Plant secondary metabolite-dependent plant-soil feedbacks can improve crop yield in the field

Abstract

Plant secondary metabolites that are released into the rhizosphere alter biotic and abiotic soil properties, which in turn affect the performance of other plants. How this type of plant-soil feedback affects agricultural productivity and food quality in the field in the context of crop rotations is unknown. Here, we assessed the performance, yield and food quality of three winter wheat varieties growing in field plots whose soils had been conditioned by either wild type or benzoxazinoid-deficient bx1 maize mutant plants. Following maize cultivation, we detected benzoxazinoid-dependent chemical and microbial fingerprints in the soil. The benzoxazinoid fingerprint was still visible during wheat growth, but the microbial fingerprint was no longer detected. Wheat emergence, tillering, growth, and biomass increased in wild type conditioned soils compared to bx1 mutant conditioned soils. Weed cover was similar between soil conditioning treatments, but insect herbivore abundance decreased in benzoxazinoid-conditioned soils. Wheat yield was increased by over 4% without a reduction in grain quality in benzoxazinoid-conditioned soils. This improvement was directly associated with increased germination and tillering. Taken together, our experiments provide evidence that soil conditioning by plant secondary metabolite producing plants can increase yield via plant-soil feedbacks under agronomically realistic conditions. If this phenomenon holds true across different soils and environments, optimizing root exudation chemistry could be a powerful, genetically tractable strategy to enhance crop yields without additional inputs.

Soil chemical and microbial gradients determine accumulation of root‐exuded secondary metabolites and plant–soil feedbacks in the field

“…A possible explanation for this is that root and rhizosphere microbiota are shaped directly by root-exuded benzoxazinoids, which were shown to be unaffected by soil parameters (Figure 5b). In line with our previous field study (Gfeller, Waelchli, et al, 2023), chemical but not microbiota patterns persisted to the next crop generation. This is in contrast to previous pot and container experiments, where microbial fingerprints from the soil conditioning phase were still present during the feedback plant's growth (Hannula et al, 2021;Hu, Robert, et al, 2018).…”

“…The extraction of benzoxazinoids and their degradation products from soil, as well as the analytical protocol, are detailed in the Supporting Information: Methods, where we also list the measured compounds with their abbreviations, chemical name and where they were sourced from. Benzoxazinoids and degradation products were analysed with an Acquity UHPLC system coupled to a G2-XS QTOF mass spectrometer (Waters AG) as previously described (Gfeller, Waelchli et al, 2023).…”

“…The Supporting Information: Methods contains the details of sample preparation, DNA extraction and the polymerase chain reaction (PCR) protocol for microbiota profiling. In brief, the collected samples were processed as previously described (Gfeller, Waelchli, et al, 2023), and DNA was extracted using the Spin Kit for Soil (MP Biomedical), following the instructions of the manufacturer. After DNA quantification using the AccuClear Ultra High Sensitivity dsDNA Quantitation Kit (Biotium), bacterial and fungal libraries were constructed largely following our two-step PCR profiling protocol described earlier (Gfeller, Waelchli, et al, 2023).…”

“…In brief, the collected samples were processed as previously described (Gfeller, Waelchli, et al, 2023), and DNA was extracted using the Spin Kit for Soil (MP Biomedical), following the instructions of the manufacturer. After DNA quantification using the AccuClear Ultra High Sensitivity dsDNA Quantitation Kit (Biotium), bacterial and fungal libraries were constructed largely following our two-step PCR profiling protocol described earlier (Gfeller, Waelchli, et al, 2023). Briefly, bacterial and fungal profiles were based on PCR primer pairs 799-F (Chelius & Triplett, 2001) and 1193-R (Bodenhausen et al, 2013) and ITS1-F (Gardes & Bruns, 1993) and ITS2-R (White et al, 1990), respectively.…”

“…The raw sequencing data are available from the European Nucleotide Archive (http://www.ebi.ac.uk/ena) with the study accession PRJEB59165 (sample IDs ERS14468209 and ERS14468210). The sequencing data were processed as previously described (Gfeller, Waelchli, et al, 2023). In short, the bioinformatic pipeline includes the following tools: FastQC and cutadapt (Andrews, 2010;Martin, 2011), DADA2 (Callahan et al, 2016) and databases SILVA v.132 (Callahan, 2018;Quast et al, 2013) and UNITE v8.1 (Nilsson et al, 2019) for bacterial and fungal taxonomy.…”