The intelligent perception of moisture content (MC) for tea leaves during the black tea withering process is an unsolved task because of the acquisition of limited sample characteristic information. In this study, both the external and internal features of withering samples were simultaneously acquired based on near-infrared spectroscopy (NIRS) and machine vision (MV) technology. Different data fusion strategies, including low-, middle- and high-level strategies, were employed to integrate two types of heterogeneous information. Subsequently, the different fused features were combined with a support vector regression (SVR) algorithm to establish the moisture perception models of withering leaves. The middle-level-variable iterative space shrinkage approach (VISSA) displayed the best performance with 5.7705 for the relative percent deviation (RPD). Therefore, the proposed multi-information fusion strategy could achieve an intelligent perception of tea leaves in the black tea withering process. The integration of NIRS and MV technology overcomes the limitations of single-technology approaches in black tea withering assessment, providing a robust methodology for precision processing and targeted quality control of black tea.

The objective of this study was to study the effect of microwave vacuum puffing (MVP) conditions on dielectric properties of berries. A central composite response surface experiment, with four factors and five levels, was carried out to assess the effect of puffing conditions on the dielectric properties. The microwave volumetric heat, dielectric constant and dielectric loss factor were, accordingly, evaluated based on the dynamic dielectric property index model of berries. As a result, the initial moisture content had significant effects on the dielectric constant and dielectric loss factor of the berry crisps. Specifically, in the early stage of puffing, the dielectric constant decreases with increasing initial moisture content. However, in the later stage of puffing, the dielectric constant first decreases and then increases as the initial moisture content rises. Meanwhile, the dielectric loss factor increases consistently with increasing initial moisture content throughout the puffing process. The MVP conditions exert a complex effect on dielectric properties of berries. Based on these findings, a theoretical for the dynamic processing mode and equipment design for MVP of berries can be provided.

The objective of this study was to study the effect of microwave vacuum puffing (MVP) conditions on dielectric properties of berries. A central composite response surface experiment, with four factors and five levels, was carried out to assess the effect of puffing conditions on the dielectric properties. The microwave volumetric heat, dielectric constant and dielectric loss factor were, accordingly, evaluated based on the dynamic dielectric property index model of berries. As a result, the initial moisture content had significant effects on the dielectric constant and dielectric loss factor of the berry crisps. Specifically, in the early stage of puffing, the dielectric constant decreases with increasing initial moisture content. However, in the later stage of puffing, the dielectric constant first decreases and then increases as the initial moisture content rises. Meanwhile, the dielectric loss factor increases consistently with increasing initial moisture content throughout the puffing process. The MVP conditions exert a complex effect on dielectric properties of berries. Based on these findings, a theoretical for the dynamic processing mode and equipment design for MVP of berries can be provided.