Zdeněk Kvíz, Milan Kroulík, Jan Chyba

Transcription

1 Evaluation of Machinery Guidance Systems Concerning Pass-to-Pass Accuracy as a Tool for More Efficient Plant Production in Fields and Soil Damage Reduction Zdeněk Kvíz, Milan Kroulík, Jan Chyba Czech University of Life Sciences Prague Faculty of Engineering Department of Agricultural Machines Prague 6-Suchdol, Czech Republic Phone: , Fax: kviz@tf.czu.cz,

2 INTRODUCTION The agricultural land represents 54 % of the total area of the Czech Republic (from 7,886 milion hectares is 4,264 milion hectares agriculture area). The area of the arable land is 3,062 milion hectares, which represents 72 % from the land suitable for agricultural production. More than 50 % of agricultural area is located on plots with more than 7 % slope, i.e. unsuitable fields with respect to the intensive land management and/or with a risk of soil structure damage. According to soil grading, more than 60 % of arable soil in the Czech Republic is situated in the less favourable areas with some kind of environmental claim.

3 The global problems connected with soil conditions are: - soil erosion (still increasing worldwide), - soil compaction (particularly in developed countries using big and heavy machinery in fields. In the Czech Republic, around 40 % of the arable soil stands in danger of soil compaction. Soil erosion and compaction by machinery traffic is one of the major problems facing modern agriculture and it is a well-recognised problem worldwide.

4 The extent of the soil compaction problem is a function of SOIL type, soil water content and soil depth, further of VEHICLE weight, speed, ground contact pressure of tyres and number of passes, as well as interactions of above mentioned with cropping frequency and farming practices Examples: degree of compaction dependent on number of machinery passes soil compaction dependence on ground contact pressure and depth

5 Machinery Guidance Systems General benefits following from the use of guidance systems: Dunn et al. (2006), Han et al. (2004), Stoll and Kutzbach (2000), Debain et al. (2000), Cordesses et al (2000) - reduction of driver fatigue - reduction in costs (no repeated application-overlaps = fuel savings, pesticides savings) - increase in productivity: higher operating speeds - improved quality: the driver can focus attention elsewhere to ensure better quality - improved safety of work - less impact on the environment (reduction of machinery passes, reduction of soil compaction ); - possibility for work at night and when visibility is poor.

6 OBJECTIVES OF RESEARCH This work evaluates: 1. Working accuracy of field jobs = pass-to-pass errors of agriculture machines 2. Percentage of wheeled area and machinery repeated passes (as a possible cause of soil compaction) = traffic intensity within a field when using different tillage technologies: - conventional tillage with ploughing (with random traffic), - conservation tillage with randomly organized traffic, - fixed machinery tracks for all field operations (controlled traffic farming CTF).

7 MATARIALS AND METHODS Evaluation of field job working accuracy pass-to-pass errors a) without using GPS guidance system manual steering - 7 different machinery units with different drivers in fields were evaluated during field operations Driver Machinery unit Working width Driver experience Orientation in a filed 1 Tractor Fendt 924 Disc tiller Lemken 2 Tractor JD 8320 Disc tiller Strom 3 Tractor Zetor 9540 Sprayer HARDI Twin Air 4 Tractor Zetor Sprayer HARDI Twin Air 5 Tractor New Holland TE 88 Seeder Accord MT 6 6 Tractor Zetor 7245 Sprayer TECNOMA 7 Tractor Zetor 7245 Sprayer TECNOMA 6 m Driver - experience 8 year 6 m Driver - experience 5 year 18 m Driver - experience 6 year 18 m Driver - experience 13 year 6 m Driver - experience 5 year 18 m Driver - experience 6 year 18 m Driver - experience 6 year By estimation of a driver By estimation of a driver By estimation of a driver Foam marker Disc marker Tramlines By estimation of a driver

8 Evaluation of field job working accuracy pass-to-pass erors - distances between tyre tracks of neighbouring passes were VI. measured manually, with the accuracy of 10 mm 7 passes of a particular machine V. 6 real working widths (Wr) = 6 values 6 times repetition = 36 values for statistical analysis IV. III. 36 values II. I.

9 Evaluation of field job working accuracy pass-to-pass errors b) with RTK navigation fully automated steering - 3 different machinery units with different drivers in fields were evaluated during field operations Driver Machinery unit Working width Treatment CAT MT765B Horsch Phantom FG8 CASE STX 450 Swifter Combi JD 8210 Lemken Soliter 10 8 m 15 m seed bed preparation tillage shallow loosening Differential signal type RTK RTK 6 m seeding RTK

10 Evaluation of field job working accuracy pass-to-pass errors b) with RTK navigation fully automated steering - a very simple equipment to monitor and save data about vehicle trajectory was placed into every machine data loggers were directly connected to RTK guidance monitor of the tractor. - the task for the driver was to run approximately 10 passes or to do at least 45 minute his field job with and further without navigation use. - these two experimental setups were repeated at least 3 times for each machine. - analysis of pass-to-pass errors was done by ArcGIS 9.2 software on PC

11 MATARIALS AND METHODS Evaluation of traffic intensity within a field All field operations and all machinery and vehicle s passes across selected fields were monitored during one year = one year traffic picture. Just simple DGPS receivers with data loggers were placed into every machine entering the fields = monitoring of all machinery passages (all machinery entries)

12 Evaluation of traffic intensity within a field 2 variants of tillage systems were observed: Conventional system with ploughing (with random traffic) Conservation tillage (with random traffic) Further CTF system was introduced on conservation tillage field and evaluated

13 Evaluation of traffic intensity within a field Trajectories for every machine run in the field were defined from the data sets Machines equipped with - DGPS receivers + RTK - data loggers - impuls logging time (2 s)

14 Evaluation of traffic intensity within a field Then the area covered by the machine tyres was calculated from the tyre type, tyre width and wheel spacing. Machine s tyre size (width) - wheeled area in [m -2 ] - wheeled area in [%] from total field acrage

15 RESULTS AND DISCUSSION part I. Evaluation of field job working accuracy pass-to-pass errors The worst results were recorded when the machine was without any guidance and any additional aids (disc markers, foam markers ) and the steering was completely dependent on driver estimation.

16 Evaluation of field job working accuracy pass-to-pass errors And also wider the working width of the machine unit, the worse was the working accuracy. 18 m 6 m 6 m

17 Evaluation of field job working accuracy pass-to-pass errors The outcome values show prevailing overlaps of passes in the range between 1,5 and 6 % of machine s working width - the case without any guidance systems. This value can be significantly minimized by utilization of precise guidance systems, based on RTK signal. Therefore these systems can be a possible way for fuel, chemicals, changeable tool parts and other additional material savings

18 RESULTS AND DISCUSSION part II. Frequency of agricultural machinery passes across a field CONVENTIONAL TILLAGE with PLOUGHING (random traffic). Conventional system with ploughing Width of tyres (mm) Working width (m) Run-over area (%) Stubble breaking Ploughing Presowing preparation Seeding Protection, fertilization (spraying rows) Harvest Grain disposal Straw ballers press Straw bales disposal Repeatedly run-over area (%) 1x 2x 3x 4x 5x 6x Run-over (total) (%) 86.13

19 Frequency of agricultural machinery passes across a field Diagram presenting TRAJECTORIES of machines when using conventional soil tillage technology in 1 ha (selected section). All machinery entering field during one cropping season.

20 Frequency of agricultural machinery passes across a field Diagram presenting TOTAL WHEELED AREA when using conventional soil tillage technology within 1 ha (selected section) - during one cropping season.

21 Frequency of agricultural machinery passes across a field CONSERVATION TILLAGE (random traffic). Conservation tillage Width of tyres (mm) Working width (m) Run-over area (%) Stubble break. Desiccation - spraying Shallow tillage Seeding Protection, fertil. (spraying rows) Harvest Grain disposal - truck Repeatedly run-over area (%) 1x 2x 3x 4x 5x Run-over (total) (%) 63.75

22 Frequency of agricultural machinery passes across a field Diagram presenting TRAJECTORIES of machines when using conservation soil tillage technology in 1 ha (selected section). All machinery entering field during one cropping season.

23 Frequency of agricultural machinery passes across a field Diagram presenting TOTAL WHEELED AREA when using conservation soil tillage technology within 1 ha (selected section) - during one cropping season.

24 Frequency of agricultural machinery passes across a field PLOUGHING CONSERVATION TOTAL WHEELED AREA 86,14% 63,75%

25 Frequency of agricultural machinery passes across a field machinery passes on HEADLANDS (headland width 25 m) Conventional system with ploughing Run-over area (%) Conservation tillage Run-over area (%) Number of passes repetitions Number of passes repetitions 1x 2x 3x 4x 5x 6x and more x 2x 3x 4x 5x 6x Run-over area (total) (%) Run-over area (total) (%) 81.76

26 PARTIAL OUTCOMES Farming practices chosen tillage technology - can significantly effect final intensity of traffic in the fields throughout a cropping season. TAKING INTO ACCOUNT LITERATURE SOURCES Intensity of traffic (number of machinery passes) in fields plays an important role in soil compaction, because soil deformations can increase with the number of passes. However, the first pass of a wheel is known to cause a major portion of the total soil compaction!!!!! IDEA DERIVED FROM PREVIOUS INFORMATION One possible tool for (further) machinery traffic reduction and therefore soil compaction reduction could be the Controlled Traffic Farming system (CTF).

27 Frequency of agricultural machinery passes across a field machinery passes across a field where fixed tracks were used (CTF system). Conservation tillage 4 m working width Run-over area (%) Conservation tillage 8 m working width Run-over area (%) Number of passes repetitions Number of passes repetitions 1x 2x 3x 4x 5x 6x x 2x 3x 4x 5x 6x and more Run-over area (total) (%) Run-over area (total) (%) 30.88

28 Conservation tillage - 4 m CTF system

29 Conservation tillage - 8 m CTF system

30 Soil compaction phenomenon is connected with number of machinery passes but also with time exposure of soil surface to contact pressure Interesting outcome the map of soil exposure to machinery time-dependent presence (tyres contact presure) visible spots where machinery stayed for a longer time (i.e. seeder loading, sprayer filling up )- the more log-impulses recorded at a particular place the darker colour in the map greater risk of compaction Tractor trajectories from bales disposal impulses record Map characterising intensity of traffic and time spent at a certain area

31 CONCLUSIONS Machinery passages in a field are for current agriculture practices inevitable but their ordering is usually random. The results show considerable high number of tyre s contacts with soil with random traffic in field (wheeled area was 86 % - ploughing and 63 % - conservation tillage). Also high number of repeatedly run over areas were observed. When using the system with fixed tracks (CTF system) for all machinery passes, the total run-over area decreased significantly up to 31 % in comparison to randomized traffic in field.

32 Very final advice: ALWAYS USE THE RIGHT TRACKS!!! Thank you for your attention!

33 Evaluation of Machinery Guidance Systems Concerning Pass-to-Pass Accuracy as a Tool for More Efficient Plant Production in Fields and Soil Damage Reduction Zdeněk Kvíz, Milan Kroulík, Jan Chyba Czech University of Life Sciences Prague Faculty of Engineering Department of Agricultural Machines Prague 6-Suchdol, Czech Republic Phone: , Fax: kviz@tf.czu.cz,