Chemical properties of the soil
There is a wide variation in soil chemical properties among the different geographic seed sources of D. brandisii, as shown in Table 2. The seven main chemical indices differed significantly (P < 0.05) between the different regions. The pH value of soil in SP was significantly higher than that in CY (P < 0.05), and significantly higher than that in the CN, MS, MT, and SM (P < 0.01), SM soil was observed to be the most acidic. In addition to CN, MS and SM, the other four areas had higher soil nutrients, and the organic matter content in CY was significantly higher than that in MS, MT, and SM (P < 0.01). The content of soil AP in MT was the highest, and the difference was very significant (P < 0.01); the content of soil AP in the SP area was significantly higher than that in CN, MS, CY, and SM (P < 0.01). The TN content in XP was significantly higher than that in MS, MT, and SM (P < 0.05), and the lowest was observed in the MS. The content of total phosphorus in MT was the highest, followed by that in CY (P < 0.01), and was significantly higher than that in CN, MS, SM, SP and XP. The soil total potassium content in XP was the highest, and the difference was significantly higher than that in the other six regions.
Table 2
Soil chemical properties in different D. brandisii geographical provenances
Soil Factor | CN | CY | MS | MT | SM | SP | XP |
pH** | 5.13 ± 0.13bc | 5.56 ± 0.20bc | 4.92 ± 0.15bc | 4.74 ± 0.01cd | 4.33 ± 0.09d | 6.50 ± 0.67a | 5.80 ± 0.05ab |
SOM*(g·kg− 1) | 49.24 ± 4.47ab | 64.83 ± 8.99a | 32.08 ± 3.89bc | 30.78 ± 1.49bc | 23.64 ± 2.44c | 43.19 ± 2.55abc | 53.10 ± 16.26ab |
AP**(mg·kg− 1) | 14.43 ± 6.01b | 5.88 ± 0.65b | 3.24 ± 0.33b | 57.85 ± 12.07a | 13.80 ± 2.82b | 3.67 ± 0.40b | 5.71 ± 3.55b |
AK**(mg·kg− 1) | 59.58 ± 15.21c | 205.83 ± 54.95bc | 68.33 ± 9.82c | 361.67 ± 127.33ab | 172.50 ± 62.37bc | 498.33 ± 60.85a | 372.08 ± 74.74ab |
TN**(g·kg-1) | 2.13 ± 0.55ab | 3.41 ± 0.63a | 1.76 ± 0.27c | 1.79 ± 0.10c | 1.78 ± 0.29c | 2.75 ± 0.15ab | 3.45 ± 0.74a |
TP**(g·kg− 1) | 0.56 ± 0.03bc | 0.90 ± 0.05a | 0.41 ± 0.02bc | 0.97 ± 0.12a | 0.38 ± 003c | 0.46 ± 0.01bc | 0.62 ± 0.12b |
TK**(g·kg− 1) | 10.09 ± 0.74d | 17.59 ± 2.81bc | 19.09 ± 1.15b | 14.20 ± 0.54cd | 21.99 ± 0.98b | 5.67 ± 0.31e | 28.96 ± 1.58a |
Values are mean ± SE; different letters in the same column indicate significant differences (P < 0.05), * and ** indicate significant differences at the 0.05 and 0.01 level, respectively. CN: Changning County, Baoshan City; CY: Cangyuan County, Lincang City; MS: Mang County, Dehong Prefecture; MT: Matai Township, Linxiang District, Lincang City; SM: Simao District, Pu'er City; SP: Shiping County, Honghe Prefecture; and XP: Xinping County, Yuxi City. SOM: soil organic matter; AP: available phosphorus; AK: available potassium; TN: total nitrogen; TP: total phosphorus; TK: total potassium.
Nutritional quality of bamboo shoots
Four appearance (individual weight, basal diameter, length, and edible rate) and eight nutritional quality indices (water content, soluble sugar, ash, crude fat, protein, lignin, cellulose, and tannin) were selected to measure the quality of D. brandisii bamboo shoots, and the results are shown in Fig. 2A–L. The appearance quality showed that the individual weight of the bamboo shoots was highest in CY, followed by MS and CN, which were significantly (P < 0.05) higher than those of bamboo shoots from MT, SM, and XP. The basal diameter of bamboo shoots in MS was highly significant (P < 0.01) in CN, CY and SP; the length of bamboo shoots in CN was the largest and highly significant (P < 0.01) and was higher than that of MT, SM, SP, and XP, and was not significantly different from CY and MS. The edible rate of bamboo shoots was highly significant (P < 0.01) in SP. There were significant differences in the appearance and morphology of D. brandisii bamboo shoots grown in natural environments of different geographies, and there were no significant correlations between shoot length, weight, basal diameter, and palatability.
Nutritional quality of D. brandisii bamboo shoots in SP and XP had significantly (P < 0.05) lower water content than CN, MS, CY and MT. The soluble sugar content was significantly higher in MS (P < 0.01) and CY (P < 0.05) than compared to CN, MT, SM, and XP. The ash content of MS (P < 0.01) bamboo shoots was significantly lower than that of CN, MT, SM, SP, and XP, whereas CY (P < 0.05) was significantly lower than that of MT and SM. The crude fat content of MT bamboo shoots was significantly (P < 0.05) higher than that of CY, SM and XP; SM bamboo shoots had the highest protein content, which was not significantly different from that of MT, SP, and XP, and MS had significantly (P < 0.05) lower content than CN, MT, SM, SP, and XP, lignin was highly significant (P < 0.01) in SM bamboo shoots than in MS and SP, and significantly higher (P < 0.05) than in CY, MT, and XP; XP bamboo shoots had the highest cellulose content, which was significantly different from CN, SM and XP. The tannin content of CN bamboo shoots was significantly (P < 0.05) higher than that of MS, MT, SM, and SP. Overall, the nutrient composition of D. brandisii bamboo shoots from different geographic seed sources varied considerably, with different degrees of variation in different nutrient components, with the nutritional quality of D. brandisii bamboo shoots in CN being better on the whole. The CN regional seed source has been approved by the Forestry and Grassland Bureau of the State Forestry and Grassland Bureau of the Forestry and Tree Species Validation Committee on January 25, 2022, "Yun Sweet No. 1" Sweet Longzhu as a national grade good seed, good seed number: State S-SV-DB-016-2021 (with Fig. 1).
Diversity of soil microbial community
A total of 910389 bacterial sequences were obtained from 21 soil samples collected from seven provenances, which were effectively classified into 6885 operational taxonomic units (OTUs) with 97% similarity, comprising of 2096 species belonging to 1001 genera, 511 families, 308 orders, 127 classes, and 40 phyla. The total number of available sequences of soil fungi was 903506, which can be divided into 7021 OTUs, including 1627 species, 901 genera, 375 families, 156 orders, 16 phyla, and 63 classes. A one-way analysis of variance (ANOVA) was performed for bacterial and fungal communities in the soil samples.
The soil microbial community diversity index of different geographical provenances showed a significant difference (P < 0.05) when comparing the α diversity of a microbial community (Fig. 3A–F), in the bacterial community, the Shannon index was significantly different between SM and CN (P < 0.05), the ACE index of fungi community was significantly different from that of SP and XP (P < 0.05), CY in Sobs index was significantly different from CN and XP (P < 0.05) and highly significantly different from SP (P < 0.01). Principal coordinate analysis (PCoA) of the bacterial and fungal communities showed that the microbial communities in the soil samples from different geographical D. brandisii provenances were significantly different. Specifically, fungal PCoA (Fig. 3H) exhibited more pronounced clustering between samples compared with bacterial PCoA (Fig. 3G), and the soil fungal communities in the CN region were more distant and different from those in the other 6 regions. Both SP and XP bacteria and fungi showed clusters, and the species composition of the microbes in the two samples was similar. In addition, analysis of similarities (ANOSIM) showed that different geographic provenances had significant effects on the structure of soil bacteria (r2 = 0.8342, P = 0.001) and fungal communities (r2 = 0.7939, P = 0.001) (Fig. 3G, H).
Soil microbial composition
The soil bacteria in the seven regions belonged to 998 genera, 509 families, 307 orders, 127 classes, and 40 phyla, as shown in Fig. 4A–D. Proteobacteria (19.78–29.06%), Actinobacteria (13.53–30.01%), Chloroflexi (8.03–31.47%), and Acidobacteria (7.12–19.17%) were the dominant Chloroflexi in the soil bacterial community and together accounted for more than 70% of the total bacterial community in each soil sample (Fig. 4A, Table S1). The relative abundance of Proteobacteria was the highest in SP (29.06%) and lowest in CN (19.78%); the relative abundance of Actinobacteria was the highest in XP (37%) and lowest in CN (13.53%); and the relative abundance of Campylobacter was the highest in CN (31%) and lowest in MT (8.03%). The dominant bacterial genera in all soil samples were Xanthobacteraceae (2.83–7.29%), AD3 (0.35–13.68%), Acidothermus (0.62–8.06%), and Gaiellales (0.94–8.64%), respectively (Fig. 4C, Table S2).
Soil fungi in the seven regions belong to 901 genera, 375 families, 156 orders, 63 classes, and 16 phyla, and the dominant fungal phyla were Ascomycota (41.72–62.44%) and Basidiomycota (18.72–45.23%), which accounted for more than 79% of the total fungal community in each soil sample (Fig. 4B, Table S3). The MT (65.01%) and CY (62.44%) regions had the highest relative abundances of ascomycetes, whereas SP had the lowest (41.72%). However, SP had the highest relative abundance of Ascomycota (45.23%), and CY had the lowest (18.72%). The dominant fungal genera of the seven geographic soil samples varied, with unclassified_p_Ascomycota and Archaeorhizomyces in CN, Mortierella and Exophiala in CY, unclassified_c_Agaricomycetes and Trechispora in MS, Penicillium and unclassified_c_Sordariomycetes with the highest abundance in MT, Saitozyma and Apiotrichum in SM, and Agaricus in SP and XP (Fig. 4D, Table S4). This result suggests that the microbial community structure varies significantly under natural conditions in different geographies and that fungal communities are more influenced by the environment.
Analysis of soil microbial abundance
Using the linear discriminant analysis effect size (LEfSe), the 21 most abundant microbial taxa with significant differences in abundance between genera were identified in the soil samples (Fig. 5A, B). This analysis revealed 21 taxonomic branches exhibiting different abundances of bacterial biomarkers (Fig. 5A, Table S5). The CY and MS samples had the least number of bacterial taxa, with significant differences in one genus each (Methyloligellaceae and 1921-2, respectively), followed by MT and SP, with significant differences between the two genera. In contrast, soil samples from site CN showed the highest number of bacterial taxa, including AD3, Acidobacteriae, Subgroup_2, Elsterales, HSB_OF53-F07, WPS-2, and FCPS473. Meanwhile, a total of 15 evolutionary clades of fungi with significant differences in abundance were identified in this study (Fig. 5B, Table S6). Among them, soil samples from MT, XP, and CY had the least number of fungal taxa, with only one genus demonstrating notable variation, namely Psathyrella, Trechisporales, and Mortierella, followed by CN and SP, with two genera. In contrast, soil samples from MS contained the highest number of fungal taxa, including five genera: Trechispora, Agaricomycetes, Pyrenochaeta, Agaricales, and Cordana.
Relationship between soil chemical properties, microbial communities, and bamboo shoot quality
Partial least squares path modeling (PLS-PM) analysis
The PLS-PM analysis of the soil chemical properties, microbial community structure, and bamboo shoot quality was performed, and the results are shown in Fig. 6A, B. Both soil chemical properties and microbial community structure had direct positive effects on bamboo shoot quality. The direct effect coefficient of the soil bacterial community on D. brandisii bamboo shoot quality was 0.865. As shown in Fig. 6, the total effect of soil bacterial community (0.865) and soil chemical properties (0.856) on bamboo shoot quality, including direct and indirect effects, was significant; the total effect of fungal community structure on bamboo shoot quality was 0.69, which was less than that of bacterial community structure and soil chemical properties, and the indirect effects of bacterial community and soil chemical properties on bamboo shoot quality was less than that of the fungal community structure.
To further explore the relationship among the three, db-RDA analysis was performed on soil microorganisms of D. brandisii bamboo from different geographical seed sources to investigate the relationship between soil factors, bamboo shoot quality, and microbial communities. Seven nutrient indicators of bamboo shoots were selected as water content, soluble sugar, ash content, crude fat, protein, lignin, cellulose, and tannin, the results showed that pH, AP, and AK were the main soil properties affecting the bacterial community structure (r2 = 0.35, P = 0.019 for pH, r2 = 0.325, P = 0.022 for AP and r2 = 0.43, P = 0.008 for AK) (Fig. 7A, Table S7). Soil pH, SOM, AK, and TN were the main factors affecting the fungal community structure (r2 = 0.669, P = 0.001 for pH; r2 = 0.46, P = 0.012 for SOM; r2 = 0.47, P = 0.003 for AK; and r2 = 0.367, P = 0.021 for TN) (Fig. 7B, Table S8). In particular, soil pH and fast-acting potassium levels affect the structure of both bacterial and fungal communities. Bamboo shoot water content, soluble sugar, ash content, protein, and lignin content were strongly influenced by the bacterial community, whereas bamboo shoot water content and tannin were strongly influenced by the fungal community.
The top 20 species in terms of relative abundance at the bacterial and fungal phyla levels were selected for Pearson correlation analysis, as shown in the heatmap (Fig. 7C, D). The major effects on the nutrition of D. brandisii bamboo shoots were Actinobacteriota, Chloroflexi, Patescibacteria, GAL15, and Cyanobacteria (Fig. 7C). At the level of fungal phyla, those that have a greater impact on the nutrition of bamboo shoots include Basidiomycota, Kickxellomycota, Mucoromycota, unclassified-k-Fungi, and Glomeromycota (Fig. 7D). Among them, crude fat, cyanobacteria, and Chytridiomycota, demonstrated a significant positive correlation (P < 0.05). Protein was significantly and positively correlated with Patescibacteria and Actinobacteriota, (P < 0.05). Water content was significantly and positively correlated with Chloroflexi (P < 0.05) and significantly and negatively correlated with Actinobacteriota, (P < 0.05); tannin was significantly positively correlated (P < 0.05) with GAL15 and Kickxellomycota, Mucoromycota, and unclassified-k-Fungi; lignin and Basidiomycota demonstrated a significant positive correlation (P < 0.05). Protein and Glomeromycota showed a significant negative correlation (P < 0.05). The soluble rate and Glomeromycota showed significant positive correlation (P < 0.05).