Transposable elements (TEs) are a significant source of genetic diversity in rice and play a crucial role in the domestication process of Asian cultivated rice. However, due to the highly repetitive nature of TE sequences, their identification typically requires high-quality genome sequences. Currently, the limited genomic resources for African cultivated rice (Oryza glaberrima, Og) hinder systematic investigations into TE diversity and its contributions to the Og domestication process.

We constructed a high-resolution pan-TE variation map using the chromosome-level genomes of 21 accessions (11 Og and 10 Oryza barthii [Ob]). We estimated the divergence of each TE variation across the genome using F_ST analysis and identified 854 selected TE variations putatively involved in the Og domestication process.

The pan-TE variation map comprises 17,097 non-redundant high-quality TE variations with a total length of 39.1 Mb, with 61.7% of the TE variations larger than 1 kb. The total number of TE variations in the Ob accessions was greater than that in the Og accessions. A total of 658 genes harboring selected TE variations were identified as potentially involved in the Og domestication process, which were significantly enriched in biological processes related to basic metabolism. Notably, 30 genes with known functions were involved in the independent domestication of Og.

This study highlights the significant role of TE variations as a source of phenotypic diversity during the Og domestication process. The high-quality pan-TE variation map not only enriches the available variation library for rice breeding but also provides critical theoretical foundations and resource support for the genetic improvement of Og germplasm.

To address the problems of high labor intensity and low efficiency in manual measurements of heading date in rice breeding, this study proposes an intelligent prediction method that integrates UAV imagery, the YOLOv10b object detection algorithm, and a random forest regression model to achieve automated and efficient prediction of heading date in rice breeding plots.

Using rice breeding plots as the research subject, UAV imagery was acquired at 15 observation time points from booting to maturity. Based on the YOLOv10b algorithm, a rice panicle detection model was trained to recognize and count panicles in plot images. Subsequently, the numbers of panicles at each observation time point were used as input variables, and the number of days from transplanting to heading was used as the prediction variable to construct and compare multiple heading date prediction models. Based on this, feature importance analysis and dimensionality reduction were performed to develop a simplified model.

Experimental results showed that the YOLOv10b model achieved a precision of 91.7%, a recall of 92.1%, and an F₁ score of 0.919 in the panicle detection task. In the heading date prediction task, the random forest model constructed using the sequential features of panicle counts from all 15 observation time points achieved an R² of 0.84, an RMSE of 1.57 days, and an MAE of 1.12 days. Furthermore, after feature dimensionality reduction based on feature importance analysis, a simplified model constructed using 9 observation time points achieved an R² of 0.83, an RMSE of 1.65 days, and an MAE of 1.16 days. This approach effectively reduced feature dimensionality while maintaining prediction accuracy, thereby improving the model's efficiency and practicality.

The proposed method can effectively reduce the workload of manual measurements, improve the efficiency of heading date monitoring, and realize automated prediction of heading date in breeding plots. It provides a feasible data foundation and technical pathway for intelligent breeding and precision agricultural management.

Grain size is a critical determinant of rice yield. This study aims to explore novel genes regulating grain size and expand the current genetic regulatory network, and provide valuable genetic resources for molecular design breeding of high-yield rice varieties.

The large-grain mutant gsn4, generated by EMS mutagenesis of the japonica rice variety W7, was used as experimental material. A combination of systematic phenotypic identification, cytological observation, gene mapping, functional verification, subcellular localization, and haplotype analysis was performed to clone and functionally characterize the candidate gene.

Phenotypic identification revealed that the gsn4 mutant exhibited pleiotropic effects. Compared with the wild type, its grain length, grain width, and 1000-grain weight were significantly increased, whereas plant height, panicle length, and grain number per panicle were significantly decreased. Cytological analysis indicated that GSN4 regulates rice grain size by modulating both cell proliferation and expansion in glumes. Map-based cloning, together with CRISPR/Cas9 gene-editing validation, confirmed LOC_Os04g46450 as the candidate gene underlying GSN4. This gene encodes a nuclear-localized E3 ubiquitin ligase protein, which acts as a negative regulator of rice grain size and modulates plant growth and development through the brassinosteroid (BR) biosynthesis pathway. Haplotype analysis further identified Hap1 as the elite haplotype conferring the most favorable effects on grain width and 1000-grain weight.

Collectively, this study elucidates the function and regulatory mechanism of GSN4, enriches the genetic regulatory network governing rice grain size, and provides important genetic resources and a theoretical basis for molecular design breeding of high-yield rice varieties.

This study investigated the effects of straw layered returning combined with its decomposing agents on the transformation of soil organic carbon (C), activities of enzymes related to C metabolism, structure of microbial community, and rice yield, in order to provide a theoretical basis for organic fertilization of low-yield yellow paddy soil and rice yield improvement.

Eight treatments were designed, including no fertilization (CK), conventional fertilization (NPK), and layered straw application at 0 cm, 0-8 cm, and 8-18 cm depths (NPKSL0, NPKSL0-8, and NPKSL8-18), and layered straw application combined with decomposing agents at 0 cm, 0-8 cm, and 8-18 cm depths (NPKSML0, NPKSML0-8, and NPKSML8-18). The content of soil organic C components, activity of C metabolism-related enzymes, soil microbial community, rice yield and its yield components were investigated, and their dominant factors that affect rice yield and soil organic C were further explored.

Compared with NPK and NPKSL0-8, NPKSL8-18 treatment significantly increased the content of soil easily oxidizable organic C, microbial biomass C, particulate organic C, activity of α-glucosidase and β-glucosidase, and the relative abundance of Acidobacteriota and Ascomycota. Compared with the single straw application, the coupling application of straw and decomposing agents further increased soil organic C, easily oxidizable organic C, particulate organic C, mineral-bound organic C, and the activity of β-glucosidase in the 0-8 cm and 8-18 cm layers. Under NPKSML8-18 treatment, the abundance of Chloroflexi group was the highest, while the groups of Rozellomycota, Anaeromyxobacter, and Nigrospora were the lowest. Compared with NPK, NPKSML0, NPKSML0-8, and NPKSML8-18 increased soil organic C and rice yield, with the increments of 27.38%-37.94% and 7.97%-23.14%, and their values were highest in the NPKSML8-18 treatment. Correlation analysis showed that soil organic C and rice yield were significantly and positively correlated with soil easily oxidizable organic C, microbial biomass C, mineral-bound organic C, particulate organic C, and the activities of β-1,4-xylanase, α-1,4-glucosidase, and β-1,4-glucosidase (P<0.05), but were negatively correlated with dissolved organic C, the bacterial Shannon index and the fungal richness index (P<0.01).

Deep application of straw coupled with decomposing agents (NPKSML8-18) increases soil organic C and rice yield, mainly by enhancing the content of soil easily oxidizable organic C, microbial biomass C, mineral-associated organic C, and particulate organic C, boosting the activities of β-1,4-xylanase, α-1,4-glucosidase, and β-1,4-glucosidase, and promoting the relative abundance of Chloroflexi involved in straw decomposition.

Rice lemma and palea development directly affects grain shape, pollination efficiency, yield and quality. This study identified mutants related to rice glume development, mapped and cloned the causal genes, and elucidated the molecular mechanisms by which the target genes regulate glume development, providing theoretical references for rice molecular breeding.

The agl1 mutant was obtained by EMS mutagenesis of japonica cultivar SN9816. Paraffin sectioning and scanning electron microscopy were used to observe the morphology of glumes and floral organs; pollen viability was assessed by I₂-KI staining. Map-based cloning delimited AGL1, candidate genes were sequenced, and conservation and diversity of the target gene were analyzed. A Foss grain analyzer was used to measure brown-rice quality parameters.

Compared with the wild-type SN9816, agl1 showed more strongly curved lemmas with unchanged longitudinal length, inwardly sunken paleae, and significantly narrowed lemma and palea; the lemma almost completely enclosed the palea. agl1 displayed abnormal lodicules, enlarged pistils and disordered stamens. Pollen activity and seed-setting rate were reduced. AGL1 was fine-mapped to a 68.7-kb interval between Indel4 and Indel5 on chromosome 2. Sequencing seven ORFs in this region revealed a single-nucleotide mutation in LOC_Os02g56610, which encodes a DUF640-domain protein. The DUF640 family in rice harbors a conserved ALOG domain and diverse regulatory elements, suggesting roles in both floral morphogenesis and grain quality. Quality analysis showed increased brown-rice protein and free fatty acid content but decreased amylose and total starch content, leading to poorer eating quality.

The AGL1 gene functions as a pivotal regulator of rice lemma and palea development and grain quality; its loss-of-function disrupts hull morphogenesis, compromises pollen viability, and likely perturbs the grain-filling process, resulting in the concomitant deterioration of both yield and grain quality.

This study aims to investigate the effects of key cultivation measures (sowing date, planting density, and nitrogen application rate) on grain yield, rice quality formation, and growth characteristics of the high-quality super rice variety Huazheyou 261. The results are expected to provide a theoretical basis for developing high-yield, high-quality, and high-efficiency cultivation techniques.

A single-factor field experiment was conducted using Huazheyou 261 as the test material. The treatments included four sowing dates (May 15, May 28, June 10, and June 23, denoted as S1, S2, S3, and S4), five transplanting densities (plant spacing of 27.0, 22.5, 19.3, 16.9, and 15.0 cm, denoted as D1 to D5, with a fixed row spacing of 30 cm), and five nitrogen application rates (0, 135, 180, 225, and 270 kg/hm², denoted as N0 to N4). Grain yield, rice quality, and growth characteristics were measured under different treatments. The correlations between yield and dry matter accumulation, as well as temperature and light resources, were analyzed. A comprehensive evaluation of rice quality under each treatment was also performed.

Sowing date, density and nitrogen application rate significantly affected grain yield, rice quality and growth characteristics of rice. Under each cultivation measure, the grain yield and comprehensive evaluation grade of rice quality showed an initial increase followed by a decrease. The grain yield of S3, D3 and N3 treatments was the highest, and the rice quality of S3, D3 and N2 treatments was the best. There was a significant quadratic relationship between grain yield and sowing date, density and nitrogen application rate. The trend of yield components and rice quality indexes varied with different cultivation measures. With the delay of sowing date, the decrease of density and the increase of nitrogen application rate, the growth period was delayed and the whole growth period was prolonged. The number of tillers increased, but the productive tiller percentage (except density treatment) decreased, and the SPAD value of leaves increased. The effective leaf area index, grain-leaf ratio (except under nitrogen treatments), dry matter accumulation from heading to maturity, harvest index, and temperature-light production efficiency all exhibited a trend of initial increase followed by decrease. Statistical analysis indicated that grain yield was significantly positively correlated with total spikelets and dry matter accumulation, with total spikelets contributing the most to grain yield. Principal component analysis identified milled rice rate, head milled rice rate, chalky grain rate, chalkiness, alkali spreading value, and gel consistency as key indicators for evaluating rice quality.

Under the experimental conditions, synergistic optimization of grain yield and rice quality for Huazheyou 261 in southeastern Zhejiang Province was achieved with the following practices: sowing between May 28 and June 15, transplanting at a row spacing of 30 cm and a plant spacing of 19.3-23.3 cm, and applying nitrogen at a rate of 176.6-209.8 kg/hm².

The effects of different irrigation and straw returning combinations on rice yield and greenhouse gas emissions were studied to provide theoretical basis and practical guidance for rice yield increase and greenhouse gas emission reduction.

Taking Yongyou 2640 and Nanjing 5718 as the test varieties, two irrigation methods were set up: conventional irrigation (CI), alternate wetting and moderate soil drying irrigation (AWD), and three straw returning methods: no straw returning (S0), straw biochar application (SC), composted straw returning to the field combined with straw biochar (SS). The effects on rice yield, dry matter accumulation, photosynthetic rate, photosynthetic potential, root activity and methane and nitrous oxide emission fluxes during the whole growth period were analyzed.

1) Compared with CI+S0, the AWD+SC and AWD+SS treatments significantly increased grain yield by 8.30%-13.90% and 18.55%-22.58%, respectively. Compared with S0 treatment, SC and SS significantly increased the effective panicle number and grain number per panicle, and AWD treatment significantly increased the grain number per panicle, seed setting rate and 1000-grain weight. 2) The increase in yield was mainly due to the significant increase of dry matter accumulation in underground and above-ground parts, net photosynthetic rate and photosynthetic potential of leaves, NSC transport in stem sheath and oxidizing power of roots. 3) SC significantly reduced methane and nitrous oxide emissions, while SS increased emissions, but AWD treatment significantly reduced methane emissions, thereby reducing the global warming potential and greenhouse gas emission intensity of rice fields.

The combination of straw returning technology (AWD+SC/SS) with alternating wet and dry irrigation can significantly improve the accumulation and transport of photosynthetic substances in rice, promote below-ground root growth, and achieve the dual goals of increasing rice yield and reducing greenhouse gas emissions in rice fields.