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Unlike carbon, water, and nitrogen, phosphorus is not present in the atmosphere as a gas. Instead, most phosphorus in the ecosystem exists as compounds, such as phosphate ions (PO43-), found in soil, water, sediment and rocks. Phosphorus is often a limiting nutrient (i.e., in short supply). Consequently, phosphorus is added to most agricultural fertilizers, which can cause environmental problems related to runoff in aquatic ecosystems.
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Phosphate-solubilizing fungus (PSF) - mediated phosphorous solubilization and validation through Artificial

Fatih Ölmez1, Zemran Mustafa2, Şahimerdan Türkölmez3

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Phosphate-solubilizing fungus (PSF) strain, Aspergillus funiculosus, significantly enhances phosphorus solubility across various phosphate sources and pH levels. Artificial intelligence models validated these findings, highlighting potential for sustainable agriculture.

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Area of Science:

  • Microbiology and Soil Science
  • Agricultural Biotechnology
  • Computational Biology

Background:

  • Phosphorus (P) is a crucial nutrient for plant growth, often limited by its low solubility in soil.
  • Phosphate-solubilizing fungi (PSF) offer a sustainable approach to enhance phosphorus availability in agricultural systems.
  • Aspergillus funiculosus is a known PSF, but its efficacy across diverse conditions and its optimization require further investigation.

Purpose of the Study:

  • To investigate the phosphorus solubilization potential of Aspergillus funiculosus across various phosphate sources and pH levels.
  • To validate and predict experimental data using artificial intelligence (AI) and machine learning (ML) models.
  • To identify optimal conditions for maximizing phosphorus solubilization by T. funiculosus.

Main Methods:

  • Culturing Aspergillus funiculosus with five different phosphate sources (Ca3(PO4)2, FePO4, CaHPO4, AlPO4, phytin) at five pH levels (4.5-7.5).
  • Statistical analysis using ANOVA, Pareto charts, and normal plots.
  • AI/ML model development and validation using Multilayer Perceptron (MLP), Random Forest (RF), and Extreme Gradient Boosting (XGBoost).

Main Results:

  • Aspergillus funiculosus demonstrated a five-fold increase in phosphate solubility compared to the control.
  • Optimal conditions for maximum soluble P were observed at pH 4.5 and with CaHPO4 as the phosphate source.
  • The combination of phytin and pH 4.5 yielded the highest dissolved phosphorus (1,537,988 ppb). RF model achieved the highest R² score (0.944).

Conclusions:

  • Aspergillus funiculosus exhibits significant potential for solubilizing various phosphate sources, particularly under acidic conditions.
  • AI/ML models effectively validated experimental results, demonstrating their utility in predicting microbial solubilization efficiency.
  • The findings support the sustainable application of Aspergillus funiculosus in agriculture for improving phosphorus availability.