IDEA (Portugal) - Efficiency of the Electronic Identification on Livestock Animals

Transcription

1 IDEA (Portugal) - Efficiency of the Electronic Identification on Livestock Animals C. Roquete, P. Fonseca, P. Pinheiro, P. Carreira, T. Prata, E. Barbosa Universidade de Évora, Departamento de Zootecnia,Núcleo da Mitra, Valverde, 7000 Évora, Portugal Abstract The IDEA project in Portugal utilized the ceramic reticular bolus equipped with a 32 mm ready only transponder, known as the HDX system, satisfying the ISO specifications for all animal species, breeds and ages ( ewes, cows and 5000 goats). The selected farms correspond to holdings with extensive production systems at the Alentejo region. The failed readings or re-tagged animals were 0.17%, 0.15% e 1.00% for cattle, sheep and goats respectively during the three years of project and less then those figures during last four year after the end of IDEA. Key words: Electronic Identification, livestock animals, traceability 1 Introduction and objectives The livestock sector of the European Union (EU) have shown that the traditional identification system with ear-tags used for sanitary purpose and fraud control are not efficient and reliable enough to warrant a correct traceability and veterinary monitoring of livestock species. The control of individual animals and their movements is a critical issue to resolve those problems and essential component for future of EU livestock. In order to improve individual animal control, the proposed solution is the unique identification of each animal during its entire life, applying an electronic identifier. A passive radio frequency based transponder allows an automatic reading of the animal s identity and provides a reliable and useful method for livestock recording and control. Two preliminary investigations had been launched by EU, the so called FEOGA project (Caja G., et al, 1994), to evaluate if current technologies were able to support the implementation of an electronic identification system in livestock species and the Project AIR 2304 (Caja G., et al, 1998), to complete and validate the results obtained in FEOGA project and design a protocol for a large-scale experiment to test not only technology for electronic identification, but also a global system. With the Commission Decision 98/562 begin the IDEA project with the main objectives to study the feasibility and the evaluation of the performance of an electronic identification system in ruminants (cattle, buffalo, sheep and goats) and the necessary organizational structure needed for any eventual future implementation of such a system on the EU (Ribó O., et al, 1999). The objective of the present paper is to show the efficiency of the electronic identification of farm animals, the tracking control and the analysis of factors that are directly involved and contributing for efficiency during the experimental phase of the Portuguese partner of the IDEA project. 966

2 2 Methodology 2.1 Organisms, farms and animals The farms proposed to participate in the IDEA project in Portugal (Alentejo) were selected in each one of the participating organisms (ACBRA, Alentejana Cattle Breeding Association; ACBM, Mertolenga Cattle Breeding Association; ACOS, South Sheep Cooperatives Association; APCRS, Serpentina Goats Breeding Association; and IDEAGT, Technical Cabinet of IDEA, controlling the Companhia das Lezirias herds and flock), taking into consideration the diversity of types of exploration, using as main criteria, the availability and the willingness to participate and collaborate in a way conducive to the fulfilment of the objectives of the IDEA project. Also the advantages for the breeder and the Association regarding improvement in the identification of the animals, as well as the size of the herd, the latter being the most representative of the conditions of the breeding of the animals under study, were taken into account. Another selection criterion was related with possibility to know the movement of the animals, among the farms in the region, as well as outside of them, in order to guarantee complete control over the productive process during the three years of the project. The next tables (1,2) shows us the number of production units and production systems (based mainly on extensive management, with its proper difficulties and increased by the nature of the animals, mainly local breeds, usually not very quit ones), and the numbers and type of livestock animals. 2.2 Material and equipment The electronic identification mechanism selected for all the animal species, breeds and ages covered by the IDEA project in Portugal is the ceramic reticular bolus. The reticular bolus will be equipped with a 32 mm read only transponder, known as the HDX system, satisfying ISO specifications. The reticular bolus will be applied using an application gun, according to the IDEA project application protocol (Ribó, O., et al, 1999). The selected readers, data processing material, data management and collection are as follows: - Hand-held intelligent portable reader (to be used by the identifier application teams); - Hand-held simple portable reader (to be used by the breeders); - Portable reading module, connected to a notebook (to be used by the control teams in the race ways and slaughterhouses); - ebook computer with modem and portable printer; - Desktop computer with modem and printer; - Software for static readings with the hand-held intelligent reader; - Software for dynamic reading on the farms; - Software for reading and control in the slaughterhouses; - Data base management software; - Commercial modem communications software; 2.3 Experimental Scheme The animals were tagged, read and recorded for several data. After the application of reticular bolus they were controlled by readings against a previous list on next day, on seven day, one month later, every seven months and when they were moved and arrive to another farm or slaughterhouse, when they died in field and at the end three times at slaughterhouse (at arrival, before died and at dirty area). 3 Results and Discussion 3.1 ings The table 3 is the image of the dimension of experimental work to realise the advantage of an electronic tag (bolo), to permit an easy control of animals and the respective animal stock, having a previous list as a base document. 967

3 It shows, by organisms (also specie) and reading type, the number of present animal (P) according the previous list; the number of animals read but not in the list (N) -a very important information for herds and flocks in extensive systems, like we have in Alentejo, our experimental IDEA region-; and the animals that were not read, but expected (F) besides the importance before described, have another one for the official services whom need control the primes-animals and for sanitary reasons (animals problem). Besides the enormous dimension of the enforced work and the increased of dangers for animals, and goodness of producers to handle the animals to the facilities: at tagging day, next day tagging and one week after; and also the following the animals out side the IDEA farms - people that have anything to do about IDEA project -; experimental work given us the possibility to argue about the critical phases : at application time and the next days surround; and the control of animals that were moved to places out of IDEA. A simple description how the reading systems were used and the perspectives of the tremendous number of hours that the equipment for controlling was working, at the hard conditions of extensive systems, and often, with not collaborating animals is at table Movement performance The other important point of the experimental IDEA project is, we are sure, the control of the movements. Half of total movements are among holdings and the other half to slaughterhouses and auction parks. If we put face to face the numbers of controlled departures and arrivals (named limbo ), for each organism, always we find a percentage of tagged animals (only a small number, 0.42% till 2.92% for organism or 0.63% over total departures) that we lost the way or, we know were they went but was not possible reading them at arrival; and sometimes happened death during the trip and the carcass went take off by the transporters. 3.3 Recovery The IDEA project has it own climax if a correct tagged animal, controlled during its life has an efficient recovery of its bolo (in an up to date language a question of positive trace ability). The table 6 give us an idea of how many bolus were recovered by specie and place type and, by side, the frequency of recoveries at IDEA slaughterhouses and out side the IDEA ones (15 from South to North Portugal Algarve to Minho. These recoveries represented km to get 1956 bolus). 3.4 Efficiency Tagging - Work time spent by specie, age and restraining condition One of the important conclusions is related with the needed time to tagging a cow, a ewe or a goat The table 7 and 8 are clear about the short time to tagging the small ruminants and for other side the applicators have to be conscience about the extra more time for tagging some adult cattle (at the end of Spring they have more body condition, that means more power; or some animals of local breeds are more nervous cause extensive system or its own nature; or the facilities have not the wished characteristics). Our field experiments tell us that restraining corridors are essential for tagging cattle after weaning. What concern small ruminants the tagging action are less demanded for facilities. Sometimes a little human help is enough. 968

4 3.4.2 ing fails by organism and reading type In terms of conceptualisation ours databases (at organism level - local database or/and Évora University level central database) have a problem, that in begin was unimaginable but after readings the controls of each seven-month became problematic, because named every seven-month control with same code (05). This situation give to the less attention reader a sensation that at reading type each seven month happen an explosion of reading failures. It is not the reality, because those numbers represent a total of several controlling and not one seven-month control. At next point (table 9), we will show various descriptive statistics that will give the interval between tagging and date where the failures ( not read and lost ) were detected ing failures and the elapsed time since tagging The restraining condition for tagging animals should be able to influence the frequency of failures, what we try explain with this table 10. In begin the distribution of failures numbers are in according with the proportional numbers of tagging. The only question seems to us, is related with restraining corridor, as reason for a large part of failures in sheep, whom is more related with breeding purpose and race of ewes (dairy Assaf and Awasi crossed sheep) than with the type of facilities. How we can see (table 11), it was very important the earliest controls (day after, seven days after and one month after tagging), because the biggest part of failures happened during this period. It is possible to see the distribution histogram, where INTV means the elapsed time between tagging and failures in days ing efficiency by organism and reading type The table 12 it is a pure emotion! There is not discussion, once the failures percentage over successful reads, never get values above 0.03 % for every reading type, although the previous explanation about the less clear meaning of every seven month reading type Re-tagging A linear thinking by specie show us (compared with overall percentage) a quasi problem with the goats, but as you will have opportunity to see at next point, the real problem is concerned with several retagging at same animal, the less number of tagged goats and not a question of breeding purpose. The results of table 13, the 0.17% of re-tagging cattle represent animals that did not give reading or lost bolus, what we call inside the re-tagged animals a normal case. Considering the table 14, for small ruminants with 21.53% animals problem (more then one re -tagging per animal) the overall percentage decreased for 0.10% in sheep and to 0.72% in goats. This means 78.47% normal and 21.53% problematic animals, what perhaps insinuate a type of allergy to the ceramic bolus Elapsed time from tagging to recovery by specie and place type It is important to knowing the elapsed time since the animal was tagged with a reticular bolo until recovery infield or slaughterhouse, so the table 15 gives descriptive statistics of the distribution of the elapsed times in month by specie and place type. The range is very similar for all species, from less then one month until three years. The minimum of 3 month to goats is related with the seasonality of marketing and no other reason. 969

5 3.4.7 Recovery efficiency The story or efficiency of the recovery bolus is given in this table 16, by species and place type and show us similar percentages of recovered bolus infield for sheep and goats (around 85%) and biggest efficiency for cattle (97%) as is understanding. What in begin seams to us a more dramatic question (related with out of IDEA recovery), was quit satisfactory resolved, with a strong work of SOS IDEAGT team, by that, only 2.4% of bolus were not recovered. With small ruminants like was expected there was a highest percentage of not recovered bolus in field conditions. The reasons are related with the large areas of the farms, the wild dogs and in singular situations the wild boar and vulture. The reasons for bolus without readable ability are very specific: one was found at slaughterhouse with a wire in the silicone central hole; five were found inside the recovered whirl; three belonging at re-tagged animals; and two with intermittent reading, not read at recovery but with reading later. One bolo was found in field, broken but giving reading. Two bolus were found at slaughterhouses inside the recovered whirl, broken but giving reading. One recovered at slaughterhouse was broken during the stockade (ceramic and glass) but following give reading Status of tagged animals The resume table 17 is a portrait of our central database data. The numbers are giving us the status of tagged animals by species, with 74.31% of alive cattle, 68.52% of alive sheep and 64.02% for goats yet at IDEA farms. Only 1.35% on average, for three species, is out side IDEA farms. There is 5.88% on average that we lost the situation, but at any moment can appear in one of ours reading controls. 4 Final Considerations and Perspectives There is some evidence, looking for the experimental data, that the electronic identification with reticular bolus is a good change to following an animal during a large part of its life (traceability), this means: First - the tagging process is easy, although with extra work for cattle; Second - with the experimental equipment is proven there is a good efficiency for the connection between animals and the database; Third - there are only a few bolus losses, which represents about 0.03% of total tagging animals, with big incidence in only a few number of animals; Fourth - the human mistakes (double tagging) or/and the less operative facilities (restraining corridors getting animals to the open fields) or/and the magnet inside rumen (less reading efficiency) do not were a real problem, because the tendency for reading failures was not explicable. Sometimes the efficiency was 100% or sometimes near the 0%. It is always a question of patience and professionalism; Fifth - is easier to recovery the bolus at slaughterhouses, but there is some problems with recovery infield, mainly with sheep and goats. Face to the results given by the IDEA project (Fonseca, D.P., et al, 2001), it is our opinion that was demonstrate definitively the applicability at large scale of the use of electronic identification, based on reticular bolus. Thinking at the generalization of this system to the near future, there is an evidence of the needs to be insured an UE co-ordination, at JRC-Ispra, to guarantee a unique pool decisions, to insure the plenty operationally and coherency of the electronic identification besides the specificity of each country profile. At the perspective of a period pos-idea, which could gave the possibility to developed the right conditions for a future implementation of the electronic identification inside UE, we must emphasize our actions to guarantee the global compatibility of the system, mainly what it concern to the Database (a processing data system, with automatism on feeding the local or central databases and a correspondent software structure to filter the data from different origins) supported over an efficient data dictionary common to the European space. 970

6 6 References Caja G., Fonseca P.D., Luini M., Electronic Identification of farm animals using implantable transponders. Final Report, FEOGA Project. European Commission, FEOGA (VI-G4), Brussels, 547 pp Caja G., Ribó O., Nehring R., Conill C., Peris S., Solanes D., Montardit J. L., Milán M. J., Farriol B., Vilaseca J. F., Alvarez J. M., Diez A., Aguilar O., Coupling active and passive telemetric data collection for monitoring, control and management of animal production at farm and sectorial level. Final Report. Contract AIR3 PL , Partner P10. Universitat Autònoma de Barcelona, Spain, 135 pp. Ribó O., Poucet A., Meloni U., Korn C., Cuypers M., IDEA Project Guide Procedures (v. 5.3). Sa-Ve-Tech Unit, ISIS Institute, JRC, Ispra, Technical note Nº I , September, 79 pp. Fonseca, P.D., Roquete C., Pinheiro P., Barbosa E., Carreira P., Prata T., Garcia M., Portugal-IDEA Project. (v. 2..2). Final Report. Universidade de Évora, Portugal, 90 pp. Anexos Table 1- Number of production units by production system and organism Production Unit by Production System Organism Specie Semi Semi Total Extensive Intensive Extensive Intensive ACBRA Cattle ACBM Cattle ACOS Sheep APCRS Goats IDEAGT Cattle Sheep Table 2 - Animals to be identified, really identified and execution level by specie and organism Animals to be Identified Identified Execution level % Cows ACBM Steer Cows CATTLE ACBRA Steer IDEAGT Cows SHEEP ACOS IDEAGT GOAT APCRS Total ing Type Table 3 Number of readings performed by organism and reading type Organism ACBRA ACBM ACOS APCRS IDEAGT Specie Cattle Cattle Sheep Goats Cattle Sheep After One Day After One Week After One Month P F N P F N P F N P F Every seven Months N

7 Out of P IDEA F Time N P-Present; F-ings failed; N- expected ing System Table 4 Number of readings performed by organism and reading system Organism ACBRA ACBM ACOS APCRS IDEAGT Specie Cattle Cattle Sheep Goats Cattle Sheep P F Dynamic N Subtotal P Static F N Subtotal P-Present; F-ings failed; N- expected Organism Specie Table 5 - Number of animals moved by organism, specie and place type Movements To Place Type Holding Slaughterhouse Market Others Total "Limbo" Arrival % of Total ACBRA Cattle 4,55% ,92% ACBM Cattle ,08% ,07% ACOS Sheep ,29% ,42% APCRS Goats ,13% ,71% IDEAGT Cattle ,80% ,10% 67 Sheep ,15% ,98% 38,51% 11,48% 0,03% 100,00% ,63% Table 6 - Number of bolus recovered by specie and place type Place Type Specie Slaughterhouse Infield IDEA (Holding) Out of IDEA Beja Sousel Total Cattle Sheep Goats

8 Tagging Spent Time By Age Table 7 - Number of animals by tagging spent time, age and specie Specie Cattle Sheep Goats <3min Less 1 year 3-5 min >5min <3min Years 3-5 min >5min <3min years 3-5 min >5min <3min More 7 years 3-5 min. 1 1 >5min. <3min More 10 years 3-5 min >5min Tagging Spent Time By Restraining Condition Table 8 - Number of tagged animals and spent time by specie and restraining condition Specie Cattle Sheep Goats <3min Loose Housing 3-5 min >5min <3min Handling Pen 3-5 min. >5min. <3min Restraining Corridor 3-5 min >5min <3min Manual Restraining 3-5 min. >5min. 3 3 <3min Milking Parlour 3-5 min. >5min ing Failed By ing Type Table 9 - Number of reading failed by organism, specie and reading type Organism ACBRA ACBM ACOS APCRS IDEAGT Specie Cattle Cattle Sheep Goats Cattle Sheep After One Day After One Week Lost ers Functioning Animal Present Lost ers Functioning Animal Present

9 After One Month Every seven Months Out of IDEA Time Lost ers Functioning Animal Present Lost ers Functioning Animal Present Lost 2 2 ers Functioning 4 4 Animal Present Table 10 - Number of failures by specie and restraining conditions Restraining Conditions Specie Loose Housing Handling Pen Restraining Manual Corridor Restraining Lost Lost Lost Lost Cattle Sheep Goats Table 11 - Elapsed time between tagging and failures in cattle, sheep and goats INTV Cumulative Cumulative Graph of (days) Count Count Percent Percent Percent Cattle Up To To To To To To To To

10 Sheep Up To To To To To To Goats Up To To To To To To Table 12 - Number and efficiency of readings by organism, specie, variable and reading type ing Type Organism Specie Variable Every Out of After One After One After One Seven IDEA Day Week Month Months Time ings ACBRA Cattle read (P) Failures % Failures 0,10% 0,06% 0,04% 0,02% 0,00% 0,05% ability 99,90% 99,94% 99,96% 99,98% 100,00% 99,95% ings ACBM Cattle read (P) Failures % Failures 0,04% 0,06% 0,04% 0,15% 0,03% 0,09% ability 99,96% 99,94% 99,96% 99,85% 99,97% 99,91% ings ACOS Sheep read (P) Failures % Failures 0,01% 0,02% 0,02% 0,02% 0,00% 0,02% ability 99,99% 99,98% 99,98% 99,98% 100,00% 99,98% 975

11 APCRS Goats Cattle IDEAGT Sheep ings read (P) Failures % Failures 0,06% 0,10% 0,23% 0,14% 0,11% 0,13% ability 99,94% 99,90% 99,77% 99,86% 99,89% 99,87% ings read (P) Failures % Failures 0,25% 0,07% 0,07% 0,08% 0,00% 0,10% ability 99,75% 99,93% 99,93% 99,92% 100,00% 99,90% ings read (P) Failures 0 % Failures 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% ability 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% ings read (P) Failures % Failures 0,02% 0,03% 0,03% 0,03% 0,01% 0,03% ability 99,98% 99,97% 99,97% 99,97% 99,99% 99,97% Table 13 - Number and percentage of re-tagging by specie and breeding purpose Breeding Purpose Double Fattening Meat Dairy Breeding Purpose Specie Cattle % of Tagged Animals 31 0,17% 200 0,15% 63 1,00% 294 0,19% Number of Re-tagging Times in the Same Animal Table 14 - Number of re-tagging animals by specie, re-tagging times in the same animal and type Specie Cattle Sheep Goats Animal type N % Normal ,47% % Of Tagged Animals 0,17% 0,10% 0,72% 0,13% Problematic 45 21,53% 976

12 Recovery With Dead Date Infield (Holding) Slaughterhouse Table 15 - Statistic distribution of elapse time in month from tagging to recovery by breed and place type Specie Cattle Sheep Goats n Mean 20,76 ± 9,82 19,28 ± 9,32 19,54 ± 9,08 Min 0,83 0,20 3,10 Range Max 35,60 36,43 36,40 Median ,53 19,70 10% 7,07 7,30 6,28 25% 10,03 10,75 10,99 Quartile 50% 23,52 19,53 19,70 75% 29,42 26,40 28,93 90% 32,27 32,03 33,60 n Mean 13,12 ± 8,99 14,21 ± 8,76 17,15 ± 10,62 Range Min 0,03 0,03 0,63 Max 35,27 35,01 33,53 Median 11,37 13,13 17,70 10% 2,53 4,13 4,63 25% 5,57 6,77 6,63 Quartile 50% 11,37 13,13 17,70 75% 20,02 20,03 28,17 90% 26,20 28,00 32,13 Specie Table 16 - Number and percentage of dead animals by specie, place type and recovery result Place Type Infield Slaughterhouse Recovered Recovered IDEA Recovered Recovered Out of IDEA Recovered Recovered Cattle 96,77% 0,00% 3,23% 99,12% 0,15% 0,73% 90,58% 0,30% 9,12% 10,51% Sheep 84,77% 0,01% 15,23% 99,83% 0,02% 0,16% 99,42% 0,07% 0,51% 85,02% Goats 85,59% 0,00% 14,41% 99,82% 0,18% 0,00% 95,90% 0,34% 3,75% 4,47% ,34% 0,01% 14,65% 99,71% 0,04% 0,25% 97,46% 0,15% 2,40% 100,00% Specie Cattle Sheep Goats Table 17 - Number and percentage of tagged animals by specie and animal status Animal Status Alive Dead Lost Stolen IDEA Out IDEA Infield Slaughtered ,31% 4,44% 0,25% 0,00% 4,64% 16,36% 100,00% 11,82% ,52% 0,82% 6,66% 0,15% 13,22% 10,64% 100,00% 84,20% ,02% 3,38% 6,01% 0,00% 13,28% 13,31% 100,00% 3,97% ,02% 1,35% 5,88% 0,12% 12,21% 11,42% 100,00% 100,00% 977