Organic Amendments and Trichoderma Change the Rhizosphere Microbiome and Improve Cucumber Yield and Fusarium Suppression

Abstract

Conventional chemical-based control methods for soil-borne diseases often degrade soil quality. The recycling of organic wastes offers a promising solution to simultaneously alleviate environmental pollution and restore soil health. As a beneficial fungus, Trichoderma plays a crucial role in enhancing plant performance. However, knowledge of the mechanisms through which organic wastes and Trichoderma interact to influence plant performance remains limited. We investigated how the combined application of organic wastes (chitin and straw) and a biocontrol fungus (Trichoderma) influenced the rhizosphere microbiome to improve plant performance. Compared with the control, organic waste alone, and Trichoderma alone treatments, the combined application of organic wastes and Trichoderma significantly (p < 0.05) increased cucumber yield and reduced pathogen density. Increased yield and reduced pathogen density were associated with changes in bacterial and fungal communities induced by this combined application treatment. Indeed, this combined application treatment enabled plants to recruit certain potentially beneficial core bacterial (e.g., Streptomyces and Flavisolibacter) and fungal taxa (e.g., Trichoderma), increasing their positive interactions in the rhizosphere. We demonstrate that the combined application of organic wastes and Trichoderma can shape distinct rhizosphere bacterial and fungal communities, promoting an increase in beneficial microorganisms and their positive interactions, which contribute to enhanced plant performance.

Keywords: Fusarium suppression; Trichoderma; chitin; cucumber yield; rhizosphere metagenomics; soil amendments; straw-waste.

Figure 1

Effects of the addition of different materials on cucumber yield (A) and pathogen density (B) in the field experiment and the relationship between cucumber yield and pathogen density (C). In (A,B), CK denotes control treatment; C denotes chitin addition treatment; S denotes straw addition treatment; T denotes the Trichoderma strain (T. guizhouense NJAU4742) addition treatment; CST denotes treatment with a mixture of straw, chitin and the Trichoderma strain (T. guizhouense NJAU4742). Units for yield are kg/ha; units for F. oxysporum density are lg copies/g soil. n = 9 and data are presented as mean ± SD. Statistical significance was calculated by Duncan’s test. Different letters represent a significant difference at p < 0.05 according to Duncan’s test. In (C), statistical significance was calculated by Spearman correlation.

Figure 2

Effects of the addition of different materials on the rhizosphere bacterial (A) and fungal (B) community composition. CK denotes control treatment; C denotes chitin addition treatment; S denotes straw addition treatment; T denotes the Trichoderma strain (T. guizhouense NJAU4742) addition treatment; CST denotes treatment with a mixture of straw, chitin and the Trichoderma strain (T. guizhouense NJAU4742). n = 9 and statistical significance was calculated by ANOSIM.

Figure 3

Rhizosphere bacterial (A) and fungal (B) taxa with both potentially yield-promoting and pathogen-suppressing functions.

Figure 4

Effects of the addition of different materials on rhizosphere bacterial (A) and fungal (B) taxa with both potentially growth-promoting and disease-suppressing functions in plants. In (A,B), CK denotes control treatment; C denotes chitin addition treatment; S denotes straw addition treatment; T denotes Trichoderma addition treatment; CST denotes treatment with a mixture of straw, chitin and the Trichoderma strain (T. guizhouense NJAU4742). n = 9 and data are presented as mean ± SD. Statistical significance was calculated by Duncan’s test. Different letters represent a significant difference at p < 0.05 according to Duncan’s test.

Figure 5

Relationships between core bacterial and fungal groups and both potentially growth-promoting and disease-suppressing functions in plants. B, bacteria; F, fungi. Relationships were calculated by Spearman correlation and p-values were adjusted with the false discovery rate method.