The construction of a smallholder credit evaluation system based on biomechanical characteristics: A synergistic analysis of crop growth potential and risk management
Year: 2025
Type: article
Abstract: This study proposes an innovative credit evaluation system for small-scale farmers by integrating biomechanical characteristics analysis with traditional credit assessment methods. Through the Analytic Hierarchy Process (AHP), we develop a comprehensive evaluation framework encompassing five dimensions: farmers’ personal characteristics, solvency, credit status, loan guarantee, and production operations. The research introduces a novel biomechanics-driven credit risk assessment model (BICAM) that establishes quantitative relationships between plant mechanical properties and agricultural management risks. The study particularly focuses on three key biomechanical indicators: root system extension force, stem supporting strength, and leaf-environment interaction, which provide objective measures of farmers’ technical capabilities and risk management potential. The integration of these biomechanical parameters has significantly improved credit risk prediction accuracy, with the Area Under the Curve (AUC) showing a 16% improvement compared to traditional evaluation methods. A multi-scale modeling approach combining fractal-mechanical coupling for root systems, beam theory for stem dynamics, and mechanical-physiological coupling for leaves provides a robust theoretical foundation. The findings suggest that farmers demonstrating superior understanding and management of crop biomechanical properties typically exhibit better credit reliability and operational stability, offering financial institutions new insights for agricultural lending risk assessment while promoting more scientific approaches to agricultural risk management.
DOI: 10.62617/mcb908
Authors: Annan Li, Na Fu
Institution: Tianjin Agricultural University
Language: English
Subfield: Accounting
Domain: Social Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4408129842