ABSTRACT
This study addresses the challenge of incomplete separation of mechanically recovered residual films and impurities in cotton fields, examining their impact on resource utilization and environmental pollution. It introduces an innovative screening method that combines pneumatic force and mechanical vibration for processing crushed film residue mixtures. A double-action screening device integrating pneumatic force and a key-type vibrating screen was developed. The working characteristics of this device were analyzed to explore the dynamic characteristics and kinematic laws of the materials using theoretical analysis methods. This led to the revelation of the screening laws of residual films and impurities. Screening tests were conducted using the Central Composite Design method, considering factors such as fan outlet, fan speed, vibration frequency of the screen, and feeding amount, with the impurity-rate-in-film (Q) and film-content-in-impurity (W) as evaluation indexes. The significant influence of each factor on the indexes was determined, regression models between the test factors and indexes were established, and the effect laws of key parameters and their significant interaction terms on the indexes were interpreted. The optimal combination of working parameters for the screening device was identified through multivariable optimization methods. Validation tests under this optimal parameters combination showed that the impurity-rate-in-film was 3.08% and the film-content-in-impurity was 1.94%, with average errors between the test values and the predicted values of 3.36% and 5.98%, respectively, demonstrating the effectiveness of the proposed method. This research provides a novel method and technical reference for achieving effective separation of residual film and impurities, thereby enhancing resource utilization.
Subject(s)
Gossypium , Cotton Fiber/analysis , Environmental Pollution/prevention & controlABSTRACT
Molecular imprinting technology (MIT) offers an effective technique for efficient separation and enrichment of specific analytes from complicated matrices and has been used for illicit veterinary drug detectionin recent years due to its high selectivity, good chemical stability, and simple preparation. The development of in silico-based approaches has enabled the simulation of molecularly imprinted polymers (MIPs) to facilitate the selection of imprinting conditions such as template, functional monomer, and the best suitable solvent. In this work, using density functional theory (DFT), the molecularly imprinted polymers of clenbuterol and its metabolites were designed by computer-aided at B3LYP/6-31 + G (d, p) level. Screening molecular imprinting components such as functional monomers, cross-linkers, and solvents has been achieved in the computational simulation considerations. The simulation results showed that methacrylic acid (MAA) is the best functional monomer; the optimal imprinting ratio for both clenbuterol (CLB) and its dummy template molecule of phenylephrine (PE) to functional monomer is 1:3, while the optimal imprinting ratio for the two dummy template molecules of CLB's metabolites is 1:5. Choosin gethyleneglycol dimethacrylate (EDGMA) as a crosslinker and aprotic solvents could increase the selectivity of the molecularly imprinted system. Atoms in Molecules (AIM) topology analysis was applied to investigate the template-monomer complexes bonding situation and helped to explain the nature of the reaction in the imprinting process. These theoretical predictions were also verified by the experimental results and found to be in good agreement with the computational results. The computer-simulated imprinting process compensates for the lack of clarity in the mechanism of the molecular imprinting process, and provides an important reference and direction for developing better recognition pattern towards CLB and its metabolite analytes in swine urine samples at the same time.
ABSTRACT
Okra (Abelmoschus esculentus) is a widely used medicine and functional food. In order to clarify the effects of the particle size on its functional properties, okra pods were subjected to superfine grinding, and its properties were determined using different methods. Four particle size levels of okra powders were prepared: 380 to 250, 250 to 75, 75 to 40 and less than 40 µm. The results showed that superfine grinding technology could efficiently pulverize the particles into the submicron scale, whose distribution was close to a Gaussian distribution. With decreasing okra powder size, the specific surface area, water holding capacity (WHC), water-retention capacity (WRC), oil-binding capacity (OBC), tapped density and total flavonoids extraction were increased significantly (p < 0.05). Moreover, the adsorption of cholesterol by okra powder was improved after superfine grinding. These results suggest that okra powder can be used in food manufacturing as a functional food ingredient.