Unraveling the Impacts of Germination on the Volatile and Fatty Acid Profile of Intermediate Wheatgrass (Thinopyrum intermedium) Seeds.

Intermediate wheatgrass (IWG) is a promising perennial grain explored for mainstream food applications. This study investigated the effects of different germination temperatures (10, 15, and 20 °C) and durations (2, 4, and 6 days) on IWG's volatile and fatty acid (FA) profiles. A method using headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) was optimized through response surface design to extract the volatile compounds, achieving ideal extraction conditions at 60 °C for 55 min. Multiple headspace extraction (MHE) was used for volatile compound quantification. Fifty-eight compounds were identified and quantified in IWG flour, mainly alcohols, aldehydes, hydrocarbons, terpenes, esters, organic acids, and ketones. The main FAs found were linoleic acid (C18:2), oleic acid (C18:1), palmitic acid (C16:0), and linolenic acid (C18:3). Principal component analysis showed a direct correlation between volatile oxidation products and FA composition. Germination at 15 °C for 6 days led to a reduced presence of aldehydes and alcohols such as nonanal and 1-pentanol. Therefore, optimized germination was successful in reducing the presence of potential off-odor compounds. This study provides valuable insights into the effects of germination on IWG flour, showing a way for its broader use in food applications.

Predicting moisture content during maize nixtamalization using machine learning with NIR spectroscopy.

KEY MESSAGE: Moisture content during nixtamalization can be accurately predicted from NIR spectroscopy when coupled with a support vector machine (SVM) model, is strongly modulated by the environment, and has a complex genetic architecture. Lack of high-throughput phenotyping systems for determining moisture content during the maize nixtamalization cooking process has led to difficulty in breeding for this trait. This study provides a high-throughput, quantitative measure of kernel moisture content during nixtamalization based on NIR scanning of uncooked maize kernels. Machine learning was utilized to develop models based on the combination of NIR spectra and moisture content determined from a scaled-down benchtop cook method. A linear support vector machine (SVM) model with a Spearman's rank correlation coefficient of 0.852 between wet laboratory and predicted values was developed from 100 diverse temperate genotypes grown in replicate across two environments. This model was applied to NIR spectra data from 501 diverse temperate genotypes grown in replicate in five environments. Analysis of variance revealed environment explained the highest percent of the variation (51.5%), followed by genotype (15.6%) and genotype-by-environment interaction (11.2%). A genome-wide association study identified 26 significant loci across five environments that explained between 5.04% and 16.01% (average = 10.41%). However, genome-wide markers explained 10.54% to 45.99% (average = 31.68%) of the variation, indicating the genetic architecture of this trait is likely complex and controlled by many loci of small effect. This study provides a high-throughput method to evaluate moisture content during nixtamalization that is feasible at the scale of a breeding program and provides important information about the factors contributing to variation of this trait for breeders and food companies to make future strategies to improve this important processing trait.

Regional Variability in Sugar and Amino Acid Content of U.S. Soybeans and the Impact of Autoclaving on Reducing Sugars and Free Lysine.

Exploring the sugar and amino acid content variability and the influence of thermal processing on these in soybeans can help optimize their utilization in animal feed. This study examined 209 samples harvested in 2020 and 55 samples harvested in 2021 from across the U.S. to assess their sugar variability and amino acid variability. Harvest regions included the East Corn Belt, West Corn Belt, Mid-South, East Coast, and the Southeast of the U.S. In addition to the sugar and amino acid contents, protein, oil, and seed size were also analyzed. Samples from 2021 were evaluated for their sugar and amino acid contents before and after autoclaving the seeds at 105-110 °C for 15 min. For the samples harvested in 2020, sucrose (4.45 g 100 g-1) and stachyose (1.34 g 100 g-1) were the most prevalent sugars. For the samples harvested in 2021, L-arginine (9.82 g 100 g-1), leucine (5.29 g 100 g-1), and glutamate (4.90 g 100 g-1) were the most prevalent amino acids. Heat treatment resulted in an 8.47%, 20.88%, 11.18%, and 1.46% median loss of free lysine, sucrose, glucose, and fructose. This study's insights into the variability in sugar and amino acid content and the heat-induced changes in the nutritional composition of soybeans provide a reference for improving soybean quality assessment and optimizing its use in animal feed formulations in the U.S.

Starch Characteristics and Amylopectin Unit and Internal Chain Profiles of Indonesian Rice (Oryza sativa).

Indonesia is arguably a major player in worldwide rice production. Though white rice is the most predominantly cultivated, red, brown, and red rice are also very common. These types of rice are known to have different cooking properties that may be related to differences in their starch properties. Investigating the starch properties, especially the fine structure of their amylopectin, can help understand these differences. This study aims to investigate the starch characteristics of some Indonesian rice varieties by evaluating the starch granule morphology and size, molecular characteristics, amylopectin unit and internal chain profiles, and thermal properties. Starches were extracted from white rice (long grain (IR-64) and short grain (IR-42)), brown rice, red rice, and black rice cultivated in Java Island, Indonesia. IR-42 had the highest amylose content of 39.34% whilst the black rice had the least of 1.73%. The enthalpy of gelatinization and onset temperature of the gelatinization of starch granules were between 3.2 and 16.2 J/g and 60.1 to 73.8 °C, respectively. There were significant differences between the relative molar amounts of the internal chains of the samples. The two white rice and black rice had a significantly higher amount of A-chains, but a lower amount of B-chains and fingerprint B-chains (Bfp) than the brown and red rice. The average chain length (CL), short chain length (SCL), and external chain length (ECL) were significantly longer for the red rice and the black rice in comparison to both the white rice amylopectins. The long chain length (LCL) and internal chain length (ICL) of the sample amylopectins were similar. Rice starches were significantly different in the internal structure but not as much in their amylopectin unit chain profile. These results suggest the differences in their amylopectin clusters and building blocks.

Machine learning approach in predicting GlutoPeak test parameters from image data with AutoML and transfer learning.

This study introduces a novel machine learning methodology for predicting GlutoPeak test parameters from image data, leveraging AutoKeras and transfer learning. The GlutoPeak test is a tool used in the baking industry to evaluate the properties of flour, based on its gluten strength and elasticity. Our research aimed to devise an efficient and cost-effective technique for quantifying the gluten properties of wheat varieties. We aimed to accomplish this by predicting the GlutoPeak test results with convolutional neural network (CNN) models, utilizing the benefits of transfer learning and AutoKeras. AutoKeras is a public code repository capable of automating neural architecture search and hyperparameter tuning. The ResNet101 model, when trained with the Adam optimizer, achieved the highest accuracy of 0.5765 in the 2-class prediction. Meanwhile, the ResNet101 model trained with the SGD optimizer reached the highest accuracy of 0.4362 in the 4-class prediction. The outcomes of this study illustrate the possibility in using machine learning and deep learning techniques for predicting GlutoPeak test parameters from image data. This offers a faster and more cost-effective approach for evaluating gluten quality in wheat varieties.

Stability of starch-proanthocyanidin complexes to in-vitro amylase digestion after hydrothermal processing.

Proanthocyanidins (PA) form poorly digestible complexes with starch. The study examined amylase degradation mechanism and hydrothermal stability of starch-PA complexes. Sorghum-derived PA was complexed with wheat starch, reconstituted into flour (10% gluten added) and processed into crackers and pancakes. In vitro digestion profile of the complexes and products were characterized. The starch-PA complexes retained more (34-84%) fragments with degree of polymerization (DP) > 6,000 after 120 min digestion than controls (0-21%). Debranching further revealed higher retention of DP 11 - 30 chains in the digested starch-PA complexes than controls, suggesting amylopectin complexation contributed to reduced starch digestion. Starch-PA complexes retained reduced digestibility (50-56% higher resistant starch vs controls) in the cracker, but not pancake model. However, removing gluten from the pancake formulation restored the reduced digestibility of the starch-PA complexes. The starch-PA complexes are stable to hydrothermal processing, but can be disrupted by hydrophobic gluten proteins under excess moisture conditions.

Cold plasma technologies: Their effect on starch properties and industrial scale-up for starch modification.

Native starches have limited applications in the food industry due to their unreactive and insoluble nature. Cold plasma technology, including plasma-activated water (PAW), has been explored to modify starches to enhance their functional, thermal, molecular, morphological, and physicochemical properties. Atmospheric cold plasma and low-pressure plasma systems have been used to alter starches and have proven successful. This review provides an in-depth analysis of the different cold plasma setups employed for starch modifications. The effect of cold plasma technology application on starch characteristics is summarized. We also discussed the potential of plasma-activated water as a novel alternative for starch modification. This review provides information needed for the industrial scale-up of cold plasma technologies as an eco-friendly method of starch modification.

Structural characterization and enzymatic hydrolysis of radio frequency cold plasma treated starches.

The effect of carbon dioxide-argon radio frequency cold plasma treatment on the in vitro digestion and structural characteristics of granular and non-granular waxy maize, potato, and rice starches was investigated in this study. The effect on the fine structure of waxy potato was very minimal after plasma treatment irrespective of their granular or non-granular form. The short chain length (SCL) of waxy maize and rice (granular and non-granular) starches was reduced leading to subsequent increases in the long chain length (LCL). In vitro digestibility studies showed that cold plasma treatment enhanced (p < 0.05) the amount of slowly digestible starches (5.62%; 10.24%) and resistant starches (0.28%; 85.66%) in non-granular waxy maize (WMS NG) and granular waxy potato starches (WPS G), respectively. The amount of rapidly digestible starches increased in granular waxy maize starch (WMS G) (85.08%) but was unaffected in non-granular waxy rice (WRS NG), WPS G, and non-granular waxy potato starches after plasma treatment. FTIR-ATR data confirmed the ability of cold plasma to induce cross-linking in waxy starches specifically in WMS NG, WRS G, WRS NG, and WPS G. Overall, the unit and internal chain structure of the waxy starches were mostly unaffected by radio frequency plasma treatment. Cross-linking served as the dominant mechanism by which plasma altered the structure and digestibility of these starches. PRACTICAL APPLICATION: Cold plasma technology has been suggested as a green technique for starch modification. More research is, however, needed to facilitate the industrial scale up of this technology. In this study, we utilized a carbon dioxide-argon radio frequency cold plasma to modify waxy maize, rice and potato starches. Cold plasma treatment resulted in starches that were resistant to digestion and were highly cross-linked. The cross-linking would give the starches the ability to possibly withstand the high temperatures and shear that can be applied during industrial processing.

Temperature of plasma-activated water and its effect on the thermal and chemical surface properties of cereal and tuber starches.

High amylose and waxy starches from maize and potato were incubated with plasma-activated water (PAW) at 25 °C, 60 °C, and 80 °C temperatures to investigate PAW treatment effects on the starches' properties. At 60 °C incubation temperature, the starches were basically annealed with PAW. Annealing starches with PAW significantly increased (p < 0.05) the gelatinization parameters except for the enthalpy of gelatinization of waxy potato starch. Furthermore, starch swelling power significantly decreased while the water absorption capacity and solubility increased significantly when incubated at 80 °C. X-ray photoelectron spectroscopy (XPS) analysis showed the oxidation of C-C/C-H and C-O into carboxyl groups in waxy and high amylose maize starches incubated with PAW at 60 °C and 80 °C, respectively. In addition, cross-linking was observed in waxy maize and high amylose potato incubated with PAW at 80 °C and 25 °C, respectively. Overall, the results indicated PAW temperature is an important factor in modifying cereals and tuber starches with PAW.

Optimizing the extrusion conditions for the production of expanded intermediate wheatgrass (Thinopyrum intermedium) products.

In this study, the effects of extrusion conditions such as feed moisture content (20%, 24%, and 28%), screw speed (200, 300, and 400 rpm), and extrusion temperature (130, 150, and 170°C) on the physical and functional properties (moisture content, expansion ratio, bulk density, hardness, water absorption index [WAI], water solubility index [WSI]) of intermediate wheatgrass (IWG) were investigated for the first time. Response surface methodology was used to model and optimize the extrusion conditions to produce expanded IWG. The model coefficient of determination (R2 ) was high for all the responses (0.87-0.98). All the models were found to be significant (p < 0.05) and were validated with independent experiments. Generally, all the extrusion conditions were found to have significant effects on the IWG properties measured. Increasing the screw speed and decreasing the extrusion temperature resulted in IWG extrudates with a high expansion ratio. This also resulted in IWG extrudates with generally low hardness and bulk density. Screw speed was found to have the most significant effect on the WAI and WSI, with increasing screw speed resulting in a significant (p < 0.05) decrease in WAI and a significant (p < 0.05) increase in WSI. The optimum conditions for obtaining an IWG extrudate with a high expansion ratio and WAI were found to be 20% feed moisture, 200 -356 rpm screw speed, and 130-154°C extrusion temperature. PRACTICAL APPLICATION: Extrusion cooking was employed in the production of expanded IWG. This research could provide a foundation to produce expanded IWG, which can potentially be used as breakfast cereals and snacks. This is critical in the efforts to commercialize IWG for mainstream food applications.

Potential of Cold Plasma Technology in Ensuring the Safety of Foods and Agricultural Produce: A Review.

Cold plasma (CP) is generated when an electrical energy source is applied to a gas, resulting in the production of several reactive species such as ultraviolet photons, charged particles, radicals and other reactive nitrogen, oxygen, and hydrogen species. CP is a novel, non-thermal technology that has shown great potential for food decontamination and has also generated a lot of interest recently for a wide variety of food processing applications. This review discusses the potential use of CP in mainstream food applications to ensure food safety. The review focuses on the design elements of cold plasma technology, mode of action of CP, and types of CP technologies applicable to food applications. The applications of CP by the food industry have been demonstrated for food decontamination, pesticide residue removal, enzyme inactivation, toxin removal, and food packaging modifications. Particularly for food processing, CP is effective against major foodborne pathogenic micro-organisms such as Listeria monocytogenes and Salmonella Typhimurium, Tulane virus in romaine lettuce, Escherichia coli O157:H7, Campylobacter jejuni, and Salmonella spp. in meat and meat products, and fruits and vegetables. However, some limitations such as lipid oxidation in fish, degradation of the oligosaccharides in the juice have been reported with the use of CP, and for these reasons, further research is needed to mitigate these negative effects. Furthermore, more research is needed to maximize its potential.

Variation in Lignin, Cell Wall-Bound p-Coumaric, and Ferulic Acid in the Nodes and Internodes of Cereals and Their Impact on Lodging.

Understanding the contribution of stem cell wall components to lodging is important in developing breeding programs aimed at reducing lodging in cereal crops. This study is one of the first to investigate the correlation between the amounts of cell wall-bound ferulic acid, p-coumaric acid, and lignin in the nodes and internodes of cereals (oat, wheat, and barley) and their lodging susceptibility during grain fill. All samples, except two-row barley, were susceptible to lodging and expressed a significantly lower stalk strength. Lignin and phenolic contents between nodes and internodes of all samples were significantly different, with internodes having higher amounts (5.5-7.0 and 10.9-16.2 µg/g p-coumaric acid, and 2.5-3.2 and 3.9-7.1 µg/g ferulic acid in nodes and internodes, respectively). The acid-soluble lignin content was different between nodes and internodes but not between crops. This data set did not correlate with lodging classification, possibly due to sample size and type.

Small differences in amylopectin fine structure may explain large functional differences of starch.

Four amylose-free waxy rice starches were found to give rise to gels with clearly different morphology after storage for seven days at 4°C. The thermal and rheological properties of these gels were also different. This was remarkable in light of the subtle differences in the molecular structure of the amylopectin in the samples. Addition of iodine to the amylopectin samples suggested that not only external chains, but also the internal chains of amylopectin, could form helical inclusion complexes. It is suggested that these internal helical segments participate in the retrogradation of amylopectin, thereby stabilising the gels through double helical structures with external chains of adjacent molecules. Albeit few in number, such interactions appear to have important influences on starch functional properties.