- Good Agricultural Practice (GAP) in Asia and Oceania
- Information Technology for Food Safety and Traceability: A Case Study of Thailand's Chicken Industry
In Thailand, 60% of its people are engaged in the agricultural sector. However, agriculture's contribution to the country's gross domestic product (GDP) has decreased from 20% to 9% in 2002. This indicates that the country's agricultural production for export is continuously decreasing. For many years now, Thailand's agricultural production for export has been mainly of primary commodities, namely, rice, maize, and para rubber.
Nonetheless, a major government policy has made Thailand "a kitchen of the world." Its livestock products for export were a major contributor to the Thai economy in 2002, with an income amounting to US$56 million. This shows that there is room for the development of livestock and poultry products for export, especially for the broiler industry.
In the last two years, the avian influenza outbreak has spread in Thailand and caused great impact and socioeconomic damage, as can be seen from the decreasing export value of its livestock products. Hence, the Thai government has launched a policy to control the avian influenza outbreak and assigned the Department of Livestock Development (DLD) to be the main organization to handle the matter. Although the outbreak control was implemented, the operation failed owing to the lack of an information system to manage a huge database. What was needed was an information system capable of compiling data related to the whole network of the broiler industry (whole supply chain) and providing information on outbreak control visualized on a geographic information system (GIS)-mana-gement information system (MIS) technology, with which authorities could develop a strategy to control the disease (Fig. 1).
A GIS is a decision support system (DSS). This system displays the data in integration by visualizing and comparing data in a spatial format. The data will be divided into tiers that can be piled up for comparison. Fig. 2 illustrates a sample of data presentation in spatial format that allows the authority to understand the comparison.
The GIS-MIS system is applied to set up the logistics of the data and analyze the spatial analysis tools. The DLD GIS Network aims to utilize the GIS-MIS to manage and make a strategic plan for livestock development in the country's broiler industry, including poultry disease control. Fig. 3 shows a sample of this system. Fig. 4 shows locations of the DLD offices throughout the country. It maps out control zones, the Regional Bureau of Animal Health and Sanitary, Provincial Livestock Office, Veterinarian Research and Development Center and Animal Quarantine Station. All these offices should provide immediate online data and information. Fig. 5 demonstrates the avian influenza outbreak and the standard farms that registered with the Provincial Livestock Office in Lopburi province.
The first step of system development is to study the system requirement and analyze it. In doing this, the development team studied the system requirement and analyzed DLD's information technology (IT) thoroughly. The system analysis was divided into three areas, namely, livestock system, data system and task system. The outputs of the analysis included weaknesses, problems and solutions.
The livestock system was precisely divided into two areas: standard livestock system (registered with DLD) and native livestock (unregistered with DLD). The livestock system has a clear system structure and can show the movement of poultry from parent stock farms to the poultry market. Also, this system has a poultry population not less than 80% of the country's total poultry population.
A standard livestock system can be visualized in a logical diagram (Fig. 6), which presents the relationship between the types of animals and the production process.
The relationship in each row of the diagram is a data tier of the GIS-MIS system. When piling up the livestock system into sub-tiers, it generates two types of comparison, namely, inner-relation comparison and outer-relation comparison. The former shows the comparison of egg chicks and parent stock, while the latter shows native chicken farms and geographic data tiers such as roads, streams, rivers and the disease outbreak ratio of infected areas.
Initiating the traceability system for the broiler industry is a priority for developing the standard and trademark for Thai products and also for complying with new regulations imposed by other countries. With traceability, product demand can be predicted. As a result, the market demand is in accordance with the production ratio, eventually stabilizing the price of poultry. Traceability of the movement of poultry in the production line is done by the Provincial Livestock Office and Quarantine Station.
As data are vital to information reproduction, data analysis is essential for system development. An investigation of the data system found that the DLD data system had five groups (Table 1). These data groups were found to work separately because they were created separately. In addition, these data were not created by proper data architecture. As a consequence, these data were duplicated and incurred error.
The first primary data (approximately 10,000 records) are on parent stock, hatcheries and poultry farms derived from farm operators that registered with the Bureau of Livestock Standard and Certification of DLD, which provides certificates on broiler chicks, layer chicks and ducks. The second primary data comprise slaughterhouses, product transform mills and poultry market registered with the Bureau of Livestock Standard and Certification of DLD, which provides domestic or international certificate to the farm operators.
The data were derived from a poultry population survey in September 2004. Surveyed were small farmers who bred poultry. Farmer data totaled approximately four million records and poultry data were more than six million records.
The types of poultry were native chickens, fighting cocks and female fighting chickens, broilers, chicken (egg), breeder chicks, bantam, turkey, meat duck, egg duck, breeder ducks, Muscovy duck, goose, partridge, ostrich, cockatoo, pigeon, swallow and love birds. Duplications, based on life cycles such as native chickens, partridge or other species such as meat duck and Muscovy duck, were found on poultry records.
The data of infected areas in Thailand were derived from the surveillance done by the Provincial Livestock Office and District Livestock Office. All the data (approximately 80,000 records) were collected by active and passive surveillance from the Emergency Response Center for Avian Influenza of DLD. Due to the emergency operation, 85% of the data were lost.
These are the DLD reference data, which comprise provincial livestock data, district divestock data, Regional Bureau of Animal Health and Sanitary, Veterinarian Research and Development Center, Quarantine Station and Check up Zone. These data are used as references for the Emergency Response for Avian Influenza, Animal Movement and DLD.
These are associated data for decision making. Included here are data on animals, communicable diseases, roads and rivers, administration, geography, meteorology data, residences of poultry owners and large water resources data.
The characteristics of data flow enable us to realize the task process, from what should be done first to what needs to be changed or cancelled and which is useful for decision making.
The concerned organizations in DLD related to the GIS-MIS Network System are as follows:
To tackle these problems, it is vital to create a unified database so that a reference task system is on the same data group and is able to be run on a central application that covers these data. In doing this, it will reduce data duplication and produce correct output.
The data system and task system analysis results pinpoint the weakness of the system. It is, therefore, necessary to upgrade to a new system. This section provides the data system design and a better task system than the old one. Furthermore, it also indicates other technical system designs, including database, application and hardware design.
This system design aims to accumulate the data by formulating a new data architecture. Fig. 8 shows the new data architecture, indicating two types of poultry data, namely, standard farm data and native farm data. The standard farm mainly focuses on farm location, while the native farm focuses on the farmer.
Fig. 9 portrays the data structure of the two groups. Since the features of the two systems are different, it is advisable to divide them into two types. The standard farm system has a huge number of poultry population, low scatter, and clear movement (have to inform regularly), while the native farm system has a small number of poultry population, high scatter and less movement (do not have to inform regularly).
In the case of the standard farm, the structure of data will mainly focus on locations such as farms and hatcheries. Two types of farm data are the status of existing number of animals, which always change, and farm feature data, which rarely change. The operators who handle the system are farm owners or managers of a company hired to handle the task.
Avian influenza data were derived from the avian influenza survey, which relied on primary data, namely, standard farm data and native farm data because the avian influenza could occur and spread from both farms.
Animal movement relying mostly on standard farm data is in accordance with the production process, that is, moving eggs from breeder farms to hatchery houses or moving broilers from hatchery houses to the farm. This movement system is under the DLD control (Provincial Livestock Office and Quarantine Station).
The DLD data were collected from the Provincial Livestock Office, District Livestock Office and Quarantine Station. These data are utilized by the entire livestock system. The Provincial Livestock Office and Quarantine Station are in charge of animal movement process.
Primary data refer to data on animals, locations and communicable diseases. These data link groups of data such as location codes with farm data of many areas.
Networking data groups make the operational feature change. It is obvious that with the new task system, data will be updated constantly by relying on operational processes and tools used for interfacing with database. Fig. 10 shows the new task system.
After all the data have been networked, the task duplication will be eradicated. Each organization is required to update data. A data network is a consequence of duplicated application on this set of database.
The avian influenza data are controlled by the Disease Control Center, Laboratory and Provincial Livestock Office. The Disease Control Center formulates the operational policy; the Provincial Livestock Office and District Livestock Office are the operators, which update the data; and the laboratory provides the sample results.
Native farm data came from the poultry population survey done by the Provincial Livestock Office, while the standard farm data came from registered farms at the Bureau of Standard and Certification, DLD. After being networked, the two data groups became the domain of national poultry records.
The new phase of animal movement data was derived from the operational process of the Provincial Livestock Office and Quarantine Station. The Provincial Livestock Office has to be informed of any animal movement. The Quarantine Station controls animal movement until the process is completed.
The primary data and DLD data are the duty of Information Technology Center. These two data groups are mostly the reference data, which are rarely changed.
The system can be shown by the relation of the data groups or the ER diagram and the data dictionary. Fig. 11 illustrates the system's ER diagram. Data are divided into five groups, namely, standard farm, native farm, DLD, primary and system. The database system was derived from the creation of a new data system.
The web application system is a computer program used for interfacing between operational system and data system in order to fix the data relationships and to present the data in many formats such as a map, table or graph.
The architecture of the web application system is shown in Fig. 12. The system is divided into two parts, Front Office (map) and Back Office (data management). The Front Office is a data system visualized on GIS, whereas the Back Office is data management involving adding deleting, or correcting data.
Fig. 13 presents the use of the Back Office. Users are controlled by the main security system. Additionally, the Back Office consists of several modules with different duties and responsibilities. The security system allows users to differently access the modules in Back Office, which consist of standard data for poultry data management. Sources of the poultry data were farms, hatcheries and slaughterhouses with standard certification.
The server system shown in Fig. 14 is used for processing and storing data. The system comprises three computers, as follows:
This is installed in two systems for checking the efficiency of both operations. First, the server is installed at DLD and linked with the Government Information Technology Services (GITS) by 2 MBPS bandwidth. On the other hand, the second server is installed at GITS. Fig. 15 illustrates the computer installation and other details. Table 2 exhibits the advantages and disadvantages of both cases.
Nevertheless, in order to know which type is more efficient in term of operation, it is necessary to try out both types. Currently, they are on trial.
The period of setting up the system was initially estimated at six months, however, it was necessary to extend it to ten months. The development process was as follows:
Previous development process is shown in Fig. 16 consisting of the following processes:
Though the duration and processes were already fixed, many problems still occurred after the system was developed. As a result, it was necessary to change the plan for the development process because the DLD livestock data system at that time was split into many groups of data and were not networked. The groups of data were as follows:
Standard data: collected from broiler farms registered with the Bureau of Farm Standard and Certification, DLD. The data comprised farm codes and farm livestock detail, stored on MS-SQL Server 2000, with approximately 10,000 records.
As a result, the development team altered the data of the three groups in the system and created a new ID to enable them to be networked. Data groups 1 and 2 remained with the system, while data group 3, because it was damaged and tended to cause error, it will be cancelled when a new survey will be made. Data group 1 will be converted into a standard farm data, while data group 2 will be converted into a native farm data.
In addition, there was avian influenza outbreak in Thailand at the beginning of the system development. Thus, the development was discontinued. Also, since the avian influenza had to be included in the system, which required a primary data processing that was time-consuming, its development was postponed. Eventually, the avian influenza data were presented on the system efficiently.
The system's development was postponed for about four months due to the problems found during the development process. Fig. 17 shows the actual development process. Nevertheless, the process will be completed when users operate the system efficiently. Though the system was delivered, the development team still has to adjust the system to work with utmost efficiency.
The customer requirement analysis process can be divided into three periods. First period analyzed the livestock system and planned the whole system at a conceptual level. The second period analyzed the avian influenza data through visualization on a map. These data were relatively damaged. The third period analyzed the old system until it was completed.
After coding and unit testing, the next processes were integrating and testing the whole system. Nevertheless, there was an adjustment of the second poultry population database and the avian influenza survey in July 2005. Hence, it was suitable to test the system in order to estimate the operation efficiency.
The Information Technology Center of DLD, Avian Influenza Emergency Response Unit, and the Hydro and Agro Informatics Institute (HAII) have agreed to set up a plan for this mission, as follows:
This process will be operated as usual, but it will be adjusted, by utilizing a computer system, instead of the manual system used in the avian influenza survey. In this regard, the Provincial Livestock Office and District Livestock Office will update the poultry population survey through the Internet network of the previous server installed at CAT. Only the poultry population checked for avian influenza will be put in the database of the new server at DLD. This new server will automatically create outputs and update the data daily. This operation will reduce processing time and output making enormously.
The outcomes of this operation are the following:
Software System Test
The test in July_August 2005 indicated that system performance had to support task load such as inputting 100,000 records of data from country organizations within a few months.
It is necessary to correct the set of programs, including making supplementary data through tables and graphs, to create the relationships among communicable disease, area, animal species and time so that the Bird Flu 1 and 2 outputs will work properly. Fig. 19 illustrates a supplementary report, apart from Bird Flu 1 and 2 outputs. This report shows the relationships among the aforementioned four types of data as well as a sample of the report presented in a table and graph.
Because farmer data are huge, inputting all these through the Internet network is not appropriate. Thus, the development team imports data from http://avflu.dld.go.th into http://dldigis.dld.go.th in order to reduce the process and have only one data input.
To improve the security system, the system requires separating its modules into sub-modules because the system engine only supports the security system at module level (sub-module is menu level).
The development team is continuously improving system performance according to user requirements. However, on the hardware, system performance indicates that increasing the file and Web servers' memory will improve operations.
At present, the problem is not the computer system but the network system of both users and servers. The servers are installed at ISP (GITS), which uses bandwidth, while the users still use ADSL or broadband, which is rather slow.
It is vital to improve, by utilizing more bandwidth and fixing the number of users in each period, at the users' side.
The GIS-MIS Network System of DLD was developed through a collaboration between DLD and HAII to manage and define the strategy of the national livestock system. This system covers Thailand's entire livestock system, including standard livestock and native livestock, and is also used as a tool for the monitoring and surveillance of communicable diseases in poultry.
For poultry, given the avian influenza problem, it is essential to include in the system the movement of poultry in order to get an accurate number of animals in each area and have a traceability process to increase security. Doing so will secure the exportation system of the country. However, this system development process is a time-consuming task; thus, it is advisable to develop it in the second phase. The agencies involved in this phase are the Quarantine Station and the District Livestock Office.
Figure 1 Avian Influenza Outbreak Control Process.
Figure 2 A Gis Data Presentation.
Figure 3 A Sample of the DLD Gis.
Figure 4 A Sample of the DLD Gis.
Figure 5 A Sample of the DLD Gis. Demonstrating Avian Influenza and Farms That Registered.
Figure 6 Logical Diagram for a Standard Livestock System.
Figure 7 Task System and Data Flow (Current).
Figure 8 The New Data Architecture.
Figure 9 (a) a Standard Farm Structure and (B) a Native Farm Structure.
Figure 10 The Network of Data and Organizations.
Figure 11 The Er Diagram.
Figure 12 A Sample of Application System.
Table 1 DLD Data Group Related to Livestock in Poultry
Figure 13 Architecture of an Application System.
Figure 14 A Terabyte Server.
Figure 15 A Network System Feature (a) and (B).Table 1. DLD Data Group Related to Livestock in Poultry
Figure 16 Process (Previous).
Figure 17 Duration and Process (Actual).
Figure 18 Computer and Operation System.
Figure 19 A Supplementary Report of Disease Surveillance.
Table 2 Advantages and Disadvantages of Both Network Systems
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