Abstract
Landfilling or incineration of fruit waste causes serious environmental problems and economic losses. Agricultural Jiaosu (AJ) can convert fruit waste into agricultural inputs. However, traditional AJ preparation requires large amounts of brown sugar and water, restricting its large-scale application. In this study, five types of single fruit waste and one type of mixed fruit waste were used to produce AJ without additional of sugar and water. The physicochemical properties and microbial community dynamics of AJ fermentation were analyzed, and the effects and potential mechanism of AJ in promoting pakchoi growth were evaluated. The results showed that during the digestion process, the pH value of all AJ gradually decreased to below 3.6. Organic acids were the main metabolites, lactic acid and acetic acid accounted for 46.55 %–99.22 % of all organic acids. As fermentation progressed, Firmicutes gradually replaced Proteobacteria as the most dominant phylum, accounting for 54.1 %–99.41 % of the microbial communities. After 90 days, Lactobacillus and Lentilactobacillus were the dominant genera in all AJ, accounting for 44.49 %–92.54 % of the communities. Structural equation modeling revealed that AJ promoted plant growth through organic acids and bacterial community. This study is the first time to propose the concept of producing AJ from fruit waste without additional sugar and water and reveals the fermentation characteristics and microbial dynamics of AJ, as well as its potential mechanism as a biological inoculant in promoting plant growth. This study provides a new approach for the large-scale utilization of fruit waste to produce green agricultural inputs.Abbreviations: AJ, agricultural Jiaosu; ANOVA, analysis of variance; ASVs, amplicon sequence variants; DNA, deoxyribonucleic acid; HPLC, high performance liquid chromatography; LDA, linear discriminant analysis; LEfSe, linear discriminant analysis effect size; PCoA, Principal coordinates analysis; PCR, polymerase chain reaction; RDA, redundancy analysis; rRNA, ribosomal RNA; SEM, structural equation modeling.
Published Version
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