Incidence of resistance to ALS and ACCase inhibitors in Echinochloa species and soil microbial composition in Northern Italy

Abstract

The increasing amount of weeds surviving herbicide represents a very serious problem for crop management. The interaction between microbial community of soil and herbicide resistance, along with the potential evolutive consequences, are still poorly known and need to be investigated to better understand the impact on agricultural management. In our study, we analyzed the microbial composition of soils in 32 farms, located in the Northern Italy rice-growing area (Lombardy) with the aim to evaluate the relationship between the microbial composition and the incidence of resistance to acetolactate synthase (ALS) and acetyl-CoA carboxylase (ACCase) inhibiting herbicides in Echinochloa species. We observed that the coverage of weeds survived herbicide treatment was higher than 60% in paddy fields with a low microbial biodiversity and less than 5% in those with a high microbial biodiversity. Fungal communities showed a greater reduction in richness than Bacteria. In soils with a reduced microbial diversity, a significant increase of some bacterial and fungal orders (i.e. Lactobacillales, Malasseziales and Diaporthales) was observed. Interestingly, we identified two different microbial profiles linked to the two conditions: high incidence of herbicide resistance (H-HeR) and low incidence of herbicide resistance (L-HeR). Overall, the results we obtained allow us to make hypotheses on the greater or lesser probability of herbicide resistance occurrence based on the composition of the soil microbiome and especially on the degree of biodiversity of the microbial communities.

Figure 1

(a) map of the land use in the Lombardy region (SIARL 2019; DUSAF 7.0, 2023). The rice cropping area, in the provinces of Pavia and Milano is bordered in red. (b) distribution of the rice farms (FR) where E. crus-galli and E. oryzicola survived herbicide were detected. The maps were generated through Q-GIS software, version 3.32 Lima (http://qgis.osgeo.org).

Figure 2

Heatmap and bootstrap-based hierarchical clustering based on “Bray-Curtis” distance and “ward.D2” algorithm. The incidence of resistant Echinochloa spp. (HeR-green), the prevalence of bacterial and archaeal (blue) and of fungal (red) orders were considered. FR.: rice farm. N.I.: taxa not identified. Other: all orders with a prevalence value < 5%. au: approximately unbiased. bp: bootstrap probability.

Figure 3

Principal Coordinates Analysis (PCoA) of the 32 soil samples collected. Values on brackets represent the percent variation explained by coordinate 1 and coordinate 2 respectively. For microbial communities, the taxonomic rank of order was considered. Blue arrows: bacterial and archaeal orders. Red arrows: fungal orders. Red ellipse: L-HeR soils group. Yellow ellipse: M-HeR soils group. Blue ellipse: H-HeR soils group. Ellipses assumed a multivariate normal distribution. Confidence level: 0.99.

Figure 4

Redundancy analysis (RDA) ordination diagram of the first two axes for the incidence of herbicide resistance (HeR). Values on brackets represent the percent variation explained by axis 1 and axis 2 respectively. The constrained sets of bacterial, archaeal and fungal orders analyzed are indicated as vectors. Lactobacillales, Rhizobiales, Solibacterales, Malasseziales and Diaporthales resulted in a significant relation with HeR incidence in the RDA (anova.cca, P < 0.01**).

Figure 5

Microbial orders (mean ± standard error) with different abundance in H-HeR and L-HeR paddies. (a) Bacteria plus Archaea. (b) Fungi. Mann–Whitney test (two tailed); *P < 0.05; **P < 0.01.

Figure 6

Heatmap and bootstrap-based hierarchical clustering based on “Canberra” distance and “ward.D2” algorithm. The incidence of resistant Echinochloa spp. (HeR) (green) and of the physical–chemical properties of soils (brown) were considered. au: approximately unbiased. bp: bootstrap probability.