Microbial community profiling of commercial pellet-based biofertilizers from Malaysia for comparative quality control insights

WAI KEAT TOH (Department of Biological Science, Faculty of Science, Universiti Tunku Abdul Rahman. Jl. Universiti, Bandar Barat, 31900 Kampar, Perak, Malaysia)
HAN MING GAN (Patriot Biotech Sdn. Bhd, Bandar Sunway, 47500 Selangor, Malaysia)
PEK CHIN LOH (Department of Biological Science, Faculty of Science, Universiti Tunku Abdul Rahman. Jl. Universiti, Bandar Barat, 31900 Kampar, Perak, Malaysia)
HANN LING WONG (Department of Biological Science, Faculty of Science, Universiti Tunku Abdul Rahman. Jl. Universiti, Bandar Barat, 31900 Kampar, Perak, Malaysia)

Biodiversitas Journal of Biological Diversity
Vol. 27 No. 4 (2026)

Abstract. Toh WK, Gan HM, Loh PC, Wong HL. 2026. Microbial community profiling of commercial pellet-based biofertilizers from Malaysia for comparative quality control insights. Biodiversitas 27 (4): d270401. https://doi.org/10.13057/biodiv/d270401. The efficacy and reliability of biofertilizers depend on their microbial composition and product stability, yet robust quality control (QC) remains limited and comprehensive microbial profiling is not routinely applied. In this study, we characterized the microbial communities of 11 commercial pellet-based biofertilizers from Malaysia using 16S rRNA amplicon sequencing of the V3 region. A total of 35 samples from finished retail products collected within their labeled shelf-life period were analyzed. Across all samples, 3,839 unique amplicon sequence variants (ASVs) were detected, revealing substantial variation in microbial richness, diversity, and community structure among products. Alpha diversity metrics differed significantly among formulations (Kruskal-Wallis, p<0.01; η² = 0.86-0.89), indicating differences in within-sample richness and diversity. Beta diversity analyses showed strong formulation-specific clustering (PERMANOVA, R² = 0.863; ANOSIM, R = 0.81-0.88; p = 0.001), together with variable within-product consistency. Heatmap analysis of the 50 most abundant ASVs and bipartite network visualization identified a shared core microbiome dominated by Bacillus, Planifilum, and Weizmannia, alongside formulation-specific taxa. Predicted functional profiling showed high similarity in KEGG pathway composition despite taxonomic differences (mean Bray-Curtis dissimilarity = 0.31±0.15), suggesting functional redundancy across products. However, these functional predictions are computationally inferred and require experimental validation. Overall, sequencing-based microbial profiling provides a comparative framework for biofertilizer evaluation by informing QC-related attributes such as product consistency, microbial diversity, and compositional stability, thereby complementing conventional QC approaches.