Key Laboratory of Sugarcane Biology and Genetic Breeding, Ministry of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
College of Agricultural, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
Microb Ecol. 2022 Nov;84(4):1195-1211. doi: 10.1007/s00248-021-01932-3. Epub 2021 Nov 24.
Fertilizers and microbial communities that determine fertilizer efficiency are key to sustainable agricultural development. Sugarcane is an important sugar cash crop in China, and using bio-fertilizers is important for the sustainable development of China's sugar industry. However, information on the effects of bio-fertilizers on sugarcane soil microbiota has rarely been studied. In this study, the effects of bio-fertilizer application on rhizosphere soil physicochemical indicators, microbial community composition, function, and network patterns of sugarcane were discussed using a high-throughput sequencing approach. The experimental design is as follows: CK: urea application (57 kg/ha), CF: compound fertilizer (450 kg/ha), BF1: bio-fertilizer (1500 kg/ha of bio-fertilizer + 57 kg/ha of urea), and BF2: bio-fertilizer (2250 kg/ha of bio-fertilizer + 57 kg/ha of urea). The results showed that the bio-fertilizer was effective in increasing sugarcane yield by 3-12% compared to the CF treatment group, while reducing soil acidification, changing the diversity of fungi and bacteria, and greatly altering the composition and structure of the inter-root microbial community. Variance partitioning canonical correspondence (VPA) analysis showed that soil physicochemical variables explained 80.09% and 73.31% of the variation in bacteria and fungi, respectively. Redundancy analysis and correlation heatmap showed that soil pH, total nitrogen, and available potassium were the main factors influencing bacterial community composition, while total soil phosphorus, available phosphorus, pH, and available nitrogen were the main drivers of fungal communities. Volcano plots showed that using bio-fertilizers contributed to the accumulation of more beneficial bacteria in the sugarcane rhizosphere level and the decline of pathogenic bacteria (e.g., Leifsonia), which may slow down or suppress the occurrence of diseases. Linear discriminant analysis (LDA) and effect size analysis (LEfSe) searched for biomarkers under different fertilizer treatments. Meanwhile, support vector machine (SVM) assessed the importance of the microbial genera contributing to the variability between fertilizers, of interest were the bacteria Anaerolineace, Vulgatibacter, and Paenibacillus and the fungi Cochliobolus, Sordariales, and Dothideomycetes between CF and BF2, compared to the other genera contributing to the variability. Network analysis (co-occurrence network) showed that the network structure of bio-fertilizers was closer to the network characteristics of healthy soils, indicating that bio-fertilizers can improve soil health to some extent, and therefore if bio-fertilizers can be used as an alternative to chemical fertilizers in the future alternative, it is important to achieve green soil development and improve the climate.
肥料和决定肥料效率的微生物群落是可持续农业发展的关键。甘蔗是中国重要的糖料作物，生物肥料的使用对中国糖业的可持续发展至关重要。然而，关于生物肥料对甘蔗土壤微生物群落影响的信息很少被研究。在这项研究中，采用高通量测序方法探讨了生物肥料的应用对根际土壤理化指标、微生物群落组成、功能和网络模式的影响。实验设计如下：CK：尿素处理（57kg/ha），CF：复合肥处理（450kg/ha），BF1：生物肥料处理（1500kg/ha 生物肥料+57kg/ha 尿素），BF2：生物肥料处理（2250kg/ha 生物肥料+57kg/ha 尿素）。结果表明，与 CF 处理组相比，生物肥料可有效提高甘蔗产量 3-12%，同时减少土壤酸化，改变真菌和细菌的多样性，极大地改变根间微生物群落的组成和结构。典范对应分析（VPA）表明，土壤理化变量分别解释了细菌和真菌变异的 80.09%和 73.31%。冗余分析和相关热图表明，土壤 pH 值、全氮和速效钾是影响细菌群落组成的主要因素，而土壤全磷、速效磷、pH 值和速效氮是影响真菌群落的主要驱动因素。火山图表明，使用生物肥料有助于在甘蔗根际水平积累更多有益细菌，并减少病原菌（如 Leifsonia）的积累，这可能减缓或抑制疾病的发生。线性判别分析（LDA）和效应量分析（LEfSe）在不同肥料处理下寻找生物标志物。同时，支持向量机（SVM）评估了对肥料间变异性有贡献的微生物属的重要性，有趣的是 CF 和 BF2 之间的细菌 Anaerolineace、Vulgatibacter 和 Paenibacillus 以及真菌 Cochliobolus、Sordariales 和 Dothideomycetes，与其他对变异性有贡献的属相比。网络分析（共现网络）表明，生物肥料的网络结构更接近健康土壤的网络特征，表明生物肥料在一定程度上可以改善土壤健康，因此，如果生物肥料可以在未来替代化肥，实现绿色土壤发展，改善气候非常重要。
