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1.重庆三峡学院 生物与食品工程学院,重庆 404020
2.三峡库区道地药材绿色种植与 深加工重庆市工程研究中心,重庆 404120
3.重庆三峡学院 环境与化学工程学院,重庆 404120
Received:20 December 2024,
Accepted:07 February 2025,
Published Online:12 February 2025,
Published:20 July 2025
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任雪杨,郎佳琪,王逾涵等.基于不同解钾细菌对太白贝母土壤肥力影响最小数据集的构建[J].中国实验方剂学杂志,2025,31(14):153-163.
REN Xueyang,LANG Jiaqi,WANG Yuhan,et al.Construction of a Minimal Data Set for Indicators of Soil Fertility Affected by Different Potassium-solubilizing Bacteria of Fritillaria taipaiensis[J].Chinese Journal of Experimental Traditional Medical Formulae,2025,31(14):153-163.
任雪杨,郎佳琪,王逾涵等.基于不同解钾细菌对太白贝母土壤肥力影响最小数据集的构建[J].中国实验方剂学杂志,2025,31(14):153-163. DOI: 10.13422/j.cnki.syfjx.20250311.
REN Xueyang,LANG Jiaqi,WANG Yuhan,et al.Construction of a Minimal Data Set for Indicators of Soil Fertility Affected by Different Potassium-solubilizing Bacteria of Fritillaria taipaiensis[J].Chinese Journal of Experimental Traditional Medical Formulae,2025,31(14):153-163. DOI: 10.13422/j.cnki.syfjx.20250311.
目的
2
探究接种不同解钾细菌后,太白贝母土壤肥力指标的变化情况,为人工栽培过程中选择优异解钾菌肥提供依据。
方法
2
分别设置接种单株菌株S1组(
Bacillus cereus
)、S2组(
Burkholderia hospita
)和S3组(
Ba. subtilis
)及组合菌株S4组(
Ba. cereus
和
Bu. hospita
)、S5组(
Ba. cereus
和
Ba. subtilis
)、S6组(
Bu. hospita
和
Ba. subtilis
)、S7组(
Bu. hospita
和
Ba. subtilis
、
Ba. cereus
),7个处理组,同时设置空白处理组(CK组),并测定各处理组的20个土壤理化指标,利用聚类分析、相关性分析、主成分分析(PCA)等方法构建影响土壤肥力的最小数据集,比较各处理组土壤肥力水平,筛选最优菌株。
结果
2
构建的最小数据集指标包括速效钾含量、速效磷含量、速效氮含量、土壤含水量、细菌数量、解钾细菌含量、真菌含量、pH;全量数据集与最小数据集的土壤肥力指数呈显著正相关,
R
2
达到了0.914,Nash有效系数为0.825,偏差系数为0.108;隶属度雷达图显示,解钾细菌处理组的面积均高于CK组,其中S7组的面积最大。最小数据集土壤肥力指数在0.264(S2)~0.760(S7),平均值分别为0.44和0.39。
结论
2
使用聚类分析、PCA、相关性分析构建的最小数据集精简度较高;施加解钾细菌能显著提高太白贝母土壤肥力,S7组的整体效果较优。
Objective
2
To explore the changes in soil fertility indicators of
Fritillaria taipaiensis
after inoculation with different potassium-solubilizing bacteria, providing a basis for selecting elite potassium-solubilizing microbial fertilizer during artificial cultivation of this plant.
Methods
2
Seven bacterial inoculation groups were designed, including
S1
(
Bacillus cereus
), S2 (
Burkholderia hospita
),
S3 (
Ba. subtilis
), S4 (
Ba. cereus
and
Bu. hospita
), S5 (
Ba. cereus
and
Ba. subtilis
), S6 (
Bu. hospita
and
Ba. subtilis
) and S7 (
Ba. cereus
,
Bu. hospita
and
Ba. subtilis
). Additionally, a blank control group (CK group) was included. Twenty soil physical and chemical indicators of each group were measured. The cluster analysis, correlation analysis, and principal component analysis (PCA) were performed to construct the minimum data set of indicators influencing soil fertility. The soil fertility was compared between groups to select the optimal strain.
Results
2
The constructed minimum data set included available potassium content, available phosphorus content, available nitrogen content, soil moisture content, bacterial count, potassium-solubilizing bacterial content, fungal count, and pH. The full data set and the minimum data set showed a significant positive correlation regarding the soil fertility index, with
R
2
of 0.914, Nash efficiency coefficient of 0.825, and deviation coefficient of 0.108. The membership radar chart showed that the area of each potassium-solubilizing bacterial inoculation group was larger than that of the CK group, with the S7 group having the largest area. The soil fertility index of the total data set ranged from 0.258 (S3) to 0.891 (S7), and that of the minimum data set ranged from 0.264 (S2) to 0.760 (S7), with average values of 0.44 and 0.39, respectively.
Conclusion
2
The minimum data set constructed by cluster analysis, principal component analysis, and correlation analysis has a high degree of simplification. The application of potassium-solubilizing bacteria significantly improves the soil fertility of
F. taipaiensis
, with the S7 group showing the best overall performance.
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