Search Results (1,752)

Rice blast, caused by the fungal pathogen Pyricularia oryzae, remains one of the most destructive diseases threatening global rice production. Although the deployment of resistant cultivars is widely regarded as the most effective and sustainable control strategy, resistance based solely on host genetics often has limited durability due to the rapid adaptation of the pathogen. Increasing evidence suggests that plant-associated microbial communities contribute to host health and disease resistance, yet the role of seed-associated microbiota in shaping rice blast resistance remains insufficiently understood. In this study, we investigated seed endophytic bacterial communities across multiple indica–japonica hybrid rice varieties from the Yongyou series that exhibit contrasting levels of resistance to rice blast. By integrating amplicon sequencing, we identified distinct seed bacterial assemblages associated with blast-resistant and blast-susceptible varieties were identified. Notably, the microbial communities in blast-resistant varieties exhibited significantly higher Shannon index, with a median value of 3.478 compared to 2.654 in susceptible varieties (p < 0.001), indicating a greater diversity and more balanced community structure compared to those in susceptible varieties. Several bacterial taxa consistently enriched in resistant varieties showed negative ecological associations with P. oryzae, both at the local scale and across publicly available global metagenomic datasets. These findings indicate that seed endophytic bacterial communities are non-randomly structured in relation to host resistance phenotypes and may contribute to rice blast resistance through persistent ecological interactions with the pathogen. This work highlights the potential importance of seed-associated microbiota as intrinsic components of varietal resistance and provides a microbial perspective for improving durable disease resistance in rice breeding programs. Full article

Speed breeding represents a pivotal technology for enhancing crop breeding efficiency. This study systematically examined the regulation of LED light environments, planting density, and gibberellic acid (GA₃) on rice growth cycle progression in plant factories, establishing an integrated speed breeding protocol. The experimental design comprised three components: (1) coupling seedling age (9–25 days, variety-dependent) with LED environments and planting densities (25–100 plants/tray); (2) combining light intensity gradients (450 and 900 μmol·m⁻²·s⁻¹) with photoperiod control; (3) applying GA₃ gradients (0–120 ppm) to enhance immature seed germination. Results indicated that high planting densities (>50 plants/tray) prolonged the growth cycle and decreased yield, whereas 25 plants/tray optimally balanced growth cycle shortening and yield maximization. Under short-day induction, Nipponbare (Nip) and Wufeng B (WFB) reached heading at 39 and 58 days after sowing (DAS), respectively. Stage-specific light responses were observed: 450 μmol·m⁻²·s⁻¹ during the basic vegetative phase (BVP) promoted morphological development, whereas 900 μmol·m⁻²·s⁻¹ during the photoperiod-sensitive phase (PSP) accelerated tillering and panicle differentiation. GA₃ treatment (60 ppm) enhanced the germination rate of immature seeds by 31%. The optimized lightregimes comprised natural light + 900 μmol·m⁻²·s⁻¹ (NL–900) and 450 μmol·m⁻²·s⁻¹ + 900 μmol·m⁻²·s⁻¹ (450–900), combined with density control (25 plants/tray) and GA₃-mediated immature seed utilization, shortened the generation time to 54 days and 70 days for Nip and WFB, respectively. This integrated protocol establishes an efficient strategy for rice speed breeding in plant factories. Full article

Temperature and relative humidity can significantly affect quality of paddy rice during storage. Limited studies established the link between storage time, environmental fluctuations, changes in grain and flour physicochemical properties, and culinary performances. In a West African context, IR 841 paddy rice variety was stored under humid–sub-humid (HSH), and dry (DRY) conditions for 12 months. Over 12 months, rice stored under DRY conditions experienced greater environmental fluctuations than rice stored under HSH conditions. Grain water absorption capacity (WAC) increased during storage under DRY conditions, rising from 3.3 ± 0.3 to 3.8 ± 0.3 g/g DM between 0 and 12 months. Flour amylose content and soluble solids remained relatively stable from month 0 to 6 in all conditions, and further under HSH conditions. The observed changes led to improved grain cooking performance after 6 months of storage under DRY conditions. After 12 months, a decrease in rice flour WAC and a peak in viscosity were observed, while mean particle size increased from 42 ± 1 to 67 ± 3 μm under HSH conditions and from 31 ± 3 to 83 ± 3 μm under DRY conditions. Storage time may reduce the breadmaking capacity of rice flour. Overall, environmental fluctuations under DRY conditions strongly affected rice grain and flour properties. Full article

This study examines the socio-demographic characteristics, rice production practices, and breeding preferences of farmers across three major rice-growing regions of Vietnam: the Mekong Delta, Central Vietnam, and North Vietnam. A survey of 109 rice farmers captured information on cultivation status, livelihood activities, and preferred breeding traits for rice improvement. The results reveal clear regional differentiation in farm structure, production objectives, and varietal preferences. Rice farming in the Mekong Delta is predominantly commercially oriented, characterized by larger landholdings and greater male participation, whereas rice production in Central and Northern Vietnam is more subsistence-oriented, with higher female involvement. Farmers across regions consistently valued locally adapted rice varieties, but articulated region-specific trait priorities shaped by agro-ecological conditions. In the Mekong Delta, preferences emphasized soft grain quality and salinity tolerance, reflecting coastal production constraints. In Central Vietnam, farmers prioritized heat tolerance and resistance to pests and diseases, while in Northern Vietnam, cold tolerance and grain quality attributes, including aroma and harder texture, were most important. Major biotic stresses, particularly blast and bacterial blight, also showed significant regional variation in reported incidence. By linking these region-specific preferences to clearly defined Target Populations of Environments (TPEs), this study provides a practical framework for aligning breeding targets with real-world production conditions. The findings offer actionable guidance for participatory breeding and decentralized varietal evaluation under the Biodiversity for Opportunities, Livelihoods, and Development (BOLD) initiative, as well as other rice improvement programs. To our knowledge, this represents the first multi-region evidence from Vietnam that systematically integrates agro-ecological variation with a TPE-based breeding approach, supporting the development of climate-resilient, farmer-preferred rice varieties and more sustainable rice production systems. Full article

Rice blast and bacterial blight cause severe harm to rice production, and the breeding of resistant varieties guarantees the safety of rice production. Meanwhile, multigene pyramiding breeding based on molecular marker-assisted selection is a crucial approach for rice breeding to combat multiple diseases. This study aimed to develop accurate and efficient PARMS markers for rice blast resistance genes Pita, Pigm, and Pi2, and bacterial blight resistance gene Xa23. A systematic genotyping analysis of the resistant alleles of these 4 genes was performed on 384 major cultivated varieties in production. The results showed that only 5.21% of the varieties harbored more than two resistant alleles simultaneously. Using traditional breeding strategies in combination with the developed PARMS markers, the high-quality three-line male sterile line Ruanfeng A (pyramiding Pita and Pigm) and the strong restorer line Gui 610 (pyramiding Pi2 and Xa23) were bred. Crossing these lines produced a new hybrid rice variety, Ruanfengyou 610. Ruanfengyou 610 pyramids 4 resistance genes (Pita/Pigm/Pi2/Xa23), exhibits resistance to both rice blast and bacterial blight, has prominent heterosis and excellent grain quality, and has strong application potential, which is of great significance for ensuring the safety of rice production. Full article

Farmers’ perceptions of improved rice varieties represent a critical initial step in their adoption as climate change adaptation strategies. This study examined farmers’ perceptions by integrating on-farm adaptive research, which compared the agronomic performance of rice varieties, with participatory approaches to capture farmers’ evaluation of improved varieties. A total of 81 farmers from climate-affected areas of Batang Regency were purposively selected as respondents. Data was collected through structured interviews and questionnaires administered during the evaluation of field demonstrations. Farmers’ perception levels were assessed using a Guttman scale and classified into three categories: high, medium, and low. Logistic regression analysis was subsequently employed to examine the relationship between farmers’ socio-demographic characteristics and their acceptance of improved rice varieties. The results indicate that, overall, farmers exhibited a low perception of improved rice varieties. Among the evaluated opinions, Inpari 32 HDB received the highest perception scores across all agronomic attributes. The regression results show that farm size and age significantly influence variety acceptance. The odds ratio for farm size (0.117) suggests that each additional hectare of cultivated land area reduces the likelihood of adopting improved rice varieties by approximately 88.3%, holding other factors constant. In contrast, the odds ratio for age (1.080) indicates that each additional year of age increases the probability of adoption by about 8%. Full article

Rice is a key food crop worldwide, but its yield and quality are severely constrained by insect pests. As environmental and regulatory restrictions on chemical pesticides grow, developing insect-resistant rice varieties has become a sustainable way to protect food security. This review covers recent progress in functional genomics and molecular marker mapping related to insect resistance in rice. We highlight the identification, cloning, and functional analysis of resistance genes targeting major pests, including the brown planthopper, rice gall midge, white-backed planthopper, small brown planthopper, and rice leaf roller. Several important resistance genes (such as Bph14, Bph3, and Bph29) have been cloned, and their roles in rice immunity have been clarified—covering insect feeding signal recognition, activation of salicylic acid and jasmonic acid pathways, and regulation of MAPK cascades, calcium signaling, and reactive oxygen species production. We also discuss how molecular marker-assisted selection, gene pyramiding, and transgenic techniques are used in modern rice breeding. Finally, we address future challenges and opportunities, stressing the importance of utilizing wild rice germplasm, understanding insect effector–plant immune interactions, and applying molecular design breeding to create long-lasting insect-resistant rice varieties that can withstand changing pest pressures and climate conditions. Full article

In the field of precision agriculture, accurately detecting rice panicles is crucial for monitoring rice growth and managing rice production. To address the challenges posed by complex field backgrounds, including variety differences, variations across growth stages, background interference, and occlusion due to dense distribution, this study develops an improved YOLO11-based rice panicle detection model, termed DRPU-YOLO11. The model incorporates a task-oriented CSP-PGMA module in the backbone to enhance multi-scale feature extraction and provide richer representations for downstream detection. In the neck network, DySample and CGDown are adopted to strengthen global contextual feature aggregation and suppress background interference for small targets. Furthermore, fine-grained P2 level information is integrated with higher-level features through a cross-scale fusion module (CSP-ONMK) to improve detection robustness in dense and occluded scenes. In addition, the PowerTAL strategy adapts quality-aware label assignment to emphasize high-quality predictions during training. The experimental results based on a self-constructed dataset demonstrate that DRPU-YOLO11 significantly outperforms baseline models in rice panicle detection under complex field environments, achieving an accuracy of 82.5%. Compared with the baseline model YOLO11 and RT-DETR, the mAP₅₀ increases by 2.4% and 5.0%, respectively. These results indicate that the proposed task-driven design provides a practical and high-precision solution for rice panicle detection, with potential applications in rice growth monitoring and yield estimation. Full article

Rice bran oil (RBO) is increasingly valued for its bioactive constituents and associated health benefits. This study presents a comprehensive comparative analysis of RBOs derived from purple (PRBO), red (RRBO), and white (WRBO) rice bran, focusing on their physicochemical properties, fatty-acid profiles, bioactive components, antioxidant activity, oxidative stability, and lipidomics. Our results demonstrate that PRBO consistently exhibited a more favorable fatty-acid composition, characterized by a higher proportion of unsaturated fatty acids and significantly greater concentrations of bioactive compounds (including tocopherols/tocotrienols, γ-oryzanol, phytosterols, and squalene). Accordingly, PRBO showed the highest radical-scavenging activity and storage oxidative stability, followed by RRBO and WRBO. Additionally, untargeted lipidomics using UPLC–MS–MS identified 2908 lipid species spanning 57 subclasses and revealed distinct variety-specific lipid signatures. PRBO was uniquely enriched in lipid species such as ceramide phosphate (CerP) and monogalactosyldiacylglycerol (MGDG). RRBO was characterized by a distinct abundance of sitosteryl esters (SiE), phosphatidic acid (PA), and cardiolipin (CL), while WRBO was distinguished by phosphatidylethanol (PEt), lysodimethylphosphatidylethanolamine (LdMePE), and sphingomyelin (SM). Overall, PRBO possessed not only a broader repertoire of lipid species but also higher relative abundances of nutritionally significant lipids. These results enable quality evaluation and varietal authentication of colored RBOs and guide their targeted use in health-oriented foods and nutritional interventions. Full article

Mechanical deep fertilization is an efficient fertilization method. However, the effects of different types of nitrogen fertilizer on rice grain yield and nitrogen use efficiency under deep-application conditions remain unclear. In this study, field experiments were carried out in 2021 and 2022. The experimental treatments consisted of three types of nitrogen fertilizer, i.e., urea (T1), slow/controlled-release fertilizer (T2), and super rice special fertilizer (T3), applied at a rate of 150 kg N ha⁻¹ via mechanical deep placement using Meixiangzhan 2 (MX) and Y liangyou 1378 (YL) as experimental materials. No fertilizer application was used as a control (T0) to calculate nitrogen use efficiency. The T2 treatment produced 29.03% and 25.52% higher grain yield for MX and YL because of the increase in productive panicles per ha and spikelet number per panicle, 21.20% and 13.68% higher nitrogen recovery efficiency, and 24.57% and 23.29% higher nitrogen agronomy efficiency than T1, respectively. In addition, the T2 treatment significantly improved the leaf area index and total aboveground biomass at the panicle initiation and heading stages. We also found that the POD, CAT, NR, and GOGAT of T2 for MX and YL at the heading stage were significantly enhanced compared to other treatments. Significant interaction was also observed in spikelet per panicle and 1000-grain weight between rice variety and nitrogen fertilizer type. Therefore, slow/controlled-release fertilizer application at the rate of 150 kg N per ha is a more feasible nitrogen fertilizer management strategy under mechanical deep placement, with the merit of increasing grain yield and improving nitrogen use efficiency in South China. Full article

Climate change poses a threat to global rice production by increasing the frequency and intensity of extreme weather events. The widespread cultivation of genetically uniform modern varieties has narrowed the genetic base of rice, increasing its vulnerability to these increased pressures. Rice landraces are traditional rice varieties that have been cultivated by farming communities for centuries and are considered crucial resources of genetic diversity. These landraces are adapted to a wide range of agro-ecological environments and exhibit valuable traits that provide tolerance to various biotic stresses, including drought, salinity, nutrient-deficient soils, and the increasing severity of climate-related temperature extremes. In addition, many landraces possess diverse alleles associated with resistance to biotic stresses, including pests and diseases. In addition, rice landraces exhibit great grain quality characters including high levels of essential amino acids, antioxidants, flavonoids, vitamins, and micronutrients. Hence, their preservation is vital for maintaining agricultural biodiversity and enhancing nutritional security, especially in vulnerable and resource-limited regions. However, rice landraces are increasingly threatened by genetic erosion due to widespread adoption of modern high-yielding varieties, habitat loss, and changing farming practices. This review discusses the roles of rice landraces in developing resilient and climate-smart rice cultivars. Moreover, the Pantiange Heigu landrace, cultivated at one of the highest altitudes globally in Yunnan Province, China, has been used as a case study for integrated conservation by demonstrating the successful combination of in situ and ex situ strategies, community engagement, policy support, and value-added development to sustainably preserve genetic diversity under challenging environmental and socio-economic challenges. Finally, this study explores the importance of employing advanced genomic technologies with supportive policies and economic encouragements to enhance conservation and sustainable development of rice landraces as a strategic imperative for global food security. By preserving and enhancing the utilization of rice landraces, the agricultural community can strengthen the genetic base of rice, improve crop resilience, and contribute substantially to global food security and sustainable agricultural development in the face of environmental and socio-economic challenges. Full article

Background/Objectives: Chemical methods for quantifying resistant starch (RS) in rice are labor-intensive, costly, and lack high repeatability, creating a bottleneck in breeding. This study aimed to develop specific, codominant molecular markers for the Wx gene to enable rapid and accurate genotype screening for RS content, thereby accelerating the development of high-RS rice varieties. Methods: Based on sequence alignment of the Wx gene in rice varieties with divergent RS content, a key single-nucleotide polymorphism was targeted. Two sets of tetra-primer amplification refractory mutation system polymerase chain reaction (ARMS-PCR) markers, T-Wx9-RS1 and T-Wx9-RS2, were designed. These markers were used to genotype diverse rice varieties and F₄ segregating populations, with results validated against standard chemical assays. Results: Sequence analysis identified a critical T → C base mutation at position 202 of the ninth exon in high-RS varieties. The developed ARMS-PCR markers successfully and consistently distinguished all three possible genotypes (homozygous mutant, homozygous wild-type, and heterozygous). The genotyping results showed complete concordance with the phenotypes determined by chemical methods. Conclusions: The developed molecular markers, T-Wx9-RS1 and T-Wx9-RS2, provide a rapid, reliable, and cost-effective tool for marker-assisted selection of high resistant starch content in rice. Their implementation can significantly enhance screening efficiency and expedite the breeding pipeline for novel, nutritionally improved rice cultivars. Full article

Rice (Oryza sativa) is one of the world’s major staple foods. However, stable rice production is constrained by various biotic and abiotic and stresses. Breeding and cultivation of rice varieties with resistance to multiple pathogens and environmental stresses is the most effective strategy to mitigate the adverse effect of pathogen attacks and abiotic stresses. Recently, researchers have focused on the exploitation of CRISPR/Cas9 technology to manipulate some negative defense-regulator genes to generate rice varieties with broad-spectrum resistance against rice pathogens. In this study, four negative regulator genes of rice blast, OsMads26, OsBsr-1, OsELF3-2 and OsERF922, were selected as CRISPR/Cas9 targets. By simultaneously knocking out all four genes via CRISPR/Cas9 technology, we created three mads26/bsr-1/elf3-2/erf922 quadruple knockout mutants. Our results demonstrated that all quadruple mutants exhibited much higher resistance not only to rice blast and bacterial blight but also to drought and salt stresses than the wildtype. Interestingly, grain yield of all three quadruple mutants was also drastically increased by 17.35% to 21.95%. Therefore, this study provides a novel strategy to rapidly improve rice varieties with broad-spectrum resistance to pathogens, elevated tolerance to abiotic stresses and enhanced yield potential. Full article

Rice yield prediction at high spatial resolution is essential to support precision management and sustainable intensification in irrigated systems. While many remote sensing studies provide yield estimates at the field scale, pixel-level predictions are required to characterize within-field variability. This study assesses the potential of multitemporal Sentinel-2 imagery and machine learning to estimate rice yield at pixel level in the Albufera rice area (Valencia, Spain). Yield data from combine harvester maps were collected for ‘JSendra’ and ‘Bomba’ Japonica varieties over five growing seasons (2020–2024) and linked to 10 m Sentinel-2 bands in the visible, near-infrared (NIR) and short-wave infrared (SWIR) regions. Random Forest (RF) and XGBoost (XGB) models were trained with 2020–2023 data and independently validated in 2024. XGB systematically outperformed RF, achieving at 110 and 130 DAS (days after showing), R² values of 0.74 and 0.85 and RMSE values of 0.63 and 0.28 t·ha⁻¹ for ‘JSendra’ and ‘Bomba’. Prediction accuracy increased as the season progressed, and models using all spectral bands clearly outperformed configurations based only on spectral indices, confirming the dominant contribution of NIR reflectance. Spatial error analysis revealed errors at field edges and headlands, while central pixels were more accurately predicted. Overall, the proposed approach provides accurate, spatially explicit rice yield maps that capture within-field variability and support both end-of-season yield estimation and early season forecasting, enabling the identification of potentially low-yield zones to support targeted management decisions. Full article

Advances in plant nutrition have driven substantial progress in modern fertilization technologies. Nevertheless, excessive chemical fertilizer application, low nutrient-use efficiency, and the resulting environmental pollution remain widespread. We have reviewed the research progress and existing limitations in the field of plant nutrition and fertilization technology. Based on the traditional plant nutrition diagnosis and integrating visual diagnosis methods, this study explores the intrinsic relationship between plant growth status, nutrient supply conditions, and crop yield and proposed the concept of “status nutrition”. Variations in environmental nutrient conditions lead plants to exhibit distinct growth status in terms of vigor and phenotype. We define the plant nutritional status reflected by this growth status as “status nutrition”. Based on growth characteristics, plant growth status can be classified as weak, normal, or vigorous, corresponding to deficient, appropriate, and excessive environmental nutrient supply, respectively. Guided by this concept, an innovative rice “extremely dense planting” technology is integrated by increasing planting density, eliminating tiller-stage fertilization, and optimizing nitrogen management. The technology adapts to growth status with low nutrient demand, coordinates population growth and main-stem panicle formation, and achieves high yield with reduced fertilizer inputs. Further research is needed on the nutrient metabolism mechanisms of plants under different growth statuses and the growth status grading system. The promotion of “extremely dense planting” is constrained by crop variety traits and soil fertility, and its parameters urgently need to be optimized. Overall, the framework of “status nutrition” provides important theoretical support for the development and application of crop high-yield cultivation technologies. Full article