| 黄河下游谷子花生间作农田土壤细菌群落结构与功能预测 |
| 摘要点击 1428 全文点击 380 投稿时间：2022-10-10 修订日期：2022-10-25 |
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| 中文关键词 黄河下游 间作 土壤细菌 群落结构 BugBase表型 |
| 英文关键词 lower Yellow River intercropping soil bacterial community structure BugBase phenotype |
| 作者 | 单位 | E-mail | | 刘柱 | 沈阳农业大学农学院, 沈阳 110866
山东省农业科学院, 济南 250100 | liuzhuzhuer@163.com | | 南镇武 | 山东省农业科学院, 济南 250100 | | | 林松明 | 山东省农业科学院, 济南 250100
齐鲁师范学院生命科学学院, 济南 250200 | | | 孟维伟 | 山东省农业科学院, 济南 250100 | | | 于海秋 | 沈阳农业大学农学院, 沈阳 110866 | | | 谢立勇 | 沈阳农业大学农学院, 沈阳 110866 | xly0910@163.com | | 张正 | 山东省农业科学院, 济南 250100 | kyczhang@sina.com | | 万书波 | 山东省农业科学院, 济南 250100 | |
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| 中文摘要 |
| 通过明确谷子花生4:4间作对黄河下游农田土壤细菌群落结构及其多样性的影响,探索农田土壤肥力对谷子花生间作模式响应的微生态变化特性,为促进黄河下游农田生态修复和耕地质量提升提供参考依据.采用Illumina MiSeq高通量测序技术与QIIME 2平台,分析单作谷子(SM)、单作花生(SP)、间作谷子(IM)、间作花生(IP)和谷子花生间作(MP)这5种土壤的细菌群落组成差异及其影响因素,并预测其生态功能.结果表明,间作土壤细菌群落α多样性与单作存在差异,但不显著, β多样性则具有显著差异(P<0.05); 所有土壤样品共获得7081 ASV,划分为34门、109纲、256目、396科、710属和1409种,其中共有的ASV为727个,在5种土壤中占24.5%~27.8%; 谷子花生间作及其单作土壤细菌群落的菌门组成相似,但相对丰度各异; 5种土壤均以放线菌门、变形菌门、酸杆菌门和绿弯菌门为主,相对丰度可达79.40%~81.33%; 土壤有机碳和碱解氮分别是引起5种土壤细菌群落结构门、属水平产生差异的最主要因子; 通过PICRUSt功能预测发现,初级功能新陈代谢的相对丰度最大(78.9%~79.3%),次级功能外源生物降解与代谢的相对丰度波动最大(CV=3.782%); 在BugBase表型方面,间作谷子或花生土壤较相应单作的氧化胁迫耐受细菌相对丰度增加,且间作谷子土壤较单作谷子显著增加(P<0.05); 氧化胁迫耐受、革兰氏阳性及需氧三类表型细菌间两两极显著正相关(P<0.01),且三者均与潜在致病性、革兰氏阴性及厌氧呈极显著负相关(P<0.01).由此可见,谷子花生间作改变了土壤细菌群落多样性、丰富度和代谢功能,存在降低潜在土壤病害发生的可能性,可用于调控土壤微生态环境,以推动黄河下游农田生态修复和农业可持续发展. |
| 英文摘要 |
| The objective of this study was to explore the microecological variability in farmland soil fertility in response to millet-peanut intercropping patterns by clarifying the effects of millet-peanut 4:4 intercropping on soil bacterial community structure and its diversity, as well as to provide a reference basis for promoting ecological restoration and arable land quality improvement in the lower Yellow River farmland. The Illumina MiSeq high-throughput sequencing technology and QIIME 2 platform were used to analyze the differences in bacterial community composition and their influencing factors in five soils[sole millet (SM), sole peanut (SP), intercropping millet (IM), intercropping peanut (IP), and millet-peanut intercropping (MP)] and to predict their ecological functions. The results showed that the α-diversity of intercropping soil bacterial communities differed from that of monocropping, though not significantly, whereas the β-diversity was significantly different (P<0.05). A total of 7081 ASVs were obtained from all soil samples, classified into 34 phyla, 109 orders, 256 class, 396 families, 710 genera, and 1409 species, of which 727 ASVs were shared, accounting for 24.5% to 27.8% in five soil species. The bacterial communities of millet-peanut intercropping and its monocropping soils were similar in phylum composition but varied in relative abundance. All five soils were dominated by the Actinobacteria, Proteobacteria, Acidobacteria, and Chloroflexi, with a relative abundance of 79.40%-81.33%. Soil organic carbon and alkaline nitrogen were the most important factors causing differences in the structures of the five soil bacterial communities at the phylum and genus levels, respectively. The PICRUSt functional prediction revealed that the relative abundance of primary functional metabolism was the largest (78.9%-79.3%), and the relative abundance of secondary functional exogenous biodegradation and metabolism fluctuated the most (CV=3.782%). In terms of the BugBase phenotype, the relative abundance of oxidative stress-tolerant bacteria increased in intercropping millet or peanut soils compared to that in the corresponding monocultures and significantly increased in intercropping millet soils compared to that in sole millet (P<0.05). Oxidative stress-tolerant, Gram-positive, and aerobic phenotypes were highly significantly positively correlated with each other (P<0.01), and all three showed highly significant negative correlations with potential pathogenicity and Gram-negative and anaerobic phenotypes (P<0.01). This showed that millet-peanut intercropping resulted in differences in soil bacterial community diversity, abundance, and metabolic functions and the possibility of reducing the occurrence of potential soil diseases. It can be used to regulate the soil microbiological environment to promote ecological restoration and sustainable development of farmland in the lower Yellow River. |
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