Design, Characterization, and Application of a Continuously Tunable Wavelength Spatial Frequency Domain Imaging System for Measuring the Optical Properties of Fruits

Spatial frequency domain imaging (SFDI) has been widely applied in fruit quality inspection because of its noncontact and wide-field advantages. However, conventional multispectral SFDI systems remain constrained by low transmission efficiency, limited spectral range, and reliance on mechanical scanning. To overcome these limitations, we developed a continuously tunable wavelength SFDI system (450–1040 nm) that enables both continuous-spectrum and selectable-band imaging through patterned monochromatic illumination. The system adopts a modular design that integrates a monochromatic light generation module, a projection module, an imaging module, and a motorized imaging platform. This configuration allows flexible coupling and replacement of light sources and projection modules, enabling automated measurement of optical properties across different wavelength ranges according to application needs. With its high tunability, the system supports customized measurements at specific wavelengths via dedicated acquisition software, and it also provides the potential for spectral extension into longer infrared bands by simply upgrading the light source and infrared-sensitive projection module. Leveraging its wavelength tunability, we further demonstrated the system’s capability for depth-resolved imaging by jointly regulating the spatial frequency and wavelength. The results showed that the system achieved an imaging depth of 3–4 mm. The optical property measurements of various fruits obtained using our system were in close agreement with the reference values provided by the integrating sphere (IS). The mean measurement error of the absorption coefficient (μa[jls-end-space/]) was approximately 0.002 mm−1, while that of the reduced scattering coefficient (μs'[jls-end-space/]) was approximately 0.02 mm−1. In the application case of peach firmness prediction, the developed model achieved a coefficient of determination for prediction (Rp2[jls-end-space/]) of 0.786. These results demonstrate that our system is more accurate than existing multiwavelength SFDI devices. This improvement indicates that the extended spectral range of the proposed SFDI system provides richer tissue information, thereby highlighting its potential for fruit quality evaluation. More importantly, this work establishes a new paradigm for SFDI instrumentation by transitioning from fixed multispectral sensing to customizable, spectrally continuous imaging, thereby broadening its applicability in the nondestructive evaluation of agricultural products and potentially other biological tissues.