Effect of conservation agriculture on soil fungal diversity in rice-wheat-greengram cropping system in eastern Indo-Gangetic plains of South Asia

Abstract

Introduction: Conservation agriculture (CA) is emerging as an eco-friendly and sustainable approach to food production in South Asia. CA, characterized by reduced tillage, soil surface cover through retaining crop residue or raising cover crops, and crop diversification, enhances crop production and soil fertility. Fungal communities in the soil play a crucial role in nutrient recycling, crop growth, and agro-ecosystem stability, particularly in agricultural crop fields.

Methods: This study investigates the impact of seven combinations of tillage and crop residue management practices of agricultural production systems, including various tillage and crop residue management practices, on soil fungal diversity. Using the Illumina MiSeq platform, fungal diversity associated with soil was analysed.

Results and discussion: The results show that the partial CA-based (pCA) production systems had the highest number of unique operational taxonomic units (OTUs) (948 OTUs) while the conventional production system had the lowest number (665 OTUs). The major fungal phyla identified in the topsoil (0-15 cm) were Ascomycota, Basidiomycota, and Mortierellomycota, with their abundance varying across different tillage-cum-crop establishment (TCE) methods. Phylum Ascomycota was dominant in CA-based management treatments (94.9±0.62), followed by the partial CA (pCA)-based treatments (91.0 ± 0.37). Therefore, CA-based production systems play a crucial role in shaping soil fungal diversity, highlighting their significance for sustainable agricultural production.

Keywords: Illumina MiSeq; soil fungal diversity; soil parameters; sustainable agriculture; zero-tillage.

Figure 1

Unique and shared operational taxonomic units (OUTs) illustrated by Venn diagram across various conservation agriculture-based production systems.

Figure 2

Box plots represent different diversity indices (Ace (A), Chao1 (B), Shannon (C), Simpson (D), Observed (E) and Fisher (F)) among conservation agriculture-based production systems. Alphabets above box indicate significant differences among agricultural practices, (p < 0.05). Colors denote the different treatments on experiment.

Figure 3

Beta diversity, as illustrated by principal coordinate analysis (PCoA) based on the Bray–Curtis dissimilarity index, indicates significant differences in fungus composition among different treatments of conservation agriculture-based production systems (ANOSIM R = 0.70909, p < 0.001). T1-First treatment, T2-Second treatment, T3-Third treatment, T4-Fourth treatment, T5-Fifth treatment, T6-Sixth treatment, T7-Seventh treatment.

Figure 4

Relative abundance of dominant fungus at the class level among different treatments of conservation agriculture-based production system. The significant difference is indicated by ‘*’.

Figure 5

The relative abundance of dominanting order among different treatments of conservation agriculture-based production systems. The standard errors of the mean are represented by whiskers.

Figure 6

Relative abundance of dominating genus among different treatments of conservation agriculture-based production system. The standard errors of mean (SEm) are represented by whiskers.

Figure 7

The different soil parameters, major fungal phyla, and earthworm count were revealed using PCA coordinates of different treatments of conservation agriculture-based production systems.

Figure 8

Soil Quality Index (SQI) is influenced by different tillage and crop establishment scenarios. Standard errors of the mean are represented by vertical bars. Different small letters indicate significant differences at p ≤ 0.05.