CN104361412A - Decision-making potato late blight prevention and control system and method - Google Patents
Decision-making potato late blight prevention and control system and method Download PDFInfo
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Abstract
The invention provides a decision-making potato late blight prevention and control system and method and relates to the field of decision-making potato late blight prevention and control. The decision-making potato late blight prevention and control system and method aims at solving the problems that pesticides are abused, planting species of potatoes are single, only the influence on late blight germs, of environmental factors, is considered during disease prevention and control and data acquisition, transmission and release are not in time. The decision-making potato late blight prevention and control system consists of a multi-point synchronous wireless acquisition and transmission module, a decision-making early warning module, a data browsing and issuing module, a user management module and an infection curve definition module. The decision-making potato late blight prevention and control method for the system comprises the following steps of 1 obtaining an available output signal of meteorological data; 2 monitoring and collecting images; 3 transmitting the data to a mobile phone browse monitoring system and a potato late blight Web decision-making supporting system sub-module; 4 obtaining a disease development curve and determining the potential severity degree of disease occurrence; 5 releasing decision-making early warning information; 6 releasing decision-making early warning result information; 7 performing data disposal and statistics. The decision-making potato late blight prevention and control system and method is applied to the field of decision-making potato late blight prevention and control.
Description
Technical field
The present invention relates to late blight of potato control system and method.In particular to a kind of decision-making late blight of potato back-up system and method.
Background technology
The late blight caused by phytophthora infestans Phytophthora infestans (Mont.) de Bary endangers potato at present to produce the most serious disease, it has popular at a high speed, prevent and treat more difficult, the annual therefore sick whole world that causes loses about 17,000,000,000 dollars, China's loss about 1,000,000,000 dollars.For a long time, chemical prevention controls the late blight of potato the most effectively and the simplest method.But, in disease control process, ubiquity medication not in time with the problems such as pesticide abuse, just be difficult to effectively to control the generation of disease and popular not in time once medication, and pesticide abuse can make toxic chemical substance in plant, in water and enrichment in soil, a part of objectionable impurities just enters in crops and people's carcass by material recycle, severe contamination agricultural product and environment, more can work the mischief to health, thus cause various disease.Therefore, research late blight of potato decision support system (DSS), particularly important, it accurately can spray germifuge, also effectively can control the generation of disease and popular, namely reduce because this disease caused damage, stop pesticide abuse again, so not only reduce production cost, and reduce chemical agent to environmental pressure, therefore, being applied in potato production of late blight of potato decision support system (DSS) has extremely important meaning.
The late blight of potato decision support system (DSS) used in the world at present has 17, and each tool relative merits, they are applied to different potato production areas respectively, as the NegFry decision support system (DSS) (DSS) in the national widespread use such as Denmark, Germany, in the ProPhy decision support system (DSS) that Holland is used widely, also has the BLITECAST model of the U.S., the CASTOR prototype software etc. of International Potato Center, these model systems all effectively control the late blight of potato occur and popular.External potato prediction model mainly runs under particular locality and environment, and external potato planting kind is single, only considers that environmental factor affects late disease bacteria during disease control, data acquisition transmission and issue the shortcoming such as not in time.According to foreign technology defect, and China's late blight of potato occurs and characteristic distributions, sets up the prediction model being applicable to this area, is to solve the task of top priority that the late blight of potato prevents and treats problem.
Summary of the invention
The object of the invention is to solve pesticide abuse in potato planting process, potato planting kind is single, during disease control, only consider a kind of decision-making late blight of potato supportive device that environmental factor proposes late disease bacteria impact and data acquisition transmission and the problem not in time of issue and method.
Above-mentioned goal of the invention is achieved through the following technical solutions:
Described late blight of potato decision support system (DSS) comprises Multipoint synchronous wireless collection transport module, warning module, browsing data release module, user management module and infects curve definitions module composition; Wherein, Multipoint synchronous wireless collection transport module is GPRS or CDMA mobile radio telecommunications submodule, browsing data release module comprises the Web decision support system (DSS) submodule of the late blight of potato and supervisory system submodule browsed by mobile phone;
Described user management module is that native system arranges module to user management and system management, and Multipoint synchronous wireless collection transport module is carried out being transferred to warning module at field image data; Transmission data are carried out finishing analysis according to infecting curve definitions module by warning module, draw disease occurrence tendency; Disease occurrence tendency is browsed supervisory system submodule at the Web decision support system (DSS) submodule of the late blight of potato and mobile phone and is issued in time by browsing data release module, user network and mobile phone terminal can displaying live view field diseases a situation arises, carry out data query, Data Comparison, data statistics and description data and curves by the Web decision support system (DSS) submodule of the late blight of potato in time.
Described a kind of decision-making late blight of potato prevention and controls, is characterized in that it comprises the steps:
Point out the weather data of wind direction by gathering humiture, rainfall amount, wind speed and wind bar after step one, weather station adopt sensor to carry out meteorological detection, and convert the usable output signal of weather data to, wherein, sensor, weather station and collector take solar electric power supply system as power;
Step 2, spore seizing device catch field late blight pathogen spore, carry out field late blight pathogen spore data monitoring and collection in real time; A situation arises and the image of weather station situation to utilize high-definition camera Real-Time Monitoring and the collection field late blight of potato, wherein, high-definition camera and spore seizing device are with sun power solar electric power supply system for power, and the image of weather station situation comprises weather station ruuning situation and weather station distributed intelligence;
Step 3, GPRS or CDMA mobile radio telecommunications submodule in Multipoint synchronous wireless collection transport module will gather the geography information of weather station, browse supervisory system submodule by the Web decision support system (DSS) submodule of the late blight of potato in browsing data release module and mobile phone and browse geographic information data in display GIS map in real time in time and in real time by the geographic information data in GIS map, the field potato disease image that a situation arises and weather data are transferred in the database of laboratory background server and the mobile phone be sent in browsing data release module is browsed in supervisory system submodule and in the Web decision support system (DSS) submodule of the late blight of potato,
Step 4, utilization infect the data analysis of curve definitions module to the reception in background server database and draw the potential generation order of severity of disease progress curve determination disease; Wherein, the potential generation order of severity of disease is the chart of weather data, the chart catching field late blight pathogen spore data and the real-time field potato disease image that a situation arises;
Step 5, warning module will by the potential generation orders of severity of disease, according to the preliminary examination model of late blight prediction modular concept design late blight of potato monitoring and prediction, according to the preliminary examination model of late blight of potato monitoring and prediction, degree is infected to difference and issue warning information; Wherein, issue warning information comprises the potential occurrence degree of pathogen, field plant growing way situation, a situation arises and pathogen spore distribution situation for disease;
Step 6, utilize the Web decision support system (DSS) submodule of the late blight of potato in the Web decision support system (DSS) submodule of the late blight of potato to analyze decision-making early warning information after; Obtain warning result, according to warning result, the Web decision support system (DSS) submodule of the late blight of potato in browsing data release module is utilized to start note and mail Real-time Alarm issue warning object information, wherein, under warning object information is included in weather data and field late blight pathogen spore data qualification, the Varieties of the potato selected, and the information of pharmacy type and dosage;
Step 7, utilize the Web decision support system (DSS) submodule of the late blight of potato and mobile phone to browse supervisory system submodule to browse late blight warning information in time; This warning information is for sharing data, and shared data are the potential occurrence degree of pathogen, field plant growing way situation, a situation arises and pathogen spore distribution situation for disease; According to the breediness of prediction information and potato, late blight pathogen flora characteristic and fungicide feature information data, carry out arranging and adding up, in input database; Judge and spray germifuge in time and carry out disease control; Namely a kind of decision-making late blight of potato prevention and controls is completed.
Invention effect
In order to effectively prevent and treat the late blight of potato, reduce production cost and every mu of saving drug cost 70 yuan., excessive dispenser is avoided to work the mischief to environment, the invention provides a kind of late blight of potato decision support system (DSS), this system is by analyzing the real-time weather data (rainfall in field, relative humidity and temperature), late disease bacteria group property, correlativity between the influence factors such as cultivar resistance, set up late blight of potato decision support system (DSS), native system effectively enhances the foresight of preventing and treating the late blight of potato and planned, timely issue PD trend, avoid blindly dispenser, the economic benefit every mu improving preventing and controlling adopts Prediction model every mu ratio not spray medicine and increases income 702 yuan, ecological benefits and social benefit, make it more economically, safety, effectively.
The present invention applies Belgian prediction modular concept, that designs applicable Heilongjiang Province observes and predicts software, meteorological data collection, arrangement and output is carried out again according to the software of autonomous Design, last according to measuring and reporting system analysis, the best can be specified and spray the medicament time, and by the development of disease, investigation effect of chemical control, determines the best control prece of the late blight of potato.To setting up applicable this area late blight of potato early warning system, finally instruct peasant's dispenser, reach the effect of application, namely Prediction model is adopted to carry out disease control, can effectively control the late blight of potato occur and popular, and adopt Prediction model prophylactico-therapeutic measures, reduce by 2 dispensers, as shown in Figure 6 and Figure 7;
Many key elements such as native system combining environmental-pathogen-host are analyzed, mainly field weather data is adopted in real time in environment, by data stored in Sql-sever database, real-time analysis data, provide the late blight of potato and infect curve, humiture and rain fall; In pathogen, main collection this area late disease bacteria, and late disease bacteria group property is studied, announce pathogenic bacteria bulk properties in time, understand disease development and change rule; Host aspect is according to this area varieties of plant situation, and every year by field test, the potato of specifying different cultivars, to late disease bacteria resistance situation, by the situation such as varietal resistance and breeding time, adjusts prophylactico-therapeutic measures in time.By above data analysis, native system, in conjunction with chemical bactericide characteristic, formulates reasonable prophylactico-therapeutic measures, provides and definitely sprays the germifuge time, shares various information with Web with mobile phone browsing mode to user, can understand late blight of potato situation whenever and wherever possible.
The present invention adopts forecast of potato late blight forecast principle, and designed, designed observes and predicts software and weather data receives software, carries out prediction, sprays medicament in time, can effectively control late blight of potato Occurrence & epidemic to the production area late blight of potato.Display is compared by the field test of 2 years, adopt Prediction model prevention effect at field control effect and spray chemical control in every 7 days and can reach equivalent effect effect, and, utilize Prediction model can reduce germifuge access times, reduce costs, improve output and adopt Prediction model compared with the control, reducing little potato rate is 3.77%., reduce the pressure that chemical agent brings environment.Therefore, this model may be used for susceptible variety short-term late blight prediction completely.
The present invention is by monitoring terminal, wireless telecommunications (GPRS mobile communication technology (wireless transport module) the Web technology in Multipoint synchronous wireless collection transport module) plant protection knowledge, epidemic disease knowledge, expertise, artificial intelligence technology, Geographic Information System (GIS), decision support system (DSS) (DSS) organically combines, Real-Time Monitoring can be carried out to the late blight of potato information of each survey station operating area, early warning and diagnosis, whether the potato of Cotton Varieties by Small Farming Households is caught an illness and carries out the forecast and decision of science the need of medical treatment, directly serve for potato produces.
Traditional Monitoring Data process means are relatively backward, such as: send mail, make a phone call, send a telegram.These means can not transmit data in time.Greatly reduce real-time and the accuracy rate of information.The present invention realizes by internet and cell phone network, and by native system platform, a situation arises can accurately to grasp disease in real time, and historical data, significantly improves and prevent and treat efficiency.
Accompanying drawing explanation
Fig. 1 is the decision-making late blight of potato control System's composition figure that embodiment two proposes;
Fig. 2 is the late blight of potato control decision making interface schematic diagram that embodiment one proposes;
Fig. 3 is that the early warning that embodiment two proposes sends early warning information interface schematic diagram;
Fig. 4 is that the late blight of potato that embodiment two proposes potentially infects curvilinear trend figure; Wherein, ordinate is medial temperature score value, and horizontal ordinate infected curve first for the first generation (not easily finding scab) July 1,28 and 30; July 5,16,12,23 and 29 infects curve first for the second generation (indivedual scab); July 24,25,26 and 27 infects curve first for the third generation (scab); According to recent weather forecast, when the third generation infect first reach 4 ~ 6 points time, adopt protective agent spraying; If rained at that time, miss spraying time, adopt protection therapeutic agent or therapeutic agent spraying; Later per the infecting first of generation of forth generation reaches 4 ~ 6 timesharing, adopts protective agent spraying; If rained at that time, miss spraying time, adopt protection therapeutic agent or therapeutic agent spraying;
Fig. 5 is medicament, the medical instruments recommendation interface schematic diagram that embodiment two proposes;
Fig. 6 is the Web decision support system (DSS) interface schematic diagram of the late blight of potato that embodiment two proposes;
Fig. 7 is that supervisory system submodule schematic diagram browsed by the mobile phone that embodiment two proposes;
Fig. 8 is data real-time query interface, the weather station schematic diagram that embodiment two proposes;
Fig. 9 is the different regions weather data comparison surface chart that embodiment two proposes;
Figure 10 is the different regions weather data statistics schematic diagram that embodiment two proposes;
Figure 11 is the weather data curve interface schematic diagram that embodiment two proposes;
Figure 12 is the weather monitoring station information schematic diagram that embodiment two proposes;
Figure 13 is the subscriber administration interface schematic diagram that embodiment two proposes;
Figure 14 arranges interface schematic diagram the potato planting monitoring phase that embodiment two proposes;
Figure 15 is that the late blight of potato that embodiment two proposes infects curve synoptic diagram; Wherein, 1 for the late blight of potato infect the lighter curve of potential generation, 2 late blights of potato infect the medium curve of potential generation, 3 late blights of potato infect the curve that potential generation is heavier and 4 potential generations are more serious;
Figure 16 is the different weather stations humid period statistics schematic diagram that embodiment two proposes;
Figure 17 is Heilongjiang Province's late blight of potato decision support system (DSS) fact monitoring schematic diagram that embodiment two proposes;
Figure 18 is the geographic information data schematic diagram in the GIS map of embodiment three proposition;
Figure 19 is that the mobile phone that embodiment three proposes is browsed supervisory system submodule and browsed the geography information schematic diagram be presented in real time in GIS map;
Figure 20 be embodiment three propose the pathogenetic order of severity of late blight and humid period continuing relationship schematic diagram;
Figure 21 is the late blight of potato pathogen flora quality event schematic diagram that embodiment three proposes;
Figure 22 is the application field control effect schematic diagram of the present invention proposed in embodiment
Figure 23 is the susceptible variety disease progress curve schematic diagram of the different disposal in 2010 proposed in embodiment
Figure 24 be between the different disposal in 2010 that propose in embodiment AUDPC value wherein, CK is blank; MH is model treatment; UH is the process of every 7 days spray medicines;
Figure 25 is the different disposal large, medium and small potato rate results in 2010 proposed in embodiment; Wherein, CK is blank; MH is model treatment; UH is the process of every 7 days spray medicines;
Figure 26 is the field diseases development trend schematic diagram in 2011 proposed in embodiment;
Figure 27 is the field diseases progress curve figure in 2011 proposed in embodiment; Wherein, CK is blank group
Figure 28 is the different disposal AUDPC value schematic diagram in 2011 proposed in embodiment; Wherein, CK is blank
Figure 29 is the late blight of potato decision support system (DSS) fortune process flow diagram that embodiment three proposes.
Embodiment
Embodiment one: a kind of decision-making late blight of potato of present embodiment prevents and treats system, specifically comprises: Multipoint synchronous wireless collection transport module (data acquisition transport module), warning module, browsing data release module, user management module and infect curve definitions module composition; Wherein, Multipoint synchronous wireless collection transport module is GPRS or CDMA mobile radio telecommunications submodule (wireless transmission submodule), browsing data release module comprises the Web decision support system (DSS) submodule of the late blight of potato and supervisory system submodule browsed by mobile phone;
Described user management module is that native system arranges module to user management and system management, and Multipoint synchronous wireless collection transport module is carried out being transferred to warning module at field image data; Transmission data are carried out finishing analysis according to infecting curve definitions module by warning module, draw disease occurrence tendency; Disease occurrence tendency is browsed supervisory system submodule at the Web decision support system (DSS) submodule of the late blight of potato and mobile phone and is issued in time by browsing data release module, user network and mobile phone terminal can displaying live view field diseases a situation arises, carry out data query, Data Comparison, data statistics and description data and curves as Fig. 2 by the Web decision support system (DSS) submodule of the late blight of potato in time.
Present embodiment effect:
Late blight of potato decision support system (DSS) is that collection disease is ecological, biology, and a complex art based on the subject such as climatology, mathematical statistics, crop cultivation, it mainly applies late blight of potato disease control work, native system predicts occurrence tendency and the extent of injury of disease exactly, in conjunction with pathogen and cultivar quality event, provide and rationally spray germifuge time and type, thus make the occurrence index of disease force down below economic injury level, guarantee the healthy growth of potato.
Forecast of potato late blight forecasting model is mainly used in late blight of potato preventing and controlling, is the utility of serving vast potato manufacturing enterprise and peasant, greatly can be reduced the production cost of enterprise and peasant by this technology.Carry out measuring and calculating according to current pesticide market price to show, prevent and treat late blight cost be 120-225 unit/hectare/time, our province potato planting area 500,000 hectares, if all prevented and treated, the rational use of medicines under measuring and reporting system instructs, reduces once unnecessary dispenser and just can save production cost 0.6 hundred million-1.125 hundred million yuans.In addition, the system documentation that the late blight work of observing and predicting accumulates, can be grasp its dynamic rule further, and even use the Theories and methods of system analysis engineering to analyze the relation of all kinds of factor and late blight occurring and damage in farmland ecosystem, provide scientific basis for working out the most rational integrated control scheme with suiting measures to local conditions.Therefore, the potato that this work is not only related to this season then produces, and has strategic importance to the overall benefit improving long-term integrated control, and then promotes the health of Potato Industry, stable, sustainable development.
1. the present invention since two thousand nine, within continuous 4 years, multispots trial, test and application are carried out, this observes and predicts system and applies in regional potato planting bases such as surrounding area, Harbin, Zhaodong, Yian and Keshans, so far add up to set up secondary 11 of late blight prediction station, measuring and reporting system application area reaches 13.95 ten thousand mu, the application of this technology, object of being directly benefited has more than 1500 potato planting person.
2. this technology is by setting up the prognoses system of zones of different climatic model, strengthen and prevent and treat the foresight of the late blight of potato and planned, timely issue PD trend, avoid blindly dispenser, not only effectively reduce the production cost of pesticide control, decrease chemical agent environmental pollution simultaneously, improve the economic benefit of preventing and controlling, ecological benefits and social benefit comprehensively, make it more economically, safety, effectively.Therefore, being applied in of forecast of potato late blight forecasting model Development of Potato Industry has high practical value and important social effect.2009-2012 continuous 4 years applied forcasting forecasting techniques are prevented and treated late blight of potato prevention effect and are reached 80-95%, and reduce pesticide dosage 15-20%, reduce costs 20%, output increased 30-50%, peasant's mu increases income 1000-2000 unit, cost-saving 1,176 ten thousand yuan.Both reduce production cost, protection of the environment, improve farmers' income again.
3. the present invention establishes an automatic processing enter of weather data, realizes the unified management of data real-time online, for the further genralrlization application of this technology provides complete hardware support.
Embodiment two: present embodiment and embodiment one unlike: described Multipoint synchronous wireless collection transport module and GPRS mobile communication technology are that latest generation divides into groups to shift transmission mode, take solar panels as power, Multipoint synchronous image data allows user to transmit and receive data under end-to-end packet transfer mode, and does not need the Internet resources utilizing circuit switched mode; Collection meteorology and field data are carried out data transmission, is transferred to GPRS or CDMA mobile radio telecommunications submodule, reports real-time weather and field data (as Fig. 1) by GPRS or CDMA mobile radio telecommunications submodule to server;
Described warning module is used for utilizing background server to carry out Treatment Analysis to reception data, is that the decision-making late blight of potato prevents and treats system core component representation layer, main issue late blight control decision making, early warning transmission, medicament medical instruments and agricultural chemicals information; Wherein, control decision making: to whether dispenser, when dispenser provides a basis for estimation, direct reflection warning result, the Preventive guidance of certain limit is artificially proposed according to design needs and warning result, and according on the basis that the preliminary examination model of late blight prediction modular concept design late blight of potato monitoring and prediction has defined, each test process infects degree to difference and carries out point emphasis prompting (as Fig. 2); Early warning sends: adopt SMS (Short Messaging Service) platform, sends late blight epidemic situation and instructs remedial proposal, allow user understand information in time to user, carries out control and prepares, grasp the best laxative time; Also there is the function (as Fig. 3) such as e-mail transmitting function and increase, deletion and amendment user profile simultaneously; Control decision making principle: mainly some of the process of preventing and treating are elaborated and explained (as Fig. 4); Medicament and medical instruments are recommended: mainly to some introductions (as Fig. 5) making with medicament, medical instruments;
Described browsing data release module is used for warning module analysis to obtain a result by network or mobile phone terminal real-time release; Browsing data release module comprises the Web decision support system (DSS) submodule (as Fig. 6) of the late blight of potato and supervisory system submodule (as Fig. 7) browsed by mobile phone, wherein, the Web decision support system (DSS) submodule of the late blight of potato is used for data query, Data Comparison, data statistics, data and curves and monitoring station information; Data query accurately inquires about weather station data (as Fig. 8) by selecting inquiry mode (day inquiry, moon inquiry) and Query Dates; Data Comparison: Data Comparison is by select time point, contrasts the data (as Fig. 9) of different weather stations synchronization; Data statistics is the data statistics to certain month of monitoring point, mainly comprises the average data in sky, extreme value data, and the statistics (as Figure 10) of the upper last ten-days period and moon summary; Data and curves is divided: day inquiry, moon inquiry, selects date-time, find the data and curves figure (as Figure 11) such as temperature on average, medial humidity, the highest temperature, the lowest temperature according to the website that will inquire about; The each website longitude and latitude of monitoring station information record, better address and nearest data time (as Figure 12); Mobile phone browses supervisory system submodule for the real-time weather data analysis of mobile phone terminal, has above function too;
Described user management module comprises: user management, New Management, pictures management; User management: for the Permission Levels according to system user, carries out user's configuration respectively, can give keeper, user distributes different authorities, can delete simultaneously, revise; In future along with native system application area expands gradually, this module will play larger effect; Wherein, user's configuration comprises configure user administration authority, Chief browsing data and the issue (as Figure 13) that predicts the outcome; New Management: relevant be in charge of personnel and can add relevant late blight of potato data, important control decision making, potato working conference, documentary whip etc. information; Pictures management: upload the pictorial information shared about potato aspect;
Described infect curve definitions module for the phase of monitoring arrange, the late blight of potato infects curve, humid period statistics, live monitoring and pathogen flora specificity analysis; The monitoring phase arranges and is used for arranging seeding stage and harvest time, guarantee potato precocious, in ripe, late variety can to monitor in whole growth course and more accurately (Figure 14); Infect curve for infecting the curve such as curve, temperature and humidity (Figure 15) according to the statistics drafting late blight of potato that infects in the monitoring phase; Humid period, statistics was used for after humidity is more than or equal to 90%, and can find out start time and end time, how long (Figure 16) final high humidity continue for; Live monitoring is used for checking the situations such as the generation of field potato growing way, disease and the generation of late blight spore, pathogen flora specificity analysis is mainly used in analyzing pathogen flora quality event in former years, carries out comprehensive descision (Figure 17) to pathogen control.Other step and parameter identical with embodiment one.
Embodiment three: present embodiment and embodiment one or two unlike: step one, the weather station being with field to protect cabinet adopt sensor to carry out meteorologically detecting the Vantage Pro2 automatic meteorological measuring instrument that DAVIS company of the Hou Ji U.S. produces and pointing out that wind direction has the weather data in 8 orientation etc. by gathering humiture, rainfall amount, wind speed and wind bar, and convert the usable output signal of weather data to, wherein, sensor, weather station and collector take solar electric power supply system as power;
Step 2, spore seizing device catch field late blight pathogen spore, carry out field late blight pathogen spore data monitoring and collection in real time; For plant disease prevention forecast provides accurate data support more; A situation arises and the image of weather station situation with collecting the field late blight of potato to utilize high-definition camera and large resolution camera (large resolution camera model and resolving range) Real-Time Monitoring, wherein, high-definition camera and spore seizing device with sun power solar electric power supply system for power, the field potato disease image that a situation arises is specially field potato leaf health degree, and whether blade falls ill and the order of severity of falling ill; The image of weather station situation comprises weather station ruuning situation and weather station distributed intelligence;
The weather data collected and image data are carried out remote transmission by GPRS or CDMA mobile radio telecommunications submodule (wireless transport module) the i.e. mobile network in step 3, Multipoint synchronous wireless collection transport module, to the geography information (latitude and longitude coordinates) of weather station be gathered, and browse supervisory system submodule by the Web decision support system (DSS) submodule of the late blight of potato in browsing data release module and mobile phone and browse geographic information data (Figure 18 and Figure 19) in display GIS map in real time in time; GIS map can go out mounted monitoring station, monitoring information inquiry can be carried out to corresponding monitoring station in Directory Enquiries, or the monitoring station clicked in GIS map ejects monitoring information; The color of each monitoring station represents: grey (countless certificate), green (without infecting), blue (generation infects), yellow (two generations infected), red flicker (more than three generations infecting); And in real time the geographic information data in GIS map, the field potato disease image that a situation arises and weather data to be transferred in the Sql Serve database of laboratory background server and the mobile phone be sent in browsing data release module is browsed in the Web decision support system (DSS) submodule of (Fig. 6) and the late blight of potato in supervisory system submodule (Fig. 7);
Step 4, utilize and infect the data analysis of curve definitions module to the reception in background server database and show that disease progress curve (i.e. the late blight of potato infect curve) determines the potential generation order of severity (Figure 20) of disease; Wherein, the potential generation order of severity of disease is the chart (Figure 15) of weather data, the chart catching field late blight pathogen spore data and the real-time field potato disease image that a situation arises (Figure 17);
Step 5, warning module will by the potential generation orders of severity of disease, according to the preliminary examination model of late blight prediction modular concept design late blight of potato monitoring and prediction, (difference infects degree and is divided into 5 kinds of degree, and grey (countless certificate), green (without infecting), blue (generation infects), yellow (two generations infected), red flicker (more than three generations infecting) carry out a point emphasis (how a point emphasis divides) issue warning information to infect degree according to the preliminary examination model of late blight of potato monitoring and prediction to difference; Wherein, issue warning information comprises the potential occurrence degree of pathogen, field plant growing way situation, a situation arises and pathogen spore distribution situation (Figure 21) for disease;
Step 6, utilize the Web decision support system (DSS) submodule of the late blight of potato in the Web decision support system (DSS) submodule of the late blight of potato to analyze decision-making early warning information after; Obtain warning result, according to warning result, utilize Web decision support system (DSS) (DSS) submodule of the late blight of potato in browsing data release module to start note such as Fig. 3 and mail Real-time Alarm for the power of epidemic situation and disease time and issue warning object information as Fig. 3, wherein, under warning object information is included in weather data and field late blight pathogen spore data qualification, the Varieties of the potato selected, and the information of pharmacy type and dosage;
Step 7, utilize the Web decision support system (DSS) submodule of the late blight of potato and mobile phone to browse supervisory system submodule to browse late blight warning information in time; This warning information is for sharing data, and shared data are the potential occurrence degree of pathogen, field plant growing way situation, a situation arises and pathogen spore distribution situation (Figure 21) for disease; Can by lander's displaying live view disease monitoring data of province, city and affiliated relevant departments thereof; According to the breediness (breeding time and disease resistance) of prediction information and potato, late blight pathogen flora characteristic if Figure 21 and fungicide feature information data are as Fig. 5, carry out arranging and adding up, in input database; Judge and spray germifuge in time and carry out disease control; Thus Real-Time Monitoring, early warning and diagnosis are carried out to the late blight of potato information of each survey station operating area, whether the potato of Cotton Varieties by Small Farming Households caught an illness and carries out the forecast and decision of science the need of medical treatment, directly serving for potato produces; By installing mobile phone client software, reach any time, any place to the real-time monitoring (flow process is shown in Figure 29) of the late blight of potato.Other step and parameter identical with embodiment one or two.
Embodiment four: one of present embodiment and embodiment one to three unlike: in step 3, background server uses Hibernate, Quartz task scheduling, JB flow process, Brit report tool, Spring framework mode and development platform to carry out early warning information issue in time.Other step and parameter identical with one of embodiment one to three.
Embodiment five: one of present embodiment and embodiment one to four are that breeding time and disease resistance are as Figure 20 unlike the breediness of: the potato selected in step 7, late blight pathogen flora characteristic is late disease bacteria biological strain, the mating type of late disease bacteria and to drug resistance if Figure 21 and fungicide feature information data are that germifuge lasting period, bactericidal agent for preventing and treating effect and germifuge type information are as Fig. 5.Other step and parameter identical with one of embodiment one to four.
Following examples are adopted to verify beneficial effect of the present invention:
Embodiment one:
A kind of decision-making late blight of potato back-up system of the present embodiment and method, specifically prepare according to following steps:
By gathering humiture, rainfall amount, wind speed and wind bar, step one, the Vantage Pro2 automatic meteorological measuring instrument being with the weather station of field protection cabinet to adopt sensor to carry out the production of DAVIS company of the meteorological detection Hou Ji U.S. point out that wind direction has the weather data in 8 orientation etc., and convert the usable output signal of weather data to, wherein, sensor, weather station and collector take solar electric power supply system as power;
Step 2, spore seizing device catch field late blight pathogen spore, carry out field late blight pathogen spore data monitoring and collection in real time; For plant disease prevention forecast provides accurate data support more; A situation arises and the image of weather station situation with collecting the field late blight of potato to utilize high-definition camera and large resolution camera (large resolution camera model and resolving range) Real-Time Monitoring, wherein, high-definition camera and spore seizing device with sun power solar electric power supply system for power, the spread spectrum frequency hopping wireless power technology of Vantage Pro2 automatic meteorological measuring instrument, wireless transmission is up to 300 meters, and weather data upgrades for every 2.5 seconds; The field potato disease image that a situation arises is specially field potato leaf health degree, and whether blade falls ill and the order of severity of falling ill; The image of weather station situation comprises weather station ruuning situation and weather station distributed intelligence;
The weather data collected and image data are carried out remote transmission by GPRS or CDMA mobile radio telecommunications submodule (wireless transport module) the i.e. mobile network in step 3, Multipoint synchronous wireless collection transport module, to the geography information (latitude and longitude coordinates) of weather station be gathered, and browse supervisory system submodule by the Web decision support system (DSS) submodule of the late blight of potato in browsing data release module and mobile phone and browse geographic information data (Figure 18 and Figure 19) in display GIS map in real time in time; GIS map can go out mounted monitoring station, monitoring information inquiry can be carried out to corresponding monitoring station in Directory Enquiries, or the monitoring station clicked in GIS map ejects monitoring information.The color of each monitoring station represents: grey (countless certificate), green (without infecting), blue (generation infects), yellow (two generations infected), red flicker (more than three generations infecting).And in real time the geographic information data in GIS map, the field potato disease image that a situation arises and weather data to be transferred in the Sql Serve database of laboratory background server and the mobile phone be sent in browsing data release module is browsed in the Web decision support system (DSS) submodule of (Fig. 6) and the late blight of potato in supervisory system submodule (Fig. 7); Wherein, background server uses Hibernate, Quartz task scheduling, JB flow process, Brit report tool, Spring framework mode and development platform to carry out early warning information issue in time;
Step 4, utilize and infect the data analysis of curve definitions module to the reception in background server database and show that disease progress curve (i.e. the late blight of potato infect curve) determines the potential generation order of severity (Figure 20) of disease; Wherein, the potential generation order of severity of disease is the chart (Figure 15) of weather data, the chart catching field late blight pathogen spore data and the real-time field potato disease image that a situation arises (Figure 17);
Step 5, warning module will by the potential generation orders of severity of disease, according to the preliminary examination model of late blight prediction modular concept design late blight of potato monitoring and prediction, (difference infects degree and is divided into 5 kinds of degree, and grey (countless certificate), green (without infecting), blue (generation infects), yellow (two generations infected), red flicker (more than three generations infecting) carry out a point emphasis (how a point emphasis divides) issue warning information to infect degree according to the preliminary examination model of late blight of potato monitoring and prediction to difference; Wherein, issue warning information comprises the potential occurrence degree of pathogen, field plant growing way situation, a situation arises and pathogen spore distribution situation (Figure 21) for disease;
Step 6, utilize the Web decision support system (DSS) submodule of the late blight of potato in the Web decision support system (DSS) submodule of the late blight of potato to analyze decision-making early warning information after; Obtain warning result, according to warning result, utilize Web decision support system (DSS) (DSS) submodule of the late blight of potato in browsing data release module to start note such as Fig. 3 and mail Real-time Alarm for the power of epidemic situation and disease time and issue warning object information as Fig. 3, by Web technology, the Web decision support system (DSS) submodule of the late blight of potato of the data in server in browsing data release module and mobile phone are browsed the network address of supervisory system submodule
http: // 218.70..37.104:7003/ input username and password conducts interviews; Wherein, under warning object information is included in weather data and field late blight pathogen spore data qualification, the Varieties of the potato selected, and the information of pharmacy type and dosage;
Step 7, utilize the Web decision support system (DSS) submodule of the late blight of potato and mobile phone to browse supervisory system submodule to browse late blight warning information in time; This warning information is for sharing data, and shared data are the potential occurrence degree of pathogen, field plant growing way situation, a situation arises and pathogen spore distribution situation (Figure 21) for disease; Can by lander's displaying live view disease monitoring data of province, city and affiliated relevant departments thereof; According to the breediness (breeding time and disease resistance) of prediction information and potato, late blight pathogen flora characteristic if Figure 21 and fungicide feature information data are as Fig. 5, carry out arranging and adding up, in input database; Judge and spray germifuge in time and carry out disease control; Thus Real-Time Monitoring, early warning and diagnosis are carried out to the late blight of potato information of each survey station operating area, whether the potato of Cotton Varieties by Small Farming Households caught an illness and carries out the forecast and decision of science the need of medical treatment, directly serving for potato produces.By installing mobile phone client software, reach any time, any place to the real-time monitoring of the late blight of potato.(flow process is shown in Figure 29), wherein, the breediness of the potato selected is that breeding time and disease resistance are as Figure 20, late blight pathogen flora characteristic is late disease bacteria biological strain, the mating type of late disease bacteria and to drug resistance if Figure 21 and fungicide feature information data are that germifuge lasting period, bactericidal agent for preventing and treating effect and germifuge type information are as Fig. 5.
Judge 1:
Carry out laboratory test according to collection pathogen, if developed immunity to drugs to certain medicament, avoid using this germifuge, or use germifuge on a small quantity.If biological strain presents complicated, compositeness microspecies dominate, illustrates Pathogenic grow, should upgrade use germifuge.
Judge 2:
Breeding time, general potato was from being seeded into the real ripe total number of days of son, and potato is generally divided into early-maturing variety, medium variety and late variety.Breeding time, difference sprayed germifuge number of times difference;
Variety resistance standard:
According to different cultivars resistance, the disease index >40 if susceptible variety adds up, middle sense kind adds up disease index >45, in anti-kind to add up disease index >50 (in anti-kind), just need the 2nd spray medicine, afterwards, cumulative rainfall amount and disease index return 0, restart to calculate, determine spraying time next time.
Table 3 Variety Disease-resistance standard
Judge 3:
The germifuge drug effect lasting period is respectively 5 days, 7 days or 10 days, and that is medicament can ensure number of days effective time; Germifuge type is respectively inner sucting conduction type and protection type and interior suction and protection and takes into account type, and according to breeding time and pathogen, a situation arises, if seedling stage, suggestion sprayed protection type germifuge; If fallen ill, suggestion sprays inner sucting conduction type germifuge; If harvest time or potato block expanding stage sprays interior suction and protection takes into account type.
Judge 4:
The potential degree that infects is divided into 5 ranks by Prediction model, is respectively without infecting, slightly infects, moderate infects, heavy infestation and extremely heavily infecting.Can judge that the potential of late blight infects degree according to Figure 20, continue hourage when horizontal ordinate represents relative humidity >=90%, ordinate represents medial temperature.Such as: when medial temperature is 7 DEG C, relative humidity >=90%, as lasting hourage < 16.5h is " without infecting "; As lasting hourage >=16.5h < 19.5h be " slightly infecting "; When lasting hourage >=when continuing hour < 22.5h be " moderate infects ", when lasting hourage >=be " heavy infestation " when continuing hour < 25.5h; When lasting hourage >=when continuing little is " extremely infect " constantly.By that analogy, determine that the late blight of potato infects the order of severity.
According to Prediction model principle, each course of disease infects curve to be needed to obtain accumulated value and reaches the process that 7 points of---spore germination---new spores that just can complete spore maturation infect.If must reach 7 points, a course of disease infects curve and terminates, and if now do not take prophylactico-therapeutic measures, then likely see and infect the scab on blade or the mould layer of the white on it.The score value of every day draws according to table 4.Then add up by sky, must reach 7 points is that the course of disease infects curve and terminates.Best spraying time is each circulation score accumulated value time corresponding to 5 ~ 6 timesharing, then determines spray date next time according to germifuge lasting period, rainfall, varietal resistance and new Infection cycie.
Table 4 Infection cycie infects the calculating standard of curve score every day
Judge 5:
Judge by grower, 1234 determine that how spraying germifuge carries out disease control more than comprehensive.Step 8, user management module is utilized to manage user, news and picture.Wherein, user management: for the Permission Levels according to system user, carries out user's configuration respectively, can give keeper, user distributes different authorities, can delete and revise simultaneously; As namely Fig. 1 completes a kind of decision-making late blight of potato prevention and controls.
(3) finally determine spraying time and type, carry out comprehensive control of disease.
1) field control effect in 2010
A. field control effect
Investigated by field diseases, result shows: first contrast CK falls ill, date of the onset is July 18, only have 3 ~ 5 blade morbidities, other process is not all fallen ill, and shows disease progress curve by Fig. 4, adopt Prediction model dispenser and every 7 days dispenser process disease slower developments, terminate to breeding time, disease percent incidence is only 7% and 4%, CK contrast all death on August 16.Calculate AUDPC value, contrast CK is 23.13, Prediction model is treated to 1.98, within every 7 days, spray medicine is treated to 1.31, variance significance analysis is carried out by the multiple range method of Duncan (LSR method), adopt Prediction model spray with every AUDPC value spraying medicine process for 7 days with contrast CK process and compare and reach the pole level of signifiance, other is more not remarkable between processing.Illustrate to adopt Prediction model to prevent and treat late blight effect and adopt disease-resistant variety and spray reagent agent in every 7 days and reach equivalent effect, as shown in Figure 22 and Figure 23.
B. different disposal useful output interpretation of result
Different disposal output is different, output is the highest is spray medicine process (UH) in every 7 days, next is Prediction model process (MH) and contrast (CK), the multiple range method of Duncan (LSR method) is adopted to carry out variance significance analysis, effect of increasing production extremely significantly (table 1) compared with contrast CK, more not remarkable between other process.UH volume increase is up to 30.94%, MH volume increase 25.56%.Late blight rotten potato rate investigation result shows, and rotten potato rate is the highest is contrast CK, and reaching 2.22%, is secondly UH and MH (table 1).
Table 1 different disposal output and rotten potato rate measure
Carry out large, medium and small potato rate to different disposal to investigate, result shows: disease-controlling effect is better, and corresponding little potato rate is lower, and big-and-middle potato rate is higher, and commodity potato rate is also higher, and little potato rate is minimum is UH, is 4.74%, and being secondly MH, is 4.88%.Contrast CK is 8.65%.Adopt Prediction model compared with the control, reducing little potato rate is 3.77%, as Figure 24.
C. Economic and Efficiency Analysis
Evaluation of economic benefit is carried out to the late blight of potato of different disposal.Prediction model volume increase value is adopted to be 852 yuan, except labour cost, deduction drug cost 150 yuan, newly-increased net return 702 yuan; Within every 7 days, spray medicine process volume increase value is 895 yuan, deduction drug cost 220 yuan, newly-increased net return 675 yuan.Draw thus, adopt Prediction model every mu ratio not spray medicine and increase income 702 yuan, increase production 27 yuan than the process of every 7 days spray medicines, save drug cost 70 yuan.Show to adopt disease-resistant variety significantly to increase income, if plantation susceptible variety, adopt Prediction model can produce obvious economic benefit, Pesticide use amount can be reduced again, reach increasing both production and income object as Figure 25.
Table 2 different disposal late blight of potato evaluation of economic benefit
Note: be 1 yuan of/kilogram of calculating by potato market average price.
2) late blight of potato prevention effect in 2011
Late blight of potato prevention effect, the different disposal disease generation order of severity, calculates different disposal AUDPC value by inquiry, size according to the value of AUDPC weighs different disposal prevention effect, if AUDPC value is high, illustrate that prevention effect is more bad, otherwise, prevention effect highly significant.Can find out disease evolution by Figure 26, Figure 27 and Figure 28, Prediction model process (MH) and every 7 days dispenser process (UH) two lines almost overlap, and illustrate that prevention effect is substantially identical.Then, comparative analysis is carried out after being converted into AUDPC value, Prediction model process (MH) and every 7 days dispenser process (UH) with contrast ratio extremely remarkable, and not remarkable between the two, illustrate, adopt Prediction model to carry out disease control, can effectively control the late blight of potato occur and popular, and adopt Prediction model prophylactico-therapeutic measures, reduce by 2 dispensers, reduce production cost 50 yuan.Production can be applied completely, on field reagent sprays, accomplished object, proper application, avoid chemical agent to waste.
The present invention also can have other various embodiments; when not deviating from the present invention's spirit and essence thereof; those skilled in the art are when making various corresponding change and distortion according to the present invention, but these change accordingly and are out of shape the protection domain that all should belong to the claim appended by the present invention.The present invention also can have other various embodiments; when not deviating from the present invention's spirit and essence thereof; those skilled in the art are when making various corresponding change and distortion according to the present invention, but these change accordingly and are out of shape the protection domain that all should belong to the claim appended by the present invention.
Claims (5)
1. the decision-making late blight of potato prevents and treats a system, it is characterized in that: described late blight of potato decision support system (DSS) comprises Multipoint synchronous wireless collection transport module, warning module, browsing data release module, user management module and infects curve definitions module composition; Wherein, Multipoint synchronous wireless collection transport module is GPRS or CDMA mobile radio telecommunications submodule, browsing data release module comprises the Web decision support system (DSS) submodule of the late blight of potato and supervisory system submodule browsed by mobile phone;
Described user management module is that native system arranges module to user management and system management, and Multipoint synchronous wireless collection transport module is carried out being transferred to warning module at field image data; Transmission data are carried out finishing analysis according to infecting curve definitions module by warning module, draw disease occurrence tendency; Disease occurrence tendency is browsed supervisory system submodule at the Web decision support system (DSS) submodule of the late blight of potato and mobile phone and is issued in time by browsing data release module, user network and mobile phone terminal can displaying live view field diseases a situation arises, carry out data query, Data Comparison, data statistics and description data and curves by the Web decision support system (DSS) submodule of the late blight of potato in time.
2. a kind of decision-making late blight of potato system of preventing and treating is characterized in that according to claim 1:
Described Multipoint synchronous wireless collection transport module take solar panels as power, and Multipoint synchronous image data allows user to transmit and receive data under end-to-end packet transfer mode; Collection meteorology and field data are carried out data transmission, is transferred to GPRS or CDMA mobile radio telecommunications submodule, reports real-time weather and field data by GPRS or CDMA mobile radio telecommunications submodule to server;
Described warning module is used for utilizing background server to carry out Treatment Analysis to reception data, is that the decision-making late blight of potato prevents and treats system core component representation layer, main issue late blight control decision making, early warning transmission, medicament medical instruments and agricultural chemicals information;
Described browsing data release module is used for warning module analysis to obtain a result by network or mobile phone terminal real-time release; Browsing data release module comprises the Web decision support system (DSS) submodule of the late blight of potato and supervisory system submodule browsed by mobile phone; Wherein, the Web decision support system (DSS) submodule of the late blight of potato is used for data query, Data Comparison, data statistics, data and curves and monitoring station information; Mobile phone browses supervisory system submodule for the real-time weather data analysis of mobile phone terminal;
Described user management module comprises: user management, New Management, pictures management; User management: for the Permission Levels according to system user, carries out user's configuration respectively, can give keeper, user distributes different authorities, can delete simultaneously, revise; Wherein, user's configuration comprises configure user administration authority, Chief browsing data and the issue that predicts the outcome;
Described infect curve definitions module for the phase of monitoring arrange, the late blight of potato infects curve, humid period statistics, live monitoring and pathogen flora specificity analysis.
3. a decision-making late blight of potato prevention and controls, is characterized in that it comprises the steps:
Point out the weather data of wind direction by gathering humiture, rainfall amount, wind speed and wind bar after step one, weather station adopt sensor to carry out meteorological detection, and convert the usable output signal of weather data to, wherein, sensor, weather station and collector take solar electric power supply system as power;
Step 2, spore seizing device catch field late blight pathogen spore, carry out field late blight pathogen spore data monitoring and collection in real time; A situation arises and the image of weather station situation to utilize high-definition camera Real-Time Monitoring and the collection field late blight of potato, wherein, high-definition camera and spore seizing device are with sun power solar electric power supply system for power, and the image of weather station situation comprises weather station ruuning situation and weather station distributed intelligence;
Step 3, GPRS or CDMA mobile radio telecommunications submodule in Multipoint synchronous wireless collection transport module will gather the geography information of weather station, browse supervisory system submodule by the Web decision support system (DSS) submodule of the late blight of potato in browsing data release module and mobile phone and browse geographic information data in display GIS map in real time in time and in real time by the geographic information data in GIS map, the field potato disease image that a situation arises and weather data are transferred in the database of laboratory background server and the mobile phone be sent in browsing data release module is browsed in supervisory system submodule and in the Web decision support system (DSS) submodule of the late blight of potato,
Step 4, utilization infect the data analysis of curve definitions module to the reception in background server database and draw the potential generation order of severity of disease progress curve determination disease; Wherein, the potential generation order of severity of disease is the chart of weather data, the chart catching field late blight pathogen spore data and the real-time field potato disease image that a situation arises;
Step 5, warning module will by the potential generation orders of severity of disease, according to the preliminary examination model of late blight prediction modular concept design late blight of potato monitoring and prediction, according to the preliminary examination model of late blight of potato monitoring and prediction, degree is infected to difference and issue warning information; Wherein, issue warning information comprises the potential occurrence degree of pathogen, field plant growing way situation, a situation arises and pathogen spore distribution situation for disease;
Step 6, utilize the Web decision support system (DSS) submodule of the late blight of potato in the Web decision support system (DSS) submodule of the late blight of potato to analyze decision-making early warning information after; Obtain warning result, according to warning result, the Web decision support system (DSS) submodule of the late blight of potato in browsing data release module is utilized to start note and mail Real-time Alarm issue warning object information, wherein, under warning object information is included in weather data and field late blight pathogen spore data qualification, the Varieties of the potato selected, and the information of pharmacy type and dosage;
Step 7, utilize the Web decision support system (DSS) submodule of the late blight of potato and mobile phone to browse supervisory system submodule to browse late blight warning information in time; This warning information is for sharing data, and shared data are the potential occurrence degree of pathogen, field plant growing way situation, a situation arises and pathogen spore distribution situation for disease; According to the breediness of prediction information and potato, late blight pathogen flora characteristic and fungicide feature information data, carry out arranging and adding up, in input database; Judge and spray germifuge in time and carry out disease control; Namely a kind of decision-making late blight of potato prevention and controls is completed.
4. a kind of decision-making late blight of potato prevention and controls according to claim 3, is characterized in that: in step 3, background server uses Hibernate, Quartz task scheduling, JB flow process, Brit report tool, Spring framework mode and development platform to carry out early warning information issue in time.
5. a kind of decision-making late blight of potato prevention and controls according to claim 3, it is characterized in that: the breediness of the potato selected in step 7 is breeding time and disease resistance, late blight pathogen flora characteristic is late disease bacteria biological strain, the mating type of late disease bacteria and be germifuge lasting period, bactericidal agent for preventing and treating effect and germifuge type information to drug resistance and fungicide feature information data.
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| CN104751368A (en) * | 2015-03-04 | 2015-07-01 | 昆明日晟农业科技有限公司 | Intelligent plant protection system and realization method thereof |
| CN106779191A (en) * | 2016-12-02 | 2017-05-31 | 黑龙江省农业科学院植物脱毒苗木研究所 | In anti-kind forecast of potato late blight forecast prevention and controls |
| CN108038588A (en) * | 2017-11-15 | 2018-05-15 | 成都东谷利农农业科技有限公司 | Pesticide field efficacy medicine test management method and device |
| CN109429833A (en) * | 2018-11-01 | 2019-03-08 | 安徽易商数码科技有限公司 | Plant disease and insect pest management system |
| CN110784493A (en) * | 2019-07-04 | 2020-02-11 | 苏州大学 | Comprehensive meteorological data acquisition system based on NB-IoT communication |
| CN111406563A (en) * | 2020-04-03 | 2020-07-14 | 内蒙古自治区农牧业科学院 | Green prevention and control method for potato late blight |
| CN112565310A (en) * | 2019-09-09 | 2021-03-26 | 云南天质弘耕科技有限公司 | Intelligent plant protection system based on artificial neural network |
| CN112710780A (en) * | 2020-11-14 | 2021-04-27 | 山西省农业科学院作物科学研究所 | Wheat scab detection device |
| CN112907061A (en) * | 2021-02-08 | 2021-06-04 | 山东省农业科学院科技信息研究所 | Potato whole industry chain management system |
| CN113379091A (en) * | 2020-02-25 | 2021-09-10 | 张斌 | Method, device, equipment and storage medium for predicting big occurrence of potato late blight |
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| CN104751368A (en) * | 2015-03-04 | 2015-07-01 | 昆明日晟农业科技有限公司 | Intelligent plant protection system and realization method thereof |
| CN106779191A (en) * | 2016-12-02 | 2017-05-31 | 黑龙江省农业科学院植物脱毒苗木研究所 | In anti-kind forecast of potato late blight forecast prevention and controls |
| CN108038588A (en) * | 2017-11-15 | 2018-05-15 | 成都东谷利农农业科技有限公司 | Pesticide field efficacy medicine test management method and device |
| CN109429833A (en) * | 2018-11-01 | 2019-03-08 | 安徽易商数码科技有限公司 | Plant disease and insect pest management system |
| CN110784493A (en) * | 2019-07-04 | 2020-02-11 | 苏州大学 | Comprehensive meteorological data acquisition system based on NB-IoT communication |
| CN112565310A (en) * | 2019-09-09 | 2021-03-26 | 云南天质弘耕科技有限公司 | Intelligent plant protection system based on artificial neural network |
| CN113379091A (en) * | 2020-02-25 | 2021-09-10 | 张斌 | Method, device, equipment and storage medium for predicting big occurrence of potato late blight |
| CN113379091B (en) * | 2020-02-25 | 2023-11-17 | 张斌 | Method and device for predicting occurrence of potato late blight, equipment and storage medium |
| CN111406563A (en) * | 2020-04-03 | 2020-07-14 | 内蒙古自治区农牧业科学院 | Green prevention and control method for potato late blight |
| CN112710780A (en) * | 2020-11-14 | 2021-04-27 | 山西省农业科学院作物科学研究所 | Wheat scab detection device |
| CN112907061A (en) * | 2021-02-08 | 2021-06-04 | 山东省农业科学院科技信息研究所 | Potato whole industry chain management system |
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