Accurate prediction of the cut chrysanthemum growth cycle is essential for precise market scheduling and quality control. While existing models primarily target the flowering date, key developmental stages remain poorly quantified. Through controlled experiments with varying planting dates and light levels, this study systematically analyzed the stage-specific influence of photosynthetic photon flux (PPF). We found that reduced PPF significantly delays both vegetative growth and harvest timing but does not affect floral bud differentiation. To address these stage-dependent responses, we developed a multi-model ensemble (MME) framework that integrates the most accurate models for each critical phase: the accumulated photo-thermal product for initiating short-day treatment, the triangular-function-based relative thermal effect for bud emergence, and the chrysanthemum clock model for the optimal harvest date. Validation results demonstrate that this integrated approach achieves significantly higher predictive accuracy than any single model. This research not only provides a reliable tool for the year-round precision production management of cut chrysanthemum but also offers a physiologically-based MME methodology reference for modeling the growth of horticultural crops.

Abstract Black spot disease (BSD), caused by Alternaria alternata, is a devastating threat to the chrysanthemum industry, yet its genetic basis remains largely elusive. The present study aimed to decipher the genetic architecture of chrysanthemum BSD resistance and to discover genetic loci and candidate genes using genome-wide association studies (GWAS) in a biparental F1 population (n = 164). Phenotypic evaluations of BSD resistance were conducted using both multi-stage detached-leaf assays and seedling-stage in vivo inoculations. The disease severity index (DSI) exhibited wide coefficient of variation (CV: 26.21%–54.84%) and high broad-sense heritability (0.71–0.95), with significant transgressive segregation observed in the F1 progeny. 375 865 high-quality SNPs-based GWAS identified 220 quantitative trait nucleotides (QTNs) and 36 QTN-by-environment interactions (QEIs), explaining up to 7.39% and 3.46% of the phenotypic variance, respectively. Among 26 stable QTNs, 17 favorable alleles displayed significant additive effects and a clear dosage-pyramiding effect (P < 0.001). By integrating functional annotation with transcriptome profiling, 34 candidate genes involved in immune defense were identified within the candidate intervals. Notably, three key candidate genes, CmABF1, CmSINAT3, and CmLTPG1, were validated as positive regulators of BSD resistance through transient overexpression and silencing assays. The research findings provide crucial genetic resources for the molecular improvement of resistance to BSD in chrysanthemums.

Under greenhouse production conditions, variability in fertilization management, substrate properties, and microenvironmental factors can disrupt balanced nutrient uptake, often resulting in localized or transient multi-element nutrient imbalances. Hyperspectral sensing provides continuous and high-resolution spectral information for plant nutrient assessment. However, most existing studies focus on single-element deficiencies or simplified scenarios, which limits their applicability to complex nutritional environments encountered in practice. To address this limitation, we designed a series of single- and dual-element deficiency treatments in four cultivars of chrysanthemum (Chrysanthemum morifolium Ramat.), an important cut-flower crop whose ornamental quality is highly influenced by nutrient supply. Sampling was conducted at five key growth stages across three independent experiments, yielding a total of 615 data points. Each treatment included replicates and was confirmed based on characteristic deficiency symptoms. A hyperspectral-based qualitative classification framework was developed to assess nutrient imbalances under controlled greenhouse conditions. Results indicate that although some nutrient deficiencies exhibit similar visual or phenotypic symptoms, their hyperspectral responses are distinguishable, suggesting that hyperspectral data can capture subtle differences associated with distinct nutrient imbalance conditions. To mitigate class imbalance, the Synthetic Minority Oversampling Technique (SMOTE) was applied, and multiple classification models were evaluated using cross-validation. The Gradient Boosting Decision Tree (GBDT) classifier combined with SMOTE showed the most consistent performance across nutrient-recognition tasks, achieving cross-validation accuracies from 0.9191 ± 0.0401 to 0.8556 ± 0.0516, balanced accuracies from 0.9595 to 0.8447, F1 from 0.9591 to 0.8496 and testing accuracies from 0.9200 to 0.8269, balanced accuracies from 0.9167 to 0.8269, F1 from 0.9140 to 0.8244. Overall, this study presents a non-destructive hyperspectral framework for classifying multi-element nutrient imbalances and demonstrates its effectiveness under greenhouse conditions, supporting hyperspectral-based nutritional assessment in ornamental crops. Further validation across diverse genotypes, seasons, and environmental conditions is needed to confirm broader applicability and model generalizability.

Cut chrysanthemum is a globally important high-value cut flower crop. Excessive nitrogen (N) application is prevalent in its production, leading not only to reduced flower quality and resource waste but also to environmental risks. However, the insufficient understanding of the dynamic N accumulation patterns throughout the entire growth cycle of chrysanthemum constrains the effective implementation of precision fertilization and scientific N reduction strategies. In this study, a two-year soilless cultivation experiment with a gradient of N application rates was conducted using the cut chrysanthemum cultivar ‘Nannong Xiaojinxing’. The study used principal component analysis (PCA) and regression modeling to systematically quantify the N requirements at key growth stages and to establish a precision fertilization strategy based on plant N accumulation. Results indicated that growth and quality indicators of chrysanthemum initially increased and then decreased with increasing N application, but the peak intervals varied among different indicators. Growth indicators were integrated via PCA into two principal components—phenotype and biomass—to generate a comprehensive score. Both this score and the cut-flower quality indicators were well-described by a quadratic regression model with N accumulation, thereby precisely determining the optimal N accumulation at each growth stage. Continued fertilization beyond the optimal N requirement induced luxury N absorption, consequently reducing N use efficiency. A conversion model between N accumulation and application rate was established. By applying the identified optimal N accumulation values to this model, the optimal N application rates were determined for the slow growth, rapid growth, flower bud differentiation, flower bud swelling, and flower color appearance stages as 89, 155, 35, 47, and 12 mg·plant⁻¹, respectively. Implementation of this optimized protocol resulted in a N agronomic efficiency of 140–160 g·g⁻¹ and an apparent N recovery rate of 60%–70%. This study pivots the N fertilization strategy for cut chrysanthemum from a fixed-amount regime to a dynamic management system centered on the plant’s optimal N status, thereby providing a robust pathway to on-demand fertilization, scientific N reduction, and stable quality production.

Black spot disease, caused by the fungus Alternaria alternata, is a global plant pathogen that lacks sustainable control measures and poses a serious threat to multiple economically important crops. One approach to enhancing disease resistance in susceptible plants is grafting them onto disease-resistant rootstocks, yet the mechanisms by which roots enhance disease resistance in shoots remain largely unknown. Here, using chrysanthemum-Artemisia vulgaris grafts, we identified that a raffinose synthase-encoding gene, CmRS6, is essential in the susceptible chrysanthemum scion for graft-transmitted resistance from the disease-resistant A. vulgaris rootstock. Exogenous raffinose treatments enhanced A. alternata resistance in chrysanthemum, tomato, cabbage, and apple, highlighting its broad defensive role. The CmERF1B transcription factor activated CmRS6 expression and raffinose accumulation, whereas CmJAZ1-like repressed CmERF1B via direct interaction. While we found evidence for rootstock-to-scion transport of raffinose, long-distance jasmonate (JA) transport from A. vulgaris rootstocks to chrysanthemum scions was the primary mechanism for graft-transmitted resistance, and A. alternata infection further promoted JA transport. Collectively, our study demonstrates that rootstock-to-scion JA transport mediates graft-transmitted A. alternata resistance by upregulating scion raffinose biosynthesis, thereby offering new strategies for the sustainable control of A. alternata in crops.

Nitrogen (N) is a key component in plants and their biological macromolecules, having a profound effect on developmental stages, such as germination, vegetative growth, and flowering. However, the mechanism of nitrogen-regulated flowering time remains unclear. In this study, CmNLP7 was isolated from the chrysanthemum cultivar ‘Jinba’ and was characterized. CmNLP7 is a transcription factor localized in the nucleus but has no transcriptional activity. Tissue expression pattern analysis showed that CmNLP7 was mainly transcribed in leaves and roots. Knocking down CmNLP7 through the artificial-miRNA method in chrysanthemum resulted in early flowering under optimal nitrogen (ON) and low nitrogen (LN) conditions; whereas overexpression lines showed delayed flowering under LN conditions. Transcriptome sequencing analysis showed that the nitrate transporters NRT2.5, NPF3.1, and NPF4.6; SBP-like genes SPL7 and SPL12, and flowering integration factor FT were significantly up-regulated in the knockdown lines. Based on the KEGG pathway enrichment analysis, the differentially transcribed genes were enriched in phenylpropanoid biosynthesis and starch and sucrose metabolism pathways, which indicated their alleged function in nitrogen-regulated flowering and development in chrysanthemum. Furthermore CmPP6 as a homolog of the Arabidopsis phosphatase PP6, was verified as an interacting protein of CmNLP7 by yeast two-hybrid, BiFC, pull-down and Biacore in vitro and in vivo, and the knockdown line of CmPP6 (amiR-CmPP6) flowered earlier compared to that of the wild-type chrysanthemum ‘Jinba’. Collectively, these results demonstrated that CmPP6 interacts with CmNLP7 to regulate chrysanthemum flowering, and CmNLP7 could regulate flowering time in response to nitrogen, which lays a foundation for the regulation of flowering and molecular breeding of chrysanthemum through changes in nutrient signaling.

Critical nitrogen concentration (Nc) and accumulation (Na) throughout the entire growth period are key indicators for diagnosing N status and implementing precision N management in cut chrysanthemum. However, direct measurement of these two parameters is both time-consuming and destructive, and establishing accurate predictive models is fundamental to their practical application. From May 2021 to July 2022, five N-gradient experiments (ranging from 14 to 574 mgf·plant−1) were conducted on the cut chrysanthemum cultivar ‘Nannong Xiaojinxing’. Predictive models for Nc and Na were developed using environmental light and temperature data during growth as driving variables. The results showed that the aboveground dry matter (DM) prediction model, which utilized the cumulative photo-thermal effect (PTE) derived from these environmental factors, demonstrated superior accuracy compared to models relying on conventional driving variables. Subsequently, the Nc and Na prediction models were established with DM as the driving variable. These models indicated that at a DM level of 1 g·plant−1, Nc and Na values were 4.53% and 45.30 mg·plant−1, respectively. The Na reached a maximum of 236.50 mg·plant−1 at the flower harvesting stage, representing the minimum N accumulation required for optimal floral quality. Using the dry matter model as a process-based model, we successfully developed predictive models for Nc and Na driven by PTE. Validation using independent experimental data confirmed the models’ high predictive accuracy, with coefficients of determination of 0.9378 and 0.9612, and low errors—root mean square errors of 0.2736% and 19.18 mg·plant−1, and normalized RMSE of 10.79% and 14.94%, respectively. These models provide a foundation for implementing precision N management and reducing fertilizer application in cut chrysanthemum production.

Black spot disease (BSD), induced by Alternaria alternata, constitutes a significant menace to chrysanthemum. Identifying resistant germplasm resources underscores its critical importance in chrysanthemum breeding. To elucidate the genetic basis and candidate genes underpinning chrysanthemum BSD resistance, we conducted a multi-locus genome-wide association study (GWAS) using a panel of 152 accessions and 351 555 single nucleotide polymorphisms (SNPs) via the 3VmrMLM method. We observed extensive phenotypic variation for the disease severity index (DSI) of BSD, with coefficients of variation ranging from 70.79% to 85.00%, and the broad-sense heritability was calculated at 74.36%. GWAS result detected seventy-one quantitative trait nucleotides (QTNs) and seven QTN-by-environment interactions (QEIs), accounting for 1.53%-7.06% and 0.68%-3.16% of the phenotypic variation, respectively. Eighteen stable QTNs were identified in more than two methods, from which eight highly favorable SNP alleles were extracted for BSD resistance. Furthermore, we observed a significant dosage-pyramiding effect (P < 0.001) among the favorable alleles. Among the genes surrounding the QTNs and QEIs, 12 were homologous to known disease-resistance genes in Arabidopsis, and 14 candidate genes were mined by combining the functional annotation and transcriptomics data, respectively. Our results help better understand the genetic architecture of BSD resistance, and the identified significant SNPs and candidate genes pave the way for future molecular breeding of chrysanthemums with enhanced BSD resistance.

Nitrogen(N)is a limiting factor that determines the yield and quality of chrysanthemum.Genetic variation in N use efficiency(NUE)has been reported among chrysanthemum genotypes.We performed a transcriptome analysis of two chrysanthemum genotypes,'Nannonglihuang'(LH,N-efficient genotype)and'Nannongxuefeng'(XF,N-inefficient genotype),under low N(0.4 mmol L-1 N)and normal N(8 mmol L-1 N)treatments for 15 d and an N recovery treatment for 12 h(low N treatment for 15 d and then normal N treatment for 12 h)to understand the genetic factors impacting NUE in chrysanthemum.The two genotypes exhibited contrasting responses to the different N treatments.The N-efficient genotype LH had significant superiority in agronomic traits,N accumulation and glutamine synthase activity under both normal N and low N treatments.Low N treatment promoted root growth in LH,but inhibited root growth in XF.Transcriptome analysis revealed that the low N treatment increased the expression of some N metabolism genes,genes related to auxin and abscisic acid signal transduction in the roots of both genotypes,as well as genes related to gibberellin signal transduction in roots of LH.The N recovery treatment just increased the expression of genes related to cytokinin signal transduction in roots of LH.The expression levels of the NRT2.1,AMT1.1,and Gln1 genes related to gibberellin and cytokinin signal transduction were higher in roots of LH than in XF under different N treatments,suggesting that the genes related to N metabolism and hormone(auxin,abscisic acid,gibberellin,and cytokinin)signal transduction in roots of LH are more sensitive to different N treatments than those of XF.Co-expression network analysis(WGCNA)also identified hub genes like bZIP43,bHLH93,NPF6.3,IBR10,MYB62,PP2C,PP2C06 and NLP7,which may be the key regulators of N-mediated responses in chrysanthemum and play crucial roles in enhancing NUE and resistance to low N stress in the N-efficient chrysanthemum genotype.These results revealed the key factors involved in regulating NUE in chrysanthemum at the genetic level,which provides new insights into the complex mechanism of efficient nitrogen utilization in chrysanthemum,and can be useful for the improvement and breeding of high NUE chrysanthemum genotypes.

Introduction:While co-inoculation with rhizobia and plant growth-promoting rhizobacteria (PGPR) can enhance soybean growth and nodulation, the interaction mechanisms between Bacillus velezensis 20507 and Bradyrhizobium japonicum USDA110 under varying nitrogen (N) supply levels (0-10 mmol/L) remain unclear. This study investigates how their synergistic interactions influence soybean nitrogen content per plant and molecular pathways. Methods:Soybean plants were co-inoculated with B. velezensis and B. japonicum across four N levels. Nodulation, plant growth, physiology, and N content were quantified. Transcriptome sequencing of soybean roots under N deficiency compared single and co-inoculation treatments. Flavonoids in B. velezensis fermentation broth were identified via mass spectrometry, and rutin's regulatory effects on B. japonicum nodulation genes (NodD1/NodD2) were tested in coculture. Results:Co-inoculation significantly increased nodulation, biomass, and N content per plant compared to single inoculations across all N levels. Under N deficiency, co-inoculation induced 5,367 differentially expressed genes (DEGs), with Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment in phenylpropanoid (ko00940) and flavonoid biosynthesis (ko00941). B. velezensis produced 29 flavonoids and 4 isoflavonoids (including rutin). Rutin (5-10 mg/L) upregulated NodD1 and suppressed NodD2 in B. japonicum. Discussion:B. velezensis enhances B. japonicum-soybean symbiosis via flavonoid secretion, particularly rutin, which modulates nodulation gene expression. This metabiotic interaction improves soybean N assimilation and growth, even under low N conditions. The findings provide a foundation for designing composite inoculants to optimize soybean yield and nitrogen-use efficiency.

Chrysanthemum morifolium is cultivated worldwide and has high ornamental, tea, and medicinal value. With the increasing area of chrysanthemum cultivation and years of continuous cropping, Fusarium wilt disease frequently occurs in various production areas, seriously affecting the quality and yield and causing huge economic losses. However, the molecular response mechanism of Fusarium wilt infection remains unclear, which limits the molecular breeding process for disease resistance in chrysanthemums. In the present study, we analyzed the molecular response mechanisms of 'Huangju,' one of the tea chrysanthemum cultivars severely infested with Fusarium wilt in the field at the early, middle, and late phases of F. oxysporum infestation. 'Huangju' responded to the infestation mainly through galactose metabolism, plant-pathogen interaction, auxin, abscisic acid, and ethylene signalling in the early phase; galactose metabolism, plant-pathogen interaction, auxin, salicylic acid signal, and certain transcription factors (e.g., CmWRKY48) in the middle phase; and galactose metabolism in the late phase. Notably, the galactose metabolism was important in the early, middle, and late phases of 'Huangju' response to F. oxysporum. Meanwhile, the phytohormone auxin was involved in the early and middle responses. Furthermore, silencing of CmWRKY48 in 'Huangju' resulted in resistance to F. oxysporum. Our results revealed a new molecular pattern for chrysanthemum in response to Fusarium wilt in the early, middle, and late phases, providing a foundation for the molecular breeding of chrysanthemum for disease resistance.

The inoculation of plants with plant growth-promoting rhizobacteria (PGPR) has been increasingly discussed as a way to sustainably promote plant growth and soil health. Although some promising results have been achieved in the laboratory, the applications of microbial inoculants in chrysanthemum production greenhouses and co-inoculation with PGPRs in ornamental planting systems have been less investigated. Here, greenhouse experiments were conducted to study the integrated effect of bioagents (Bacillus velezensis and Pseudomonas aeruginosa) on chrysanthemum nutrient use efficiency, plant growth, and quality. The growth-promoting mechanisms were further elucidated by transcriptome analysis. Co-inoculation with the two PGPRs increased the absorption and utilization of nitrogen, phosphorus, and potassium. The quality and growth of chrysanthemum were significantly higher than those of single PGPR inoculation or soil conditioner application. Transcriptome analysis revealed that differentially expressed genes (DEGs) were co-expressed at 30, 60, and 90 days after chrysanthemum co-inoculation with the two PGPRs. DEGs were primarily enriched in metabolic and signal transduction pathways. PDC encoding pyruvate decarboxylase in the glycolysis pathway and SAUR32 and SAUR36 encoding auxin were upregulated in chrysanthemum during the PGPRs inoculation period. Notably, the transcription factors WRKY70 and BHLH35 belonging to signal transduction and defense responses were both upregulated, demonstrating that chrysanthemum system and disease resistance were activated. The results of this study could help to elucidate the mechanism of 2 PGPRs on chrysanthemum growth and development at the transcriptome level, which could lay a theoretical foundation for the highly efficient cultivation of cut chrysanthemum "Qinhuai Yulian".

Trichomes are specialized hair-like structures in the epidermal cells of the above-ground parts of plants and help to protect them from pests and pathogens, and produce valuable metabolites. Chrysanthemum morifolium, which is used in tea products, has both ornamental and medicinal value; however, it is susceptible to infection by the fungus Alternaria alternata, which can result in substantial economic losses. Increasing the density of glandular trichomes enhances disease resistance and improves the production of medicinal metabolites in chrysanthemums, and jasmonate (JA) is known to promote the formation of trichomes in various plants. However, it remains unclear whether glandular trichomes in chrysanthemums are regulated by JA. In addition, grafting, a technique that can improve plant resistance to biotic stresses, has been poorly examined for its impact on glandular trichomes, terpenoids, and disease resistance. In this study, we demonstrate that grafting with Artemisia vulgaris rootstocks improves the resistance of chrysanthemum scions to A. alternata. Heterografted chrysanthemums exhibited higher trichome density and terpenoid content compared to self-grafted counterparts. Transcriptome analysis highlighted the significant role of CmJAZ1-like in disease resistance in heterografted chrysanthemums. Lines overexpressing CmJAZ1-like exhibited sensitivity to A. alternata, and this was characterized by reduced glandular trichome density and limited terpenoid content. Conversely, CmJAZ1-like silenced lines exhibited resistance to A. alternata and showed increased glandular trichome density and terpenoid content. Higher JA content was found in the heterografted chrysanthemum scions compared to self-grafted ones. Furthermore, we established that JA promoted the development of glandular trichomes and the synthesis of terpenoids while also inducing the degradation of CmJAZ1-like proteins in chrysanthemums. Our findings suggest that higher JA increases trichome density and terpenoid content, thereby enhancing resistance to A. alternata by regulating CmJAZ1-like in heterografted chrysanthemums. Grafting with disease-resistance rootstocks of Artemisia increases jasmonate content and degradation of JAZ1-like proteins in Chrysanthemum scions, leading to increased trichome density and terpenoid content, and thereby improving resistance to Alternaria alternata .

Chrysanthemum black spot disease caused by Alternaria alternate infestation is a widespread and extremely destructive foliar disease of chrysanthemums. We compared the resistance of 14 chrysanthemum relatives to chrysanthemum black spot disease, and identified the main indicators for the evaluation and screening of chrysanthemum disease resistance, which is of great significance in laying the foundation for a larger-scale screening of chrysanthemum relatives for disease resistance and the breeding of new disease-resistant cultivars. After artificial inoculation and identification, two disease-resistant germplasm resources, 11 moderately resistant materials, and one sensitive material were obtained. In both resistant and susceptible species, we found that the trichome density and leaf wax content of the resistant material were significantly higher than that of the sensitive material, while the stomata size was smaller than that of the sensitive material. In addition, we found that the leaf extract of the disease-resistant germplasm effectively inhibited the growth rate of A. alternate mycelium on the plate, and GC-MS components found that the leaves of resistant germplasm contained more volatile antifungal organic compounds, of which the abundant falcarinol and Germacrene D might play an important role in resistance to chrysanthemum black spot disease. In summary, epidermal trichome density, wax content and terpene substance content are three important reference indicators for disease resistance evaluation of related genera of chrysanthemum. The identified resistant germplasm can also be used as parents for future cross-breeding or as rootstocks.

Water plays an important role in the growth process of cut chrysanthemum (Chrysanthemum morifolium Ramat.). Accurate monitoring of plant water content (PWC) is a vital guarantee for the high-quality production of cut chrysanthemums. Hyperspectral remote sensing technology has been widely used in precision agriculture due to its rapid, convenient, and nondestructive advantages, but relatively little is known about its use for predicting the PWC of cut chrysanthemums. Therefore, this study aimed to evaluate the performance of hyperspectral reflectance from different leaf layers for estimating the PWC of cut chrysanthemums. A hyperspectral spectroradiometer was used to collect hyperspectral reflectance data (350-2500 nm) from three leaf layers at different critical growth periods. Immediately following the spectra measurements, cut chrysanthemum canopies were sampled for PWC. Spectral index and partial least square regression (PLSR) were then used to establish PWC estimation models of cut chrysanthemums. The results showed that the first leaf layer (LL1) was the optimal leaf layer for estimating the PWC of cut chrysanthemum. The new proposed two-band spectral index, NDVI-LL1 (R2280, R1885), exhibited moderate prediction capability for PWC cut chrysanthemum (R2=0.54658, RMSE=0.02352). Moreover, compared with the spectral index model, the model using the PLSR-LL1 showed the best performance for estimating the cut chrysanthemum PWC (R2=0.93510, RMSE=0.00887). Our results can provide technical support for spectral monitoring of PWC and precise irrigation in cut chrysanthemums.

Nitrogen (N) is a limiting factor that determines the yield and quality of Chrysanthemum. Genetic variation in N use efficiency (NUE) has been reported among Chrysanthemum genotypes. We performed a transcriptome analysis of two Chrysanthemum genotypes, ‘Nannonglihuang’ (‘LH’, N-efficient genotype) and ‘Nannongxuefeng’ (‘XF’, N-inefficient genotype), under low N (0.4 mmol·L-1 N) and normal N (8 mmol·L-1 N) treatments for 15 d and an N recovery treatment for 12 h (low N treatment for 15 d and then normal N treatment for 12 h) to understand the genetic factors impacting NUE in Chrysanthemum. The two genotypes exhibited contrasting responses to the different N treatments. The N-efficient genotype ‘LH’ had significant superiority in agronomic traits, N accumulation and glutamine synthase activity under both normal N and low N treatments. Low N treatment promoted root growth in ‘LH’, but inhibited root growth in ‘XF’. Transcriptome analysis revealed that the low N treatment increased the expression of some N metabolism genes, genes related to auxin and abscisic acid signal transduction in the roots of both genotypes, as well as genes related to gibberellin signal transduction in roots of ‘LH’. The N recovery treatment just increased the expression of genes related to cytokinin signal transduction in roots of ‘LH’. The expression levels of the NRT2.1, AMT1.1, and Gln1 genes related to gibberellin and cytokinin signal transduction were higher in roots of ‘LH’ than in ‘XF’ under different N treatments, suggesting that the genes related to N metabolism and hormone (auxin, abscisic acid, gibberellin, and cytokinin) signal transduction in roots of ‘LH’ are more sensitive to different N treatments than those of ‘XF’. Co-expression network analysis (WGCNA) also identified hub genes like bZIP43, bHLH93, NPF6.3, IBR10, MYB62, PP2C, PP2C06 and NLP7, which may be the key regulators of N-mediated responses in Chrysanthemum and play crucial roles in enhancing NUE and resistance to low N stress in the N-efficient Chrysanthemum genotype. These results revealed the key factors involved in regulating NUE in Chrysanthemum at the genetic level, which provides new insights into the complex mechanism of efficient nitrogen utilization in Chrysanthemum, and can be useful for the improvement and breeding of high NUE Chrysanthemum genotypes.

Precise nitrogen supply is crucial for ensuring the quality of cut chrysanthemums (Chrysanthemum morifolium Ramat.). The nitrogen nutrition index (NNI) serves as an important indicator for diagnosing crop nitrogen (N) nutrition. Hyperspectral remote sensing (HRS) technology has been widely used in monitoring crop N status due to its rapid, accurate, and non-destructive capabilities. However, its application in estimating the NNI of cut chrysanthemums has received limited attention. Therefore, this study aimed to use HRS to accurately determine the cut chrysanthemum NNI, thereby providing valuable guidance for managing N fertilization. During several key growth stages, a hyperspectral spectroradiometer was used to capture hyperspectral reflectance data (350–2500 nm) from three leaf layers. Subsequently, cut chrysanthemum canopies were sampled for aboveground biomass (AGB) and plant nitrogen concentration (PNC). The collected AGB and PNC data were then utilized to fit the critical N (Nc) dilution curve of cut chrysanthemums using a Bayesian hierarchical model, enabling the calculation of the NNI. Finally, spectral indices and partial least squares regression (PLSR) were used to establish the NNI estimation model for cut chrysanthemums. The results showed that the Nc dilution curve of the cut chrysanthemums was Nc = 5.401 × AGB−0.468. The first leaf layer (L1) proved to be optimal for estimating cut chrysanthemum NNI. Additionally, a newly proposed two-band spectral index, DVI-L1 (R1105, R700), demonstrated moderate predictive capabilities for the NNI of cut chrysanthemums (R2 = 0.5309, RMSE = 0.3210). Compared with the spectral index-based NNI estimation model, PLSR-L1 showed the best performance in estimating the cut chrysanthemum NNI (R2 = 0.8177, RMSE = 0.2000). Our results highlight the rapid NNI prediction potential of HRS and its significance in facilitating precise N management in cut chrysanthemums.

Nitrogen (N), phosphorus (P), and potassium (K) are three macronutrients that are crucial in plant growth and development. Deficiency or excess of any or all directly decreases crop yield and quality. There is increasing awareness of the importance of rhizosphere microorganisms in plant growth, nutrient transportation, and nutrient uptake. Little is known about the influence of N, P, and K as nutrients for the optimal production of Chrysanthemum morifolium. In this study, a field experiment was performed to investigate the effects of N, P, and K on the growth, nutrient use efficiency, microbial diversity, and composition of C. morifolium. Significant relationships were evident between N application rates, C. morifolium nutrient use, and plant growth. The N distribution in plant locations decreased in the order of leaf > stem > root; the distributions were closely related to rates of N application. Total P fluctuated slightly during growth. No significant differences were found between total P in the roots, stems, and leaves of C. morifolium vegetative organs. Principle component analysis revealed that combinations of N, P, and K influenced soil nutrient properties through their indirect impact on operational taxonomic units, Shannon index, and abundance of predominant bacterial taxa. Treatment with N, P, and K (600, 120, and 80 mg·plant−1, respectively) significantly improved plant growth and quality and contributed to the bacterial richness and diversity more than other concentrations of N, P, and K. At the flowering time, the plant height, leaf fresh weight, root dry weight, stem and leaf dry weight were increased 10.6%, 19.0%, 40.4%, 27% and 34.0%, respectively, when compared to the CK. The optimal concentrations of N, P, and K had a positive indirect influence on the available soil nutrient content and efficiency of nutrient use by plants by increasing the abundance of Proteobacteria, decreasing the abundance of Actinobacteria, and enhancing the potential functions of nitrogen metabolism pathways. N, P, and K fertilization concentrations of 600, 120, and 80 mg·plant−1 were optimal for C. morifolium cultivation, which could change environmental niches and drive the evolution of the soil microbial community and diversity. Shifts in the composition of soil microbes and functional metabolism pathways, such as ABC transporters, nitrogen metabolism, porphyrin, and the metabolism of chlorophyll II, glyoxylate, and dicarboxylate, greatly affected soil nutrient cycling, with potential feedback on C. morifolium nutrient use efficiency and growth. These results provide new insights into the efficient cultivation and management of C. morifolium.

Tea chrysanthemums generally have a distinctive and appealing aroma, which typically depends on the volatiles and affects the market share of different tea chrysanthemum varieties. Recently, many tea chrysanthemum cultivars and elite hybrids have been released for production. Therefore, understanding the diversity of the volatile compounds is critical to the quality improvement of tea chrysanthemums. Here, we studied the volatile compounds of 41 commercial tea chrysanthemum cultivars and elite hybrids using gas chromatography-mass spectrometry (GC-MS). One hundred and seventy volatile components were identified, of which 25 were species-specific, and palmitic acid was the only component present in all samples. Functional grouping divided the volatile components into 78 terpenoids, 15 hydrocarbons, 15 acids, 26 esters, 13 alcohols, 11 ketones, 3 aldehydes, and nine other compounds. There was a considerable variation in volatile compound contents among the investigated accessions, ranging from 481.04 ng/g of 'Suju-8' to 2495.67 ng/g of 'Suju-11'. A heatmap and dendrogram visualization suggested that the 41 tea chrysanthemums could be separated into two groups: commercial cultivars dominated one, while the other was composed mainly of elite hybrids. The principal component analysis found that 'Xiaohuangju', 'Zaohua-1', and 'CH7-18' had the best final scores with their special distinction in four principal component axes, and 'Suju-11' showed superiority in terpenoids, acids, es-ters, and ketones contents. The findings enable a better understanding of the composition of volatile compounds of tea chrysanthemums and are conducive to developing new varieties with superior volatiles in the future.

BackgroundChrysanthemum Fusarium wilt is a common fungal disease caused by Fusarium oxysporum, which causes continuous cropping obstacles and huge losses to the chrysanthemum industry. The defense mechanism of chrysanthemum against F. oxysporum remains unclear, especially during the early stages of the disease. Therefore, in the present study, we analyzed chrysanthemum 'Jinba' samples inoculated with F. oxysporum at 0, 3, and 72 h using RNA-seq.ResultsThe results revealed that 7985 differentially expressed genes (DEGs) were co-expressed at 3 and 72 h after F. oxysporum infection. We analyzed the identified DEGs using Kyoto Encyclopedia of Genes and Genomes and Gene Ontology. The DEGs were primarily enriched in "Plant pathogen interaction", "MAPK signaling pathway", "Starch and sucrose metabolism", and "Biosynthesis of secondary metabolites". Genes related to the synthesis of secondary metabolites were upregulated in chrysanthemum early during the inoculation period. Furthermore, peroxidase, polyphenol oxidase, and phenylalanine ammonia-lyase enzymes were consistently produced to accumulate large amounts of phenolic compounds to resist F. oxysporum infection. Additionally, genes related to the proline metabolic pathway were upregulated, and proline levels accumulated within 72 h, regulating osmotic balance in chrysanthemum. Notably, the soluble sugar content in chrysanthemum decreased early during the inoculation period; we speculate that this is a self-protective mechanism of chrysanthemums for inhibiting fungal reproduction by reducing the sugar content in vivo. In the meantime, we screened for transcription factors that respond to F. oxysporum at an early stage and analyzed the relationship between WRKY and DEGs in the "Plant-pathogen interaction" pathway. We screened a key WRKY as a research target for subsequent experiments.ConclusionThis study revealed the relevant physiological responses and gene expression changes in chrysanthemum in response to F. oxysporum infection, and provided a relevant candidate gene pool for subsequent studies on chrysanthemum Fusarium wilt.