Genomic imprinting is an epigenetic phenomenon by which certain genes display differential expression in a parent-of-origin-dependent manner. Hundreds of imprinted genes have been identified from several plant species. Here, we identified, with a high level of confidence, 208 imprinted gene candidates from rice (Oryza sativa). Imprinted genes of rice showed limited association with the transposable elements, which contrasts with findings from Arabidopsis (Arabidopsis thaliana). Generally, imprinting in rice is conserved within a species, but intraspecific variation also was detected. The imprinted rice genes do not show signatures of selection, which suggests that domestication has had a limited evolutionary consequence on genomic imprinting. Although conservation of imprinting in plants is limited, we show that some loci are imprinted in several different species. Moreover, our results suggest that different types of epigenetic regulation can be established either before or after fertilization. Imprinted 24-nucleotide small RNAs and their neighboring genes tend to express alleles from different parents. This association was not observed between 21-nucleotide small RNAs and their neighboring genes. Together, our findings suggest that the regulation of imprinting can be diverse, and genomic imprinting has evolutionary and biological significance.

MYB transcription factors (TFs) comprise a large gene family that plays an important role in plant growth, development, stress responses, and defense regulation. However, their functions in peanut remain to be further elucidated. Here, we identified six AhMYB44 genes (AhMYB44-01/11, AhMYB44-05/15, and AhMYB44-06/16) in cultivated peanut. They are typical R2R3-MYB TFs and have many similarities but different expression patterns in response to drought stress, suggesting different functions under drought stress. Homologous genes with higher expression in each pair were selected for further study. All of them were nuclear proteins and had no self-transactivation activity. In addition, we compared the performances of different lines at germination, seedling, and adult stages under drought stress. After drought treatment, the overexpression of AhMYB44-11 transgenic plants resulted in the longest root length at the seedling stage. Levels of proline, soluble sugar and chlorophyll, and expression levels of stress-related genes, including P5CS1, RD29A, CBF1, and COR15A, were higher than those of the wild type (WT) at the adult stage. While the overexpression of AhMYB44-16 significantly increased the drought sensitivity of plants at all stages, with differential ABA content, the expression levels of the ABA-related genes PP2CA and ABI1 were significantly upregulated and those of ABA1 and ABA2 were significantly downregulated compared with the WT. AhMYB44-05 showed similar downregulated expression as AhMYB44-16 under drought stress, but its overexpression in Arabidopsis did not significantly affect the drought resistance of transgenic plants. Based on the results, we propose that AhMYB44-11 plays a role as a positive factor in drought tolerance by increasing the transcription abundance of stress-related genes and the accumulation of osmolytes, while AhMYB44-16 negatively regulates drought tolerance through its involvement in ABA-dependent stress response pathways.

GPAT enzymes (glycerol-3-phosphate 1-O-acyltransferase, EC 2.3.1.15) catalyze the initial and rate-limiting step of plant glycerolipid biosynthesis for membrane homeostasis and lipid accumulation, yet little research has been done on peanuts. By reverse genetics and bioinformatics analyses, we have characterized an AhGPAT9 isozyme, of which the homologous product is isolated from cultivated peanut. QRT-PCR assay revealed a spatio-temporal expression pattern that the transcripts of AhGPAT9 accumulating in various peanut tissues are highly expressed during seed development, followed by leaves. Green fluorescent protein tagging of AhGPAT9 confirmed its subcellular accumulation in the endoplasmic reticulum. Compared with the wild type control, overexpressed AhGPAT9 delayed the bolting stage of transgenic Arabidopsis, reduced the number of siliques, and increased the seed weight as well as seed area, suggesting the possibility of participating in plant growth and development. Meanwhile, the mean seed oil content from five overexpression lines increased by about 18.73%. The two lines with the largest increases in seed oil content showed a decrease in palmitic acid (C16:0) and eicosenic acid (C20:1) by 17.35% and 8.33%, respectively, and an increase in linolenic acid (C18:3) and eicosatrienoic acid (C20:3) by 14.91% and 15.94%, respectively. In addition, overexpressed AhGPAT9 had no significant effect on leaf lipid content of transgenic plants. Taken together, these results suggest that AhGPAT9 is critical for the biosynthesis of storage lipids, which contributes to the goal of modifying peanut seeds for improved oil content and fatty acid composition.

Cold stress is one major threats to field crops. The cold tolerant ability is a key limiting factor for the popularization of peanut (Arachis hypogaea L.) in cold areas. Our previous research showed three key metabolic change time points of peanut buds in response to low temperature. The present study applied iTRAQ proteomic to further quantify differentially expressed proteins in three key metabolic change time points. A total of 2684 non-redundant proteins and 333 differentially expressed proteins across the three cold stress treatment points were identified. The results enrich the cold stress regulation network and provide useful information for further improving the ability of peanut under cold stress.

As a critical land cover type, tidal flats play an essential role in carbon sequestration, ecological conservation, and disaster risk reduction. However, tidal flat areas exhibit significant spatiotemporal variability due to the dynamic influences of tides, waves, and precipitation. Moreover, the complex characteristics of tidal flat farmlands in high-resolution remote sensing imagery, coupled with the limited capabilities of conventional extraction methods, preclude large-scale, high-precision farmland delineation. To address this challenge, this study develops a comprehensive tidal flat farmland dataset using high-resolution remote sensing imagery and proposes a novel remote sensing foundation model based on a Sandglass module encoder-decoder architecture. The key contributions of this work encompass four major innovations:1. Development of a novel lightweight Multi-Scale Edge-Aware Module (MSEAM) that integrates learnable gradient operators with parallel multi-scale convolutions, effectively suppressing background noise while adaptively enhancing critical edge regions; 2. Construction of an efficient Sandglass encoder-decoder structure employing a lightweight Sandglass network as the feature extraction backbone, combined SCSE modules, achieving enhanced feature representation capabilities while reducing parameter count and computational complexity; 3. Introduction of an Adaptive Feature Fusion Module (AFM) that facilitates effective integration of high-level and low-level semantic information through a dynamic weight allocation mechanism, emphasizing useful channel features; 4. Integrating the enhanced Sandglass encoder-decoder model with the large-scale vision-language model CLIP. Experimental validation demonstrates that the proposed model achieves an accuracy of 96.75% and mIoU of 90.42% on the high-resolution tidal flat farmland dataset. So the model can realize the extraction of fine geographic patches of farmland in the coastal tidal flat area, and the extracted plot data can be used as the base map data for the observation and research of crop phenology, which is of great significance for the precise delineation of crop planting areas.

In order to address the problems of high mechanical damage rate (MDR) and poor variety adaptability in mechanical peanut shelling, this paper improves a small, flexible arc-plates drum–circular grid bar concave screen-type peanut-shelling device. Firstly, by combining the Hertz theory and the Weibull distribution model, the shelling and separation models of drums of rigid rods and flexible arc-plates were established. Through comparative analysis, it was verified that the latter has a lower MDR and energy consumption and has excellent shelling performance. Then, through single-factor experiments and an Analysis of Variance (ANOVA), the influence laws of peanut moisture content, drum speed, shelling spacing, and hardness of flexible material (silicone) on the MDR and shelling efficiency (SE) were explored. Subsequently, Box–Behnken’s four-factor three-level regression experiments were carried out, and the optimal shelling operation parameters were obtained by using the response surface multi-objective optimization method (RSM) and verified experiments. The results show that when moisture content is 11%, drum speed is 227 rpm, shelling spacing is 24 mm, and silicone hardness is 40 HA, the kernel’s MDR after shelling is 4.73%, which is reduced by 5.51% and the SE is 95.21%, which is increased by 3%. The R² and the Root Mean Square Error (RMSE) of the actual value versus the predicted value of the model were 0.9921, 0.9624, 7.99 × 10⁻², and 3.1 × 10⁻³, respectively. The relevant research provides references for reducing losses, improving quality, and applying new materials for components in mechanical peanut shelling.