In intensive aquaculture, the real-time detection and monitoring of common infectious disease is an important basis for scientific fish epidemic prevention strategies that can effectively reduce fish mortality and economic loss. However, low-quality underwater images and low-identification targets present great challenges to diseased fish detection. To overcome these challenges, this paper proposes a diseased fish detection model, using an improved YOLOV5 network for aquaculture (DFYOLO). The specific implementation methods are as follows: (1) the C3 structure is used instead of the CSPNet structure of the YOLOV5 model to facilitate the industrial deployment of the algorithm; (2) all the 3 × 3 convolutional kernels in the backbone network are replaced by a convolutional kernel group consisting of parallel 3 × 3, 1 × 3 and 3 × 1 convolutional kernels; and (3) the convolutional block attention module is added to the YOLOV5 algorithm. Experimental results in a fishing ground showed that the DFYOLO is better than that of the original YOLOV5 network, and the average precision was improved from 94.52% to 99.38% (when the intersection over union is 0.5), for an increase of 4.86%. Therefore, the DFYOLO network can effectively detect diseased fish and is applicable in intensive aquaculture.

The replacement of natural fiber with biochars to prepare biocomposites has attracted widespread attention recently. Biochar has unique properties, including the porous structure, large specific surface area, high thermal stability, good conductivity, renewable and abundant feedstock source, and environmental friendliness, which provide excellent properties, environmental benefits, and low production costs for biochar-based composites. Biocomposites from organic solid waste-derived biochars show good prospects worldwide in terms of positive social, environmental, and economic impacts. This paper reviews current biochars, elucidates the effects of biochars on the characteristics and performance of biochar composites, and points out the challenges and future development prospects of biochar composites.

Tea is an important economic crop and health beverage in China. The presence of heavy metal ions in tea poses a significant threat to public health. Here, we prepared an aptamer biosensor labelled with AIEgen nanospheres to detect Pb²⁺ in tea. The dsDNA modified by amino and phosphoric acid was combined with the carboxylated AIEgen NPs to form AIEgen-DNA with a fluorescence group, which was then fixed to the surface of Zr-MOFs to quench the fluorescence of AIEgen NPs. At the same time, PEG was added to remove nonspecific adsorption. Then Pb²⁺ was added to cut the DNA sequences containing the cutting sites, and AIEgen NPs and part of the DNA sequences were separated from the Zr-MOFs surface to recover the fluorescence. By comparing the fluorescence changes before and after adding Pb²⁺, the detection limit of Pb²⁺ can reach 1.70 nM. The fluorescence sensor was applied to detect Pb²⁺ in tea, and the detection results showed that the tea purchased on the market did not contain the concentration of Pb²⁺ within the detection range. This study provides new insights into monitoring food and agriculture-related pollutants based on fluorescent biosensors.

Aiming to ease the cutting of kenaf stalks via bionics, the bionic disc cutter was designed. The upper jaw of the Batocera horsfieldi was used as a bionic prototype. Further, to explore its dynamic performance, an indoor multi-stalk cutting experimental bench was used to simulate the field operation process. A three-factor and two-level interaction orthogonal experiment was carried out; cutting speed, stalk conveying speed (machine forward speed), and blade type (ordinary disc cutter and bionic disc cutter) were used as experiment factors. The cutting pass rate and cutting specific energy consumption were selected as evaluation indexes. The range, variance, and fuzzy comprehensive evaluation analysis were carried out on the experiment results. Moreover, the main order factors affecting the bionic cutter performance were determined-blade type, conveying speed, the interaction between the cutter speed and conveying speed, and cutter speed. The optimal parameter combination scheme had a cutter speed of 1000 r/min, conveying speed of 0.4 m/s, and included bionic blades. Under this condition, the best index was the 92% cutting pass rate, with a specific energy consumption of 4.38 J/stalk. The variance analysis has shown that, with 95% confidence, the blade type has a rather significant influence on the comprehensive index. Additionally, the conveying speed also significantly influenced it, while other factors and interactions had no notable effect. The experimental comparison under the same working condition shows that the bionic blade has better cutting effect. This study provides a reference for the development of cutter and the selection of kenaf harvester operational parameters. Keywords: kenaf harvester, bionic, disc cutter, orthogonal experiment, interaction DOI: 10.25165/j.ijabe.20231606.7997 Citation: Tian K P, Zhang B, Ji A M, Huang J C, Liu H L, Shen C. Design and experiment of the bionic disc cutter for kenaf harvesters. Int J Agric & Biol Eng, 2023; 16(6): 116–123.

Industrial hemp is an important cash crop in China and has a very important role to play in increasing farmers’ income and eliminating poverty. However, drug loss risks, policy risks and regulatory challenges in the industrial hemp supply chain plague the healthy development of the industrial hemp industry. In order to address the problems in the industrial hemp industry, this paper described the problems in financing, traceability, and regulation, which are typical supply chain problems, by analyzing the industry of industrial hemp in China. Through a literature review, this paper reviewed the research results of blockchain technology in the agricultural supply chain, and analyzed the feasibility of blockchain technology to solve the financing problem of industrial hemp industry in combination with Chinese agricultural production and management modes, and analyzed the feasibility of blockchain technology to solve the traceability and supervision problems of industrial hemp industry in combination with Chinese anti-drug policies. Finally, based on the feasibility analysis, the idea of building a consortium blockchain consisting of market entities, financial institutions and drug-fighting agencies in the industrial hemp industry was proposed to solve the problems existing in the industrial hemp industry.

In response to the unclear issue of whether the dynamic cutting performance and structural parameters of an industrial hemp blade, which was developed earlier based on the bionic prototype of the batocera horsfieldi, can be optimized in actual working conditions, this paper analyzes the effective clamping conditions of a reciprocating double-acting cutting blade for stalks and the cutting motion. To investigate the effect of different structural and motion parameters, as well as their interactions, of the bionic blade on cutting energy consumption, bionic blades with different combinations of tooth pitch and tooth angle were designed. A Box–Behnken response surface method with three factors and three levels was used to design an experimental scheme. Utilizing rigid-flexible coupling numerical simulation technology, numerical simulation experiments were conducted to investigate the cutting performance of industrial hemp stalks using the blade. A regression model for cutting energy consumption was established, and variance analysis indicated that tooth angle, speed ratio, and the interaction between tooth angle and speed ratio had an extremely significant effect on the regression model. The primary and secondary orders of factors affecting cutting energy consumption were determined to be: speed ratio > tooth angle > tooth pitch. Through optimization, the optimal parameter combination was found to be a blade tooth pitch of 6.61 mm, a tooth angle of 30°, and a speed ratio of 1.62. Under these conditions, the cutting energy consumption was 3947.99 mJ. The optimized parameters were verified through numerical simulation cutting experiments, and the results showed that the error compared with the optimization results was only 8.16%. This indicates that the optimization results have high credibility and further verifies the reliability of the model. This study can provide a reference for the development of cutting devices for industrial hemp harvesters and the selection of motion parameters.