A Review on the Application of Deep Learning Methods in Detection and Identification of Rice Diseases and Pests

In rice production,the prevention and management of pests and diseases have always received special attention.Traditional methods require human experts,which is costly and time-consuming.Due to the complexity of the structure of rice diseases and pests,quickly and reliably recognizing and locating them is difficult.Recently,deep learning technology has been employed to detect and identify rice diseases and pests.This paper introduces common publicly available datasets;summarizes the applications on rice diseases and pests from the aspects of image recognition,object detection,image segmentation,attention mechanism,and few-shot learning methods according to the network structure differences;and compares the performances of existing studies.Finally,the current issues and challenges are explored fromthe perspective of data acquisition,data processing,and application,providing possible solutions and suggestions.This study aims to review various DL models and provide improved insight into DL techniques and their cutting-edge progress in the prevention and management of rice diseases and pests.

Technical Points of Green Prevention and Control Technology of Major Diseases and Pests in Lixian Rhubarb(Rheum palmatum L.)

Based on different types of diseases,pests and weeds in the whole growth period of rhubarb(sowing period-harvesting period),the corresponding green prevention and control technology is proposed,aiming to further reduce the application amount of pesticides and fertilizers in the production of medicinal sources of Lixian rhubarb during the"14 th Five-Year Plan"period.The results will provide a theoretical basis for increasing the promotion and application of agricultural prevention and control(including disease-resistant varieties,ecological regulation),physical prevention and control,biological prevention and control measures,thus ensuring effective protection of the ecological environment,green,healthy and sustainable development of traditional Chinese medicine agriculture in Longnan,and source quality of authentic medicinal materials.

Major Diseases and Pests of Blueberry in Guizhou Province and Progress in Their Prevention and Control

As the blueberry industry continues to evolve,the effective control of its diseases and pests has become an essential component of local agricultural development.This paper provides a comprehensive overview of the principal types of blueberry diseases and pests in Guizhou Province,along with the corresponding control measures,in order to serve as a valuable reference for blueberry growers.

Social Cost Analysis of Biological Control Technology for Crop Diseases and Insect Pests

With the rapid development of modern agriculture,the prevention and control of crop diseases and insect pests has become an important part to ensure the safety of agricultural production,the quality of agricultural products and the safety of agricultural ecological environment.Although the effect of traditional chemical prevention and control technology is remarkable,the health risks and environmental problems brought by it should not be ignored.As a green and environmentally friendly means of prevention and control,biological prevention and control technology has gradually become a hot research topic and a trend of agricultural production.This paper is intended to comprehensively evaluate the social costs of biological control technologies for crop diseases and pests,including the health risks reduced,environmental improvements,economic benefits,and barriers to promotion,and put forward corresponding policy recommendations.

Comprehensive Prevention and Control Technology of Vegetable Diseases and Pests in Shandong Province

An in-depth research and practice has been conducted on vegetable diseases and pests in Shandong Province,and the principles of comprehensive and ecological control of diseases and pests are put forward,including agricultural control measures such as crop rotation,field cleaning,fertilizer and water management,physical control measures such as catching and killing,trapping,blocking,photoelectric energy treatment,biological control measures such as the use of natural enemies,pathogenic microorganisms,other beneficial organisms and metabolites,and scientific and rational chemical control measures.Comprehensive prevention and control not only controls vegetable diseases and pests effectively,but also protects the ecological environment.

Effects of Six Cultivation Patterns on Occurrence of Major Diseases and Pests and Yield of Rice

The occurrence rules of major diseases and pests in rice were investigated under six cultivation patterns, i.e., mechanical plowing-artificial transplanting, mechanical plowing-mechanical transplanting, mechanical plowing-scattered transplanting,cattle plowing-artificial transplanting, cattle plowing-mechanical transplanting and cattle plowing-scattered transplanting. The results showed that the six cultivation patterns showed small effects on the occurrence of rice sheath blight, second-generation rice planthopper, rice stem borer and rice false smut, but showed great effects on the occurrence of rice leaf folder, third-and fourth-generation rice planthopper and weeds; there were certain differences in the rice yield among different cultivation patterns, and the rice yield under the pattern of mechanical plowing-mechanical transplanting ranked first, while that under the pattern of cattle plowing-scattered transplanting ranked last.

Synergistic effects of the entomopathogenic fungus Isaria javanica and low doses of dinotefuran on the efficient control of the rice pest Sogatella furcifera

The rice planthopper,Sogatella furcifera,is a piercing-sucking insect pest of rice,Oryza sativa.It is responsible for significant crop yield losses,and has developed moderate to high resistance to several commonly used chemical insecticides.We investigated the effects of the insect fungal pathogen Isaria javanica,alone and in combination with the chemical insecticide dinotefuran,on S.furcifera under both laboratory and field conditions.Our results show that I.javanica displays high infection efficiency and mortality for different stages of S.furcifera,reducing adult survival,female oviposition and ovary development.Laboratory bioassays showed that the combined use of I.javanica with a low dose(4-16 mg L^(-1))of dinotefuran resulted in higher mortality in S.furcifera than the use of I.javanica or dinotefuran alone.The combined treatment also had more significant effects on several host enzymes,including superoxide dismutase,catalase,peroxidase,and prophenol oxidase activities.In field trials,I.javanica effectively suppressed populations of rice planthoppers to low levels(22-64%of the level in untreated plots).Additional field experiments showed synergistic effects,i.e.,enhanced efficiency,for the control of S.furcifera populations using the combination of a low dose of I.javanica(1×10^(4) conidia mL^(-1))and a low dose of dinotefuran(~4.8-19.2%of normal field use levels),with control effects of>90%and a population level under 50 insects per 100 hills at 3-14 days post-treatment.Our findings indicate that the entomogenous fungus I.javanica offers an attractive biological control addition as part of the integrated pest management(IPM)practices for the control of rice plant pests.

Enhanced Ultraviolet-B Radiation Suppresses Magnaporthe oryzae Infection and Alleviates Its Damage to the Photosynthesis of Rice Leaves

In the present study,an indoor potting experiment was conducted to study the effects of enhanced UV-B radiation and Magnaporthe oryzae on the growth,stomatal structure,photosynthesis,and endogenous hormone contents of a traditional rice cultivar Baijiaolaojing in the Yuanyang terraces of Yunnan Province.In addition,the relationships between these parameters and disease indices were analyzed.We aimed to clarify the response of the photosynthetic physiology of rice under the combined stress of UV-B radiation and M.oryzae.Compared with the M.oryzae infection treatment,all the treatments,including M.oryzae infection before(MBR),simultaneously with(MSR),and after(MAR)UV-B radiation significantly increased the rice height and biomass by 4%–11%and 30%–111%,respectively,and the stomatal structure and carotenoids content of leaves,while decreasing the contents of chlorophyll a and b,by 21%–41%and 63%–73%,respectively.Both the MSR and MBR treatments significantly increased the photosynthetic rate and transpiration rate of rice leaves.The MAR treatment weakened chlorophyll fluorescence parameters,including the actual photosystem II(PS II)photochemical efficiency,electron transport rate,photochemical quenching,and nonphotochemical quenching by 40%,39%,43%,and 24%,respectively.Moreover,the treatments of MAR,MSR,and MBR decreased the phytohormones content and the M.oryzae disease index by 27%–62%in rice leaves.Thus,the enhanced UV-B radiation contributed to suppressing the M.oryzae infection and alleviating its damage to the photosynthesis of rice leaves.This study is valuable for the control of rice blast fungus and offers important insights into plant pathology.

YOLO-CRD:A Lightweight Model for the Detection of Rice Diseases in Natural Environments

Rice diseases can adversely affect both the yield and quality of rice crops,leading to the increased use of pesticides and environmental pollution.Accurate detection of rice diseases in natural environments is crucial for both operational efficiency and quality assurance.Deep learning-based disease identification technologies have shown promise in automatically discerning disease types.However,effectively extracting early disease features in natural environments remains a challenging problem.To address this issue,this study proposes the YOLO-CRD method.This research selected images of common rice diseases,primarily bakanae disease,bacterial brown spot,leaf rice fever,and dry tip nematode disease,from Tianjin Xiaozhan.The proposed YOLO-CRD model enhanced the YOLOv5s network architecture with a Convolutional Channel Attention Module,Spatial Pyramid Pooling Cross-Stage Partial Channel module,and Ghost module.The former module improves attention across image channels and spatial dimensions,the middle module enhances model generalization,and the latter module reduces model size.To validate the feasibility and robustness of this method,the detection model achieved the following metrics on the test set:mean average precision of 90.2%,accuracy of 90.4%,F1-score of 88.0,and GFLOPS of 18.4.for the specific diseases,the mean average precision scores were 85.8%for bakanae disease,93.5%for bacterial brown spot,94%for leaf rice fever,and 87.4%for dry tip nematode disease.Case studies and comparative analyses verified the effectiveness and superiority of the proposed method.These researchfind-ings can be applied to rice disease detection,laying the groundwork for the development of automated rice disease detection equipment.

Development of Spectral Features for Monitoring Rice Bacterial Leaf Blight Disease Using Broad-Band Remote Sensing Systems

As an important rice disease, rice bacterial leaf blight (RBLB, caused by the bacterium Xanthomonas oryzae pv.oryzae), has become widespread in east China in recent years. Significant losses in rice yield occurred as a result ofthe disease’s epidemic, making it imperative to monitor RBLB at a large scale. With the development of remotesensing technology, the broad-band sensors equipped with red-edge channels over multiple spatial resolutionsoffer numerous available data for large-scale monitoring of rice diseases. However, RBLB is characterized by rapiddispersal under suitable conditions, making it difficult to track the disease at a regional scale with a single sensorin practice. Therefore, it is necessary to identify or construct features that are effective across different sensors formonitoring RBLB. To achieve this goal, the spectral response of RBLB was first analyzed based on the canopyhyperspectral data. Using the relative spectral response (RSR) functions of four representative satellite or UAVsensors (i.e., Sentinel-2, GF-6, Planet, and Rededge-M) and the hyperspectral data, the corresponding broad-bandspectral data was simulated. According to a thorough band combination and sensitivity analysis, two novel spectralindices for monitoring RBLB that can be effective across multiple sensors (i.e., RBBRI and RBBDI) weredeveloped. An optimal feature set that includes the two novel indices and a classical vegetation index was formed.The capability of such a feature set in monitoring RBLB was assessed via FLDA and SVM algorithms. The resultdemonstrated that both constructed novel indices exhibited high sensitivity to the disease across multiple sensors.Meanwhile, the feature set yielded an overall accuracy above 90% for all sensors, which indicates its cross-sensorgenerality in monitoring RBLB. The outcome of this research permits disease monitoring with different remotesensing data over a large scale.

Breeding and Application Techniques of a New Rice Variety Liliang-you 3822 with High Yield and Disease Resistance

Liliangyou 3822 is a novel indica hybrid rice variety that exhibits disease resistance,high yield,lodging resistance,and late maturity.It employs a self-selected two-line sterile line,Li 38S,and a self-selected restorer line,R22.This variety was subjected to a regional test of indica late-maturing groups in the middle and lower reaches of the Yangtze River in 2020.The results demonstrated that the average yield of the variety was 9.95 t/hm 2,which was 10.67%higher than that of the control Fengliangyou 4,indicating a highly significant yield increase.In the continuous test in 2021,the average yield was 9.74 t/hm 2,representing a 6.52%increase over the control,which also exhibited a significant increase.Finally,the average yield of the two years regional test was 9.84 t/hm 2,which was 8.58%higher than that of the control.In the 2021 production test,the average yield of the variety was 9.32 t/hm 2,which was 12.19%higher than that of the control,indicating a remarkably significant yield increase.In 2022,the variety was validated by the National Crop Variety Approval Committee(GSD 20220143).

Control Effect of 35% Thiamethoxam-prochloraz FS to Plant Diseases and Insect Pests at Rice Seedling Stage and Safety Evaluation

The prevention and control effect of 35% thiamethoxam-prochloraz FS to rice thrips and rice bakanae disease and its influence on the quality of rice seedlings were studied. The results show that when 100 kg of rice seeds were coated with 200 g of 35% thiamethoxam-prochloraz FS,the control effects to rice thrips were 93.0% and 84.7% 15 and 20 days after sowing, and the control effect to rice bakanae disease was 90.8% 30 days after sowing. As 100 kg of rice seeds were coated with 250 g of 35% thiamethoxam-prochloraz FS, the control effects to rice thrips were 98.2% and 94.9% 15 and 20 days after sowing, and the control ef- fect to rice bakanae disease was 94.6% 30 days after sowing. 35% thiamethoxam- prochloraz FS is safe to rice seedlings and can effectively promote the growth of rice seedlings.

Effects of Rice-duck Mutualism on Diseases Insect Pests and Weeds and Economic Benefits

[Objective] Study on the effects of rice-duck mutualism on weeds and insects pests and economic benefits of paddy field. [Method] Comparison of the incidence of weeds, sheath blight and insects pest under rice-duck mutualism, conventional cultivation and control treatment, the yield and economic benefits were analyzed under the 3 treatments. [Result] Average occurrence of weeds in rice-duck mutualism group decreased by 2.33 and 52.0g ind/m^2 compared with that in conventional cultivation and control treatment ; the control rate of mutualism was up to 75% against rice hopper, but just between 25% -60% against rice leaf roller and Chilo suppressalis. The rates of diseased plant and diseased bell against rice sheath blight were higher and disease indices were lower compared with control group. The yield of mutualism group was identical with conventional cultivation, Which was greatly higher than that of control group. The results suggested an higher economic benefits and lower cost benefit ratio for rice-duck mutualism treatment. [Conclusion] Rice-duck mutualism gives birth to a positive effect to control the diseases, insect pests and weeds, as well as to economic benefits, providing basis on extension of rice-duck mutualism system.

Towards Intelligent Detection and Classification of Rice Plant Diseases Based on Leaf Image Dataset

The detection of rice leaf disease is significant because,as an agricultural and rice exporter country,Pakistan needs to advance in production and lower the risk of diseases.In this rapid globalization era,information technology has increased.A sensing system is mandatory to detect rice diseases using Artificial Intelligence(AI).It is being adopted in all medical and plant sciences fields to access and measure the accuracy of results and detection while lowering the risk of diseases.Deep Neural Network(DNN)is a novel technique that will help detect disease present on a rice leave because DNN is also considered a state-of-the-art solution in image detection using sensing nodes.Further in this paper,the adoption of the mixed-method approach Deep Convolutional Neural Network(Deep CNN)has assisted the research in increasing the effectiveness of the proposed method.Deep CNN is used for image recognition and is a class of deep-learning neural networks.CNN is popular and mostly used in the field of image recognition.A dataset of images with three main leaf diseases is selected for training and testing the proposed model.After the image acquisition and preprocessing process,the Deep CNN model was trained to detect and classify three rice diseases(Brown spot,bacterial blight,and blast disease).The proposed model achieved 98.3%accuracy in comparison with similar state-of-the-art techniques.

Occurrence Dynamics and Control Strategies of Major Pests and Diseases of Sugarcane in Yunnan

In recent years, the occurrence and harm of many kinds of pests and diseases have become increasingly serious in Yunnan sugarcane areas, which have greatly affected the sustained and stable development of sugarcane production, so the situation of their prevention and control has become rigorous. In order to scien- tifically and effectively prevent and control pests and diseases of sugarcane to en- sure the safety of sugarcane production, on the basis of an investigation and re- search, according to the present situation of sugarcane production in Yunnan, the occurrence dynamics of major pests and diseases of sugarcane were analyzed, and corresponding control strategies were proposed according to the major pests and diseases as well as their occurrence and damage characteristics.

Advanced biosensing technologies for monitoring of agriculture pests and diseases:A review

The threat posed to crop production by pests and diseases is one of the key factors that could reduce global food security.Early detection is of critical importance to make accurate predictions,optimize control strategies and prevent crop losses.Recent technological advancements highlight the opportunity to revolutionize monitoring of pests and diseases.Biosensing methodologies offer potential solutions for real-time and automated monitoring,which allow advancements in early and accurate detection and thus support sustainable crop protection.Herein,advanced biosensing technologies for pests and diseases monitoring,including image-based technologies,electronic noses,and wearable sensing methods are presented.Besides,challenges and future perspectives for widespread adoption of these technologies are discussed.Moreover,we believe it is necessary to integrate technologies through interdisciplinary cooperation for further exploration,which may provide unlimited possibilities for innovations and applications of agriculture monitoring.

Differentiation of Wheat Diseases and Pests Based on Hyperspectral Imaging Technology with a Few Specific Bands

Hyperspectral imaging technique is known as a promising non-destructive way for detecting plants diseases and pests.In most previous studies,the utilization of the whole spectrum or a large number of bands as well as the complexity of model structure severely hampers the application of the technique in practice.If a detection system can be established with a few bands and a relatively simple logic,it would be of great significance for application.This study established a method for identifying and discriminating three commonly occurring diseases and pests of wheat,i.e.,powdery mildew,yellow rust and aphid with a few specific bands.Through a comprehensive spectral analysis,only three bands at 570,680 and 750 nm were selected.A novel vegetation index namely Ratio Triangular Vegetation Index(RTVI)was developed for detecting anomalous areas on leaves.Then,the Support Vector Machine(SVM)method was applied to construct the discrimination model based on the spectral ratio analysis.The validating results suggested that the proposed method with only three spectral bands achieved a promising accuracy with the Overall Accuracy(OA)of 83%.With three bands from the hyperspectral imaging data,the three wheat diseases and pests were successfully detected and discriminated.A stepwise strategy including background removal,damage lesions recognition and stresses discrimination was proposed.The present work can provide a basis for the design of low cost and smart instruments for disease and pest detection.

Main Pests and Diseases of Zingiberaceae and Their Control

The primary diseases affecting Zingiberaceae plants include ginger plague, spot blotch, anthracnose, leaf spot, leaf blight, and soft rot. Insect pests that pose a threat to these plants encompass root-knot nematode disease, drilling bugs, beet nightshade moths, mesquite, thrips, and aphids. This article aims to summarize the defining features of the principal pests and diseases as well as their control methods. The intention is to offer theoretical support for the preservation of ginger plants.

Effects of Diseases and Pests on Quality, Industry and International Trade of Tea

Starting from the effects of diseases and pests on tea quality,tea industry and export trade,the status quo and control of tea diseases and pests,assurance and traceability of tea quality safety,tea industry and export trade development are analyzed in detail,and green prevention and control measures against tea diseases and pests are put forward combined with the status quo of tea in China.

Species and Control Techniques of Main Diseases and Insect Pests of Camellia oleifera in Anhui Province

[Objectives]The paper was to master the species,incidence regularity and control techniques of main diseases and insect pests of Camellia oleifera in Anhui Province.[Methods]The species of main diseases and insect pests of C.oleifera in major C.oleifera afforestation bases and seedling bases in Anhui Province were investigated through field survey and literature search.Afterwards,the symptom characteristics,occurrence regularity and harms of diseases and insect pests were analyzed,and scientific and reasonable control techniques were put forward.[Results]The main diseases of C.oleifera in Anhui Province were soft rot disease,blister blight,anthracnose,sooty blotch,etc.,and the main insect pests were Euproctis pseudoconspersa,Biston marginata,Hypomeces squamosus,Curculio chinensts,Chrenoma atritarsis,etc.The control techniques mainly included ecological regulation,physical prevention and control,chemical prevention and control,and biological prevention and control.[Conclusions]The results will promote the high-quality development of C.oleifera industry in Anhui Province,and contribute to the improvement of China s edible vegetable oil supply and national grain and oil security.