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

Cilt: 53 Sayı: 2 22 Haziran 2016
Arzu Yazgı *, Adnan Değirmencioğlu
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Development of Prediction Functions for a Maximized Precision Seeding Performance Based on Optimized Variables

Öz

 

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.

Anahtar Kelimeler

Central composite design,physical properties,seed,performance,mathematical modeling

Kaynakça

  1. Box, G. E. P. and N. Draper, 1987. Empirical Model-Building and Response Surfaces. John Wiley & Sons, New York. 669 p.
  2. International Organization for Standardization (1984). Sowing equipment- Test methods- Part1: Single seed drills (precision drills) 7256/1.
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  5. 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.
  6. 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.
  7. Srivastava A K; Goering C E; Rohrbach R P (1993). Engineering Principles of Agricultural Machines. ASAE, St. Joseph, Michigan, USA
  8. St Jack D; Dianne C. Hesterman, Andrew L. Guzzomi (2013). Precision metering of Santalum spicatum (Australian Sandalwood) seeds. Biosystems Engineering 115 (2013): 171-183.
  9. 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.
  10. 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.

Kaynak Göster

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
AMA
1.Yazgı A, Değirmencioğlu A. Development of Prediction Functions for a Maximized Precision Seeding Performance Based on Optimized Variables. Journal of Agriculture Faculty of Ege University. 2016;53(2):179-187. doi:10.20289/zfdergi.389108
Chicago
Yazgı, Arzu, ve Adnan Değirmencioğlu. 2016. “Development of Prediction Functions for a Maximized Precision Seeding Performance Based on Optimized Variables”. Journal of Agriculture Faculty of Ege University 53 (2): 179-87. https://doi.org/10.20289/zfdergi.389108.
EndNote
Yazgı A, Değirmencioğlu A (01 Haziran 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.
IEEE
[1]A. Yazgı ve A. Değirmencioğlu, “Development of Prediction Functions for a Maximized Precision Seeding Performance Based on Optimized Variables”, Journal of Agriculture Faculty of Ege University, c. 53, sy 2, ss. 179–187, Haz. 2016, doi: 10.20289/zfdergi.389108.
ISNAD
Yazgı, Arzu - Değirmencioğlu, Adnan. “Development of Prediction Functions for a Maximized Precision Seeding Performance Based on Optimized Variables”. Journal of Agriculture Faculty of Ege University 53/2 (01 Haziran 2016): 179-187. https://doi.org/10.20289/zfdergi.389108.
JAMA
1.Yazgı A, Değirmencioğlu A. Development of Prediction Functions for a Maximized Precision Seeding Performance Based on Optimized Variables. Journal of Agriculture Faculty of Ege University. 2016;53:179–187.
MLA
Yazgı, Arzu, ve Adnan Değirmencioğlu. “Development of Prediction Functions for a Maximized Precision Seeding Performance Based on Optimized Variables”. Journal of Agriculture Faculty of Ege University, c. 53, sy 2, Haziran 2016, ss. 179-87, doi:10.20289/zfdergi.389108.
Vancouver
1.Arzu Yazgı, Adnan Değirmencioğlu. Development of Prediction Functions for a Maximized Precision Seeding Performance Based on Optimized Variables. Journal of Agriculture Faculty of Ege University. 01 Haziran 2016;53(2):179-87. doi:10.20289/zfdergi.389108