Sugarcane (Saccharum officinarum L.) is one of the world’s most important agro-industrial crops, and the technological quality of its juice directly determines the efficiency of sucrose extraction and recovery processes. In tropical soils with low P availability, conventional fertilization is often inefficient due to nutrient immobilization, which increases production costs and environmental risks. In this regard, plant growth-promoting bacteria (PGPBs) have emerged as a sustainable alternative to improve nutrient use efficiency. This study evaluated the effect of inoculation with A. brasilense, P. fluorescens, and B. subtilis (single strains and consortia), combined with two levels of residual p (160 and 225 kg P₂O₅·ha⁻¹), on the technological quality of the juice and the microbial dynamics of the rhizosphere. The experiment was conducted under tropical field conditions using a randomized complete block design with split plots and five replications. A highly significant interaction between phosphorus and inoculation (p < 0.001) was observed for °Brix, Pol, purity, and sucrose. The B. subtilis + P. fluorescens consortium under reduced phosphorus (160 kg P₂O₅·ha⁻¹) achieved the highest values for sucrose (17.26%), °Brix (20.32), and purity (87.03%). A linear regression model showed that rhizosphere microbial density explained a large proportion of the variability in sucrose (R² = 0.96; β = 2.02; p < 0.001). Principal component analysis explained 91.8% of the total variance, clearly separating the consortia from the individual strains and the controls. These results indicate that PGPB consortia, combined with moderate pH fertilization, can improve the technological quality of sugarcane while enhancing rhizosphere functionality, representing a promising strategy for more sustainable production systems in tropical environments.

This article presents an innovative methodology that integrates Dual STATIS analysis with neutrosophic logic to evaluate the stability of the structure of relationships among financial variables in savings and credit cooperatives. The developed approach makes it possible to incorporate the uncertainty present in financial indicators and analyze their temporal evolution. Unlike classical STATIS, which focuses on similarity among cooperatives, the dual approach analyzes the covariance structure among the variables, identifying stable latent dimensions and turning points in the cooperative system. The results reveal patterns of structural stability and significant changes associated with relevant economic events, including the impact of the COVID-19 pandemic. The proposed methodology constitutes a useful alternative for strengthening financial supervision processes and supporting strategic decision-making in the cooperative sector.