The hopper is an important piece of basic equipment used for storing and transporting materials in the agricultural, grain, chemical engineering, coal mine and pharmaceutical industries. The discharging performance of hoppers is mainly affected by material properties and hopper structure. In this work, the flow capacity of cylindrical pellets in the hopper with the unloading paddle is studied. A series of numerical simulation analyses with the aid of the discrete element method (DEM) platform are carried out. Then, the discharging process is illustrated, and the flow capacity of pellets in the hopper is analyzed by the mass flow index (MFI), the dynamic discharging angle (DDA) formed in the discharging process and porosity among pellets. Furthermore, the effect of parameters such as hopper half angle, rotation speed of the unloading paddle and outlet diameter of the hopper is investigated. The results show that MFI increases with an increase in hopper half angle or outlet diameter and a decrease in rotation speed. Meanwhile, DDA and porosity decrease with the increase in the hopper half angle or outlet diameter and the decrease in the rotation speed. Finally, the MFI ~0.24 is identified as the criterion to distinguish the mass flow from the funnel flow for the hopper with an unloading paddle, and the optimization results are decided as follows: hopper half angle greater than 60°, outlet diameter greater than 60 mm and rotation speed between 45 rpm and 60 rpm. These results should be useful for providing a theoretical reference for the optimization design of feeding devices for swine feeders.

The plant hormone abscisic acid (ABA) plays an important role in crop growth and development, so it is urgent to establish a simple and sensitive method for the detection of ABA. (1) As one of the most sensitive spectral detection methods, surface-enhanced Raman spectroscopy (SERS) has made some progress in the detection of ABA, but it involved a complicated modification process of noble metal nanoparticles and was time-consuming. (2) In this work, a SERS and (local surface plasmon resonance) LSPR dual-signal aptamer (Apt) sensor based on the aggregation of dispersed (gold nanoparticles) AuNPs and the improved plasmonic coupling with formed SERS was developed and applied to the detection of the plant hormone ABA. Through the specific recognition of Apt and ABA, the prepared crystal violet (CV) and Apt modified AuNPs tended to aggregate in a high concentration salt solution, resulting in changes in LSPR characteristics of the detection system and enhanced SERS intensity of CV signal molecules. Thus, the quantitative relationship between ABA concentration and SERS intensity of signal molecule CV and the degree of absorbance change of AuNPs were established. (3) The linear range detection of SERS was 0.04~40 µM, the detection limit lod (LOD) was 17.6 nM, the linear range detection of LSPR was 0.4~80 µM, and the LOD was 36 nM. (4) The sensor has a good ability to detect ABA in the samples of common plants such as cucumber and tomato and has the characteristics of no chemical bond modification, more reliable detection results, and a universal detection platform.