Agriculture Communications最新文献

The PROSPECT model, widely employed for leaf radiation transfer analysis, relies heavily on input biochemical parameters to calculate spectral reflectance. This dependence often results in similar simulated spectra for different parameter combinations, which complicates the inversion of leaf chlorophyll content (Cab). To address this ill-posed problem, we enhanced the model's application by integrating a support vector machine (SVM)-based parameter combination discriminator with the Look-Up Table (LUT) constructed from the PROSPECT model. We marked samples in the LUT to reflect their closeness to measured parameters, facilitating the identification of reasonable versus unreasonable parameter combinations. The discriminator could effectively discriminate between reasonable and unreasonable parameter combinations, achieving accuracies of 0.894 and 0.888 in the training and test sets, respectively. The discriminator was then employed to refine the LUT, and an improved third-generation non-dominated ranking genetic algorithm (NSGA-III) was used to optimize the extreme learning machine. The inversion of rice Cab using the refined LUT and the NSGA-III demonstrated substantial improvements. The LUT was significantly improved after integration with the discriminator, yielding R² and RMSE of 0.665 and 7.220 ​μg ​cm⁻², respectively. The NSGA-III inversion, which utilized the “constraint method” with discriminator results as optimization objectives, achieved the best inversion accuracy, with R² and RMSE values of 0.809 and 4.788, respectively. This study demonstrates that the effective use of a parameter discriminator can significantly enhance the accuracy of Cab inversion based on the PROSPECT model, offering a substantial advancement in addressing its inherent ill-posed challenges.

Abiotic stresses, such as drought and salt, are major factors affecting plant growth, development, and productivity. The GRAS gene family is a class of transcriptional regulators in plants that influence plant responses to various biotic and abiotic stresses. In this study, we cloned the maize (Zea mays L.) GRAS gene ZmGRAS72 and preliminarily analyzed its biological function. ZmGRAS72 was highly expressed in maize stems and young leaves, and was induced by abiotic stress and phytohormone treatments. Transient expression assays of maize protoplasts showed that ZmGRAS72 was localized to the nucleus. Heterologous expression of ZmGRAS72 in A. thaliana significantly improved plant tolerance to drought and salt stresses, increased chlorophyll content, decreased malondialdehyde content, and enhanced peroxidase activity. In addition, heterologous expression of ZmGRAS72 in A. thaliana upregulated or downregulated the expression levels of abscisic acid biosynthesis genes (NCED3), signaling genes (ABI1, ABI2, ABI4, and ABI5), and stress-related genes (RD22, RD29A, and KIN1) under abiotic stress. These results indicate that ZmGRAS72 may be responsive to abiotic stress, which forms a basis for further research on the mechanisms underlying the action of ZmGRAS72 in maize.

We developed a partial least squares regression (PLSR) model based on competitive adaptive reweighted sampling (CARS) to predict the processing factors of 54 pesticides during soybean oil processing. Characteristic variables were selected to improve the performance of the model. Four calculators were used to compute the molecular descriptors used in the model, and the model based on values computed with ChemoPy produced the best results: Rc ​= ​0.94, RMSEc ​= ​0.67, Rp ​= ​0.91, and RMSEp ​= ​0.54 for hot-pressed oil and Rc ​= ​0.93, RMSEc ​= ​0.73, Rp ​= ​0.93, and RMSEp ​= ​0.59 for cold-pressed oil. A rapid and quantitative model of processing factors was established to predict the behaviour and distribution of pesticide residues during food processing. The model was further validated using data from field-grown soybeans; it demonstrated a high correlation coefficient between predicted and measured residue concentrations (Rp ​> ​0.93, RMSEp ​< ​0.72) and successfully predicted the distribution and behaviour of pesticide residues. Our model provides a reference for assessing safety risk and determining the maximum residue limits for pesticides in processed products.

The Nitrogen Nutrition Index (NNI), based on the Critical Nitrogen Concentration (N_c), is widely utilized to evaluate crop nitrogen nutrition. However, the impact of water deficit on crop N_c remains unclear. To address this, a 3-year joint water-nitrogen regulation experiment on winter wheat was conducted to investigate the responses of N_c dilution curve parameters (A1 and A2 in N_c ​= ​A1DM^−A2, where DM represents aboveground dry biomass), nitrogen accumulation (NA), and grain yield (GY) to different water management strategies. The study employed Bayesian statistical methods to establish the N_c dilution curve, which revealed a slightly lower curve compared to that derived using classical methods. The posterior distribution indicated substantial overlap in parameters A1 (89.8%) and A2 (89.4%) between deficit irrigation (DI) and full irrigation (FI). The overlap of parameter A1 was 67.2% between rainfed and irrigated (DI and FI) treatments, whereas for parameter A2, it was only 29.9%. Analysis of variance showed a significant difference (p ​< ​0.05) in parameter A2 between rainfed and irrigated treatments, but no significant differences were found (p ​> ​0.05) between DI and FI treatments. Additionally, NA and GY of winter wheat displayed insignificant differences between irrigation treatments; however, they were, on overage, significantly higher by 31.2% and 23.2%, respectively, under irrigated conditions compared to rainfed conditions. This study is the first to demonstrate that severe water deficit (rainfed conditions) significantly affects parameter A2 of the N_c dilution curve, underscoring the importance of considering actual water conditions in applying the NNI for nitrogen fertilizer management.

The capitalization of agricultural subsidies is highly relevant to sustainable agricultural development. This study applies meta-analysis to systematically investigate the overall mean effects of capitalization of agriculture subsidies in China, the EU, and the USA. We explore capitalization rates across different types and recipients, including potential sources of heterogeneity. Our primary objective is to address the debate of whether agricultural subsidies are ultimately capitalized into land rental prices. Results show that the overall mean effect of subsidies on land capitalization in the European Union (5.5%) is greater than that in the United States (2.9%), with no significant and positive effects observed in Chinese markets. Additionally, we conclude that decoupled payments may not reduce the capitalization of agricultural subsidies in the European Union and the USA. Notably, agricultural subsidies received by landowners/contractors tend to be lower than those received by tenants. Finally, the capitalization of agricultural subsidies is influenced by several potential sources of heterogeneity, including farmland scales, aggregated data, sample sizes, lagged subsidies, and the starting and ending dates of publications. These findings provide comprehensive insights into the capitalization of agricultural subsidies and offer practical policy recommendations for the effective mitigation of capitalization rates.

Halophytes face continuous challenges from environmental salt conditions throughout their lifecycle, and adaptive strategies are essential for their growth and survival. Hordeum brevisubulatum, a halophytic forage grass, relies on efficient K⁺ uptake for salt tolerance, as demonstrated by the inducible expression of HbHAK2 (high affinity K⁺ transporter 2). Using genome walking, we isolated a unique 744-bp HbHAK2 promoter, distinct from the upstream sequences of HvHAK2 in barley. Transgenic Arabidopsis plants carrying the GUS gene, driven by the HbHAK2 promoter, exhibited higher activity in tissues and cells exhibiting polar growth, including root hairs, lateral root initiation sites, trichomes, and shoot apical meristems (SAM), particularly under various stresses compared to control conditions. In both Arabidopsis and Brachypodium distachyon, the expression of HbHAK2, driven by its promoter (proHbHAK2) improved K⁺ uptake, promoted a root architecture characterized by increased lateral branching, and enhanced salt tolerance by augmenting the root system (including lateral roots and root-hair development and growth) under salt stress. Therefore, variation in the HbHAK2 promoter represents a specific strategy for halophytic H. brevisubulatum to cope with salt stress, which holds potential for improving salt tolerance in crop breeding programs.

Brassica species, globally cultivated as economically important vegetable and oilseed crops, face challenges from pathogens impacting their growth and productivity. Among these, blackleg, caused by the fungal pathogen Leptosphaeria maculans, stands out as a significant concern. Genetic resistance, primarily mediated by resistance gene analogues (RGAs), is key to sustainable blackleg control. Utilising wild relatives of Brassica species presents a promising avenue for enhancing resistance to blackleg in cultivated crops. In this study, we employed the newly published Hirschfeldia incana reference genome to identify the genome-wide RGAs in H. incana. A total of 914 candidate RGAs were identified; the receptor-like protein kinases (RLK) family contained the highest number with 608 (66.53%), followed by the Transmembrane coiled-coil (TM-CC) family with 167 (18.27%), nucleotide-binding site-leucine-rich repeats (NLR) family with 98 (10.72%) and receptor-like proteins (RLPs) with 41 (4.48%). We conducted duplication analysis on the 914 candidate RGAs, which revealed gene duplication occurs frequently to expand the RGAs in H. incana and significantly contributes to plant defence responsiveness. The phylogenetic analysis provided insights into the diversification and functional implications of the identified groups. We used the sequences of the 49 cloned R genes to identify homologs across H. incana. A total of 75 cloned disease-resistance gene homologs (CDRHs) were found. Cis-acting elements (CREs) were analysed in promoter sequences of 914 RGAs in H. incana, which confirmed their potential function in disease defence. Overall, the results suggest that the wild species H. incana could be a potential R gene source for various disease resistances, including blackleg.

The composition and content of fatty acids (FAs) and amino acids (AAs) are important nutritional and sensory traits in aquaculture fish. To meet increasing demand while retaining quality, genetic selection in breeding programs is urgently needed to improve these traits. In this study, we performed the genome-wide association study (GWAS) to identify genetic variants and candidate genes potentially linked to FA and AA compositions in grass carp muscle. We focused on key dietary components, including unsaturated FAs and essential AAs. Through profiling of total FA and AA contents, we identified strong positive correlations among the compositions of most FAs and AAs. From our GWAS panel, 4,913,199 high-quality single nucleotide polymorphisms (SNPs) were identified across the genome, of which 32 SNPs linked to 18 candidate genes were significantly associated with FA levels, and 202 SNPs linked to 115 candidate genes associated with AA contents. In addition, we categorized our sequencing population by region and detected allele frequencies of SNPs across four geographic locations. Notably, four FA-associated SNPs and 28 AA-associated SNPs exhibited geographic specificity. These results offered valuable insights into the complex genetic basis of FA and AA metabolism and deposition. Furthermore, this work provides potential genetic markers for selective breeding aimed at enhancing flesh quality in the economically important fish species, grass carp.

Utilizing image-based computer vision techniques, many high-throughput phenotyping methods have been employed to capture intricate growth trait characteristics, offering reliable estimates of phenotypic traits crucial for breeding programs. In this study, we explored the application of partial differential equation (PDE)-based level set approaches to introduce image-based body area percentage (IBAP) as a novel growth trait in Plectropomus leopardus, as a substitution for the traditional growth trait body weight (BW). Assessing the genetic parameters essential for robust growth trait improvement in P. leopardus breeding programs, we estimated SNP-based heritability for IBAP and BW using a comprehensive set of SNPs (673,039 SNPs with MAF >2%). Results revealed heritability estimates of 0.515 (S.E. 0.06) for IBAP and 0.542 (S.E. 0.06) for BW. Moreover, strong phenotypic and genetic correlations of 0.812 (S.E. 0.001) and 0.903 (S.E 0.021) between IBAP and BW, respectively, underscored the potential for IBAP as a surrogate trait of BW for the genetic improvement of P. leopardus. We established a linear regression model of IBAP and BW (y ​= ​−730 ​+ ​1700×, (R² ​= ​0.71)), after rigorous assessments of linearity, normality, and homoscedasticity, to confirm model fit. Evaluation of breeding value prediction accuracies using two linear models (rr-GBLUP and Bayes B) and a non-linear (RKHS) model demonstrated the superior performance of RKHS across IBAP and BW. Exploring the impact of varied marker densities for SNP selection on genomic prediction accuracy for IBAP and BW demonstrated a threshold of 10,000 SNPs for maximal model accuracy. These findings provide essential reference information and methodological groundwork for leveraging image-based traits in P. leopardus breeding endeavors, facilitating more efficient and precise genetic improvement programs.

Fruit has an important role in human nutrition and health; therefore, the systematic study of fruit genomic data is essential. The Genomic Database of Fruits (TGDF, http://tgdf.bio2db.com/), established through whole-genome analyses of 44 fruit species, is a comprehensive, user-friendly fruit database. TGDF contains a wealth of functional genes, including 11,350 flowering genes, 3161 auxin signaling genes, 2164 anthocyanin synthesis genes, 1464 abscisic acid (ABA) synthesis genes, 10,931 ​cell division and expansion genes, 1786 starch synthesis genes, 294 fruit size genes, and 6311 sugar transporter genes. Additionally, TGDF contains 1,433,368 CRISPR guide sequences from various fruit genomes, along with information on homologous genes and duplication types for the 44 fruit species. TGDF contains 6,417,060 gene annotations sourced from TrEMBL, SwissProt, Nr, and Gene Ontology databases, along with tools such as Sequence Fetch, BLAST, Synteny, and JBrowse for bioinformatics analyses. Transcriptomic data were also collected and collated from fruits, including details on instruments, tissues, or growth stages. This comprehensive, user-friendly resource is the first collection of fruit genomic data. Users can easily download genomic sequences, gene annotations, and bioinformatics analysis results from TGDF, which will be updated continually. We anticipate that TGDF will become a primary resource for fruit comparative and functional genomic studies.