Accurate measurement of bean particle size is essential for automated grading and quality control in agricultural processing. However, existing image segmentation methods often suffer from low efficiency, over-segmentation, and high computational cost. We proposed a distance-gradient dual constrained watershed algorithm for precise segmentation and measurement of bean particles. The method integrated distance transform-based seed extraction with gradient-constrained flooding, effectively suppressing noise-induced region fragmentation and improving the separation of adherent particles. An experimental platform was constructed using an industrial camera and an image-processing pipeline to evaluate performance. Compared with the conventional watershed algorithm, the proposed method improves segmentation accuracy by 7.2% and reduces the mean particle size error by 27.8% (0.13 mm, representing a relative error of 2.4%). Validation on three soybean varieties confirmed the robustness and generalizability of the approach. The results indicated that the proposed algorithm provided an efficient and accurate technique for agricultural particle size analysis, offering potential for integration into practical low-cost inspection systems.

Lactate, as a metabolite, plays a significant role in a number of fields, including medical diagnostics, exercise physiology and food science. Traditional methods for lactate measurement often involve expensive and cumbersome instrumentation. This study developed a portable and low-cost lactate measurement system, including independently detectable hardware circuits and user-friendly embedded software, computer, and smartphone applications. The experiment verified that the relative error of the detection current in the device circuit was less than 1%. The electrochemical performance was measured by comparing the [Fe(CN)₆]³⁻/[Fe(CN)₆]⁴⁻ solution with the desktop electrochemical workstation CHI660E, and a nearly consistent chronoamperometry(CA) curve was obtained. Two modified lactate sensors were used for CA testing of lactate. Within the concentration range of 0.1 mmol·L⁻¹ to 20 mmol·L⁻¹, there was a good linear relationship between lactate concentration and steady-state current, with a correlation coefficient (R²) greater than 0.99 and good repeatability, demonstrating the reliability of the developed device. The lactate measurement system developed in this study not only provides excellent detection performance and reliability, but also achieves portability and low cost, providing a new solution for lactate measurement.