Porphyra yezoensis has attracted much attention due to its gelling properties and bioactivity. In this study, the chemical structure of Porphyra yezoensis polysaccharides (PYPSs) was characterized, and the effects of concentration, temperature, pH, and calcium ion (Ca²⁺) addition on the rheological properties of PYPS were systematically investigated. Chemical composition analysis indicated that PYPS primarily contained galactose (89.76%) and sulfate (15.57%). Rheological tests demonstrated that PYPS exhibited typical pseudoplastic properties, with apparent viscosity increasing with an increasing concentration. Temperature elevation from 30 °C to 90 °C weakened the intermolecular forces and reduced the apparent viscosity, whereas neutral pH (7.0) provided an optimal electrostatic equilibrium to maintain the highest viscosity. Ca²⁺ could modulate the interactions between PYPS molecules and affect the formation of the gel network structure. When the Ca²⁺ concentration reached the optimal value of 6 mM, the calcium bridges formed between Ca²⁺ and PYPS molecules not only enhanced the rheological behavior and textural properties but also formed a smooth and well-ordered network structure, achieving the highest value of fractal dimension (D_f = 2.9600), though excessive Ca²⁺ disrupted this well-ordered structure. Furthermore, PYPS possessed significant scavenging ability against DPPH, ABTS, and HO• radicals, demonstrating its potential application as a natural antioxidant in functional foods.

The of monitoring the Internet of Things (IoT) in the cold chain allows process data, including packaging data, to be more easily accessible. Proper optimization modelling is the core driving force towards the green and low-carbon operation of cold chain logistics, laying the necessary foundation for the development of a data-driven modelling system. Since efficient packaging is necessary for loss control in the cold chain, its final efficiency during circulation is important for realizing continuous loss prevention and efficient supply. Thus, it is urgent to determine how to utilize these continuously acquired data and how to formulate a more accurate packaging efficiency control methodology in the agri-products cold chain. Through continuous monitoring, we examined the feasibility of this topic by focusing on the concept of data-driven evaluation modelling and the dynamic formation mechanism of comprehensive packaging efficiency in cold chain logistics. The packaging efficiency in the table grape cold chain was used as an example to evaluate the comprehensive efficiency evaluation index system and data-driven evaluation framework proposed in this paper. Our results indicate that the established methodology can adapt to the continuity of comprehensive packaging efficiency, also reflecting the comprehensive efficiency evaluation of the packaging for different times and distances. Through the evaluation of our results, the differences and the dynamic processes between different final packaging efficiencies at different moments are effectively displayed. Thus, the continuous improvement of a low-carbon system in cold chain logistics could be realized.