在这项研究中,我们采用跨学科的方法,将农艺田间试验与土壤化学相结合,分子生物学技术,和统计数据来调查有机残留修正的影响,如酒糟(甘蔗乙醇生产的副产品),对土壤微生物组和温室气体(GHG)生产的影响。这项研究调查了不同干扰的影响,包括有机残留物单独施用或与无机氮肥结合施用。这些方法评估了土壤微生物组动态(组成和功能),温室气体排放,和植物生产力。现场实验设置的详细步骤,土壤取样,土壤化学分析,细菌和真菌群落多样性的测定,定量与硝化和反硝化途径相关的基因,气体通量(N2O,CH4和CO2),并提供了植物生产力的测定。这些方法的结果在我们的出版物中有详细的介绍(Lourenço等人。,2018a;洛伦索等人。,2018b;洛伦索等人。,2019年;洛伦索等人。,2020)。此外,概述了用于分析大型数据集的统计方法和脚本。目的是通过解决大规模现场实验中的共同挑战来帮助研究人员,提供切实可行的建议,以避免常见的陷阱,并提出潜在的分析,从而鼓励不同研究小组之间的合作。•跨学科方法和科学问题允许探索更广泛的相互联系的环境问题。•所提出的方法可以作为评估土壤改良剂对土壤微生物组的影响的模型和协议,温室气体排放,和植物生产力,促进更可持续的管理实践。•时间序列数据可以提供对特定生态系统的详细见解,特别是关于土壤微生物群(分类学和功能)。
In this study, we adopt an interdisciplinary approach, integrating agronomic field experiments with soil chemistry, molecular biology techniques, and statistics to investigate the impact of organic residue amendments, such as vinasse (a by-product of sugarcane ethanol production), on soil microbiome and greenhouse gas (GHG) production. The research investigates the effects of distinct disturbances, including organic residue application alone or combined with inorganic N fertilizer on the environment. The methods assess soil microbiome dynamics (composition and function), GHG emissions, and plant productivity. Detailed steps for field experimental setup, soil sampling, soil chemical analyses, determination of bacterial and fungal community diversity, quantification of genes related to nitrification and denitrification pathways, measurement and analysis of gas fluxes (N2O, CH4, and CO2), and determination of plant productivity are provided. The outcomes of the methods are detailed in our publications (Lourenço et al., 2018a; Lourenço et al., 2018b; Lourenço et al., 2019; Lourenço et al., 2020). Additionally, the statistical methods and scripts used for analyzing large datasets are outlined. The aim is to assist researchers by addressing common challenges in large-scale field experiments, offering practical recommendations to avoid common pitfalls, and proposing potential analyses, thereby encouraging collaboration among diverse research groups.•Interdisciplinary methods and scientific questions allow for exploring broader interconnected environmental problems.•The proposed method can serve as a model and protocol for evaluating the impact of soil amendments on soil microbiome, GHG emissions, and plant productivity, promoting more sustainable management practices.•Time-series data can offer detailed insights into specific ecosystems, particularly concerning soil microbiota (taxonomy and functions).