Multiscale bioimpedance detection methods and modeling for dynamic non-destructive monitoring of agricultural product quality

Abstract

Background

Ensuring the quality and safety of agricultural products is a crucial aspect of modern agricultural production. However, existing detection methods are often hindered by limitations such as complexity, high costs, and time consumption. To address these challenges, multiscale bioimpedance detection has emerged as a non-invasive and rapid alternative. This technique evaluates the electrical impedance characteristics of agricultural products, offering valuable insights into their internal properties and presenting a more efficient solution for quality monitoring.

Scope and approach

This paper examines the principles of the multiscale bioimpedance detection method, focusing on its technical framework, measurement system, and data processing techniques. Additionally, it explores how this method facilitates dynamic and nondestructive monitoring of agricultural product quality at multiple levels, including molecular, cellular, and individual scales. The objective is to showcase its applications in multiscale agricultural product detection, emphasize its advantages in enhancing detection accuracy, and analyze its technical characteristics and practical value. Lastly, the paper outlines potential future development directions for this technology.

Key findings and conclusions

Multiscale bioimpedance detection can achieve targeted pretreatment at the molecular, cellular and individual levels in the quality monitoring of agricultural products. By constructing a detection framework and model, the purpose of non-destructive testing can be achieved. This multiscale approach can comprehensively assess the macro and micro levels of agricultural products and help to judge their quality status more accurately. At the same time, in order to further improve the stability and accuracy of quality assessment, this technology needs to be integrated with emerging technologies for optimization.