Impact of integrated nutrient management on soil microbiome diversity and health in rice based cropping system: Insights from long-term agricultural practices

IF 3.5 3区 生物学 Q1 PLANT SCIENCES Rhizosphere Pub Date : 2025-02-12 DOI:10.1016/j.rhisph.2025.101048
Subhojit Datta , Sonali Paul Mazumdar , Bijan Majumdar , N.M. Alam , Lipi Chattopadhyay , Sourav Ghosh , Dipnarayan Saha , Amit Ranjan Saha , Gouranga Kar
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Abstract

The rhizosphere soil microbiomes, which are essential for plant development, stress adaptability, and general soil health, are greatly impacted by agricultural management practices, particularly those involving nutrient applications. This study evaluated the long-term effects of nutrient management practices on soil physicochemical properties, microbial communities, enzyme activities, and biological soil health in a rice-lentil-jute cropping system. The treatments included a control, inorganic fertilizers (recommended dose of fertilizers), and Soil Test Crop Response based integrated nutrient management (combination of inorganic fertilizer based on soil test-based fertilizer prescription equations, farmyard manure (FYM), and bioinoculants). When compared to both control and inorganic treatments, integrated nutrient management (INM) enhanced soil organic carbon, available nitrogen, phosphorus, and potassium. Microbial populations, comprising of bacteria, actinomycetes, fungi, Azotobacter, and phosphate-solubilizing microorganisms, along with soil enzymatic activities, showed marked increases under INM. Metagenomic analysis of the hypervariable V3-V4 region of 16S rRNA indicated that the bacterial community in the rice-lentil-jute cropping sequence was dominated by Proteobacteria, with 58 phyla having over 1% abundance. The INM treatment increased the Shannon diversity index by 12.6% compared to the control, reflecting improved microbial diversity, richness, and resilience, which are critical for enhancing crop productivity and stress tolerance. The Biological Soil Health Index (BSHI) was highest in the INM treatment, with average contributions from Azotobacter (22.7%), Bacteroidota (12.1%), Actinobacteriota (21.9%), very labile organic carbon (23.1%), and labile organic carbon (20.2%) to BSHI. In summary, ten years of INM enhanced soil health and bacterial community structure and composition, leading to sustainable crop yields in rice-based cropping system. These findings highlight the necessity of integrating balanced nutrient management in long-term agricultural practices.

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综合养分管理对水稻种植系统土壤微生物群多样性和健康的影响:来自长期农业实践的见解
根际土壤微生物群对植物发育、逆境适应能力和总体土壤健康至关重要,它们受到农业管理做法,特别是涉及养分施用的农业管理做法的极大影响。本研究评估了养分管理措施对水稻-扁豆-黄麻种植系统土壤理化性质、微生物群落、酶活性和土壤生物健康的长期影响。处理包括对照、无机肥料(推荐用量)和基于土壤试验作物反应的综合养分管理(基于土壤试验肥料处方方程的无机肥料、农家肥(FYM)和生物接种剂的组合)。与对照处理和无机处理相比,综合养分管理(INM)提高了土壤有机碳、速效氮、磷和钾。微生物种群,包括细菌、放线菌、真菌、固氮菌和磷酸盐溶解微生物,以及土壤酶活性在INM下显着增加。16S rRNA高变区V3-V4区宏基因组分析表明,水稻-小豆豆-黄麻种植序列细菌群落以变形菌属(Proteobacteria)为主,丰度超过1%的有58个门。与对照相比,INM处理使Shannon多样性指数提高了12.6%,反映出微生物多样性、丰富度和恢复力的提高,这对提高作物生产力和抗逆性至关重要。INM处理土壤生物健康指数(BSHI)最高,固氮菌(22.7%)、拟杆菌(12.1%)、放线菌(21.9%)、极不稳定有机碳(23.1%)和不稳定有机碳(20.2%)对BSHI的平均贡献最大。综上所述,10年的INM改善了土壤健康和细菌群落结构和组成,实现了水稻种植系统的可持续作物产量。这些发现强调了在长期农业实践中整合均衡营养管理的必要性。
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来源期刊
Rhizosphere
Rhizosphere Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
5.70
自引率
8.10%
发文量
155
审稿时长
29 days
期刊介绍: Rhizosphere aims to advance the frontier of our understanding of plant-soil interactions. Rhizosphere is a multidisciplinary journal that publishes research on the interactions between plant roots, soil organisms, nutrients, and water. Except carbon fixation by photosynthesis, plants obtain all other elements primarily from soil through roots. We are beginning to understand how communications at the rhizosphere, with soil organisms and other plant species, affect root exudates and nutrient uptake. This rapidly evolving subject utilizes molecular biology and genomic tools, food web or community structure manipulations, high performance liquid chromatography, isotopic analysis, diverse spectroscopic analytics, tomography and other microscopy, complex statistical and modeling tools.
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