Fangzhou Wang

Wensheng Sun

The Study of Quality and Safety Traceability System of Vegetable Produce of Hebei Province

Keywords: Vegetable products, Quality and safety, Traceability system, EAN, UCC, Traceability label

To enhance the management of vegetable products quality and safety of Hebei Province, through practical research of vegetable enterprises, based on Web the authors design a quality and safety traceability system of vegetable products to enhance the monitoring of each participant in the production process. Combining the information and technology of the network and the reality of vegetable cultivation, applying the EAN•UCC system, the authors draw up the traceability coding scheme of the vegetable products, design the quality traceability label of the vegetable products and achieve the traceability management of the vegetable products quality. The system can not only provide the detailed information inquiries of vegetable products for the consumers, but also provide a good operating platform for the production management and the monitoring quality and safety of vegetable products in the enterprises.

Introduction

Vegetables are the major source of vitamins, minerals and dietary fiber what the human body needs. With living standards improving, people become increasingly concerned about product quality and safety of vegetables. In recent years, our high pesticide residues in vegetables to make poisoning incidents occur from time to time. How to ensure the safety of vegetables, improve product quality and safety standards of the "food basket" and let urban and rural residents eat the safety in long, which is not only the focus of attention of ordinary people, but also an important condition for improving the competitiveness of vegetable industry.

The connotation of quality and safety of vegetable products

Vegetables security is a relative concept, which has narrow and broad sense. Broad concept also includes the safety of quality, nutrition and genetically modified vegetables. Today the potential threats of genetically modified vegetables have not been well authenticated. Narrow concepts and standards include mainly four categories: (1) Pollution-free vegetables. These vegetables are that production environment, production process and product quality meet the related standards of pollution-free of the nation or agriculture, which are qualified and certified by the quality supervision and inspection institution, which have also the pollution-free food logo of the relevant department. (2) General products. It has not been particularly explained whether these vegetables are pollution-free food, green food and organic food or not, but today many countries have formulated the industry standard. (3) Green food. Following the principles of sustainable development, in accordance with the specific production methods, these vegetables can be permitted to use the green food mark which is identified by the specialized agencies. (4) Organic food.

According to the international organic standards for agricultural production and corresponding processing requirements, these vegetables are the agricultural products that they are certified by the independent organic food certification agency. Therefore, this article defined the vegetables safety in a narrow sense. As long as the toxic substances were in limited context, which include a pesticide residue, heavy metals, nitrates, harmful micro-organisms, parasite eggs, etc, they can be called safe vegetables.

3

The concept and composition of traceability system

The concept of traceability system

According to the European Union definition of traceability system, it can be expressed as: "The continuity security system of information flow of food market in various stages". Popular that the system can track the interrelated information systems of the entire process from production, handling, processing, distribution and sale through each product bar codes and manage files to use modern management techniques.

The composition of traceability system

The application object of traceability system of vegetables product quality and safety is vegetable enterprises of production, supply and integration, which is made of the center management system, the subsystem of production base management, the subsystem of distribution center management, the public inquiries subsystems. The center management system as a server, the server has the subsystem of production base management and the subsystem of distribution center management [START_REF] Davis | Practical aspects of beef carass traceability non-commercial beef processing plant using an electronic identification system[END_REF]. If the public want to inquiry the subsystem, they need only to call the data of the center management system. The relationship structure of each subsystem can be seen from Figure 1. The center management system. The center management system is installed in the government administration, and the government is responsible for the management. The center management system is made of the corporate records, certification status, the base construction and the data center [START_REF] Petersen | Ponsgen Schmidte: Computerised food safety monitoring in animal production[END_REF]. The center management system can finish the file management of enterprises operation and the production base, and it can also standardize and unify the production information, the information standards and the quality control information for vegetables.

The subsystem of production base management. The subsystem of production base management is installed in the vegetable production base, which includes the corporate records, the production management, the test management, the sales management and the data center. It can achieve the data management of production records management, product quality management, product sales management and production data base management. It also includes the distribution of agricultural land code and the seed, pesticide, fertilizer procurement, storage. At the same time, it can collect the quality information, automatically generate vegetable product trace label and print traceability code label.

The subsystem of distribution center management. The subsystem of distribution center management is installed in the vegetable distribution centers, which include business records, test management, sales management and data center. It mainly realizes the distribution and sales management of vegetable products in the vegetable production enterprises. It also realizes the delivery from the wholesale packaged product to the retail them and print retrospective code label.

The subsystem of public inquiries. The subsystem of public inquiries links to the Internet, which is a module subsystem of single function. Information centre traceability code [START_REF] Stanford | Traceability in cattle and small ruminants in Canada[END_REF]. We also adopt GB/T16986-2003 " Application identifier of EAN • UCC system " standard to set the appropriate application identifier, the trade item identifier using AI (01) to identify the vegetable product identification code, the production date identifier using AI (11 ) to identify the production date, with the source entity reference code identifier AI (251) to identify the farmland code.

The identification code of vegetable products

The trade item identifier AI (01) indicates the meaning of the data segment is the global trade item codes (Global Trade Item Number, for short GTIN). We have chosen the EAN • UCC-13 code structure as an example.

The production date code

The production date identifier AI (11) indicates the meaning of data segment is the production date of trade item. For vegetable products, the production date is the picking date, whose coding structure adopts YYYYMMDD format [START_REF] Xinting | The design and application of the quality traceability label in the food safety control[END_REF].

Figure3. The coding structure of EAN/UCC-13

The field code

The data segment meaning of field identifier of source entity reference code AI ( 251) is the source entity reference code of trade item for tracking the original source of trade item. For vegetable products, the farmland number is the field code. The field codes are distributed by the manufacturer, but they should ensure every code is unique. The vegetable products that they are same field with the growing code are identical in the same period of the planting process. Six numbers, letters or numbers and letters mixed consists of the field code [START_REF] Fu | The traceability system of vegetable quality and safety------Based on Web[END_REF].

We use Cabbage code of a vegetables enterprise as an example. If a vegetable production enterprise code is "6909999", the product code of Chinese cabbage can be shown in Figure 4. It was picked in April 15, 2010, whose field code is A1604.

The traceability code is unique as the information carriers of vegetable products. While providing the product information, the origin and production date information, it meets the code standard of EAN • UCC.

The traceability label design of vegetable products quality

The vegetable product packaging is usually relatively simple, usually using plastic baskets, foam boxes, cartons, plastic bags or mesh bags as package after picking. The processing and distribution sectors use usually plastic bags, bandages as package, therefore, the label design should be short as much as possible, so that the bar code symbol distort little [START_REF] Shan | The process quality control of vegetable production from plough to table[END_REF]. From the cost view, the label should be as small as possible, but it should contain enough information. Giving adequate consideration to the circulation, the traceability label of vegetable product should also contain business name, origin and vegetable varieties. Based on enterprises, origin, date and vegetable varieties, the traceability code of vegetable product will automatically generate. The operation of traceability system

The traceability system of quality and safety of vegetable products has been applied. The center management system has been installed in the quality inspection station of pollution-free agricultural products in Shijiazhuang. It can effectively monitor the vegetable production, circulation and quality information in the production base to establish the credit management files. Its main is the identity management, responsible management and credit management, while the function as the server can be successfully achieved for the security of management and organization, stability and orderly in the entire system and database.

Discuss

The traceability system should be established on the basis of production processes, but the mechanization level of production process is not high in the most enterprises of Hebei Province, which are mainly manual production. Therefore, when the traceability system protects the quality and safety of vegetable products, it needs more the control steps and the various factors of affecting the quality and safety of vegetable products. Based on production process to establish the traceability system, we want to learn fully each process and monitor and record the information to complete the traceability chain. The traceability system of complete supply chain should also involve the wholesalers, retailers and ultimately consumers. Today the scope of traceability system becomes larger and larger. The docking and coordination the individual information of different levels will increase the more difficulty for traceability system. Our project is developing the connectivity of the distribution, supply chain etc to form a more perfect traceability system of vegetable products.

The future development direction is digital management adopting the information technology for the vegetable production circulation, but now general agricultural and high-quality, safe agricultural products are coexist to increase the vegetable products costs. If we fully promote this system, beyond the capacity of the market, it will affect the effectiveness of the system's application to make the further application of the system become difficult. Government departments should support and guide actively, regulate the market and vigorous propaganda from point to area to push gradually the implementation of quality and safety of the traceability system.

Figure 1 .

 1 Figure 1. The chart of Quality and Safety Traceability System of Vegetable Produce of Hebei Province

  It provides a platform of vegetable traceability code through the Internet. The public can check the enterprises vegetables production, production base, harvest dates, as well as the information of the vegetable seed, fertilizer and pesticide. It can also search the vegetable information through the traceability code of vegetables names and enterprises names.

Figure 2 .

 2 Figure 2. The block diagram of quality and safety traceability system of vegetableproduce of Hebei Province

  : Application indentifier; 9: Indicator; 6909999: Manufacturers identification code; 01040: Variety code; 3: Check code; (11): Production date application identification code; 20100415: Production date; (251): Field code application indentifier; A1604: Field number.

Figure 4 .

 4 Figure 4. The traceability label of vegetable product quality of Hebei province

Table 1 .

 1 The coding table of vegetable varieties in Hebei Province (part)

	Vegetables	Vegetable varieties	Variety code
	category
		Chinese cabbage	01010
		Cabbage	01040
	Cabbage
		Seaweed stalk	01050
		Stalk vegetables	01060
		Cabbage brassica	02010
	Brassica
		Cauliflower	02020
		Cucumber	05010
		Melon	05020
	Melon
		Loofah	05030
		Bitter melon	05040
		Chili	06010
	Eggplant	Sweet pepper	06020
		Tomato	06030

  The management subsystem of production base is installed in the vegetable product base of the Shijiazhuang Dijie Ecological Agriculture Co., Ltd. It can make the traceability label automatically generate, and it can also make the print functions smoothly realize. The distribution centre management subsystem has been installed in the distribution centre of the Shijiazhuang Dijie Ecological Agriculture Co., Ltd. It can make the whereabouts information collection and delivery of vegetable sales reliable. The subsystem of public inquiry links to the Internet of quality and safety of vegetable product in Shijiazhuang. The consumers can quickly and easily inquire the information of quality and safety on vegetable product through the Internet.

		Name: Cabbage
	LVGANG	Production areas:
		Shangyi County
	Shijiazhuang Dijie Ecological Agriculture
	Development Co., Ltd
	(01) 9 6909999 01040 3 (11) 20100415 (251) A1604


Feng Yang
email: yangf@nercita.org.cn

Xiandi Zhang

Zhongqiang Liu

Zhenzh I Wang
email: wangky@nercita.org.cn

Kaiyi Wang

Research on the Application Integration Model for the Agricultural Enterprise of Integrative Production and Marketing

Keywords: agricultural products, production and marketing integration, management, information, heterogeneous environment

To integrate application systems under heterogeneous environments has gradually become a pressing demand for most agricultural enterprise. The vast diversity of implementation technologies increases the complexity of applications integration. With the aim of facilitating the development of integration solutions, we propose the specification of application integration. To achieve this, we analyzed the current situation of information, the environment of application systems, and the specific requirements of integration. We also studied the integration technologies. And then the ESB-SOA model for the agricultural enterprise of integrative production and marketing was proposed on the basis of a number of advanced technologies, such as ESB, SOA, EAI and Web Service. Based on ESB and SOA technologies, the model is able to utilize and integrate effectively various service resources on the geographically distributed computing environments. And through intelligent agent technologies, it supports cooperation and coordination mechanisms for the service activities. To exemplify and validate the profile, a case study is presented in which the proposed profile is used.

Introduction

With the extensive application o f information technolog ies, the information of agricultural enterprises that integrative production, process, circulat ion and market ing have also entered a new phase. For a long t ime, d ifferent depart ments in different production processes applied different info rmation systems, resulting in the heterogeneous environments that a variety of hardware devices, operating systems, databases, network protocols coexist. Due to lack of standardization and compatibility, it is difficult to share informat ion resources and there are many "informat ion islands", applications integration has become an urgent demand for enterprise development [START_REF] Guoqing | The Choice M odel of EAI Suited for Integration the Information Systems of Supply Chain M anagement[END_REF]. Ho w to use advanced informat ion technologies to share resources in all p roduction processes is a co mmon problem for many enterprises of integrative production and marketing. In addition to study application systems under the heterogeneous environment in integrated production and marketing agricultural enterprises, an integration model is presented based on ESB (Enterprise Service Bus) and SOA (Service-Oriented Architecture).

Enterprise Application Systems Analysis

The integrative production and market ing of agricultural products refers to "on the professional basis, agricultural products production and marketing departments are integrated into a unified whole in the economy and organization, that is, the production, marketing, processing, storage and transportation of agricultural products are united in a jo int operation in large enterprises , so that the whole process completely reach organic integration and coordinated development" [START_REF] Xiaoxiang | Integrative Production and M arketion of Angricultral Products[END_REF]. However, the lack of p lanning, distributed disorder, departments division, there are a variety o f information systems coexist in the integrative p roduction and market ing enterprise. A mong information systems, the development platforms, data storage, network protocols and operating environment are heterogeneous, which resulted in duplicate construction, waste of resources, informat ion block of enterprise systems, and so on. For examp le, as shown in Fig. 1, there are a variety of informat ion systems that are independent of each other coexist in a vegetables enterprise of integrated production and market ing.

Whether within or between internal and external systems, each system is basically independent of each other. In this way, the following problems are inevitable: [START_REF] Guoqing | The Choice M odel of EAI Suited for Integration the Information Systems of Supply Chain M anagement[END_REF] The same type of data spread across multip le systems, not a single application can access to all data; (2) There is no unified data model, business personnel can not get a global data view; (3) Different applications can't share data and services, this will result in duplication of develop ment; (4) System can only provide data in accordance with fixed demand, when the user needs a particular type of new data, the system can not automatically adapt [START_REF] Jinming | Study on the Service-oritented Enterprise Application Integration Architecture and its Application[END_REF].

Referred to above present "information islands" problems for most integrative production and marketing agricultural enterprise are facing, this paper propose a enterprise application integration model based on SOA and ESB. The model is used to complete the task that the system can not complete alone, and to solve the informat ion integration and exchange problems in some cross-system and cross-databases. Thus, more co mprehensive services are provided to the various departments of agricultural enterprises.

Applications Integration Model Design

Service Oriented Architecture is an architectural paradigm for co mponents of a system and interactions or patterns between them. A co mponent offers a service that waits in a state of readiness. Other components may invoke the service in compliance with a service contract [START_REF] Zhou Xiaoyan | The Research on Application of Enterprise Service Bus in SOA Implementation[END_REF]. Suppose all IT resources are refined into service and published, and services can call each other, so that you can call .Net service in the J2EE environ ment, but this also can be done without SOA. As long as the two IT systems recognized each other's way, it also enables that point to point interconnection even if there is no public or uniform service interface. So we have to admit, if we o wn service, but the requestor and the service providers are still in need of such the exp licit call of point to point between them, then this is not a typical SOA framewo rk. The participation of both services still have to establish the link one to one, this does not meet our scalability, flexibility requirements [START_REF] Hongwei | Enterprise Application Integration Solution Based on Service-Oriented Architecture and Enterprise Service Bus[END_REF]. As shown in Fig. 2. Facing continuing expansion, a tool to manage these services is necessary to simp lify the deploying and accessing of services in the system integration process . ESB (Enterprise Services Bus Enterprise Service Bus) is generated in such demand which is popular in the System Integration currently. Whether internal or external users to access various data sources at the time based on point to point manner. Truly reflects the concept of SOA, everything is service, service bus (BUS) in an equal position. And it has good scalability. The concept model of ESB-SOA is shown in Fig. 3.

OA

Fig. 3. Enterprise Service Bus Concept model

ESB is co mposed primarily of by three main parts : the service gateway (Service Gateway), service adapter (Serv ice Adaptor), service registries (Serv ice Reg ister) [START_REF] Liping | Research and implementation of an adapter for Web Services with ESB-SOA architecture[END_REF]. 2. Serv ice adapter is an important part of ESB, which bears the protocol conversion of message and services to imp lement different protocol formats of the interaction between services.

Service

3. ESB also needs some service registry to provide help for service routing. However, SOA may still have a separate business services directory, its most basic form may be the services directory in designing, and it's used to achieve the reuse of services in development activit ies.

Service Adapter

The function of service adapter is to find, bind, and call web services, and so on. So that the client calls web services in back without knowing the details, and accesses to local or remote web service transparently. Fig. 4 describes the implementation of principles of Service Adapter. The Service Adapter consists mainly of three major processing units. 2) BD (Business Delegate): It is used for controlling the business calling. All business requests are comp leted through calling for service wrapper.

Service

3) SW (Service Wrapper): It wraps the discovery, binding, calling web services in a unified package, thus to shield the details of various web services.

Service adapter first receives the SOAP message from the transmission adapter (TA), and then parsing SOAP messages for security processing (such as SOAP digital signatures and encryption, etc.), then the SOAP message are passed to the business agent, business agent get corresponding semantic descriptions of each web service WSDL address by looking up the corresponding semantic function, and resolve the semantic description.

Service Gateway

Service Gateway design is shown in Fig. 6 includes the follo wing co mponents: 1. Serv ice Processor: It operates the message in security and transmits it to the business agent to deal.

2. Business Agent: It is used for controlling the business call, all business requests are completed through it calling for service manager.

3. Service Manager: It wraps the discovery, binding, calling web services in unified package, thus to shield the details of various web services.

Service Processor Service Wrapper

Bus iness Delegate Service Gateway

Service Adapter

Request Respons e

Fig. 6. Service Gateway

The following is a co mprehensive description of the Service Gateway: 1. Service consumer sends a request to Enterprise Service Bus (ESB). 2. In ESB, Service Adapter comp letes protocol conversion. Then, the converted request is send to Service Gateway.

3. The request is parsed in Service Gateway's Service processor and Business Delegate and passed to Service Manage.

4. The request parameters, and important data in the Service Manage have been resolved will be stored in a service-oriented types data.

5. Service Manage gets the binding informat ion and the relative position of service by querying in Service Reg ister. If there is no appropriate information of services, an error message is returned to service consumer.

6. Query results are returned to Service Manage, and then the result as a parameter saved in the Data Window together with the request parameters will be passed to Service Pro xy module.

7. Serv ice Pro xy module is responsible for calling the appropriate service implementation, and to call the results back to the Data Window and reset the parameters.

8. Service Manage returned the response results to the service processor and Business Delegate. 9. Service Processor will return response back to Service Adaptor, and then returned to service requester by Service Adaptor.

In summary, the dynamic service d iscovery and routing are achieved through Service Manage, and seamless integration of applications is achieved using Service Pro xy.

Service Adapter

Service Processor Service Register Service Manage

Bus iness Delegate Service Proxy

Service Gateway

Web Service

Service Registry

Service is resisted and discovered through the service registry UDDI (Universal Description Discovery and Integration). UDDI uses XML to describe the service provider and the provided of web service,, dynamic bind and call service.

In ESB-SOA, the core class of the service registry is "serviceBusportal", using the "plug-in -Service" configuration file defines the name of the service and location to achieve the service's registration.

Service registration: users publish their own services to the ESB-SOA system registry. The released service of should have service information and service provider information.

Service d iscovery: the client user sends queries commands and the command is transferred to the class "serviceBusPortal" in center for reg istration, and then the service will be found according to the location of service defined in "Plug-in-service" configuration file.

Service binding : After found the service, "ServieeBusPortal" load the corresponding service dynamically.

The relationship between them is shown in Fig. 7:

Fig. 7. Service registry

Log Management

Log service management model is based on Message Service, and uses asynchronous approach. When you need to register log, processing component calls for the API of record ing in formation provided by log service, and then log informat ion will be insert into the log queue by the API. Because it is asynchronous approach, so insert the log informat ion to the log queue to get the response message will not be blocked. Message Service monitor log queue listens from time to time, when log informat ion is inserted into the log queue, Message Service listener extract log informat ion fro m the log queue and write to back-log database by Log

Bus iness Delegate

Plugin-Service

Servlet Service

Bus Portal

Service Registry

Service Manage

Binding Service Adapter in accordance with the standard format, and then delete the log queue processed log informat ion. When query log, the APIs of log services access the log database through the Log Adapter, and get the specified level o f log informat ion. Log management imp lementation is shown in Fig. 9.

Fig. 8. Log management

Model Application

Beijing Tian An Agriculture Development Co. Ltd is a production and business-oriented vegetable agricultural enterprises, after years of information establishment, several informat ion systems have been established, such as ERP, Field Record Management System, Vehicle Transportation Control System, Enterprise portal, OA. Ho wever, each o f them is independent relatively. And it is hard to share data because of the difference in development language, database. Meanwhile, the current system is mainly used in the enterprise, but the field planting, terminal marketing and sales are not managed in the way with informat ion. According to the actual needs of Tian An Co m., we built enterprise application integration platform based on the above proposed ESB-SOA enterprise application integration model, and developed a mobile sales management system, sales management system, mobile production management system, production management systems, and integrated systems by applications integration platform. The application integration logic structure of Tian An Co m. is shown in Fig. 9.

Log

Production Application Integration

The production management of Tian An Co m. is main ly related to the record of the field plant. On the one hand, the field record is sent to the enterprise's production management system, and then summit to the public quality tracing platfo rm. Through the ESB-SOA platform, production management sys tem registers records management services to Service Registry, mobile production systems sends a request to the ESB-SOA, the ESB-SOA finds production management services upon request informat ion, and then the service calls for APIs to submit field file informat ion to the service of production management system in the server. On the other hand, public quality tracing platfo rm registers services to the ESB-SOA Service Reg istry, enterprise production management system sends a request to the ESB-SOA to submit a field record to the public quality tracing platform. Field records management flowchart is shown in Fig. 10, system imp lementation is shown in Fig. 11 and Fig. 12.

ESB-SOA

Sales Application Integration

According the sales information need of Tian An Com., a mobile sales system and sales management systems in server are imp lemented. At the same time, sales management system and ERP registered to Serv ice Registry in ESB-SOA platfo rm. Thus, mobile client sends request to the ESB-SOA to call for services to submit the order, and then the sales management system on the server sends request to the ESB-SOA to call for ERP service to submit the order. The flowchart of sales management is shown in Fig. 13, systems implementation is shown in Fig. 14 and Fig. 15.

Concluding Remark

Because of many production process and loose management, the agricultural enterprise of integrative production and marketing has special requirements for informat ion. Based on the analysis of systems application status in the agricultural enterprise of integrative production and marketing integration, an ESB-SOA model of application integration is proposed based on SOA and ESB technologies. And on this basis, an application integration platform was imp lemented in Tian An Co m. according to the ESB-SOA model. Thus, different departments in Tian An Co m. could share data resources through the platform and interoperability among systems become possible. Moreover, information management is extended to plant record management in field and order management in supermarket. More important is that ESB-SOA has good scalability, and it is easy to plug and play for new application.

Fig. 1 .

 1 Fig. 1. Information Systems in an enterprise of integrated production and marketing

Fig. 2 .

 2 Fig. 2. Point-to-Point service integration

Fig. 4 .

 4 Fig. 4. Enterprise Service Bus architecture

Fig. 5 .

 5 Fig. 5. Service adapter schematic 1) SP (Service Processor): It is used for receiving and parsing SOAP messages passed over the TA (transmission adapter), processing security, such as digital signatures and encryption.2) BD (Business Delegate): It is used for controlling the business calling. All business requests are comp leted through calling for service wrapper.3) SW (Service Wrapper): It wraps the discovery, binding, calling web services in a unified package, thus to shield the details of various web services.Service adapter first receives the SOAP message from the transmission adapter (TA), and then parsing SOAP messages for security processing (such as SOAP digital signatures and encryption, etc.), then the SOAP message are passed to the business agent, business agent get corresponding semantic descriptions of each web service WSDL address by looking up the corresponding semantic function, and resolve the semantic description.

Fig. 9 .

 9 Fig. 9. Application Integration Logic Structure of Tian an Com

Fig. 10 .Fig. 11 .

 1011 Fig. 10. Field Records M anagement Flowchart

Fig. 13 .Fig. 14 .

 1314 Fig. 13. The flowchart of sales management

Acknowledgements. This research is funded by the Support of Science and Technology Project of the State, Programmed award No. 2008BA DA0B02.


Yiwei Dong

Yongxing Chen

Dazhou Zhu

Yuzhong Li

Chunying Xu

Wei Bai

Yanan Wang

Qiaozhen Li

The Determination of Total N, Total P, Cu and Zn in Chicken Manure Using Near Infrared Reflectance Spectroscopy

Keywords: near infrared spectroscopy, chicken manure, total N, total P, Cu, Zn

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

In the last decades, intensive livestock operations produced considerable amounts of animal manure that may cause serious environmental problems [START_REF] Gay | Odor, total reduced sulfur and ammonia emissions from animal housing facilities and manure storage units in Minnesota[END_REF]. China is one of the largest producers of animal manure in the world, with an annual output of more than 3 billion tonnes [START_REF] Zhang | Research and Application of Nutrient Resources Integrated Management Technology[END_REF]. Composting is an appealing solution for sustainable management of animal manure especially the chicken manure [START_REF] Remy | Efficiency of near-infrared reflectance spectroscopy to assess and predict the stage of transformation of organic matter in the composting process[END_REF]. Use of composting results in a stabilized, mature, deodorized and hygienic product, free of pathogens and rich in humic substances, which is environmentally friendly and marketable as an organic amendment or fertilizer [START_REF] Haug | The Practical Handbook of Compost Engineering[END_REF][START_REF] Ouatmane | Compost maturity assessment using calorimetry, spectroscopy and chemical analysis[END_REF].

The parameters established by the legislation for marketable composts are electrical conductivity (EC), total organic matter (TOM), total organic carbon (TOC), total nitrogen(TN) and C/N ratio, macronutrient contents (N, P, K) and potentially pollutant element concentrations (Fe, Cu, Mn and Zn) [START_REF] Galvez | Estimation of phosphorus content and dynamics during composting: Use of near infrared spectroscopy[END_REF]. The determination of these important parameters of composts required numerous reagents, skilled labors and expensive analytical equipments. Consequently, a more convenient and reliable method is necessary.

Near-infrared spectroscopy (NIR) (800-2500 nm), which reflects the overtones and combinations of fundamental vibrations of C-H, O-H and N-H bonds, has been widely used for quantitative and qualitative analysis for organic components in petrochemical, agricultural and pharmaceutical field [START_REF] Pasquini | Near infrared spectroscopy: fundamentals, practical aspects and analytical applications[END_REF]. Previous study have also indicated that one of the mechanism for measuring heavy metals by NIR was their inter correlation with organic compounds [START_REF] Malley | Use of near-infrared reflectance spectroscopy in prediction of heavy metals in freshwater sediment by their association with organic matter[END_REF]. In recent years, NIR was also applied as an inexpensive tool for rapid analysis of important component in animal manures [START_REF] Malley | Rapid analysis of hog manure and manure-amended soils using near-infrared spectroscopy[END_REF][START_REF] Ye | The transfer of beef cattle feedlot manure calibrations between near infrared spectrophotometers using three standardization techniques[END_REF][START_REF] Saeys | Potential for onsite and online analysis of pig manure using visible and near infrared reflectance spectroscopy[END_REF][START_REF] Yang | Rapidly estimating nutrient contents of fattening pig manure from floor scrapings by near infrared reflectance spectroscopy[END_REF].

The purpose of this study was to explore the feasibility of analyzing organic and inorganic components of chicken manure using NIR simultaneously.

Materials and methods

Sample Preparation and chemical analysis

In this study, the chicken manure samples were collected from a chicken farm from Heishan county, Liaoning Province. The samples were dried at 65 ºC in a forced-air drier to a constant weight and ground to pass a 1 mm screen for latter analysis. In total, 74 samples were prepared.

NIR Spectra Collection

NIR spectra were recorded by a Fourier transformed near-infrared spectrometer (IFS 28/N, BRUKER, Germany) with integral sphere accessory. The ground chicken manure was filled into a cylindrical quartz cup with 20 mm depth to insure that light did not permeate the sample. The cylindrical cup was rotated slowly to assure fine sample distribution. And the reflectance spectra were recorded within the band between 12500 and 4000 cm -1 (800-2500 nm), at 16 cm -1 interval. For each sample, the spectra were scanned 64 times and the average spectrum was obtained.

Measurement of Total Nitrogen, Total Phosphorus, Cu and Zn

The chemical analyses were performed by the Analysis and Test Center, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Science. The total nitrogen (TN) was determined by dry combustion at 975 °C using a PE-2400 C-N Elemental Analyzer (PerkinElmer Corp., USA). The total Phosphorus (TP) was determined according to the method described in NY525-2002, which is the standard of Ministry of Agriculture. The content of Cu and Zn were measured using an acid digestion method with inductively coupled plasma-atomic emission spectroscopy (ICP-AES, PerkinElmer 3300DV) [13].

Data Analysis

The spectra were not being pre-processed since the quality of original spectra was relatively high. Principle component analysis (PCA) was used to explorer the spectra distribution in the latent space. The calibration model between reference values and spectra were constructed by partial least square regression (PLSR). The outliers for each model were eliminated according to the plot of COOK value vs. leverage value [START_REF] Otto | Chemometrics: Statistics and Computer Application in Analytical Chemistry[END_REF]. For each model, the reference value was sorted in an ascending order. Every third sample was selected as calibration set, while the remaining part the prediction set. The calibration set was used for the model construction, while the prediction set was used for the model validation. The optimal number of PLS factors was selected by leave-one-out (LOO) cross validation. The corresponding PCs were selected when the prediction residual error sum of square (PRESS) was the lowest. The predictive performance of the calibration model was evaluated by the correlation coefficient (r) for the calibration set, the standard deviation of calibration (SEC), the standard error of cross-validation (SECV), the standard deviation of prediction (SEP). A good model are supposed to have small SEC, small SEP and high r. The PCA calculation was carried out with the software Unscrambler 9.1 (Camo Corp., Norway), and the PLSR was conducted by MATLAB 7.0 (The Math Works, Inc., Natick, MA, USA).

Results and discussion

The Characteristics of the components of chicken manure

Table 1 shows the composition statistics in calibration sets and validation sets for total N, total P, Cu and Zn, respectively, which include the number of samples, the mean, standard deviation and range value. It could be seen that the components of prediction set full in the scope of calibration set, which assured the representative of the calibration models.

NIR Spectra and the PCA plots of chicken manure

The full wavelength range of the spectra was 800-2500 nm. The original spectra were shown in Figure 1. The spectra had several absorbance peaks at the wavelength of about 1135 nm, 1340 nm, 1540 nm, 1657 nm, 1870 nm, 2010 nm, 2235 nm, 2416 nm, indicting rich information was contained in the spectra. The possible water absorption peaks was not obvious because the samples were already dried at 65 ºC to a constant weight.

Figure 2 showed the result of PCA analysis. It can be seen that the samples constituted a sample set that

The Calibration Models for chicken manure

The calibration models of total N, total P, Cu and Zn were shown in Table 2. It can be seen that the total P, Cu and Zn model had high calibration accuracy, with the correlation coefficient (r) of 0.8577, 0.9479 and 0.9352, respectively. Figure 3 shows that the NIR predicted value of total P, Cu and Zn and its reference value were closely arranged with the 45 o line, indicating the prediction error was low. The above result suggested that total P, Cu and Zn of chicken manure could be measured by NIRS. The measurement of Cu and Zn were the indirect relation between metal elements and NIR spectra. Previous study have indicated that one of the mechanism for measuring heavy metals by NIR was their inter correlation with organic compounds [START_REF] Malley | Use of near-infrared reflectance spectroscopy in prediction of heavy metals in freshwater sediment by their association with organic matter[END_REF]. For the Zn model of compost of pig manure on fresh and dried basis, the R 2 and r 2 values were about 0.69 and 0.6 [START_REF] Huang | Evaluation of the nutrient metal content in Chinese animal manure compost using near infrared spectroscopy (NIRS)[END_REF]. The current Zn model had higher calibration accuracy than that of previous study [START_REF] Huang | Evaluation of the nutrient metal content in Chinese animal manure compost using near infrared spectroscopy (NIRS)[END_REF].

The calibration model of total N, however, showed relatively lower accuracy. In the calibration set, NIR spectra and total N had some certain relationship, with the correlation coefficient (r) of 0.6923, which was much lower than that of total P, Cu and Zn model.

According the scatter plot, the NIR predicted total N and its reference value were also distributed aside the 45 o line (see Figure 3). However, they were not as close as that of Cu and Zn, indicating that the prediction error was relatively high. The calibration results suggested that although NIR spectra had some extent of relation with total N, the prediction accuracy could not satisfy the requirement of quantitative measurement. Future research may focus on how to improve the accuracy of total N model.

Table 2. The statistic results of calibration models for chicken manure

Conclusions

The current study explored the simultaneous evaluation of organic and inorganic components of chicken manure using NIRS. The results showed that the NIRS technique could be a complementary detecting method to the conventional analysis. However, further research is needed to improve the prediction precision of calibration models by enlarging the number and range of samples. The present study only constructed the linear calibration models for the four components of chicken manure. In order to improve the precision of models, future studies may apply non-linear methods such as artificial neural networks to build the non-linear relation between spectra and components.

Fig 1 . 14 -Fig. 2 .

 1142 Fig 1. The NIR spectra of chicken manure

Fig 3 .

 3 Fig 3. The scatter plots of reference values and NIR predicted values for the components of chicken manure

Table 1 The statistic characteristics of calibration set and prediction set for chicken manure

 1

			Number of	Min	Max	Mean	Standard
			samples	value	value	value	deviation
	N(%)	Calibration Prediction	50 24	3.51 3.55	7.55 6.79	5.36 5.29	0.91 0.85
	P(%)	Calibration Prediction	42 21	1.73 1.85	4.12 3.88	2.86 2.86	0.56 0.55
	Cu(mg/Kg)	Calibration Prediction	47 23	23.41 23.80	64.22 57.24	41.93 41.44	10.85 10.53
	Zn(mg/Kg)	Calibration Prediction	44 22	144.63 145.16	291.98 291.42	222.83 222.44	39.91 40.97

Acknowledgements

This work was supported by Major projects on control and rectification of water body pollution(2008ZX07425-001)


Lei Xi

Shuping Xiong

Yanna Ren

Qiang Wang

Juan Yang

Longlong Zhang

Xinming Ma
email: xinmingma@126.net

Virtual Visualization System for Growth of Tobacco Root

Keywords: Tobacco, root, simulation model, virtual plant, visualization

Visualization study on the growth of virtual plant roots is of great significance to enhance the overall level of research on virtual plant growth. In this study, with the tobacco root as the object, its growth was divided by systematic analysis into three stages: root emergence, root growth, and root branching. Through the quantitative analysis of the morphological data of the tobacco root and in combination with results of previous studies, the tobacco root growth, branching and other models were established, and parameter values of the models were extracted. On this basis, computer graphics technology was applied to establish a virtual visualization system for tobacco root growth that should be capable of simulating root growth and computing indicators of roots including the number, length, density, etc. Results indicated that this system can do a better job of simulating the morphological features for the tobacco root and virtually displaying the process of tobacco root growth in a more realistic way.

Introduction

With its rapid progress, the virtual plant study has become one of the frontier fields of research on agricultural sciences since the 1980s. Virtual studies have been successively carried out at home and abroad on corn, wheat, and rice [START_REF] De Vries F W T, Jamsen | Simulation of ecophysiological processes of growth of several annuals crops[END_REF][START_REF] Xiuhai | Survey on Virtual Growth and Development of Maize[END_REF][START_REF] Liping | Studies on the Simulation Model for Wheat Phenology[END_REF][START_REF] Hui | Construction and implementation of model-based visual growth system[END_REF]. The root is one of important integral organs. Diggle [START_REF] Diggle | ROOTMAP:A model in three-dimensional coordinates of the growth and structure of fibrous root systems[END_REF][START_REF] Diggle | ROOTMAP: A ROOT GROWTH MODEL[END_REF] established the first threedimensional model of root age, location, and root segment orientation. Over 20 years of development, virtual root growth models of different plants were established through the L system, fractal method, reference axis technology, and method of threedimensional reconstruction of plants [START_REF] Adiku | Simulating root growth dynamics[END_REF][START_REF] Pages | A simulation model of the three-dimensional architecture of the maize root system[END_REF][START_REF] Gongming | Analysis and Compare of Virtual Plant Roots Growth Model[END_REF][START_REF] Ge | Simulation models of plant root system architecture and application: A review[END_REF][START_REF] Xuyang | Study on the Geometry Modeling for Corn Root System[END_REF][START_REF] Feng Bin | Simulation of the Root Growth by Using the Image and Fractal Growth Technology[END_REF][START_REF] Wuping | Three-dimensional Model Simulating Development and Growth of Cotton Root System[END_REF][START_REF] Jijoon | A growth model for root systems of virtual plants with soil and moisture control[END_REF]. However, these models have not taken the relationship between the root structure and its function into account. Simulation studies on roots have developed slowly because of the invisibility of the environment of root growth as well as the limitations in measurement techniques; the study on the tobacco root is even rarely reported. Tobacco is a special economic crop featured by the double-peak phenomenon in its root growth, which has a direct impact on the quality of tobacco. In this study, the experiment was designed with the rhizobox method to systematically investigate the morphological development of the tobacco root, and the model of tobacco root growth and development was established by summarizing previous results and analyzing test data of tobacco root morphogenesis. Based on the morphological model, a virtual growth system of the tobacco root was established with OpenGL in the Visual C + + platform. The visual expression of morphological characteristics in the process of tobacco root growth was initially realized, so as to provide a technological basis for virtual crop studies.

The Dynamic Model of Tobacco Root Growth

Root Emergence

The tobacco has a taproot system that consists of primary, lateral and adventitious roots. It is measured that the root begins to emerge when the effective accumulated temperature that is ≥10 o C in the seedbed period comes up to 100 o C, and the total number of roots is in an exponential relationship with the accumulated soil temperature. It is also known that there is a linear relationship between the accumulated soil temperature at 5 cm below the ground and the accumulated gas temperature in seedbed period, thus the number model of roots in seedbed period is shown as follows: T represents the accumulated gas temperature from seed-sowing to some day.

Root Growth Model

Root growth is represented by potential growth rate and actual growth rate that are under the influence of the soil temperature, the sunshine duration, and the carbohydrate supply from above the ground. The potential root growth rate [START_REF] Bar-Yosef | Rhizos: a simulation of root growth and soil processes, sensitivity analysis and validation for cotton[END_REF] could be described by a kinetic equation:

dt dP ri / dt dR wi / wgi ci ri R R dt dP • = (2)
In Equation ( 2), i represents the sequence of soil layers; is the root's potential growth (

) in the i th soil layer; shows the root's dry weight ( ) of the i th layer; indicates the rate constant of root growth in the i th layer which depends on the soil temperature and sunshine duration.

ri P 1 3 - -• • d cm mg 3 - wgi R • cm mg ci R ) )( 24 ( ) ( b n K L b d K L ci R T R D R T R D R - • - + - • = (3)
Where, represents the available sunshine hours( ); is the soil constant; and represent the average temperature during the day and at night respectively, which could be obtained by the following formula:

L D T h ) 1 ( 2 - • d R b d n T ⎩ ⎨ ⎧ + - = + - = min min max min min max ) ( 15 . 0 ) ( 55 . 0 T T T T T T T T n d (4)
In Equation ( 4

Δ • Δ • • = ) ( (6)
In Equation [START_REF] Diggle | ROOTMAP: A ROOT GROWTH MODEL[END_REF], DM is the tobacco's amount of accumulated dry matter

( ); 2 - • cm mg DMR 1 - • d
, the amount of accumulated dry matter within unit time ( ); , actual amount of dry matter growth within ; and , the supply coefficient of the tobacco plant.

t Δ t Δ 2 - • cm mg ) (t f CH DMA Δ 2.

The Stretching Direction Model

Based on the model of root growth direction by Pages et al, environmental factors such as soil during root growth are set aside in this system. Under the hypothesis that the root grows in the homogeneous soil with the relatively superior growth environment and without serious environmental stress, the ultimate growth direction of the root within in current growth cycle depends on factors in three categories: the growth direction of the root in the previous cycle, geotropism, and random factors. Therefore, the stretching direction of new root tip D N could be expressed as:

' 1 N G N N D D D D + + = - (7)
Where, is the growth direction of the root in the previous cycle, represented by the cosine function of the straight direction the root follows; is the downward growth trend of the root, a vector pointing to the center of the earth; random factor is the deviation between the axial angle and the radial angle based on the original direction, represented by

1 - N D G D ' N D
φ and θ whose value ranges from 0 to30 o and from - 180 o to180 o , respectively.

The Root Branching Model

The Branching Locations of the Root

Because of apical dominance, lateral roots arise within a certain range on the mother root [START_REF] Lungley | The growth of root systems: A numerical computer simulation model[END_REF]. As shown in Figure 1a, the length of the non-lateral-root section at the lower part of the primary root was set as LB while that at the top part was LA, so lateral roots would only appear when the root axis was longer than the sum of LB and LA. Shown in Figure 1b, branching points B and C both occurred in root segment AD. The number of points similar to B and C determined the branching density of this root segment. Since B and C were assumed in the system to occur at any part on root segment AD, then if the coordinate of point D was known, then starting points B and C of the branching root axis could be determined with location coefficient ε and the coordinates of A and D. ε , a random quantity in [0,1], is defined as:

BD AB = ε (8)
In this way, the starting point coordinate of the root axis growing from B, any point on root AD, is as follows:

) 1 /( ) ( ) 1 /( ) ( ) 1 /( ) ( ε ε ε ε ε ε + + • = + + • = + + • = A D B A D B A D B z z z y y y x x x (9)

The Root Branching Directions

The branching direction of the root is jointly determined by the axial branching angle β and the radial branching angle α . The direction vector of mother root u r would change into through the axial rotation of angle ' u r β , and the new vector would become vector ' by the radial rotation of angle ' u r α , i.e., the new branching direction. α and β range from 0 to180 o and from 0 to 90 o , respectively.

The Root Number and Length

The primary root grows rapidly after its emergence. When reaching a certain branching age, the primary root generates the primary lateral root, which produces the secondary lateral root at the branching age.

The number of primary lateral roots: [START_REF] Ge | Simulation models of plant root system architecture and application: A review[END_REF] where, number 1 represents primary lateral roots and i is their ordinal number.

∑ = = n i i N N 1 1 1
The number of secondary lateral roots: [START_REF] Xuyang | Study on the Geometry Modeling for Corn Root System[END_REF] in which number 2 represents secondary lateral roots and i is their ordinal number.

∑ = = n i i N N 1 2 2
The total number of roots:

2 1 N N N + = (12)
As regards to the root length, the lengths of all roots within the same level are calculated based on root levels. The formulas are as follows:

The length of primary lateral roots:

∑ = = n i i SL SL 1 1 1 (13)
The length of secondary lateral roots:

∑ = = n i i SL SL 1 2 2 (14)
Total root length:

2 1 SL SL SL + = (15)
The length of root segment is calculated as follows:

⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ - - • - - - = ))) ( sin( ( sin 1 2 1 2 1 2 1 2 1 2
x x y y arctg y y z z arctg z z sl [START_REF] Lungley | The growth of root systems: A numerical computer simulation model[END_REF] Where, , , and , , represent the coordinates of starting and ending points (points A and B of the root segment) respectively.

1 x 1 y 1 z 2 x 2 y 2 z 2.

Determination of Model Parameters

The development of the tobacco root is under the influence of a number of factors, such as soil moisture, ground temperature, carbohydrate supply, dry matter accumulation, and its own characteristics. According to experiments and related literature [START_REF] Feng | Simulation of long term nitrogen behavior in agricultural soil[END_REF] parameters that affect models of tobacco root growth and branching are shown in table 1. Length between branch on first order root length1 0.1 cm 3 Three-dimensional Simulation of Tobacco Roots

Design Methods

Tobacco roots are considered as a group of branch axes, that is, the primary branch (primary lateral root) is connected to the primary root, and the secondary branch (secondary lateral root) is connected to the primary branch, etc. Everyday, there might be new branch axes, and the existing root axes might grow and branch. To determine the spatial location of roots, it is necessary to know enough spatial coordinates of points on roots. Suppose that root axis is composed of a series of linear root segments in different directions, since the root segments are developed from growing apexes' moving to the new locations in a limited period of time, two coordinates are enough to determine its spatial location.

During the simulation, the accumulated temperature cycle of root growth 1d is set as one step. Within each time step, all the survival root segments in each growth cycle are first updated, (three-dimensional correlation connections of root segments, branch levels, spatial coordinates, geometric sizes, branching sequences, etc.), according to the models of root growth and branching, and all the updated information serves as the basis of root parameters (root length, number, root length index, root length density, etc.) calculation. Then, based on the rule of mass distribution, the mass quality distributed to individual roots is obtained, and the potential demands of new roots' absorption are calculated based on soil resistance and temperature of the surrounding soil of the root segments. If the quantity available for absorption assigned to the roots is less than the potential requirements, then all the root segments would shrink back accordingly. Root simulation flow-process is shown in Figure 2.

Data Structure

Plant roots had a clear hierarchical relationship, which can be described with the tree structure. Each root is decomposed into multiple nodes, with each node representing a root segment. Stored in the form of structural element, the node carries the required information for root growth. The running program visits and links each node in the tree structure, thus the morphological structure of the root is obtained. The data structure is shown as follows:

struct rootdata //

}

Information contained in this data structure is: (1) the spatial coordinates of the endpoint of the root segment, with which the direction of root growth is determined;

(2) the physiological age of the root, one of the root properties, through which the physiological age of the root or the root segment, parameters about the geometrical size of the root, branching conditions, the factor of geotropism during growth, and parameters of axial angles are correspondingly identified to determine the behavioral characteristics of the root; (3) the growth age of the root, reflecting the number of cycles the root axis has experienced since its emergence from the mother axis, which was primarily used to characterize that roots of the same physiological age have the same growth rate at different ages of growth; (4) data pointers, which are used to establish logical relations among data.

Data Structure

It is supposed that the root begin to grow at point (0, 0, 0), and the root growing out of the origin point is a primary root. In the general sense, if it is supposed that the current root is at level N; A is the starting point of the root; and D is the ending point, then another root growing out from this root (within the line segment BC) is in level N+1, and the root emerging at point B is in level N. With Figure 3b, the root information is determined as follows:

(1) The first root A1

min 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 , 1 , 1 0 , 0 , 0 0 , 0 , 0 R radius A rank A age A z A y A x A z A y A x A = = = → = → = → = → = → = → = → = →
(2) For roots of lower order, B2 and C2, in accordance with the aforementioned branching model, ). Therefore, the branch location and direction of branching root B2 are:

( ) ( ) ( ) min 2 2 2 2 2 2 1 1 2 2 2 2 1 1 2 2 2 2 1 1 2 , 2 , 2 1 1 1 1 1 1 1 1 1 R radius B rank B age B z A z A z B y A y A y B x A x A x B B B B B B B = → = → = → - ⋅ → + ⋅ → = → - ⋅ → + ⋅ → = → - ⋅ → + ⋅ → = → ε ε ε ε ε ε ( ) ( ) ( ) 2 2 2 cos cos cos 2 1 2 2 2 2 1 2 2 2 2 1 2 2 2 B B B z B z B y B y B x B x B γ ν β ν α ν ⋅ + → = → ⋅ + → = → ⋅ + → = →
Those of branching root C2 can be determined likewise.

(3) For root of the same level (root tip), D1, in accordance with the aforementioned root extension model, φ andθ are randomly generated, that is, the random rotation of A1 in the axial and radial direction. Based on the model of tobacco root development, the virtual system of tobacco root growth was established with OpenGL in the Visual C + + platform. Functions of the system mainly include: (1) the input of environmental parameters of root growth; (2) with the input parameters (sowing depth, soil constants, branching age, soil hydraulic conductivity, morphological parameters, biomass allocation, etc.) and meteorological data (sunshine duration, soil temperature, atmospheric density, atmospheric pressure, temperature, etc.), the system can output parameters about tobacco root growth at different stages (root length, root number, root length index, root length density, surface area, volume and water absorption as well as dry matter distribution, etc.) and three-dimensional visual results, allowing the examination of growth and distribution of tobacco roots from all angles. Figure 4a is the input interface of model parameters.

Conclusion

Based on observations and studies of the structure, growth and distribution of the tobacco root morphogenesis, as well as the results of previous studies, the method of systematic analysis was employed to divide the growth of tobacco root into three stages: root emergence, root growth, and root branching. According to the quantitative relationship between tobacco root development and the environment, the growth pattern of each stage and the correlation between different stages were elaborated. Based on these patterns, a virtual system of tobacco root growth was created with computer graphics. The system is able to simulate the three-dimensional dynamic growth of the root and calculate the root parameters at the same time. The result suggests:

(1) Since the relationships between tobacco root growth and the environment, nutrition supply of aerial parts and root growth, etc. are considered systematically, the model is systematic and universal.

(2) The simulation result is basically consistent with the growth and development of tobacco root, and reflects the pattern of tobacco root growth and development. Thus, the system could be utilized as a tool to study the growth and development of the tobacco root, and assist the digitalized regulation for high yield and quality of the tobacco.

(3) In the simulation, the information of root development quantity, length, distribution characteristics at any given time is stored in the root description file. The content recorded in this file is not only the current output, but also the input information for subsequent simulations, thus making it possible to continue the previously aborted simulation. Therefore, it is ideal to study the impact of different environmental backgrounds on the morphology of a partially developed root with this function.

(4) Although the model rather successfully simulates the dynamic change of root morphological characteristics, it still needs improvement in terms of simulating the impact of local soil's nutrition distribution on the roots as well as the interactions and competitions between adjacent roots.

Fig. 1 .

 1 Fig. 1. Branching Locations of the Root Axis.

Fig. 2 .

 2 Fig. 2. Flow of Simulation of Tobacco Root Growth.

2 C ε and 2 Bε

 22 are randomly generated, which, coupled with the range of radial angle α and axial angle β , randomly generate (

Fig. 3 .

 3 Fig. 3. Branching of Root Axis.

Fig. 4 .

 4 Fig. 4. Visualization of tobacco root growth.

, CH is the part that is lacking in CH supply, i.e., the difference

	),	T	max	and	T	min	represent the maximum and minimum temperature
	in the soil, respectively. If CH is in abundant supply, the actual root growth rate is
	equivalent to the potential rate (	dP dt ri /	); if the CH supply is insufficient, the actual
	root growth rate is calculated as follows:
				dt dR	wi	=	CH	∑ +	P CH ri	d	dt dP	ri	(5)
										i
	In Equation (5)d
	between from above the ground within time t required and actually provided. The actual CH supply to the root CH CH Δ is shown as follows:
			CH		f	CH	t	DMR	DM DMA	t

Table 1 .

 1 Parameters of root growth and branch models.

	module	Parameter	Value	Unit
	Model of	Soil parameter Rk	0.0125	1•d -1 • o C	-1
	root growth
		Soil parameter Rb	0.125	1•d -2
		Support ratio of tobacco	0.15
		fCH(t)
		Root weight in the ith soil	Rwgi=0.765/(1+exp(17.734-	mg•cm	-3
		layer Rwgi	0.152t))
			When i=0-10cm t≥80d
			Rwgi=0.495/(1+exp(10.146-
			0.088t))
			When i=10-20cm t≥80d
			Rwgi=0.275/(1+exp(9.317-
			0.079t))
			When i=20-30cm t≥80d
			Rwgi=0.136/(1+exp(11.589-
			0.094t))
			When i=30-40cm t≥95d
	Model of	Length of non branch on	0.5	cm
	root branch	basis of main root LB
		Length of non branch on	2	cm
		top of main root LA
		Length non branch on	1	cm
		basis of first order root L1B
		Length non branch on top	5	cm
		of first order root L1A
		Branch age of main root	3	d
		age0
		Length between branches	0.1	cm
		on main root length0
		Branch age of first order	7	cm
		root age1

  The data structure to store the root data { float x1,y1,z1;// To store the starting point of root segment float x2,y2,z2;// To store the ending point of root segment int phy_age; // To store the physiological age of root segment int growth_age; // To store the growth age of root segment struct rootdata *next;// The pointer pointing to the next data in the linked list struct rootdata *pre; // The pointer pointing to the pervious data in the linked list struct rootdata *f; // The pointer pointing its father node

E-mail: Uhnaustu@126.comU, HUxinmingma@126.net*

Acknowledgements

This study has been funded by China National 863 Plans Projects (Contract Number: 2008AA10Z220) and key scientific and technological project of Henan Province(Contract Number: 082102140004).


Wenying He
email: hewenying1227@126.com

Sen Yang

Rui Guo

Yaxiong Chen

Weihong Zhou

Chaojie Jia

Guojun Sun

GIS-based Evaluation of Soybean Growing Areas Suitability in China

Keywords: soybean, MCE, GIS, Suitable Level

In this study, the suitable areas for soybean in China were presented by GIS-based Multi-Criteria Evaluation (MCE) approach. We collected datas of environmental conditions and soybean growth associated factors, then, by the GIS technology we established spatial database of regional weather, topography, and soil conditions. Using the Spatial Analyst, the Spatial Interpolation, the Reclassification and the Weighted Overlay of ARCGIS9.2 operated to the database. Then the suitable criteria map of soybean in China was created, and the potential suitability of soybean planting areas was evaluated. The results showing 5,960,271 km 2 of areas are fit for spring soybean and 5,286,643 km 2 of areas are fit for summer soybean in the Northeast Plain, the Huang-Huai Plain and the Yangtze River Delta, in addition, there are lots of scattered suitable areas for soybean cultivation. This present study was aimed to provide some value references for Government formulating policies on the adjustment of industrial structure, and some reasonable guidance for farmers cultivating the agricultural products, more importantly, to achieve the purpose of utilizing natural resources reasonably.

Introduction

China has the longest history of the cultivation of soybeans, which is over 5000 years [START_REF] Qiuguang | The research of soybean cultivation history and value‖[END_REF]. The distribution of soybeans in China is extremely extensive, and before the 1950s, China had been the world's leading soybean producer all the time, not only having a surplus in self-sufficiency but with large quantities of soybeans exported abroad [START_REF] Hujun | Enhance breeding of new cultivars for special use,promote the development of soybean production and processing‖[END_REF]. However, since 1996, China's import of soybeans has been increased year after year, having currently developed into the largest soybean importer in the world [START_REF] Hong-Qi | HAO Yang-kun,-Historical review,current situation and development countermeasure of Chinese soybean‖[END_REF]. Because soybeans are of high nutritional values and healthcare functions, they are increasingly appreciated by the public, resulting in a boost in the demand [START_REF] Zhonghua | Soybean nutritional value and therapeutic care‖,Food and nutrition in China[END_REF]. While the current situation of the soybean in China shows that the soybeans are of low oil extraction rate and yield but of high cost, having difficulty in the competition with the imported soybeans. It can be said that Chinese soybeans are now "besieged on all sides and involved in trouble."

When digging into the reasons, it's found that the real shock to Chinese soybeans is the development of Chinese agriculture which is of low production input and productivity as well as poor competitiveness.

Meanwhile, China is seriously lacking in the investment in soybean research and the promotion of soybean technology. Although the breeds of corn, rice and wheat have been updated dozens of times throughout the country, many farmers in the main producing areas of soybeans are still cultivating the old soybean breed of many years ago [START_REF] Xigang | The development and countermeasures of China's soybean‖,Chinese Rural Economy[END_REF].

Currently, the soybean research in China is mainly focused on its nutrition and healthcare, in addition to the study of physiology, breeding and other aspects. Since there's a lack of macro research, it's necessary to develop the soybean mapping. In this research, the Multi-Criteria Evaluation (MCE) of GIS will be adopted to evaluate the potentially suitable planting areas for Chinese soybeans. The so-called MCE-GIS method is to employ reference standard and its weights in the assistance of the decision-maker to select the most appropriate option and solve a practical problem (objective) with an evaluation matrix [START_REF] Rico | Application of multicriteria evaluation to a spatial conflict in the urban fringe[END_REF]. In addition, the result could be visualized. This combination of MCE and GIS has been widely used in the evaluation and decision analysis of breed suitability. And in the central Mexico, the potential producing areas of corns, potatoes and oats have been assessed in the adoption of MCE method [START_REF] Ceballos-Silva | Delineation of suitable areas for crops using a Multi-Criteria Evaluation approach and Land use/cover mapping: a case study in Central Mexico[END_REF]. In this research the MCE method is carried out across the county to evaluate the potentially suitable planting areas of the crops, and to assess the potential producing area of Chinese soybeans. It is hoped that the research result could provide a visual guidance to the reasonable cultivation and the distribution planning of soybeans in China, helping to solve the existing cultivating problems of Chinese soybeans and to improve the efficiency of land use. This would also facilitate the instruction of farmers on agricultural production, increase the decision efficiency of the government and eliminate the blindness in agricultural investment, to further boost the investment incomes and the living standards of the farmers.

Methods

The main steps in the evaluation of the potentially suitable planting areas of Chinese soybeans are as follows: (1) to select the climate and soil factors that are essential to the growth of soybeans in reference to the opinions of the experts and relevant literature [START_REF] Xiaozen | Effects of various soil moisture on the yield of soybean[END_REF][START_REF] Sorte | Effect of water logging on soybean critical growth stages‖[END_REF][START_REF] Li | Grey Relational Analysis of Meteorological Factors on Soybean Growth and Yield‖[END_REF][START_REF] Heatherly | Vegetative development of soybeans grown on different soil types‖[END_REF][START_REF] Lan-Fang | Soil Respiration During a Soybean-Growing Season‖[END_REF][START_REF] Bhatia | Analysis of potential yields and yield gaps of rainfed soybean in India using CROPGRO-Soybean model‖[END_REF][START_REF] Burton | Soyabean ( Glycine max(L.) Merr.)‖[END_REF][START_REF] Del | An interdisciplinary model of soybean yield in the Amazon Basin: The climatic, edaphic, and economic determinants‖[END_REF]. [START_REF] Hujun | Enhance breeding of new cultivars for special use,promote the development of soybean production and processing‖[END_REF] to establish a database for the factors selected nationwide. In ArcGIS9.2, using spatial analysis module and Kriging spatial interpolation module to convert the raw data of each impact factor into raster layer. (3) to re-classify the raster layers of all the variables with re-classification module in the integration of the experts' opinions so as to get the suitable hierarchy map of each factor that affecting the growth of soybeans. (4) to adopt Analytic Hierarchy Process (AHP), in which all the factors will be compared and scored by agriculture exper t in pairs to calculate the weight of each impact factor. [START_REF] Xigang | The development and countermeasures of China's soybean‖,Chinese Rural Economy[END_REF] to carry out weighted superposition of the suitable hierarchy map of each factor in the use of the weighted superposition module in ArcGIS9.2, and finally adding in the information of land use/ land cover, together with the national province boundaries to develop the map of the potentially suitable planting areas of soybeans across China.

Research Area and Research Object

The research area covers the approximate 9.6 million square kilometers of the entire land area of China, which stretches out to the north of the center of Heilongjiang at the town of Mohe (53°31′N), to the south of the South Sea Island (4°15′N), to the west of the Pamirs (73°40′E), and to the east of the confluence of Heilongjiang and the Ussuri (135°05′E). In this research, soybeans are divided into summer soybeans and spring soybeans according to different time of sowing and harvesting in order to improve the accuracy of the experiment.

Selection of Evaluation Factors

The selection of evaluation factors mainly conforms to the following principles: a. dominance-the selection of major factors that affect the growth of soybeans; b. difference-the selection of factors that have significant difference and could create critical value; c. incompatibility (independence)-the selected factors shouldn't have correlations; d. operability-the relevant resources of the selected factors should be easy to get [START_REF] Liu Yaolin | Land Suitability Evaluation Based on Fuzzy Comprehensive Judgement‖[END_REF].

On this basis, the selection of factors that affect the distribution of soybeans includes: accumulated temperature at the whole growth period (≥10℃), precipitation at the whole growth period, sunshine duration at the whole growth period, the lowest temperature at the whole growth period (May), the highest temperature at the whole growth period (August), PH value of soil, field moisture capacity and type of soil.

Establishment of Database

Topographic Database

The national 1:250 thousand contour data are provided by the National Mapping Bureau, and the national digital elevation model (DEM) is developed in ArcGIS9.2. Firstly, the original contour data are converted into Triangulated Irregular Network (TIN) in ArcInfo, and then further into DEM to draw elevation information. Finally, the grid size is confined to 1000m×1000m in the use of Albers projection.

Meteorological Database

The multi-year average climatic data at 749 stations across China are provided by the Central Meteorological Bureau, recorded from 1971 to 2008. Making vectorization of the climatic data in ArcGIS9.2 could get the vector data of the coverage at the nationwide 749 stations. And then making spatial interpolation of these vector data in ArcMap and inserting the climatic data at the research area to get raster layers of each factor. Finally, the grid size is confined to 1000m×1000m in the use of IDW interpolation (Inverse Distance Weighted) and Albers projection.

Before the vectorization of the original data, origin7.5 is used to obtain a multiple regression equation of longitude, latitude and altitude, which is used to calculate the climatic data at each weather station and its difference with the original climatic data. And this difference should be vectorized. Then the regression coefficient will be adopted in the Spatial Analyst module of ArcGIS9.2 to make grid computing, the result of which will be overlapped with the vector data. In this way, the impacts of longitude, latitude and altitude are all taken into consideration, so the interpolation would be more accurate.

Soil Database

The national 1: 1 million soil type data are provided by Nanjing Institute of Soil Science. Firstly, the data are sampled into 99034 point data, to which spatial Kriging interpolation are carried out in ArcGIS9.2, and in this way the raster layer of soil is obtained. Then in combination with Soil Species of China, soil texture, soil PH value and other information about different types of soil are extracted, which are then used in ArcGIS9.2 to create the raster layers of each type of soil. Finally, the grid size is confined to 1000m×1000m in the use of Albers projection.

Re-classification

On the basis of the established database, the suitability of climatic and soil data is divided in accordance with the growing conditions of soybeans into five categories: highest, high, medium, low and minimum (five standards as shown in Table 1,Table 2). And then the map of the suitability of soybean factors is created through the re-classification in ArcGIS(Fig. 1,Fig. 2).

Table2:Specific level per factor for the summer soybean.

Multi-Criteria Evaluation (MCE)

The relatively mature methods adopted in the confirmation of evaluation factors include DELPHI, AHP, regression analysis, grey relation degree, principal component analysis and so on. In this paper, AHP method is employed. It is a kind of paired comparison method put forward by Saaty (1977) in the context of decision making [START_REF] Eastman | Raster procedures for multi-criteria/multiobjective decisions[END_REF]. This simple, flexible and practical MCE method can be used in the quantitative analysis of qualitative problems. Firstly, agriculture experts are asked to compare and score the relative importance of factors at the same level in pairs (see Table 3), then the results will be calculated in MATLAB2006 to obtain the weight value which represents the relative importance of factors at the same level, and finally the relative weight value of all factors will be computed and rearranged according to the general ordering of all levels. The calculated weight coefficients respectively are: accumulated temperature of 0.2657, precipitation of 0.2744, the lowest temperature of 0.1396 at the whole growth period, the highest temperature of 0.1633 at the whole growth period, sunshine duration of 0.0505, field moisture capacity of 0.0410, soil PH value of 0.0328 and soil texture of 0.0328. The weighted superposition should be carried out on these eight factors in the use of weight coefficients to obtain the hierarchy map, which should then be overlapped with the land use map that has deducted the areas of water, sand, desert and high cold wasteland to get the potentially suitable planting areas of soybeans in China (Fig. 4,Fig. 5).

Results and Discussions

Potential distributing areas for Soybean as show as Fig. 3.If the levels of Very high, High and Medium are selected the suitable planting areas, the overall suitable area of Chinese spring soybeans is5,960,271 km 2 , taking up79% of the total area and summer soybeans is 5,286,643 km 2 , taking up70% of the total areas. Since this is basically in line with the actual distribution of the cultivation of soybeans, it is demonstrated that this method is applicable to the division of the suitable planting areas of soybeans.

The evaluation of the potentially suitable planting areas of soybeans is an indispensable part of Chinese crop map system, having realized the visualization of the potentially suitable planting areas of Chinese soybeans and the suitable hierarchy. After the completion of the entire crop map system in the future, the internet would be should to provide visualization information about the distribution of crops in the provinces even in the counties and countries across China, filling the vacancy of online system of Chinese crops.

Problems and Prospects

The suitable planting areas of soybeans in this research are a kind of potential distribution, for the actual evaluation of the suitable planting areas of soybeans is likely to be affected by the micro topography, economic level, living tradition and other factors. Although there's a slight discrepancy between the potential distribution and the actual distribution, this research has roughly simulated the potentially suitable planting areas of soybeans in China. In the next step of work, market demand and supply, price fluctuation and other factors will be further studied to consummate the distribution map of the suitable planting areas for soybeans; in addition, the yield model would also be integrated in the evaluation of the potential production capacity of soybeans.

Meanwhile, the influence of climatic change on the distribution of the suitable planting areas of soybeans is also investigated. At last, this research evaluates the formation process of the components of yield, input, resource utilization, environmental load, potential pollution and so on, and it could also combine the economical analysis module to carry out marginal utility analysis of input and output, to form strategies that can replace the management measure and decision-making consultancy.

Chinese soybeans have the advantage of containing non-genetically modified ingredients, which confirms to the international consumption trend and should be made full use of to develop more effective cultivation planning, in the hope of boosting the yield of soybeans and improving China's production capacity of soybeans as well as the comprehensive competitiveness.

Table3:Analysis

  of system-level indicators and the results of the comparison:AT = Accumulate temperature(≥10℃), PR = Precipitation, MI = Minimum temperature(℃), MA = Maximum temperature(℃), SH = Sunshine hours ,WC = field water capacity ,ST = Soil type, pH = Soil pH

Fig. 1 :

 1 Fig.1: Factor map for spring soybean, including suitability levels for each factors: 1=Accumulate temperature(≥ 10℃); 2= Precipitation; 3= Minimum temperature in growing season (℃); 4= Maximum temperature in growing season (℃);5= Sunshine hours (h);6= field water capacity;7= Soil type;8= Soil pH.

Fig. 2 :

 2 Fig.2: Factor map for summer soybean, including suitability levels for each factor : 1=Accumulate temperature(≥10℃);2= Precipitation;3= Minimum temperature in growing season (℃);4= Maximum temperature in growing season (℃);5= Sunshine hours (h);6= field water capacity;7= Soil type;8= Soil pH.

Fig. 3 :

 3 Fig.3: The potential distributing area for soybean in China(1= Very High, 2=High, 3=Medium, 4=Low, 5=Very Low)

Fig. 3 :

 3 Fig.3: Suitability map for spring soybean in China.

Fig. 4 :

 4 Fig.4: Suitability map for summer soybean in China.