Simulation of cucumber downy mildew Spread and sedimentation based on HYSPLIT

Guilin Xu, Han ping Mao — Fri, 02 Jun 2023 00:00:00 +0000

Cucumber downy mildew is a typical fungal airborne disease in which pathogenic spores are transmitted remotely by air currents, resulting in regional endemics. It is of great significance to study and analyze the temporal and spatial changes of downy mildew spores, especially the trajectory and sedimentation concentration of spores propagating with airflow in the air, for the prediction of downy mildew in cucumbers. Therefore, based on GDAS meteorological data from October to November 2017, this study uses the HYSPLIT-5 model to simulate the airflow propagation trajectory and sedimentation of downy mildew pathogen spores in the main cucumber planting areas in China, analyzes the trajectory frequency and sedimentation concentration in the long-distance and long-term series propagation process, and explores the transmission law of airborne disease spores, which provides a theoretical basis for predicting downy mildew in cucumbers.

Tilapia feeding decision system based on adaptive neuro-fuzzy inference

Haiyang Cao, Hanping Mao — Tue, 30 May 2023 00:00:00 +0000

In industrial recirculating aquaculture, the feed required by fish accounts for a major part of the total expenditure. In this paper, a multi-factor decision making system based on aggregation FIFFB of fish feeding behavior, water temperature T of environmental factors and biomass weight W was proposed to solve the problem of feed waste under the traditional mode. To verify the performance of this model, a fuzzy inference FIS model is constructed for comparison. The experimental results show that the root mean square error (RMSE) and mean absolute error (MAE) between the predicted and actual feeding amount of ANFIS triplet are 0.78 and 0.19, respectively, which are much lower than the FIS model, and this model is more suitable for predicting the feeding amount decision. At the same time, growth parameters such as WGR, FMAE, K and FCR were compared. The fish growth specifications were fatter and the economic benefits were higher, and the feed conversion rate was increased by 12.35%. Therefore, the triplet ANFIS feeding prediction and decision-making system based on fish aggregation degree, water temperature and body weight is effective and has guiding significance for the precise feeding design of unmanned aquaculture.

JOURNAL OF ADVANCES IN AGRICULTURE

Simulation of cucumber downy mildew Spread and sedimentation based on HYSPLIT

Tilapia feeding decision system based on adaptive neuro-fuzzy inference