Prediction of Seed Flow Rate of a Multi-Slot Rotor Feeding Device of a Corn Planter

ماشین های کشاورزی

Article 2, Volume 11, Issue 1 - Serial Number 21, 2021, Pages 17-27   

Document Type: Research Article-en

DOI: 10.22067/jam.v11i1.79992

Authors

H. Balanian¹; S. H. Karparvarfard^{* 1}; A. Mousavi Khanghah²; M. H. Raoufat¹; H. Azimi-Nejadian¹

¹Department of Biosystem Engineering, College of Agriculture, Shiraz University, Shiraz, Iran

²Department of Food Science, Faculty of Food Engineering, State University of Campinas (UNICAMP), 13083-862 Campinas, São Paulo, Brazil

Abstract

In this study, a model was developed for predicting the seeding rate of corn seeds of a typical row-crop planter equipped with a multi-slot feeding device. To this, nine multi-slot rotors (with 4, 5 and 6 slots in three angles of mouth including 23°, 25° and 27°) were designed and manufactured. Tests were carried out at four levels of angular velocity of 40, 52, 62 and 78 rpm on grease belt moving at constant speed of 3.5 km h^-1. Tests were completed in three replications. Discharge flow rate was measured and recorded for each treatment. The data were used to develop a model which can be used for predicting the seeding rate under various numbers of slot, mouth angle and rotor angular velocity. According to the results, angle mouth of slots, number of slots, angular velocity and the dual interaction between them showed increasing effects on weight flow rate of seeds (P-value<0.01). In the next step, raw data were used to develop the two desired models: based on the dimensional analysis technique and response surface methodology (RSM). The models outputs were compared to experimental data. The standard error of estimate for flow rate for dimensional analysis and response surface methodology (RSM) were 68.13 mm³ s^-1 and 475.59 mm³ s^-1, respectively. The dimensional analysis model was closer to experimental data rather than the RSM method. Thus, to predict the volume flow rate of seed, the dimensional analysis model is recommended.

Keywords

corn; Dimensional analysis; Response surface methodology; row planting

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