Study On The Propagation Rule And Early Warning Technology Of Cucumber Downy Mildew

In recent years,the demand for the "vegetable basket" project has been increasing due to the rapid development of the social economy.Particularly,the vegetable industry has experienced significant growth in our country.Currently,China has surpassed all other countries in terms of greenhouse cultivation area,with an area exceeding 4 million hectares.Greenhouse vegetables play a crucial role in ensuring a stable vegetable supply and increasing farmers’ income.However,cucumber downy mildew,a highly contagious disease,can rapidly spread in environments with suitable temperature and humidity,leading to severe crop yield reduction or even crop failure.Furthermore,the expansion of greenhouse cultivation area and the practice of continuous cropping have intensified the threat of airborne diseases.Therefore,it is of great significance to effectively predict and provide early warnings for greenhouse vegetable diseases,both to ensure a stable vegetable supply in our country and to enhance farmers’ income.However,the current methods for early disease diagnosis only focus on detecting disease spores on crop leaves,which often delays the optimal timing for control measures.Moreover,these methods fail to consider various factors such as the source of cucumber downy mildew,future weather changes,and their combined impact on disease prevalence in the target area.Many of the existing studies are isolated,without establishing organic connections among the crop growth environment,downy mildew spread and sedimentation patterns,and crop disease occurrence and epidemic trends.As a result,achieving accurate early warning for disease occurrence and epidemic in the upcoming days has proven difficult.To address these challenges,this paper aims to develop an early warning system for cucumber downy mildew.The research focuses on the following key aspects:(1)In this study,the effects of different nutrient solution concentration treatments on the growth parameters of "Jinyou No.1" cucumber were investigated.The results revealed that compared to the 100% nutrient solution concentration treatment,the cucumber plants under the50% nutrient solution concentration treatment exhibited significant reductions in plant height,stem diameter,and leaf area.Specifically,plant height decreased by 27.32%,stem diameter decreased by 29.75%,and leaf area decreased by 31.15%.On the other hand,under the 150% nutrient solution concentration treatment,the cucumber plants showed a significant decrease in plant height but significant increases in leaf area and stem diameter.Plant height decreased by 8.55%,stem diameter increased by 4.59%,and leaf area increased by 11.88%.Furthermore,the study investigated the influence of different environmental parameters on the incidence of cucumber downy mildew.The findings indicated that an average temperature between 20°C and 25°C and relative humidity above 70% were the most favorable conditions for the occurrence of cucumber downy mildew.Conversely,temperatures below 15°C or above 35°C and relative humidity below60% were unfavorable for the occurrence of cucumber downy mildew.These findings provide preliminary insights into the occurrence and prevalence patterns of cucumber downy mildew and offer guidance for its prevention.(2)The study focused on the analysis of long-term trajectory frequency of cucumber downy mildew spores using the Mete Info Map3.5 based on the Lagrangian particle trajectory method.The results showed that the dispersion trajectory of the spores is influenced by atmospheric circulation.They spread through air currents to the surrounding areas of the disease source,intersecting with each other,and exhibiting a relatively wide range of transmission.The transmission patterns demonstrated a certain level of universality,providing a theoretical basis for early prediction of cucumber downy mildew spread.Additionally,the HYSPLIT-5 model and Arc Map 10.2 were used to simulate the deposition concentration of cucumber downy mildew spores.The results indicated consistent deposition patterns,with the majority of spores depositing in the local disease source and its surrounding areas,with a deposition probability of over 60%.As the spores gradually spread outward,the deposition concentration decreased to below 20%.By analyzing the spore dispersion trajectory and deposition concentration of cucumber downy mildew,the study revealed the basic spatiotemporal distribution patterns of spore dispersion in the air.Combining these findings with actual disease surveys and transmission predictions can provide theoretical support for long-term prediction of cucumber downy mildew.(3)A predictive model for cucumber downy mildew was established based on the LSTM-BP neural network algorithm.The prediction results of the LSTM-BP neural network model were compared with those of the LSTM and BP neural network models in terms of the severity of cucumber downy mildew.The results showed that the LSTM-BP neural network model achieved the lowest MAE of 0.0133,reducing the MAE by 0.0011 and 0.004 compared to the LSTM and BP neural network models,respectively.The LSTM-BP neural network model also achieved the lowest MSE of 0.0068,reducing the MSE by 0.0028 and 0.004 compared to the LSTM and BP neural network models,respectively.Additionally,the LSTM-BP neural network model achieved the lowest RMSE of 0.0825,reducing the RMSE by 0.0155 and 0.0214 compared to the LSTM and BP neural network models,respectively.The R2 value of the LSTM-BP neural network model reached the highest at 0.942,improving by 0.028 and 0.05 compared to the LSTM and BP neural network models,respectively.The LSTM-BP neural network model demonstrated the best prediction results,achieving an accuracy rate of over 95.44% in predicting the severity of cucumber downy mildew within the next seven days.This provides a more accurate method for early prediction of cucumber downy mildew.Furthermore,a cucumber downy mildew early warning system was designed using Qt Designer,which enables data collection,analysis,and disease prediction.By integrating the probabilities of downy mildew spore dispersion and settling with the disease prediction results,the system achieves early and accurate warning for cucumber downy mildew.In summary,this paper has proved the propagation law of cucumber downy mildew spores through the above research,and realized the early and accurate early warning of cucumber downy mildew,which is of great significance for timely guiding the prevention of cucumber downy mildew and the occurrence of catastrophic hazards in greenhouse cucumber production.Significance.