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Maize breeding is greatly affected by hybrid vigor, a phenomenon that hybrids exhibit superior performance than parental lines. The immortalized F2 population (IMF2) is ideal for the genetic dissection and prediction of hybrid performance. Here, in this study, we conducted the QTL mapping and genomic prediction of six traits related to plant architecture using an IMF2 population. Broad-sense heritability of these traits ranged from 0.85 to 0.94. Analysis of genetic effects showed that additive variance was the main contributor to phenotypic variations. The mapping of quantitative trait loci (QTLs) revealed 10 to 16 QTLs (including pleiotropic loci and epistatic QTLs) for the six traits. Additionally, we identified 15 fine-tuning QTLs for plant height (PH). For genomic prediction (GP), the model of additive and dominance (AD) exhibited higher prediction accuracy than those fitting general combining ability (GCA) and its combination with special combining ability (SCA) effects for all tested traits. And adding the epistasis (E) effect into the AD model did not significantly increase its prediction accuracy. Moreover, the identified 15 fine-tuning QTLs of PH, which exerted large genomic prediction effects, were verified by the marker effect of GP. Our results not only provide an approach for the fine-mapping of fine-tuning QTLs but also serve as references for GP breeding in crops. [ABSTRACT FROM AUTHOR]

Reverse transcription quantitative real-time PCR (RT-qPCR) is arguably the most prevalent and accurate quantitative gene expression analysis. However, selection of reliable reference genes for RT-qPCR in rice (Oryza sativa) is still limited, especially for a specific tissue type or growth condition. In this study, we took the advantage of our RNA-seq datasets encompassing data from five rice varieties with diverse treatment conditions, identified 12 novel candidate reference genes, and conducted rigorous evaluations of their suitability across typical rice tissues. Comprehensive analysis of the leaves, shoots, and roots of two rice seedlings subjected to salt (30 mmol/L NaCl) and drought (air-dry) stresses have revealed that OsMED7, OsACT1, and OsOS-9 were the robust reference genes for leaf samples, while OsACT1, OsZOS3-23, and OsGDCP were recommended for shoots and OsMED7, OsOS-9, and OsGDCP were the most reliable reference genes for roots. Comparison results produced by different sets of reference genes revealed that all these newly recommended reference genes displayed less variation than previous commonly used references genes under the experiment conditions. Thus, selecting appropriate reference genes from RNA-seq datasets leads to identification of reference genes suitable for respective rice tissues under drought and salt stress. The findings offer valuable insights for refining the screening of candidate reference genes under diverse conditions through the RNA-seq database. This refinement serves to improve the accuracy of gene expression in rice under similar conditions. [ABSTRACT FROM AUTHOR]

Mountainous cities face various land use challenges, including complex topography, low land use efficiency, and the insufficient control of land use in small-scale areas at the urban fringe. Considering population changes, environmental conservation, and urban planning, this study first established three scenarios: economic priority (Econ. Prior.), ecological priority (Ecol. Prior.), and balanced development (BD), and then used the Multi-Objective Planning (MOP) model to calculate the optimal land use structure. Finally, it carried out land use spatial layout optimization based on the Patch-generating Land Use Simulation (PLUS) model in 2035, Caijia Cluster, Chongqing, China. This approach, known as MOP-PLUS modeling, aimed to optimize land use. Meanwhile, the applicability of the PLUS model in simulating land use changes was discussed in small-scale mountainous areas. The results show the following: (1) The "quantity + space" approach in the MOP-PLUS model demonstrated the feasibility of the PLUS model in simulating land use change in small-scale mountainous areas. The overall accuracy (OA) of land use change simulation reached 81.60%, with a Kappa value of 0.73 and a Figure of Merit (FoM) coefficient of 0.263. (2) Land use optimization: Under the Econ. Prior. scenario, economic benefits peaked at 4.06 × 1010 CNY. Urban expansion was the largest, leading to increased patch fragmentation. The Ecol. Prior. scenario yielded the highest ecological benefits, reaching 7.46 × 107 CNY. The urban development pattern exhibited inward contraction, accompanied by urban retrogression. In the BD scenario, economic benefits totaled 3.89 × 1010 CNY, and ecological benefits amounted to 7.16 × 107 CNY. Construction land tended to concentrate spatially, leading to relatively optimal land use efficiency. Therefore, based on a comprehensive consideration of the regional land use constraint policies and spatial layout, we believe that a balance point for land use demands can be found in the BD scenario. It can ensure economic growth without compromising the ecological environment. [ABSTRACT FROM AUTHOR]

Maintaining rice yield and reducing nitrogen (N) input are two important targets in sustainable agriculture practices. The adoption of a nitrogen-saving variety (NSV) provides a unique opportunity to achieve this. However, limited options in NSV japonica rice and a lack of information on their responses to N reduction make management decisions difficult. This study aims to explore the responses of yield and nitrogen use efficiency (NUE) in NSV to N reduction. Two newly released NSVs and two popular general varieties (GVs) of japonica rice were field tested in Yangzhou, located at the lower reaches of Yangtze River of China, in two consecutive years. The results showed that for NSVs, with a 40–60% reduction in common practice N rate (300 Kg ha−1), the rice yield could maintain a record average level (p < 0.05), whereas the yield for the GV would drop 20–30% (p < 0.05). This indicates that combining the practices of adoption of NSV and N reduction to 120–180 Kg N ha−1 could balance the yield and N consumption. Moderate N reduction promotes the N accumulation and NUE, and it increases the number of tillers, the productive tiller percentage and the total amount of spikelets in the population, and increases the carbon and N metabolism of the population in the NSV. Compared with GV, NSV showed higher NUE and non-structural carbohydrate re-mobilization in the reduced N rate. The results showed that the practice of N reduction has to adopt NSV at the same time in order to maintain the grain yield level in rice. [ABSTRACT FROM AUTHOR]

Rice is the primary source of food for more than half of the global population. Accordingly, improving the cold tolerance of rice is vital for ensuring food security. In this study, a new cold tolerance-related QTL in rice (qPSR7-2) was detected on chromosome 7 following a genome-wide association study involving 173 japonica rice germplasm resources. The fine mapping of this locus identified Os07g0541800 as a candidate gene associated with qPSR7-2. This gene encodes a cysteine-rich receptor-like kinase. The functional verification of Os07g0541800 involving transgenic plants indicated that qPSR7-2 positively regulates rice cold tolerance at the seedling stage. The examination of the cold tolerance of 984 germplasm resources from the 3000 Rice Genomes Project at the seedling stage and their respective haplotypes at qPSR7-2 revealed that the proportion of favorable haplotypes in germplasm resources increased as the latitude increased. More than 90% of the rice varieties cultivated in Europe and Japan appear to carry qPSR7-2, implying that qPSR7-2 may mediate the acclimation of rice to low-temperature stress. The findings of this study will further clarify the molecular networks regulating rice cold tolerance, while also providing researchers and breeders with new genetic resources and information relevant for developing cold-tolerant rice varieties. [ABSTRACT FROM AUTHOR]

Gridded gross domestic product (GDP) data are a crucial land surface parameter for many geoscience applications. Recently, machine learning approaches have become powerful tools in generating gridded GDP data. However, most machine learning approaches for gridded GDP estimation seldom consider the geographical properties of input variables. Therefore, in this study, a geographically weighted stacking ensemble learning approach was developed to generate gridded GDP data. Three algorithms—random forest, XGBoost, and LightGBM—were used as base models, and the linear regression in stacking ensemble learning was replaced by geographically weighted regression to locally fuse the three predictions. A case study was conducted in China to demonstrate the effectiveness of the proposed approach. The results showed that the proposed GDP downscaling approach outperformed the three base models and traditional stacking ensemble learning. Meanwhile, it had good predictive power on county-level GDP test data with R2 of 0.894, 0.976, and 0.976 for the primary, secondary, and tertiary sectors, respectively. Moreover, the predicted 1 km gridded GDP data had a high accuracy (R2 = 0.787) when evaluated by town-level GDP data. Hence, the proposed GDP downscaling approach provides a valuable option for generating gridded GDP data. The generated 1 km gridded GDP data of China from 2020 are of great significance for other applications. [ABSTRACT FROM AUTHOR]

Buckwheat is an important minor grain crop with medicinal and edible functions. The accurate judgment of buckwheat maturity is beneficial to reduce harvest losses and improve yield. With the rapid development of unmanned aerial vehicle (UAV) technology, it has been widely used to predict the maturity of agricultural products. This paper proposed a method using recursive feature elimination cross-validation (RFECV) combined with multiple regression models to predict the maturity of buckwheat in UAV-RGB images. The images were captured in the buckwheat experimental field of Shanxi Agricultural University in Jinzhong, Northern China, from September to October in 2021. The variety was sweet buckwheat of "Jinqiao No. 1". In order to deeply mine the feature vectors that highly correlated with the prediction of buckwheat maturity, 22 dimensional features with 5 vegetation indexes, 9 color features, and 8 texture features of buckwheat were selected initially. The RFECV method was adopted to obtain the optimal feature vector dimensions and combinations with six regression models of decision tree regression, linear regression, random forest regression, AdaBoost regression, gradient lifting regression, and extreme random tree regression. The coefficient of determination ( R 2 ) and root mean square error (RMSE) were used to analyze the different combinations of the six regression models with different feature spaces. The experimental results show that the single vegetation index performed poorly in the prediction of buckwheat maturity; the prediction result of feature space "5" combined with the gradient lifting regression model performed the best; and the R 2 and RMSE were 0.981 and 1.70 respectively. The research results can provide an important theoretical basis for the prediction of the regional maturity of crops. [ABSTRACT FROM AUTHOR]

Intermittent records of satellite soil moisture data are major obstacles that constrain their hydrometeorological applications. Based on the European Space Agency Climate Change Initiative (ESA CCI) soil moisture combined product, two machine learning models were employed to reconstruct soil moisture in China during 1979–2019 in both temporal and spatial domains, and latent errors for reconstructed series, as well as their performances for tracing climate extremes, were analyzed. The results showed that with the homogeneity of available data over space, the spatial approach performed well in reproducing the spatial heterogeneity of soil moisture (with medians of the correlation coefficient (CC) above 0.8 and root mean square errors (RMSEs) ranging from 0.02 to 0.03 m3∙m−3). The temporal approach (CC values of 0.7 and RMSEs ranging between 0.02 and 0.03 m3∙m−3) was superior in capturing the seasonality features and the timely and accurate mapping of short-term soil moisture dynamics impacted by rainstorms. However, both approaches failed to identify the location and severity of droughts accurately. The findings highlight the benefits of combining the strengths of both temporal and spatial gap-filling approaches for improving the estimation of missing values and hydrometeorological applications. [ABSTRACT FROM AUTHOR]

Urban fire occurs within the built environment, usually involving casualties and economic losses, and affects individuals and socioeconomic activities in the surrounding neighborhoods. A good understanding of the spatiotemporal dynamics of fire incidents can offer insights into potential determinants of various fire events, therefore enabling better fire risk estimation which can assist with future allocation of prevention resources and strategic planning of mitigation programs. Using a twelve-year (2002-2013) dataset containing the urban fire events in Nanjing, China, this research explores the spatiotemporal dynamics of urban fires using a range of exploratory spatial data analysis (ESDA) approaches. Of particular interest here are the fire incidents involving residential properties and local facilities due to their relatively higher occurrence frequencies. The results indicate that the overall amount of urban fires has greatly increased in the last decade and the spatiotemporal distribution of fire events varies among different incident types. The identified spatiotemporal patterns of urban fires in Nanjing can be linked to the urban development strategies and how they have been reflected in reality in recent years. [ABSTRACT FROM AUTHOR]

China's resource-based cities have made tremendous contributions to national and local economic growth and urban development over the last seven decades. Recently, such cities have been in transition from resource-centered development towards human-oriented urbanization to meet the requirements of long-term sustainability for the natural environment and human society. A good understanding of urban expansion and evolution as a consequence of urbanization has important implications for future urban and regional planning. Using a series of remote sensing (RS) images and geographical information system (GIS)-based spatial analyses, this research explores how a typical resource-based mining city, Datong, has expanded and evolved over the last two decades (2000–2018), with a reflection on the role of urban planning and development policies in driving the spatial transformation of Datong. The RS images were provided and processed by the Google Earth Engine (GEE) platform. Spatial cluster analysis approaches were employed to examine the spatial patterns of urban expansion. The results indicate that the area of urban construction land increased by 132.6% during the study period, mainly along with the Chengqu District, the Mining Area, and in the southeast of the Nanjiao District, where most new towns are located. Reflection on the factors that influence urban expansion shows that terrain, urban planning policies, and social economy are driving Datong's urban development. [ABSTRACT FROM AUTHOR]

Reducing nitrogen (N) input is a key measure to achieve a sustainable rice production in China, especially in Jiangsu Province. Tiller is the basis for achieving panicle number that plays as a major factor in the yield determination. In actual production, excessive N is often applied in order to produce enough tillers in the early stages. Understanding how N regulates tillering in rice plants is critical to generate an integrative management to reduce N use and reaching tiller number target. Aiming at this objective, we utilized RNA sequencing and weighted gene co-expression network analysis (WGCNA) to compare the transcriptomes surrounding the shoot apical meristem of indica (Yangdao6, YD6) and japonica (Nipponbare, NPB) rice subspecies. Our results showed that N rate influenced tiller number in a different pattern between the two varieties, with NPB being more sensitive to N enrichment, and YD6 being more tolerant to high N rate. Tiller number was positively related to N content in leaf, culm and root tissue, but negatively related to the soluble carbohydrate content, regardless of variety. Transcriptomic comparisons revealed that for YD6 when N rate enrichment from low (LN) to medium (MN), it caused 115 DEGs (LN vs. MN), from MN to high level (HN) triggered 162 DEGs (MN vs. HN), but direct comparison of low with high N rate showed a 511 DEGs (LN vs. HN). These numbers of DEG in NPB were 87 (LN vs. MN), 40 (MN vs. HN), and 148 (LN vs. HN). These differences indicate that continual N enrichment led to a bumpy change at the transcription level. For the reported sixty-five genes which affect tillering, thirty-six showed decent expression in SAM at tiller starting phase, among them only nineteen being significantly influenced by N level, and two genes showed significant interaction between N rate and variety. Gene ontology analysis revealed that the majority of the common DEGs are involved in general stress responses, stimulus responses, and hormonal signaling process. WGCNA network identified twenty-two co-expressing gene modules and ten candidate hubgenes for each module. Several genes associated with tillering and N rate fall on the related modules. These indicate that there are more genes participating in tillering regulation in response to N enrichment. [ABSTRACT FROM AUTHOR]

Japonica and indica are two important subspecies in cultivated Asian rice. Irradiation is a classical approach to induce mutations and create novel germplasm. However, little is known about the differential response between japonica and indica rice after γ radiation. Here, we utilized the RNA sequencing and Weighted Gene Co-expression Network Analysis (WGCNA) to compare the transcriptome differences between japonica Nipponbare (NPB) and indica Yangdao6 (YD6) in response to irradiation. Japonica subspecies are more sensitive to irradiation than the indica subspecies. Indica showed a higher seedling survival rate than japonica. Irradiation caused more extensive DNA damage in shoots than in roots, and the severity was higher in NPB than in YD6. GO and KEGG pathway analyses indicate that the core genes related to DNA repair and replication and cell proliferation are similarly regulated between the varieties, however the universal stress responsive genes show contrasting differential response patterns in japonica and indica. WGCNA identifies 37 co-expressing gene modules and ten candidate hub genes for each module. This provides novel evidence indicating that certain peripheral pathways may dominate the molecular networks in irradiation survival and suggests more potential target genes in breeding for universal stress tolerance in rice. [ABSTRACT FROM AUTHOR]

Pb can damage the physiological function of human organs by entering the human body via food-chain enrichment. Revealing the mechanisms of maize tolerance to Pb is critical for preventing this. In this study, a Pb-tolerant maize inbred line, 178, was used to analyse transcription factors (TFs) expressed under Pb stress based on RNA sequencing data. A total of 464 genes expressed in control check (CK) or Pb treatment samples were annotated as TFs. Among them, 262 differentially expressed transcription factors (DETs) were identified that responded to Pb treatment. Furthermore, the DETs were classified into 4 classes according to their expression patterns, and 17, 12 and 2 DETs were significantly annotated to plant hormone signal transduction, basal transcription factors and base excision repair, respectively. Seventeen DETs were found to participate in the plant hormone signal transduction pathway, where basic leucine zippers (bZIPs) were the most significantly enriched TFs, with 12 members involved. We further obtained 5 Arabidopsis transfer DNA (T-DNA) mutants for 6 of the maize bZIPs, among which the mutants atbzip20 and atbzip47 , representing ZmbZIP54 and ZmbZIP107 , showed obviously inhibited growth of roots and above-ground parts, compared with wild type. Five highly Pb-tolerant and 5 highly Pb-sensitive in maize lines were subjected to DNA polymorphism and expression level analysis of ZmbZIP54 and ZmbZIP107 . The results suggested that differences in bZIPs expression partially accounted for the differences in Pb-tolerance among the maize lines. Our results contribute to the understanding of the molecular regulation mechanisms of TFs in maize under Pb stress., Competing Interests: The authors declare no conflict of interest.

The protective effect of sesamin (SES) from sesame meal on NIT-1 pancreatic β-cells damaged by streptozotocin (STZ) in vitro was investigated. The cell viability, insulin secretion, the activity of superoxide dismutase(SOD), glutathione peroxidase (GSHpx) and the content of reduced glutathione (GSH) increased significantly when incubated with SES (400, 200 µg mL-1). The content of malondialdehyde (MDA), nitric oxide (NO) production, and the activity of NO synthase (NOS), inducible NOS (iNOS), decreased significantly when incubated with SES. The destructive changes of NIT-1 cells were ameliorated when treated with SES under microscopic observation. These data suggested that SES had obvious protective effect on NIT-1 pancreatic β-cells damaged by STZ, which might be related to its effects of decreasing levels of β-cell-destroying factors such as oxidative stress and NO synthesis.