Wang Yunsheng

Xu Shipu

Wan Changzhao

Cheng Jihong

Guo Qian

Yang Juan

Zhao Jingying

Towards Developing an Edible Fungi Factory HACCP MIS Base on RFID Technology

Keywords: edible fungi factory, HACCP, MIS, RFID

According to the low yield of edible fungus and the poor quality of edible fungi in factory, the production management situation in edible fungi factory was analyzed. Then the solution of edible fungi factory HACCP(Hazard Analysis Critical Control Point) MIS(management information system) based on RFID(Radio Frequency Identification) technology was presented. Edible fungi production process by the hazard analysis to determine the raw materials, burden mix materials and bottling, inoculation, culture, and growth as the critical control points. For each critical control points, respectively, to develop appropriate critical limits, clearly defined monitoring objects, methods, frequency and corrective measures, critical control point of information collection for the use of RFID technology. Through the implementation of HACCP MIS, edible fungi yield and quality have improved.

Introduction

Edible fungi factory mode of production in the 1970s originated in Japan, it is a biotechnology, automation engineering, information technology, eco-technology, processing maintaining freshness technology in one integrated system [START_REF] Jihong | Development and Application of HACCP Intelligent Control Systerm on Edible Fungus Factory Produc Chinese[END_REF] . Industrial production of edible fungi is a traditional agricultural and modern industrial production of a product of the combination with the characteristics of industrial production, production targets at the same time it is with life. Industrial production of edible fungi and the development of advanced scientific and technological progress, as well as the development of special equipment and use, making the form of the production of great changes have taken place to achieve seasonal hand from the original workshop production of the anniversary of the modern industrial-scale supply changes in production methods [START_REF] Heping | Introduction to the Industrial Productive Approaches of Edible Fungi.Edible Fungi of China[END_REF] . Since the 1990s, factory production of edible fungi in China have been developing rapidly and has now become in the world the biggest edible fungus producer country and exporter country [START_REF] Hu Yongguang | Exploitation on Industrialized Production Pattern for Edible Fungi[END_REF] , the edible fungus output value is situated sixth in the crop production [START_REF] Yunsheng | Towards developing a edible fungi factory production management system based on RFID technology[END_REF] . Edible fungi production technology has brought production management to new issues and challenges: how to improve the quantity and quality of edible fungi products, ensure food safety.

The Pillsbury Company encountered this dilemma in the 1960s in its attempts to fulll several food production contracts with the US Army and the National Aeronautics and Space Administration (NASA). NASA in particular had very stringent microbiological acceptance criteria, not wanting to risk the illness of an astronaut during a space mission (what an inopportune time for a ''two-bucket'' illness!). In essence, nothing short of 100% product testing could assure NASA that a particular packet of food was safe to consume. It was obvious to all involved that product testing could not be used to guarantee food safety. A much better system of food safety assurance was required.

Thus, the genesis of the HACCP concept, a joint development by The Pillsbury Company, the US Army, and NASA. Unlike QC systems, HACCP is a preventive system in which food safety can be designed into the product and the process by which it is produced. It is a system of product design and process control. The HACCP system of food safety is very active at controlling identied hazards. Most importantly, it does not rely upon product testing to assure food safety. Over the next three decades, the HACCP system spread into the food processing industry of the US, and into other countries [START_REF] William | HACCP does not work from Farm to Table[END_REF] .

At present, some Chinese edible fungi production factory have passed the HACCP system certification, but the lack of security on the impact of edible fungi of the various critical control points of information for automatic acquisition, quality control in artificial acquisition, the text records stage, the impact of the implementation of the HACCP system. It is therefore based on the RFID technology of production of edible fungi HACCP intelligent monitoring system, to improve production efficiency and produce safe and high quality agricultural products are of the significance.

RFID radio frequency identification technology is in the 1990s began to rise an automatic recognition technology, is a RF signal through spatial coupling (alternating magnetic field or electromagnetic field) implementation of the non-contact information is passed, and do pass it to achieve the objective recognition technology. In industrial automation control, the RFID technology has been widely used [START_REF] Rajagopalan | A Coordinated Production Planning Model with Capacity Expansion and Inventory Management[END_REF] , it can meet modern industrial production in the process of information uniquely identifying the needs of article uniqueness, you can use to monitor the product in the various processes in the status of implementation of the total quality product tracking, mastering the operations of the finished records and parts of the installation of the record, after sales maintenance records for more information, such as refrigerator manufacturing [START_REF] Meihua | RFID technology based on the production line of digital research[END_REF] , automobile production [START_REF] Chunfeng | Research on Production Logistics System in Automobile Enterprise Based on Radio Frequency Identification.Logistics[END_REF] and so on; you can start from the item the production process of instockroom per conjections data to be accurate, timely of acquisition and recording, processing, and timely feedback from instockroom to grasp items online, in products, methylpyrrolidine, outstockroom of State and location, and implementation of the item's track and on the implementation of the plan steps strict control.

HACCP MIS system and the integration of RFID technology can improve the realtime data acquisition CCPs, the HACCP MIS system to improve quality control on the credibility of the entire software system to improve sensitivity, improve data accuracy; also can be dynamically updated or rewritten in the packaging or the label information, that does not need manual intervention, or do not have to be completed in the visual environment of the scanning of product information, can provide the service process to further simplify and the automated tool [START_REF] Dai Qingyun | Produce Pursuing and Management System Based on RFID.Computer & Telecommunication[END_REF]3] ..

Edible fungi factory production process

Edible fungi factory production process can be divided into pre-vaccination, inoculation and mycelial growth and fruiting the three links, respectively, corresponding to the places of production workshops, inoculation rooms and mushroom houses, the basic process shown in Fig 1 . More edible fungi factory production, will every aspect of the final product quality and production of edible fungi have a decisive impact [START_REF] Chunfeng | Research on Production Logistics System in Automobile Enterprise Based on Radio Frequency Identification.Logistics[END_REF] .

Fig1

Edible fungi factory production quality management needs analysis

Industrial production of edible fungi production and management of the main problems is rooted in the manual method of data collection, production workshop, inoculation room, mushroom house and other data mainly paper-based carrier, and its record is mainly manual records. Industrial production of edible fungi are widespread information and records management manual mass automatic access to environmental information and preservation of the issue cannot be matched, with advanced methods of data collection is to enhance the production of edible fungi factory management level of the principal means of RFID technology and its production and management systems in the following areas:

Real-time status of the batch in the products

Need to be able to achieve the quality of the real-time monitoring, the quality of automatically generated reports, the quality of statistics on the cause of the problem occurred and those responsible; to keep abreast of the current link in the production of products for each batch in the number of products, realizes the goods in process quantity report form accurate statistics.

On the production process to achieve monitoring and correction of deviation from the threshold

Monitoring mixes the material and Culture Collection training and so on, need to know specifically what a batch of edible fungi in the growth of the current state of how the growth of environmental conditions, has deviated from the threshold, the need for corrective adjustment.

Real-time understanding production schedule

To keep abreast of current edible fungi production in every link of production, as well as each production link's to be whether balanced, personnel's of assignment is whether reasonable, whether needs to carry on the production scheduling and the follow up mission arrangement.

Reduces the workshop and the mushroom room management workload

Realizes the management carefully, records each Production workshop and the mushroom room edible fungi production situation promptly, in order to carries on the contrastive analysis with the control system record's capacity for large real-time environmental data, realizes the prompt statistics to each kind of report form, reduces the workshop and the mushroom room management workload.

CCPS and their corresponding threshold

Industrial production of edible fungi in the use of a large number of automation equipment, such as the automatic bottling machine, the vaccination machine, mushroom house control equipment, automatic air conditioning and humidifier, any equipment failures may affect the product quality and safety [START_REF] Savage | Hazard Analysis Critical Control Point:A Review. Food reviews international[END_REF] . Shanghai Finc Biotech lnc. is mainly engaged in Hypsizgus marmoreus cultivation factory production, has been through ISO9001: 2000 certification, constructed the GMP Production workshop, has established the HACCP system, and Table 1 for the critical control points and the threshold. RFID based on the HACCP MIS factory production of edible fungi have been the whole process of monitoring, including information on raw materials, the operator, operation date, process technological parameter, deviation information, product character, products batch excellent rate, fraction defective and delivery inspection situation. Key to affect the product quality security the key aspect to set up corrected an error automatically the reset function, and the product entire production process prompt unmistakable record, to produce the superintendent to provide promptly the ideal management tool, also has provided the important basis for the product post-sale quality follow-up and the data analysis [START_REF] Jihong | Development and Application of HACCP Intelligent Control Systerm on Edible Fungus Factory Produc Chinese[END_REF] .

Edible fungi factory production quality management needs analysis

This According to the edible fungi factory production's characteristic, proposed based on RFID technical HACCP MIS solution. The system mainly carries on the quality control and the production schedule control, but also involves the productive plan management, the workshop management, the mushroom house management, the man management and so on, needs to carry on the massive essential data handle work. As shown in Fig 2.

RFID Application

The RFID applications are mainly located at the bottom of HACCP MIS; face the workshop level's production process, coupled with the sensor indicators on the threshold of CCPs for the collection and recording. It emphasized that the refinement and implementation of HACCP, controls the workshop production process, the management of products, protection of the quality and safety of edible fungi. The overall goal of RFID-based HACCP MIS is to enable enterprise managers and workers will be able to timely and accurate grasp of the production of edible fungi, edible fungi of the quality and safety of the situation, the main links are as follows:

RFID tags issued

In the beginning of links , for each batch of raw materials paid by an RFID tag, according to different sources of raw materials, different types, different quality standards and other information written to the RFID tags and database; the beginning of the mother fungi preservation of relevant information will be written into the RFID tag and the database; After the bottling, the turnover box as a unit for issuing an RFID tag, will each box edible fungi cultivation information write to the RFID tags and database, write the information, including production dates, types of raw materials, raw material batch, formula type, vaccination information, edible fungi scratching information, growth information.

Production link record

In workshop or a mushroom house access place establishment a long-range RFID reader, once the raw materials, mother fungi or the turnover box w ith RFID tags to get into the area, RFID reade r w ill be able to automatically written to RFID tags and automatically recorded the beginning time and relevant information.

Production process information record

In warehouses, burden and mix materials workshops, bottling workshops, sterilization room, inoculation room and so on, set of long-range RFID reader, when this place has the products in process with R F ID tag e nte rs , R F ID re ade r w ill b e ab le to auto mati c re c o rdi ng t he ti me o f completes the work in the database and the related information. Manually issuing RFID tags before the raw materials into the warehouses, and other links using a turnover box be fixed RFID tags, without additional manual operation, it can be achieved on the production process of the logistics and the quality monitoring, the monitoring granularity may achieve the box level.

The edible fungi factory the CCPs management and the quality control

HACCP system made a series of effects of edible fungi product safety, health, and quality control of CCPs, including requirements relating to the use of materials, water safety, production environmental conditions, such as heavy metal content of raw materials, process parameters temperature, humidity, CO 2 concentration , the water content of raw materials, pH and so on, real-time monitoring and controlling , product traceability records management, were all of the need for supervision, and the CCPs need to cyclical records, large data, through the complete record of man-made and often lags behind some of the information, the impact of the decision-making and the timeliness of corrective action.

HACCP MIS for the management of the various batches of product CCPs, including batch management, CCPs management, CCPs threshold, history records inquiry and so on functions. Users can set up in accordance with the lot numbers of products critical control points and control point threshold, automatic monitoring of control points, if in the production process, the control point value more than threshold, the system immediately report to the user, at the same time to start correcting control system automation. The system can reduce the workload of the quality of management, reduce the production and the quality control cost.

Quality traceability

Through HACCP MIS application, in production management module establishment batches of product information management, in the software sorting each batches of product according to the production date, to the parameters of each process to monitor, record and statistics, and statistical data timely input into the system, simultaneously it the deviation which and the correcting an error event has in the production process, saves automatically to this product file, forms the complete production process file. This provides with convenient channels and the most convenient tool. And the realization of the production quality traceability, enhanced the product quality confidence level, but also lets the consumer be able to feel relieved.

Monitoring of environmental parameters

The environment parameter refers to edible fungi habitat each kind of parameter, including the temperature, the humidity, CO 2 and the strength of illumination and so on, the output result indicated by the concrete value and the curve diagram form, clear perspicuity. And may act according to the time selection historical situation parameter record, the early alarm management including the environment alarm range setting, the environment exceptionally reports to user, alarm record processing, alarm record inquiry. Moreover, this module also has the establishment to allow the environment parameter variation range, when the environment parameter variation surpasses the range scope or has the unusual circumstance, the system will report to the user. The environment monitoring reduced the manual monitor workload, avoids error which the manual control produces, enhances the early alarm the accuracy.

Production environment monitoring

The use of cameras will be the state of production and the environment in real-time photography, video streaming through the signal transmission to control room server, and in accordance with the actual situation in the production workshop, adjustment photography angle and focal distance. Through video monitoring, production management personnel may in the control room examine that each workshop the production situation, to reduce the scene contact's frequency, to reduce the workload, improve efficiency.

Conclusion

RFID technology has developed rapidly in recent years, the RFID technology's application was already getting more and more widespread, the RFID equipment technology mature and the cost reduced causes to use in the RFID technology Production enterprise's informationization managing massively into the possibility. The edible fungi production process management to the edible fungi yield, the quality and safety is critical [START_REF] Yi | Edible fungus factorization facility cultivation question and countermeasure[END_REF][START_REF] Shaofeng | Discussion on Some Problems in the Industrial Production of Edible Fungi[END_REF] , but whether obtains the edible fungi production process related real-time data is the key. The HACCP MIS based on RFID has been used in the industrial production of edible fungi, which monitor the process of production to ensure production stability, provide protection to increase productivity, the HACCP MIS development and the application has solved the agricultural product production quality security problem to a great extent, to improve the comprehensive competitiveness of agricultural products, increase agricultural productivity and reduce production costs.

MIS is composed of the human and the computer, to manage information collection, transmission, storage, processing, maintenance and use, the information acquisition method usually needs to be artificially auxiliary. This article studies is the establishment in management information system's foundation to the edible fungi production, has carried on the expansion to information acquisition's way, proposed based on RFID HACCP MIS solution, can real-time and automatic collect information, based on RFID technical management system carries on effectively allthe-way tracking and to plans the execution step to carry on the strict control, safeguards the edible fungi product safety and realizes the product quality safety to trace.

System in the application that there are imperfections, along with the deepening of the application, needs to make the adjustment unceasingly according to the edible fungi factory production actual situation.

  Fig1 Put a figure in a "Figure" style, followed by a "Figure Caption."

Fig 2 .

 2 Fig 2. Structure of edible fungi factory HACCP MIS based on RFID

Table 1

 1 Critical Control Point and the threshold CCP No.

		Name	threshold
	CCP 1	Annual inspection of raw	Record
		materials situation
	CCP 2	Bottled water	63%-65%
	CCP 3	PH value of bottling	6-6.8
	CCP 4	The average weight of bottling	625-650g
	CCP 5	Mixing temperature	118-121℃
	CCP 6	Sterilization time	10min
	CCP 7	Culture contamination rate of	1%
		the Housing
	CCP 8	Scratch fungi water	1cm
	CCP 9	PH value of fungi to scratch	5.5-6.0
	CCP 10	The ninth day reminder lei	Record
		(sensory)
	CCP 11	Cover mushrooms tumor	Record
		(incidence)
	CCP 12	Storage temperature	2-5℃
	CCP13	Fresh air filter case	Record
	CCP 14	Colony growth	Record
	CCP 15	Uniformity (scratch bacteria	Record
		first 16 days of total fruiting
		situation)

Acknowledgements

This study was supported by Science and Technology Commission of Shanghai Municipality Program (073919103).


Qingyao Luo

Benhai Xiong

Zhi Geng

Liang Yang

Jiayi Pan

A Study on Pig Slaughter Traceability Solution Based on RFID

Keywords: words: Pig, RFID, Traceability, Automatic Collection

Due to an assembly line production and poor environment conditions in pig slaughterhouses, collection of slaughter tracing information is not a simple thing. Based on the UHF radio frequency identification (RFID) technologies, this study designed a RFID tag for carcass, a RS232-PS2 data conversion line and some data norms such as the RFID carcass tag and partition meat label norm, and developed online reading and writing system for RFID tags, accomplished RFID identification for carcass and automatic identification on the slaughter line.

Through identifying ear tags at the pig heading process, fixing RFID carcass tags at the half-carcass process, printing partition labels at pork exclusive stores, the study were able not only to collect, transmit and deal traceability information for pig slaughter in the key processes of the whole pig slaughter line, but also print a set of commercial cutting meat tags of 1D bar code based RFID carcass tag in the sales store. This study has been applied for demonstration in Tianjin and explored any possibility for application of RFID technology in pork quality traceability system from both technology and application links.

Introduction

Since a case of the Bovine spongiform encephalopathy(BSE) occurred in Britain in 1986, zoonosis(BSE) , highly pathogenic avian Influenza (HPAI) and food quality safety problems such as Sudan red powder, inferior milk powder happened occasionally and so have been paid wide attention [START_REF] Fu | Animal Identification and Product Traceability Technology[END_REF][START_REF] Lu | Animals and their Products Identification Technologies as well as Traceability Management[END_REF] .The first quality traceability system for animal products in China was the animal immune identification system began in 2002 [START_REF]The Measures on the Administration of Animal Quarantine[END_REF] . Following Animal Industry Act in 2005, the ministry of agriculture has promulgated "The measures on the administration of animal identification and farming files" ("the administrative measures") [START_REF]The Management Method of Livestock and Poultry Identification and the Farming Files[END_REF] , which put in effect on July 1, 2006. Implementing the administrative measures begins mainly to construct the animal quarantine traceability system and gradually to establish the traceability system of animal products quality and safety. The animal quarantine traceability system, the demonstration project of the ministry of agriculture, mainly adopted 2-D barcode technologies to identify animal individuals, took IC cards as mobile data carriers for animal quarantine, conducted identification in the cold-chain transportation, subdividing and packaging links and collection, transmission and switching of the traceability data by the GPRS communication, PDA identification devices and the remote central database [START_REF] Xiong | A Solution on Pork Quality Safety Production Traceability from Farm to Dining Table-Taking Tianjin City as an Example[END_REF][START_REF] Xiong | Identification of Swine Individuals and Construction of Traceability System under Free-range Pig-rearing System[END_REF][START_REF] Xiong | A Solution on Pork Quality Traceability from Farm to Dinner Table in Tianjin City, China[END_REF][START_REF] Ma | Overall monitoring of pork industrialization production and development of traceability system[END_REF] . This program mainly solved how to establish electronic farming files in the pig farming link, how to take the supervision and collect data in transportation of live pigs. But systematic official regulations for information collection in the swine slaughter link and the pork sale link was not found due to different administrative departments.

Therefore, technically to explore reliable identification technologies of intermediate-to-end pork products such as the slaughtering link and data collection technologies such as core technologies about internet of things is an important content of constructing comprehensive tracking and traceability system for animal products, especially pork products in China.

Radio frequency Identification (RFID) is a contactless automatic identification technique and can

identify target object automatically via radio frequency signal and obtain relative data. Based on the working frequency, it is divided into: low frequency system (LH,124 ~ 134KHz) with the characteristics of stable technical performance, strong penetrability and diffraction, cheap cost, but short reading distance; High frequency system (6~13.56 MHz) with a weak penetrability and diffraction, a long recognition distance, a better anti-collision ability, identification speed quicker than LH, bigger environmental impact; Ultrahigh frequency ( UHF,840~960MHz) RFID system with a good anti-conflict ability, strong penetrability, many times reading and writing, big memory capacity, low cost for passive tags, small volume, high reliability and long life, tolerance of poor environments, and convenient for using in assembly line [9][10] .In practical applications, the earliest reports were respectively LF RFID chip implanted in piglets until the sale [START_REF]RFID World website: Strengthen RFID System of Animal Identification and Disease in Ningxia[END_REF] , or identifying pork carcass [START_REF] Lu | Design of Digital Traceability System for the Safety of Factory Pork Production[END_REF] , UHF RFID (13.56MH z) applied in the slaughter link in a beef traceability system [START_REF] Zan | Design and Development of Quality Traceability Information Management System and Safety of the Beef Production's Entire Processes[END_REF] . But, as to most of present assembly lines in pig slaughterhouses, environments were often worse than beef processing slaughtering line, such as dark and damp, and workers with a low cultural level were difficult to ensure entirely corrected identification if bar code identification was used and more manual intervention required. As for a LF or HF system, an effectively automatic identification and data collection system was not found up to now because of special characteristic of the slaughter line. Thus, this paper developed an UHF RFID data collection system being able to identify pig carcass and to get identification data automatically and continuously, and a pork quality traceability platform with the collection of identification data in the pig slaughter link, and realized an association with the breeding files record system in the pig breeding link and the data query system in the sale link, in order to build a tracking and tracing platform for the quality and safety of pig, and to explore a high efficient, reliable data collection solution in the pig slaughter link based on internet of things.

Material And Methods

Study Object

This study took pig slaughterhouses in Tianjin as a study model, pig and products as study objects and explored the collection solution of the slaughter traceability information of commercial pigs.

Traceability Ear Tag

According to the administrative measures stipulated by the ministry of agriculture, all pigs are required to wear a traceability ear tag with a unique identification number in the first vaccination, and establish breeding files (electronic or paper files) in the farm. When commercial pigs were purchased by pig slaughterhouses, traceability ear tags, the original area quarantine card and the vehicle disinfection certificate card were all checked. Only qualified pigs were purchased.

Identification code number According to the administrative measures, the unique identification number for pig consists of 15 digits, in which the first digit represents the type of animal, namely 1 for pig, 2 for cattle, 3 for sheep. The following 6 digits represent the administrative division code which division pig breeding farmer is located in and in line with the GB T2260-1999 (Dec 31, 2006) [START_REF]Codes of administrative regions of the People's Republic of China[END_REF] . 8 digits from eighth to 15th represent an individual sequence number of the same type of animal breeding in the same administrative division. For example, a code number as "1 120111 00006008" means that breeding animal type is pig and the breeding administrative division is Xiqing district (120111), the sequence number of the individual pig is 6008. If the last number is not 8 digits, it should be supplemented to 8 digits by zero in order to make the code number up to 15 digits.

Traceability Ear tag Based on the above code rules, the type of ear tag as figure 1 was designed. A kind of special 2D barcode is engraved on top of the ear tag, which is identified by the special code reader. On both sides of the 2D barcode figure, there are code digits being able to be identified by eyes.

On the top of ear tag is a 30mm 2 of circle area, the distance from the circle area at the top to the small round cone at the bottom is 25mm. The area of 2D barcode figure is 12×12mm 2 .

Fig.1 the special 2-D bar code tag used in China

Traceability devices for the ear tag The ear tag is key identification information for breeding information, moving information and monitoring information during pig production, and accurately collecting the pig ear tag information is required in order to make an association between the pig slaughter traceability information and the former pig breeding information.

Traceability Device for ear tag: Although digits on the traceability ear tag can be seen by eyes, 2-D bar code can only be identified by the special reader device with the 2-D decoding procedure. Two intelligent mobile PDA devices are authorized by the animal traceability administrative, the ministry of agriculture by the public bidding, which can identify the traceability ear tag for pig with a camera (fig 2) [START_REF] Xiong | A Solution on Pork Quality Safety Production Traceability from Farm to Dining Table-Taking Tianjin City as an Example[END_REF] . The left PDA is based on Microsoft Windows mobile 6.0 and the right on Linux system.

Information of ear tags can not only directly upload, but also temporarily save in the IC inserted into PDA devices.

In the fig 3, there is a barcode scanner identifying 2-D barcode on the tracing ear tag, fit for the workplace with a computer terminal. Ear tag information identified not only saved in the connecting computer terminal, and also uploaded to a server database by the intranet. Its identifying speed and effect are better than that of the former two mobile intelligent PDA.

RFID Carcass Tag

Pork carcass is intermediate products in the pig meat production chain, is a connecting link between pig individuals (pig breeding) and pork partition products (pork sales). Reasonably to identify carcass is a key part of realizing the whole pork production traceability.

RFID code number the cod number is 20 digits, the first 6 digits is the administrative code, 2 digits from the 7th to the 8th represent the sequence number of pig slaughterhouse in the administrative district, the following 8 digits show the date digit(yyyymmdd), the last 4 digits are the serial number of the same batch of slaughtering pig in the slaughter house. The most number of each batch slaughtering pigs is 9999. For example, as for 320021 01 20100327 0001, "320021" is the administrative code, "20100327" means that the slaughtering date is march 27,2010, "01" and "0001" respectively for sequence number of the slaughterhouse in the administrative district and pig individual in the slaughtering batch.

RFID tag Because there is an assembly line production in the pig slaughterhouse and the processing work is also in worse environments, adopted tags are required to be waterproof and to be able to read and write quickly. RFID tags was finally designed after many times of write and read test and waterproof test. In order to ensure write and read quickly in the line production, size of RFID chip was required to be considered. At the top of the tag was a rectangle hole for fixing tags.

RFID reader and antenna UHF RL9001 RFID reader this RFID reader as shown in fig 4 (left) is able to write and read electric tags according to ISO-18000-6B and EPC CLASS1 G2, which is widely used in data collection system for animal tracking and tracing, monitoring and controlling of logistics, manufacturing automation management. The reader adopts aluminum alloy shell and is able to install in indoor enclosure or outdoor protective box with good ventilated, dustproof and rainproof condition.

Its working frequency is 902MHz -928MHz, the effective read distance is more than 5 meters and the write distance more than 3 meters, reading and writing time each single-byte is respectively 6 ms and 50 ms.

UHF RL9021 RFID flat reader As shown in fig 4 (right) is developed for pork sales counters in pork product traceability system, data communication interface with built-in antennas is RS232, the distance for reading tag is less than 10 cm, the writing distance is less than 5 m. In order to cooperate with printing the pork partition label, RS232-PS2 data conversion line has been developed, by which data information collecting by RFID reader transmits to the partition printer named as "Dingjian" to print 1-D barcode partition label corresponding with RFID carcass tags.

Partition Tag

Partition tags mainly include tag information at the top of the tag, products description information at the middle including product name, batch, date, company, carcass barcode and visible digits, traceability style prompt at the bottom. In the above tag, carcass code firstly identified by UHF RFID reader and then transmits to barcode printer through RS232-PS2 data conversion line, finally the printer print out 1-D barcode and digits according to carcass code number. "Product name" is usually selected and then print out partition labels through the manual buttons. The worker at the heading process uses the scanner to identify barcode information with ear tags and upload to the slaughter traceability data center while heading and cutting off ear tags.

Software Architecture for Slaughter System

During scalding process, ear tags sometimes lose. In order not to impact normal running of the slaughter assembly line and to ensure integrity of tracing information, the ear tag information system produces an alternative ear tag code for the pig lost its ear tag and upload to the slaughter tracing data center [START_REF] Yang | The design and realization of slaughter technology in the system of pork quality safe traceability[END_REF] . Because any pig slaughterhouse slaughter in turn based on suppliers of commercial pig during purchasing and slaughtering commercial pigs, the accuracy of information for origins or owners of commercial pigs will not be affected.

Fastening Carcass tag

Fixing RFID tag is located at the half-carcass process, where a computer with "RFID tag read and write system" (fig 7), UHF RFID reader and antenna are assigned. The computer connects to the slaughter tracing center by the intranet.

Before slaughter, the antenna is first adjusted to suitable location, then the computer is turned on and "read and write system for RFID tag" is automatically started. The system obtains ear tag numbers in sequence from the slaughter tracing database and generates RFID tag number according to RFID carcass metadata norm. During slaughtering, the worker firstly put RFID tag in front of the RFID antenna and makes the tag code written, then fixes it in the front-end of the half carcass and finally put the carcass on half partition machine to make it into the half carcass. Lashing used is a hard plastic belt with tooth and ring by one head fastening with the other one through the tag hole and round the small hole in the front-end of the carcass.

According to requirements of the slaughterhouse, the relationship of ear tags with carcass tags is not only 1 to 1, but also 1 to 2. Due to ensure reading and writing speed for tags and decrease potential errors, only 20 digits of RFID carcass tag is written into RPC district of RFID tag in the system and the others all into the slaughter tracing database.

RFID tags are made by two ways: one is that RFID carcass tags are written by date and sequence before slaughter, and fastened on the carcass in turn during slaughter. The other is that RFID carcass tags are written and fastened during pig slaughter.

In general, after slaughter, the official veterinary or quality supervisor at the slaughterhouse firstly check in information for ear tags, carcass tags and carcass quarantine and then submit all information the pork traceability center. While submitting, a slaughter event for every carcass is produced according to the slaughter tracing metadata standard and then uploads to the pig traceability database center.

Conclusion

Quality traceability of pork products begins with pig breeding until dining-table of consumers and involves many segments. Influencing factors are complicated; a variety of data is required to be collected and perceived. At present, it is very difficult to collect and carry out whole traceability information. Therefore, only information for ear tags at removing ear tags and RFID carcass tags at halving pig carcass process is collected based on analysis of traceability key points, especially on intermediate slaughter processes. That is, the study not only collected wholly and normatively processed slaughter traceability information, and also made one-one relation between pig breeding process information and terminal sales information according to the systematic design, realized the traceable query of pork quality and safety. This study is a subsystem of the traceability system for quality and safety of swine products, mainly to reduce or avoid phenomenon that easily occur or make mistakes between material chain and information chain in tracing system for animal products' quality by things internet technologies, i.e. UHF RFID, that not only ensures the integration of tracing information and improves the effectiveness of tracing information query [START_REF] Xiong | A Solution on Pork Quality Safety Production Traceability from Farm to Dining Table-Taking Tianjin City as an Example[END_REF][START_REF] Xiong | Identification of Swine Individuals and Construction of Traceability System under Free-range Pig-rearing System[END_REF][START_REF] Xiong | A Solution on Pork Quality Traceability from Farm to Dinner Table in Tianjin City, China[END_REF] . Now, this data collection system for slaughter link has applied to the traceability platform for quality and safety of swine products in Dongying city in Shangdong province, Tianjin city and Hebei province [START_REF] Yang | The design and realization of slaughter technology in the system of pork quality safe traceability[END_REF][START_REF] Xiong | Development for Breeding Performance Management System on Pig Farms[END_REF][START_REF] Xiong | A Solution on Identification and Rearing Files in Smallhold Production[END_REF][START_REF] Luo | A Collection Scheme for Tracing Information of Pig Safety Production[END_REF] .

Collecting solution of key data in slaughter link is all responsible by the official veterinarian. Data may be collected and uploaded by the slaughterhouse technologist who must be authorized by the official vet responsible for the authenticity. Obviously, this mode combines present official veterinarian and meat quality traceability system, which is currently a temporary solution without an independent third-party certification. Expected effects have obtained through some cities' demonstration. However, the responsibility, right and interest need to be solved by institutional construction.

Application of RFID technology in slaughterhouses traceability system, helpful to ensure automation, reliability and validity of collecting pig slaughtering traceability information during the pig slaughter process, solved technical challenges of information collection in a harsh environment of pig slaughtering and reached technical effects better than the low frequency and high frequency RFID technology. This shows that UHF RFID technology has wide application prospects in the slaughtering link for pig slaughtering and other animal slaughtering. But there are still some problems to pay attention [9] .

The first is how to unity articles coding and frequency. If code or frequency applying in food supply chains is disunity, it must result in a lot of inconvenience for arrangement of reading and writing devices, query, tracking and tracing. Because so called ultra high frequency is actually involved with a wider scope of frequency interval, i.e. 860~960MHz [START_REF] Xi | Need perfect Standards for RFID frequency[END_REF][START_REF] Zhang | Application Standards of RFID Technology in logistics Standards of wave frequency[END_REF] , which specific frequency is used need discuss extensively and avoids conflicting with other industries. The second is the cost and recycle of RFID tags. If every single product, including immediate products such as pork, beef , is able to use RFID tags, this will inevitably require that price of tags is reasonable, tags is able to recycle, the identifying cost every carcass reduced to a certain acceptable degree for all pig slaughterhouses.

Passive chips used in this system adopted the imported inlay chip and its price is relative high, so it is just for a small demonstration application. Once substantive demonstration put in effect, price of tags require reduce to an acceptable balance.

Although large-scale application of RFID tags in food safety field has a long way to go, with the rapid development of digit and information technology, the tendency that identification means based on RFID and the global unity of coding system together with HACCP system are applied in food safety and traceability system, is invariable. For example, EU has a regulation early, all beef products in EU markets must have electronic identification since 2005 [START_REF] Fu | Animal Identification and Product Traceability Technology[END_REF][START_REF] Lu | Animals and their Products Identification Technologies as well as Traceability Management[END_REF] . Therefore, to save something for a rainy day, to start with new technology research as early as possible, to provide better service for control and supervision of food safety, to supply more safety and relieved food for consumers is the only way.

Fig. 2

 2 Fig.2 Two types of PDA with reading camera

Fig. 4 UHF

 4 Fig.4 UHF RFID reader

Fig 5 Framework of slaughter system based on RFID 2

 52 Fig 5 Framework of slaughter system based on RFID

Fig 6

 6 Fig 6 Interface for Writing UHF RFID

Fig 7

 7 Fig 7 Interface for Writing UHF RFID

Acknowledgements

Appreciation is extended to Wu Weiping, for his practical suggestions and helps in process of this system development. Funding were provided by the national high technology research and development program of China (863 Program) (2006AA10Z266), Tianjin municipal science & technology Innovation fund (06FZZDNC0100) and the national key technology R&D program (2006BAK02A16).


Zhimei Li

Zhihong Li

Fuxiang Wang

Wei Lin

Jiajiao Wu

TBIS: A Web-Based Expert System for Identification of Tephritid Fruit Flies in China Based on DNA Barcode

Keywords: Expert system, Pests identification, DNA barcode, SQL server, Tephritidae

Tephritid fruit flies (Diptera: Tephritidae) include serious agricultural insect pests in the world. Besides causing severe damage to fruits and vegetables, this kind of pests could enter countries or regions with international trade easily. Strict trade quarantine measures are imposed in many countries or regions in order to prevent their introduction and spread. Thus accurate and rapid identification is regarded as an essential component of plant quarantine. Traditional expert systems for assistant identification of agricultural insect pests are based on their morphological characteristics. Compared with the morphological identification, however, molecular identification has more advantages especially for the identification of the immature samples which are intercepted more frequently. Among the molecular identification methods, DNA barcoding is very effective and has been selected by the taxonomists in recent 5 years. In view of the above, a network expert system based on the DNA barcode, Tephritid Barcode Identification System (TBIS) was developed with ASP.NET and C# to improve the molecular identification of fruit fly pests in China. The system was supported by Microsoft SQL server 2008 database. Three functions were provided such as molecular identification based on DNA barcode, information browse and inquiry. DNA sequence similarity alignment dynamic programming algorithm served as the inference mechanism. Molecular identification knowledge was obtained from the public database on the Internet and Plant Quarantine Laboratory of China Agricultural University, which contained about 400 COI sequences of nearly 150 species of fruit flies. Moreover, detailed information such as morphological description and pictures of adult, hosts, and geographical distribution are presented in this system. Mixed with molecular, morphological and distributional data, the system can be used as an identification tool both for quarantine technicians and for educational purposes in China.

Introduction

Fruit flies (Diptera: Tephritidae) include some of the world's most serious agricultural pests. Of the nearly 4,500 species of 500 genera currently known worldwide, over 150 species are considered as pests [START_REF] Li | General Animal and Plant Quarantine[END_REF] which cause the loss of billions of dollars in production to a wide variety of fruits, vegetable and flower crops such as citrus, apple, mango, and sunflower. They can easily enter many countries through international trade. At present, over 47 species of fruit flies have been introduced to many countries for purpose or unintentionally by human activities, which lead to a broader distribution of fruit flies. As a result, they limit the development of agriculture in many countries or regions because of the strict trade quarantines imposed to prevent their introduction and spread [START_REF] Carroll | Pest Fruit Flies of the World (Version: 15th[END_REF][START_REF] Wu | Identification Atlas for Important Pest Fruit Flies[END_REF]. For example, there are 10 species or genera of fruit flies in the 'list of plant quarantine pests for entry in the People's Accurate and rapid identification is important for any pest species and especially necessary for fruit flies because this group of pests like fruit flies occupies an important place in the plant quarantine worldwide. Identification of flies (Diptera), particularly fruit flies, is primarily based on morphological characters of adults. Larvae or pupae intercepted generally need to be raised to adults for identification [START_REF] Li | General Animal and Plant Quarantine[END_REF]which necessitate an integrated means to identification of fruit flies that is accurate and rapid for virtual emergency of detecting fruit flies for pest control and management. With advancement in molecular biology and genomic technology molecular approaches offer a effective alternate means for tephritid identification in plant quarantines with greater advantages, such as the superiority to distinguish among related species, complex species, subspecies, biological types, and geographical populations that look alike; can identify all stages of life; can identify a species from bits and pieces; can avoid being affected by individual developmental instars and environmental conditions [START_REF] Liang | On the Role of the Morphological and Molecular Identification of Insects (in Chinese)[END_REF][START_REF] Wang | Application Prospect of Molecular Biological Techniques in Identification of Quarantine Insect (in Chinese)[END_REF].

Therefore researchers are trying to use the molecular biological methods to complete the rapid identification for various instars of fruit flies. Among the molecular identification methods, DNA barcoding is very effective and has been selected by the taxonomists in recent 5 years. DNA barcoding employs sequence diversity in short, standardized gene regions to aid species identification and discovery in large assemblages of life. A 648-bp region of the cytochrome c oxidase I (COI) gene forms the primary barcode sequence for members of the animal kingdom [START_REF] Hebert | Biological Identifications through DNA Barcodes[END_REF][START_REF] Savolainen | Towards Writing the Encyclopedia of Life: an Introduction to DNA Barcoding[END_REF]. A much smaller fragment MINI COI and ND6 also can be used for species identification. By the way, the Consortium for the Barcode of Life (CBOL) was launched in May 2004 and now includes more than 120 organizations from 45 nations [START_REF] Ratnasingham | BOLD: The Barcode of Life Data System (www.barcodinglife.org)[END_REF].

Expert System is an important branch of Artificial Intelligence, using knowledge and inference to solve problems that only an expert can solve. Originated from the 1960s, through 40 years' development, with rapid expansion of application area, expert systems have been applied to many aspects in plant protection, involving assisted identification of pests, integrated pest management, prediction and forecasting, monitoring and early warning and so on [START_REF] Li | Preliminary Study on the Development and Application of the Expert System for Plant Protection[END_REF][START_REF] Zheng | Principle and Application of Artificial Intelligence and Expert System[END_REF][START_REF] Zheng | Expert System and Its Application and Development in Plant Protection[END_REF]. Technology and application of the traditional expert system for pests identification based on morphology have been well developed. With the development of the molecular identification especially the DNA barcoding, it is not only possible but also a trend of biological identification to use the molecular identification due to the advantages of the molecular identification. The Barcode of Life Data System (BOLD) based on the DNA barcode emerged in time. BOLD is an informatics workbench aiding the acquisition, storage, analysis and publication of DNA barcode records. There are three functional units now available on BOLD such as the Management and Analysis System, the Identification System and the External Connectivity System [START_REF] Ratnasingham | BOLD: The Barcode of Life Data System (www.barcodinglife.org)[END_REF]. Up to now (June 20, 2010), there are 73,592 formally described species with barcodes in BOLD, including Animals, Fungi, Plants and Protists. The number of fruit fly specimens with barcodes is 2,157, distributed in North America, South America, Oceania, Africa, Europe and Asia, among which only 3 specimens in China. There are 517 species of fruit flies with DNA barcodes in the BOLD, however, only 113 species with 344 public sequences which can be downloaded.

Considering fruit fly identification in China, the BOLD has limitations as follows: the number of fruit flies without public sequences is 404, almost accounts for 80% of the fruit flies with barcodes; there are no ink drawings which is important for the identification; also there is no basic information such as Chinese name, synonym, host, geographical distribution and morphological characteristics [START_REF]Barcode of Life Data System[END_REF]. Up to now, no fruit flies identification systems based on DNA barcode was reported in China.

Considering the reasons mentioned above, Tephritid Barcode Identification System (TBIS) was developed with ASP.NET and C# to improve the identification of fruit fly pests in China. Supported by Microsoft SQL server 2008 database, three functions were provided, such as identification based on DNA barcode, information browse and inquiry. DNA sequence similarity alignment dynamic programming algorithm served as the inference mechanism. Identification knowledge was obtained from the public database on the Internet and Plant Quarantine Laboratory of China Agricultural University, and then represented in the knowledge base of the expert system which contained about 400 COI sequences of nearly 150 species of fruit flies. Moreover, detailed information such as morphological description and pictures of adults, hosts, and geographical distribution were presented in the system.

The Knowledge Acquisition

The translation of the knowledge possessed by the experts into a knowledge base is the bottleneck in the process of knowledge acquisition [START_REF] Edward-Jones | Knowledge-based Systems for Pest Management: an Application-based Review[END_REF][START_REF] Plant | Knowledge-based Systems in Agriculture[END_REF]. For the system based on molecular biology, knowledge acquisition is also an important problem. By consulting the relevant foreign systems, books and scientific publications, we got the barcode information and basic information of the fruit flies involved in this system.

Barcode Information Acquisition

As identification knowledge the barcode sequences had been obtained from BOLD and Plant Quarantine Laboratory of China Agricultural University, standardized to certain length, and then represented in the knowledge base of the expert system which contained about 400 COI sequences of nearly 150 species of fruit flies.

Basic Information Acquisition

Detailed information used to confirm the identification results such as morphological description and pictures of adults, hosts, and geographical distribution were collected from the 'Identification Atlas for Important Pest Fruit Flies' wrote by Dr. Jiajiao Wu and the DELTA database (http://delta-intkey.com/ffa/index.htm).

TBIS Expert System Design and Development

Three basic functions such as identification based on DNA barcode, information browse and inquiry, together with two secondary functions such as notice and basic knowledge for identification are provided. The general structure which designed according to the functional requirement is shown in

Development Software Selection

Since a web-based system can facilitate the data delivery, TBIS was designed to run on the internet to realize the remote access and real-time data sharing. Supported by Microsoft SQL server 2008 database, the system was developed with ASP.NET, C# and HTML. Besides, Dreamweaver 8, Fireworks 8 and Flash 8 were used to design the interface.

Inference Process

DNA sequence similarity alignment dynamic programming algorithm served as the inference mechanism [START_REF] Li | Introduction to Bioinformatics[END_REF]. Fig. 2 shows the inference process. Start from the barcode identification, first, the users should choose the type of the barcodes. At present, there are three types such as COI, mini COI and ND6, and the most common barcode type used in the identification of fruit flies is COI. Second, input the barcode, simply by copy and paste. Third, submit the barcode, the system will show users the identification result after the similarity alignment between the barcode users input and the barcodes stored in the database by using the DNA sequence similarity alignment dynamic programming algorithm. The identification result is represented in the form of similarity values ordered from high to low. In almost all cases, users can find only one species' similarity beyond 98.00%, and when the similarity value between two DNA sequences is more than or the same as 98.00% we can infer that the two DNA sequences belong to the same species, so it is the final result. However, it is possible that users find two or more species' similarity values beyond 98.00%. For example, when it comes to complex species, you have to do the further identification by the DNAMAN, a kind of software used to create tree map. The barcode sequences of the complex species have been collected into one file folder, users can create a tree map based on the barcode sequences of all the complex species or just choose the similarity values beyond 98.00% ones to save time. Moreover, when there is no species' similarity value beyond 98.00%, maybe it is because the system does not store the species users want to indentify or users' barcode sequence is not a standard one. Here we want to notice users that one species often has more than one barcode sequences from different geographical populations, and these sequences may have different similarity values. At last, users can browse the basic information such as the morphological description and pictures of adults, hosts, and geographical distribution.

Users Interface

With abundant combinations of textual information and images, the interface of this system was designed to be easy to operate and user-friendly. There are three main options: information browse, information inquiry and identification based on DNA barcode. On the 'information browse' page, the system displays a list of fruit flies and the user can inspect detailed information related to a specific species after choosing its 'browse' link. If the user clicks the 'information inquiry' option, the system provides an array of inquiry items for users to input keywords. Boolean logical operators ('or', 'and') and inquiry formats ('not exact match', 'exact match') are provided for users to get more suitable results.

As it is shown in Fig. 3, the 'identification based on DNA barcode' page firstly offers three barcode types such as COI, MINI COI and ND6 for selecting. If one of the types is selected, the system will access to the database which stores that type of barcodes. Here we chose 'COI' and inputted the COI sequence of the Bactrocera (Bactrocera) correcta (Bezzi) collected from Yunnan, China. Fig. 4 shows the identification result. Users can further check the detailed information of the identified species by clicking on the Chinese names.

  Republic of China ' promulgated in 2007, such as Anastrepha Schiner, Bactrocera Macquart, Carpomya incompleta (Becker), Carpomya vesuviana Costa, Ceratitis Macleay, Dacus spp. (non-Chinese distributed species), Monacrostichus citricola Bezzi, Myiopardalis pardalina (Bigot), Rhagoletis spp. (non-Chinese distributed species) and Toxotrypana curvicauda Gerstaecker.

Fig. 1 Fig. 1 .

 11 Fig.1.

Fig. 2 .

 2 Fig. 2. TBIS inference process

Fig. 3 .Fig. 4 .

 34 Fig. 3. The identification based on DNA barcode page of TBIS

Acknowledgements

We would like to thank Prof. Ding Yang, Prof. Zhen Su and Master Jiaqi Liu for the advices of the inference mechanism. We also appreciate to Mr. Wenxin Li for his help on code design. Thank Liang Liang and Yingcai Chen for providing the barcode sequences and advices for the requirement analysis.

Thanks for all other members of the Plant Quarantine Laboratory of China Agricultural University (CAUPQL). This study was supported by project of Ministry of Agriculture, China (No. 2009-Z41).

Conclusions and Future Development

The system was originally conceived to improve the identification of fruit fly pests, the identification of which is very difficult for there are so many species and many of which are extremely similar.

Mixed with molecular, morphological and distributional data, the system can be used as an identification tool both for quarantine technicians and for educational purposes in China.

TBIS is different from traditional expert systems based on morphological identification. DNA sequence similarity alignment dynamic programming algorithm served as the inference mechanism.

The system contained about 400 COI sequences of nearly 150 species of fruit flies with detailed information such as morphological description and pictures of adults, hosts, and geographical distribution to confirm the identification results in some ways. Moreover, TBIS is a web-based system so it is accessible to Chinese with a computer and internet connection.

Due to the advantages of the molecular identification, it is the trend to use molecular identification with the assistant of the morphological knowledge. However, we should consider the further improvements to make the system more useful. The accuracy of the molecular identification depends on the number of the species and sequences stored in the database as well as how typical and standard the sequences are. Therefore, more species and sequences should be added. What's more, to use different types of DNA sequences at the same time also helps to confirm the identification result, so considering the system' extension, since we have already designed three types of barcodes that can be used for the identification of fruit flies, we need to collect more sequences belong to that three types of barcodes.


Hongyi Li

Three-dimensional Visualization of Soil Electrical Conductivity Variation by VRML

Keywords: Electrical Conductivity, Three-dimensional Variation, Threedimensional Visualization, VRML

High quality three-dimensional (3-D) earth data is very important for environmental assessment studies, precision agriculture and water quality simulation modeling. In the present study, the soil apparent electrical conductivity (ECa) inversed by the EM38 linear model from aboveground EM38 measurements were selected as the data source of 3-D spatial variability. Firstly, the sphere model which built by VRML approach was used to present the 3-D distributed ECa sites. Then, the plume model was built with the help of EVS, which presents soil volume of ECa greater than a certain value. The VRML models presented a superior visualization of spatial distribution of ECa in 3-D space that 2-D interpolation can't achieve. It was shown that the field in the east corner and low salinity level in the west and northern corner of the field has a high salinity level. The salinity increased with the increase of the soil depth at the vertical direction. At last, the vrml models were placed on a WWW server, which can be opened and accessed by anyone. Using WWW to transfer information to the public is considered as a very important and practical method.

Introduction

Soil salinization limits the growing of crops, constrains agricultural productivity [START_REF] Amezketa | An Integrated Methodology for Assessing Soil Salinization, a Pre-condition for Land Desertification[END_REF]. In the coastal land with which we are concerned, [START_REF] Yu | Observation on Salt Spots in Coastal Land and Study on Tolerance of Barley and Cotton to Salt[END_REF] found that the salt profile of the upper 100cm is a good diagnostic of the suitability of the soil for arable crops. So, anyone assessing soil for farming needs to consider simultaneously the lateral and vertical variation in salt concentration. He or she needs to be able to describe and map three-dimensional distributions.

The three-dimensionality of soil is widely acknowledged. Thousands of papers and reports record variation of soil property, but almost all of the study only surveyed the variation at the soil surface. Many research studies use a 2-D design of soil maps to address a 3-D problem [START_REF] Oliver | The Elucidation of Soil Pattern in the Wyre Forest of the West Midlands, England. II. Spatial Distribution[END_REF]. [START_REF] Meirvenne | Three-dimensional Variability of Soil Nitratenitrogen In an Agricultural Field[END_REF] analyzed the three dimensional variability of soil nitrate in an agricultural field by the three dimensional ordinary kriging method. But these types of study are quite few in soil science.

There is need for high quality three-dimensional earth data for environmental assessment studies, precision agriculture and water quality simulation modeling [START_REF] Grunwald | 3D geographic reconstruction and visualization techniques applied to land resource management[END_REF]. We can think of several reasons why pedometricians have been reluctant to study soil properties in three dimensions at the field scale. One of the difficulties is visualization. How do you display the results of three-dimensional interpolation? Soil variation at different depth in profile or at one direction was presented by slice model only [START_REF] Nash | Horizontal and vertical kriging of soil properties along a transect in southern New Mexico[END_REF][START_REF] Liu | Three-dimensional spatial variability of hydraulic conductivity in the Choushui River alluvial fan, Taiwan[END_REF]. Soil was shown as a noncontinuum in these types of visualization results. [START_REF] Meirvenne | Three-dimensional Variability of Soil Nitratenitrogen In an Agricultural Field[END_REF] made some improvement. A 'grid' model was built to presenting the 3-D variability of soil nitrate. However, it won't be enough in the 3-D visualization.

Virtual Reality Modeling Language (VRML) is a computer language developed for 3-D graphics applications, which is suitable for stand-alone or browser-based interactive viewing. It had been widely used in other subject disciplines, such as Geology, Architecture, and so on. Grundwald and Barak (2003) presented a 3-D soil landscape using VRML. Application of virtual reality to soil variation will make possible the precise recognition of the distribution of soil salinity.

So, the objective of this study was to investigate the use of VRML, to create 3-D soil landscape models for presenting the soil salinity variation in a costal saline land.

Materials and methods

Study area

The land in the coastal zone of Zheijang province south of China's Hangzhou Gulf of the Yangtse delta is formed of recent marine and fluvial deposits. The soil is dominantly light loam or sandy loam with a sand content of about 60%. It is also saline, with large concentrations of Na and Mg salts (in many places >1%). Over the past 30 years much of this zone has been enclosed and reclaimed for agriculture under a series of projects. For this study we chose a field of 2 ha in the north of Shangyu City that was reclaimed in 1996 and used for paddy rice. Its coordinates are 30°90´N, 120 º 48´W (Fig. 1).

Sampling

56 soil profiles were collected after the rice was harvested in December 2006. Each site was geo-referenced using a Trimble Global Positioning System (Fig. 1). Ninety-six EM38 readings were taken at each site: the receiver end of the EM38 was aligned in the four directions of the compass (N, NE, S, and SE) in both the horizontal (EM H ) and vertical (EM V ) coil-mode configurations and at heights of 0, 10, 20, 30, 40, 50, 60, 75, 90, 100, 120 and 150 cm above the soil surface.

VRML method

VRML is a programming language and library for 3-D computer graphics and has many functions. VRML 2.0 was published in August 1996 by the International Standards Organization's (ISO) JTC1/SC24 committee and was accepted as the current ISO standard under the name 'VRML 97' [START_REF] Carey | The annotated VRML97 reference manual[END_REF].Virtual reality modeling language is a 3-D analog to Hypertext Markup Language (HTML), an open-standard 3-D graphics language, which uses the object-oriented paradigm. VRML code is hierarchical, portable and modular. It can be integrated into any World Wide Web (WWW) browser using VRML plug-ins. Within the VRML-capable browser, the user can move around these VRML 'worlds' in three dimensions, scale and rotate objects and the view updates in real-time. The capabilities of VRML include 3-D interactive animation; 3-D worlds (scenes) comprising of several different 3-D objects; scaling of objects; material properties and texture mapping for 3-D objects; setting of different viewpoints and use of light sources and much more [START_REF] Lemay | 3D graphics and VRML 2[END_REF].

The key elements of the VRML language are nodes that describe shapes, colors, lights, viewpoints, how to position and orient shapes, animation timers, interpolators, etc. and their properties in a world.

In VRML, 3-D objects are models extending in three dimensions. A VRML object has a form or geometry that defines its 3-D structure [START_REF] Ames | VRML 2.0 Sourcebook[END_REF]. Coordinates of objects are defined using a 3-D coordinate system with x, y and z-axis. The Shape node specifies the 3-D geometry of an object.

The VRML uses the RGB (red (R), green (G) and blue (B)) classification system to specify the amount of red, green and blue light to mix together to produce a color. The color field of the IndexedFaceSet node and Material node specifies RGB values as three floating-point values, each one between 0.0 and 1.0. The process of ECa variation 3-D visualization was shown in Fig. 2.

VRML and visualization procedure

(1)The linear model with the inverse procedure was adopted to predict the depth electrical conductivity of the 56 sites at the depth of 5, 15, 25, 35, 45, 55, 67.5, 82.5, 95 and 110 cm. That's not we are interested in, the author had finished in his past research [START_REF] Li | Inversion of Soil Conductivity Profiles Based On EM38 Apparent Electrical Conductivity[END_REF]. The ECa profiles were selected as the datum resource of 3-D variation and 3-D visualization.

(2)A 3-D anisotropic variogram was constructed which consisted of an isotropic nugget effect and three spherical models by the help of Gslib 2.0. Also, the author had finished in his past research [START_REF] Li | Research on three-dimension spatial variability of soil electrical conductivity of coastal saline land using 3D ordinary kriging method[END_REF].

(3)We used Environmental Visualization Software (EVS Standard Version; Huntington Beach, CA) to export the geometry of 3-D objects. Surfaces were created using 3-D ordinary kriging [START_REF] Li | Research on three-dimension spatial variability of soil electrical conductivity of coastal saline land using 3D ordinary kriging method[END_REF]. The 3-D model was converted to VRML format.

(4)The VRML program was reedited in the software VrmlPad 2.1. The parameters of background, viewpoint, rotation, and transform can be changed if necessary.

(5) Our VRML soil salinity models were loaded into the Internet Explorer 7 (and higher) with Cortona VRML Client 5.1.

Results

Visualization of virtual environment

To show the x, y, and z dimension of VRML soil salinity models, we should build a 3-D coordinate system model. A polyhedron model was used to express the border of the study area, and the IndexedLineSet node was used to build the prototype. The virtual environment of the coordinate system was shown in Fig. 3. Since the VRML code is hierarchical, portable and modular, the model can be used in the fellow ECa visualization.

Visualization of ECa Profiles

The linear model inversed ECa at the depth of 5, 15, 25, 35, 45, 55, 67.5, 82.5, 95 and 110 cm is the datum resources of 3-D variation. The sphere prototype was designed to express these 460 inversed sites. One site was defined by one Transform node. The Shape node was component by several fields, such as appearance Apperance, geometry, and Sphere_s. The ECa value was rendered by the color, and the diffuseColor field which decided by three values was used for the visualization of soil ECa models. In addition, the settled value of diffuseColor field is same as the legend value which versus the same ECa. Part of the code as fellow: The ECa profiles were shown in Fig. 4. The disturibution of ECa can be seen more clearly in 3-D space. The higher ECa, the higher the salinity is. The deeper the depth is, the larger the soil average ECa is. The map of ECa displayed a spatial distribution with a high salinity level in the east corner and low salinity level in the west and northern corner of the field. Obviously, the salinity in the bottom of southeast is relative high in this study area.

Visualization of ECa 3-D variation

The plume model was adopted to express the 3-D ECa variation. The Indexedfaceset node was used to establish the surface of the plume. The same as the ECa profiles model, the ECa value was rendered by the color, and the diffuseColor field was used for the visualization of soil ECa models.

Fig. 5(a), (b), and (c) showed the volume of soil where the ECa was greater than 0 mSm -1 , 170 mSm -1 , and 300 mSm -1 , respectively. The Anchor node acts as the trigger, helping us analyze the ECa change dynamically. For example, if we click the Fig. 5(a), the screen was cut from it to the Fig. 5 As expected, the prediction volume of soil shrinks as the specified ECa thresholds increased. This is a very important method which can be used to evaluate soil salinity in 3-D space. Obviously, the salinity in the bottom of southeast is relative high in this study area.

Communication on the WWW

The VRML programs made in this study were placed on a WWW server. The soil salinity model in this study can be opened and be accessed by anyone. Using WWW to transfer information to the public is considered as a very important and practical method, and the VRML soil landscape models are accessible via the WWW at http://agri.zju.edu.cn/vrml.html.

Conclusions

In this study, it was summarized a procedure that from 3-D distributed sites to 3-D visualization salinity model.

The object-oriented 3-D graphics language VRML was used to create 3-D soil salinity models. The sphere and plume model was built for presenting the ECa sites and ECa variation, respectively. The VRML models presented a superior visualization of spatial distribution of ECa in 3-D space. It was shown that the field in the east corner and low salinity level in the west and northern corner of the field has a high salinity level. The salinity increased with the increase of the soil depth at the vertical direction.

VRML was so attractive for soil salinity modeling because: (1) it creates realistic 3-D virtual reality, [START_REF] Carey | The annotated VRML97 reference manual[END_REF] what is more important to us, the VRML models can be placed on the WWW. It is very convenient for the public to access the soil salinity information, and (3) soil salinity models have merit for soil information systems updating, helping for soil site-specific management.

We were able to create coherent 3-D ECa models using VRML. This study investigated relatively static ECa property; however, the potential to visualize 3-D transport processes within and on soils using animated VRML movie techniques is enormous.

Fig. 1 .

 1 Fig. 1. The study area and spatial distribution of soil sampling sites

Fig. 2 .

 2 Fig. 2. Process of 3-D Soil salinity simulation using VRML

Fig. 3 .

 3 Fig. 3. Virtual environment of coordinate system

Fig. 4 .

 4 Fig. 4. Visualization of ECa profiles

1 Fig. 5 .

 15 Fig. 5. Visualization of ECa variation

Fig. 6 .

 6 Fig. 6. Internet distribution interface of the ECa

Acknowledgements

The author acknowledges the funding of this work by the National Natural Science Foundation of China (No. 40871100, No. 40701007) and the National Science and Technology Support Program of China (No. 2006BAD10A09).


Jianhua Zhang

Ronghua Ji

Kaiqun Hu

Xue Yuan

Hui Li

Lijun Qi

Analysis on the factors causing the Real-time Image blurry and Development of Methods for the Image Restoration

Keywords: Machine vision, Real-time, Blurred image, Radon transform, Image restoration

The blurred images will make image processing difficult and be hard to get high image solution for recognition, which will lower the precision of a variable rate spray system in pesticide application. In this paper, Radon transform in frequency domain is used in this work to test the blur angle and blur length in different tractors speeds and camera heights. Four image restoration methods in terms of the shape, color, texture and computing time were compared. The results showed that the speed of tractor and the height of camera played an important role on the blur extent of real-time image. A mathematical model corresponding blur angle and blur length with the speed of tractor and the height of camera is established, which would provide a theoretical basis for reducing blur and improving the quality of real-time image.

Introduction

The images captured by the variable rate spraying system based on machine vision are often blurry in some extent due to the relative move between camera and objects as well as the vibration of the system in the field [START_REF] Schuon | Comparison of motion deblur algorithms and real world deployment[END_REF][START_REF] Ebrahimi | Motion blur identification in noisy images using mathematical models and statistical measures[END_REF][START_REF] Gonzalez Rc | Digital Image Processing. 2 version. Restoration new Ruanyu Zhi and translating[END_REF][START_REF] Shi-So | Real-time motion blur image restoration algorithm[END_REF][START_REF] Gao Yong | Used as an effective method to restore motion-blurred images[END_REF][START_REF] Xiaohong | Uniform linear motion blur of the PPS estimates[END_REF][START_REF] Jiangsheng | Based on inverse and singular value decomposition of the exercise of fruit fuzzy image restoration[END_REF][START_REF] Cai Huimin | A kind of uniform linear motion blur parameter estimation method[END_REF]. Motion blur will make image processing difficult and be hard to get high image solution for recognition, which will lower the precision for the system to adjust the spray volume in terms of the practices of the crops [START_REF] Lokhande R | Identification of parameters and restoration of motion blurred images[END_REF][START_REF] Chen | The image motion blur restoration technique[END_REF][START_REF] Gao Shuo | Motion-blurred image restoration techniques improved algorithm[END_REF]. As the variable rate spraying system in the actual operation, how to reduce the blur of real-time image captured and restore the blurred image is crucial.

In the imaging process, image always appears blur due to the relative move between camera and objects, Imaging equipment with external interference and inherent defects, The vibration and light scattering of the camera, and noise interference [START_REF] Shi-So | Real-time motion blur image restoration algorithm[END_REF]. The blurring needs to determine the point spread function, it can be expressed as:

⎪ ⎩ ⎪ ⎨ ⎧ - = ≤ + = others y x L y x L y x h 0 ) tan( / , / 1 ) , ( 2 2 θ ( 1
)
Where L is blur length, θ is blur angle, they are two important parameters of motion blur [START_REF] Gao Yong | Used as an effective method to restore motion-blurred images[END_REF]. The main methods of detecting blur angle and blur length are divided into differential method and frequency spectrum. Differentiation is the calculation of the direction of the process of differential reference only to two adjacent pixels of the gray value, not well reflect the changes in the gray image areas, and the result error is relatively large. Spectrum method is based on computation of the power spectrum of the image in the frequency domain, and the error is relatively low [START_REF] Xiaohong | Uniform linear motion blur of the PPS estimates[END_REF].

The image restoration methods have been matured, which are then based on deconvolution methods such as iterative Lucy-Richardson and Blind deconvolution or non-iterative Wiener algorithms and Regularized filter [START_REF] Jiangsheng | Based on inverse and singular value decomposition of the exercise of fruit fuzzy image restoration[END_REF]. However, these realtime image restoration method to evaluate the need for restoration effect. Common image evaluation methods are: Mean Absolute Error(MAE), Mean Square Error (MSE), Normalized Mean Square Error (NMSE), Signal to Noise Ratio (SNR) and Peak Signal to Noise Ratio(PSNR) [START_REF] Cai Huimin | A kind of uniform linear motion blur parameter estimation method[END_REF]. However, these methods are based on reference image quality assessment, and not meet the interest in evaluation of machine vision.

In this paper, mathematical models established for blurred image analysis through testing blur degree at the different speed of tractor and the height of camera, which provide a theoretical basis for reducing motion blur in images. Comparison of the four kinds of classical methods of image restoration such as Wiener filter, Regularized filter, Lucy Richardson (L-R) and Blind algorithm already in use and some which have been recently proposed in the literature for finding a restoration method suitable for real-time image.

2

Experimental materials and methods

Experimental equipment

Real-time image acquisition system was based on a small four-wheel system DFH tractor as the carrier, and pre-high-resolution color camera for the OK_AC1300 RGB camera, 230 frames / second. Image acquisition card was OK_RGB10B RGB color component capture card. Lenovo notebook computer with Pentium4 / 2.6G processor, 512M memory was used. Speed sensor was DJRVS11 made by Spraying System Company, USA.

Image Acquisition

We had a trial in the experimental base for China Agricultural University in early June 2010, Cotton as the experimental object, which was seedling growth period and its height between 10~20cm. This was orthogonal experimental design, the heights of Camera were 50cm, 80cm, 110cm, 140cm and 170cm, tractor speeds were 2km/h, 4km/h, 6km/h, 8km/h, 10km/h and 12km/h of 6 speed. We used real-time image acquisition system for image acquisition on cotton leaves, each collection was repeated 3 times, and stored the image acquainted through image acquisition card in the computer. Image acquisition card comes with the package can choose from 7 different image resolution for storage.

Motion blurring parameters estimation

When the gradient of such a blurred image is transformed into the frequency domain by the Fast Fourier Transform (FFT) a regular structure is contained within the power spectrum in the frequency domain. This regular structure has a relationship to the length and the direction of the blur. The distance between neighboring stripes is related to the length of the motion blur. The relationship between blur length L and the distance between neighboring stripes d can be simply expressed as: L= a/(d+b).

The main ideas of the finding blur parameters process are illustrated in Fig. 1.

FFT transform

Blur length estimate

Blurred image

Radon transform

Blur angle estimate

Fig. 1. The process of finding blurring parameters.

Image restoration methods

(1) Wiener filter The Wiener filter seeks to minimize the following error function:

⎭ ⎬ ⎫ ⎩ ⎨ ⎧ - = ∧ 2 2 ) ( f f E e ( 2
)
Where E denotes the expected value operator, f is the undegraded image and ∧ f its estimate. The solution to the thereof arising optimization task can be written as follows in the frequency domain:

B v u S v u S v u H v u H v u H F t ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎣ ⎡ + = ∧ ) , ( / ) , ( ) , ( ) , ( ) , ( 1 2 2 η (3)
Where H(u,v) is the PSF in the frequency domain, (2) Regularized filter (reg) This algorithm [START_REF] Ben-Ezra | Motion-based motion deblurring[END_REF] is based on finding a direct filter solution using a criterion C, which ensures optimal smoothness of the image restored. Therefore the filter construction task is to find the minimum of

[ ] ∑∑ = = ∇ = M u N v v u f C 1 1 2 2 ) , ( (4) 2 2
* n f h b = - ∧ (5)
In the frequency domain the solution to this problem can be written as follows:

) , ( ) , ( ) , ( ) , ( ) , ( 2 2 * v u B v u P v u H v u H v u F ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎣ ⎡ + = ∧ γ (6)
Where γ is the parameter which has to be adjusted to fulfill the constraint C and P(u,v) is the Laplacian operator in the frequency domain.

(3) Lucy-Richardson deconvolution (L-R) This algorithm was invented independently by Lucy [START_REF] Akira | Median and neural networks hybrid filters[END_REF] and Richardson [START_REF] Ben-Ezra | Motion-based motion deblurring[END_REF]. Its usage is further outline din [START_REF] Gonzalez | Digital Image Processing Using MATLAB[END_REF]. The L-R algorithm is an iterative restoration algorithm that maximizes a Poisson statistics image model likelihood function. As summed up in [START_REF] Liang | Adaptive landweber method to deblur images[END_REF] the RL algorithm consists of one initial and three iterative steps:

Step 1: A first approximation of the restored image ∧ 0 f must be made, typically the constant average of all pixel values in the blurred image b.

Step 2: The current approximation is convolved with the PSF:

∧ = n n f h * ϕ (7)
Step 3: A correction factor is computed based on the ratio of the blurred image and the result of the last step: Step 4: A new approximate is composed out of the current one and the correction factor:

n n n f f φ ⋅ = ∧ + ∧ 1 (9)
(4) Blind deconvolution (Blind) Blind deconvolution algorithm restores the original blurred image with estimating PSF. The solution improved through iteration, the likelihood of that increases in the number of iterations, eventually converge with the greatest likelihood of Solutions Division. The advantage of the algorithm is able to achieve the blurred image of the recovery operations, in the case of no prior knowledge [START_REF] Richardson | Bayesian-based iterative method of image restoration[END_REF].

3

Experimental Results and Analysis

Analysis Blurred Factors of Image

To minimizing the blur extent, need for analysis of blur factors. Tractor speed and the camera above the ground as the factors, we made the analysis of blur angle and blur length with 90 images, which were detected by Radon transform in frequency domain.

We established the relationship between blur angle and tractor speed with camera height shown in Fig. 2, and the relationship between blur length and tractor speed with camera height shown in Fig. 3. As can be seen from Fig 2, engine vibration amplitude became larger and more increase degree of body bump with the increase of tractor speed. Therefore, Angle of deviation from the center line of tractors and the blur angle of image acquisition increased. Average blur angle increased from 3 degrees to 16 degrees as tractor speed increased from 2 to 12. As the camera away from the higher ground, its body was shaking with the more severe. Therefore, with the increase of the height of camera, the image blur angle became more. Moreover, camera height greater impact on blur angle of image with tractor traveling increase, the average blur angle expand 0.6 degrees with camera height increase from 50cm to 170cm at the speed of 2, while the average blur angle expand 5.2 degrees with camera height increase from 50cm to 170cm at the speed of 12km/h. Blur angle increased with tractor speed and height of camera increase, the related mathematical model can be expressed as

H a V a a 2 1 0 + + = θ
Where a0 is constant, a1, a2 is coefficient, V is tractor speed, H is height of camera 1 shows that tractor speed and camera angle has an impact on the blur of image with p value of a1 and a2 less than 0.05. The value of a1 was more than those of a2, which show that tractor speed has more impact on blur angle than height of camera. The regression equation can be expressed as: As can be seen from Fig 3, blur length of image increase with tractor speed increase for the increase of tractor distance in exposure time. Therefore, blur length increased from 5 pixels to 25 pixels while tractor speed changed from 2 to 12. However, the decrease of shooting range of camera is made when height of camera increased, which cause blur length of image decrease and this trend is evident as tractor speed increase. Therefore, average blur length decrease 0.7 pixels while the height of camera changed from 50 to 170 at tractor speed of 2, but average blur length decreased 4.3 pixels at the speed of 12.

Image blur length increase with the increase of tractor speed, but decrease with the increase of camera height, the correlation model can be expressed as: 2 shows that tractor speed and camera angle has an impact on the blur length of image with p value of b 1 and b 2 less than 0.05. The value of b 1 is more than those of b 2 , which show that tractor speed has more impact on blurring length than height of camera. The regression equation can be expressed as:

H b V b b L 2 1 0 + + = Where b 0 is constant, b 1 , b 2 is coefficient, V is tractor speed,

and H is height of camera

L= 1.805778+1.971714V-0.01556H
Where correlation coefficient R2 = 0.96. In order to obtain maximum reduction of blur image, we must adjust two parameters of tractor speed and camera height. According to the regression equation of blur angle and blur length has obtained, we establish two trend lines. The one trend line is between blurring angle and length with the increase of tractor speed shown in As can be seen from Fig 4(a), blurring angle and blur length increased while tractor speed became faster,but there is a significant turning point at tractor speed of 8km/h. The growth of blur angle and blur length as speed of tractor less than eight is less than growth of those as speed of tractor more than 8km/h .

As can be seen from Fig 4(b), blur angle is increased with the increase of height of camera. On the contrary, blur length is decreased when height of camera increased. There is a point of intersection at 115cm heights of camera, which is the lowest point of the sum of blurring angle and blurring length. Therefore, if the height of camera were 115cm, the image acquisition would keep in lower blur extent.

Based on the above analysis, speed of tractor and height of camera have a significant impact on blur angle and blur length, but speed of tractor has a more significant impact on those than height of camera. In order to obtain maximum reduction of blurred image, tractor speed should not exceed 8km / h and camera height should be around 115cm.

Blurred Image Restoration

The images captured by the variable rate spraying system based on machine vision are often blurry in some extent. Background segmentation is used to separate the cotton leaf from field soil in the recovery image, which is able to analyze shape and color of cotton leaf after recovery. The image space is transformed from RGB to HSI space, and based on H variables Otsu threshold algorithm image segmentation is used, which results shown in Fig 6.

The results of comparison of cotton leaf shape shows that cotton leaves connected, some leaf shape deformed and image distortion is serious in the blurred image. The effect of RL algorithm, Reg algorithm and Wiener algorithm were better than Blind algorithms due to the leaves recovered by which had less linked together and leaf contour clearly. among these three methods, RL algorithm is better than Reg algorithm and Wiener algorithm in noise suppression, so RL algorithm is the best method in recovery of cotton leaf shape.

The results of comparison of cotton leaf color shows that cotton leaf edge section contains a large number of earth colors, which made the error would more if this color were picked up as characteristic variable in the blurred image. After recovery, there were less earth colors on cotton leaf edge in Blind Algorithm and L-R algorithm, while there were no earth colors in Reg algorithm and Wiener algorithm. So Reg algorithm and Wiener algorithm is better than Blind algorithm and L-R algorithm in the recovery effect of cotton leaf color. The results of computing time on cotton images that computing time of four algorithms increased in some extent with the increase of Image resolution seen from Fig 8 . Computing time of Blind algorithm and L-R algorithm which are belong to non-linear methods increased multiply from 1.3s and 0.51s to 35.89s and 13.35s respectively, while computing time of Reg algorithm and Wiener algorithm which are belong to linear methods increased slowly from 0.12s and 0.05s to 2.42s and 1.04s respectively. In comparison from the same resolution such as 480 * 320, Wiener algorithm which had a top velocity is 0.19s, Reg algorithm is 0.50, while Blind algorithm and L-R algorithm is 6.6s and 2.3s respectively. Therefore, make a comparison on computing time, Wiener algorithm is at a distinct advantage among the four algorithms. The test had compared the restoration effect of four recovery methods from color, shape and texture, and compared processing speed from computing time. The results of appraising the four algorithms from the above four aspects with 5 points for each are shown in Table 3. As we can see from the table, the two nonlinear algorithms of Blind algorithm and L-R algorithm got lower points were 7 points and 16 points, while the two linear algorithms of Reg algorithm and Wiener algorithm get higher points were 18 points and 19 points. From the overall evaluation results, Wiener algorithm is the most suitable algorithm for real time image recovery.

Conclusion

According to the practical need of Real-time in the variable rate spraying system, we obtained two groups through this experiment.

The one hand, the speed of Tractor and the height of camera have a important role on the blur extents of real-time image Acquired, and a Regression equations of blur angle and blur length with the speed of tractor and the height of camera is established, which obtained a result that blur degree of real-time image at low levels if the speed of tractor below 8km/h and the height of camera about 115cm.

The other hand, we compared Wiener algorithm, Reg algorithm, R-L algorithm and Blind algorithm in terms of the shape, color, texture and computing time. The results of comparison show that R-L algorithm got highest scores in the shape for good shape of cotton leaves and less noise. Because of the edge of leaf color no soil color and leaf texture is Recovered Absolutely in image, Reg algorithm and Wiener algorithm is good at the recovering of color and texture. Wiener algorithm on the processing time had obvious advantages, which is much smaller than the other three kinds of image restoration algorithm. Through the above four aspects of evaluation, the result show that Wiener algorithm most suitable for real-time image restoration.

  of the undegraded image F.

h

  denotes the PSF in reverse order and n b ϕ / a "pixel-by-pixel" division.

Fig. 2 .

 2 Fig.2. The relationship of between tractor speed and blur angle

Fig. 3 .

 3 Fig.3. The relationship of between tractor speed and blur length

Fig 4 (

 4 a), the other line is between blurring angle and length with the increase of camera height shown in Fig 5(b).

Fig. 4 .

 4 Fig.4. The trend of tractor speeds and camera height with blurring length and angle

  Fig 10(a) is the blurred image captured by the camera with a velocity of 8km/h and 110cm up to the ground, which has 8 degree blur angle and 15 pixel blur length measured by Radon transform. Taking Fig 10(a) as an object, a comparison is made among the 4 recovery method on the basis of MATLAB7.0, two of them are nonlinear iteration recovery (Blind algorithm and L-R algorithm) and the other two are linear recovery (Reg algorithm and Wiener algorithm). We want to find a proper recovery method to image processing in real-time from recovery effect and calculation time. Blind Algorithm, L-R algorithm, Reg algorithm and Wiener algorithm four restoration methods Used to recover blurred image Fig 5(a), among which the iteration frequency of Blind Algorithm and L-R algorithm is 15, the recovery results shown in Fig 5. The results show that the recovery effect of Reg algorithm and Wiener algorithm is better than Blind Algorithm and L-R algorithm, a clear image of cotton fields had been recovered by Reg algorithm and Wiener algorithm. On the contrary, inordinately ripple and circular whorl appeared in the images which were recovered by Blind Algorithm and L-R algorithm for iteration. Therefore, their definition is no better than those of Reg algorithm and Wiener algorithm.

Fig. 5 .

 5 Fig.5. Blurred cotton image and recovery image by 4 kinds of algorithms, (a is blurred cotton image, b is image recovered by Blind Algorithm, c is image recovered by L-R algorithm, d is image recovered by Reg algorithm, e is image recovered by Wiener algorithm)

Fig. 6 .Fig. 7 .

 67 Fig.6. blurred cotton image and 4 kinds of algorithm recovery image after background segmentationThe results of comparison of cotton leaf texture shows that the texture information of blurred images which are made by Prewitt operator on background segment image shown in fig 7 is lost basically and there is no way to extract its texture information as Feature variable. Part of leaf texture is recovered by Blind Algorithm in image, but which is changed and appear some ripple and circular whorl. L-R algorithm is better than Blind algorithm in leaf texture, it recovered the leaf vein normally and there is still some recovery of leaf texture unfinished, while Reg algorithm and Wiener algorithm recovered the texture information completely, leaf vein and rough grain of leaf surface is apparent in image. Reg algorithm and Wiener algorithm is the best in texture.

Fig. 8 .

 8 Fig.8. computing time of recovery algorithm

Table 1 .

 1 Parameter value and significance of blur angle

		Coefficient	t Stat	P-value
	a 0	-3.52089	-3.97802	0.000469
	a 1	1.471714	19.61055	1.68E-17
	a 2	0.021111	3.49414	0.001658
	Table

Table 2 .

 2 Parameter value and significance of blur length

		Coefficient	t Stat	P-value
	b 0	1.805778	2.049102	0.040284
	b 1	1.971714	26.38732	8.18E-21
	b 2	-0.01556	-2.58583	0.015432
	The table

Table 3 .

 3 Appraisal results of image recovery methods

		Blind	L-R	Reg	Wiener
	Shape	2	5	4	4
	Color	3	4	5	5
	Texture	1	4	5	5
	Time	1	3	4	5
	Total	7	16	18

Acknowledgements

This study has been funded by National 863 Plan sub-project NO: 2008AA100905.