To investigate the differences in components and bioactivities of Polygonatum cyrtonema Hua （PC）， Lycium chinense Mill （LC） and Panax ginseng C. A. Mey （PG） under varying compatibility ratios， this study determined the contents of total sugar， total phenolic， total saponin， and other substances， and assessedantioxidant capacity in vitro. The optimal formulations were selected through the comprehensive evaluation and the oxidative stress and lipid-lowering activity were validated through the Caenorhabditis elegans model. The results revealed that there was a correlation between herb-ingredients-activity， and some combinations showed synergistic effect on activities. Following comprehensive evaluation， the combination of PC， PC and PG in ratio of 1∶2∶0 （PC-LC）， 2∶0∶1 （PC-PG）， and 1∶2∶1 （PC-LC-PG） demonstrated superior overall performance compared to other proportional combinations within the same formulation. The C. elegans model experiment demonstrated that the PC-LC group could enhance on superoxide dismutase （SOD） activity compared to the control group， and its inhibitory effect on malondialdehyde （MDA） accumulation was better than that of the single- drug administration groups. In terms of lipid-lowering activity， the triglyceride content of PC-LC-PG group （low concentration） and PC-PG group （high concentration） was significantly lower than that of single drug （P<0.05）， thereby indicating a synergistic effect. Consequently， in the compatibility of PC， LC and PG， the changes of herb-components-activities were correlated， and some of the compatibility showed synergistic effects in antioxidant and lipid-lowering. This study reveals the variation patterns of components and activities after the compatibility of PC， LC， and PG， which provide references for the subsequent development of products formulated with PC and the utilization of related resources.

To investigate the effects of different concentrations of exogenous 5-aminolevulinic acid （ALA） and boron fertilizer on the growth of sweet potato and the accumulation of soluble sugars in tuberous roots.Sweet potato varieties Violet and Hami were used as test materials. The field experiment was conducted in a split-plot design with different concentrations of boron fertilizer （BNa₃O₃， 0， 2， 4， and 8 g·L^-1） and ALA （0， 50， 100， and 150 mg·L^-1） spraying during the reproductive period of sweet potato. The aboveground vine length， leaf area， the ratio of top to root （T/R ratio）， photosynthetic parameters， and the content of soluble sugar， sucrose， fructose， and glucose in the belowground were measured at 60， 90， and 120 days after transplanting （DAP）of sweet potato， respectively. The correlation between the indexes was analyzed. The results showed that the 8 g·L^-1 boron fertilizer concentration treatment significantly increased the soluble sugar， sucrose， fructose， and glucose contents compared with the treatment without boron fertilizer. The low concentration of ALA promoted the growth and metabolism of sweet potato， and 50-100 mg·L^-1 ALA was more beneficial for promoting the accumulation of soluble sugars in sweet potato tubers. Sweet potato yield gradually increased with increasing boron fertilizer concentration， while exhibited a trend of an initial increase followed by a decrease with increasing ALA concentration. Violet had the highest yield under the interaction treatment of 8 g·L^-1 boron fertilizer and 100 mg·L^-1 ALA， with a theoretical yield of 87 817.50 kg·hm^-2， and Hami had the highest yield under the interaction treatment of 8 g·L^-1 boron fertilizer and 50 mg·L^-1 ALA， with a theoretical yield of 83 497.50 kg·hm^-2. Correlation analysis showed that the soluble sugar content was highly significantly correlated with photosynthetic parameters， sucrose content， fructose content， and yield. In conclusion， the combined application of 8 g·L^-1 boron fertilizer and 50-100 mg·L^-1 ALA had a better effect on the growth， yield， and soluble sugar accumulation of sweet potato. The results of this study provide a theoretical basis for the regulation of soluble sugar accumulation and high-quality cultivation of sweet potato.

To evaluate the freshness-preserving effects of 1-methylcyclopropene （1-MCP） and ethylene absorber （EA） on the post-harvest storage of prunes， this study evaluated the effects of 1-methylcyclopropene （1-MCP）， ethylene absorbents （EA）， and their combined application （EA+1-MCP） on maintaining postharvest quality and flavor characteristics of ‘French’ plums （Prunus domestica L.） during cold storage （0 ℃， relative humidity 80%-90%）. The results showed that all three treatment groups delayed the deterioration of fruit quality compared to the control group （CK）， with the EA+1-MCP treatment group demonstrating the most significant preservation effect. This combined treatment significantly suppressed the increases in weight loss rate， relative electrical conductivity， and chromatic parameters （L^* and b^* ）， while effectively inhibiting the decreases in a^* values， fruit firmness， and titratable acidity. It maintained higher soluble solids content， postponed respiratory and ethylene production peaks， and resulted in 30.31% higher total phenolic content and 23.53 percentage points higher ascorbic acid retention rate compared to CK at the end of cold storage. Electronic nose and electronic tongue analyses further confirmed that EA+1-MCP treatment optimally preserved prune-specific flavor profiles during cold storage. In conclusion， the synergistic EA+1-MCP treatment demonstrated superior efficacy in maintaining postharvest quality and flavor integrity of prunes. This study provides scientific guidance for the research and development of postharvest storage and preservation technologies for prunes.

MYB is one of the most abundant and functionally diverse transcription factors in fungi， representing a highly conserved family of transcription factors in eukaryotes. To identify the MYB family in Ganoderma lingzhi and the potential role in the metabolism of pharmacodynamic ingredients， based on the whole genome of Ganoderma lingzhi， this study identified members of the MYB gene family in G. lingzhi using a hidden Markov model. Bioinformatics methods were employed to analyze their chromosomal localization， collinearity， gene structure， phylogenetic tree， and cis-regulatory elements. Additionally， qRT-PCR was used to examine the expression levels of G. lingzhi MYB under MeJA and in different tissues. The results revealed that G. lingzhi harbors 9 MYB members （GlMYB1-GlMYB9）， which were classified into 4 subfamilies and distributed across 9 different chromosomes. Interspecies collinearity analysis demonstrated the conservation of G. lingzhi within the Polyporaceae family， while phylogenetic tree and conserved motif analyses indicated the evolutionary conservation of G. lingzhi MYB. Promoter cis-element analysis showed that G. lingzhi MYB contains numerous light responsive elements， hormone responsive elements， and stress responsive elements， particularly jasmonic acid responsive elements. The results of qRT-PCR confirmed that the expression levels of GlMYB varied significantly across different developmental stages， with GlMYB9 showing high expression in mycelium， young fruiting bodies， and mature fruiting bodies. Under MeJA treatment， the expression of most GlMYB members was upregulated， except for GlMYB1， GlMYB5， and GlMYB7. Notably， GlMYB4 and GlMYB9 exhibited the most pronounced upregulation. These findings identified key candidate genes that may play crucial roles in G. lingzhi development and stress responses and provided an important theoretical foundation for further exploration of the physiological mechanisms underlying G. lingzhi growth and development， as well as its responses to hormones and abiotic stress， and offer insights into the genetic regulation of secondary metabolism in G. lingzhi.

The effects of different probiotics fermentation on strawberry juice quality， screening of the best strains， and optimization of the fermentation process were studied to develop nutritional， healthy and flavoured strawberry juice fermented with probiotics. Results showed that the pH， total phenolics， total flavonoids and antioxidant capacity of probiotic fermented strawberry juice were significantly reduced， but the total acid content increased by 17.05%-63.07% than unfermented strawberry juice. A total of 64 volatile organic compounds were detected in strawberry juice， including 12 ketones， 20 esters， 8 acids， 7 aldehydes， 13 alcohols， and 4 other compounds. The probiotic fermented strawberry juice had higher levels of ketones （323.7-573.0 µg·L^-1）， acids （677.4-2 592.9 µg·L^-1）， alcohols （576.7-827.4 µg·L^-1） and other compounds （133.7-1 676.6 µg·L^-1） than unfermented strawberry juice. Lactiplantibacillus plantarum showed the best overall performance based on the coefficient of variation method and was the best strain for strawberry juice fermentation. At optimal fermentation time （23 h）， fermentation temperature （34 ℃） and inoculum size （4%），the Lactiplantibacillus plantarum fermented strawberry juicehad 7.48 lg （CFU·mL^-1） of viable cell count， 87.0 of sensory score and 47.24 of composite score. Results of this study could provide insights into the comprehensive processing and high-valued utilization of strawberries.

To improve the accuracy of wheat yield estimation， this study employed 270 recombinant inbred lines （RILs） derived from the ZM 578/JM 22 population. Canopy multispectral data collected at seven key growth stages were used to construct yield prediction models based on seven machine learning algorithms. The results show that， compared to normalized difference vegetation index （NDVI）， the proposed overall differential response vegetation index （ODRVI） demonstrated stronger yield correlations during the flag leaf， early grain-filling， late grain-filling， and wax-ripening stages. 13 vegetation indices and 4 multispectral bands at the flag leaf， flowering， early grain-filling， and middle grain-filling stages exhibited significant correlations with yield （|r|≥0.53）. The early grain-filling and middle grain-filling stages were identified as the optimal periods for single-time series yield prediction， with R² values ranging from 0.53 to 0.63. The R² threshold range for deep learning models （0.69~0.72） was lower than that of other machine learning models （0.66~0.74）， demonstrating more stable fitting performance. By incorporating stratified sampling cross-validation， the R² of the predictive models improved by 2.85%-7.91%. The ridge regression model based on multi-temporal stratified sampling exhibited the highest predictive accuracy ［R²=0.74， root mean square error （RMSE）=0.51 t·hm^-²， mean absolute error （MAE）=0.41 t·hm⁻²］. This study improves the accuracy of wheat yield prediction models through optimized machine learning algorithms， providing technical support for precision management in crop production.

To explore the potential mechanism of Polygonatum Rhizome in intervening Type Ⅱ diabetes mellitus （T2DM）， network pharmacology and cell experiments were conducted to screen its active components and corresponding targets using TCMSP database， while T2DM related targets were curated from Genecards and Omim databases. Venny tools were utilized to identify the common targets between Polygonatum Rhizome and T2DM. The David database was employed to perform Gene Ontology（GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis on these shared targets. Cytoscape software was then utilized to construct an “active component- target- pathway” interaction network. An insulin-resistant HepG2 （IR-HepG2） cell model was established to assess the impacts of active components extracted from Polygonatum rhizome on cellular glucose consumption， uptake， and the expression of key targets. The results indicated that 13 active components identified from Polygonatum Rhizome， including baicalein and diosgenin， were were associated with 67 common targets such as protein kinase B（AKT1）， tumor protein P53（TP53）， mitogen-activated protein kinase（MAPK）. These targets were enriched in 154 signaling pathways， including the phosphatidylinositol 3 kinase-protein kinase B （PI3K/AKT） pathway and the advanced glycation end products-receptor for advanced glycation end products （AGE-RAGE） pathway， both critically implicated in diabetes pathogenesis. The main active components of Polygonatum Rhizome were found to enhance glucose consumption and uptake in IR-HepG2 cells to varying degrees and upregulate the expression of AKT1 and PI3K. In conclusion， components such as baicalein and diosgenin may intervene in T2DM by targeting AKT1 and PI3K， thereby regulating the PI3K/AKT signaling pathway. The study provides a scientific foundation for developing Polygonatum Rhizome as a medicinal and edible health product aimed at type Ⅱ diabetes prevention.

Auxin response factor （ARF） is a kind of crop-specific auxin-responsive transcription factor， which regulates plant growth and development through the auxin metabolic pathway. To investigate the role of ARF transcription factors during the development of maize kernels， the ZmARFTF2 （Zm00001eb045640 ） gene was cloned in the study. Bioinformatics analysis revealed that the gene was located on chromosome 1 of the maize reference genome， with a coding sequence （CDS） of 2 076 bp encoding 691 amino acids. The predicted ZmARFTF2 protein contains a transmembrane domain and the isoelectric point （pI） is 7.92. Structural analysis identified conserved domains characteristic of the B3 subfamily and Auxin_resp superfamily. Promoter analysis of the 2 kb upstream region identified cis-acting elements associated with ABA biosynthesis， drought induction， gibberellin response， and endosperm-specific expression. Phylogenetic reconstruction of the maize ARF gene family demonstrated that ZmARFTF2 and ZmARF17 share closest evolutionary relationship. In the ethyl methanesulfonate （EMS）-induced mutant EMS3-0a1dd2 （B73 background）， a single-base substitution in ZmARFTF2 generated a premature termination codon. Compared to the wild-type inbred line B73， homozygous EMS3-0a1dd2 mutants exhibited significant increases in kernel length， width， thickness， 100-kernel weight， and volume weight. Notably， amylose content in mutants was significantly elevated， whereas amylopectin content was reduced. Phenotypic characterization revealed that loss-of-function of ZmARFTF2 converted kernel morphology from dent-type to flint-type. ZmARFTF2-overexpressing Arabidopsis thaliana lines displayed significantly smaller pods and seeds compared to wild-type. These findings demonstrate that ZmARFTF2 negatively regulates maize kernel size and 100-kernel weight， influencing the starch biosynthesis. This study provides critical genetic resources for improving kernel and quality traits in maize.

The combination of herbicide resistant varieties and corresponding herbicides is an important method to control weed damage in rice fields. Marker-assisted selection can accelerate the breeding process of herbicide resistant varieties. To rapidly improve the herbicide resistance of rice varieties， a functional marker for the herbicide resistance gene was developed and rice variety HR1 with imidazolinone herbicides resistance was utilized to improve Yanghangnuo 1 in this study. Sequence alignment showed that the 548th encoded amino acid of ALS gene in the herbicide resistant variety was mutated from tryptophan to methionine （W548M）， conferring resistance to ALS-inhibiting herbicides. To accelerate the breeding process， a functional marker ALS1642 was developed based on the principle of tetra-primer ARMS-PCR technology according to ALS gene sequence specificity. This marker can accurately identify the genotype associated with the herbicide resistance in seedlings. Using this marker， we screened the genetic segregation population derived from the cross between Yanghangnuo 1 and HR1 for herbicide resistance gene， and obtained several new rice lines carrying the gene. The results indicate that ALS1642 can be widely applied for marker-assisted selection of the W548M mutant genotype and the development of new rice varieties resistant to imidazolinone herbicides. This study is of great significance in improving herbicide resistance of rice varieties and enhancing breeding efficiency.

To investigated the accumulation patterns of metabolites in Dendrobium officinale under different lights， Dendrobium officinale was grown under white light （control， CK） and four different light-emitting diode （LED） therapy， including blue （B）， yellow （Y）， purple （P）， and green （G）. Metabolomic analysis was conducted using high-performance liquid chromatography and tandem mass spectrometry， combined with transcriptomic analysis using Illumina sequencing， with a focus on the differentially accumulated metabolites and differentially expressed genes under CK and G treatments. Results showed that among four different LED light treatments， G light has the most pronounced impact on promoting flavonoids accumulation. Metabolomic analysis identified a total of 673 differentially accumulated metabolites， with flavonoids constituting the dominant category （44.03%）， particularly 3，4，2′，4′，6′-pentahydroxychalcone which showed a 10.99-fold accumulation. Transcriptomics identified 6 114 differentially expressed genes （2 561 upregulated and 3 553 downregulated）， with the most significant change observed in the AP2 transcription factor family. This study revealed that G light can promote flavonoids accumulation in D. officinale， providing important mechanistic insights from metabolomics and transcriptomics perspectives for the precision cultivation of medicinal plants through light regulation.

To explore the therapeutic mechanisms of Astragalus membranaceus and Ganoderma lucidum in treating hyperglycemia， the target proteins and signaling pathways through which A. menbrunucrus and G. lucidum exert their hypoglycemic effects were elucidated using network pharmacology approaches. Molecular docking was employed to predict the binding affinities between active compounds with target proteins. A. menbrunucrus and G. lucidum possessed 35 effective constituents and 173 correlated targets， among which 73 were specific to hyperglycemia. The main active components of A. menbrunucrus and G. lucidum included quercetin， isorhamnetin， kaempferol， β-sitosterol， and etc. They acted on insulin signaling pathway， AGE-RAGE signaling pathway， and cancer pathway， with corresponding targets including AKT1， IL6， MAPK1， PPARG， and TNF. Molecular docking indicated that the core bioactive components showed strong binding affinities with these key target proteins. Enzyme activity assays revealed a 5∶1 ratio （m/m） of A. menbrunucrus to G. lucidum exhibited maximum inhibitory effects on α-glucosidase and α-amylase with 85.81% and 78.35% respectively. Non-enzyme protein glycosylation experiments demonstrated that （AM-GL （5∶1）） reduced advanced glycation end products （AGEs） generation by 77.38%. These two traditional Chinese medicines synergistically treated hyperglycemia through a multi-component， multi-target and multi-pathway mechanism， involving the regulation of insulin signaling pathway， inhibition of AGE-RAGE signaling pathway， retardation of intestinal glucose absorption and improvement of insulin resistance. The results of this study provide theoretical basis for the clinical application of of A. membranaceus and G. lucidum in prevention and treatment of hyperglycemia.

To investigate the effect of steam explosion （SE） pretreatment on the extraction efficiency， structural properties， and bioactivity of Dendrobium officinale polysaccharides， the variations in yield， total sugar content， and uronic acid content were evaluated under different SE conditions， including raw material particle size and SE pressure. Additionally， the structural characteristics and antioxidant activity of the extracted polysaccharides were comprehensively analyzed. The results revealed that SE pretreatment significantly enhanced the D. officinale polysaccharides yield， total sugar content， and uronic acid content compared to the untreated control. The optimal extraction was achieved with a raw material particle size of （0.5， 1］ cm and an SE pressure of 1.5 MPa for 240 seconds （DOP_1.0-1.5M）， resulting in increases by 25.52， 17.43 and 5.02 percentage points， respectively， compared to the control （DOP）. SE treatment also markedly altered the polysaccharides’ apparent structure， increasing their structural irregularity. Compositional analysis indicated that the polysaccharides primarily consisted of mannose and glucose. Although SE had little impact on the monosaccharide profile， it significantly elevated the molar ratio of glucose. FT-IR analysis further confirmed the findings related to polysaccharide yield. Furthermore， in vitro antioxidant assays indicated that SE pretreatment under optimized conditions effectively improved the antioxidant activity of D. officinale polysaccharides， with DOP_1.0-1.5M exhibiting the highest activity. These findings provide valuable theoretical references and technical support for the efficient extraction and high-value utilization of D. officinale polysaccharides.

To elucidate the effects of nitrogen fertilizer application on N₂O and CH₄ emissions from croplands in China， a meta-analysis was conducted focusing on major grain-producing regions （wheat， maize， and rice）. The study compared the impacts of various climatic conditions， soil basic physicochemical properties， and nitrogen fertilizer management practices on soil N₂O and CH₄ emissions， global warming potential （GWP）， and greenhouse gas intensity （GHGI） after nitrogen fertilizer application. The results indicated that the warm temperate climate zone exhibited the highest increases in cumulative N₂O emissions， GWP， and GHGI after nitrogen application. Mean annual temperature significantly influenced cumulative N₂O emissions and GWP， while annual precipitation and sunshine hours had greater effects on cumulative CH₄ emissions and GHGI， respectively. Cumulative N₂O emissions were higher when soil total nitrogen content ranged from 0.9 to 1.5 g·kg^-1， whereas cumulative CH₄ emissions were higher when soil total nitrogen exceeded 1.5 g·kg^-1. Cumulative N₂O and CH₄ emissions， GWP， and GHGI were all higher when soil organic matter content was between 15 and 30 g·kg^-1. Increasing soil pH promoted greenhouse gas emissions. Nitrogen application rate had a significant （P<0.05） positive effect on cumulative N₂O emissions. Split application of nitrogen fertilizer （base + topdressing） was more effective in reducing emissions compared to a single basal application. The combined application of nitrogen fertilizer with biochar resulted in lower increases in GWP and GHGI compared to straw return and organic fertilizer treatments. Slow-release nitrogen fertilizers produced fewer greenhouse gases than conventional fertilizers. In conclusion， optimizing nitrogen management by adopting split application （base <topdressing， base-to-topdressing ratio of 5∶5 to 0∶10）， using slow-release nitrogen fertilizers， or combining nitrogen with biochar can effectively reduce soil greenhouse gas emissions and lower emission intensity compared to conventional nitrogen fertilizer practices in major grain-producing regions of China. The results of this study are of great significance for the scientific application of nitrogen fertilizers and greenhouse gas mitigation in Chinese croplands.

To investigate the effects of ⁶⁰Co-γ ray irradiation and sterilization on Panax notoginseng powder， this study investigated the changes of color， physicochemical properties， active components， fingerprints， antioxidant capacity and microbial counts of Panax notoginseng powder under different irradiation doses. The results showed that compared with the non-irradiated group， the color， moisture， total ash， and antioxidant activity of Panax notoginseng powder were not significantly affected after irradiation with 1-30 kGy ⁶⁰Co-γ rays （P>0.05）， and the similarity of the fingerprint profiles was 0.998-1.000. When the irradiation dose was greater than 10 kGy， the alcohol-soluble leachate was significantly reduced， which could not meet the 2020 edition of the Chinese Pharmacopoeia standard， Part One. At an irradiation dose of 30 kGy， the contents of ginsenoside Rg₁， ginsenoside Rb₁， and ginsenoside Rd were significantly reduced （P<0.05）. In conclusion， in the production of pharmaceuticals， under the premise of determining the initial microbial load of ≤10³ cfu·g^-1， it was recommended that the ⁶⁰Co-γ irradiation sterilization dose of Panax notoginseng powder ranges from 6 to 10 kGy， which can achieve the sterilization effect and maintain its quality， and ensure that the Panax notoginseng powder is safe， effective， and of controlled quality in the production and use process. This study provides a theoretical basis for the application of ⁶⁰Co-γ radiation in the sterilization process of Panax notoginseng powder.

Current quantitative assessment methods are hindered by several critical limitations： inadequate characterization of lodging dynamics across growth stages， poor generalizability of conventional single-modal algorithms， and a lack of robust frameworks for multi-source data synergy and integration analysis. In this study， four deep learning models—U-Net， DeepLabV3+， PSP-Net， and HR-Net were employed to extract lodging regions from RGB images of 3 783 natural wheat populations. The multi-spectral data was integrated to calculate vegetation indices and a yield estimation model were constructed using four machine learning algorithms， including Support Vector Machine （SVM）， Gradient Boosting Regression （GBR）， Multilayer Perceptron （MLP）， and Random Forest （RF）. Yield loss was calculated by comparing predicted normal growth yield with the actual harvested yield after lodging. The results showed that for the task of lodging region extraction， U-Net achieved the highest recall and mean average precision， both exceeding 90.63%. However， its precision was slightly lower than that of the other three models. Under different growth conditions， there is significant variation in the accuracy of wheat lodging-region extraction. At the heading stage， the R² value ranged from 0.19 to 0.32， it increased to 0.84-0.88 in the early grain-filling stage， then decreased to 0.71-0.77 in the mid-grain-filling stage， and remained at 0.65-0.74 in the late grain-filling stage. It indicated that early grain-filling stage was the optimal period for lodging region extraction. During the heading and grain-filling stages of wheat， incorporating lodging features extracted by the U-Net algorithm into the yield estimation models resulted in an increase of R² value by 0-0.26. The model constructed by the MLP algorithm achieving the highest accuracy （R²=0.68） in the early grain-filling stage. For yield loss prediction， an ‘upright-lodging dual-track modeling’ strategy was adopted： first， upright-wheat yield models that did not incorporate lodging-area features were built separately using four algorithms SVM， GBR， MLP and RF to estimate the potential yield； second， lodging-wheat yield models were established， and the difference between the two predictions was taken as the actual yield loss caused by lodging. The MLP-MLP algorithm achieved the highest accuracy （R²=0.89） and the smallest error （RMSE=419.47 kg·hm^-2） in estimating yield loss when predicting both lodged and normal wheat yields. In summary， the combination of multiple intelligent algorithms improved the accuracy of wheat lodging region extraction and yield loss estimation. This study provides theoretical basis and technical support for high-precision assessing the impact of lodging on wheat yield loss.

In order to objectively reflect the interspecific differences in heavy metal accumulation by leafy vegetables and their impacts on human health， a pot experiment was carried out to investigate the contamination status， hazard index （HI） and total carcinogenic risk （TCR） of 16 types of leafy vegetables by using the zonal red soil with slightly acidity and high bioavailability of cadmium （Cd） and lead （Pb） in Yunnan Province. The results revealed that the exceeding rates of cadmium （Cd）， lead （Pb） and arsenic （As） in the aboveground parts of the 16 leafy vegetables were 87.5%， 100% and 25%， respectively. The highest contents of Cd， Pb and As were observed in Spinacia oleracea （0.99 mg·kg^-1）， Coriandrum sativum （6.12 mg·kg^-1） and Ipomoea aquatica （2.91 mg·kg^-1）， while the lowest were present in Perilla frutescens （0.03 mg·kg^-1）， Lactuca sativa var. ramosa （0.83 mg·kg^-1） and Brassica oleracea var. capitata （0.09 mg·kg^-1）， respectively. P. frutescens had the lowest bioconcentration and translocation factors for Cd， and B. oleracea var. capitata had the lowest bioconcentration and translocation factors for As， while I. aquatica had the highest bioconcentration and translocation factors for As. The Nemerow synthetic pollution index， HI and TCR values of Cd， Pb and As in the aboveground part of Brassica rapa var. glabra were significantly lower than those of other vegetables. The Nemerow synthetic pollution index of S. oleracea and C. sativum was significantly higher than that of other leafy vegetables. The hazard indexes and total carcinogenic risk values of the 16 leafy vegetables were approximately twice those of adults for children， especially I. aquatica had the highest HI （20.45） and TCR （0.03） for children. Therefore， Chinese cabbage can be preferentially planted in red soil contaminated by heavy metals， but coriander， spinach and water spinach are not recommended. This study provides a basis for the rational arrangement of leafy vegetable cultivation in heavy metal-contaminated red soil areas.

With the rapid development of remote sensing technology and artificial intelligence， the low-altitude economy centered on unmanned aerial vehicles （UAV） has emerged as a key force driving the development of modern agriculture， particularly in crop breeding innovation. Traditional crop genetics and breeding has long been hampered by low efficiency in phenotypic identification， which significantly slows the breeding progress. As a new quality productive force， the low-altitude economy empowers genetics and breeding of oilseed crop through UAV-based high-throughput phenotyping. This paper explores the policy context and core technological equipment underlying the low-altitude economy， focusing on the characteristics and application scenarios of different UAV platforms such as multi-rotor and fixed-wing and sensor types， including visible light， multispectral， hyperspectral， and LiDAR. It further analyzes the principles of how UAV-based high-throughput phenotyping technology accelerates traditional breeding and systematically outlines the entire workflow from multi-source data acquisition and standardized processing to artificial intelligence （AI） model analysis. Based on this foundation， the paper reviews literature on the application of these technologies to major oilseed crops like soybean， rapeseed， peanut， sesame， and sunflower， highlighting their use in stress tolerance screening， yield and quality trait assessment， and related gene localization. Finally， the paper discusses current challenges related to cost， flight endurance， data processing， and standardization. It also provides an outlook on future directions， including integrated space-air-ground monitoring， intelligent autonomous systems， and the application of large AI models. This review aims to offer theoretical insights and technical support for intelligent breeding and industrial upgrading of oilseed crops in China.

Soil salinization affects soybean emergence， chlorophyll synthesis and yield components. To comprehensive evaluation of salt tolerance and high-yield potential， this study assessed 73 soybeans varieties grown in saline-alkali soil throughout their whole growth cycle. Correlation and principal component analysis were employed to evaluate 18 saline-alkali tolerance related indicators and 6 yield components aiming to identify key traits associated with saline-alkali tolerance and yield performance. Membership function and cluster analysis were used to screen soynbean germplasm suitable for cultivation in the saline alkali soil of Xinjiang. The results showed that root fresh weight， transpiration rate， leaf area， leaf width， intercellular CO₂ concentration and plant height were effective indicators for evaluating saline-alkali tolerance. Yield per plant， pod dry weight and branch number could be served as indicators of yield composition. Soybean varieties were classified into four saline-alkali tolerance categories： highly tolerant （Class i， 3 varieties： Lvzuan， Tiedou 69， Liaoxin 1 and Tiedou 53）， moderately tolerant （Class ii， 54 varieties）， low tolerance （Class iii， 12 varieties）， and sensitive （Class iv， 3 varieties： Zhongdou 29， Zhongdou 39 and Nanchundou 51）. Based on yield composition， the soybean varieties were further categorized into high yield （Class Ⅰ， five varieties： Heinong 531， Beijiang 121， Liaoxin 1， Jiyu 96， and Hefeng 53）， moderate-yield （Class Ⅱ， 11 varieties）， and low-yield （Class Ⅲ， 57 varieties） groups. While saline-alkali tolerance influences yield， it is not the sole determinant of final yield. Notably， Liaoxin 1 exhibited both high salt tolerance and high yield potential. In summary， saline-alkali stress mainly affects the final yield by affecting soybean germination and emergence. Liaoxin 1 is a high-salt-tolerant and high-yield variety suitable for the northern slope of Tianshan Mountains in Xinjiang. The results of this study provide a basis for high-yield soybean cultivation in saline-alkali soils.

High-quality agricultural growth and the sustainable use of arable land resources are severely hampered by soil salinization and alkalization. Using 111 representative foxtail millet germplasm resources as materials， the current study examined the tolerance of foxtail millet varieties during germination under 70 mmol·L^-1 mixed saline-alkali （Na₂SO₄∶NaCl∶NaHCO₃∶Na₂CO₃=4∶1∶4∶1） stress to encourage the comprehensive utilization of saline-alkali soil. The findings demonstrated that during the foxtail millet germination stage， the mixed salt-alkali stress had negative effects on eleven indices， including germination potential （GP）， germination rate （GR）， and shoot length （SL）， with a particularly significant effect on root length （RL）. Principal component analysis converted the ten individual indicators into four representative principal components， resulting in a cumulative contribution of 82.89%. Three highly tolerant varieties， 28 salt-alkali tolerance varieties， 71 sensitive varieties， and 9 highly sensitive varieties were filtered out based on cluster analysis and the membership function method， which was used to determine the integrated salt-alkali tolerant assessment value of foxtail millet during the germination period. In the meantime， linear stepwise regression analysis was used to establish the regression equation D=1.018-0.018X₂+0.110X₅+0.405X₈+0.012X₉， where D was the salt-alkali tolerant value and X₂， X₅， X₈， and X₉ were the relative bud length （RBL）， relative bud dry weight （RBDW）， relative root fresh weight （RRFW）， and germination rate salt damage rate （SDRGR）. Germination rate， salt damage rate （SDRGR）， relative bud length （RBL）， relative bud dry weight （RBDW）， and relative root fresh weight （RRFW） may be employed as evaluation indices of salt-alkali tolerance in foxtail millet， according to the equation’s coefficient of determination， R²=0.977 5. Following salt-alkali stress， the antioxidant enzyme activities of highly sensitive varieties Yugu23 and A29 and high salt-alkali tolerant varieties MUjigou and Baimaogu revealed that the high-tolerant varieties could induce the expression of SOD， POD， and CAT enzyme activities early on to scavenge the excess intracellular reactive oxygen species， which were involved in the process of foxtail millet’s salt-alkali tolerance. The findings of this study provide a theoretical foundation for breeding foxtail millet varieties and elucidating the physiological mechanism underlying salt-alkali tolerance.

To establish a stable and reliable multidimensional evaluation system for chrysanthemum black spot resistance， twenty-two chrysanthemum germplasms were selected for field investigations under natural disease conditions in Chuzhou and Baima. Simultaneously， indoor resistance evaluations were used three artificial inoculation methods： in vivo spore inoculation， in vivo mycelium inoculation， and in vitro leaf inoculation. A comprehensive evaluation that strategy combines the Analytic Hierarchy Process （AHP） and K-means clustering was proposed. AHP was utilized to integrate and assign weights to field and artificial inoculation data， while K-means objectively classified resistance levels based on multidimensional data， ensuring scientific validity and stability of the evaluation results. The findings demonstrated that various identification methods exhibited high consistency in evaluating both highly resistant and susceptible materials； however， they displayed discrepancies in classifying moderately resistant and moderately susceptible materials. Environmental conditions significantly influenced the expression of resistance： the disease index at Chuzhou was decreased by 21.7% compared to Baima， likely because it avoided the high-humidity rainy season， Among the artificial inoculation methods， in vivo techniques demonstrated relatively stable results， whereas detached leaf inoculation yielded lower resistance scores， leading to decreased resistance classifications for some varieties. The AHP-K-means model classified the 22 germplasms into four resistance levels， identifying three highly resistant and stable core germplasms： Zhongshan wuji， Jinsi huangju， and Suju 6. The established multidimensional evaluation system significantly improved the reliability of resistance assessment. The selected highly resistant germplasms can be directly utilized in disease resistant breeding， and the proposed strategy provides a practical reference for resistance evaluation in other crops.