Search Results (51)

CO₂ geo-storage is a promising approach in reducing greenhouse gas emissions and controlling global temperature rise. Although numerous studies have reported that offshore saline aquifers have greater storage potential and safety, current suitability evaluation models for CO₂ geo-storage primarily focus on onshore saline aquifers, and site-level evaluations for offshore CO₂ geo-storage remain unreported. In this study, we propose a framework to evaluate the site-level offshore CO₂ geo-storage suitability with a multi-tiered indicator system, which considers three types of factors: engineering geology, storage potential, and socio-economy. Compared to the onshore CO₂ geo-storage suitability evaluation models, the proposed indicator system considers the unique conditions of offshore CO₂ geo-storage, including water depth, offshore distance, and distance from drilling platforms. The Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) methods were integrated and applied to the analysis of the Ying–Qiong Basin, South China Sea. The results indicated that the average suitability score in the Yinggehai Basin (0.762) was higher than that in the Qiongdongnan Basin (0.691). This difference was attributed to more extensive fault development in the Qiongdongnan Basin, suggesting that the Yinggehai Basin is more suitable for CO₂ geo-storage. In addition, the DF-I reservoir in the Yinggehai Basin and the BD-A reservoir in the Qiongdongnan Basin were selected as the optimal CO₂ geo-storage targets for the two sub-basins, with storage potentials of 1.09 × 10⁸ t and 2.40 × 10⁷ t, respectively. This study advances the methodology for assessing site-level potential of CO₂ geo-storage in offshore saline aquifers and provides valuable insights for engineering applications and decision-making in future CO₂ geo-storage projects in the Ying–Qiong Basin. Full article

The leaf plastochron serves as an indicator of the rate of leaf appearance, biomass accumulation, and branch number, while also impacting plant architecture and seed yield. However, research on the leaf plastochron of crops remains limited. In this study, 2116C exhibited a rapid leaf plastochron compared to ZH18 during both rosette and bud periods. There were significant positive correlations among the leaf plastochron and primary branch number of the F₂ populations (r ranging from 0.395 to 0.635, p < 0.01). Genetic analyses over two years demonstrated that two equally dominant genes might govern the leaf plastochron. Through bulk segregant analysis sequencing (BSA-seq), three novel genomic intervals were identified on chromosomes A02 (9.04–9.48 Mb and 13.52–13.66 Mb) and A04 (19.84–20.14 Mb) of ZS11 and Darmor-bzh reference genomes. By gene functional annotations, single-nucleotide variation (SNV) analyses, transcriptome data from parents, genetic progeny, and natural accessions, we identified ten candidate genes within the intervals, including FLOWERING LOCUS T, RGL1, MYB-like, CYP96A8, BLH3, NIT2, ASK6, and three CLAVATA3/ESR (CLE)-related genes. These findings lay the molecular foundation for further exploration into the leaf plastochron and the implications in plastochron-related breeding in rapeseed. Full article

In the present study, an electrospinning freshness monitoring film prepared by gelatin/zein loading with purple sweet potato anthocyanins (PSPA) was produced to track the freshness state of Penaeus vannamei. The electrospun nanofiber films with the gelatin and zein weight ratio of 1:0, 3:1, 2:1, and 1:1 were named GA, GZA 3:1, GZA 2:1, and GZA 1:1, respectively. The impacts of zein concentration on the electrospun nanofiber film properties were investigated. SEM results showed that a smooth surface was observed for the electrospun nanofiber films. As the zein content increased, the average diameter decreased. No new characteristic peaks were shown by FTIR and XRD, indicating the good compatibility between gelatin, zein, and PSPA. The incorporation of zein decreased the swelling ratio (from completely dissolved to 100.7%) and water solubility (from 100% to 30%) and increased the water contact angle (from 0° to 113.3°). The GA, GZA 3:1, GZA 2:1, and GZA 1:1 had apparent color changes to NH₃ and demonstrated good stability and reversibility. Furthermore, the freshness states (fresh, sub-fresh, and spoiled) of Penaeus vannamei storage at 4 °C could be effectively distinguished by GZA 3:1 by showing different colors (from pink to grayish purple to blue). Consequently, GZA3:1 exhibited improved hydrophobicity and pH sensitivity and has great potential in real-time monitoring of aquatic product quality. Full article

β-ketoacyl-CoA synthase (KCS) enzymes play a pivotal role in plants by catalyzing the first step of very long-chain fatty acid (VLCFA) biosynthesis. This process is crucial for plant development and stress responses. However, the understanding of KCS genes in maize remains limited. In this study, we present a comprehensive analysis of ZmKCS genes, identifying 29 KCS genes that are unevenly distributed across nine maize chromosomes through bioinformatics approaches. These ZmKCS proteins varied in length and molecular weight, suggesting functional diversity. Phylogenetic analysis categorized 182 KCS proteins from seven species into six subgroups, with maize showing a closer evolutionary relationship to other monocots. Collinearity analysis revealed 102 gene pairs between maize and three other monocots, whereas only five gene pairs were identified between maize and three dicots, underscoring the evolutionary divergence of KCS genes between monocotyledonous and dicotyledonous plants. Structural analysis revealed that 20 out of 29 ZmKCS genes are intronless. Subcellular localization prediction and experimental validation suggest that most ZmKCS proteins are likely localized at the plasma membrane, with some also present in mitochondria and chloroplasts. Analysis of the cis-acting elements within the ZmKCS promoters suggested their potential involvement in abiotic stress responses. Notably, expression analysis under abiotic stresses highlighted ZmKCS17 as a potential key gene in the stress response of maize, which presented an over 10-fold decrease in expression under salt and drought stresses within 48 h. This study provides a fundamental understanding of ZmKCS genes, paving the way for further functional characterization and their potential application in maize breeding for enhanced stress tolerance. Full article

Accurate and timely extraction and evaluation of sandy land are essential for ecological environmental protection; it is urgent to do the research to support the sustainable development goals (SDGs) of Land Degradation Neutrality. This study used Sentinel-1 Synthetic Aperture Radar (SAR) data and Landsat 8 OLI multispectral data as the main data sources. Combining the rich spectral information from optical data and the penetrating advantages of radar data, a feature-level fusion method was employed to unveil the intrinsic nature of vegetative cover and accurately identify sandy land. Simultaneously, leveraging the results obtained from training with measured data, a comprehensive desertification assessment model was proposed, which combines multiple indicators to achieve a thorough evaluation of sandy land. The results showed that the method based on feature-level fusion achieved an overall accuracy of 86.31% in sandy land detection in Gansu Province, China. The integrated multi-indicator model C22_C/FVC is the ratio of correlation texture features of VH to vegetation cover based on which sandy land can be classified into three categories. When C22_C/FVC is less than 2.2, the pixel is classified as fixed sandy land. Pixels of semi-fixed sandy land have an indicator value between 2.2 and 5.2. Shifting sandy land has values greater than 5.2. Results showed that shifting sandy land and semi-fixed sandy land are the predominant types in Gansu Province, with 85,100 square kilometers and 87,100 square kilometers, respectively. The acreage of fixed sandy land was the least, 51,800 square kilometers. The method presented in this paper is robust for the detection and evaluation of sandy land from satellite imageries, which can potentially be applied for conducting high-resolution and large-scale detection and evaluation of sandy land. Full article

To investigate the effects and mechanism of prolonged inorganic nitrogen (N) fertilization on the N-use efficiency of spring wheat (Triticum aestivum L.), a long-term study initiated in 2003 was conducted. The study analyzed how N fertilization affects dry matter translocation, N translocation, soil NO₃-N, and N-use efficiency. Five different N-fertilizer rate treatments were tested: N0, N52.5, N105, N157.5, and N210, corresponding to annual N fertilizer doses of 0, 52.5, 105.0, 157.5, and 210.0 kg N ha⁻¹, respectively. Results showed that increasing N-fertilizer rates significantly enhanced the two-year average dry matter accumulation amount (DMA) at maturity by 22.97–56.25% and pre-flowering crop growth rate (CGR) by 17.11–92.85%, with no significant increase beyond 105 kg N ha⁻¹. However, no significant correlation was observed between the dry matter translocation efficiency (DTE) and wheat grain yield. Both insufficient and excessive N applications resulted in an imbalanced N distribution favoring vegetative growth over reproductive growth, thus negatively impacting N-use efficiency. At maturity, the N-fertilized treatments significantly increased the two-year average N accumulation amount (NAA) by 52.04–129.98%, with no further increase beyond 105 kg N ha⁻¹. N fertilization also improved the two-year average N translocation efficiency (NTE) by 56.89–63.80% and the N contribution proportion (NCP) of wheat vegetative organs by 27.79–57.83%, peaking in the lower-N treatment (N52.5). However, high-N treatment (N210) led to an increase in NO₃-N accumulation in the 0–100 cm soil layer, with an increase of 26.27% in 2018 and 122.44% in 2019. This higher soil NO₃-N accumulation in the 0–100 cm layer decreased NHI, NUE, NAE, NPFP, and NMB. Additionally, N fertilization significantly reduced the two-year average N harvest index (NHI) by 9.89–12.85% and N utilization efficiency (NUE) by 11.14–20.79%, both decreasing with higher N application rates. The NAA followed the trend of anthesis > maturity > jointing. At the 105 kg N ha⁻¹ rate, the highest N agronomic efficiency (NAE) (9.31 kg kg⁻¹), N recovery efficiency (NRE) (38.32%), and N marginal benefit (NMB) (10.67 kg kg⁻¹) were observed. Higher dry matter translocation amount (DTA) and N translocation amount (NTA) reduced NHI and NUE, whereas higher NTE improved NHI, NUE, and N partial factor productivity (NPFP). Overall, N fertilization enhanced N-use efficiency in spring wheat by improving N translocation rather than dry matter translocation. Full article

A novel compact broadband negative group delay (NGD) circuit with flatness and bandwidth enhancement is presented. The presented negative group delay circuit (NGDC) consists of a high-impedance transmission line connected by two resistors, which are linked together with two coupled lines and a low-impedance transmission line. The flatness of the NGD is enhanced by tuning the characteristic impedance of the transmission lines. In order to verify the method, a compact broadband NGDC with a size of 29.4 mm × 58.1 mm (0.14 λ_g × 0.29 λ_g) is designed, fabricated, and measured at the center frequency of 1.0 GHz. The measured results show that an NGD time of −0.49 ns at the center frequency is obtained with return loss and insertion loss of 35.0 dB and 18 dB, respectively. And, the flat-NGD bandwidth reaches 509 MHz (50.9%) over 0.766 to 1.275 GHz with 19% group-delay fluctuation. Full article

The role of amino acid transporter (AAT) genes in facilitating the transmembrane movement of amino acids between cells and various cellular components has been characterized in several plant species. Quinoa (Chenopodium quinoa Willd.), a renowned nutritious crop known for its amino acid composition, has not yet had its AAT genes characterized. Therefore, the identification and characterization of AAT genes in quinoa will help bridge this knowledge gap and offer valuable insights into the genetic mechanisms underlying amino acid transport and metabolism. This study focuses on gene expression, gene structure, duplication events, and a comparison of functions studied to establish the role of AAT genes. A total of 160 non-redundant AAT genes were identified in quinoa and classified into 12 subfamilies, with 8 subfamilies belonging to the amino acid/auxin permease (AAAP) family and 4 to the amino acid-polyamine-organocation (APC) superfamily family. The chromosomal localization, gene structures, and conserved motifs of these genes were systematically analyzed. Expression profiling revealed diverse expression patterns across various tissues and in response to drought and salt stresses. Segmental and tandem duplications were found to contribute to the gene duplication and expansion of the CqAAT gene family. Additionally, CqCAT6 and CqAAP1 were predicted to regulate the long-distance transportation and distribution of amino acids, making them potential candidate genes for further research. Overall, this information could serve as a foundation for the identification and utilization of CqAATs in Quinoa, enhancing our understanding of amino acid transport mechanisms in this important crop. Full article

This study aims to understand the influence of nitrogen accumulation, fungal endophyte, yield, nitrogen use efficiency, and grain nutritional quality parameters on the yield of quinoa in some areas of China. The endophytic microbial community in plants plays a crucial role in plant growth, development, and health, especially in quinoa plants under different nitrogen fertilizer levels. The results from the present study indicated that appropriate nitrogen application significantly enhanced the nitrogen accumulation and yield of quinoa grains during maturity, increasing by 34.54–42.18% and 14.59–30.71%, respectively. Concurrently, protein content, amylose, total starch, ash, and fat content also increased, with respective growth rates of 1.15–18.18%, 30.74–42.53%, 6.40–12.40%, 1.94–21.94%, and 5.32–22.22%. Our constructed interaction network of bacterial and fungal communities revealed that bacteria outnumbered fungi significantly, and most of them exhibited synergistic interactions. The moderate increase in N150 was beneficial for increasing quinoa yield, achieving nitrogen use efficiency (NUE) of over 20%. The N210 was increased, and both the yield and NUE significantly decreased. This study provides novel insights into the impact of nitrogen fertilizer on quinoa growth and microbial communities, which are crucial for achieving agricultural sustainable development. Full article

In recent years, the semantic segmentation model has been widely applied in fields such as the extraction of crops due to its advantages such as strong discrimination ability, high accuracy, etc. Currently, there is no standard set of ground true label data for major crops in China, and the visual interpretation process is usually time-consuming and laborious. The sample size also makes it difficult to support the model to learn enough ground features, resulting in poor generalisation ability of the model, which in turn makes the model difficult to apply in fine extraction tasks of large-area crops. In this study, a method to establish a pseudo-label sample set based on the random forest algorithm to train a semantic segmentation model (U-Net) was proposed to perform winter wheat extraction. With the help of the GEE platform, Winter Wheat Canopy Index (WCI) indicators were employed in this method to initially extract winter wheat, and training samples (i.e., pseudo labels) were built for the semantic segmentation model through the iterative process of “generating random sample points—random forest model training—winter wheat extraction”; on this basis, the U-net model was trained with multi-time series remote sensing images; finally, the U-Net model was employed to obtain the spatial distribution map of winter wheat in Henan Province in 2022. The results illustrated that: (1) Pseudo-label data were constructed using the random forest model in typical regions, achieving an overall accuracy of 97.53% under validation with manual samples, proving that its accuracy meets the requirements for U-Net model training. (2) Utilizing the U-Net model, U-Net++ model, and random forest model constructed based on pseudo-label data for 2022, winter wheat mapping was conducted in Henan Province. The extraction accuracy of the three models is in the order of U-Net model > U-Net++ model > random forest model. (3) Using the U-Net model to predict the winter wheat planting areas in Henan Province in 2019, although the extraction accuracy decreased compared to 2022, it still exceeded that of the random forest model. Additionally, the U-Net++ model did not achieve higher classification accuracy. (4) Experimental results demonstrate that deep learning models constructed based on pseudo-labels exhibit higher classification accuracy. Compared to traditional machine learning models like random forest, they have higher spatiotemporal adaptability and robustness, further validating the scientific and practical feasibility of pseudo-labels and their generation strategies, which are expected to provide a feasible technical pathway for intelligent extraction of winter wheat spatial distribution information in the future. Full article

Blackleg disease, a major threat to Brassica crops worldwide, is primarily caused by the pathogen Leptosphaeria biglobosa. Investigating the genetic variation of L. biglobosa is crucial for managing and preventing the disease in Brassica napus. To date, there is scarce genomic variation information available for populations of L. biglobosa in China. In this study, 73 L. biglobosa strains of canola stalks were collected from 12 provinces in China and subjected to re-sequencing. The 73 assemblies averaged 1340 contigs, 72,123 bp N50, and 30.17 Mb in size. In total, 9409 core orthogroups and 867 accessory orthogroups were identified. A total of 727,724 mutation loci were identified, including 695,230 SNPs and 32,494 indels. Principal component analysis (PCA) and population structure analysis showed that these strains could be divided into seven subgroups. The strains in most provinces were clustered into a single subgroup, suggesting a strong influence of the geographic environment on strain variation. The average nucleotide diversity (θπ) of all strains was 1.03 × 10⁻³, indicating important genetic diversity among strains from different regions of China. This study provides valuable resources for future comparative genomics, gives new insights into the population evolution of L. biglobosa, and supports the development of strategies for managing blackleg disease in canola. Full article

In this study, 300 quinoa accessions were systematically screened for adaptation to low-altitude areas using seventeen traits. The experiment was conducted in Taigu District, Jinzhong City, Shanxi Province, in 2021, at an altitude of 791 m. Out of the 300 genotypes, 107 were able to produce flowers and fruit, with yields ranging from 538 to 5132 kg ha⁻¹ and with 1000-grain weights between 1.19 g and 2.37 g. These 107 quinoa genotypes were categorized into four groups based on grain yield: below 1500, 1500–2250, 2250–3000, and above 3000 kg ha⁻¹. These groups consisted of 33, 33, 24, and 17 genotypes, respectively. This study found that the 1000-grain weight ranged from 1.19 g to 2.37 g, with an average of 1.72 g, 1.72 g, 1.83 g, and 1.92 g for the respective yield levels. Among the 107 genotypes, 25 had a 1000-grain weight exceeding 2 g, and 13 of these genotypes also had yields exceeding 2250 kg ha⁻¹. The growth period of quinoa genotypes in the low-altitude area was approximately 138–142 days, with longer growth periods associated with higher yield levels. JQ-00084 is the only genotype with a yield > 3000 kg ha⁻¹ and meets all the growth criteria, including a 1000-grain weight exceeding 2 g and a flowering-to-maturity period of over 80 days. Meanwhile, JQ-00315, JQ-00521, JQ-1029, and JQ-02405 fulfilled at least four criteria. These results highlight the importance of germplasm screening for low altitudes, and a large set of germplasms could be screened using the above criteria of phenology, growth, and yield traits. Full article

Crop rotation has been considered a potential solution to mitigate the negative effects of the continuous cropping of sorghum, including soil quality issues, inadequate plant development, and diminished yield and quality. A two-year field experiment was conducted to compare the effects of sorghum–sorghum continuous cropping and quinoa–sorghum rotation on soil properties and sorghum yield. The treatments were arranged in a randomized complete block design with three replicates. Sorghum seeds (Jinza 22) and quinoa seeds (‘Jiaqi 1’ variety) were used. Soil samples were collected before and during the experiment for the analysis of physicochemical properties. The yield traits of sorghum were measured at maturity. The results showed that soil nutrients and organic matter were higher in the top 0–20 cm soil depth compared to 20–40 cm depth, with significant differences observed between cropping systems. Sorghum–quinoa cropping increased soil total N and organic matter, particularly at the jointing and maturity stages of sorghum. However, the available phosphorus was higher under continuous cropping at all growth stages. Crop rotation significantly improved sorghum yield traits, including spike fresh weight, spike dry weight, grain weight per spike, and grain yield per hectare. A correlation analysis revealed positive relationships between soil total N, organic matter, and sorghum yield. Overall, sorghum–quinoa rotation demonstrated potential for improving soil fertility and enhancing crop productivity compared to continuous cropping, although further studies are needed to explore the long-term effects and optimize management practices. Full article

Genome selection (GS) technology is an important means to improve the genetic improvement of dairy cows, and the mining and application of functional genes and loci for important traits is one of the important bases for accelerating genetic improvement. Our previous study found that the apolipoprotein A5 (APOA5) and AKT serine/threonine kinase 3 (AKT3) genes were differentially expressed in the liver tissue of Chinese Holstein cows at different lactation stages and influenced milk component synthesis and metabolism, so we considered these two genes as the candidates affecting milk production traits. In this study, we found in total six single nucleotide polymorphisms (SNPs), three in APOA5 and three in AKT3. Subsequent association analysis showed that the six SNPs were significantly associated with milk yield, fat yield, protein yield, or fat percentage (p ≤ 0.05). Three SNPs in APOA5 formed a haplotype block, which was found to be significantly associated with milk yield, fat yield, and protein yield (p ≤ 0.05). In addition, four SNPs were proposed to be functional mutations affecting the milk production phenotype, of which three, 15:g.27446527C>T and 15:g.27447741A>G in APOA5 and 16:g.33367767T>C in AKT3, might change the transcription factor binding sites (TFBSs), and one is a missense mutation, 15:g.27445825T>C in APOA5, which could alter the secondary structure and stability of mRNA and protein. In summary, we demonstrated the genetic effects of APOA5 and AKT3 on milk production traits, and the valuable SNPs could be used as available genetic markers for dairy cattle’s GS. Full article