Genomics and Applied Biology 2026, Vol.17, No.1, 37-50 http://bioscipublisher.com/index.php/gab 45 reduced chemical fertilizer rates (75%) with bio-organic fertilizers containing beneficial microbes like Trichoderma maintained yields equivalent to full chemical fertilization but significantly increased fruit sugar (+24%) and vitamin C (+57%) while reducing nitrate accumulation (-62%) in tomatoes (Ye et al., 2020). Similarly, digestate-based organic fertilizers combined with chemical fertilizers increased tomato yield by up to 26% compared to chemical-only treatments under greenhouse conditions while improving fruit protein content and sugar-acid balance (Li et al., 2023). Soil health benefits include increased total nitrogen, organic carbon content, improved pH balance in acidic soils, enhanced enzyme activities (urease, catalase), and reduced bulk density following partial organic substitution (Dong et al., 2019; Fan et al., 2023). These improvements correlate positively with better plant growth parameters such as chlorophyll content and photosynthetic rate (Stoleru et al., 2020; Li et al., 2023). However, long-term studies suggest that moderate substitution ratios (~30%-60%) optimize sustainability by balancing yield gains with environmental impacts; full organic substitution may reduce yield despite improving some soil fertility indices due to nutrient imbalances or slower nutrient release rates (Han et al., 2025; Liu et al., 2025). Overall, partial replacement of chemical fertilizers with organic amendments offers a promising strategy for sustainable greenhouse tomato production by simultaneously enhancing soil microbial functions, crop quality, and environmental outcomes. 7 Research Methods and Analytical Techniques 7.1 Application of high-throughput sequencing in soil microbial studies High-throughput sequencing (HTS) has become a pivotal tool for investigating soil microbial communities due to its ability to provide comprehensive and high-resolution data on microbial composition and function. HTS techniques, including amplicon sequencing of marker genes (e.g., 16S rRNA for bacteria and ITS for fungi) and shotgun metagenomics, enable researchers to capture the vast diversity of soil microbes, many of which are unculturable by traditional methods (Zhang et al., 2021; Reid et al., 2025). These approaches allow detailed profiling of microbial taxa and functional genes, facilitating insights into how microbial communities respond to environmental changes such as organic fertilizer application in greenhouse soils. Moreover, HTS can be integrated with RNA sequencing to assess active microbial populations and their metabolic potential, providing a dynamic view of soil microbiomes (Reid et al., 2025). The use of co-assembly strategies in shotgun metagenomics further enhances genome recovery from complex soil samples, improving detection of rare taxa and functional genes (Johansen et al., 2025). This depth of sequencing is essential for understanding the intricate interactions within soil microbial communities that influence nutrient cycling and plant health in tomato cultivation systems. 7.2 Microbial diversity analysis and bioinformatics methods Analyzing microbial diversity from HTS data involves calculating alpha diversity metrics (e.g., species richness, Shannon index) to assess within-sample diversity, as well as beta diversity measures to compare community composition across samples (Xia et al., 2020; He et al., 2023). Bioinformatics pipelines typically include quality filtering, sequence clustering or denoising into operational taxonomic units (OTUs) or amplicon sequence variants (ASVs), taxonomic assignment using reference databases, and statistical analyses to identify significant differences among treatments or environmental gradients (Zhang et al., 2021; Edwin et al., 2025). These methods reveal how factors like organic fertilizer substitution alter bacterial and fungal community structures in greenhouse soils. Advanced analyses also incorporate network construction to explore microbial co-occurrence patterns and identify keystone taxa that drive ecosystem functions (Zhao et al., 2025). Functional prediction tools infer metabolic capabilities based on taxonomic profiles, linking community shifts to potential changes in nutrient cycling processes (Xia et al., 2020). The choice between amplicon versus shotgun sequencing depends on project goals; amplicon sequencing offers cost-effective community profiling while shotgun approaches provide deeper functional insights but require more computational resources (Edwin et al., 2025).
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