A method for screening and grading of quality grading index of cymbidium seedlings

Abstract

This invention provides a method for screening and grading quality indicators for Rhododendron seedlings, thereby determining grading standards and classifying seedling quality. Through systematic testing of various quality indicators of one-year-old Rhododendron seedlings, and by comprehensively applying multivariate statistical analysis, principal component analysis was used to extract the three key indicators with the highest contribution, serving as the main basis for seedling grading. Combined with K-means clustering algorithm, seedlings were scientifically divided into four quality grades based on these core indicators. Verification has shown that these grading indicators can effectively reflect the growth of Rhododendron seedlings after transplanting, providing a scientific basis for quality control of Rhododendron seedlings in production.

Description

Technical Field

[0001] This invention relates to the field of quality control technology for Chinese medicinal herb seedlings, and in particular to a method for screening and grading quality grading indicators for Rhododendron seedlings. Background Technology

[0002] Azalea ( Cremastra appendiculata (D. Don) Makino is a perennial terrestrial herb belonging to the genus *D.* of the Orchidaceae family (Editorial Committee of Flora of China, Chinese Academy of Sciences. Flora of China [M]. Beijing: Science Press, 1999, 18: 165). Its dried pseudobulbs are used medicinally, possessing properties such as clearing heat and detoxifying, resolving phlegm and dissipating nodules. It is used to treat carbuncles, boils, scrofula, and other skin abscesses (National Pharmacopoeia Commission. Pharmacopoeia of the People's Republic of China, Part I, 2020 Edition [M]. Beijing: China Medical Science and Technology Press, 2020: 34). Multiple active ingredients in the pseudobulbs of *D.* have been shown to have effects such as lowering blood pressure, lowering blood sugar, and anticancer properties (Chen Shi, Zhao Yue, Wang Zhen, et al. Research progress on the pharmacological effects and clinical applications of *Cremastra appendiculata* [J]. Chinese Journal of Traditional Chinese Medicine, 2023, 41(06): 247-250). The developed traditional Chinese medicine formulas, including Compound Cidan Capsules, Aiyu Capsules, Toujie Quwen Granules, Zijin Pills, and Zhou's Huisheng Pills, have shown significant efficacy in the clinical treatment of diseases. However, with the continuous increase in market demand, uncontrolled harvesting coupled with its own reproductive difficulties has led to the near depletion of wild Rhododendron resources, resulting in its listing as a Class II rare and endangered protected plant in my country.

[0003] Traditional cultivation of Rhododendron relies on division propagation using pseudobulbs, but the propagation coefficient is extremely low. Tissue culture propagation is technically cumbersome and costly. With the screening and application of germination-promoting fungi, fungal seed dressing and direct seeding technology is now widely used to produce Rhododendron seedlings. However, most seedlings are produced and sold by farmers themselves, lacking objective, scientific, and systematic seedling quality evaluation indicators and grading standards. This results in inconsistent seedling quality, seriously affecting transplant survival rate and the yield and quality of medicinal materials, making it difficult to guarantee the sustainable industrial development of this rare medicinal material. Therefore, it is urgent to screen suitable grading indicators for Rhododendron seedling quality and formulate seedling quality grading standards. Summary of the Invention

[0004] To address the above problems, the purpose of this invention is to provide a method for screening and grading quality indicators for Rhododendron seedlings. This method can screen suitable grading indicators for Rhododendron seedlings and formulate seedling quality grading standards. This provides an important foundation for ensuring the yield, quality, and safety of medicinal materials.

[0005] The objective of this invention can be achieved through the following technical solutions: This invention provides a method for screening and grading quality indicators for Rhododendron seedlings, comprising the following steps: One-year-old seedlings of suitable age were taken from a rhododendron seedling production base with mature fungal seed dressing and direct seeding technology. Seedling quality indicators were tested and statistically analyzed. The seedling quality indicators included pseudobulb diameter, number of fibrous roots, length of fibrous roots, number of leaves, leaf length, leaf width, leaf area, petiole length, petiole thickness, relative chlorophyll content, and plant fresh weight. The obtained raw data were recorded as T0. Descriptive statistics are performed on the original data T0; Correlation analysis is performed on the original data T0. Based on the correlation coefficient, a group of strongly correlated indicators is selected, and redundant indicators with collinearity and indicators with weak correlation are removed. The original data of the core indicators obtained are denoted as T1. Principal component analysis was performed on the original data T1 of the core indicators, and the three key seedling quality indicators with the highest contribution were extracted.

[0006] In one embodiment, the screening method further includes: The original data of the three key seedling quality indicators with the highest contribution extracted by the principal component analysis are denoted as T2. K-means cluster analysis is performed on the original data T2, and the threshold of the graded indicator level is determined by referring to the obtained K-means.

[0007] In one embodiment, the three key seedling quality indicators with the highest contribution under principal component analysis include pseudobulb diameter, plant fresh weight, and leaf area.

[0008] In one embodiment, the K-mean of the pseudobulb diameter includes 0.64, 1.53, and 2.35, the K-mean of the plant fresh weight includes 2.25, 6.08, and 11.89, and the K-mean of the leaf area includes 25.92, 53.91, and 80.72.

[0009] In one embodiment, the descriptive statistics are performed using SPSS software.

[0010] In one embodiment, the software used for correlation analysis is SPSS.

[0011] In one embodiment, the software used for principal component analysis is SPSS.

[0012] In one embodiment, the cluster analysis was performed using SPSS software.

[0013] In one embodiment, descriptive statistics include calculating the maximum, minimum, range, mean, standard deviation, and coefficient of variation of the seedling quality indicators.

[0014] A method for screening and grading quality indicators of Rhododendron seedlings, comprising: measuring the quality indicators of Rhododendron seedlings and grading them according to the results, wherein the quality indicators are obtained by screening using the method described above.

[0015] In one embodiment, the grading criteria include: The pseudobulb diameter is greater than or equal to 2.30 cm, the fresh weight of the plant is greater than or equal to 12 g, and the leaf area is greater than or equal to 80 cm². 2 Then it is a Grade I seedling; The pseudobulb diameter is greater than or equal to 1.50 cm and less than 2.30 cm, the fresh weight of the plant is greater than or equal to 6 g and less than 12 g, and the leaf area is greater than or equal to 50 cm². 2 and less than 80 cm 2 Then it is a Grade II seedling; The pseudobulb diameter is greater than or equal to 0.6 cm and less than 1.50 cm, the fresh weight of the plant is greater than or equal to 2 g and less than 6 g, and the leaf area is greater than or equal to 25 cm². 2 and less than 50 cm 2 Then it is a Grade III seedling; The pseudobulb diameter is less than 0.6 cm, the fresh weight of the plant is less than 2 g, and the leaf area is less than 25 cm². 2 Then it is a Grade IV seedling; Among the pseudobulb diameter, number of fibrous roots, and number of leaves, pseudobulb diameter is the first key grading indicator, plant fresh weight is the second key grading indicator, and leaf area is the third key grading indicator.

[0016] Compared with the prior art, the present invention has the following beneficial effects: Based on their research on Rhododendron azaleas, the inventors analyzed seedling quality indicators using various statistical methods and selected the three key seedling quality indicators with the highest contribution (cumulative contribution rate exceeding 70%) under principal component analysis as grading indicators. Verification showed that the test data corresponding to these grading indicators can effectively reflect the growth of Rhododendron azalea seedlings after transplanting, providing a scientific basis for selecting high-quality seedlings in the standardized and large-scale artificial cultivation of Rhododendron azaleas. Attached Figure Description

[0017] Figure 1 This is a sampling point for azalea seedlings; Figure 2 Samples of Rhododendron seedlings of four grades (where A, B, C, and D are grade 1, grade 2, grade 3, and grade 4 seedlings, respectively, with a bar of 5 cm). Detailed Implementation

[0018] To more clearly illustrate the present invention, a more detailed description will be provided below.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this specification is for the purpose of describing particular embodiments or examples only and is not intended to limit the invention. The optional range of the term "and / or" as used herein includes any one of two or more of the related listed items, as well as any and all combinations of the related listed items, including any two related listed items, any more related listed items, or a combination of all related listed items.

[0020] Seedlings of Chinese medicinal herbs are the most basic and important production materials for medicinal herb production. High-quality seedlings are a prerequisite for improving the yield and quality of medicinal herbs (Li Longyun, Peng Rui, Li Hongli, et al. Development strategy of seeds and seedlings of Chinese medicinal herbs [J]. Chinese Journal of Traditional Chinese Medicine, 2010, 35(2): 247-252). The formulation of quality standards for seedlings of Chinese medicinal herbs is crucial for the sustainable development of the Chinese medicinal herb industry. The national level has also gradually begun to pay attention to the development of Chinese medicinal herbs (General Office of the State Council. Opinions of the General Office of the State Council on Improving the Quality of Chinese Medicine and Promoting the High-Quality Development of the Chinese Medicine Industry. Guo Ban Fa

[2025] No. 11). Previous studies have focused on the quality grading of Murraya paniculata seedlings (Xie Wenbo, Liao Zhenfeng, Huang Jinpeng, et al. Research on the quality grading of Murraya paniculata seedlings [J]. Molecular Plant Breeding, 2024, 1-7), Citrus aurantium seedlings (Xu Jin, Zhang Ying, Cui Guanglin, et al. Research on the quality grading standards of Citrus aurantium seedlings [J]. Chinese Journal of Traditional Chinese Medicine, 2020, 45(13): 3091-3097), Dictamnus dasycarpus seedlings (Wu Wei, Yin Haibo, Wang Dan, et al. Research on the quality grading standards of Dictamnus dasycarpus seedlings [J]. Seeds, 2023, 42(10): 139-143), and Bletilla striata seedlings (Zhang Zhihui, Wang Li, Wang Jiajin, et al. Research on the quality grading standards of Bletilla striata tissue culture seedlings from Yunnan [J]. Southwest China Journal of Agricultural Sciences, 2017, 30(4): 894-899; Lin Li. Evaluation of Bletilla striata germplasm resources and research on seed and seedling quality standards [D]. Guizhou University, Research was conducted on the quality indicators of Chinese medicinal materials such as Morinda officinalis (application number: CN202110863069.7, Chinese invention patent application) in 2019, and relevant grading standards were formulated.

[0021] However, current research on Rhododendron molle mainly focuses on pharmacological effects (Chen Shi, Zhao Yue, Wang Zhen, et al. Research progress on pharmacological effects and clinical applications of Pseudobulbus Cremastrae [J]. Chinese Journal of Traditional Chinese Medicine, 2023, 41(06): 247-250), tissue culture (Chen Fang, Qin Shunwang, Wang Yuehua, et al. Study on rapid proliferation of Rhododendron molle protocorms [J]. Seeds, 2021, 40(06):141-145), symbiotic screening (Wang Jing, Pan Changneng, Wang Congwei, et al. Promotion effect of Coprinus radiata on Rhododendron molle seed germination [J]. Chinese Medicinal Herbs, 2023, 46(11): 2658-2662), and cultivation (Yang Yuting, Wu Xuesan, Xiong Yongqin, et al. Propagation and cultivation techniques of Rhododendron molle seedlings [J]. Agriculture and Technology, 2025). There are no reports on the screening and grading standards for quality indicators of Rhododendron seedlings in terms of 45(08): 80-83).

[0022] In view of this, this invention conducts relevant experiments on the quality of Rhododendron seedlings. Seedlings were collected from the Rhododendron seedling production base in Dafang County, Bijie City, Guizhou Province, a typical Rhododendron producing area with mature fungal seed dressing and direct seeding technology, a high degree of scale, and strong representativeness. Ten trait indicators, including pseudobulb diameter, number of fibrous roots, and fibrous root length, were measured. Through statistical analysis and combined with actual production, key indicators of seedling quality were screened and seedling quality grading standards were formulated, aiming to provide a scientific basis for the selection of high-quality seedlings in the standardized and large-scale artificial cultivation of Rhododendron.

[0023] On the one hand, the present invention provides a method for screening quality grading indicators for azalea seedlings, the screening method comprising the following steps: One-year-old seedlings of suitable age were taken from a rhododendron seedling production base with mature fungal seed dressing and direct seeding technology. Seedling quality indicators were tested and statistically analyzed. The seedling quality indicators included pseudobulb diameter, number of fibrous roots, length of fibrous roots, number of leaves, leaf length, leaf width, leaf area, petiole length, petiole thickness, relative chlorophyll content, and plant fresh weight. The obtained raw data were recorded as T0. Descriptive statistics are performed on the original data T0; Correlation analysis is performed on the original data T0. Based on the correlation coefficient, a group of strongly correlated indicators is selected, and redundant indicators with collinearity and indicators with weak correlation are removed. The original data of the core indicators obtained are denoted as T1. Principal component analysis was performed on the original data T1 of the strongly correlated indicators, and the three key seedling quality indicators with the highest contribution were extracted.

[0024] In the process of screening suitable quality grading indicators for Rhododendron seedlings using the screening method of this invention, it is not necessary to consume a large sample size (this invention only uses 300 samples) to screen out suitable grading indicators for Rhododendron seedling quality. The obtained grading indicators can well reflect the plant vigor and growth status of Rhododendron seedlings after transplanting. In addition, the grading indicators screened by this invention have simple and fast data acquisition methods (such as pseudobulb diameter and plant fresh weight), low technical difficulty, and are very suitable for front-line production.

[0025] In one example, the filtering method further includes: The original data of the three key seedling quality indicators with the highest contribution under the principal component analysis are denoted as T2. K-means cluster analysis is performed on the original data T2, and the threshold of the graded indicator level is determined by referring to the obtained K-means.

[0026] In one embodiment, the three key seedling quality indicators with the highest contribution under principal component analysis include pseudobulb diameter, plant fresh weight, and leaf area.

[0027] In one embodiment, the K-mean of the pseudobulb diameter includes 0.64, 1.53, and 2.35, the K-mean of the plant fresh weight includes 2.25, 6.08, and 11.89, and the K-mean of the leaf area includes 25.92, 53.91, and 80.72.

[0028] In one embodiment, the descriptive statistics are performed using SPSS software.

[0029] In one embodiment, the software used for correlation analysis is SPSS.

[0030] In one embodiment, the software used for principal component analysis is SPSS.

[0031] In one embodiment, the cluster analysis was performed using SPSS software.

[0032] In one embodiment, descriptive statistics include calculating the maximum, minimum, range, mean, standard deviation, and coefficient of variation of the seedling quality indicators.

[0033] On the other hand, the present invention provides a method for grading the quality of azalea seedlings, the method comprising: measuring the quality indicators of azalea seedlings and grading them according to the results, wherein the quality indicators are obtained by screening using the method described above.

[0034] In one embodiment, the grading criteria include: The pseudobulb diameter is greater than or equal to 2.30 cm, the fresh weight of the plant is greater than or equal to 12 g, and the leaf area is greater than or equal to 80 cm².2 Then it is a Grade I seedling; The pseudobulb diameter is greater than or equal to 1.50 cm and less than 2.30 cm, the fresh weight of the plant is greater than or equal to 6 g and less than 12 g, and the leaf area is greater than or equal to 50 cm². 2 and less than 80 cm 2 Then it is a Grade II seedling; The pseudobulb diameter is greater than or equal to 0.6 cm and less than 1.50 cm, the fresh weight of the plant is greater than or equal to 2 g and less than 6 g, and the leaf area is greater than or equal to 25 cm². 2 and less than 50 cm 2 Then it is a Grade III seedling; The pseudobulb diameter is less than 0.6 cm, the fresh weight of the plant is less than 2 g, and the leaf area is less than 25 cm². 2 Then it is a Grade IV seedling; Among the pseudobulb diameter, plant fresh weight, and leaf area, pseudobulb diameter is the first key grading indicator, plant fresh weight is the second key grading indicator, and leaf area is the third key grading indicator.

[0035] Example 1 1. Materials Starting in early April 2025, the rhododendrons used ( Cremastra appendiculata The (D. Don) Makino seedlings were one-year-old Rhododendron seedlings directly propagated with fungal seed dressing and reaching transplanting age. They were collected from the Rhododendron Seedling Production Base in Shachang Yi Township, Baili Rhododendron Management Area, Bijie City, Guizhou Province (currently a Rhododendron seedling production base with high maturity of fungal seed dressing direct propagation technology, good demonstration effect, large production scale, and strong representativeness). Using a random sampling method, five 1 m × 1 m quadrats were selected from the seedling base, and all seedlings in the quadrats were dug up intact, totaling more than 2,000 plants.

[0036] 2 Methods 2.1 Selection and Quality Indicator Determination of Rhododendron Seedlings One hundred one-year-old Rhododendron seedlings were randomly selected. Ten parameters were measured: pseudobulb diameter, number of fibrous roots, fibrous root length, number of leaves, leaf length, leaf width, leaf area, petiole length, petiole diameter, relative chlorophyll content, and plant fresh weight. The measurements were performed in triplicate. Pseudobulb diameter: This is the maximum diameter of the pseudobulb, measured using vernier calipers.

[0037] Number of fibrous roots: The number of fibrous roots longer than 2 cm that emerge from the base of the pseudobulb.

[0038] Fibrous root length: The longest fibrous root is measured using a ruler.

[0039] Leaf count: Direct observation and counting. Rhododendrons commonly have single leaves, rarely double leaves, and extremely rarely three leaves.

[0040] Leaf length: The length from the unfolded part of the leaf to the tip of the leaf, measured with a ruler.

[0041] Leaf width: Measure the widest part of the leaf at the middle using a ruler.

[0042] Leaf area: The area of ​​30 representative leaves was measured using ImageJ software. A multiple linear regression equation was established between leaf area and leaf length and width: Leaf area = 4.066 * length + 5.946 * width - 35.814, R² 2 =0.949, calculate the leaf area of ​​the remaining samples.

[0043] Petiole length: The length from the tip of the pseudobulb to the base of the leaf, measured with a ruler.

[0044] Petiole diameter: The diameter of the petiole at the middle is measured using a vernier caliper.

[0045] Relative chlorophyll content: The SPAD value of the leaves was measured using a chlorophyll content meter (SPAD-502 Plus) (the average value of 3 measurements was taken).

[0046] Fresh weight of the plant: Wash the pseudobulbs and fibrous roots and dry the surface moisture. Weigh the entire seedling using an electronic balance.

[0047] The measurement results are recorded as raw data.

[0048] 2.2 Rhododendron seedling quality grading method Using SPSS 24.0 statistical analysis software, descriptive statistics and correlation analysis were performed on 11 indicators of Rhododendron seedlings, including pseudobulb diameter, number of fibrous roots, length of fibrous roots, number of leaves, leaf length, leaf width, leaf area, petiole length, petiole diameter, relative chlorophyll content, and plant fresh weight. After removing indicators with weak correlation, such as petiole diameter and relative chlorophyll content, as well as indicators with strong collinearity and redundancy, principal component analysis was performed on the core indicators. K-means cluster analysis was then performed on the extracted principal components. Finally, based on the cluster analysis results and actual production, a progressive discrimination method based on the importance of indicators was adopted to formulate the quality grading standard for Rhododendron seedlings. That is, the initial classification was based on the first important indicator, and then the second and third important indicators were used to further subdivide and adjust each level, thereby constructing a hierarchical grading system.

[0049] 3. Data Analysis and Results 3.1 Analysis of differences in quality-related indicators of Rhododendron seedlings Descriptive statistics were performed on the quality indicators of azalea seedlings. The operational steps included: In SPSS, go to Analyze → Descriptive Statistics → Descriptive. In the Descriptive window, select the raw data for 10 indicators. Click Options to open the Descriptive Options window. Check the Mean, Standard Deviation, Maximum, and Minimum values, then click OK. Manually calculate the range and coefficient of variation. As shown in Table 1, the data provides basic information on the maximum, minimum, range, mean, standard deviation, and coefficient of variation for each indicator of the Rhododendron seedlings. The degree of variation for each indicator, from highest to lowest, is as follows: plant fresh weight, pseudobulb diameter, leaf area, fibrous root length, petiole diameter, leaf width, number of fibrous roots, leaf length, number of leaves, petiole length, and chlorophyll SPAD value, with coefficients of variation of 76.67%, 60.19%, 48.83%, 47.67%, 43.60%, 39.68%, 39.53%, 24.36%, 23.97%, 19.23%, and 14.65%, respectively. The results showed that there were significant differences in traits among individual Rhododendron seedlings, and the seedlings sampled in this study can be used for seedling quality grading.

[0050] Table 1. Descriptive statistics of quality indicators for Rhododendron seedlings

[0051] Correlation analysis was performed on the quality indicators of Rhododendron seedlings. The operation steps included: In SPSS, go to Analyze → Correlation → Bivariate to open the Bivariate Correlation window. Select the raw data for 10 indicators, check Pearson's coefficient, perform a two-tailed test, and mark the correlation as significant. In the Options menu, select the mean and standard deviation, and exclude cases by list. After confirming, you will get the significantly correlated data, as shown in Table 2.

[0052] Table 2 Correlation among quality indicators of Rhododendron seedlings

[0053] Note: ** indicates significant correlation at the 0.01 level (two-tailed), * indicates significant correlation at the 0.05 level (two-tailed).

[0054] As shown in Table 2, there is a highly significant positive correlation between pseudobulb diameter, number of fibrous roots, fibrous root length, number of leaves, leaf length, leaf width, leaf area, petiole diameter, and plant fresh weight. P <0.01, because there is strong collinearity among the three indicators of leaf length, leaf width and leaf area, and leaf area is more representative of leaf size, redundancy was removed from the variables, and leaf length and leaf width were excluded; while the correlation between petiole length and each indicator was not significant; chlorophyll SPAD value was only significantly positively correlated with root length and plant fresh weight ( P <0.05, showing a highly significant positive correlation with leaf width ( P<0.01). The correlation between petiole length and relative chlorophyll content and other indicators was weak.

[0055] The above analysis shows that the differences in petiole length and relative chlorophyll content among individual Rhododendron seedlings are small (coefficients of variation are all less than 20%), and the correlation with other seedling quality indicators is weak. However, there is redundancy between leaf length, leaf width, and leaf area, and there is a highly significant positive correlation between pseudobulb diameter, number of fibrous roots, fibrous root length, number of leaves, leaf length, leaf width, petiole diameter, and plant fresh weight. P <0.01) indicates that, apart from petiole length and relative chlorophyll content, the other indicators can be used as grading indicators to a certain extent.

[0056] Principal component analysis (PCA) is a common dimensionality reduction statistical method that transforms many highly correlated variables into a few independent or uncorrelated variables, known as principal components. Principal components are ranked according to their variance contribution rate; a higher variance contribution rate better represents the overall information.

[0057] In this embodiment, principal component analysis is used to extract principal components, with a cumulative contribution rate of 70.647%. A grading index is selected based on the magnitude of the eigenvector values ​​under each principal component. The specific operation process includes:

Analysis

Dimensionality Reduction

Factor Analysis

Description

[0058] Table 3. Eigenvalues, cumulative contribution rates, and eigenvectors of principal components

[0059] Table 3 shows that the cumulative contribution rate of the extracted principal component reached 70.647%, which can reflect the seedling quality information well. The representative index of the principal component is the pseudobulb diameter, and the plant fresh weight and leaf area have high loading values. Therefore, pseudobulb stem diameter, plant fresh weight, and leaf area are selected as key evaluation indicators for Rhododendron seedling quality. Since the pseudobulb is not only a traditional vegetative reproductive organ but also an important storage site for substances, it can endow the plant with stronger resistance and stress recovery ability. Therefore, it is recommended as the primary evaluation indicator for seedling grading. Since the fresh weight of Rhododendron plants mainly comes from its underground pseudobulbs and fibrous roots, fresh weight can serve as a direct indicator for measuring the degree of pseudobulb enlargement and root development. This fully demonstrates the core role of its underground organs in substance storage and plant support. Meanwhile, the life cycle of Rhododendron azaleas undergoes a shift in nutritional strategy. Seed germination and early seedling growth rely on mycorrhizal fungi. After leaves emerge, they gradually transition to photosynthetic autotrophy. For photosynthetic autotrophic plants, leaf area is directly related to the accumulation of photosynthetic assimilates. Therefore, the pseudobulb diameter, plant fresh weight, and leaf area extracted from the principal components are sufficiently reasonable as quality indicators for Rhododendron azalea seedlings.

[0060] K-means cluster analysis was used. The procedure was as follows: In SPSS software, go to [Analyze] → [Classify] → [K-means Cluster Analysis]. Select the original data for three indicators: pseudobulb diameter, plant fresh weight, and leaf area. Select 3 for the number of clusters. Select ANOVA table in [Options] and exclude cases by list. After confirming, the final cluster center table is obtained, as shown in Table 4.

[0061] Table 4. K-means cluster center table for Rhododendron seedlings

[0062] 3.3.2 Quality Grading of Rhododendron Seedlings Clustering was performed using three main seedling quality indicators: pseudobulb diameter, plant fresh weight, and leaf area. Three final clustering results were obtained, as shown in Table 4. The quality grading standards for Rhododendron seedlings were then determined based on these results, as shown in Table 5. Details are as follows: Table 5. K-cluster grading standards and proportions for Rhododendron seedling quality

[0063] 3.4 Analysis of the growth of azalea seedlings of different grades In April 2025, Rhododendron seedlings were collected and divided into four grades according to the established quality grading standards. They were transplanted to the experimental base of the South Campus of Guizhou University. After the seedlings died (the above-ground parts withered), the pseudobulb sprouting time of seedlings of different grades was tracked and recorded. In early September of the same year, the survival rate, number of fibrous roots, length of fibrous roots, number of leaves, length of leaves, width of leaves and other indicators of seedlings were counted. At least 40 seedlings of each grade were randomly selected and the differences in seedling growth were compared and analyzed. The results are shown in Table 6.

[0064] Table 6. Growth of seedlings of different grades after transplanting

[0065] Note: Different letters after the values ​​in the same column in the table represent highly significant differences. P <0.01).

[0066] Table 6 shows that there are significant differences in the growth of seedlings at each grade. Except for the fact that all seedlings at each grade have only one leaf and the survival rate of Grade I and II seedlings is not significantly different, the number of fibrous roots, the length of fibrous roots, the length of leaves, and the width of leaves are all highly significant. Among them, Grade I and II seedlings are significantly better than Grade III seedlings. Grade IV seedlings even only grow leaf buds without unfolding leaves and no new underground roots during the observation period. The order is Grade I seedlings > Grade II seedlings > Grade III seedlings > Grade IV seedlings. The higher the seedling grade, the higher the transplant survival rate, the larger the leaves, the more developed the root system, and the earlier the pseudobulb budding time. This shows that the grading standard has theoretical and practical significance.

[0067] The embodiments described above are only for the purpose of facilitating a specific and detailed understanding of the technical solutions of the present invention and should not be construed as excluding other embodiments. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these should all fall within the protection scope of the present invention. It should be understood that technical solutions obtained by those skilled in the art based on the technical solutions provided by the present invention through logical analysis, reasoning, or limited experimentation are all within the protection scope of the appended claims. Therefore, the protection scope of this patent should be determined by the content of the appended claims, and the specification can be used to interpret the content of the claims.

Claims

1. A method for screening grading indicators for Rhododendron seedlings, characterized in that, Includes the following steps: One-year-old seedlings of suitable age were taken from a rhododendron seedling production base with mature fungal seed dressing and direct seeding technology. Seedling quality indicators were tested and statistically analyzed. The seedling quality indicators included pseudobulb diameter, number of fibrous roots, length of fibrous roots, number of leaves, leaf length, leaf width, leaf area, petiole length, petiole thickness, relative chlorophyll content, and plant fresh weight. The obtained raw data were recorded as T0. Descriptive statistics and correlation analysis were performed on the above seedling quality index data. Based on the correlation coefficient, a group of strongly correlated indicators was selected, and redundant indicators with collinearity and indicators with weak correlation were removed. The original data of the core indicators obtained were denoted as T1. Principal component analysis was performed on the original data T1 of the core indicators, and the three key indicators with the highest contribution were extracted as the main basis for seedling quality grading.

2. The method for screening grading indicators for Rhododendron seedlings according to claim 1, characterized in that, The screening method further includes: The original data of the three key seedling quality indicators with the highest contribution were extracted by principal component analysis and denoted as T2. K-means cluster analysis was performed on the original data T2, and the threshold of the graded indicator level was determined by referring to the obtained K-means.

3. The method for screening grading indicators for Rhododendron seedlings according to claim 2, characterized in that, The three seedling quality indicators with the highest contribution extracted by the principal component analysis include pseudobulb diameter, plant fresh weight, and leaf area.

4. The method for screening grading indicators for Rhododendron seedlings according to claim 3, characterized in that, The K-mean values ​​of the pseudobulb diameter include 0.64, 1.53, and 2.35; the K-mean values ​​of the plant fresh weight include 2.25, 6.08, and 11.89; and the K-mean values ​​of the leaf area include 25.92, 53.91, and 80.

72.

5. The method for screening grading indicators for Rhododendron seedlings according to any one of claims 2 to 4, characterized in that, The cluster analysis was performed using SPSS software.

6. The method for screening grading indicators for Rhododendron seedlings according to any one of claims 1 to 4, characterized in that, The software used for raw data processing is SPSS, and / or the software used for descriptive statistics is SPSS.

7. The method for screening grading indicators for Rhododendron seedlings according to any one of claims 1 to 4, characterized in that, The software used for correlation analysis is SPSS, and / or the software used for principal component analysis is SPSS.

8. The method for screening grading indicators for Rhododendron seedlings according to any one of claims 1 to 4, characterized in that, Descriptive statistics include the maximum, minimum, range, mean, standard deviation, and coefficient of variation of the seedling quality indicators.

9. A method for grading the quality of Rhododendron seedlings, characterized in that, The grading method includes: determining relevant indicators for quality grading of Rhododendron seedlings and grading them according to the results, wherein the seedling quality indicators are obtained by screening using the method described in any one of claims 1 to 4.

10. The grading method for Rhododendron seedlings according to claim 9, characterized in that, The classification criteria include: The pseudobulb diameter is greater than or equal to 2.30 cm, the fresh weight of the plant is greater than or equal to 12 g, and the leaf area is greater than or equal to 80 cm². 2 Then it is a Grade I seedling; The pseudobulb diameter is greater than or equal to 1.50 cm and less than 2.30 cm, the fresh weight of the plant is greater than or equal to 6 g and less than 12 g, and the leaf area is greater than or equal to 50 cm². 2 and less than 80 cm 2 Then it is a Grade II seedling; The pseudobulb diameter is greater than or equal to 0.6 cm and less than 1.50 cm, the fresh weight of the plant is greater than or equal to 2 g and less than 6 g, and the leaf area is greater than or equal to 25 cm². 2 and less than 50 cm 2 Then it is a Grade III seedling; The pseudobulb diameter is less than 0.6 cm, the fresh weight of the plant is less than 2 g, and the leaf area is less than 25 cm². 2 Then it is a Grade IV seedling; Among the pseudobulb diameter, plant fresh weight, and leaf area, pseudobulb diameter is the first key grading indicator, plant fresh weight is the second key grading indicator, and leaf area is the third key grading indicator.

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