ANNEX IIIOF FINAL REPORT

OF THE CONCERTED ACTION"ANIMAL FEED AND NUTRITION" (AFN)

EUROPEAN FEED DATA MANAGEMENT MASTERPLAN(PRELIMINARY FINAL VERSION)

NOT INCLUDING:

APPENDEX I TO ANNEX III

“PROPOSAL FOR A CONCERTED ACTION “ANIMAL FEED AND NUTRITION; HARMONIZATION OF FEED INFORMATION AND ACHIEVEMENT OF ITS APPROPRIATE AVAILABILITY THROUGHOUT THE EC”

APPENDEX II TO ANNEX III

“FEED DATA BASES, FEED DATA MANA-GEMENT AND FEED DATA EXCHANGE IN EUROPE; PROCEEDINGS OF SESSION 2 OF THE NUTRITION COMMISSION DURING THE 42ND ANNUAL MEETING EAAP IN BERLIN 1991

ENFIC SECRETARIATJAGERSVELD 28222 AB LELYSTAD

EU AIR CONCERTED ACTION ”ANIMAL FEED AND NUTRITION”SECRETARIAT : JAGERSVELD 2, 8222 AB LELYSTADPHONE : + 31 320 231819FAX : + 31 320 213089EMAIL : enfic@wxs.nlINTERNET : www.wxs.nl/~enfic

THE NETHERLANDS

EUROPEAN FEED DATA MANAGEMENT MASTERPLAN

CONTENTS

1. THE EUROPEAN NETWORK OF FEED INFORMATION CENTRES1.1 RELEVANCE1.2 STATE OF THE ART1.3 TARGET1.4 MASTERING THE PROBLEMS

2. NATIONAL FEED INFORMATION CENTRE2.1 TARGET2.2 STATE OF THE ART2.3 MASTERING THE PROBLEMS

3. FEED DATA MANAGEMENT3.1 TARGET

- the need for databases- major data base users

3.2 STATE OF THE ART3.3 MASTERING THE PROBLEMS IN:

*FEED IDENTIFICATION (NAME, DESCRIPTION, NUMBER)- feed identification/describing, naming and numbering of feeds- international vs local codes names

*FEED DATA COLLECTION/RECORDING and*FEED DATA VALIDATION/SELECTION- What data- data acquisition and quality*FEED DATA PROCESSING AND MAINTENANCE and*FEED DATA DISSEMINATION- feed data processing and maintenance.- general- insertion- unit normalization- data checking- data maintenance- other routine database management tasks- data base maintenance- use of the feed databank; feed data dissemination- dissemination of compiled data- dissemination of individual data- dissemination media

4. DATA BASE CONSTRUCTION4.1 TARGET:4.2 STATE OF THE ART:

- overall plan

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- software- hardware- codes and keywords- interfacing the feed database with end users

4.3 MASTERING THE PROBLEMS

5. FOLLOW UP OF THE CONCERTED ACTION “ANIMAL FEED AND NUTRITION” AFTER 1997/1998.

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THE EUROPEAN FEED DATA MANAGEMENT MASTERPLAN

GOAL: PLAN TO MASTER THE PROBLEMS IN FEED DATA MANAGEMENT AND FEED INFORMATION IN THE EU (EUROPE) RESULTING IN AN EUROPEAN NETWORK OF FEED INFORMATION CENTRES1).

1. THE EUROPEAN NETWORK OF FEED INFORMATION CENTRES

1.1 RELEVANCE: In the framework of the production, processing and consumption of agricultural products, animal feeds play an important role in agriculture and in the light of growing interest in quality, efficiency and the environment, this role will gain in importance. The availibility of reliable, up to date information on feeds and feeding is essential for the realisation of a competitive and sustainable agriculture.

Animal feeds play a keyrole in agriculture. On the one hand an important part from the output of arable land and the (potential polluting) byproducts from the agricultural processing industries contribute to animal production. The prob-lems of releasing these by- and offal products are substantially reduced by their use in animal diets and consequent conversion to food of high quality.There are also large areas of land which can only be utilized as pasture and thereby contribute to high quality food supply for the human population.On the other hand all these feeding stuffs are the essential input for animal production.

Information on feeds, feed supply and feeding is therefore very important and indispensable. In this respect it should be mentioned that: - Having better access to good quality information about feeds and feeding,

on a macro (national and international) level can avoid or reduce imbal-ances. It gives politicians and the Animal Production sector better tools to set up and run the "National Farm", e.g. taking the right (legislative) mea-sures to guarantee a competitive, sustainable, environment friendly and food safe animal husbandry.

- On micro (farmer) level, animal husbandry can be practised more efficiently whilst simultaneously minimizing negative environmental impact.

1.2 STATE OF THE ART: The existence of a diverging, unharmonised situation (differences between MS´s in feed identification, feed data incompatibility and feed data management and as a consequence of that differences in feed(ing)-efficiency

1 ?) In the light of the growing demand for quality products from a sustainable agriculture, e.g. the demand for international agreed references and standards and the possibilities of modern computer and telecommunication technology, the International Network of Feed Information (INFIC) decided in 1989 to focus the coming decade on the establishment and international cooperation of Feed Information Centres in as much as possible countries in which the scientific, educational and applicable agricultural societies are supposed to work closely together. Together with the FAO Animal Production Service, INFIC in 1989 therefore proposed to stimulate the establishment of regional (continental) Main Centres, e.g. in Europe, Central- and South America, Africa, Middle East and Asia which can function as the umbrella of the national Feed Information Centres in these regions. Against the background of the reform of the CAP and complementory to EU feed legislation, in 1994 the European Commission in the framework of the EU AIR 3 RTD Programme, decided to support the establishment of an EU ( European) Network of Feed Information Centres with the following main objectives :- Guidance and assistance to the local FICs for their conceptual and practical organization, so that they may benefit of the collective experience; -Creation and operation of a common Feed Data Base, usable both on national and international level, linked to a European Feed Nomenclature System

and fed by the local FICs;- Dissemination of harmonised feed data at a EU (European) level.

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and competitiveness of the animal production systems) between MS´s both on micro and macro level).

The availability of reliable and up to date information on feeds and feeding in Europe can be characterized as rather diverse, both qualitatively and quanti-tatively. However, the information yielded from chemical analysis and in vivo digestibility trials would provide a common starting point for the interpretation of feed data - it is this interpretation which varies across Europe.

Only few countries in Western Europe have an adequate National Feed Information Network available. In this networks, modern research is closely linked to governmental- and animal industry related extension and education networks. Several countries in Eastern, Central and Southern Europe either do not have such an infrastructure or one operating at a low level. All existing national networks would clearly profit from a systematic access to data-sources outside the host country.

Historical, linguistic and scientific barriers have caused diversity in the definition and evaluation of feeds. In combination with the above mentioned variation in the dissemination of feed information, this causes huge differences in the level of practical application in and between countries. This impedes the desirable progress in and execution of EU Agricultural Policy towards adequate production and usage of feeds at farm level and fair trade in feedstuffs. It also inhibits international co-operation in animal nutrition research, thus making it more difficult to solve the economical, environmental and food safety problems in animal production.

1.3 TARGET: To collect, process and disseminate in a uniform way compatible feed data/information on MS- and EU level, based on cooperation (supply and exchange of compatible feed data) by/between individual Member State Feed Information Centres and a coordinating secretariat (European Feed Information Centre).

Formulation and execution of overall EU Agricultural Policy requires reliable, uniform, easily accessible and up to date information about feeds and feeding. Such information contributes markedly to fair economical competition between member states and would facilitate EU feed legislation. In the framework of an open EU market, probably expanding with 8-10 other non EU European countries in the future, an improvement in the uniformity of feed information is urgently required.

1.4 MASTERING THE PROBLEMS: By this CONCERTED ACTION “ANIMAL FEED AND NUTRITION”, in particular by a proper execution of the following chapters in this master plan. It should result in:

- The establishment of national Feed Information Centres;- The production of a European Feed Data Management Package, being the

amalgamation of this European Feed Data Management Master plan (in particular the European Feed Naming System and accompanying Feed Data Source Software) with specific Feed Data Base Software.

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- The testing (and amendment) of the European Feed Data Management Package as well in a small and a more comprehensive proto type of European Network of Feed Information Centres.

- The release of the tested European Feed Data Management Package for use both on national and international level.

- The establishment of an European Network of Feed Information Centres with the European Feed Information Centre as coordinating institution.

Ongoing regular EUactivities (developing EU feed legislation and EU Feed Utilization Matrices) are complemented by the European Association of Animal Production (EAAP) activity to establish a European Network of Feed Information Centres (ENFIC) and the initiative of eight Animal Nutrition Research Institutes to formulate common EU Feed Evaluation Research Projects (An EU Shared Cost project entitled “Development and Harmonization of Laboratory Methods for predicting Energy value of Feedstuffs for Ruminants and Pigs”). All these actions are further attempts to contribute to a solution to the above mentioned diversity.

In the light of the Third EU Framework Programme (1990-1994), RTD programme in the field of Agriculture and Agro-Industry, including Fisheries, these two activities (EAAP and EU) have led to the establishment of an EU ad hoc Group of Feed and Animal Nutrition Experts. In meetings in October and December 1991, this group has inventoried the existing problems in the field of animal nutrition in Europe, and indicated necessary actions to solve them.

To master the problems, it is clear that both on international and national level action has to be undertaken:

Action on international level is taken by this Concerted Action. It covers in particular the establishment of the governing, organizational, administrative and (preparatory) technical structures for a future European Network of Feed Information Centres with a central and driving role for steering group, project group and coordinating secretariat. After the design and adoption of the European Feed Data Management Package (European Feed Data Management Master plan plus accompanying common European Feed Data Base soft ware), participating teams (FIC´s) in a limited number of EU countries will start a prototype-ENFIC-network. The experience gained from these beginnings will be used to present and expand the full system to all EU Member States and, if appropriate, to other interested European countries.

Action on national level is supposed to be taken by the national coordinators (participants), stimulating the establishment of a national Feed Information Centre in their respective countries and furthering its co-operation in ENFIC.To maintain full subsidiarily, complete autonomy should be left to these national feed information centres. Governed and operated by the national authorities (animal husbandry/animal feed sector representatives, in many countries still with important governmental (research/education and extension) involvement), these centres are the hub in the national feed information networks and de facto the executives of the feed information harmonization on national level. They autonomously decide if and till what extent they will participate in the activities of the European Network of Feed Information Centres.

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To ensure the continuity in feed harmonization throughout the EU after 1997/98, it is proposed to transform in due time the secretariat of this Concerted Action into the European Feed Information Centre. However, for an important part it is up to the EU countries (e.g. their participating national Feed Information Centres), till what extent this European Feed Information Centre will be developed. Either its activities will be limited to secretarial/coordinating work or it will be developed into a real spider in the European Network of Feed Information Centres (ENFIC) with an own official European Feed Data Base linked to designated public and private feed data bases throughout the EU.

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2. NATIONAL FEED INFORMATION CENTRE

2.1 TARGET: To collect, process and disseminate feed data/information on central national level, based on cooperation of participants in a Member State feed data network, with the final goal of providing the end users with reliable up to date information on feeds and feeding. In the framework of this masterplan it is assumed that all FIC’s develop the necessary activities to co-operate (in due time) in the European Network of Feed Information Centres23)!

A local or national Feed Information Centre (FIC) is supposed to act as the official recognised Central Bureau of Feed Information in a country or a region.

Such a Centre functions on the crossroad of scientific institutes and practice. Its primary function is to collect continuously data about feeds and feeding and to amalgamate these into updated feed values of feeds which properly should be disseminated to endusers. According to the structure of the local feed (research) sector, it may also participate in the establishment of feeding standards and feeding methods in the different animal production systems.

These data are used in practice to maintain the most efficient method of animal nutrition under evolving product quality and environmental requirements. Supposing (1) a well functioning public and private infrastructure, including (central guided) official research, extension and educational facilities in animal production, and (2) cooperation in agricultural society (farmers unions, supplying and processing agricultural industry), countries must be able to increase their local use of (potential) available feedstuffs by a more efficient animal nutrition.

A FIC only can operate successfully, if there is an open and continuous communication between participants e.g. farmers, feed trade, compound feed industry, extension, research and education. This implies that a FIC has to create its own vertical integrated communication network which covers the whole chain from practice to research (via extension/education) and opposite

The FIC in this network acts as a spider and is the coordinator between participants. It stimulates the information exchange and formulates at the end the general accepted, most up to date feed data, feeding standards and accompanying feeding methods. These data are disseminated to all end users (farmers, extension, research, education etc.) in a suitable way (tables, brochures, or electronically via diskettes or on line connection).

2.2 STATE OF THE ART: A description of the diverging (technical-organizational) situation in the different European countries is given in chapter 4 of “Feed Data Bases, Feed Data Management and Feed Data Exchange in Europe" (Proceedings of session 2 of the Nutrition Commission of the 42nd annual meeting of EAAP in

2 3This Concerted Action emphasizes the importance of establishing uniform oriented and operating, strong national Feed Information Centres, being the backbone of a well functioning ENFIC. However, the near future will point out wether and till what extend EU countries will be able/willing to execute this aim or that they (in majority?) tend towards the establishment of a strong central located European Feed Information Centre (EFIC) with an own official European Feed Data Base linked with designated public and private feed data bases throughout the EU.

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Berlin 1991) describing the current situation, development and future prospects of Feed Data Bases in Western Europe (NL, UK, F, G), Eastern Europe (PL, USSR, H, Tsj.-Sl), Northern Europe (S, N, Finl, DK) and Southern Europe (It, JSl, GR., P, Esp.). It is clear that these differences in infrastructure together with differences in feed evaluation sytems not only leads to differences in feed efficiency but also to problems in international co-operation.

2.3 MASTERING THE PROBLEMS: On the hand of a clear description of the desirable organizational and technical set up of a national Feed Information Centre (FIC) and the urgent advice to national coordinators to stimulate in their respective countries the realisation of a national FIC according the description given her below:

ORGANIZATIONAL AND TECHNICAL SET UP OF A FIC

The Feed Information Centre should be governed by a board consisting of representatives of the following participating groups:

- PRACTICE (farmers, compound feed industry, feed trade);, - RESEARCH (fundamental and applied): - EXTENSION/EDUCATION (Governmental extension service,

Agricultural University and Agricultural Primiry and Secondairy Schools) and - AGRICULTURAL POLICY (Ministry of Agriculture).

Its duty is to establish and to maintain the communication network between participants and watch the overall goal of the FIC. It is responsible for the final functioning and products of the Feed Information Centre. In this respect together with the FIC personnel the board shall be heavely involved with:

a. the collection, processing and dissemination of data and information of feed quality : results of experiments, feed tables etc. with data about nutritional value of feeds and feeding standards for animals, but also descriptions of analytical methods, industrial processes etc.

b. the organization of expert and extension meetings to discuss and solve ad hoc problems in animal nutrition and to explain the application of most recent results from animal nutrition research etc.

Under this board several working groups are acting. Participants in these groups are representatives from animal nutrition research/feed laboratories, food processing industry, feed trade, compound feed industry as well as farmers, educational and extension personnel.

The principal group is a Working Group for feed data collection, storing processing and feed data dissemination. Participants in this group are supposed to collect, store, and disseminate feed data (names, description, chemical analysis, metabolic coefficients and nutritive value (energy, protein and minerals), and to compose from the raw data updated feed tables.

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There may be also a Working Group for establishing feeding standards and accompanying feeding methods for the different animal species if the Centre is entitled to work on these issues. This group is responsible for composing and updating the feeding standards for animals. It is important that this group operates as objective and neutral as possible and decides about feed evaluation systems to be used in the First Group.

Both Working Groups are responsible for the composition and updating of the entire National Feed and Feeding Tables. To stimulate a broad use in practice, it is advised to extract from the National Feed Table an abbreviated and simplified pocket format.

FIC personnel (secretary/director and technical assistants) coordinates all the activities described in this chapter. They also are involved with the implementation and use of feed data tables in practice. Therefore, in cooperation with extension services, local pilot projects on farm level are proposed. In these projects farmers should be guided in practical ration calculation etc.

The heart of a modern Feed Information Centre is a computerized Feed Data Base. Data Bases only are able to handle (recording, storing, processing) the growing amount of data adequately and put them into a desirable format feed composition tables etc. To operate these data bases, highly educated personnel is necessary with both nutritional and computing skills.

3. FEED DATA MANAGEMENT4) 3.1 TARGET: Efficient, uniform handling (collecting, processing and dissemination) of

compatible data of equally identified feeds, (these days markedly) facilitated by powerful computers and modern data base software.

THE NEED FOR DATA BASES

Information on feeds and feeding comprehensively is disseminated by Feed Tables. Tables of chemical composition and nutritive values of animal feeds have been in use for some 180 years, the first recorded publication being that of Thaer (1809).

4 ?) PURPOSE OF DATABASES; APPROPRIATE FEED DATA MANAGEMENT

The major purpose of a feed database is an appropriate management of feed data. FEED DATA MANAGEMENT can be defined as the whole cluster of activities with Feed Data. It consists of:

FEED IDENTIFICATION DESCRIBING/NAMING/ NUMBERING.

FEED DATA RECORDINGCOLLECTING/SELECTING/VALIDATION

FEED DATA PROCESSINGSTORING AND PROCESSING (including the IMPLEMENTATION of results of animal nutrition research)

FEED DATA DISSEMINATION PUBLICATION AND DISSEMINATION of feed data.

The different compartments of Feed Data Management comprehensively are defined and worked out in the International Feed Data Bank System

(International Feed Data Bank System) (INFIC Publications Nr 2, 3 and 5). In the framework of this Concerted Action it has been decided to update,

streamline and simplify this IFDBS as indicated below.

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The widespread development of tables of feed composition and nutritive value has highlighted the demand for this sort of information. However the past 30 years has seen the amount and type of data available increase enormously. This has resulted from more sophisticated and rapid analytical procedures, the introduction of new feeds and the expansion in many countries of a more extensive animal production industry. Whilst the use of feed tables will continue for some time, they are no longer suitable for the storage of large quantities of data. The availability of computers and software to take over and extend this role has been fortuitous.

Information presented in traditional tables of feed composition has been shown to have some major drawbacks.- Firstly it has concentrated heavily on the chemical composition of feedstuffs

with little reference to biological or nutritionally meaningful values. The usefulness of chemical composition data depends, amongst other things, on the availability of the component to the animal.

- Then, most tables do not provide information about the likely variability of the biological and chemical determinations for each feedstuff. To provide the users with nutritionally meaningful information, it is essential that feedstuff databases should also provide details on variability and on how this and the mean values may change with time.

- Another typical drawback of feed tables is that many of them, being composed manually, cannot be updated as often as they should. Computerized databases are the only way to automate table composition, thus reducing the time interval between updates.

- The last problem associated with paper tables is that they cannot be comprehensive any more : it is, practically impossible to squeeze into a single book a table made up of thousands of feedstuffs crossed with hundreds of chemical and biological determinations.

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MAJOR USERS OF FEED DATA BASES

The major users of feed databases tend to fall into 6 categories, namely :- people involved with animal nutritional research- feed providers and traders- feed manufacturers - extension workers - farmers - government policy makers

Whilst research workers are often heavily involved in experimental work which results in information becoming available for inclusion in databases, they are also users of database contents. For example, the availability of up-to-date values, the knowledge of the different experimental processes in use, are helpful in the formulation of experimental diets, in the teaching of students and, in a very important way, to enable identification of areas where knowledge is lacking.

Feed providers and traders wish to have comprehensive views of the feedstuffs available on the current market and of their use by the feed manufacturers. This enable them to evaluate the quality of their products in comparison to their competitors and to build their marketing and R & D policies .

Feed manufacturers require rapid access to information on feedstuffs to make informed decisions regarding commodity purchase and sale, together with information which will allow them to formulate economic diets or compound feeds. Precise composition data are also essential to take pollution problems into account.

Education and extension workers require reliable and meaningful information on the nutritive value of feedstuffs which will assist them to formulate and teach farmers to formulate diets to get economic and efficient animal production. In the foregoing example, any inadequacy in the relevance or quality of data will manifest itself fairly rapidly.

It is clearly necessary for government policy makers to be able to plan the utilisation of national feed resources and to understand the interrelationships in the feed-livestock economy. One way in which agricultural policy makers can assess changes in the feed livestock economy is through the use of a feed utilisation matrix (FUM) which indicates the utilisation of all feed types by each class of livestock. A full description of the development of FUMs for member countries of the Organization of Economic Cooperation and Development has been given by Parris and Tisserand (1988). The operation of FUMs is heavily dependent on the availability of databases for the provision of nutritional information on the feedstuffs that are relevant to each country.

3.2 STATE OF THE ART:

A description of the diverging, non harmonised situation in thedifferent European countries - in particular the excistence of feed data bases - and its consequences has been given under heading 2.2.

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3.3 MASTERING THE PROBLEMS: by uniforming/harmonisation of the different elements in feed data management, as follows:

*FEED IDENTIFICATION (NAME, DESCRIPTION, NUMBER)By the proposed EU Feed Naming System Software;

FEED IDENTIFICATION/DESCRIBING, NAMING AND NUMBERING OF FEEDS

Feed description, combined with feed naming and feed numbering plays a key role in (international) feed handling/feed data management as they are the essential fundament of all activities with feed and feed data either this occurs in practice (farm, trade) or in research, extension, education, etc.

Since an immense number of plants, animals, or other materials (minerals, chemicals, etc.) as such, partly or after been subjected to processes or treatments can be used as feed, it is clear that a very sophisticated system is needed to describe, name and number feeds in a consequent, systematic, understandable and retrievable way. A further requirement is that not only the different feeds will be described, named and numbered unambiguously and unique but that the system also generally will be used.

At the moment different systems are in use:

- Official nomenclatures (such as Council Directive 96/25 /EC or the NIMEXE) use common names associated with a literal definition of the feeds. Every feed has a meaningless code number. Terms used in common names and descriptions are (mostly) defined in glossaries.

- Private nomenclatures - maintained by feed companies and some R & D organizations - use generally common names associated with code numbers.

- Other R & D organizations use the INFIC nomenclature or an INFIC-like nomenclature : the INFIC system consists in describing the feeds through a set of facets such as ORIGIN, PART, PROCESS, MATURITY, CUTTING or CROP and GRADE.

INTERNATIONAL VS LOCAL CODES AND NAMES

FIC databases have to cope with an internal contradiction. On the one hand, they must provide their users with intelligible, tailored information. This means, for instance, that the data must be presented in the users language. Accumulated experience from actual FICs shows that each country, each region has its own ways for naming and using feed information (and this may vary ,through time). To be successful, a young FIC must convince its users of its usability , and talking the same language as its users is probably the best way to achieve. On the other hand, a FIC must be able to exchange data with other FICs, and that means a thorough standardization of terminologies, at least for feed and feed nutrient names.

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Ideally, ENFIC should be able to centralize all that naming and coding work. But the creation and maintenance of hundreds of thousands names and codes for everything, from feeds to laboratories throughout the world, does not seem very realistic. Furthermore, some data that have a precise and important meaning at local level may not be relevant at international level.

To meet both purposes, a FIC should therefore maintain one first set of locally defined terminologies (about feeds, nutrients, methods etc.) and ensure at the same time the perfect compatibility of its local names and codes with the names and codes defined at international level. Part of the ENFIC role will be of naming and coding the information necessary to correct data or commodities exchange.

*FEED DATA COLLECTION/RECORDING and*FEED DATA VALIDATION/SELECTION

By specific European Feed Data Source Software, covering protocols on background, chemical composition and bioavailibility data;

WHAT DATA ?

In a perfect world all information about feeds and feeding would be freely available and could contribute towards national and international databases. Indeed, every measurement made on every feedstuff would be gathered and considered for entry to the database. However, data stored must be of a certain quality in terms of the samples chosen and the methods used and should relate to what the different kinds of users need or want to know now or in future.

To facilitate feed data recording and to get reliable, system tailored information into its system, INFIC developed an international Source Form (ISF). The information to be gathered falls broadly into 3 main areas:1. Background information 2. Chemical composition 3. Biological measurements.

It covers data about:

Origin of Data (e.g. laboratory) and Origin of Sample, Feed Description according to the 6 facets approach, Chemical Composition (including method of analyse), Energy, Minerals, Vitamins content, Other analyses, Digestibility Trial(s), Other biological coefficients.

However, being in particular too time consuming and judged as too complicated, the ISF has been hardly or only to a very limited extent accepted by raw data providers. They have preferred to provide national databases with copies of their own tailored information, being often just a small part of the entire ISF.This means that the selection and validation process has to be done by the feed database manager itself.

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To facilitate feed data recording from the source, specific European Feed Data Source Software, covering protocols on background, chemical composition and bioavailibility data has been developed to preensure as much as possible accuracy and reliability, including the right provision and check of Feed description and Feed numbering.

DATA ACQUISITION AND QUALITY

Data may be generated specifically for a database, it may be generated by laboratories for their own purposes, it may be abstracted from literature or transferred from other databases. Each of these four major methods of acquiring data is discussed below.

Specific generation

Data produced specifically for a database has the advantage of meeting all the standards and requirements for this application. Background information is available, the feed can be accurately named and described, methods of analysis can be chosen in advance to ensure they are robust and adequately referenced and approved, quality can easily be controlled and the data produced is very relevant. However, this can tend to become rather introverted and isolated unless the data and methodology undergoes regular comparison with laboratories undertaking similar projects. Ways in which this can be monitored include the use of ring tests for both in vivo and in vitro methods in which standard samples are circulated to a group of workers involved in similar work at different centres.

Common features of external sources

Before discussing the different kinds of external data sources, it is necessary to present their common features.First, the analytical methods used will vary considerably and may include local, undocumented improvements , even for officially defined methods. Depending on the sources, other methods will be described with a much varying precision. Some methods will have to be labelled as unknown while others will be fully described. It is also often difficult to obtain sufficient background information to describe the material adequately. Vagueness of methodology description and background information make the pooling of data sometimes questionable, when not the data themselves.The second problem associated with external data is their heterogeneity. Whilst electronic data become more and more compatible from a physical point of view, naming and coding of feeds nutrients, methods etc. are quite different between countries and organizations and relating different coding systems still need both time and knowledge. For instance, at different places, a same product can have different names and a same name can mean different products.In fact, when managing external feed data, one must be perfectly aware of the lack of control or knowledge regarding the quality and relevance of these data.

A third point concerns the confidentiality of data. Unpublished data, especially industrial data, are not always free of use. Feed companies want to keep totally

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secret some strategic information or do not want their data to go to competitors. Of course, they are not obliged to give away every information they have, but it is also possible to design some confidentiality systems that allow data dissemination without violating any industrial secrecy. Many times, it will be enough that the data are unsigned , i.e. that they do not bear the sources name. Some peripheral information, such as the data origin (the feed provider, for instance) can also be kept secret. Other data will be usable only for statistical computations.

Data from other laboratories

Data can be provided by external laboratories, research laboratories or the ones operated by feed manufacturers.Most of the data produced by manufacturer laboratories will be chemical determinations, often limited to, for instance, proximate analysis, as they have been produced for a specific purpose and not for a scientific investigation. However, some important laboratories can go much further than the proximate analysis and the main feed companies have experimental stations for biological essays. In addition, parts of the information may be confidential and hence subject to special arrangements in terms of coding and storage. However, data from external laboratories have some important features that make them very interesting :Being industrially generated, they come in huge numbers. Hundreds of thousands of samples are yearly analysed by these laboratories. In fact, they produce most of the feed data in the world. These large amounts of data will allow, for instance, statistical analysis otherwise impossible. Industrial data give a realtime picture of the feed market, because the samples correspond to the actual feeds used in the feed industry. Most large laboratories have computerized systems and databases for managing their information, and these systems are becoming more and more open as the need for internal (between different services) or external (between companies or affiliates) data exchange arises within the companies. It is therefore possible to automate, at low costs, the data transfer from these laboratories databases to a FIC database.

Data produced by other research laboratories are often mostly available through literature.

Data from literature sources

Literature can provide data about:- recent research developments in feeds and feeding- nonconventional feeds - uncommon chemical/biological determinations- surveys on feeds quality.

Literature data represent also quite a significant volume (though much less significant than industrial laboratories do). However, integrating these data in a database means a fairly high and continuous cost as continuity of literature surveillance is desirable: literature data demand a highly trained staff who must read the literature and then analyse, extract and type the data, and this process cannot be automated.

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Data acquisition from literature sources can appear complementary to acquisition from industrial laboratories. Decisions that need to be made prior to taking this approach are largely defined by the number of publications that will be screened routinely, hence the size of geographical area involved, the range of feeds of interest and types of animal production all need consideration.

Data from other FIC databases

Data may be acquired from other databases, for example INFIC holds information from many different countries which may, if suitable, be combined. INFIC/ENFIC can play an important role in the process of data exchange by defining standards for the data: some of these standards may be logical: naming and coding systems, for instance. Other standards, such as file formats may be physical.

*FEED DATA PROCESSING AND MAINTENANCE and*FEED DATA DISSEMINATIONBy the provision of Specific European Feed Data Base Software enabling the most suitable and modern methods of processing and dissemination, currently in use.

FEED DATA PROCESSING AND MAINTENANCE.

GENERAL

Data usually arrive under a raw form, not immediatly compatible with the ENFIC structures. They first need to be translated . The feed names, for instance, will be converted to EFNS.All available information foreground and background will so be translated into the standardized system.

Then, all information is listed and checked for errors. Data are converted to standard units. New data being entered are compared to data in the existing data files. Potential erroneous data are automatically flagged and listed for visual inspection by the database managers. Truly erroneous data are corrected or deleted and acceptable data are reentered into the data file. New data and corrected data are then inserted in the database structure.

Before they enter the database, the raw data are usually in the form that best suited the data producer. For instance, literature data are not databaselike structured : they are scattered through the different columns and tables of the paper document. Laboratory data may come on floppies and they may be coded as they were in the laboratory computer.The database managers must first physically convert the data, by typing paper data into temporary data files or by converting the original data files into a file format compatible with the database software.

The second step of data insertion is a logical one. Data texts or codes must be translated so tht they can be understood and processed by the databases structures and softwares. A local feed name or feed code will then be translated in a unique EFNS. A similar process will occur with every kind of information. At this point, internal coding in the database is of course extremely important and ensures data

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coherence: correct codes must be provided, and if necessary created by the database managers.

UNIT NORMALIZATION

Depending on their trade, localization etc., data producers have their own preferences about units, and raw data arrive under every imaginable kind of units. However, data processing requires standardization for the units (to calculate means, for instance).

Therefore, the database managers have to decide for standard units into which all external units will be translated. A particular mention has to be made about the choice of a on dry matter or a as fed way of expressing the values. The DM expression is usually preferable (when it is relevant), for on DM data are more comparable. However, for compound feed formulation purposes, the as fed way is the only way. Therefore, it can be proposed to retain, when possible, the two expressions for a same value.

DATA CHECKING

After inserting the data, it must be checked. The best way to do this is to store for each feed the minimum and maximum values for each variable. After the data have been inserted all values are compared with the stored criteria and when the result of an analysis does not fall between the minimum and maximum value, this is reported to the database manager. He has to check whether a mistake was made during the coding or the insertion of the data or even in the source laboratory. It is also possible that the feedstuff has not been adequately defined, it could be a mixed product or even a falsification. Such samples must not be used in the further calculations. The criteria used for data validation must be up to date, because populations can change, for example as a result of plant breeding programs or new processing methods. Information for updating the minimum and maximum values can be displayed in the form of histograms and graphs for the different feeds. Outliers can easily be identified and one can also see if the population as a whole is changing. It is possible to calculate the range automatically.

If there is a certain number of samples of a particular feed in the database, it will be appropriate to calculate the standard deviation (probably multiplied 2 or 3 times) as an indication of the range. Large changes in the range should be reported to the database manager. The calculation programs can also contain checks to trace incorrect data. It is possible to check, for example, whether toluene dry matter content is Rreater than oven dry matter content, and if this is not the case, it is likely that an analytical error has been made.It is important to realize that the computer is not able to do all the checks. If many checks, including double data elimination and proper codinR enforcement, can be automated, for data validity, only the detection of questionable results can be automated ; in the last resore, a person with a sound knowledge of feeds and feeding has to examine them and decide whether to keep or refuse them.

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DATA MAINTENANCE

One of the main interests of a feed database is its capacity to acknowledge the changes in the feed world : new feeds, new technological processes, new methods of analysis are daily being created and tested.

The database managers have the task of continuously adapting the database to these changes, by creating and coding new feed definitions, ew methods of analyses etc., and even new countries.

The database managers have also to decide how long samples are to be kept in the database. While old samples may not be used in the current calculations, they cannot be totally discarded because they can still bear some interest, at least historical. Some old samples can also be of great importance, for instance when they have been analysed for a particularly rare or costly nutrient. After having decided what samples to keep in the main database, the database managers can store the discarded samples and attached results elsewhere in the database structure (so they can be easily retrievable when necessary) or on a physical media external to the database (hard disk, floppies or tape).

OTHER ROUTINE DATABASE MANAGEMENT TASKS

The database managers are responsible for the safety and security procedures in the system.

At a physical level, the database must be backed up regularly.

For multiusers databases, the database managers also have a coordinating task. They must grant (or revoke) the correct privileges to users : some users may only look up to data, while others may also be permitted to insert and delete data and update mean values etc.

DATABASE MAINTENANCE

The effort involved in the maintenance of the database must not be underestimated.

Data change, but the way people are likely to use them also vary. New ways of entering, translating, checking or disseminating data must be reflected into the programs originally built to use the database.

An additional problem is that many database software companies periodically update their products. A new version of a database management system (DBMS) can have more features than the old one, thus old sections of the database application programs can be rewritten in improved ways, sometimes faster or with more facilities.

A database is a constantly evolving entity. Changes in structure as well as in the database application programs will be made during all the databases cycle life. Therefore, the continued assistance of a good analyst/programmer, (possibly parttime) is essential.

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USE OF THE FEED DATABANK; FEED DATA DISSEMINATION

The primary task of a (Network of) Feed Information Centre (s) is to collect and process feed data for dissemination.

Feed composition tables are one of the most effective means of conveying information to users. These tables are composed according to different uses and to meet specific needs. Mostly requires the composition of such tables (e.g. feed tables for ruminants) the selection of different datasets (e.g. the selection of all feeds fed to ruminants and the selection of those kinds of nutrients relevant for ruminants).

Energy values as well as other nutritive values (for instance digestibility values) shall also be included, when such means are relevant, in the general process of compiling composition tables5. These values may be means calculated from measured values collected from different laboratories as the feed composition values or, when measured values are not available nutritive values can be derived from other values (it then has to be mentioned). As already mentioned above, the other steps included in this process should be the selection of data and the calculation of averages and standard deviation, the sorting of the material and the combination of the data with the right International Feed Descriptions or International Feed Names (or Country names in a specific language).More generally, the FIC should be able to disseminate feed data under whatever shape and format, from raw data (the individual aminograms of a thousand wheat samples) to tailored statistical values (e.g. the means, standard deviations and extrema for the aminoacids on British wheat).

Not only numerical data can be diffused by the FIC(s). Textual information on feed origins, technological processes, analytical methods, experimental protocols, etc. that are stored in the database can be, even apart from their related numerical results, very useful and have to be directly and easily retrievable.

At last, the database via terminals or internet may be open for individual use or its content may be provided together with feed tables to endusers on an updated diskette, CD ROM etc.

DISSEMINATION OF COMPILED DATA

Data may be disseminated after compilation. Data may be output as tabulated values, in the form of a book or a floppy disk. The period between updating these publications must be considered. Alternatively, more updated summary tables may be accessed by a direct online search of the database (through a VIDEOTEX service, for instance), either by the database manager or an informed user. Data is usually required either for immediate practical use such as ration formulation, or for longer term research purposes. The kind of application will normally define the

5 ?) The intention is to include in the European Feed Data Base for every feed incorporated:COMMON NAME, FULL DESCRIPTION, STANDARDISED CHEMICAL COMPOSITION (average and standard deviation), VITRO/VIVO DIGESTIBILITY if appropriate and COUNTRY FEED VALUE’s (energy/protein and minerals if appropriate).

THE COMMISSION SERVICES AT THE END OF 1996 REQUIRED ALSO THE INCLUSION OF CONVERSION FACTORS FOR OBTAINING FROM THE COUNTRY FEED VALUES PRELIMINARY EUROPEAN ENERGY-, PROTEIN- AND MINERAL VALUE’S FOR THE DIFFERENT SPECIES FARM ANIMALS. THE LATTER IN PARTICULAR TO FACILITATE THE COMPLETION OF EU FEED UTILIZATION MATRICES (FUM’S)!

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form of output as to how up to date and detailed it needs to be. Retrieval of compiled data has to be undertaken at least according to feed description and this is why it is important to be able to classify feeds accurately and as completely as possible. For example, a simple request for soyabean meal might include fullfat, hipro, 44/0, 44/7, solvent and mechanically extracted products, the mean results of which would be meaningless, hence as detailed and accurate a classification as possible must be given.

The way the output is presented depends on its users. For practical use, a very detailed output is not normally necessary, but when the results are used for research purposes, there may be a demand for more detailed or more specific information (with conditions on the feed origin or the analytical methods for instance).

For global feed composition, the most frequently presented values are :- mean value: the average value calculated for a certain feed or for a quality class

of a feed (e.g. palm kernel expeller < 220 g/kg crude fibre and palm kernel expeller > 220 g/kg crude fibre).

- standard deviation; this is calculated when 5 or more samples are used. Using the standard deviation, a range can be calculated in which 95~ of the whole population will fall. The use of a standard deviation only applies to normally distributed populations, and accordingly in some cases it will not give an adequate description of the distribution of the population.

- median; in populations which do not have a normal distribution, the median (in combination with the range) gives more information than the standard deviation.

- minimum and maximum values; give the full range in which the results fall.- number of values; shows how many samples are used in the calculations and

help to evaluate the meaning of the value.

Other forms of compiled output that can be produced are:

- histograms; a histogram can be useful to see how the population is distributed and if there are any outliers in it. It is also possible to see whether a population consists of two different groups. In this case the product can be split up into two quality classes.

- graphs; for instance, a graph shows how two different analyses are related to each other, e.g. the protein and crude fibre content of palm kernel expellers. From the graph outliers and different groups in a population are easily identified. Many other graphs can be compiled.

- regression analyses, when two or more different variables seem to be related to each other, the relationship can be tested by performing a regression analysis. A regression model can also be used to predict values from other analyses, for example in The Netherlands, regression relationships are used to predict the content of phytate phosphorus in a feed from the analysed total phosphorus content (CVB, 1977).

DISSEMINATION OF INDIVIDUAL DATA

Today's widespread use of microcomputers and accompanying softwares (databases, spreadsheets, graphical and statistical packages) has made possible the process of individual feed data (i.e. on a sample basis) by endusers who want to do

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their own compilations and analysis. For these users, already used to processing their own (internal) data, readymade compilations are not enough.

Data files can be of all imaginable contents and formats: they can contain numerical and textual data, or even be only textual (lists of methods of analysis, for instance). In this context background information that are usually unavailable in readymade compilations become very useful for comparing and assessing feeds and feed data. For instance, a file containing the analytical results for a batch of samples, the sampling dates and the samples providers names can be used for multiple purposes.

Individual data dissemination does not replace the feed tables. It just allows a more specific, and thus efficient and profitable, use of the evergrowing flow of feed data for the users who need to know more than the usual mean values.

Of course, the use of such data requires some training. Individual data files should not be transmitted to all endusers, lest some misuse and misunderstanding of data significance would occur. Individual data dissemination can be monitored by the FICs Working Groups.

DISSEMINATION MEDIA

Until now, the only dissemination media for feed data have been the paper tables. As previously discussed, paper tables have many advantages, the first being their handiness, and this dissemination media will remain the best suited for common purposes.

However, paper is not a convenient media for handling large amounts of data, such a those processed and disseminated by a feed database. Computer incompatibility being not what it used to be, individual data, as well as some compiled data, should be disseminated under an electronic form so that these data could be integrated to the data flow of the users organization. For example, a diskette from the FIC arrives to the users office; the files on it are read by the users microcomputer and processed by the users favourite statistical package. Results from the analysis are then imported into a final report written by the user. In this kind of processing chain, not at all unusual these days, data are never retyped, thus sparing secretary time and avoiding entering errors (at least at this level). This same batch of data will perhaps be processed, some time later, by another user.

Even more newer technologies could be of use for dsseminating feed data. Online services, such as the highly popular French MINITEL, could be a cheap and userfriendly alternative to feed tables. The whole database itself could be accessed through an online service by users paying an annual fee (such databases already exist, for chemicals or legal texts for instance).

Hypertext software technology, associated with CDROMs or INTERNET, becomes more and more widely used in the educational and training fields, and it is not totally utopian to imagine a Feeds and Feeding CDROM Handbook where both textual (how to feed cattle ?) and numerical (what is the feeding value of alfalfa hay for cattle ?) information would be made intuitively retrievable through hypertext

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links (by pointing and clicking a mouse device on the hay keyword in the "how to feed cattle " chapter).

4. DATA BASE CONSTRUCTION

4.1 TARGET: To facilitate an efficient way of handling of hugh amounts of feed data.

4.2 STATE OF THE ART: Below, an indication is given about the way data bases in their technical and organizational environment are developed, e.g. including the interfaces to endusers.

OVERALL PLAN

In the last 20 years or so, database building has become an industry in itself, with its own methodologies and specialists. Despite claims by some microcomputer hard and software companies, building a professional database is not an easy job, and requires much effort and time. The best way to begin is to first make a detailed study of the overall task, preferably with a systems analyst. This study has to result in a masterplan, essentially a detailed description of the system to be built.

The first step of the study is to identify clearly the users requirements. This information can be gathered by interviewing the potential users, and an idea of some of the questions to be answered are:

- What is the general aim of the database ?- What information has to be stored ? (types of analysis, additional information). - What is/are the origin(s) of the information ? (laboratories, literature).- How many samples will be stored for current use (i.e. except the old ones that

can be discarded) ? - How many samples are likely to be added each year/month/week ? - Which values will be calculated ? (mean, standard deviation, other statistical

analyses). - What output must be processed ? (individual data, tables and/or graphics).

Using this information it is possible to make a preliminary design of the system consisting basically in two models. One model the datamodel describes the information to be stored and the relationships between the various attributes. A second model the processes model describes the different ways the data are likely to be used. These models are not specific to any hardware or operating systems and can theoretically be implemented on any system with database management abilities.

The final masterplan gives a review of the user requirements, a description of the data/processes models, advises about hard and software and provides a time schedule for the project. This plan must also contain information (number and qualifications) concerning the technical staff which are needed initially, for the period of system development and thereafter for the technical maintenance. Another point of importance is the staff required to load the data to get the database

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operational and for maintaining the stored data. This masterplan forms the basis for the construction of the database.

A widely used method in developing user applications is termed prototyping. After the programmers have tested the programs, the users start testing the prototype database with a special set of data, the test set. After a certain period, an evaluation takes place. Discussions are then held relating to specific problems in using the database, response time, results of calculations etc. If the prototype proves unsatisfactory, a new one is made. If the problems are only minor, the programs are adapted accordingly, and when the users are completely satisfied, the database is delivered.At this point the users start inserting real data using the facilities. It is advisable to perform a further evaluation after the first few months of operation, as sometimes improvements to the programs will be needed as a result of suggestions made whilst using the system in this initial period. Another point of importance is the response time. During the test period relatively small sets of data are used, so the response time will always be short, but after inserting a large number of samples (hundreds or thousands) the response time may be ,longer. When the response time becomes too lengthy it may become advantageous to run the large programs (checking data, large calculations) at night in batches.

SOFTWARE

Database Management Systems (DBMS) are special packages for building databases. These packages, which comprise several programs, have several features for data manipulation :

the database engine manages the internal storage and retrieval of data.

- a query language; a language to manipulate the stored data. A well known query language is SQL (pronounced sequel). SQL was developed and defined by IBM Research, and has become an ISO standard as a language for relational database systems.

Other optional, though current, features include :

- screen programs; for direct access to the data (insert, delete, update, etc.). application generators; for quick design and creation of applications programs

- host language interface; an interface that makes it possible to access the database with programs written in the programming language of the host computer, for instance Fortran, Pascal or C.

- a report generator; for producing reports with a specified layout.- backup facilities; for making backup copies of data to be used in case of

calamities such as a computer crash.- a dataloader; for transferring external files, such as ASCII, files into database

format.- usual commercial spreadsheet or word processor software should be able to

access the data stored in the database

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One of the aims of a feed database is to apply statistical calculations to the stored data. Most database packages have only limited facilities for such calculations, thus there is a need for a software interface with a statistical package, so that data can then be retrieved from the database and loaded into the statistical program. The most frequently used calculations or options in a feed database are mean, standard deviation, median, minimum/maximum values, regression analyses, histograms and graphs. The numerical results from these calculations can then be stored in the database if required.

HARDWARE

Until recent years, all important databases were built on mini or mainframe computers. Due to the evergoing improvements in the microcomputer technology, it is now possible to run a truly professional database on a comparatively lowpriced microcomputer.

A DBMS needs important hardware resources, such as a large amount of disk storage capacity (depending on the amount of data to be stored, probably more than 200 or 500 Mb including the operating programs) and at least 16Mb of internal memory. A fast, powerful CPU (Central Processor Unit) is also required so that the response time are satisfactory, especially in case of multi-user systems.

Though minicomputers and mainframes monitored through dumb terminals are still an interesting solution (for instance if such a machine, used for other purposes and shared by other users, is made available to the feed database managers), the most adaptive hardware for a multiuser feed database seems to be a microcomputer network based on a client-server architecture. In this architecture, the database is installed on a powerful micro or mini computer called the server. Queries are made by users working on normal micros the clients linked to the server; the queries are then processed by the server and the answers are sent back to the users. The main interest in this kind of architecture is that the users can query the database from their own micros, sometimes through their usual software tools. Many companies in the microcomputer software world now include database querying abilities in their bestselling softwares classic statistical packages, spreadsheets and even some word processors are able to query a SQL database and to integrate the answer in their cells, files, texts etc.If the feed database is a mono-user one, a 486 or Pentium-based microcomputer can be powerful enough. If the database was to become multiuser after some time, this machine can be used as a server or as a client station.

CODES AND KEYWORDS

In modern databases, efficiency in complex data retrieval and maintenance is achieved through precise and thorough coding of information. This is a structural necessity, whose details should be let to the system analyst responsible for the physical implementation of the database. The FIC databases being managed (created, updated) at local level, these structural codes cannot be decided and maintained at higher (International, Regional) level, for it would result in a general paralysis of FIC databases.

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However, this structural coding must not be confounded with the different coding systems necessary if the FICs are to exchange data. The IFN code (and the associated glossary codes and descriptions) has been already discussed in Chapter 4.1.. Other International Codes, for nutrients or geographical areas, for instance, will have to be (re) designed to ensure FIC data compatibility. All these codes will have to be maintained at International level, and quickly implemented at local level.

Other attributes that can be coded include methods of analysis, source laboratory, soil types etc. Most of these codes will have to be designed maintained locally, but the information behind these codes should be cIear enough so the related data can be exchanged.

INTERFACING THE FEED DATABASE WITH ENDUSERS

In former databases, little attention was paid to the users ease and comfort. Users had to know lists of codes and rummage through heavy users handbooks before making queries. Software technology, particularly for PCs and workstations, has made some progress since and todays users are very sensitive to the interface quality. Graphical User Interfaces (GUI), for instance, are becoming common to most operating systems. Not only they are more pleasant to work with, but most GUIbased softwares have the same basic logic (online hypertext help screens, mouse use, cut & paste etc., icons etc.), thus reducing training costs for new users and improving global efficiency of using sofwares.

It is clear now that, to be successful, a feed database must be equipped with intuitive, friendly interfaces (text or GUIbased). Interface development is still expensive (up to 80% of the total cost of a saleable software package), but new software technologies are lowering the costs.

It is difficult to give precise guidelines yet, for, most of all, interfaces are userdependent and should not be described beforehand. The only certitude about the feed database interface is that the inexperienced enduser should be able to query the database using his own, locally rele~ant, terminology. In any case, local names should be preferred when possible (but the interface could provide the standard, international descriptions with the local names so that users eventually use the standards). Some DBMS packages even include phonetic patternmatching routines that allow, for instance, the retrieval of the soybean products even if the user actually typed soya bean. A quick, alternative access by codes could also be provided for experienced database users.

MASTERING THE PROBLEMS: The provision of common European Feed Data Base Software, (to be) included in the Feed Data Management Package. Additional software may be developped for inclusion/interfacing with existing feed data bases, statistical purposes (e.g. FUMs) Etc.

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5. FOLLOW UP OF THE CONCERTED ACTION “ANIMAL FEED AND NUTRITION” AFTER 1997/1998.

It is supposed that at the end of the project period the main TARGET of this concerted action will be realised being the availability of a (well tested) European Feed Data Management Package describing:

(a) the set up of a national Feed Information Centre in its technical and organizational environment and

(b) how to identify feeds via the European Feed Naming Systemand containing software to:

(c) identify in a proper and uniform way feeds (EFNS) and (d) to handle (store, validate/select, process and distribute) a large range of

different kinds of feed data also enabling the easy exchange of these data between the different participants (being national FIC´s) and the coordinating secretariat.

Furthermore it may be assumed that at the end of the project period, participants and the national FIC´s have become eager to cooperate in a European Network of Feed Information Centres, enabling them to get in a cheaper way substantial more information of higher quality.

This because in the short term many farmers throughout the EU (Europe) will benefit from this network as this up to date feed information facilitates an efficient, sustainable animal husbandry. Besides, the animal feed and nutrition research in the different EU Member States will discover that such an information network is a very useful tool to identify the essential missing knowledge and white spots in animal nutrition and stimulates international cooperation and -funding to solve these.

WHICH VERY FUTURE COORDINATION

In the philosophy that the (execution of the) national collection, processing and distribution of feed data is an autonomous business of national FIC´s, one could state that also the international exchange between FIC´s should be done on an autonomous base and leave this totally up to the FIC´s. In such a model, international coordination should be restricted to the establishment and maintenance of the different protocols of identification and validation (in particular chemical analyses).However, to benefit throughout the EU (Europe) from the already available (public) knowledge and experience of other FIC´s (who are far ahead), it seems advisable to continue the coordination in a more active way by transforming the secretariat of the CA AFN in due time into a European Feed Information Centre (EFIC) and give it the following tasks:

(1) The assistance to Member States to establish a well functioning national Feed Information Centre, including the set up of an

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infrastructure guaranteeing the supply of sufficient adequate raw feed data;

(2) the maintenance and expansion of an European Feed Data Base in which all via FIC´s published and on line provided EU feed data are collected (processed) and (electronically) put on line throughout the EU (Europe);

(3) the continuation of the establishment/completion of protocols for a uniform and compatible feed identification, methods of chemical analyses, methods of obtaining bioavailibility data and the acceptance of these protocols by the FIC´s (if appropriate in cooperation with other international organizations as EU, CEN and ISO);

(4) the stimulation and assistance to participants/FIC´s for international (EU) animal feed and nutrition research projects.

THE EUROPEAN FEED INFORMATION CENTRE (EFIC)

To play above mentioned active coordinating role in EU feed information, EFIC should be placed centrally in the EU Network of Feed Information Centres. EFIC should be governed by a board, consisting of the heads of the FIC´s of the 15 EU Member States. EFIC should install a technical committee, consisting of representatives from the 15 EU FIC´s, discussing and deciding about technical matters concerning identification and (re)examination of (new) feeds and their implementation into the EU feed data base. To assure sufficient authority, it seems advisable to locate EFIC, in the first five years or so (1998-2003), on the same location as one of the most important and experienced, modern equipped and well functioning Member State Feed Information Centre. However, also other attractive options should not be excluded, such as an integration with other centrally located (future) EU services or agencies active in the field of animal nutrition.The managing and technical staff of EFIC should at least consist of an international coordinating director, a scientific co-worker and EFIC database manager.

FINANCING

EFIC should be financed on European level. As a majority of the 15 participating national FIC´s in ENFIC in the beginning even will not yet be established in their respective Member States themselves, it is impossible to ask from these national FIC´s a financial contribution for EFIC. On the contrary, EFIC as a successor of the CA AFN should continue to stimulate the establishment of FIC´s in the appropriate Member States! For this reason EFIC should be financed by the EU by means of a new Concerted Action called “European Network of Feed Information Centres”. This project should be formulated and submitted to the EU in the first part of 1997 by the current participants of the CA AFN in a new (F)AIR frameworkprogramme.

The possibilities of financing of EFIC after the year 2003 on a contributional or commercial way should be examined during the period 1998-2003.

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