Soil Microbiome Responses to Sustainable Agricultural Practices

作者
Dragana Bjelić,Jelena Marinković,Marjana Vasiljević,Vuk Đorđević,Marie Aristea Bakogianni,Nikolaos Nikoloudakis,Ioannis Manikas
出处
期刊:Agriculture [Multidisciplinary Digital Publishing Institute]
卷期号:16 (18): 1957-1957 被引量:1
标识
DOI:10.3390/agriculture16181957
摘要

Agricultural practices based on sustainable principles (e.g., conservation tillage, crop rotation, cover cropping, and the application of organic inputs) have been tested for their potential to improve soil structure, enhance soil organic matter, and support agrobiodiversity. These practices are directly linked to soil microbial diversity. Diverse soil microbial communities play multiple roles in promoting beneficial interactions between plants and their environment and in maintaining functional agroecosystems. Key functions enabled by soil microorganisms are carbon dynamics, nutrient cycling, soil structure improvement, pathogen suppression, plant growth promotion, and stress tolerance. Soil microorganisms are increasingly recognized as a promising but still underexploited source in tackling sustainability challenges in agricultural production. However, their potential varies depending on the interactions among abiotic and biotic factors, as well as the applied cultivation practices. In recent decades, advances in DNA extraction from soil and next-generation sequencing (NGS) technologies have enabled comprehensive characterization of microbial diversity, community composition, and functional potential for assessing soil health and agroecosystem functioning. Understanding, predicting, and exploring relevant plant–soil–microbiome interactions are essential for enhancing agroecosystem capacity for sustainable production. This review paper highlights how different factors and agricultural practices affect microbiome biodiversity. The focus is on microbiome approaches that integrate information on community composition with assessments of functional potential and measured microbial activity and ecosystem processes, combining state-of-the-art molecular monitoring, ecological indicators, and predictive modeling to support evidence-based management recommendations, distinguishing approaches that are currently applicable in agricultural practice from those that require further experimental validation.

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