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Potassium nutrition regulates growth, nutrient-carbon interactions and lignification during autumn in Tsoongiodendron odorum seedlings.

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Potassium nutrition regulates growth, nutrient-carbon interactions and lignification during autumn in Tsoongiodendron odorum seedlings - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites. Search Log in Dashboard Publications Account settings Log out Search… Search NCBI Primary site navigation Search Logged in as: Dashboard Publications Account settings Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide PERMALINK Copy As a library, NLM provides access to scientific literature. 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Learn more: PMC Disclaimer | PMC Copyright Notice BMC Plant Biol . 2026 Mar 10;26:695. doi: 10.1186/s12870-026-08497-8 Search in PMC Search in PubMed View in NLM Catalog Add to search Potassium nutrition regulates growth, nutrient-carbon interactions and lignification during autumn in Tsoongiodendron odorum seedlings Wen Gan Wen Gan 1 Key Laboratory for Cultivation and Utilization of Subtropical Forest Plantation, Guangxi Universities, Nanning, Guangxi China 2 School of Forestry, Guangxi University, Nanning, 530004 Guangxi China Find articles by Wen Gan 1, 2 , Xinyu Deng Xinyu Deng 1 Key Laboratory for Cultivation and Utilization of Subtropical Forest Plantation, Guangxi Universities, Nanning, Guangxi China 2 School of Forestry, Guangxi University, Nanning, 530004 Guangxi China Find articles by Xinyu Deng 1, 2 , Yujun Liu Yujun Liu 3 Nanning Arboretum, Nanning, Guangxi 530031 China Find articles by Yujun Liu 3 , Li Liu Li Liu 3 Nanning Arboretum, Nanning, Guangxi 530031 China Find articles by Li Liu 3 , Mei Yang Mei Yang 1 Key Laboratory for Cultivation and Utilization of Subtropical Forest Plantation, Guangxi Universities, Nanning, Guangxi China 2 School of Forestry, Guangxi University, Nanning, 530004 Guangxi China Find articles by Mei Yang 1, 2 , Yuanyuan Xu Yuanyuan Xu 1 Key Laboratory for Cultivation and Utilization of Subtropical Forest Plantation, Guangxi Universities, Nanning, Guangxi China 2 School of Forestry, Guangxi University, Nanning, 530004 Guangxi China Find articles by Yuanyuan Xu 1, 2, ✉ Author information Article notes Copyright and License information 1 Key Laboratory for Cultivation and Utilization of Subtropical Forest Plantation, Guangxi Universities, Nanning, Guangxi China 2 School of Forestry, Guangxi University, Nanning, 530004 Guangxi China 3 Nanning Arboretum, Nanning, Guangxi 530031 China ✉ Corresponding author. Received 2025 Nov 27; Accepted 2026 Feb 28; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13085730  PMID: 41803723 Abstract Tsoongiodendron odorum is a precious tree species native to the subtropical region of southern China, valued for both timber production and ornamental purposes. However, the optimal potassium application rate for its seedlings during autumn and the underlying physiological response mechanisms remain unclear. In this study, one-year-old T. odorum seedlings were subjected to six potassium levels (25, 65, 105, 145, 185, and 225 mg·plant⁻ 1 ) and a control (0 mg·plant⁻ 1 ) to investigate the effects on seedling growth, carbohydrate content, and nutrient accumulation. The results showed that moderate potassium supply (65–105 mg·plant⁻ 1 ) significantly promoted seedling growth and root development, with the 105 mg·plant⁻ 1 treatment achieving maximum values for seedling height, basal diameter, biomass, and root traits. This treatment also optimized nutrient stoichiometric ratios (N:P, N:K, and K:P within balanced ranges), increased leaf soluble protein and non-structural carbohydrate contents, and enhanced stem lignin accumulation. Redundancy analysis (RDA) identified starch, total nitrogen, and soluble protein as the dominant factors influencing growth; partial least squares structural equation modeling (PLS-SEM) further revealed that potassium supply regulated seedling growth through both direct pathways and indirect pathways mediated by nutrient and carbohydrate status. In conclusion, autumn potassium application at 105 mg·plant⁻ 1 effectively improves the quality of T. odorum seedlings, providing a theoretical basis and practical guidance for nutrient management in autumn nursery cultivation of this species. Keywords: Tsoongiodendron odorum , Autumn fertilization, Potassium, Carbohydrate, Lignification Introduction In subtropical evergreen tree species, autumn represents a critical growth phase for seedlings. During this period, seedlings shift from active shoot elongation to nutrient storage, root development, and tissue lignification—a physiological transition that fundamentally determines their overwintering success and subsequent field performance after outplanting. Seedling quality largely depends on their nutritional and physiological status during this stage, which in turn affects their post-transplant survival, growth, and stress resistance [ 9 , 59 ]. Adequate nutrient accumulation during autumn is particularly critical for sustaining metabolic stability and structural reinforcement, as roots and foliage remain physiologically active, contributing to osmotic adjustment, energy storage, and cell wall lignification [ 50 ]. In contrast, nutrient deficiency or imbalance this transitional stage can disrupt physiological homeostasis, impair reserve formation, and ultimately reduce seedling quality [ 18 ]. Previous studies have demonstrated that autumn fertilization promotes stable nutrient loading and carbohydrate accumulation, thereby improving seedling performance and stress resilience [ 32 , 59 , 60 ]. Nitrogen(N), phosphorus(P), and potassium(K) are three essential macronutrients for plant growth and development. Specifically, N promotes protein synthesis, P is involved in energy metabolism, and K regulates osmotic balance and enzyme activity. A coordinated supply of these nutrients is essential for sustaining healthy plant growth [ 29 ]. In particular, physiological processes such as photosynthetic efficiency, growth rate, and stress resistance are closely related to the uptake and allocation of these elements in plants [ 18 ]. Among these three macronutrients, K plays a particularly critical role during autumn acclimation in evergreen species. It actively participates in osmotic regulation, nutrient transport, and lignification—key processes that enable the transition from active growth to reserve accumulation. However, compared to N and P, the specific effects of K supply on seedling physiology during this phenological stage remain poorly understood. K is characterized by high mobility within plants [ 1 , 55 ]. Increasing evidence indicates that K functions as a central coordinator of nutrient acquisition and carbon metabolism, facilitating the conversion of photosynthates into structural components and contributing to stress tolerance [ 14 , 23 , 29 , 43 , 54 , 64 ]. In addition, K enhances nutrient uptake and storage by increasing root activity and selective ion absorption [ 5 , 71 ], thereby sustaining intracellular metabolic homeostasis [ 48 ]. The importance of K in autumn seedlings hardening is highlighted by recent findings. For example, applying K in autumn has been shown to significantly increase osmoregulatory substances content and improve nutritional stoichiometry in Parashorea chinensis seedlings, thereby enhancing their stress resistance [ 58 ]. However, plant responses to K availability are highly species-specific and vary with developmental stage, and environmental conditions. For example, in walnut ( Juglans regia ), K deficiency suppresses root development and photosynthetic capacity [ 25 ], whereas excessive K restricts assimilate translocation to roots and suppresses biomass accumulation [ 49 ]. These contrasting responses underscore the necessity for species-specific optimization of K supply. Tsoongiodendron odorum is an evergreen tree species of the family Magnoliaceae. As a rare and relict plant endemic to China, it is primarily distributed in subtropical regions including Guangxi, Guangdong, Yunnan, Fujian, and Jiangxi provinces. This species is valued for its high-quality timber and ornamental characteristics, making it significant for both wood utilization and landscape greening. High-quality seedlings (characterized by rapid growth and strong stress resistance) are fundamental to its development and utilization. Current research on T. odorum has primarily focused on wood properties, provenance selection, seedling cultivation techniques, and genetic diversity [ 26 , 41 , 56 , 62 , 66 ]. Our previous research has found that T. odorum seedlings exhibit a full-year growth pattern, with seedling height following an "S"-shaped growth curve. The rapid growth phase occurs from April to October, while seedlings continue to grow at a relatively slow rate from November to March of the following year. Basal diameter growth peaks alternately with height growth, with faster growth from January to September [ 67 ]. We have also explored traditional spring fertilization regimes for this species [ 69 ]. Autumn represents a critical transitional stage in seedling development, during which biomass accumulation continues. Ceasing fertilization during this period reduces soil nutrient availability, potentially leading to nutrient dilution and a decline in seedling quality. Autumn fertilization is recognized as an effective steady-state nutrient loading strategy that enhances nutrient reserves. However, no studies have reported on autumn fertilization strategies specifically for T. odorum seedlings. Given the key role of K in autumn physiological processes, this study used one-year-old T. odorum seedlings in a pot experiment to investigate the effects of autumn K application. The objectives of this study were to: (1) investigate the effects of varying autumn K supply levels on seedling growth, nutrient, and carbohydrate accumulation in T. odorum , (2) explore the relationships among these traits to identify the key factors influencing seedling performance; (3) identify the optimal K supply level for autumn seedling cultivation, providing a scientific basis for autumn nursery nutrient management and high-quality seedling cultivation in T. odorum . Materials and methods Study site description The experiment was conducted in a transparent rain-shelter in the nursery of the College of Forestry, Guangxi University (108°17′9″E, 22°50′28″N). This region is characterized by a South Subtropical monsoon climate, which features long summers and short winters. According to long-term climate data (1991–2020) obtained from the China National Climate Science Data Center ( https://data.cma.cn/ ), the experimental site has a long-term mean annual temperature of 21.6 ± 5.4 °C, a mean winter temperature of 12.8 ± 4.2 °C, annual precipitation averages 1304.2 mm, and a mean annual relative humidity of 79%. Rain shelters effectively block precipitation while maintaining light conditions identical to the natural environment, with air temperatures during the experiment remaining consistent with regional climatic conditions. Plant material and experimental design Healthy, one-year-old T. odorum seedlings with similar growth vigor were selected as the experimental material (average seedling height: 25.1 ± 3.1 cm, average basal diameter: 4.80 ± 0.49 mm). The seeds originated from Dingjiao Village, Delong Township, Napo County, Baise City, Guangxi Province, China (Fig. 1 ). Both the seed collection site and the experimental site are located in Guangxi. Our preliminary research has demonstrated that this T. odorum provenance exhibits strong adaptability to Nanning, where it can successfully flower and bear fruit. The seedlings were planted in 20 cm × 20 cm non-woven fabric bags, with one seedling per bag. The growth substrate consisted of yellow subsoil (locally referred to as yellow-heart soil, a highly weathered Ferralic Cambisol derived from Quaternary red clay, collected from a depth of 20–40 cm in a nearby forestland), perlite, and coarse sand mixed in a volume ratio of 3:1:1. Each pot contained 3.5 kg of substrate. The initial nutrient properties of the substrate were as follows: nitrate nitrogen (NO 3 − -N) content of 6.02 mg·kg −1 , ammonium nitrogen (NH 4 + -N) content of 11.0 mg·kg −1 , available phosphorus (P) content of 2.89 mg·kg −1 , available potassium (K) content of 35.9 mg·kg −1 , and organic matter content of 18.22 g·kg −1 . Seedlings were transplanted on September 30, 2023, and allowed a three-week recovery period in the rain-shelter. The experiment commenced after the seedlings had resumed normal growth. Fig. 1. Open in a new tab The natural range of T. odorum , seed collection site, and experimental location The experiment commenced on October 20, 2023, and concluded on March 1, 2024, lasting a total of 133 day. Our previous study indicated that applying N 120 mg·plant −1 , P 60 mg·plant −1 , and K 80 mg·plant −1 in spring is most beneficial for the growth of T. odorum [ 69 ]. However, the optimal potassium (K) application rate during autumn remains unclear. To address this, we established seven K concentration treatments based on our previous experiment. The levels were set at 0 (control), 25, 65, 105, 145, 185, and 225 mg·plant⁻ 1 , covering a gradient from deficiency to excess. It should be noted that the K concentration gradient used in this study was designed for containerized seedling cultivation and represents a range of K supply levels under controlled fertilization conditions, rather than an attempt to simulate natural soil K availability. The experiment followed a completely randomized block design (RCBD) with seven K treatment levels. Each treatment was replicated three times (block), and each replication (plot) consisting of 10 T . odorum seedlings, totaling 210 plants. To ensure normal seedling growth, nitrogen(N) and phosphorus(P) fertilizers were applied uniformly across all treatments, in addition to the variable K level, while no micronutrients were supplemented. The total N application rate was 30 mg·plant −1 sourced from urea (CO(NH 2 ) 2 , N: 46%). The total P application rate was 60 mg·plant −1 sourced from superphosphate (P 2 O 5 , P: 16%). Potassium fertilizer was sourced from potassium chloride (K 2 O, K: 60%). The total amount of N, P, and K fertilizer for the entire experimental period was applied in three equal split doses on October 20, November 5, and November 20, 2023, by ring application method (subsurface banding around each plant). Throughout the experiment, management practices were consistent across all treatments: the relative soil water content was maintained at approximately 60%, and regular weeding, watering, and pest and disease control were performed. Determination of seedlings morphological traits During the experiment, the seedling height and basal diameter of plants in all treatment measured every two weeks. Seedling height was measured using a steel tape measure (from the soil line at the stem base to the apical bud, accurate to 0.1 cm). Basal diameter (stem thickness at the soil line of the stem base, accurate to 0.01 mm) was determined using a digital caliper. From each replicate, three seedlings were randomly selected. After being rinsed with deionized water, they were separated into roots, stems, and leaves. The samples were first dried at 105 °C for 30 min, then dried to a constant weight at 75 °C, after which the biomass of each organ was measured. The dry weight of roots, stems, and leaves was determined using electronic scale (accurate to 0.01 g). The dried samples, after biomass measurement, were ground and passed through a 100-mesh sieve for determining the nutrient element content in each organ. Based on these measurements, total biomass, height-to-diameter ratio (H/D), and shoot-to-root ratio (S/R) were calculated according to the corresponding formulas: 1 2 3 Seedling quality was evaluated using the Dickson Quality Index (DQI) [ 10 , 47 ], which was calculated according to the formula: 4 Determination of root traits Three seedlings were randomly selected for each replication for determining the total root length, total surface area, average diameter, and total tip number with an Epson Expression 10000XL scanner (Regent Instruments, Canada). Data was analyzed using a WinRHIZO software. Determination of physiological parameters This study primarily measured the carbohydrate parameters of seedlings, including Nonstructural Carbohydrates (NSC) and Structural Carbohydrates (SC) [ 6 , 11 , 61 ]. For NSC, soluble sugars and starch in leaves were determined, while for SC, lignin and cellulose in stems were measured. The anthrone-sulfuric acid method was used to determine soluble sugar and starch contents [ 7 ]. Lignin content was quantified using the acetyl bromide spectrophotometric method [ 39 ], and cellulose content was measured by the anthrone-sulfuric acid colorimetric method following acid hydrolysis [ 15 ]. Additionally, we determined the soluble protein content in seedling leaves and root activity. Soluble protein content was measured using the Coomassie brilliant blue G-250 staining method [ 16 ]. Root activity was assessed by the 2,3,5-Triphenyl Tetrazolium Chloride (TTC) reduction method [ 8 ]. For each parameter, leaf or stem samples (1 g fresh weight, FW) were randomly collected from each biological replicate. All measurements were conducted with three technical replicates. Plant nutrient content and stoichiometric ratio measurement Approximately 0.2 g of the powder was weighed into a digestion tube, soaked in 5 mL H 2 SO 4 overnight, and then digested at 4 h [ 42 , 68 ]. The contents of total nitrogen and total phosphorus were determined by an automatic discontinuous chemical analyzer (Smartchem200; AMS, Rome, Italy). Total K contents were determined by a flame photometer (FP6450, Shanghai, China). And per measurement was repeated thrice. Further, based on the nutrient content of each organ, the nutrient accumulation and nutrient stoichiometric ratios of each organ were calculated. The formula for calculating nutrient accumulation was: 5 The whole-plant nutrient stoichiometric ratios, including N:P, N:K, and K:P, were calculated as mass ratios based on the total nutrient contents in roots, stems, and leave. Statistical analysis Experimental data were initially organized using Excel 2021, and results were presented as mean ± standard deviation. One-way analysis of variance (ANOVA) was performed using SPSS 24.0 (IBM SPSS Statistics 24.0) to test differences among K supply levels, followed by Tukey’s Honestly Significant Difference (HSD) test for multiple comparisons. Statistical significance was set at p < 0.05. Graphical outputs were generated using OriginPro 2025. Pearson correlation analysis was conducted to assess pairwise relationships among all measured variables. Redundancy Analysis (RDA) was performed using Canoco 5.0 to provide a multivariate visualization of seedling growth, physiological, and nutrient variables across K supply levels. Partial Least Squares-Structural Equation Model (PLS-PM) was constructed using SmartPLS 4.0 (version 4.1.1.5) to further verify the potential causal pathways of K supply level on nutrient status, physiological characteristics, and growth-related traits. The PLS-SEM model structure was defined a priori based on the experimental design and observed variable groupings. K supply level was treated as the exogenous construct, while measured traits were categorized into four endogenous latent variables: nutrient status, leaf non-structural substances, stem lignification and seedling quality. This structure was used to examine how these trait groups were statistically associated across K treatments. Following the methodological standards [ 20 , 24 ], the measurement model was validated for reliability and convergent validity, while the overall structural fit was assessed using the Standardized Root Mean Square Residual (SRMR). Results Effects of potassium application on seedling growth traits and quality of T. odorum Seedling growth traits Autumn K application significantly affected seedling height, basal diameter, and biomass of T. odorum seedlings ( p < 0.05) (Fig. 2 ). Among them, seedling height was significantly higher under 105, 145, 185, and 225 mg·plant⁻ 1 K treatments than in the control ( p < 0.05), with no significant differences among these four treatments ( p > 0.05); no significant difference was observed between the control and the 25 or 65 mg·plant⁻ 1 treatments ( p > 0.05). Basal diameter was significantly higher than the control across all K treatments (25–225 mg·plant⁻ 1 , p < 0.05). The highest value was observed at 145 mg·plant⁻ 1 , which did not differ significantly from those under 65, 105, or 225 mg·plant⁻ 1 (Fig. 2 a). Root biomass was significantly higher under the 25, 65, and 105 mg·plant⁻ 1 K treatments than in the control ( p < 0.05). Stem biomass under the 65, 105, and 145 mg·plant⁻ 1 K treatments was significantly higher than in the control ( p < 0.05). Leaf biomass and total biomass were significantly greater under all K treatments (25–225 mg·plant⁻ 1 ) than in the CK ( p < 0.05). The 105 mg·plant⁻ 1 K treatment produced the highest values for root, stem, leaf, and total biomass, with increases of 27.14%, 13.87%, 35.37%, and 23.56%, respectively, over the control. No significant differences in these biomass parameters were observed between the 105 and 65 mg·plant⁻ 1 treatments ( p > 0.05) (Fig. 2 b, c). Fig. 2. Open in a new tab Differences in seedling growth of T. odorum under different potassium (K) supply levels. ( a) Seedling height and basal diameter; ( b ) Biomass of each organ; ( c ) Total biomass. Different lowercase letters (a, b, c, d) indicate significant differences at p < 0.05 based on one-way ANOVA by Tukey’s HSD tests. Data are means ± standard deviation ( n = 3) Seedling root morphology As presented in Table 1 , autumn K application significantly affected root morphological traits of T. odorum seedlings ( p < 0.05). Total root length was significantly higher under K treatments of 65–185 mg·plant⁻ 1 than in the control ( p < 0.05). Total root surface area and total root volume were significantly higher under the 25, 65, and 105 mg·plant⁻ 1 K treatments than in the control and all other K treatments ( p < 0.05). The number of root tips was significantly higher under 25, 65,105, 145, 185 mg·plant⁻ 1 treatments compared to the control ( p < 0.05). Average root diameter at 105 mg·plant⁻ 1 K was significantly higher than at 225 mg·plant⁻ 1 ( p < 0.05), but did not differ significantly from the control or other K treatments ( p > 0.05). Among all treatments, the 105 mg·plant⁻ 1 K treatment exhibited the highest values for total root length, total root surface area, total root volume, and number of root tips. While total root length and number of root tips under this treatment did not differ significantly from those under the 65 mg·plant⁻ 1 treatment ( p > 0.05), its total root surface area and total root volume were significantly greater than those of all other treatments ( p < 0.05). Table 1. Differences in root morphology of T. odorum seedlings under different potassium (K) supply levels. Treatment (mg·plant −1 ) Total Root Length (cm) Total Root Surface Area (cm 2 ) Total Root Volume (cm 3 ) Average Root Diameter (cm) Number of Root Tip (bars) Control 374.31 ± 3.65 c 142.66 ± 4.90 c 4.36 ± 0.09 d 1.16 ± 0.01 ab 1 015.0 ± 13.90 c 25 407.02 ± 2.01 bc 161.04 ± 2.87 b 5.05 ± 0.24bc 1.28 ± 0.08 ab 1 151.0 ± 25.90 b 65 426.70 ± 16.25 ab 157.83 ± 3.18 b 5.09 ± 0.18 b 1.25 ± 0.15 ab 1 250.0 ± 43.50 a 105 460.56 ± 25.53 a 181.15 ± 6.09 a 6.18 ± 0.18 a 1.36 ± 0.07 a 1 284.3 ± 42.70 a 145 418.11 ± 15.08 b 146.10 ± 0.96 c 4.62 ± 0.08 bcd 1.22 ± 0.11 ab 1 143.3 ± 32.60 b 185 411.73 ± 5.50 b 145.48 ± 1.16 c 4.57 ± 0.15 cd 1.12 ± 0.13 ab 1 124.7 ± 30.60 b 225 405.18 ± 8.22 bc 143.95 ± 3.82 c 4.38 ± 0.2 5 d 1.08 ± 0.04 b 1 094.0 ± 26.50 bc Open in a new tab Data are means ± standard deviation ( n = 3) Different lowercase letters ( a, b, c, d ) indicate significant differences at p < 0.05 based on one-way ANOVA by Tukey’s HSD tests Seedling quality The height-to-diameter ratio (H/D ratio), shoot-to-root ratio (S/R ratio), and Dickson Quality Index (DQI) were used to evaluate seedling quality of T. odorum under different K supply levels (Table 2 ). The H/D ratio did not differ significantly among K treatments ( p > 0.05). In contrast, significant differences were observed in both the S/R ratio and DQI ( p < 0.05). The lowest S/R ratio (1.48) was recorded under the 105 mg·plant⁻ 1 treatment; this value was comparable to those under CK, 25, 65, and 185 mg·plant⁻ 1 ( p > 0.05), but was significantly lower than those under 145 and 225 mg·plant⁻ 1 ( p < 0.05). The DQI was significantly higher under the 25, 65, 105, and 145 mg·plant⁻ 1 treatments than in the control ( p < 0.05), with no significant differences among these four treatments ( p > 0.05). Additionally, the DQI under the 65 and 105 mg·plant⁻ 1 treatments was significantly greater than that under the 185 and 225 mg·plant⁻ 1 treatments ( p < 0.05). Table 2. Height-to-Diameter ratio (H/D ratio), Shoot-to-Root ratio (S/R ratio), and Dickson Quality Index (DQI) of T. odorum seedlings under potassium (K) application Treatment (mg·plant −1 ) Height-To-Diameter Ratio (cm·mm −1 ) Shoot-To-Root Ratio(g·g −1 ) Dickson Quality Index (DQI) Control 5.91 ± 0.20 a 1.56 ± 0.02 bc 0.42 ± 0.01 c 25 5.46 ± 0.43 a 1.58 ± 0.07 abc 0.50 ± 0.03 ab 65 5.20 ± 0.11 a 1.52 ± 0.01 bc 0.54 ± 0.03 a 105 5.48 ± 0.18 a 1.48 ± 0.03 c 0.56 ± 0.01 a 145 5.32 ± 0.28 a 1.69 ± 0.04 a 0.51 ± 0.03 ab 185 5.80 ± 0.46 a 1.59 ± 0.03 abc 0.46 ± 0.03 bc 225 5.49 ± 0.13 a 1.61 ± 0.04 ab 0.48 ± 0.01 bc Open in a new tab Data are means ± standard deviation ( n = 3) Different lowercase letters ( a, b, c, d ) indicate significant differences at p < 0.05 based on one-way ANOVA by Tukey’s HSD tests Effects of potassium application on root activity, soluble protein, and carbohydrate contents of T. odorum seedlings As shown in Fig. 3 , root activity, soluble protein content, and carbohydrate content of T. odorum seedlings differed significantly among different K treatment ( p < 0.05). The highest root activity was observed at 105 mg·plant⁻ 1 , significantly exceeding the control and all other treatments ( p < 0.05). Root activity was also significantly higher than the control under the 25, 65, 145, and 185 mg·plant⁻ 1 treatments ( p < 0.05) (Fig. 3 a). Leaf soluble protein content was significantly higher under all K treatments (25–225 mg·plant⁻ 1 ) than in the control ( p < 0.05), with the highest value (72.19% above control) observed at 105 mg·plant⁻ 1 (Fig. 3 b). Fig. 3. Open in a new tab Differences in physiological traits of T. odorum seedlings under different potassium (K) supply levels. a Root activity; b Soluble protein; c Soluble sugar and starch; d Lignin and cellulose. Different lowercase letters (a, b, c, d, e, f) indicate significant differences at p < 0.05 based on one-way ANOVA by Tukey’s HSD tests. The data were mean ± standard deviation ( n = 3) For leaf non-structural carbohydrates (NSC), soluble sugar content was significantly higher under the 65, 105, 145, 185, and 225 mg·plant⁻ 1 K treatments than in the control and the 25 mg·plant⁻ 1 treatment ( p < 0.05). The highest soluble sugar content was observed at 105 mg·plant⁻ 1 , which did not differ significantly from that at 145 mg·plant⁻ 1 ( p > 0.05). Soluble starch content was significantly higher under all K treatments (25–225 mg·plant⁻ 1 ) than in the control ( p < 0.05), with the maximum value recorded at 105 mg·plant⁻ 1 (Fig. 3 c). For stem structural carbohydrates (SC), lignin content was significantly higher under 65, 105, 145, and 185 mg·plant⁻ 1 treatments than in the control and the 25 and 225 mg·plant⁻ 1 treatments ( p < 0.05). No significant differences were detected among the 65, 105, 145, and 185 mg·plant⁻ 1 treatments ( p > 0.05). Cellulose content was significantly higher under the 145, 185, and 225 mg·plant⁻ 1 K treatments than in the control, while it was significantly lower under the 25, 65, and 105 mg·plant⁻ 1 treatments compared to the control ( p < 0.05, Fig. 3 d). Effects of potassium application on organ nutrient accumulation and stoichiometric ratios in T. odorum seedlings Nutrient accumulation K application significantly affected nutrient accumulation at the whole-plant level and in individual organs (roots, stems, and leaves) of T. odorum seedlings ( p < 0.05, Fig. 4 ). Whole-plant total N, P, and K accumulation were significantly higher under all K treatments (25, 65, 105, 145, 185, and 225 mg·plant⁻ 1 ) than in the control ( p < 0.05), with the highest values for all three nutrients observed at 105 mg·plant⁻ 1 ( p < 0.05). In roots, total N accumulation was significantly higher under the 105 mg·plant⁻ 1 treatment than under the control and all other K treatments ( p < 0.05). Total P accumulation was significantly higher under the 25 and 105 mg·plant⁻ 1 treatments, while total K accumulation was significantly higher under the 65, 105, and 225 mg·plant⁻ 1 treatments compared to the control and the remaining treatments ( p < 0.05). In stem, total N accumulation was significantly higher under 65 and 105 mg·plant⁻ 1 treatments than the control and the other K treatments ( p < 0.05). Total P accumulation was significantly higher under 65 mg·plant⁻ 1 treatments than and all other treatments ( p < 0.05). Total K accumulation was significantly higher under 65, 105, 145, and 225 mg·plant⁻ 1 treatments than under the control and the other K treatments ( p < 0.05). In the leaves, total N accumulation was significantly higher under 25, 105, 145 mg·plant⁻ 1 treatments than under the control and all other treatment ( p < 0.05). Total P accumulation showed its highest value under the 225 mg·plant⁻ 1 treatments. Total K accumulation was significantly higher under all treatments from 65 to 225 mg·plant⁻ 1 than under the control and the 25 mg·plant⁻ 1 treatment ( p < 0.05). Regarding nutrient allocation patterns, N was predominantly accumulated in leaves and stems, P and K were mainly distributed in stems and roots. Fig. 4. Open in a new tab Accumulation of the whole-plant and different organs nutrients of Tsoongiodendron odorum seedlings under various potassium (K) treatment. a Total nitrogen (N) accumulation; b Total phosphorus (P) accumulation; c Total potassium (K) accumulation. Different lowercase letters (a, b, c, d) and uppercase letters (A, B, C, D, E) indicate significant differences at p < 0.05 based on one-way ANOVA by Tukey’s HSD tests. Lowercase letters represent significant differences among different treatments within the same organ, and uppercase letters represent significant differences in whole-plant accumulation among different treatments. The data were mean ± standard deviation ( n = 3) Nutrient stoichiometric ratios In this study, nutrient stoichiometric ratios (N:P, N:K, and K:P) were calculated to characterize the nutrient balance status of the seedlings. As shown in Table 3 , the stoichiometric ratios of T. odorum seedlings varied considerably among different K application levels. The N:K ratio remained above 2.1 and the K:P ratio remained below 3.4 across all K treatments. Under the 105 and 145 mg·plant⁻ 1 treatments, the N:P ratio ranged from 14 to 16. In contrast, the N:P ratio was below 14 for the CK, 25, 65, and 225 mg·plant⁻ 1 treatments, while it exceeded 16 under the 185 mg·plant⁻ 1 treatment. Table 3. Nutrient stoichiometric ratios in T. odorum seedlings under different potassium Treatment (mg·plant −1 ) N:K Ratio K:P Ratio N:P Ratio Control 3.6 ± 0.05 ab 3.64 ± 0.33 c 13.09 ± 1.02 cd 25 3.74 ± 0.08 a 3.67 ± 0.21c 13.74 ± 1.03 bc 65 3.35 ± 0.23 bc 3.65 ± 0.27 c 12.19 ± 0.09 cd 105 3.52 ± 0.08 ab 4.6 ± 0.19 b 15.88 ± 0.29 a 145 3.34 ± 0.03 bc 4.59 ± 0.17 b 15.51 ± 0.61 ab 185 3.04 ± 0.12 c 5.38 ± 0.12 a 16.33 ± 0.29 a 225 2.51 ± 0.08 d 4.73 ± 0.18 b 11.88 ± 0.46 d Open in a new tab The data were mean ± standard deviation ( n = 3) Different lowercase letters ( a, b, c, d ) indicate significant differences at p < 0.05 based on one-way ANOVA by Tukey’s HSD tests Relationships among nutrients, carbohydrates, and growth in T. odorum seedlings under potassium application Correlation analysis To investigate the relationships among growth, physiology, and nutrient traits in T. odorum seedlings under K supply, correlation analysis was performed on the measured parameters (Fig. 5 a). The results showed that seedling height (SH), basal diameter (BD), biomass, total root length (TRL), and total root surface area (TRSA) were significantly or extremely significantly positively correlated with root activity (RV) and the contents of soluble protein (SP), soluble sugar (SS), starch (ST), lignin (LIG), total nitrogen accumulation (TN), total phosphorus accumulation (TP), and total potassium accumulation (TK) ( p < 0.05 or p < 0.01). RV, SP, SS, ST, and LIG were significantly or extremely significantly positively correlated with TN, TP, and TK ( p < 0.05 or p < 0.01). There was also an extremely significant positive correlation between TN and TP, as well as between TN and TK ( p < 0.01). Fig. 5. Open in a new tab Integrated analysis of the physiological and nutritional mechanisms underlying seedling quality under different potassium (K) supply levels. a Pearson correlation matrix of growth traits, physiological parameters, and nutrient accumulation. Red and blue ellipses indicate positive and negative correlations, respectively ( p < 0.05, ** p < 0.01, *** p < 0.001). b Redundancy analysis (RDA) showing the relationships between K supply levels (environmental factors) and seedling traits. c Partial Least Squares Structural Equation Model (PLS-SEM) revealing the mediation pathways. Numbers on solid arrows represent standardized path coefficients ( β ), with red solid lines indicating significant effects (* p < 0.05, ** p < 0.01, *** p < 0.001) and dashed lines indicating non-significant effects ( p > 0.05). R 2 and Q 2 values represent explanatory and predictive power, respectively. Abbreviations: SH: Seedling height; BD: basal diameter; LB: leaf biomass; SB: stem biomass; RB: root biomass; TB: total biomass; H/D: height –to–diameter ratio; S/R: shoot – to – root ratio; TRL: total root length; TRSA: total root surface area; TRV: total root volume; ARD: average root diameter; NRT: number of root tip, RV: root activity; SP: soluble protein content; SS: soluble sugar content; ST: starch content; LIG: lignin content; CEL: cellulose content; TN: total nitrogen accumulation; TP: total phosphorus accumulation; TK: total potassium accumulation Redundancy analysis To further explore the relationships among physiological, nutritional, and growth parameters under different potassium supply levels and to identify the key factors driving seedling growth, redundancy analysis (RDA) was conducted. Growth-related traits—including seedling height (SH), basal diameter (GD), root biomass (RB), stem biomass (SB), and leaf biomass (LB)—were designated as response variables (solid arrows). Root activity (RV), soluble protein (SP), soluble sugar (SS), soluble starch (ST), lignin (LIG), cellulose (CEL), total N accumulation (TN), total P accumulation (TP), and total K accumulation (TK), were treated as explanatory variables (hollow arrows). As shown in Fig. 5 b, the first two RDA axes explained 69.56% and 11.39% of the total variation, respectively, indicating that these axes effectively captured the majority of the relationship between seedling growth and the physiological and nutritional parameters. In the RDA sorting diagram, the length of each explanatory variable arrow reflects its relative contribution to the explained variance, with longer arrows indicating stronger influence. The cosine of the angle between an explanatory and a response variable arrow represents the strength of their correlation—smaller angles correspond to stronger positive correlations. ST, TN, and SP exhibited the longest arrows, suggesting that these were the most influential factors driving seedling growth. Specifically, SH was positively correlated with SS and TK; GD was positively correlated with ST and LIG; LB was positively correlated with TN; and RB and SB were positively correlated with TP, RV, and SP. In addition, the RDA sorting diagram showed that the 105 and 145 mg·plant⁻ 1 K treatments were positioned more closely to the variables associated with seedling growth, nutrient accumulation, and carbohydrate-related traits, indicating that this concentration range is closely associated with these physiological processes. Path analysis Based on the aforementioned findings, a Partial Least Squares Structural Equation Model (PLS-SEM) was constructed to examine the relationships among potassium (K) supply level, nutrient status, non-structural Substances, lignification, and seedling performance (Fig. 5 c). The model comprised one exogenous variable (K supply levels) and four endogenous latent variables with their respective reflective indicators: Nutrient Status was represented by total nitrogen (TN), total phosphorus (TP), and total potassium (TK) accumulation; Non-structural Substances was represented by soluble protein (SP), soluble sugar (SS), and starch (ST); Lignification was represented by lignin (LIG) content; and Seedling Performance was represented by basal diameter (BD), seedling height (SH), and total biomass (TB). Cellulose (CEL) was initially included as an indicator of structural carbohydrates but was excluded from the final model due to low factor loading and non-significant associations with K supply. The SRMR value for our final model is 0.098. Model evaluation indicated acceptable explanatory and predictive capacity. The coefficients of determination ( R 2 ) for Seedling Quality was 0.879, respectively, and all predictive relevance ( Q 2 ) values for endogenous variables were greater than zero. Path analysis showed that K supply was positively associated with Nutrient Status ( β = 0.402, p < 0.05), and the Nutrient Status exhibited a dominant positive effect on Non-structural Substances ( β = 0.807, p < 0.001). In addition, Nutrient Status significantly has a positive effect on Lignification ( β = 0.547, p < 0.01). Although K supply showed a direct association with Non-structural Substances ( β = 0.312, p < 0.05), its association with Lignification was primarily indirect, mediated through the improvement of nutrient status ( β = 0.041, p > 0.05). Discussion Effects of potassium supply on seedling morphology and quality of T. odorum seedlings Autumn fertilization is a key practice for cultivating high-quality seedlings for afforestation, and seedling morphological traits commonly used to reflect physiological vigor and potential field performance after transplantation. Studies have shown that seedling height, basal diameter and biomass reflect overall seedling performance and resource allocation, while well-developed root systems facilitate water and nutrients uptake [ 12 ]. In this study, autumn K application significantly affected the growth of T. odorum seedlings (Fig. 1 , Table 1 ). Seedling height was significantly higher under the 105–225 mg·plant⁻ 1 treatments than in the control, and basal diameter was significantly higher under all K treatments compared to the control. The 105 mg·plant⁻ 1 treatment produced the highest biomass values in all organs and at the whole-plant level, although these did not differ significantly from the 65 mg·plant⁻ 1 treatment. These results indicate that moderate autumn K supply benefits both aboveground and belowground growth of T. odorum seedlings. Root morphological traits also exhibited differential responses to K supply (Table 1 ). Total root length, total root surface area, total root volume, and number of root tips were significantly higher under the 65–105 mg·plant⁻ 1 treatments than in the control, while average root diameter did not differ significantly among treatments. The 105 mg·plant⁻ 1 treatment showed the highest values for all measured root traits, suggesting that moderate K supply enhances root absorptive area primarily by promoting root branching and elongation rather than increasing root diameter, thereby improving water and nutrient uptake capacity. Regarding overall seedling quality (Table 2 ), the shoot-to-root (S/R) ratio was lowest at 105 mg·plant⁻ 1 (1.48), and the Dickson Quality Index (DQI) was significantly higher under the 25–145 mg·plant⁻ 1 treatments than in the control. These findings demonstrate that moderate K supply (65–105 mg·plant⁻ 1 ) comprehensively improves seedling quality by promoting growth, optimizing root architecture, and coordinating biomass allocation, with 105 mg·plant⁻ 1 identified as the optimal treatment for overall performance. The growth response of T. odorum seedlings to autumn K application followed a nonlinear pattern: growth promotion diminished or was inhibited under lower (0–25 mg·plant⁻ 1 ) or higher (145–225 mg·plant⁻ 1 ) K supply levels, indicating an optimal K range for this species during autumn. Such dose-dependent responses—where growth is optimized at intermediate nutrient supply and suppressed under deficiency or excess—have been well documented in woody plants, with similar patterns reported in K fertilization studies on P. chinensis [ 58 ] and J. regia [ 25 ]. Reduced growth under low K may be associated with impaired osmotic regulation and assimilate transport, while excessive K may lead to ionic imbalance or nutrient antagonism [ 27 , 34 , 52 , 54 ]. Notably, the 105 mg·plant⁻ 1 treatment exhibited the most favorable combination of traits, including maximum biomass and DQI, along with lower S/R ratios. These morphological adjustments, particularly the more balanced biomass partitioning, are consistent with improved structural stability, although their functional significance for overwintering survival requires direct validation. Potassium-mediated changes in nutrient accumulation and stoichiometric Nutrient accumulation and stoichiometric ratios provide important indicators of nutrient uptake, allocation, and balance in plants [ 23 , 43 ]. Unlike the active growing season, autumn in perennial evergreen species exhibits a distinct nutrient dynamic. Nutrient uptake and internal allocation during this period are primarily directed toward reserve formation and metabolic stabilization, rather than immediate biomass expansion. In this study, whole-plant N, P, and K accumulation in T. odorum seedlings were higher under all K treatments than in the control, with the highest values for all three nutrients observed at 105 mg·plant⁻ 1 (Fig. 4 ). This indicates that optimal K supply favors nutrient storage in T. odorum seedlings. The N:P, N:K, and K:P ratios varied significantly among treatments (Table 3 ). Across all K treatments, the N/K ratio remained above 2.1 and the K/P ratio below 3.4, suggesting that K limitation was unlikely under any treatment based on the thresholds proposed by Olde Venterink et al. [ 46 ]. Under the 105 and 145 mg·plant⁻ 1 treatments, the N:P ratio ranged from 14 to 16, a range often interpreted as indicating N and P co-limitation or balanced supply [ 33 ]. In contrast, N:P ratios below 14 (CK, 25, 65, and 225 mg·plant⁻ 1 ) and above 16 (185 mg·plant⁻ 1 ) were observed, consistent with possible N or P limitation, respectively. However, it should be noted that these thresholds were originally developed for natural wetland vegetation, and their applicability to fertilized nursery seedlings remains uncertain. Therefore, these stoichiometric patterns should be considered indicative rather than definitive evidence of nutrient limitation. The balanced stoichiometry observed under the 105 mg·plant⁻ 1 treatment, together with its optimal growth performance, suggests that moderate K supply improves nutrient coordination. This may be related to the well-documented role of K⁺ in stimulating root H⁺-ATPase activity, which enhances ion uptake capacity and regulates rhizosphere conditions [ 19 , 29 ]. Although enzyme activities were not directly measured in this study, the observed nutrient responses are consistent with such regulatory functions. Under low K supply, reduced nutrient accumulation may reflect impaired root absorption capacity and osmotic regulation, as reported in other studies [ 34 , 45 ]. Under high K supply, the decline in N and P accumulation could be associated with cation antagonism or altered nutrient dynamics in the root zone [ 4 , 22 , 53 ]. Organ-specific analysis revealed distinct allocation patterns (Fig. 4 ): N was predominantly accumulated in leaves and stems, while P and K were mainly distributed in stems and roots. This pattern may reflect functional differentiation—with leaves maintaining metabolic activity and stems and roots serving as storage organs—a strategy that could enhance internal nutrient retention and improve seedling adaptability during periods of low external nutrient availability [ 65 , 73 ]. However, the adaptive significance of these allocation patterns remains to be tested. Effects of potassium supply on carbohydrate leaf non-structural substances and stem lignification The improvement of seedling quality and vigor often results from enhanced nutrient status and metabolic efficiency. In this study, potassium supply significantly affected leaf physiological indicators and stem structural carbon components of T. odorum seedlings (Fig. 2 ). Root activity is a key indicator of root metabolic intensity and absorption capacity. Higher root activity not only promotes nutrient and water uptake but also enhances seedling adaptability to stress conditions such as drought and low temperature [ 13 ]. In this study, root activity was significantly higher under the 25–185 mg·plant⁻ 1 treatments than in the control, reaching its maximum at 105 mg·plant⁻ 1 . This indicates that moderate K supply effectively maintains root metabolic activity, providing driving force for nutrient and water uptake while establishing a physiological foundation for seedlings to cope with autumn environmental changes. Soluble protein not only serves as an important form of nitrogen storage but also participates in osmotic regulation and stress response processes. Its accumulation helps maintain cell turgor and protect enzyme activities, thereby improving seedling cold tolerance and stress resistance [ 28 , 57 ]. Our study showed that leaf soluble protein content was significantly higher under all K treatments (25–225 mg·plant⁻ 1 ) than in the control, with the highest value observed at 105 mg·plant⁻ 1 , representing a 72.19% increase over the control. This substantial increase may be partially attributed to the low baseline effect caused by suppressed protein synthesis in K-deficient control plants, and also reflects the important role of K in activating key enzymes involved in nitrogen assimilation and protein synthesis [ 3 ]. Similar substantial increases have been observed in other woody species; for example, Ullah et al. [ 58 ] reported that autumn K application significantly increased leaf soluble protein content by 65%–80% in P. chinensis seedlings [ 58 ]. Non-structural carbohydrates (NSC) are the main storage form of photosynthetic products in plants. Soluble sugars, as osmotic regulators, can lower the freezing point of cells and prevent membrane system damage under low-temperature stress; starch can be rapidly broken down into soluble sugars when needed, providing energy for respiratory metabolism under stress conditions [ 40 , 44 , 51 ]. In this study, soluble sugar content was significantly higher under the 65–225 mg·plant⁻ 1 treatments than in the control, with no significant difference between the 105 and 145 mg·plant⁻ 1 treatments; soluble starch content was significantly higher under all K treatments (25–225 mg·plant⁻ 1 ) than in the control, reaching its maximum at 105 mg·plant⁻ 1 . These results indicate that moderate K supply promotes leaf NSC accumulation, providing sufficient energy and carbon skeletons for seedling growth and metabolism. This promoting effect is consistent with the role of K in activating enzymes involved in sugar and starch metabolism [ 35 , 38 , 72 ], although direct measurements of enzyme activities require further investigation. The accumulation of NSC further reflects enhanced seedling stress resistance, although stress resistance-related indicators need to be further measured. Lignin and cellulose are major components of the cell wall, and their deposition directly affects stem mechanical strength and lodging resistance. Additionally, the formation of lignified tissues is closely related to cold tolerance—tissues with higher lignification have thicker cell walls and lower water content, effectively resisting cell damage caused by low temperature [ 35 , 38 , 70 ]. In this study, a moderate to high potassium supply (65–185 mg·plant⁻ 1 ) facilitated lignin accumulation, whereas a higher potassium supply (145–225 mg·plant⁻ 1 ) promoted cellulose accumulation. This suggests that an adequate potassium supply contributes to enhancing stem structural strength and stress resistance. A similar trend was also observed in P. chinensis seedlings by Mo et al. [ 73 ]. However, under K treatments, lignin and cellulose contents in stems of T. odorum seedlings exhibited different accumulation patterns. Lignin content was significantly higher under the 25–185 mg·plant⁻ 1 treatments than in the control, while cellulose content showed a contrasting pattern: significantly higher under the 145–225 mg·plant⁻ 1 treatments and significantly lower under the 25–105 mg·plant⁻ 1 treatments compared to the control (Fig. 2 ). This divergent response may be explained by carbon allocation prioritizing lignin biosynthesis over cellulose synthesis under moderate K limitation (25–105 mg·plant⁻ 1 ) as a resource-conserving strategy to maintain vascular integrity with lower carbohydrate investment. Compared to cellulose, lignin deposition requires less carbohydrate mass per unit of structural reinforcement. Similar trade-offs between lignin and cellulose under nutrient limitation have been observed in other woody species [ 35 , 37 , 38 ]. Under higher K supply (145–185 mg·plant⁻ 1 ), both lignin and cellulose increased, suggesting that adequate K availability may alleviate carbon limitation and support balanced secondary wall deposition, thereby better enhancing stem mechanical strength and stress resistance. However, under the highest K treatment (225 mg·plant⁻ 1 ), lignin content showed no significant difference from the control, and cellulose content declined, possibly reflecting ionic stress or metabolic disruption associated with K excess [ 17 , 31 ]. These interpretations remain speculative, and the underlying regulatory mechanisms require further elucidation. Taken together, moderate K supply (65–105 mg·plant⁻ 1 ) contributes to improved carbon metabolism, structural strength, and stress adaptation potential of T. odorum seedlings by enhancing root activity, benefitting leaf NSC and soluble protein accumulation, and optimizing stem lignin accumulation. The coordination of these physiological responses provides important clues for understanding the regulatory role of K in autumn seedling acclimation, although the functional significance for overwintering survival and field stress resistance requires direct validation. Integrated relationships among nutrients, carbohydrates, and growth This study revealed the relationships among growth, physiological, and nutrient traits in T. odorum seedlings under potassium supply through multivariate analyses. Correlation analysis demonstrated strong positive associations between growth parameters and both physiological indicators and nutrient accumulation (Fig. 5 a), indicating that seedling growth was highly synchronized with physiological status and nutrient conditions under K treatments. Potassium, as an essential macronutrient for plant growth and development, participates in various biochemical processes including protein synthesis, carbohydrate metabolism, and enzyme activation [ 30 ]. In this study, RDA further identified starch (ST), total nitrogen (TN), and soluble protein (SP) as the key factors driving growth variation (Fig. 5 b, indicating their central roles in K-mediated growth regulation. Starch serves as the primary carbon reserve providing energy for growth; TN accumulation reflects nitrogen assimilation capacity, directly influencing protein synthesis and metabolic activity; and soluble protein functions in both nitrogen storage and physiological regulation. Studies have shown that potassium synergistically optimizes nitrogen-potassium balance by regulating the expression of transporters involved in nitrogen uptake and assimilation (such as NRTs and HAKs/KUPs, thereby enhancing photosynthetic nitrogen use efficiency and carbon assimilation capacity [ 36 ]. The synergistic enhancement of these three factors constitutes the physiological basis for K-promoted growth. PLS-SEM was employed to construct hypothesized pathways linking K supply to seedling growth (Fig. 5 c). The model indicates a significant positive regulatory relationship between potassium supply and nutrient (N, P, K) accumulation. Nutrient accumulation, in turn, positively regulated the content of soluble protein, non-structural carbohydrates (NSCs), and lignin, ultimately influencing seedling growth and quality. This finding aligns with the multifaceted roles of potassium in maintaining ion homeostasis, regulating osmotic balance, and functioning as a signaling molecule in stress responses [ 21 , 63 ]. Research indicates that potassium can trigger metabolic switches by modulating cytosolic K⁺ concentrations, influencing processes such as autophagy and programmed cell death, thereby coordinating plant growth and development with stress adaptation [ 34 ]. It should be emphasized that PLS-SEM results reflect statistical associations consistent with the theoretical framework rather than conclusive evidence of causation. This model should be viewed as a physiological hypothesis regarding K regulatory pathways, requiring further validation through molecular and physiological experiments. The RDA ordination also showed that the 105 and 145 mg·plant⁻ 1 treatments were positioned closer to variables associated with growth, nutrients, and carbohydrates in the ordination space (Fig. 5 b), further confirming the physiological suitability of this concentration range for autumn growth of T. odorum seedlings. Potassium deficiency reduces photosynthetic efficiency and assimilate utilization, leading to leaf necrosis and growth restriction [ 2 ], while excessive potassium may cause ionic imbalance and nutrient antagonism—consistent with the growth inhibition observed under low and high K treatments in this study. Collectively, the multivariate analyses demonstrated that moderate potassium supply (65–105 mg·plant⁻ 1 ) has a positive effect on growth and physiological integration in T. odorum seedlings through coordinated regulation of nutrient accumulation and carbon metabolites, with 105 mg·plant⁻ 1 identified as the optimal treatment for overall performance. Limitations and future directions This study investigated the effects of autumn potassium supply on the growth, physiological traits, and nutrient characteristics of T. odorum seedlings, explored the relationships among these indicators, and identified the optimal potassium application rate. The findings provide a theoretical basis for optimizing seedling nutrient management and improving nursery stock quality. However, several limitations should be acknowledged. First, the proposed regulatory pathways are inferred from physiological responses and literature evidence rather than direct experimental validation; further studies incorporating targeted assays are needed to verify these hypotheses. Second, while PLS-SEM elucidates the strength and directionality of variable relationships, it cannot establish definitive causality; the path model should therefore be regarded as a statistically supported hypothesis rather than a confirmed causal network. Third, the N:P threshold values (14 and 16) employed in this study were originally developed for natural vegetation, and their applicability to fertilized nursery seedlings remains uncertain; thus, stoichiometric interpretations should be considered indicative rather than conclusive. Fourth, although observed changes in traits associated with overwintering preparedness—such as NSC accumulation and lignification—are consistent with acclimation processes, direct evidence linking these adjustments to improved overwintering survival under field conditions is lacking. As this study was conducted during a single autumn season under controlled nursery conditions, the functional significance of these physiological responses warrants further investigation. Future research should incorporate overwintering survival trials, cold tolerance assessments, and post-transplant field evaluations to determine whether optimal potassium supply enhances seedling resilience and long-term growth performance. Additionally, given the species-specific nature of these findings, comparative studies across multiple evergreen species are recommended to assess the broader applicability of the observed response patterns. Conclusion This study demonstrates that autumn potassium supply in T. odorum seedlings is associated with concentration-dependent changes in growth, nutrient, carbohydrate accumulation, and lignification. The optimal K rate of 105 mg·plant⁻ 1 was consistently associated with the most favorable outcomes across multiple trait categories, including enhanced biomass, balanced nutrient stoichiometry, increased accumulation of non-structural carbohydrates (NSC) and soluble protein, and improved lignification. These coordinated adjustments in nutrient status and carbohydrate accumulation have potential implications for overwintering preparedness. Multivariate analyses revealed that starch, total nitrogen, and soluble protein were the traits most strongly associated with growth variation. PLS-SEM results supported a model in which K supply influences growth both directly and indirectly through its effects on nutrient and carbohydrate status. These findings provide species-specific knowledge for autumn nursery management of T. odorum and establish a physiological basis for producing high-quality seedlings. The optimal K rate of 105 mg·plant⁻ 1 offers practical guidance for nutrient management in this species. However, direct validation of overwintering benefits under field conditions is needed. The results highlight the importance of optimizing K nutrition during the autumn nursery phase as a potential strategy to enhance seedling quality, while also underscoring the need for cautious interpretation of correlational data and the value of future mechanistic and field-based studies. Acknowledgements This work was completed with funding support, and we sincerely thank the co-workers of our research group for their help in the process of pot experiment. Authors’ contributions **Wen Gan:** Writing—original draft & editing, Writing- original draft, Visualization, Data curation. **Xinyu Deng:** Writing—original draft, Investigation, Data curation. **Yujun Liu:** Project administration, Investigation. **Li Liu 2:** Project administration, Investigation. **Mei Yang:** Project administration, Formal analysis, Conceptualization. **Yuanyuan Xu:** Writing—original draft, Project administration, Conceptualization. Funding This research was supported by Guangxi Forestry Science and Technology Program [GuiLin Scientific Research [2022ZC] No. 71 and the Guangxi Tree Improved Variety Project GuiLinChangFa [2025] No. 10. Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Declarations Ethics approval and consent to participate No wild individuals were collected for this study. The seedings of Tsoongiodendron odorum used in this study were from Dingjiao Village, Delong Township, Napo County, Baise City, Guangxi Province, China, which were legally obtained with the permission of Napo County Forestry Bureau. The voucher specimen of Tsoongiodendron odorum used in this study has been deposited in the Guangxi University Forest Plant Herbarium, the accession number 20221015, and species identification was confirmed by Rongyan Deng. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Akhtyamova Z, Martynenko E, Arkhipova T, Seldimirova O, Galin I, Belimov A, et al. Influence of plant growth-promoting rhizobacteria on the formation of apoplastic barriers and uptake of water and potassium by wheat plants. Microorganisms. 2023;11(5):1227. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 2. Anil Kumar S, Kaniganti S, Hima Kumari P, et al. Functional and biotechnological cues of potassium homeostasis for stress tolerance and plant development. Biotechnol Genet Eng Rev. 2024;40(4):3527–70. 10.1080/02648725.2022.2143317. [ DOI ] [ PubMed ] 3. Berg WK, Brouder SM, Cunningham SM, Volenec JJ. Potassium and Phosphorus Fertilizer Impacts on Alfalfa Taproot Carbon and Nitrogen Reserve Accumulation and Use During Fall Acclimation and Initial Growth in Spring. Front Plant Sci. 2021;12(2021):715936. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 4. Britto DT, Kronzucker HJ. Futile cycling at the plasma membrane: a hallmark of low-affinity nutrient transport. Trends Plant Sci. 2006;11(11):529–34. [ DOI ] [ PubMed ] [ Google Scholar ] 5. Cakmak I. The role of potassium in alleviating detrimental effects of abiotic stresses in plants. J Plant Nutr Soil Sci. 2005;168(4):521–30. [ Google Scholar ] 6. Chapin FS, Schulze E-D, Mooney HA. The Ecology and Economics of Storage in Plants. Annu Rev Ecol Syst. 1990;21(1990):423–47. [ Google Scholar ] 7. Chow PS, Landhäusser SM. A method for routine measurements of total sugar and starch content in woody plant tissues. Tree Physiol. 2004;24(10):1129–36. [ DOI ] [ PubMed ] [ Google Scholar ] 8. Clemensson-Lindell A. Triphenyltetrazolium chloride as an indicator of fine-root vitality and environmental stress in coniferous forest stands: applications and limitations. Plant Soil. 1994;159(2):297–300. [ Google Scholar ] 9. Cuesta B, Villar-Salvador P, Puértolas J, Jacobs DF, Rey Benayas JM. Why do large, nitrogen rich seedlings better resist stressful transplanting conditions? A physiological analysis in two functionally contrasting Mediterranean forest species. For Ecol Manage. 2010;260(1):71–8. [ Google Scholar ] 10. Dickson A, Leaf AL, Hosner JF. Quality appraisal of white spruce and white pine seedling stock in nurseries. For Chron. 1960;36(1):10–3. [ Google Scholar ] 11. Dietze MC, Sala A, Carbone MS, Czimczik CI, Mantooth JA, Richardson AD, et al. Nonstructural Carbon in Woody Plants. Annu Rev Plant Biol. 2014;65(2014):667–87. [ DOI ] [ PubMed ] [ Google Scholar ] 12. Chirino E, Hernández AV, Matos EI, Vallejo VR. Effects of a deep container on morpho-functional characteristics and root colonization in Quercus suber L. seedlings for reforestation in Mediterranean climate. For Ecol Manage. 2008;256(4):779–85. [ Google Scholar ] 13. Eissenstat DM, Wells CE, Yanai RD, Whitbeck JL. Building roots in a changing environment: implications for root longevity. New Phytol. 2000;147(1):33–42. [ Google Scholar ] 14. Engels C, Kirkby E, White P. Chapter 5 - Mineral Nutrition, Yield and Source–Sink Relationships. Marschner's Mineral Nutrition of Higher Plants (Third Edition). P. Marschner. San Diego, Academic Press. 2012:85–133. 15. Gao J. Experimental guidance for plant physiology. Beijing: Higher Education Press; 2006. [ Google Scholar ] 16. Grintzalis K, Georgiou CD, Schneider Y-J. An accurate and sensitive Coomassie Brilliant Blue G-250-based assay for protein determination. Anal Biochem. 2015;480(2015):28–30. [ DOI ] [ PubMed ] [ Google Scholar ] 17. Gu Y, Guo D, Li C, Zheng C, Li X, He F, et al. Optimising potassium levels improved the lodging resistance index and soybean yield in maize-soybean intercropping by enhanced stem diameter and lignin synthesis enzyme activity. Agro Crop Sci. 2025;211(2):e70036. [ Google Scholar ] 18. Guolei L, Yong L, Yan Z. Review on advance in study of fall fertilization regulating seedling quality. Sci Silvae Sin. 2011;47(11):166–71. [ Google Scholar ] 19. Hao D, Li X, Kong W, Chen R, Liu J, Guo H, et al. Phosphorylation regulation of nitrogen, phosphorus, and potassium uptake systems in plants. Crop J. 2023;11(4):1034–47. [ Google Scholar ] 20. Henseler J, Ringle CM, Sarstedt M. Testing measurement invariance of composites using partial least squares. Int Mark Rev. 2016;33(3):405–31. [ Google Scholar ] 21. Hermans C, Hammond JP, White PJ, Verbruggen N. How do plants respond to nutrient shortage by biomass allocation? Trends Plant Sci. 2006;11(12):610–7. [ DOI ] [ PubMed ] [ Google Scholar ] 22. Hoopen Ft, Cuin TA, Pedas P, Hegelund JN, Shabala S, Schjoerring JK, et al. Competition between uptake of ammonium and potassium in barley and Arabidopsis roots: molecular mechanisms and physiological consequences. J Exp Bot. 2010;61(9):2303–15. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 23. Hu J, Yu H, Li Y, Wang J, Lv T, Liu C, et al. Variation in resource allocation strategies and environmental driving factors for different life-forms of aquatic plants in cold temperate zones. J Ecol. 2021;109(8):3046–59. [ Google Scholar ] 24. Hu Lt, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling. 1999;6(1):1–55. [ Google Scholar ] 25. Huang X, Wu J, Feng D, Sun X. Effects of potassium deficient stress on growth and physiological characteristics of walnut seedlings. J Beijing For Univ. 2022;44(8):23–30. [ Google Scholar ] 26. Huang Y, Chen ML, Zhou JH, Fu YL, Wei PL. Hot compression of calcium chloride and sodium carbonate modifies wood for Tsoongiodendron odorum . Forests. 2024;15(1):66. [ Google Scholar ] 27. Jakobsen ST. Interaction between plant nutrients: III. antagonism between potassium, magnesium and calcium. Acta Agric Scand Sect B Soil Plant Sci. 1993;43(1):1–5. [ Google Scholar ] 28. Janmohammadi M, Zolla L, Rinalducci S. Low temperature tolerance in plants: Changes at the protein level. Phytochemistry. 2015;117(2015):76–89. [ DOI ] [ PubMed ] [ Google Scholar ] 29. Jiaying M, Tingting C, Jie L, Weimeng F, Baohua F, Guangyan L, et al. Functions of nitrogen, phosphorus and potassium in energy status and their influences on rice growth and development. Rice Sci. 2022;29(2):166–78. [ Google Scholar ] 30. Johnson R, Vishwakarma K, Hossen MS, Kumar V, Shackira AM, Puthur JT, et al. Potassium in plants: Growth regulation, signaling, and environmental stress tolerance. Plant Physiol Biochem. 2022;172(2022):56–69. [ DOI ] [ PubMed ] [ Google Scholar ] 31. Kamran M, Cui W, Ahmad I, Meng X, Zhang X, Su W, et al. Effect of paclobutrazol, a potential growth regulator on stalk mechanical strength, lignin accumulation and its relation with lodging resistance of maize. Plant Growth Regul. 2018;84(2):317–32. [ Google Scholar ] 32. Keke YE, Qingmei LI, Yan ZHU, Jingjing YAN, Zihan ZHANG, Sai FENG, et al. Responses of growth and afforestation performance of Pinus tabuliformis container and bareroot seedlings to fall fertilization. Journal of Nanjing Forestry University (Natural Sciences Edition). 2023;47(01):136–44. [ Google Scholar ] 33. Koerselman W, Meuleman AFM. The vegetation N:P ratio: a new tool to detect the nature of nutrient limitation. J Appl Ecol. 1996;33(1996):1441–50. [ Google Scholar ] 34. Kumar P, Kumar T, Singh S, Tuteja N, Prasad R, Singh J. Potassium: a key modulator for cell homeostasis. J Biotechnol. 2020;324(2020):198–210. [ DOI ] [ PubMed ] [ Google Scholar ] 35. Li Q, Fu C, Liang C, Ni X, Zhao X, Chen M, et al. Crop lodging and the roles of lignin, cellulose, and hemicellulose in lodging resistance. Agron. 2022;12(8):1795. [ Google Scholar ] 36. Li W, Xu G, Alli A, Yu L. Plant HAK/KUP/KT K+ transporters: Function and regulation. Semin Cell Dev Biol. 2018;74(2018):133–41. [ DOI ] [ PubMed ] [ Google Scholar ] 37. Li X, Gao Y, Cui Z, Zhang T, Chen S, Xiang S, et al. Optimized nitrogen and potassium fertilizers application increases stem lodging resistance and grain yield of oil flax by enhancing lignin biosynthesis. J Integr Agric. 2024. 10.1016/j.jia.2024.09.006. [ Google Scholar ] 38. Li Y, Yin M, Li L, Zheng J, Yuan X, Wen Y. Optimized potassium application rate increases foxtail millet grain yield by improving photosynthetic carbohydrate metabolism. Front Plant Sci. 2022;13(2022):1–16. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 39. Lin Z, Jiajia F, Chaoran M, Li D, won BN, Weidong G, et al. Determination of the lignin content of flax fiber with the acetyl bromide-ultraviolet visible spectrophotometry method. Text Res J. 2023;93(11–12):2633–45. [ Google Scholar ] 40. Liu Q, Huang Z, Wang Z, Chen Y, Wen Z, Liu B, et al. Responses of leaf morphology, NSCs contents and C:N:P stoichiometry of Cunninghamia lanceolata and Schima superba to shading. BMC Plant Biol. 2020;20(1):354. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 41. Liu X, Fu Y. Anatomy and basic density of Tsoongiodendron odorum . J Zhejiang Univ. 2013;30(5):769–76. [ Google Scholar ] 42. Lü N, Zhu H, Yang P, Xu S, Huang J, Cao G, et al. Effects of different light substrates on the growth and nutrient accumulation of Cunninghamia lanceolata container seedlings. J Northwest For Univ. 2024;39(2):60–9. [ Google Scholar ] 43. Luo Y, Peng Q, Li K, Gong Y, Liu Y, Han W. Patterns of nitrogen and phosphorus stoichiometry among leaf, stem and root of desert plants and responses to climate and soil factors in Xinjiang, China. CATENA. 2021;199(2021):105100. [ Google Scholar ] 44. Mo Q, Chen Y, Yu S, Fan Y, Peng Z, Wang W, et al. Leaf nonstructural carbohydrate concentrations of understory woody species regulated by soil phosphorus availability in a tropical forest. Ecol Evol. 2020;10(15):8429–38. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 45. Mostofa MG, Rahman MM, Ghosh TK, Kabir AH, Abdelrahman M, Rahman Khan MA, et al. Potassium in plant physiological adaptation to abiotic stresses. Plant Physiol Biochem. 2022;186(2022):279–89. [ DOI ] [ PubMed ] [ Google Scholar ] 46. Olde Venterink H, Wassen MJ, Verkroost AWM, De Ruiter PC. Species richness–productivity patterns differ between N-, P-, and K- limited wetlands. Ecology. 2003;84(8):2191–9. [ Google Scholar ] 47. Pessoa AC, Balbinot LC, Balbinot LC, Walter LS, Kratz D, Auler AC, et al. Bentonite as substrate conditioner under different water regimes – A Eucalyptus dunnii seedling assay. For Ecol Manage. 2024;574(2024):122352. [ Google Scholar ] 48. Polara KB, Sardhara R, Parmar KB, Babariya NB, Patel K. Effect of potassium on inflow rate of N, P, K, Ca, S, Fe, Zn and Mn at various growth stages of wheat. Asian J Soil Sci. 2009;4(2):228–35. [ Google Scholar ] 49. Qin H, Zhang X, Tian G, Liu C, Xing Y, Feng Z, et al. Magnesium alleviates growth inhibition under low potassium by enhancing photosynthesis and carbon-nitrogen metabolism in apple plants. Plant Physiol Biochem. 2024;214(2024):108875. [ DOI ] [ PubMed ] [ Google Scholar ] 50. Ritchie GA, Dunlap JR. Root growth potential: its development and expression in forest tree seedlings. N Z J For Sci. 1980;1980(10):218–48. [ Google Scholar ] 51. Sami F, Yusuf M, Faizan M, Faraz A, Hayat S. Role of sugars under abiotic stress. Plant Physiol Biochem. 2016;109(2016):54–61. [ DOI ] [ PubMed ] [ Google Scholar ] 52. Sardans J, Peñuelas J. Potassium control of plant functions: ecological and agricultural implications. Plants. 2021;10(2):419. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 53. Scherer HW, Mackown CT, Leggett JE. Potassium-ammonium uptake interactions in tobacco seedlings. J Exp Bot. 1984;35(7):1060–70. [ Google Scholar ] 54. Soumare A, Sarr D, DiÉDhiou AG. Potassium sources, microorganisms and plant nutrition: challenges and future research directions. Pedosphere. 2023;33(1):105–15. [ Google Scholar ] 55. Sperling O, Perry A, Ben-Gal A, Yermiyahu U, Hochberg U. Potassium deficiency reduces grapevine transpiration through decreased leaf area and stomatal conductance. Plant Physiol Biochem. 2024;208(2024):108534. [ DOI ] [ PubMed ] [ Google Scholar ] 56. Tang X, Kang Y, Liang X, Ma D, Wang L. Effects of N,P and K proportional fertilization on the physiological and photosynthetic characteristics of Tsoongiodendron odorum seedlings. J Northwest For Univ. 2022;37(4):37–42. [ Google Scholar ] 57. Tcherkez G, Carroll A, Abadie C, Mainguet S, Davanture M, Zivy M. Protein synthesis increases with photosynthesis via the stimulation of translation initiation. Plant Sci. 2020;291(2020):110352. [ DOI ] [ PubMed ] [ Google Scholar ] 58. Ullah S, Liu F, Xie L, Liao S, Li W, Ali I, et al. Autumnal potassium induced modulations in plant osmoprotectant substances, nutrient stoichiometry and precision sustainable seedling cultivation in Parashorea chinensis . Forests. 2024;15(2):310. [ Google Scholar ] 59. Villar-Salvador P, Uscola M, Jacobs DF. The role of stored carbohydrates and nitrogen in the growth and stress tolerance of planted forest trees. New For. 2015;46(5):813–39. [ Google Scholar ] 60. Wang M, Liu Y, Li G, Peng Y, Liu C, Zhao J, et al. Effects of autum fertilization on quality, field performance and nutrient resorption of Populus tomentosa seedling. Sci Silvae Sin. 2021;57:51–60. [ Google Scholar ] 61. Wang X, Liu X, Yuan Y, Mo W, Chen K, Yi Z, et al. Relationships between non-structural carbohydrates and root economic space in woody plants. Plant Soil. 2025;514(1):1111–25. [ Google Scholar ] 62. Wang YP, Li HH, Yang ZJ, Liu BY, Liu YJ, Zhong YD. Genotyping-by-sequencing study of the genetic diversity and population structure of the endangered plant Tsoongiodendron odorum Chun in China. Forests. 2024;15(6):910. [ Google Scholar ] 63. Wegner LH, Pottosin I, Dreyer I, Shabala S. Potassium homeostasis and signalling: from the whole plant to the subcellular level. Quant Plant Biol. 2025;6(2025):e13. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 64. Xu X, Du X, Wang F, Sha J, Chen Q, Tian G, et al. Effects of Potassium Levels on Plant Growth, Accumulation and Distribution of Carbon, and Nitrate Metabolism in Apple Dwarf Rootstock Seedlings. Front Plant Sci. 2020;11(2020):904. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 65. Yan Z, Tian D, Han W, Tang Z, Fang J. An assessment on the uncertainty of the nitrogen to phosphorus ratio as a threshold for nutrient limitation in plants. Ann Bot. 2017;120(6):937–42. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 66. Yang J, Cai L, Liu D, Chen G, Gratzfeld J, Sun W. China’s conservation program on Plant Species with Extremely Small Populations (PSESP): Progress and perspectives. Biol Cons. 2020;244(2020):108535. [ Google Scholar ] 67. Yang R, Huang X, Chen Y, Li Y, Xu Y, Yang M. Phenotypic trait variations of Michelia odora from different provenances at the seedling stage and their correlations with geographical-climate factors. J Central South Univ For Technol. 2026;46(4):1–11. [ Google Scholar ] 68. Yao X, Li Y, Liao L, Sun G, Wang H, Ye S. Enhancement of nutrient absorption and interspecific nitrogen transfer in a Eucalyptus urophylla × eucalyptus grandis and Dalbergia odorifera mixed plantation. For Ecol Manage. 2019;449(2019):117465. [ Google Scholar ] 69. Yu Z, Cheng H, Liu L, Xu Y, Yang M, Liu Y. Effects of different fertilization season and nutrient on the growth and physiological characteristics of Michelia odora at seedling stage. J Southwest For Univ. 2026;46(01):14–21. [ Google Scholar ] 70. Zeng Y, Himmel ME, Ding S-Y. Visualizing chemical functionality in plant cell walls. Biotechnol Biofuels. 2017;10(1):263. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 71. Zhang S, Wang H, Fan J, Zhang F, Cheng M, Yang L, et al. Quantifying source-sink relationships of drip-fertigated potato under various water and potassium supplies. Field Crop Res. 2022;285(2022):108604. [ Google Scholar ] 72. Zhao S, Zhang Y, Tan M, Zhang C, Jiao J, Wu P, et al. NnNF-YB1 induced by the potassium fertilizer enhances starch synthesis in rhizomes of Nelumbo nucifera. Ind Crops Prod. 2023;203(2023):117197. [ Google Scholar ] 73. Mo Z, Ma D, Xie Le, Li T, Yuanyuan Xu, Yang M, et al. Dose effects of potassium application in autumn on seedling growth, lignification and nutrient accumulation of two Parashorea chinensis provenances. J Plant Nutr Fertil. 2025;31(08):1644–59. [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. 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