Research in farm management technologies using the expert method

Transcription

1 Agronoy Research 4(3), 8 80, 06 Research in far anageent technologies using the expert ethod A. Laurs *, Z. Markovics, J. Priekulis and A. Aboltins Latvia University of Agriculture, Faculty of Engineering, Institute of Agriculture Machinery, J. Čakstes bulv. 5, LV-300 Jelgava, Latvia ²Riga Technical University, Faculty of Coputer Science and Inforation Technology, Institute of Coputer Control, Autoation and Coputer Engineering, Daugavgrīvas iela, LV-048 Rīga, Latvia * Correspondence: arins.laurs@proedia.lv Abstract. The task of the research was to state the ost popular peculiarities of far anageent technologies depending on the size of the herd in order to use the research results in calculations of greenhouse gas eissions. The research was perfored applying the expert ethods based on the far anageent technologies as they are closely related to the size of the herd and the kind of the obtained far anure. The expert ethod can be applied for research in far anageent technologies of different anial species and groups, but in the present article only ilk cow anageent technologies will be discussed as they produce the biggest aount of greenhouse gas eissions. The practice shows that on sall fars the cows are tied, on ediu fars either tied or loose, but on large fars only loose. On the fars where the cows are tied solid litter anure is obtained, but where the cows are handled loose liquid anure is obtained. Besides, on the fars with a sall herd the cows are pastured in suer and in this period anure spread in the pastures is produced. Stating the axial size of the herd that is pastured and the length of the pasture period as well as the arginal size at which the transition fro tied to loose handling takes place and additionally using the statistical data on the total nuber of cows in the country and the proportion of anials according to the size of the herd, it is possible to state fro which proportion of ilk cows solid litter is produced and fro which liquid anure. Therefore, the experts were given the task to nae the arginal values of the above entioned technology paraeters based on the value intervals stated in advance. Thereupon that the experts had to state only one chosen value, it was not possible to apply the traditional expert evaluation ethods and this ethod had to be adapted in accordance to the existing situation. The research results showed that in Latvia the critical size of the ilk cow herd at which the transition fro tied to loose handling takes place is 85 cows, the herds that are not larger than 90 cows are pastured but the pasture period lasts in average for 65 days. Key words: far anageent technologies, size of the herd, far anure anageent, the expert ethod. INTRODUCTION Ipleenting the European econoic zone progra National Cliate Politics project Developent of a Methodology for Calculating GHG Eissions in the Agricultural Sector and Modelling Tool for Data Analyses, Integrating Cliate 8

2 Change the task was set to state what kind of far anure in Latvia is produced fro the ost popular far anial and poultry species and their groups as well as to state the proportion of this anure. It was necessary for using the research results in calculations of greenhouse gas eissions caused by far anure anageent. Considering the data of the Guidelines for National Greenhouse Gas Inventories (006 IPCC) and statistics as well as suarising and analysing the present experience of far anageent specialists the ost popular species and groups of anials used in agriculture and poultry as well as the kinds of far anure produced by each of these groups were stated in Latvia. The obtained results are suarized in Table. Table. Kinds of anure produced by the ost popular far anials in Latvia Anial and poultry groups Kinds of anure Pasture Solid anure anure Liquid anure Deep bedding Poultry anure with litter Milk cows x x x Milk cow calves and x x young stock Beef cattle, their x x calves and young stock Pigs x x Sheep x x Goats x x Horses x x Laying hens x x x Broilers x Geese x x Ducks x x Turkeys x x Rabbits x Fur anials Deer x Note: technology of far anure used in the table is coordinated with 006 IPCC. Poultry and fur anial anure without litter In order to calculate the anure proportion obtained fro the corresponding far anials a new ethodology was developed (Priekulis et al., 05) based on using of the statistical data and the far anial zootechnical and technological paraeters. Soe of the zootechnical and technological paraeters necessary for the calculations are given in the scientific literature and the Regulations of the Cabinet of Ministers No But additionally it is necessary to state the arginal sizes of the herd of every group of anials at which the transition fro one kind of handling to another takes place and also the length of the anial pasture (airing) period. For this reason it was not possible to trace all fars (population) that are engaged in poultry and anial breeding in Latvia as in that case inforation on all the working force and financial resources would be necessary. Also, it was not possible to for representative and large enough saple fars as the fars engaged in poultry and anial breeding are unevenly distributed along the whole territory of Latvia. Nevertheless, this proble can be solved applying x 8

3 the expert observation ethod and orientating on the research in anial and poultry breeding technologies depending on the size of the herd. In order to show the possibilities of application of the expert observation ethod clearly as an exaple only one of the far anial groups entioned in Table will be discussed, i.e., ilk cows as they produce the largest aount of the greenhouse gas eissions (National Inventory Subissions, 04). MATERIALS AND METHODS According to the scientific literature (Priekulis, 000) and the practice it can be concluded that in Latvia on sall fars (up to 50 ilk cows) the anials are handled tied, on ediu fars (50 00 cows) tied or loose, but on large fars (ore than 00 cows) only loose. On fars with tied handling litter is used and solid anure is produced, but on loose handling fars litter is not used and liquid anure is produced. Besides, in suer cows fro sall and ediu fars are usually pastured and therefore a part of anure is not collected as it stays in the pastures. In turn, calves and young stock are usually handled loose either in individual or group enclosures (depending on the age). There litter is used that is periodically stocked up and the produced solid anure is taken to the anure storage if necessary. If ilk cows are pastured, the young stock is pastured also. Therefore, it can be concluded that the obtained kind of anure is related to the kind of anial handling and the size of the herd on the far. One of the ais of the present research was to state the arginal value of the size of the herd at which the transition fro one kind of handling to another takes place. Besides, the question about the axial size of the herd that is pastured and the length of pasturing has also to be explained. Therefore, the experts were asked the following questions. What is the size of the herd (arginal value) at which the transition fro tied to loose handling of cows takes place? What is the axial size of the cow herd at which the cows are pastured (if there are pastures)? What is the average length of the pasturing period (nuber of days)? The group of experts necessary for the research was copleted according to the voluntary ethod including in it advisers fro the Latvian Rural Advisory and Training Center, Latvian Milk Producer Association specialists as well as experienced anial breeding specialists and far anagers. The total nuber of experts was 8 people. It corresponds to the recoendations given in the scientific literature (Markovics, 009) where 0 0 experts are recoended. In order to get the individual opinion of the experts special enquiries or telephone enquiries were used. The task was to show the value interval in which, according to the opinion of the experts, the authentic value of the object lies. Before the basic enquiry the pilot enquiry was perfored. Its ai was to ake the enquiry questions and the intervals of the researched values ore precise and to state the understanding of the experts about the stated task. 83

4 Processing of the data obtained in the experient was done in the following sequence: suarising of the ranging of the obtained results; selection of the data; deterination of the extent of the expert agreeent; obtaining of quantitative values fro the ranged rows. The enquiry results were ranged and suarised in a table the for of which is given in Table. Table. For of enquiry result ranging Experts Objects (n) () x x x i x n r r r i r n j r ji r r r i r n R i Note: in the table with n the objects or their values are arked, with experts, with r object ranging and with R the resulting value of every object. Still, it should be entioned that all present expert evaluation ethods are eant for the tasks to evaluate any objects, respectively, to state their ranged row. Probles occur if the tea of experts has to evaluate only one value or take one decision as it is in the present research. In such case the research ethods need to be adapted which in this case anifests as follows. Every expert arks only the square of the object which he/she prefers. After that the ranged row is fored using the following approach. If the expert chooses gradation fro one or the other end of the given row, this gradation is given the first range, the next gradation will be the second range, still the next the third range etc If the expert chooses soe gradation fro the iddle of the given row, the ranging can be as follows: the chosen gradation gets the range ; the proxial gradations (to the left and right fro the chosen) have equal range, but theoretically they occupy the nd and the 3rd range in the result of what every reduced range is calculated + 3 r red = =.5 ; further gradations to the left or right occupy the fourth and fifth range but the reduced range between the both is 3.5 etc. If the expert chooses gradation fro the iddle of the row, the version is possible that the nearest to the chosen gradation will get the ranges ; 3 etc. only in one direction, 84

5 for instance, to the right fro the first range. Besides, gradations to the left will be ranged in the furthest end of the ranged row. With such technique of adaptation all expert ranged rows for every square of the table can be obtained and it is possible to process the results atheatically by any of the traditional ethods described in literature (Voronin, 974; Hand et al, 00; Dunha, 003; Tan & Steinbach, 006; Markovics, 009). After ranging of the results the data were selected. In practice the situations are possible when in the data array there is an extraneous nuber present that does not fit in the total row of nubers. Therefore, the so called data selection is necessary that is done in all coluns by turn. The expert ethods have a restriction that the degree of the expert agreeent and the inforation obtained in the enquiry can be used in further calculations only in case if the degree of agreeent is bigger than the threshold value. Therefore, big choices of techniques have been developed how to evaluate the degree of expert agreeent, but the ethod of Kendall (Markovics, 009) that is using the concordance coefficient has becoe ost popular. The concordance coefficient is calculated according to forula () or (). If the expert evaluation ranges do not agree, forula () should be used. n ì åíå r ji - i= î j= W = 85 ( n+ ) 3 ( n - n) ü ý þ, () where nuber of experts; n nuber of objects; r object range; i object ordinal nuber; j expert ordinal nuber. If the expert evaluation ranges coincide, the concordance coefficient is calculated according to forula (). n ì åíå r i= îj= W = ji - ( n+ ) 3 ( n - n) - åt j In forula () the value Tj is calculated according to forula (3) T j = å tj 3 ( t - t ) j j j ü ý þ (), (3) where t j nuber of repeating ranges in j-th expert ranging. The range of the concordance coefficient is fro 0 to. If W = 0, there is no agreeent aong the ranging, if W =, there is coplete agreeent. To prove the statistic validity of the obtained result, the statistic hypothesis testing ethod with the Pearson coefficient χ² is applied. It is calculated according to forula (4): χ²apr = (n-)w (4) Fro χ² tables χ² tab is found according to the freedo degree ν = n -.

6 If χ² tab < χ² apr, then the hypothesis on expert evaluation agreeent with the concordance coefficient is assued with probability at least It should be entioned that by the Pearson criterion only the statistic validity of the concordance coefficient is tested. But this testing does not give inforation on whether the value of the concordance coefficient is high enough to judge about the agreeent aong the experts. Therefore, the question is open what value of the coefficient W can be considered to be sufficient. It cannot be stated theoretically, but in practice it is assued that the concordance coefficient is big enough if W > 0.5 (Markovics, 009). If the degree of agreeent is larger than the threshold value, it is possible to obtain the quantitative values fro the ranged rows. It is ost easy to calculate the average arithetic values for every colun, but in case of a sall nuber of data (such are all the data given by the experts) the average arithetic value can give a big istake. Therefore, a ethod, known in literature as Voronin ethod, is applied (Voronin, 974). It is based on calculation of iterative atheatical expectation for sall nuber cases. Matheatical expectation is calculated according to forula (5). é ù ê ( y ) ( ) ú ik- - y ji - å y ê ú ji exp - j= ê ú ê å( yik- - y ji) ú ë j= û y ik = (5) é ù ê ( y - ) ( - ) ú ik- y ji å expê- j= ê ê å ( y - ) ú úú ik- y ji ë j= û where y ik atheatical expectation in k-th step; y ik- atheatical expectation in the previous k- step; in the first step instead of y ik- the average arithetic is put; y ji i-th object evaluation according to j-th expert opinion; nuber of experts. To perfor calculations using forula (5) special coputer software MatLab was developed in the prograing edia. Considering that in the present research the experts have not to choose quantitative values but the intervals of these values, the task has to be adapted to the foral ethod. The values y ij are obtained taking the average values fro the intervals that every expert has evaluated with the first range. In the result a row of nubers is fored that is obtained replacing the first ranges in the table by the average values of the corresponding interval. Therefore, only one nuber is obtained atheatical expectation of the searched arginal value that can be afterwards used for explanation of the researched probles. RESULTS AND DISCUSSION Ranging of the expert answers and the results of the expert agreeent degree calculations related to the transition fro tied handling of cows to loose handling are suarised in Table 3. 86

7 Table 3. Ranging of the expert answers and the results of the expert agreeent degree calculations researching the question about the size of the herd at which the transition fro tied handling of cows to loose handling takes place Expert Average size of herd (nuber of cows) serial No W 0.58 Concordance coefficient W statistic validity >0.99 Table 3 shows that in this case the concordance coefficient W = 0.58, i.e., its value is higher than the sufficient value (W = 0.5) and also its statistic validity is high enough. So, the expert agreeent degree is satisfactory and the value of the searched paraeter can be calculated. The calculation results are shown in Table 4. Table 4. Deterination of the herd arginal size at which the transition fro tied handling of cows to loose handling takes place Expert serial No Herd size interval, nuber of cows Herd size critical size, nuber of cows 85 Consequently, fro Table 4 it can be concluded that the critical size of the herd at which the transition fro tied handling of cows to loose handling takes place is 85 cows. In turn, Table 5 shows the research results on the axial size of the herd which is pastured Table 5 shows that also in this case the degree of expert agreeent is satisfactory (W > 0.5), so the searched value can be calculated. In turn, the calculation results show that the axial size of the herd that is pastured is 90 cows. Table 6 suarises the expert enquiry results on the length of the pasture period of cows. 87

8 Table 5. Ranging of the expert answers, the results of the expert agreeent degree and atheatical expectation calculations deterining the axial size of the herd that is pastured Expert Size of herd, nuber of cows serial No. < W 0.76 Concordance coefficient >0.99 W statistic validity Maxial size of herd, 90 nuber of cows Table 6. Ranging of the expert answers, the results of the expert agreeent degree and atheatical expectation calculations researching in the length of the cow pasture period Expert Length of the pasture period, nuber of days serial No W 0.78 Concordance coefficient >0.99 W statistic validity Length of the pasture 65 period, nuber of days 88

9 Also for the answers suarised in Table 6 the degree of expert agreeent is satisfactory, but the calculation results show that the average length of the pasture period is 65 days. Applying the above described expert ethod siilar research was perfored also for the other far anial groups included in Table stating the length of the pasture (airing) period as well as perforing research in the critical sizes of pig and laying hen herds at which transition fro producing of one kind of anure to another takes place (for pigs fro solid anure to liquid anure, for laying hens fro solid anure to anure without litter). These investigations show that application of the expert ethod opens wide possibilities for research in anial breeding technologies in the result of which new quantitative values are to be obtained. In the present case the change of far anial handling depending on the size of the herd was taken as the basic principle of the research. But this ethod can be applied also in the research of another character where it is not possible to trace all fars (population) or for representative and quantitatively large enough saple groups. Nevertheless, application of the expert ethod in the research in far anageent systes can cause non-standard situations that are not described in scientific literature. For instance, in the present research the proble of deterination of the expert agreeent degree. It is based on coparison of ranged rows, but in the present research the experts chose only one value. Therefore, it was necessary to foralize the obtained results in accordance to the calculation ethods and to adapt the initial data to calculate the atheatical expectation applying the Voronin ethod. CONCLUSIONS In order to state the peculiarities of far anial handling technologies for the ost popular anial species and groups in Latvia it is not possible to trace all fars that are engaged in poultry or anial breeding. Also, it is not possible to for representative saple fars as the fars of the corresponding anials are unevenly scattered along the whole territory of Latvia. Still, this proble can be solved applying the expert evaluation ethod and basing on the changes of far anial and poultry handling technologies depending on the size of the herd. Applying the expert evaluation ethod it has been stated that the size of the ilk cow herd at which the transition fro tied handling to loose handling takes place as well as fro producing of solid anure to liquid anure is 85 cows. Besides, the anials are pastured and anure left in pastures is obtained if the size of the herd does not exceed 90 cows, but the average length of the pasturing period is 65 days. As the experts participating in the research had to choose only one interval of values that best suits the given question, it was not possible to apply the traditional expert evaluation ethods. Therefore, it was necessary to adapt the ranging deterining the expert agreeent degree as well as foralising the nuber rows calculating the atheatical expectations. 89

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