Qiu Chongwen, Bao Yuanyuan, Petropoulos Evangelos, Wang Yiming, Zhong Zhenfang, Jiang Yaozhi, Ye Xuhong, Lin Xiangui, Feng Youzhi
Ministry of Agriculture Key Laboratory for Northeast Preservation of Cultivated Land, National Engineering Research Centre for Efficient Utilization of Soil and Fertilizer Resources, College of Land and Environment, Shenyang Agricultural University, Shenyang 110065, China.
Guangdong Haina Institute of Agriculture, Huizhou 516000, China.
Microorganisms. 2022 Feb 21;10(2):482. doi: 10.3390/microorganisms10020482.
The dynamic patterns of the belowground microbial communities and their corresponding metabolic functions, when exposed to various environmental disturbances, are important for the understanding and development of sustainable agricultural systems. In this study, a two-year field experiment with soils subjected to: chemical fertilization (F), mushroom residues (MR), combined application of chemical fertilizers and mushroom residues (MRF), and no-fertilization (CK) was conducted to evaluate the effect of fertilization on the soil bacterial taxonomic and functional compositions as well as on the rice yield. The highest rice yield was obtained under MRF. Soil microbial properties (microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), urease, invertase, acid phosphatase, and soil dehydrogenase activities) reflected the rice yield better than soil chemical characteristics (soil organic matter (SOM), total N (TN), total K (TK), available P (AP), available K (AK), and pH). Although the dominant bacterial phyla were not significantly different among fertilizations, 10 bacterial indicator taxa that mainly belonged to Actinobacteria (, , , and unclassified ) with functions of xenobiotic biodegradation and metabolism and amino acid and nucleotide metabolism were found to strongly respond to MRF. Random Forest (RF) modeling further revealed that these 10 bacterial indicator taxa act as drivers for soil dehydrogenase, acid phosphatase, pH, TK, and C/N cycling, which directly and/or indirectly determine the rice yield. Our study demonstrated the explicit links between bacterial indicator communities, community function, soil nutrient cycling, and crop yield under organic and inorganic amendments, and highlighted the advantages of the combined chemical and organic fertilization in agroecosystems.
地下微生物群落的动态模式及其相应的代谢功能在受到各种环境干扰时,对于理解和发展可持续农业系统至关重要。在本研究中,进行了一项为期两年的田间试验,土壤分别施加:化肥(F)、蘑菇渣(MR)、化肥与蘑菇渣联合施用(MRF)以及不施肥(CK),以评估施肥对土壤细菌分类和功能组成以及水稻产量的影响。在MRF处理下获得了最高的水稻产量。土壤微生物特性(微生物量碳(MBC)、微生物量氮(MBN)、脲酶、转化酶、酸性磷酸酶和土壤脱氢酶活性)比土壤化学特性(土壤有机质(SOM)、全氮(TN)、全钾(TK)、有效磷(AP)、有效钾(AK)和pH)更能反映水稻产量。尽管不同施肥处理下优势细菌门没有显著差异,但发现10个主要属于放线菌(、、和未分类的)的细菌指示类群,具有异源生物降解与代谢以及氨基酸和核苷酸代谢功能,对MRF有强烈响应。随机森林(RF)建模进一步表明,这10个细菌指示类群是土壤脱氢酶、酸性磷酸酶、pH、TK和碳氮循环的驱动因素,它们直接和/或间接决定水稻产量。我们的研究证明了在有机和无机改良措施下细菌指示群落、群落功能、土壤养分循环和作物产量之间的明确联系,并突出了化学与有机肥料联合施用在农业生态系统中的优势。