Teraviljakülviku valimine - alused ja mudel
Laen...
Kuupäev
2013
Kättesaadav alates
ainult raamatukogus, only in library
Autorid
Sepp, Ergo
Ajakirja pealkiri
Ajakirja ISSN
Köite pealkiri
Kirjastaja
Abstrakt
Käesoleva töö eesmärgiks oli selgitada, millised on teraviljakülviku valikut mõjutavad tegurid, milliste seoste abil neid tegureid arvestada ja koostada külviku valiku mudel. Eesmärgi saavutamiseks püstitati rida ülesandeid. Kokkuvõte käesoleva töö tulemustest on järgmine.
1. Koostati ülevaade teravilja külviviisidest - reaskülvi, hajuskülvi, lintkülvi, lägakülvi ning otsekülvi kohta.
2. Koostati ülevaade külvitehnoloogiatest – operatsioonide järjekord erinevate külvikutüüpide korral, külvikute liikumisviisid põllul ja külvikute transport põllule.
3. Koostati ülevaade teraviljakülvikutest, nende liigitusest, osadest ja lisaseadmetest.
4. Küsitleti külvikumüüjaid ja hangiti internetist andmeid, et koostada ülevaade Eestis müüdavatest uutest külvikutest. Selle tulemusel ilmnes, et Eestis pakuvad teadaolevalt 10 külvikumüüjat vähemalt 135-t erinevate omadustega uut külvikut. Kuigi küsitlusel võeti eesmärgiks katta kõiki Eestis tegutsevaid müüjaid, võis mõni siiski uuringust välja jääda. Küsitlusel saadi andmed muuhulgas külvikute tüübi haardelaiuse, annusti tüübi, külvisekasti mahu, seemendite tüübi, võimsustarbe, transpordilaiuse ja hinna kohta. Hinnad saadi 62 külvikumudeli kohta.
5. Koostati ülevaade agronõuetest teravilja külvile ja nõuetest teraviljakülvikutele.
6. Uuriti, milliseid külvikute valikumeetodeid on seni Eestis ja mujal maailmas välja töötatud. Leitud käsitlused on üldised ülevaated erinevatest külvikute juures kasutatavatest tehnilistest lahendustest ja mõningal määral kirjeldavad nende lahenduste eeliseid ja puudusi. Samas ei õnnestunud käesoleva töö autoril leida valikumudelit või algoritmi, mis oleks külvikuostjal abiks oma ettevõttele sobivaima külviku valimisel.
7. Küsitleti ka Eesti külvikute müüjaid ja põllumehi, millest nad lähtuvad ettevõttele sobivaima külviku valimisel. Teraviljakasvatajad valivad külvikut külvipinna, olemasolevate mullaharimisriistade, tootlikkuse ja hinna ning kvaliteedi suhte järgi. Masinamüüjad soovitavad ostjale külvikut külvipinna, tootlikkuse ja maaharimisviisi ja traktori võimsuse järgi. Üldiselt toimub külvikute valimine kogemuste põhjal ilma selget valikumudelit kasutamata.
8. Koostati ülevaade teguritest, mis mõjutavad külviku valikut ja nende tegurite vahelistest seostest. Tegurid rühmitati valdkondade kaupa agronoomilisteks, ettevõttest tulenevateks, majanduslikeks ja logistilisteks.
9. Koostati valikumudel, mis koosneb kahest osast. Esimeses osas teatud küsimuste ja vastuste süsteemi alusel kitsendatakse külvikute valikut – see tähendab üldisest külvikute loendist välistatakse ettevõttele ebasobivad või ebavajalikud külvikud. Mudeli teises osas arvutatakse iga valikusse jäänud külviku jaoks kulude summa. Kulude summa koosneb külvitöö masinakuludest ja külvi ajastamatusest tingitud tulukaost. Ettevõttele on sobivaim külvik, mille kulude summa on väikseim.
10. Valikumudeli kitsendava osa põhjal koostati vooskeem ja arvutava osa põhjal koostati MS Excelis kalkulaator kulude summa arvutamiseks. Kalkulaator võimaldab kiirest leida kulud erinevatele külvikutele erinevate tootmistingimuste korral.
11. Valikumudeli abil selgitati kolme põllumajandusettevõtete andmete põhjal, kas milliste parameetritega külvik on ettevõttele sobivaim. Esimesele ettevõttele mudel soovitas mõnevõrra suurema külvisekastiga aga sama laia külvikut. Teisele ettevõttele aga oli soodsaimaks lahenduseks olemasolevast kaks korda kitsam ja väiksema külvisekastiga seade, aga ka pikem külviaeg. Kolmandal ettevõttel oli kasutuses olev külvik ka kõige soodsam. Uute külvikute loendist oli mudeli arvates sobiv sama lai aga 2,5 korda suurem kastiga külvik, mille kulude summa aga oli mõnevõrra suurem ettevõtte enda külviku kuludest.
12. Mudeli arvutavas osas uuriti ka arvutustulemuste tundlikust sisendparameetrite muutusele. Uuritud parameetriteks olid saagikus, külvisenorm ja laadimiskaugus. Neist suurimaks mõjutajaks osutus saagikus – kuludes summa muutus oli 0,19 eurot kui saagikus muutus 1%. Külvisenormi ja laadimiskauguse korral olid vastavateks suurusteks 0,06 ja 0,02 €/%. Nende parameetrite muutumisest sõltus ka see, milline külvik on ettevõttele sobivaim.
Mudeleksperimentidest võib järeldada, et koostatud valikumudeli sobis uuritud ettevõtetele külviku valimisel. Külvikumüüjatel oleks kasulik kasutada valikumudelit. Kahel juhul kolmest soovitas mudel soodsamat lahendust võrreldes olemasolevaga. 66
Mudeliga tuleks edaspidi teha veel täiendavaid eksperimente äärmuslikumate tootmistingimustega korral, et selgitada milliseid täiendusi see veel vajaks. Samuti peaks seda laskma testida külvikute müüjatel ja põllumeestel, et täiendada mudeli esimest, kitsendavat osa.
The purpose of present research is to specify fundamentals i.e. factors and relationships which have influence on the choosing of a grain seeder and build a model which helps farmers to select most suitable machine from the market. The aim is achieved 1) by compiling an overview about the agronomical requirements for the grain sowing, 2) by compiling an overview about the sowing technologies, 3) also an overview about the grain seeders sold in Estonia, 4) by questioning equipment sellers and farmers about the method they use by choosing the grain seeder, 5) by compiling an overview about factors influencing the decision process, 6) by composing the selection model and 7) by composing model experiments with the real farm data and composed model, and at last 8) by making the sensitivity analysis for model. Today, there are 10 companies in Estonia selling new grain seeders – they had 135 models in list in total: conventional and direct drills, mono and combo drills, with different work widths (2,5-12 m) and grain box volumes (105-8000 l). For present study, sellers disclosed the prices for 62 grain seeder models. Three farmers and four equipment sellers were questioned, what factors they take into account if they are choosing grain drill and have they any kind of selection model. Three farmers and two sellers gave response. They are taking into account the grain production area, the time span available for grain sowing, the tillage technology and the tractor power used in the farm. The sellers said that they use own experiences and often the farmer don’t want any advice. The overview about factors consists agronomical, farm based, economical and logistical factors. On the bases of those factors a selection model was composed. The selection model composed in this study consist two parts: 1) the choice of seeders is limited by excluding machines which have unsuitable or unnecessary properties for farm; 2) for every seeder remained into list a sum of costs is calculated. The sum of costs includes sowing costs and timeliness costs depending on number of sowing days in spring and autumn. The most suitable grain seeder has lowest sum of costs. The selection model was used to find out a most suitable grain seeder for three farms. The selection was made from the list consisting 63 machines with known selling price. The seeders suggested by model were compared with machines existing in farm today. Farm 1 had 6 m wide grain seeder with 2000 l grain box volume pulled by 118 kW tractor with sum of costs 89 €/ha. The model suggested for this farm a 6 m grain seeder with 4200 l box volume pulled by 130 kW tractor with sum of costs 86 €/ha. Thus the model recommended quite similar solution compared to existing one. However, the bigger grain box volume enables to raise work speed and shorten sowing period. Resulting lowering of the timeliness costs compensate bigger tractor and seeder costs and gives even some additional cost benefit. Farm 2 had 8 m wide grain seeder with 3300 l grain box volume pulled by 116 kW tractor with sum of costs 52 €/ha. The model suggested for this farm a 4 m grain seeder with 2000 l box volume pulled by 81 kW tractor with sum of costs 48 €/ha. The model recommended also to use longer sowing period - 8 days instead 5 at spring and 6 days instead 4 in autumn. Thus the smaller seeder and tractor are so much cheaper that even by longer sowing period the recommended solution gives additional cost benefit compared to the existing one. Farm 3 had 3 m wide grain seeder with 440 l grain box volume pulled by 79 kW tractor with sum of costs 34 €/ha. The model did not found cheaper solution from list of grain seeders. Most inexpensive variant in the list was by a 3 m grain seeder with 1100 l box volume pulled by 100 kW tractor with sum of costs 40 €/ha. For this case the number of sowing days declines form 5 to 3. Similarly to the farm 2 the smaller seeder and tractor are so much cheaper that even by longer sowing period the recommended solution gives additional cost benefit compared to the existing one. The sensitivity analysis was with the calculating part of model. Tested were model with different yield levels, grain seeding rates, distances from work pass to the loading point. Reference conditions based on farm 2 with yield level 4000 kg/ha, seeding rate 170 kg/ha, distance to the loading point 0,7 km and grain seeder no 40 from list. Analysis shows that from studied parameters has greatest influence on the sum of costs yield - 0,19 € per 1% yield change. The influence of seeding rate and distance were correspondingly 0,06 and 0,02 €/%. Probably the limiting part of model does not contain all factors today. This part needs further analysis - is there possibility to change the model such way that it considers production conditions in the farm even more than today. The calculating part can be complemented with transportation costs of grain seeders from farm centre to the fields.
The purpose of present research is to specify fundamentals i.e. factors and relationships which have influence on the choosing of a grain seeder and build a model which helps farmers to select most suitable machine from the market. The aim is achieved 1) by compiling an overview about the agronomical requirements for the grain sowing, 2) by compiling an overview about the sowing technologies, 3) also an overview about the grain seeders sold in Estonia, 4) by questioning equipment sellers and farmers about the method they use by choosing the grain seeder, 5) by compiling an overview about factors influencing the decision process, 6) by composing the selection model and 7) by composing model experiments with the real farm data and composed model, and at last 8) by making the sensitivity analysis for model. Today, there are 10 companies in Estonia selling new grain seeders – they had 135 models in list in total: conventional and direct drills, mono and combo drills, with different work widths (2,5-12 m) and grain box volumes (105-8000 l). For present study, sellers disclosed the prices for 62 grain seeder models. Three farmers and four equipment sellers were questioned, what factors they take into account if they are choosing grain drill and have they any kind of selection model. Three farmers and two sellers gave response. They are taking into account the grain production area, the time span available for grain sowing, the tillage technology and the tractor power used in the farm. The sellers said that they use own experiences and often the farmer don’t want any advice. The overview about factors consists agronomical, farm based, economical and logistical factors. On the bases of those factors a selection model was composed. The selection model composed in this study consist two parts: 1) the choice of seeders is limited by excluding machines which have unsuitable or unnecessary properties for farm; 2) for every seeder remained into list a sum of costs is calculated. The sum of costs includes sowing costs and timeliness costs depending on number of sowing days in spring and autumn. The most suitable grain seeder has lowest sum of costs. The selection model was used to find out a most suitable grain seeder for three farms. The selection was made from the list consisting 63 machines with known selling price. The seeders suggested by model were compared with machines existing in farm today. Farm 1 had 6 m wide grain seeder with 2000 l grain box volume pulled by 118 kW tractor with sum of costs 89 €/ha. The model suggested for this farm a 6 m grain seeder with 4200 l box volume pulled by 130 kW tractor with sum of costs 86 €/ha. Thus the model recommended quite similar solution compared to existing one. However, the bigger grain box volume enables to raise work speed and shorten sowing period. Resulting lowering of the timeliness costs compensate bigger tractor and seeder costs and gives even some additional cost benefit. Farm 2 had 8 m wide grain seeder with 3300 l grain box volume pulled by 116 kW tractor with sum of costs 52 €/ha. The model suggested for this farm a 4 m grain seeder with 2000 l box volume pulled by 81 kW tractor with sum of costs 48 €/ha. The model recommended also to use longer sowing period - 8 days instead 5 at spring and 6 days instead 4 in autumn. Thus the smaller seeder and tractor are so much cheaper that even by longer sowing period the recommended solution gives additional cost benefit compared to the existing one. Farm 3 had 3 m wide grain seeder with 440 l grain box volume pulled by 79 kW tractor with sum of costs 34 €/ha. The model did not found cheaper solution from list of grain seeders. Most inexpensive variant in the list was by a 3 m grain seeder with 1100 l box volume pulled by 100 kW tractor with sum of costs 40 €/ha. For this case the number of sowing days declines form 5 to 3. Similarly to the farm 2 the smaller seeder and tractor are so much cheaper that even by longer sowing period the recommended solution gives additional cost benefit compared to the existing one. The sensitivity analysis was with the calculating part of model. Tested were model with different yield levels, grain seeding rates, distances from work pass to the loading point. Reference conditions based on farm 2 with yield level 4000 kg/ha, seeding rate 170 kg/ha, distance to the loading point 0,7 km and grain seeder no 40 from list. Analysis shows that from studied parameters has greatest influence on the sum of costs yield - 0,19 € per 1% yield change. The influence of seeding rate and distance were correspondingly 0,06 and 0,02 €/%. Probably the limiting part of model does not contain all factors today. This part needs further analysis - is there possibility to change the model such way that it considers production conditions in the farm even more than today. The calculating part can be complemented with transportation costs of grain seeders from farm centre to the fields.
Kirjeldus
Märksõnad
bakalaureusetööd