of biochemical markers concentrated in the aleurone layer cytoplasm: i.e. ash, phytic acid and albumins-globulins. These results suggested that drought affects either the aleurone layer proportion or its thickness. This is consistent with the known impact of drought on reducing germination, given the key role of the aleurone layer during this stage of plant growth. X-ray micro-tomography was then used to analyze the aleurone layer in three-dimensions. No changes were observed in the overall volume proportion of the aleurone layer between grains grown under distinct hydric conditions. However, for the first time, variations in the aleurone layer thickness were highlighted, with drought reducing the median thickness within this tissue.
Gluten quality is a critical determinant of the end-use properties of wheat. The viscoelastic protein network that constitutes gluten is primarily composed of glutenins and gliadins, with high molecular weight glutenin subunits (HMW-GS) playing an important role in determining gluten strength and extensibility. In common wheat, HMW-GS are encoded by the GLU-A1, GLU-B1 and GLU-D1 loci. For the GLU-B1 locus, up to 98 alleles have been described and compiled in the Wheat Gene Catalogue (WGC); however, the true extent of this variability remains uncertain, as many alleles have not been compared in conjunction and the associated germplasm is not always accessible. The present study aimed to collect and characterise the germplasm associated with GLU-B1 variability described in the WGC, to verify the allelic composition of each accession by SDS-PAGE and to assess whether the variability currently recorded is accurate. The identity of the majority of alleles was confirmed, while some cases of duplicated entries were identified, and others could not be verified due to the unavailability of the representative germplasm or genetic drift occurring in gene banks over time. Based on these findings, we propose the development of a master set of accessions representing the current GLU-B1 variability as confirmed by SDS-PAGE. The availability of this master set will improve the quality of future studies on HMW-GS variability and facilitate the use of a broader range of GLU-B1 alleles in breeding programs aimed at enhancing processing and end-use quality.
This study investigated the effects of mass-based sodium/potassium salt replacement on semi-dried noodle hardness. Two formulation backgrounds were compared. The salt system contained 1.0% total NaCl/KCl. The alkaline system contained fixed 1.0% NaCl plus 0.5% total Na2CO3/K2CO3. Cooked hardness, cooking quality, water distribution, gluten network properties, starch gelatinization, and correlation patterns were evaluated. In the salt system, 25% KCl replacement maintained disulfide cross-linking and gluten network compactness. This treatment showed the highest cooked hardness (312.86 g). It also improved overcooking resistance and produced the lowest cooking loss. Complete KCl replacement reduced hardness by 5.5%. In the alkaline system, the all-sodium carbonate treatment showed high cooked hardness (408.90 g). The 25% K2CO3 replacement maintained comparable noodle quality. However, higher K2CO3 replacement weakened disulfide cross-linking. It also disrupted the membrane-like gluten network. Starch gelatinization enthalpy and setback viscosity were also reduced. Complete K2CO3 replacement reduced hardness by 5.5% and markedly increased cooking loss. Alkalinity strongly restricted water mobility. The cooked-noodle T23 in the alkaline system was only about one-third of that in the salt system. Under the tested gradients, 25% KCl or K2CO3 replacement was the highest tested level that maintained noodle quality.
Pigmented brown rice flour (PBRF) is a promising functional ingredient, yet the links between flour traits and product quality remain unclear. Here, five PBRFs differing in pericarp color and amylose content were characterized and used for rice cake production. Amylose content strongly contributed to variations in starch functionality and rice cake quality within the whole PBRFs matrix. High amylose rice flours tended to show restricted hydration, higher pasting temperature, and stronger cooling-stage viscosity recovery, producing rice cakes with denser microstructures, distinct water-related proton mobility, higher hardness, and lower springiness. In contrast, waxy rice flours tended to produce more porous and elastic cakes. Darker cultivars showed higher soluble phenolic contents and stronger antioxidant capacities, with B-F showing the highest antioxidant potential. B-C had the highest trained-panel acceptability, whereas Y-C showed the strongest aroma response. This study links cultivar differences, especially amylose-related starch behavior, to rice cake quality and supports the targeted utilization of pigmented brown rice.
Producing wheat of low free asparagine content is one strategy to meet international goals for allaying food safety concerns that arise from acrylamide formation in bread. However, factors that affect free asparagine in wheat also affect protein content and composition, and through their effects on dough viscoelasticity, bread quality. We investigated relationships between dough rheological properties and wheat free asparagine concentration using dynamic and static shear rheometry. From a population of 128 wheats, 10 were selected from which doughs with a wide range of asparagine concentrations were prepared. Within the linear viscoelastic region (LVR), dough’s tanδ and free asparagine concentration were positively related, a result that appears to depend on protein composition. Outside the LVR, significant relationships between rheological parameters and free asparagine content were found. The dough’s relative capacity to recover in creep-recovery tests was significantly impaired at elevated asparagine content. Similarly, stress relaxation tests showed that as wheat asparagine content increased, dough relaxation moduli decreased. Excellent fits of stress relaxation curves to a two-element Maxwell model were obtained. Both relaxation times decreased as asparagine concentration increased, showing that gluten strength attributes arising from gliadins and network-structuring proteins were both negatively affected in wheats of high asparagine content. In summary, wheat with high free asparagine concentrations led to more fluid-like doughs, i.e., weaker glutens. A welcome result is that strategies pursued to reduce acrylamide in bread through reduction in wheat’s asparagine content will not impair bread quality.
Infrared radiation (IR) can suppress lipid deterioration during rice storage, but its regulatory mechanism in hexanal formation remains unclear. This study investigated the effects of IR on lipid-metabolic pathways, enzyme activities, gene expression, lipase (LPS) structure, and ex vivo hexanal generation in stored rice grains. Compared with the air-dried control (AAD), the IR-treated (IRD) group showed lower initial LPS activity (1.582 ± 0.051 vs. 2.856 ± 0.009 U/L) and maintained reduced LPS activity during 180 days of storage. LOX activity was 20.8% lower at 180 days, and HPL activity decreased significantly after 120 days (P < 0.05). Transcriptomic analysis showed that IR modulated genes associated with LPS (Os05g0408300), LOX (Os03g0179900, Os04g0447100), and HPL (Os02g0218700, Os02g0110200), indicating reduced flux through linoleic and linolenic acid oxidation. The ex vivo model confirmed a 34.87% reduction in hexanal content. Circular dichroism suggested IR-induced conformational adjustment of LPS. Overall, IR limits hexanal formation by coordinating lipid hydrolysis, lipid oxidation, and LPS structural modulation.
This study compared the effects of non-thermal plasma (NTP), cellulase (CBR), and ultrasonic treatment (UTBR) on the quality of Bao Yod Muang brown rice (Oryza sativa L.). Compared to NTP, UTBR and CBR significantly and more markedly altered rice composition and cooking quality. The effects of NTP varied with treatment intensity. All treatments modified the grain properties, notably the removal of bran layer. The loss of non-carbohydrate constituents caused a relative increase in carbohydrate from 84.8% to 86.8%. UTBR and CBR caused reductions in cooking time from 20.7 min to 13.8 and 15.2 min, increased water absorption rate from 0.043 to 0.067 and 0.059 g grice−1 min−1, increased solid loss rate from 0.035 to 0.055 and 0.042 g 100 grice−1 min−1, respectively. The hardness decay coefficient (B) of UTBR was the highest and did not differ from that of white rice (p > 0.05), followed by that of CBR and NTP. NTP showed a better ability to maintain nutritional value. Low-power NTP maintained total phenolic content (TPC), total flavonoid content (TFC), and DPPH radical scavenging activity, at levels statistically equivalent to untreated brown rice (UBR). All treatments increased the estimated glycemic index (eGI) compared with UBR. However, the eGI values of NTP-treated rice and UTBR were not significantly different from those of UBR, whereas CBR showed a significantly higher eGI.
Pearl millet is a vital dietary source for dry land populations and is often regarded as a “super cereal”; however, genetic improvement has lagged behind major cereals, resulting in slow progress in nutritional enhancement. In the present study, genotyping-by-sequencing-derived SNP markers were used in a 178-line PMiGAP panel evaluated across four agro-ecologically diverse environments to dissect genomic diversity, population structure, and linkage disequilibrium associated with four mineral traits (Fe, Zn, P, and Mn) and two anti-nutritional traits (PAC and TTC). A total of 76,220 high-confidence SNPs were retained for analysis. Population structure resolved five genetically coherent yet variably admixed subgroups aligned with geographic origin, while genome-wide FST scans revealed heterogeneous selection signatures across the panel. GWAS using the BLINK algorithm identified 16 significant MTAs distributed across six chromosomes, including two environmentally stable SNPs, S1_237185612 (Zn) and S4_57239923 (TTC). Functional annotation showed that S4_57239923 (Chr Pgl04; Pgl_GLEAN_10024187) functions in Ca2+-dependent signalling and vascular transport, influencing micronutrient allocation via ZIP/ZIF-mediated Zn mobilization and ferritin-driven Fe sequestration. SNP S1_237185612 (Chr Pgl01; Pgl_GLEAN_10014727, 10014726, 10014724, 10014723, 10014728) mapped to pathways related to metal sensing, protein turnover, cell-wall chelation, and nutrient signalling, consistent with established Zn transport and micronutrient buffering mechanisms. These findings represent the first multi-environment SNP-based genomic dissection of nutritional and anti-nutritional traits using the globally diverse PMiGAP panel evaluated across representative A1, A, and B agro-ecological zones of India, providing robust genomic resources, stable diagnostic markers, and functionally supported candidate genes for marker-assisted selection, genomic prediction, and precise nutritional enhancement.
Quality Protein Maize (QPM) has elevated lysine and tryptophan levels, yet the stability of these nutritional advantages under abiotic stress remains largely unknown. This study evaluated the effects of low-rainfall and low Nitrogen (N) conditions on grain yield, and protein, tryptophan, iron (Fe) and zinc (Zn) accumulation in QPM hybrids. Forty QPM hybrids and five checks were tested under optimal, low N, and low-rainfall conditions in Ethiopia and Zimbabwe. Grain nutritional traits were quantified using near-infrared spectroscopy, colorimetric tryptophan assay, and atomic absorption spectrophotometry. Grain yield and micronutrient density were decreased under low N and low-rainfall conditions. Low N reduced protein and tryptophan concentrations, whereas low-rainfall conditions increased total protein. Fe and Zn concentrations declined under both stresses. Zn showed better stability under low-rainfall conditions. Grain yield weakly correlated with almost all nutritional traits. Significant positive correlations were observed between protein and Fe, protein and Zn, and tryptophan and Zn under low-rainfall, and Fe and Zn under low N conditions, indicating the possibility of simultaneous nutrient improvement. Performance under optimal and low N and low-rainfall conditions was associated for yield, protein, tryptophan, and Zn, indicating the possibility of simultaneous improvement of yield and nutritional quality. Selection under optimal conditions may accelerate breeding for stress-prone environments without compromising nutritional value.
Conventional breeding programs have often led to a dilution of grain nutrient concentrations, leaving micronutrient deficiencies unresolved. To address this challenge, two evolutionary plant breeding experiments were carried out involving durum wheat (DW) and barley populations, to identify populations with better genetic biofortification potential at specific test locations. Grain samples from 27 DW populations plus four barley populations at Habru Seftu and 23 DW populations at Debrezeit Agricultural Research Center were analyzed alongside pure-stand check varieties for nutritional composition. Laboratory analyses were conducted at CIHEAM Bari, Italy. The DW populations exhibited wide variation for most nutritional traits across both locations. At Habru Seftu, some populations showed higher concentrations of total dietary fiber (TDF) up to 20.83, iron (Fe) up to 44.44%, and zinc (Zn) up to 30.76% than sole-stand improved varieties, while at DzARC, up to 4.45% higher TDF was recorded in populations over the sole-stand varieties. Populations assisted through participatory farmers' selection consistently dominated the top-performing groups for key nutrients across locations. Female farmers’ selected populations were particularly superior for the most deficient micronutrients, with Fe- and Zn-rich mixtures outperforming all other entries. Overall, the results highlight dynamic mixtures/evolutionary populations, especially those shaped through participatory and gender-disaggregated selection— can be considered as a promising alternative for enhancing grain nutritional quality and advancing genetic biofortification in durum wheat and barley.
NIR spectroscopy has been widely applied as a rapid screening tool for quality traits in cereal breeding programs, genetic evaluation, and grain quality assessment. The objective of this study was to evaluate the feasibility of using a portable NIR instrument to predict amylose content, gelatinisation temperature (GT), and Rapid Visco Analyser (RVA) pasting parameters directly from intact white rice kernels. A total of 144 rice samples representing commercial and breeding material were analysed using a handheld NIR spectrometer operating within the 950–1600 nm spectral range. Reference measurements for amylose content, GT, and RVA parameters were obtained using standard laboratory methods. PLS regression models were developed following second derivative spectral preprocessing and dataset partitioning using the Kennard–Stone algorithm. Among the evaluated traits, GT showed the strongest predictive performance, achieving coefficients of determination of R2cv = 0.79 and R2p = 0.80, with RPD values exceeding 2.0, indicating suitability for screening applications. Moderate predictive capability was obtained for peak and trough viscosity, while amylose content and other RVA parameters exhibited limited quantitative prediction under external validation. The results demonstrate that portable NIR spectroscopy can capture spectral information related to starch–water interactions governing thermal transitions in rice, despite measurements being performed on intact kernels. Although complete replacement of laboratory-based RVA analysis remains challenging, portable NIR instruments provide a rapid, non-destructive approach for preliminary screening and classification of rice quality traits within breeding and industrial workflows.
The functionality of starch is associated with its cross-scale hierarchical architecture, ranging from Ångström-level molecular chains to micrometer-scale granules. Nevertheless, within the conventional reductionist framework, classical linear statistical approaches are often inadequate for resolving high-dimensional, nonlinear structure–function relationships. Their dependence on averaged structural descriptors may further mask important heterogeneity at the individual-granule level. In this context, deep learning is no longer merely a data-fitting strategy, but is increasingly emerging as a promising analytical approach for characterizing the multiscale structure–function relationships of starch.This review proposes a physics-informed analytical framework for supporting data-informed starch research. At the microscopic level, convolutional neural networks (CNNs) enable the extraction of topological fingerprints from microscopy images, allowing granule-level heterogeneity to be quantitatively captured. At the spectral level, end-to-end learning architectures can disentangle nonlinear responses from complex food matrices, enhancing the robustness of nondestructive analysis. At the spatiotemporal level, physics-informed neural networks (PINNs) provide a means of embedding thermodynamic and kinetic constraints into data-driven algorithms, thereby creating new opportunities to connect molecular simulations, retrogradation kinetics, and macroscopic rheological behavior.Looking forward, an important future challenge is the development of standardized, shareable, and data-secure StarchNet-like data resources. Coupled with explainable artificial intelligence, physics-informed modeling, and generative inverse design, such data resources may facilitate the transition of starch research from empirical prediction toward mechanism-constrained and function-oriented, data-informed design.
X-ray microcomputed tomography (μCT) enables non-destructive visualization of the internal microstructures of grains. In this study, underutilized grains with growing demand, including sorghum, millet, buckwheat, and quinoa, were investigated as valuable alternatives to traditional cereals. A comprehensive 3D characterization of their internal architecture was performed to provide quantitative insights relevant to food processing and functional applications. By determining the spatial organization and relative volumes of major grain components, structural factors influencing mechanical behavior, hydration kinetics, nutrient distribution, and overall functional performance can be better understood. Image reconstruction and segmentation software were applied to CT datasets to generate 3D images from 2D cross-sectional images, enabling volumetric structural analysis. This approach facilitates the identification and quantification of internal microstructural features that are often inaccessible through conventional imaging techniques. The total grain volume, as well as the volume of major anatomical components, were quantified. Phenotypic characterization included grain shape, internal component morphology, and spatial organization. The embryo, endosperm, and outer layers were clearly distinguishable in all grains, while in quinoa, additional structures such as the perisperm, funicle, and cotyledons were also resolved. The CT-derived volumetric and spatial datasets generated in this study contribute to the limited body of quantitative 3D grain anatomy literature, which has predominantly focused on single crops or relied on schematic rather than true volumetric representations. These findings provide a valuable resource for advancing structural understanding and application of underutilized grains in the food sector.
