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Tek Dane Ekim Performansı Maksimizasyonunda Optimum Değişkenlere Bağlı Genel Model Denklemlerinin Geliştirilmesi

Year 2016, , 179 - 187, 22.06.2016
https://doi.org/10.20289/zfdergi.389108

Abstract








 






Bu çalışmanın amacı tek dane ekim performansı üzerinde
etkisi olan değişkenlerin tahminleme eşitliklerinin geliştirilmesidir.
Çalışmada, tohumun fiziksel özelliklerine bağlı olarak değişen, tohumun
yakalanması, bırakılması ve toprakla temasında sistemi yöneten parametrelerden
olan vakum basıncı, plaka çevre hızı ve plaka delik çapı değişkenleri bağımlı
değişkenler olarak ele alınmıştır. Denemeler, Tepki Yüzeyleri Metodolojisi
(RSM) deneme desenlerinden biri olan Merkez Esaslı Dizayna göre farklı tohumlar
kullanılarak laboratuvarda yürütülmüştür. Küresellik, bin dane ağırlığı, yüzey
izdüşüm alanı, kritik hız, ortalama anma çap ve metal üzerinde sürtünme
katsayısı vb. fiziksel ve aerodinamik özellikleri birbirinden farklı tohumlar
kullanılarak ekim performansını maksimize eden tahminleme modellerinin
geliştirilmesi hedeflenmiştir. İstatistik analiz sonuçlarına göre, plaka delik
çapı ve vakum basıncına ilişkin tahminleme modelleri geliştirilirken, plaka
çevre hızına ilişkin istatistiksel olarak anlamlı bir model elde edilememiştir.
Uygun plaka delik çapının, tohumun ortalama anma çapı ve küresellik
değerlerinin bir fonksiyonu olduğu ve model denkleminin tahminleme katsayısının
%92.69 olduğu saptanmıştır. Vakum basıncı ise küresellik ve kritik hız
değerlerinin bir fonksiyonu olup tahminleme katsayısı %76.74’dir. Geliştirilen
model denklemlerinin geçerliliği farklı tohumlarla da test edilerek tohum
dağılımları değerlendirilmiştir.

References

  • Box, G. E. P. and N. Draper, 1987. Empirical Model-Building and Response Surfaces. John Wiley & Sons, New York. 669 p.
  • International Organization for Standardization (1984). Sowing equipment- Test methods- Part1: Single seed drills (precision drills) 7256/1.
  • Karayel D; Barut Z; Özmerzi A (2004). Mathematical Modelling of Vacuum Pressure on a Precision Seeder. Biosystems Engineering, 87 (4): 437-444.
  • Moody F H; Hancock J H; Wilkerson J B (2003). Evaluating planter performance-cotton seed placement accuracy. ASAE Paper No. 03 1146, St Joseph, Michigan, USA
  • Onal, O., I. Onal (2009). Development of a computerized measurement system for in-row seed spacing accuracy. Turkish Journal of Agriculture and Forestry 33(2009) 99-109.
  • Singh R C; Singh G; Saraswat D C (2005). Optimisation of design and operational parameters of a pneumatic seed metering device for planting cottonseeds. Biosystems Engineering, 92(4), 429-438.
  • Srivastava A K; Goering C E; Rohrbach R P (1993). Engineering Principles of Agricultural Machines. ASAE, St. Joseph, Michigan, USA
  • St Jack D; Dianne C. Hesterman, Andrew L. Guzzomi (2013). Precision metering of Santalum spicatum (Australian Sandalwood) seeds. Biosystems Engineering 115 (2013): 171-183.
  • Yazgi, A, A. Degirmencioglu. (2007). Optimisation of the seed spacing uniformity performance of a vacuum-type precision seeder using response surface methodology. Biosystems Engineering 97(3): 347-356.
  • Yazgı, A. 2010. Vakumlu Tek Dane Ekimde Optimizasyon ve Makina Performansının Matematiksel Modellemesi (Optimization of the Precision Seeding and Mathematical Modeling of the Machine Performance). Unpublished PhD. Dissertation, 196 p. Graduate School of Natural and Applied Sciences, Ege University, Bornova-Izmir/Turkey, 2010.

Development of Prediction Functions for a Maximized Precision Seeding Performance Based on Optimized Variables

Year 2016, , 179 - 187, 22.06.2016
https://doi.org/10.20289/zfdergi.389108

Abstract








 






The objective of this study was to develop
prediction functions for the variables that affect precision seeding
performance. The variables considered were the amount of vacuum, peripheral
speed and the diameter of the holes on vacuum plate. On the other hand, these
variables are significantly affected by physical properties of the seeds and
govern the seeding phenomenon that is the capture, release and incorporation of
seeds into the soil. Experiments using Central Composite Design which is one of
the designs in Response Surface Methodology (RSM) were conducted in the lab and
different seeds were used to meet the objective. Hence, using different seeds
with different physical and aerodynamic properties such as sphericity, thousand
seed mass, projected area, terminal velocity, mean particle diameter and
coefficient of friction of material on metal are expected to contribute the
development of prediction models for a maximized seeding performance.  According to results of the statistical
analyses, hole diameter and vacuum pressure models were developed while no
significant model was developed for the peripheral the speed of the vacuum
plate. The appropriate hole diameter was found to be the function of mean
particle diameter and sphericity with a coefficient of determination of 92.69%,
while vacuum pressure was correlated to sphericity and terminal velocity (R2=76.74
%). The developed models were verified by the use of different seeds and seed
distribution was evaluated.

References

  • Box, G. E. P. and N. Draper, 1987. Empirical Model-Building and Response Surfaces. John Wiley & Sons, New York. 669 p.
  • International Organization for Standardization (1984). Sowing equipment- Test methods- Part1: Single seed drills (precision drills) 7256/1.
  • Karayel D; Barut Z; Özmerzi A (2004). Mathematical Modelling of Vacuum Pressure on a Precision Seeder. Biosystems Engineering, 87 (4): 437-444.
  • Moody F H; Hancock J H; Wilkerson J B (2003). Evaluating planter performance-cotton seed placement accuracy. ASAE Paper No. 03 1146, St Joseph, Michigan, USA
  • Onal, O., I. Onal (2009). Development of a computerized measurement system for in-row seed spacing accuracy. Turkish Journal of Agriculture and Forestry 33(2009) 99-109.
  • Singh R C; Singh G; Saraswat D C (2005). Optimisation of design and operational parameters of a pneumatic seed metering device for planting cottonseeds. Biosystems Engineering, 92(4), 429-438.
  • Srivastava A K; Goering C E; Rohrbach R P (1993). Engineering Principles of Agricultural Machines. ASAE, St. Joseph, Michigan, USA
  • St Jack D; Dianne C. Hesterman, Andrew L. Guzzomi (2013). Precision metering of Santalum spicatum (Australian Sandalwood) seeds. Biosystems Engineering 115 (2013): 171-183.
  • Yazgi, A, A. Degirmencioglu. (2007). Optimisation of the seed spacing uniformity performance of a vacuum-type precision seeder using response surface methodology. Biosystems Engineering 97(3): 347-356.
  • Yazgı, A. 2010. Vakumlu Tek Dane Ekimde Optimizasyon ve Makina Performansının Matematiksel Modellemesi (Optimization of the Precision Seeding and Mathematical Modeling of the Machine Performance). Unpublished PhD. Dissertation, 196 p. Graduate School of Natural and Applied Sciences, Ege University, Bornova-Izmir/Turkey, 2010.
There are 10 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Arzu Yazgı

Adnan Değirmencioğlu This is me

Publication Date June 22, 2016
Submission Date January 11, 2016
Acceptance Date March 30, 2016
Published in Issue Year 2016

Cite

APA Yazgı, A., & Değirmencioğlu, A. (2016). Development of Prediction Functions for a Maximized Precision Seeding Performance Based on Optimized Variables. Journal of Agriculture Faculty of Ege University, 53(2), 179-187. https://doi.org/10.20289/zfdergi.389108

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