Bass detection model based on improved YOLOv5 in circulating water system.

The feeding amount of bass farming is closely related to the number of bass. It is of great significance to master the number of bass to achieve accurate feeding and improve the economic benefits of the farm. In view of the interference caused by the problems of multiple targets and target occlusion in bass data for bass detection, this paper proposes a bass target detection model based on improved YOLOV5 in circulating water system.

Credible pigeon permissioned blockchain traceability platform integrated with IoT based on HACCP.

The pigeon food production industry from breeding to processing into food for market circulation involves many stages and people, which is prone to food safety issues and difficult to regulate. To address these problems, one possible solution is to establish a traceability system. However, in traditional traceability systems, a number of stages involved and each of them provides their own data accumulated in the database.

A Novel Combined Model for Predicting Humidity in Sheep Housing Facilities.

Accurately predicting humidity changes in sheep barns is important to ensure the healthy growth of the animals and to improve the economic returns of sheep farming. In this study, to address the limitations of conventional methods in establishing accurate mathematical models of dynamic changes in humidity in sheep barns, we propose a method to predict humidity in sheep barns based on a machine learning model combining a light gradient boosting machine with gray wolf optimization and support-vector regression (LightGBM-CGWO-SVR). Influencing factors with a high contribution to humidity were extracted using LightGBM to reduce the complexity of the model.

A Hybrid Model for Temperature Prediction in a Sheep House.

Too high or too low temperature in the sheep house will directly threaten the healthy growth of sheep. Prediction and early warning of temperature changes is an important measure to ensure the healthy growth of sheep. Aiming at the randomness and empirical problem of parameter selection of the traditional single Extreme Gradient Boosting (XGBoost) model, this paper proposes an optimization method based on Principal Component Analysis (PCA) and Particle Swarm Optimization (PSO).

Integration of Privacy Protection and Blockchain-Based Food Safety Traceability: Potential and Challenges.

Concern about food safety has become a hot topic, and numerous researchers have come up with various effective solutions. To ensure the safety of food and avoid financial loss, it is important to improve the safety of food information in addition to the quality of food. Additionally, protecting the privacy and security of food can increase food harvests from a technological perspective, reduce industrial pollution, mitigate environmental impacts, and obtain healthier and safer food.

Pollution index of waterfowl farm assessment and prediction based on temporal convoluted network.

Environmental quality is a major factor that directly impacts waterfowl productivity. Accurate prediction of pollution index (PI) is the key to improving environmental management and pollution control. This study applied a new neural network model called temporal convolutional network and a denoising algorithm called wavelet transform (WT) for predicting future 12-, 24-, and 48-hour PI values at a waterfowl farm in Shanwei, China.

Association of TGF-ß1 polymorphisms and chronic hepatitis C infection: a Meta-analysis.

Background: Although several researches have reported the connection between the transforming growth factor-beta 1 (TGF-β1) gene polymorphisms and chronic hepatitis C virus (HCV) infection, the conclusions of these studies were not always consistent. Here, this paper proposed a meta-analysis to evaluate whether the TGF-ß1 gene polymorphisms, -509C/T (rs1800469), codon 10 T/C (rs1982073) and codon 25G/C (rs1800471), were associated with chronic HCV infection.

Methods: The summary odds ratios (ORs) of chronic HCV infected patients and controls with all SNPs were obtained by adaptive fixed or random effect model.