植物乳植杆菌对紫花苜蓿青贮温室气体排放的影响

doi:10.13560/j.cnki.biotech.bull.1985.2025-1442

摘要/Abstract

摘要：

目的探究植物乳植杆菌（Lactiplantibacillus plantarum, LP）对紫花苜蓿青贮过程中温室气体减排的影响。方法设置不添加菌剂（CK）与添加植物乳植杆菌（LP）处理，于青贮第3、7、15、30、45天采集气体样品测定二氧化碳（CO₂）、甲烷（CH₄）及氧化亚氮（N₂O）排放量；测定pH、氨态氮（NH₃-N）及干物质含量（DM）；于第7和45天测定粗蛋白（CP）含量；采用高通量测序分析细菌群落结构，并构建共现网络与随机森林模型。结果与CK相比，LP处理显著降低CO₂、CH₄（除第3天和45天）和N₂O的排放量（P<0.05），降低pH与NH₃-N含量，提高DM保存率，CP含量无显著变化。LP处理显著降低第7天和45天细菌群落多样性。主成分分析显示LP与CK处理样品在Y轴明显分离。网络分析表明，LP处理节点数与连接数减少，脆弱性降低，负内聚力提升，正内聚力下降。随机森林模型显示，肠杆菌属、植物乳植杆菌属、乳酸乳球菌属相对丰度、pH、香农指数、PCoA1解释度对CO₂排放贡献显著；肠杆菌属相对丰度、NH₃-N含量、pH、乳酸乳球菌属相对丰度对CH₄排放贡献显著；pH、乳酸乳球菌属相对丰度、香农指数、植物乳植杆菌属相对丰度、PCoA1解释度、肠杆菌属相对丰度对N₂O排放贡献显著。相关性分析表明，CO₂排放与植物乳植杆菌属相对丰度、CP含量呈显著负相关；CH₄排放与肠杆菌属相对丰度呈显著正相关；N₂O排放与肠杆菌属相对丰度、香农指数呈显著正相关，与植物乳植杆菌属相对丰度、CP含量、PCoA1解释度呈显著负相关。结论添加植物乳植杆菌可改善苜蓿青贮发酵品质，降低温室气体排放，并调控细菌群落结构，其中肠杆菌属、植物乳植杆菌属及群落多样性是影响气体排放的关键微生物因子。

关键词: 苜蓿青贮, 植物乳植杆菌, 温室气体, 细菌群落, 网络分析, 随机森林

Abstract:

Objective This study aimed to investigate the effect of Lactiplantibacillus plantarum (LP) on greenhouse gas emissions during the ensiling of alfalfa (Medicago sativa L.). Method Two treatments were established: A control (CK, no additive) and an LP inoculation group. Gas samples were collected at day 3, 7, 15, 30, and 45 of ensiling to measure emissions of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O). The pH, ammonia nitrogen (NH₃-N), and dry matter (DM) contents were determined. Crude protein (CP) content was analyzed on day 7 and 45. Bacterial community structure was assessed using high-throughput sequencing, and co-occurrence networks and random forest models were constructed. Result Compared with CK, LP treatment significantly reduced the emissions of CO₂, CH₄, and N₂O (P<0.05), decreased pH and NH₃-N content, and increased DM preservation, with no significant change in CP content. LP treatment also significantly reduced bacterial diversity on day 7 and 45. Principal coordinate analysis revealed clear separation between LP and CK samples along the Y-axis. Network analysis indicated that LP treatment reduced node number and connectivity, lowered vulnerability, enhanced negative cohesion, and decreased positive cohesion. The random forest model identified the relative abundance of Enterobacter, Lactiplantibacillus, and Lactococcus, pH, Shannon index, and the contribution of PCoA1 as significant contributors to CO₂ emissions; the relative abundance of Enterobacter, NH₃-N content, pH and the relative abundance of Lactococcus as key factors for CH₄ emissions; and pH, the relative abundance of Lactococcus, Shannon index, the relative abundance of Lactiplantibacillus, the contribution of PCoA1 andthe relative abundance of Enterobacter as major contributors to N₂O emissions. Correlation analysis showed that CO₂ emissions were negatively correlated with the relative abundance of Lactiplantibacillus and CP content; CH₄ emissions were positively correlated with the relative abundance of Enterobacter; and N₂O emissions were positively correlated with the relative abundance of Enterobacter and Shannon index, but negatively correlated with the relative abundance of Lactiplantibacillus, CP content, and the degree of explanation of PCoA1. Conclusion Inoculation with L. plantarum improves fermentation quality, reduces greenhouse gas emissions, and modulates the bacterial community structure in alfalfa silage, with Enterobacter, Lactiplantibacillus, and microbial diversity serving as key microbial factors influencing gas emissions.

Key words: alfalfa silage, Lactiplantibacillus plantarum, greenhouse gas, bacterial community, network analysis, random forest

王雁萍, 孙品天, 顾松松, 汤晓雪, 孟晨阳, 韩修菊, 简媛, 王恩召. 植物乳植杆菌对紫花苜蓿青贮温室气体排放的影响[J]. 生物技术通报, 2026, 42(5): 185-192.

WANG Yan-ping, SUN Pin-tian, GU Song-song, TANG Xiao-xue, MENG Chen-yang, HAN Xiu-ju, JIAN Yuan, WANG En-zhao. Effect of Lactiplantibacillus plantarum on Greenhouse Gas Emissions during Alfalfa Silage[J]. Biotechnology Bulletin, 2026, 42(5): 185-192.

图/表 6

图1 温室气体排放量A：不同时间点二氧化碳排放量；B：不同时间点甲烷排放量；C：不同时间点氧化亚氮排放量；其中CK代表不加菌处理，LP代表添加植物乳植杆菌处理。不同小写字母表示在P<0.05水平上差异显著。下同

Fig. 1 Greenhouse gas emissionsA: Carbon dioxide emissions at different time points. B: Methane emissions at different time points. C: Nitrous oxide emissions at different time points. CK: The treatment without bacterial addition. LP: The treatment with L. plantarum added. Different lowercase letters indicate the significant difference at the P<0.05 level. The same below

图2 青贮发酵品质

Fig. 2 Silage fermentation quality

图3 细菌群落结构及多样性

Fig. 3 Bacterial community structure and diversity

图4 细菌共现网络（A，B）及拓扑性质（C，D，E）A：CK处理细菌共现网络；B：LP处理细菌共现网络。Eb：肠杆菌属（Enterobacter）的OTU节点，Lb：植物乳植杆菌属（Lactiplantibacillus）的OTU节点，节点颜色：不同模块；连接颜色红色：正相关，绿色：负相关

Fig. 4 Bacterial co-occurrence networks(A, B) and topological properties(C, D, E)A: Bacterial co-occurrence network under CK treatment. B: Bacterial co-occurrence network under LP treatment. Eb: OTU node representing Enterobacter, Lb: OTU node representing Lactiplantibacillus. Node colors indicate different modules; node colors: red for positive correlations, green for negative correlations

图5 属水平连接度之和

Fig. 5 Sum of node degrees at the genus level

图6 随机森林模型及相关性分析A：不同指标对二氧化碳排放的贡献度；B：不同指标对甲烷排放的贡献度；C：不同指标对氧化亚氮排放的贡献度；D：不同指标与温室气体排放之间的相关性

Fig. 6 Random forest model and correlation analysisA: Contribution of different indicators to carbon dioxide emissions. B: Contribution of different indicators to methane emissions. C: Contribution of different indicators to nitrous oxide emissions. D: Correlation between different indicators and greenhouse gas emissions

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