Search Results (36)

The utilization of brown rice from long-term stored paddy is severely limited by lipid deterioration, which is primarily characterized by a high free fatty acid value (FAV). Although microwave treatment shows promise in mitigating lipid deterioration, its underlying mechanism in degraded grains remains poorly understood. This study systematically investigated the efficacy and mechanism of microwave treatment using a multi-analytical approach. Brown rice from long-term stored paddy (Longjing-46, stored for 6 years) was treated using a laboratory microwave oven (420 W or 560 W, 1–5 min). The reduction in FAV was quantified, lipid structural changes were analyzed by FT-IR spectroscopy, and lipid metabolic alterations were profiled using untargeted lipidomics. Results showed that microwave treatment significantly reduced FAV in a time- and power-dependent manner, with a maximum reduction of 76.3%. Treatment at 420 W for 4 min was identified as the optimal condition. FT-IR analysis confirmed that the treatment inhibited lipid oxidation and hydrolysis at the molecular level. Importantly, lipidomics revealed that the mechanism extended beyond simple enzyme inactivation. Microwave treatment induced a reprogramming of the lipid metabolic network, characterized by the synergistic downregulation of key lipid species and the activation of the autophagy pathway. This study provides a comprehensive, lipid-centric explanation of microwave-mediated quality improvement in long-term stored brown rice, integrating enzyme inactivation with metabolic network reprogramming. The findings offer a novel scientific basis for applying this technology to valorize degraded grain stocks, contributing to the reduction in postharvest loss. Full article

Wheat and rice are major sources of human nutrition worldwide. Solid-state fermentation (SSF) with lignocellulolytic mushrooms can enhance their nutritional value and increase their functional properties. However, this technology is not yet widely applied. In this work, whole wheat and brown rice hydrated to 60% were used as substrates for the edible mushroom Pleurotus ostreatus and the medicinal Ganoderma sessile, which were incubated for 14 days at 25 °C in the dark. The fermented substrate biomass was incorporated into standard sugar-snap cookie recipes, substituting 20% of the wheat flour. We evaluated the technological and nutritional properties of alternative fermented flours and cookies. Both the fermented flours and cookies exhibited increased soluble and total protein content, antioxidant power, and phenol content, indicating overall functional improvement. Fermented G. sessile flour also showed increased triterpenoid content. The physical quality of cookies remained within expected ranges, demonstrating the feasibility of the application. These results highlight the potential of SSF as a method for nutritional and functional enrichment of grains and extend the health benefits of mushrooms to populations relying on low-cost, grain-derived carbohydrates. Further studies on digestibility and in vivo activity of metabolites are needed to confirm the potential health benefits of fermented flours. Full article

Extruded whole flours from blends of cereals and pulses have great potential to be key ingredients in the development of more innovative gluten-free products, both from a technological and nutritional perspective. The objective of this work was to obtain pre-cooked flours from four formulations based on blends of whole cereals (PR: parboiled brown rice; PM: pearl millet) and pulses (CP: chickpea; CB: common bean). CB was fixed at 10%, and the other components (PR-PM-CP) were set at 60-15-15 (F1), 15-60-15 (F2), 15-15-60 (F3), and 30-30-30 (F4), which were extruded at two combined conditions of feed moisture and screw speed: mild E1 (30% and 300 rpm) and severe E2 (18% and 600 rpm). The temperature profile was kept constant from 25 to 130 °C (from feed to output). The protein, dietary fiber, and ash contents in the raw formulations varied from 11.2 to 17.4%, 9.8 to 15.0%, and 2.2 to 3.3%, respectively, according to the low or high pulse content in the blend. As more mechanical energy was delivered to the raw formulations (W·h/kg, 63.7 for E1 and 179.4 for E2), the extruded particles had increased water absorption (g/g) from 1.7 to 4.5 (E1) or 3.8 (E2), increased water solubility due to E2 from 10.9 to 20.9%, and decreased oil absorption (g/g) from 1.5 to 0.9 (E1 and E2). The peak viscosity (PV, cP) was noticeable only in the raw formulation F2 (355), which decreased 10.3% due to E1. In the other formulations, PV appeared due to E1 in F1 (528), F3 (420), and F4 (371), while it disappeared due to E2 in all formulations. However, at the E2 condition, they did show cold viscosity in the initial stage (222 to 394 cP). The final viscosity (FV, cP) decreased from 795 to 390 (E1) or 123 (E2). In F2, the contents of phenolic compounds (285 µg GAE/g) and ABTS⁺ (13.2 μmol TE/g) were more than twice that in the other formulations, and their respective degradations were low due to E1 (4.2 and 12%) and high due to E2 (16 and 17%). Extrusion cooking did not cause significant changes in the luminosity (81) and redness (0.9) of particles, while yellowness increased from 15.7 to 18.2 (E1) or 18.7 (E2). Based on these findings, it is concluded that both extrusion conditions improved the technological and functional properties. Regarding the formulations, F2 stood out for being rich in antioxidant capacity, which poorly degraded under the conditions studied. Further work is needed to contribute to understanding the optimization of formulas and processes that would improve the nutritional, sensorial, and functional properties while still preserving the bioactive value of the final products. Full article

In recent years, as two globally recognized green grain storage technologies, CO₂-modified atmosphere (CO₂) storage and temperature-controlled (TC) storage have gained prominence. However, research on their integrated application remains limited. This study monitored quality dynamics and microbial activity in rice stored for 360 days under CO₂ + TC versus conventional storage (control), with analyses conducted at stratified sampling points (upper, middle, and lower layers). Compared to conventional storage, CO₂ + TC preserved rice color more effectively, while retarding the increase in fatty acid value and the decline in brown rice yield, head rice yield, and germination percentage. Furthermore, CO₂ + TC storage effectively suppresses the proliferation of Fusarium and Aspergillus, thereby retarding aflatoxin B1 (AFB1) accumulation by inhibiting fungal metabolic activity. Non-targeted metabolomics analysis further verified that CO₂ + TC storage enhanced rice antioxidant capacity and disease resistance by modulating amino acid, carbohydrate, and linolipid metabolic pathways. This technology effectively maintained nutrient retention (e.g., amino acids and proteins) and delayed quality deterioration in stored rice. These findings elucidated the underlying mechanism of CO₂ + TC on rice quality, offering a novel perspective for grain storage technology. Full article

Rice has excellent nutritional quality as a dietary food and is easily puffed. The aim of this study was to investigate the effects of puffing technology on the physicochemical parameters, structure properties and volatile components of brown rice (BR) and refined rice (RR). XRD and FT-IR spectroscopic data demonstrated that puffing under high temperature and pressure conditions triggered starch gelatinization, concurrently reducing starch crystallinity and inducing a V-type polymorphic structure. In addition, it substantially weakened hydrogen bonding networks in rice flour. In detail, 136 volatile compounds of raw and puffed rice were analyzed by HS-SPME-GC-MS, and the results showed that aldehydes, ketones, and pyrazines were the main volatile aroma compounds after puffing. By correlation analysis, benzaldehyde, 2-octenal, 2-methoxy-phenol, and furfural were identified as key contributors. The volatile components, especially ketones and alcohols, were higher in the BR as compared to those in the RR, with a significant difference observed between the two (p < 0.05). Combined with sensory evaluation, 1212CH was found to have a high score (17.63). These results could provide a theoretical basis for understanding the effect of puffing on rice flour and the volatile components of puffed products. Full article

Insects and their bacterial endosymbionts form intricate ecological relationships, yet their role in host–pathogen interactions are not fully elucidated. The small brown planthopper (Laodelphax striatellus), a polyphagous pest of cereal crops, acts as a key vector for rice stripe virus (RSV), a significant threat to rice production. This study aimed to compare the endosymbiont community structures of nonviruliferous and RSV-viruliferous L. striatellus populations using 16S rRNA gene sequencing with high-throughput sequencing technology. Wolbachia was highly dominant in both groups; however, the prevalence of other endosymbionts, specifically Rickettsia and Burkholderia, differed markedly depending on RSV infection. Comprehensive microbial diversity and composition analyses revealed distinct community structures between nonviruliferous and RSV-viruliferous populations, highlighting potential interactions and implications for vector competence and virus transmission dynamics. These findings contribute to understanding virus-insect-endosymbiont dynamics and could inform strategies to mitigate viral spread by targeting symbiotic bacteria. Full article

Three-dimensional (3D) food printing (3DFP) is an emerging technology that enables the creation of personalized and functional foods by precisely controlling nutritional content and shape. This study investigated the 3D printability and rheological behavior of cereal–legume starch-based gels formulated with germinated brown rice (GBR) and red adzuki bean (RAB) flours, supplemented with xanthan and guar gums as functional additives. The physicochemical and structural properties of the gels were characterized through FT-IR, rheology, texture analysis, SEM, and sensory evaluation. In addition, the 3D printing fidelity, rheological behavior, color attributes, textural properties, microstructure, and sensory scoring of the printed products were evaluated. The results indicated that the gels exhibited pseudoplastic behavior, with the RABF/GBRF ratio of 1:2 (RG1:2) formulation showing optimal color properties (ΔE* = 0.60 ± 0.86) and the RABF/GBRF ratio of 2:1 (RG2:1) formulation demonstrating superior printing fidelity and structural stability (printing accuracy = 99.37 ± 0.39%). The gels’ mechanical properties, such as hardness and chewiness, were significantly influenced by the RABF and GBRF ratios, with RG2:1 exhibiting the highest hardness (1066.74 ± 102.09) and RG1:2 showing the best springiness (0.64 ± 0.10). The sensory evaluation results indicated that the RABF/GBRF ratios of 1:1 (RG1:1) and RG1:2 had relatively high overall acceptance scores. These findings indicate that specific ratios of RABF and GBRF improve the 3D printability and textural properties of cereal–legume starch-based gels, enhancing their suitability for 3D food printing applications. This study provides valuable insights into the development of personalized and functional cereal–legume starch-based foods using 3DFP technology. Full article

Germinated brown rice (GBR), rich in high starch content and bioactive compounds, has excellent gel-forming properties, rendering it highly promising for applications in food 3D printing, a cutting-edge personalized manufacturing technology. This study systematically investigates the effects of different concentrations of konjac glucomannan (KGM) and curdlan (CD) blends on the 3D printing performance and physicochemical properties of GBR gel. The results indicated that the appropriate addition of KGM/CD blends significantly enhances the printing accuracy and shape retention of GBR gel. Specifically, under the KGM to CD ratio of 3:1 (KC3) formulation obtained by combining 2.25% KGM and 0.75% CD, the printing accuracy was highest with a minimized error of 4.97 ± 0.45%, and optimal structural stability was maintained within 5 h post-printing. Rheological measurements revealed that the flow behavior index (n) of the KC3 system was 0.049 ± 0.014, indicating superior flowability and significantly improved overall rheological stability. Additionally, the blend system not only increased the hardness and gel elasticity of the GBR gel but also significantly enhanced its cohesiveness and adhesiveness, reaching the highest values of 0.323 ± 0.02 and −217.488 ± 22.499, respectively, in the KC3 formulation. Further thermal analysis, low-field nuclear magnetic resonance analysis, along with Fourier-transform infrared spectroscopy and scanning electron microscopy observations, collectively demonstrated that the KGM/CD blend effectively reinforced the stability of the GBR gel network structure. These findings provide theoretical support for optimizing GBR applications in food 3D printing. Full article

This study explores the potential of some commercially available plant proteins to increase the protein content of gluten free cookies produced from green lentil flour. Isolates from hemp seed, brown rice, yellow pea, and pumpkin seed were investigated. Cookies were additionally enriched with inulin and matcha tea. Products were characterized in terms of physicochemical parameters (e.g., crude protein content, total phenolics and flavonoids, antioxidant activity, and color). Additionally, technological properties including geometry, baking loss, and texture profile were determined, and a sensory profile test was conducted. The replacement of a quarter of lentil flour with plant proteins increased the protein content (control: 12.4% vs. 15.1–20.4%), but suppressed the polyphenol content, resulting in reduced antioxidant capacity (3.13 vs. 2.14–2.69 mmol TE/100 g). The geometry, texture properties, and color of the cookies were affected by all the proteins investigated. The biggest difference was shown in the case of using yellow pea (YP) protein, which showed the highest browning index (YP: 66.36 vs. 42.63–63.45) and spread ratio (8.38 vs. 5.63–6.39) among the samples tested. The sensory attributes of the cookies, such as tea notes, surface homogeneity, crunchiness, and crumbliness, proved to be negatively affected by the plant proteins, which may be a limitation for consumer acceptance. Full article

Rice leaf diseases critically threaten global rice production by reducing crop yield and quality. Efficient disease detection in complex field environments remains a persistent challenge for sustainable agriculture. Existing deep learning-based methods for rice leaf disease detection struggle with inadequate sensitivity to subtle disease features, high computational complexity, and degraded accuracy under complex field conditions, such as background interference and fine-grained disease variations. To address these limitations, this research aims to develop a lightweight yet high-accuracy detection model tailored for complex field environments that balances computational efficiency with robust performance. We propose RDRM-YOLO, an enhanced YOLOv5-based network, integrating four key improvements: (i) a cross-stage partial network fusion module (Hor-BNFA) is integrated within the backbone network’s feature extraction stage to enhance the model’s ability to capture disease-specific features; (ii) a spatial depth conversion convolution (SPDConv) is introduced to expand the receptive field, enhancing the extraction of fine-grained features, particularly from small disease spots; (iii) SPDConv is also integrated into the neck network, where the standard convolution is replaced with a lightweight GsConv to increase the accuracy of disease localization, category prediction, and inference speed; and (iv) the WIoU Loss function is adopted in place of CIoU Loss to accelerate convergence and enhance detection accuracy. The model is trained and evaluated utilizing a comprehensive dataset of 5930 field-collected and augmented sample images comprising four prevalent rice leaf diseases: bacterial blight, leaf blast, brown spot, and tungro. Experimental results demonstrate that our proposed RDRM-YOLO model achieves state-of-the-art performance with a detection accuracy of 94.3%, and a recall of 89.6%. Furthermore, it achieves a mean Average Precision (mAP) of 93.5%, while maintaining a compact model size of merely 7.9 MB. Compared to Faster R-CNN, YOLOv6, YOLOv7, and YOLOv8 models, the RDRM-YOLO model demonstrates faster convergence and achieves the optimal result values in Precision, Recall, mAP, model size, and inference speed. This work provides a practical solution for real-time rice disease monitoring in agricultural fields, offering a very effective balance between model simplicity and detection performance. The proposed enhancements are readily adaptable to other crop disease detection tasks, thereby contributing to the advancement of precision agriculture technologies. Full article

Background: Oryza sativa L. is one of the main staple crops in the South Korea. While rice production has remained stable over the past decades, rice consumption has gradually declined, leading to a rapid stockpile in rice inventory. Conventional rice storage methods often fail to preserve functional properties and long-term stability, necessitating innovative processing techniques. Methods: To address this issue, we developed a grain stabilization technique (GST) to enhance the functionality and shelf life of white rice (WR), brown rice (BR), and rice germ (RG). The GST process was conducted in a single-batch system, integrating a controlled temperature cycle (65~85 °C) with 60 rpm rotation, far-infrared (26,400 W/m²), and ultraviolet (254 nm, 60,880 J/m²) irradiation in an enclosed chamber equipped with an exhaust system for moisture, odor, and impurity removal. The process was followed by air drying (25 °C, 15 h) to ensure stability. Results: The GST significantly increased resistant starch content in BR and WR by 214% and 27%, respectively, but not in RG. Additionally, GST enhanced the contents of campesterol, stigmasterol, β-sitosterol, and octacosanol in BR and RG, but not significantly in WR. Furthermore, this technique markedly reduced moisture content, acidity, and bacterial counts over a 90-day storage period and kept mycotoxin levels within safe limits in WR, BR, and RG. GST also altered the microstructures of WR and BR, indicating gelatinization and amorphization of starch granules. Conclusions: These findings contribute to advancing food science by presenting GST as a transformative method to extend shelf life and improve the nutritional profile of rice, aligning with global efforts to reduce food waste, improve dietary health, and develop sustainable food processing technologies. Full article

Malted grains subjected to extrusion technology could have better quality indices than non-malted grains. The effects of malting and extrusion on the functional and physical qualities of foods extruded from malted brown rice and pigeon pea flour blends were investigated. Malted pigeon pea and brown rice flours were processed into blends, extruded under various conditions of feed moisture levels (15–20), feed compositions (8–30%), and barrel temperatures (100–130 °C), and analyzed using Response Surface Methodology with a Box–Behnken design. The impacts of malting and extrusion were assessed on the following functional qualities: bulk density, rheology, swelling capacity, water absorption capacity, and solubility. The physical quality assessment included a 2-D photographic representation of the extrudates, a microscopic assessment of their internal structure, expansion index, color parameters (L*, a*, b*), and alterations in the color index. Increased feed moisture, malted pigeon pea, and decreased barrel temperature resulted in a higher bulk density (0.72 to 0.84 g/cm³) of the extrudates. There was a decrease in water absorption capacity (6.82–4.49%) with an increase in barrel temperature above 100 °C. All the samples showed a decrease in viscosity with increasing shear rate. At low barrel temperatures, feed compositions, and feed moistures, extrusion led to increases in the expansion index (3.5 to 12.94) and the color lightness (66.83–81.71) of the extrudates. Samples with a higher proportion of malted brown rice showed a higher expansion index, lower bulk density, and lighter color of the extrudates. Full article

Cadmium (Cd) is a highly toxic metal that is difficult to completely eliminate from soil, despite advancements in modern agricultural and environmental technologies that have successfully reduced Cd levels. However, rice remains a key source of Cd exposure for humans. Even small amounts of Cd absorbed by rice can pose a potential health risk to the human body. Laser-induced breakdown spectroscopy (LIBS) has the advantages of simple sample preparation and fast analysis, which, combined with the transfer learning method, is expected to realize the real-time and rapid detection of low-level heavy metals in rice. In this work, 21 groups of naturally matured rice samples from potentially Cd-contaminated environments were collected. These samples were processed into rice husk, brown rice, and polished rice groups, and the reference Cd content was measured by ICP-MS. The XGBoost algorithm, known for its excellent performance in handling high-dimensional data and nonlinear relationships, was applied to construct both the XGBoost base model and the XGBoost-based transfer learning model to predict Cd content in brown rice and polished rice. By pre-training on rice husk source data, the XGBoost-based transfer learning model can learn from the abundant information available in rice husk to improve Cd quantification in rice grain. For brown rice, the XGBoost base model achieved R_C² of 0.9852 and R_P² of 0.8778, which were improved to 0.9885 and 0.9743, respectively, with the XGBoost-based transfer learning model. In the case of polished rice, the base model achieved R_C² of 0.9838 and R_P² of 0.8683, while the transfer learning model enhanced these to 0.9883 and 0.9699, respectively. The results indicate that the transfer learning method not only improves the detection capability for low Cd content in rice but also provides new insights for food safety detection. Full article

The technology for reducing cadmium (Cd) contamination in rice is being explored globally. In this study, the ratios of nitrogen fertilizers used were 5:5:0:0 (T1), 4:4:2:0 (T2), 6:0:2:2 (T3), and 3:2:2:3 (T4). The objective of the pot experiment was to understand how nitrogen management can reduce Cd accumulation in rice by influencing soil pH, the bioavailability of Cd concentrations in soil, Cd adsorption by iron membranes on rice roots, and the transport of mineral elements. The results indicated that nitrogen fertilizer application acidifies the soil and increases the bioavailable Cd concentration. A correlation analysis revealed a significant positive correlation between Cd concentration in the Fe plaque on rice roots and Cd concentration in the roots. Overall, the application of nitrogen fertilizers increased the concentrations of Cd and mineral elements in rice tissues, particularly in Cu, Mn, and Zn, but reduced the transfer of Cd between tissues. After nitrogen application, the concentrations of mineral elements in brown rice significantly increased, with negative correlations being observed between the Cu, Mn, and Zn concentrations and Cd concentration in brown rice. The brown rice with a nitrogen fertilizer proportion of 6:0:2:2 exhibited the lowest Cd concentration, showing significant reductions of 48.04% (X13H) and 43.46% (YZX) compared to the control treatment. These findings suggest that nitrogen management can enhance the coefficients of mineral element uptake in rice, compete against the transport of Cd to the grains, and that late-growth-stage nitrogen application can be more effective in reducing Cd concentration in brown rice. Full article

The brown planthopper (Nilaparvata lugens, BPH) is a serious insect pest responsible for causing immense economic losses to rice growers around the globe. The development of high-throughput sequencing technologies has significantly improved the research on this pest, and its genome structure, gene expression profiles, and host–plant interactions are being unveiled. The integration of genomic sequencing, transcriptomics, proteomics, and metabolomics has greatly increased our understanding of the biological characteristics of planthoppers, which will benefit the identification of resistant rice varieties and strategies for their control. Strategies like more optimal genome assembly and single-cell RNA-seq help to update our knowledge of gene control structure and cell type-specific usage, shedding light on how planthoppers adjust as well. However, to date, a comprehensive genome-wide investigation of the genetic interactions and population dynamics of BPHs has yet to be exhaustively performed using these next-generation omics technologies. This review summarizes the recent advances and new perspectives regarding the use of omics data for the BPH, with specific emphasis on the integration of both fields to help develop more sustainable pest management strategies. These findings, in combination with those of post-transcriptional and translational modifications involving non-coding RNAs as well as epigenetic variations, further detail intricate host–brown planthopper interaction dynamics, especially regarding resistant rice varieties. Finally, the symbiogenesis of the symbiotic microbial community in a planthopper can be characterized through metagenomic approaches, and its importance in enhancing virulence traits would offer novel opportunities for plant protection by manipulating host–microbe interactions. The concerted diverse omics approaches collectively identified the holistic and complex mechanisms of virulence variation in BPHs, which enables efficient deployment into rice resistance breeding as well as sustainable pest management. Full article