Effectiveness of GNSS-based tractor auto steering systems in crop spraying

Year 2019, Special Issue: 1st Int. Congress on Biosystems Engineering 2019, 78 - 90, 27.12.2019

Mustafa Topcueri , Muharrem Keskin

Abstract

Aims:
This study aimed to compare
pass-to-pass overlaps and spacings in adjacent parallel passes in spraying with
and without tractor automatic steering (AS).

Methods and Results:
The data were obtained from 13 farmer
fields (cotton, corn and peanut) to assess the performance of AS systems in
real farmer conditions. Root mean square errors (RMSE) of overlaps and spacings
were determined on the maps generated from the coordinates of the tractor
recorded while spraying. Variations between the fields were also examined. The
RMSE was lowest (7.5 ± 1.7 cm) in the fields on which farmers used AS (with RTK
correction signal) in all three operations of tillage, sowing and spraying.
RMSE values were comparatively higher for the fields on which farmers used AS
only in ridge tillage but not in sowing and spraying (CORS-GSM: 46.1 ± 6.5 cm,
SBAS: 76.5 ± 13.9 cm). The fields with manually-steered ridge tillage, sowing
and spraying (all three) had the highest RMSE value of 100.8 ± 27.8 cm
(p<0.05). The mean RMSE in the manual spraying (without AS) were found to be
significantly higher than those using the AS (p<0.05).

Conclusions:
AS systems were found to be beneficial in
reducing the mean pass-to pass overlap and spacing errors (RMSE) in spraying.
However, most of the farmers used AS only in soil ridge tillage and made the
spraying without AS by referencing marking flags and/ or soil ridges which were
formed using AS. Main reason of this is the high cost of the AS systems and
farmers cannot afford to equip all of their tractors. The use of AS systems not
only in ridge tillage but also in planting and spraying reduced the errors and
increased the benefit of AS usage. The level of benefit from the AS could
change from farmer to farmer; thus, farmers should use the AS systems carefully
with appropriate equipment settings to obtain a higher level of benefits.

Significance and Impact of
the Study: Appropriate
use of AS systems in spraying offers benefits to reduce overlap and gaps and
the amount of pesticides resulting in lower amount of environmental pollution
and pesticide residues on crops, lower application time, lower fuel and labor
consumption.

Keywords

GNSS, auto steering, spraying, overlap, spacing

Thanks

The authors thank Mr. Omer Selim Alporal (from Graftek), Dr. Yunus Emre Sekerli, Dr. Selcuk Ugurluay and all farmers who made contributions in data collection and analysis. This paper was produced from the MSc thesis of Mr. Mustafa Topcueri under the supervision of Dr. Muharrem Keskin.

İlaçlama işleminde GNSS esaslı traktör otomatik dümenleme sistemlerinin etkinliği

Abstract

Amaç: Bu çalışmada, traktör otomatik dümenleme
(OD) sistemi ile ve manuel dümenleme ile yapılan ilaçlamada yan yana paralel
geçişlerdeki örtüşme ve boşluk miktarları karşılaştırılmıştır.

Yöntemler ve Bulgular: Veriler, OD sistemlerinin gerçek çiftçi
koşullarındaki performansını değerlendirmek için 13 çiftçi tarlasından (pamuk,
mısır ve yerfıstığı) elde edilmiştir. İlaçlama sırasında traktörün izlediği
noktaların koordinatları kayıt altına alınmış, bu noktalardan oluşturulan
haritalar üzerinden ortalama örtüşme ve boşluk hata değerleri (Hataların
ortalama kare kökü; Root mean square error: RMSE) belirlenmiş ve analiz
edilmiştir. Tarlalar arasındaki değişkenlik de incelenmiştir. RMSE değerinin
çiftçilerin sırta toprak işleme, ekim ve ilaçlama işlemlerinin her üçünde OD
kullandığı (RTK düzeltme sinyaliyle) tarlalarda en düşük değerde (7.5 ± 1.7 cm)
olduğu gözlemlenmiştir. Çiftçilerin sadece sırta toprak işlemeyi OD sistemiyle,
ekim ve ilaçlamayı manuel olarak (OD kullanmadan) yaptığı tarlalarda ortalama
hata değerinin daha yüksek olduğu tespit edilmiştir (CORS-GSM: 46.1 ± 6.5 cm,
SBAS: 76.5 ± 13.9 cm). Sırta toprak işleme, ekim ve ilaçlamanın hepsinin manuel
dümenleme ile yapıldığı tarlalarda ise ortalama hata değerinin en yüksek
düzeyde olduğu (100.8 ± 27.8 cm) görülmüştür (p<0.05). Manuel ilaçlama
durumunda (OD kullanılmadan) ortalama hata değerinin OD kullanılan tarlalara
göre önemli derecede daha yüksek olduğu bulunmuştur (p<0.05).

Genel Yorum: OD sistemlerinin, ilaçlamada yan yana
paralel geçişlerdeki ortalama ötüşme ve boşluk hata değerini azaltmada yararlı
olduğu tespit edilmiştir. Ancak, çiftçilerin çoğunun OD sistemini sadece toprak
sırtı oluşturmada kullandığı, ekim ve ilaçlamayı toprak sırtlarını referans
alarak OD kullanmaksızın elle dümenleme ile yaptığı belirlenmiştir. Bu durumun
temel nedenlerinden biri, OD sistemlerinin maliyetinin yüksek olması ve
çiftçilerin tüm traktörlerini OD sistemi ile donatacak mali gücünun
olmamasıdır. OD sistemlerinin sadece sırta toprak işlemede değil, aynı zamanda
ilaçlamada da kullanımının örtüşme ve boşluk hatalarını azalttığı ve OD
kullanımının yararını arttırdığı gözlenmiştir. OD'den elde edilen fayda
düzeyinin çiftçiden çiftçiye değişebildiği tespit edilmiş olup, daha yüksek
düzeyde faydalar elde etmek için çiftçilerin OD sistemlerini uygun ekipman
ayarlarıyla dikkatli bir şekilde kullanmaları gereklidir.

Çalışmanın Önemi ve Etkisi: OD sistemlerinin ilaçlama işleminde
uygun şekilde kullanımı, örtüşme ve boşluk miktarında azalmaya bağlı olarak
tarım ilacı kullanımında azalma, bitkiler üzerinde daha az toksik etki, ürün
üzerinde daha düşük miktarda pestisit kalıntısı, daha az çevre kirliliği, daha
düşük ilaçlama süresi, daha düşük yakıt tüketimi ve daha düşük işçilik masrafı
potansiyeline sahiptir.

Keywords

GNSS, otomatik dümenleme, ilaçlama, örtüşme, boşluk, hata

References

• Akdemir B (2016) Evaluation of precision farming research and applications in Turkey. 10.7251/AGRENG1607227. pp.1498-1504.
• Altinkaradag A (2014) Development of Automatic Steering System for Tractors. PhD Dissertation. Namık Kemal University, Tekirdag, Turkey. 135 pp.
• Ashworth AJ, Lindsay KR, Popp MP, Owens PR (2018) Economic and Environmental Impact Assessment of Tractor Guidance Technology. Agric. & Envir. Letters. 5pp.
• Baillie CP, Lobsey CR, Diogenes LA, McCarthy CL, Thomasson JA (2018) A review of the state of the art in agricultural automation. Part III: Agricultural machinery navigation systems. ASABE Annual International Meeting, 29 July - 1 August 2018, Detroit, MI, USA.
• Bayar G, Bergerman M, Koku AB, Konukseven EI (2015) Localization and control of an autonomous orchard vehicle. Comput. Electron. Agric. 115: 118–128.
• Buick R, Lange AF (1998) Assessing Efficiency of Agricultural Chemical Application with Differential GPS, ArcView and Spatial Analyst. Precision Agriculture. P.C. Robert, R.H. Rust and W.E. Larson (Ed.). p. 1035-1045.
• Buick R, White E (1999) Comparing GPS Guidance with Foam Marker Guidance. Fourth International Conference on Precision Agriculture. pp.1035-1045.
• Erickson B, Widmar DA (2015) Precision agricultural services dealership survey results. Purdue University. West Lafayette, Indiana, USA. 37pp.
• Evrenesoglu M, Karatas U (2019) The Effect of Automatic Steering on Agro-Technical Success in Deep Chisels. 32nd National Agricultural Mechanization and Energy Congress, 4-6 September 2019, Canakkale, Turkey. pp 10-11.
• Gisgeography (2018) How to Calculate Root Mean Square Error (RMSE) in Excel. https://gisgeography.com/root-mean-square-error-rmse-gis (Accessed on: 30.12.2018)
• Grisso R, Alley M, Groover G (2009) Precision Farming Tools: GPS Navigation. Virginia Cooperative Extension. Publication No 442-501. 7 pp.
• Hudson G, Shofner R, Wardlow G, Johnson D (2007) Evaluation of three tractor-guidance methods for parallel swathing at two field speeds. Discovery, 8:61-66.
• Keskin M, Görücü Keskin S (2012) Precision Agriculture Technologies (Hassas Tarım Teknolojileri). Book (In Turkish). Mustafa Kemal University, Turkey. No: 35. 212 pp.
• Keskin M (2013) Factors Affecting the Adoption of the Precision Agriculture Technologies and the Adoption Rate of these Technologies in the World (In Turkish with Abstract in English). J. Agric. Mach. Sci. 9(4): 263-272.
• Keskin M, Sekerli YE (2016) Awareness and adoption of precision agriculture in the Cukurova region of Turkey. Agron.Res. 14(4): 1307-1320.
• Keskin M, Sekerli YE, Say SM, Topcueri M (2018) Farmers’ Experiences with GNSS-Based Tractor Auto Guidance in Adana Province of Turkey. J. Agric. Fac. Gaziosmanpasa Univ. 35(2):172-181.
• Kunz C, Weber JF, Peteinatos GG, Sökefeld M, Gerhards R (2018) Camera steered mechanical weed control in sugar beet, maize and soybean. Precision Agric. 19: 708–720
• Leonard E (2014) Precision Agriculture Down Under. www.precisionag.com/guidance/precision-ag-down-under.
• Li M, Imou K, Wakabayashi K, Yokoyama S (2009) Review of research on agricultural vehicle autonomous guidance. J Agric & Biol Eng. 2(3):1-26.
• Lowenberg-DeBoer J (1999) GPS Based Guidance Systems for Agriculture. 6 December 1999.
• McDougall K, Gibbings P, Wolski I (2001) Comparison of a d-GPS system and conventional guidance for spraying applications. In: 5th Precision Agriculture in Australasia Symposium: Information for Better Production and Envir Manag., 17-19 Jul 2001, Sydney, Australia.
• Molin JP, Cerri DGP, Baio FHR, Torrezan HF, Esquerdo JCDM, Ripoli MLC (2002) Evaluation of a light bar for parallel swathing under different forward speeds. World Congress of Computers in Agr. and Natural Resources. 13 March 2002. Iguacu Falls, Brazil: ASABE.
• Morgan M, Ess D (2003) The precision farming guide for agriculturists. Second edition. John Deere Publishing, Moline, Illinois, USA.
• Morrow TF (2002) Evaluation of DGPS Row Guidance Systems, Analyzing Operator Feedback Methods Based on Accuracy and Operator Insights. MSc Thesis, Univ of Tennessee. 93 pp.
• Mousazadeh H (2013) A technical review on navigation systems of agricultural autonomous off-road vehicles. J. Terramech. 50: 211–232. Müller Elektronik (2018) Steering systems & GPS. Brochure. 12pp. www.mueller-elektronik.de
• Norwood S, Fulton J (2009) GPS/GIS Applications for Farming Systems. Alabama Farmers Federation Commodity Organizational Meeting. 5 February 2009.
• Reichhardt (2012). Auto Guidance System Brochure. Reichhardt, 12 First Street Southi Sabin, MN 56580. www.reichhardt.com.
• Reid JF, Zhang Q, Noguchi N, Dickson M (2000) Agricultural automatic guidance research in North America. Comput. Electron. Agric. 25: 155–167.
• Santos AF, Silva RP, Tavares TO, Ormond ATS, Rosalen DL, Assis LC (2017) Parallelism error in peanut sowing operation with auto-steer guidance. Revista Brasileira de Engenharia Agrícola e Ambiental. 21(10):731-736.
• Santos AF, Correa LN, Gírio LAS, Paixao CSS, da Silva RP (2018) Position Errors in Sowing in Curved and Rectilinear Routes Using Autopilot. Eng. Agríc. 38: 568-576.
• Say SM, Keskin M, Sehri M, Sekerli YE (2017) Adoption of Precision Agriculture Technologies in Developed and Developing Countries. International Science and Technology Conference, 17-19 July 2017 Berlin, Germany. pp.41-49.
• Silva CB, Moraes MAF, Molin JP (2011) Adoption and use of precision agriculture technologies in the sugarcane industry of Sao Paulo state, Brazil. Precis. Agric. 12: 67–81.
• Torres FP, Ribeiro Filho AC, Baio FHR (2000) Comparaçao da utilizaçao da barra de luz na agricultura de precisao em relaçao ao marcador de espuma. In: Agric. de Precisao. Viçaso: UFV. 357-364.
• USDA (2015a) Agricultural Resource Management Survey: US Peanut Industry. United States Department of Agriculture (USDA) National Agric Stat Service (NASS). No 2015-1. 4 pp.
• USDA (2015b) Agricultural Resource Management Survey: US Rice Industry. United States Department of Agriculture (USDA) National Agric Stat Service (NASS). No 2015-2. 4 pp.
• Unal I, Topakci M (2012) Navigation Methodology and Different Navigation Systems for Agricultural Applications (In Turkish with Abstract in English). 27. National
• Agricultural Mechanization Congress, 5-7 September 2012, Samsun, Turkey.
• Verma L (2015) China Pursues Precision Agriculture on a Grand Scale. Resource Magazine. July/August 2015. 22: 18–19.
• Whelan B, Taylor J (2013) Precision agriculture for grain production systems. Csiro Publishing. 199 pp.