Online laboratory evaluation of seeding-machine application by an acoustic technique

Abstract

RESEARCH ARTICLE OPEN ACCESSsliding or bouncing seeds on the sticky belt, especially at high belt speed (Kocher et al., 1998). However, it is convenient and has been tried by some researchers for evaluating a single row seed metering mechanism (Panning, 1997;Molin et al., 1998;Singh et al., 2005;Anantachar et al., 2010;Zhan et al., 2010;Li et al., 2012;Önal et al., 2012;Yasir et al., 2012). Among other alternative techniques, an opto-electronic seed spacing determination system has been developed (Kocher et al., 1998;Lan et al., 1999) which determines time intervals between seeds by detecting seed drop events relative to the planter. Panning et al. (2000) found that the spacing measured from the optoelectronic system was 15 mm greater than the theoretical one and the inaccuracy of the opto-electronic sensor was related to seeds with diameter <3 mm.With current advances in digital video technology, machine vision has shown potential as a sensing technology for seeding performance evaluation. In this case, spatial AbstractResearchers and planter manufacturers have been working closely to develop an automated system for evaluating performance of seeding. In the present study, an innovative use of acoustic signal for laboratory evaluation of seeding-machine application is described. Seed detection technique of the proposed system was based on a rising voltage value that a microphone sensed in each impaction of seeds to a steel plate. Online determining of seed spacing was done with a script which was written in MATLAB software. To evaluate the acoustic system with desired seed spacing, a testing rig was designed. Seeds of wheat, corn and pelleted tomato were used as experimental material. Typical seed patterns were positioned manually on a belt stand with different spacing patterns. When the belt was running, the falling seeds from the end point of the belt impacted to the steel plate, and their acoustic signal was sensed by the microphone. In each impact, data was processed and spacing between the seeds was automatically obtained. Coefficient of determination of gathered data from the belt system and the corresponding seeds spacing measured with the acoustic system in all runs was about 0.98. This strong correlation indicates that the acoustic system worked well in determining the seeds spacing. Additional key words: seeds spacing; seed detection technique; acoustic system; acoustic signal; impact plate. Abbreviations used: MAPE (mean absolute percentage error); TSW (thousand seed weight). Citation: Karimi, H.; Navid, H.; Mahmoudi, A. (2015). Online laboratory evaluation of seeding-machine application by an acoustic technique.

Research progress of small size seed metering devices

“…The keywords that emerged during the rapid development stage are "performance", "optimization", "spacing uniformity", "uniformity", and "simulation". These representative keywords indicate that the content of scientific research in recent years has focused on the simulation, consistency, operability and practical performance of machines [8,9].…”

Design and analysis of a performance monitoring system for a seed metering device based on pulse width recognition

“…The change in the equivalent dielectric constant as the seeds pass through the detection area of the capacitance sensor causes a change in the capacitance output value Complex ambient light and dust have less effect on capacitive sensors The method could detect more than one seed at a time Capacitance sensors are easily influenced by the seed water content, machine vibrations, temperature, and parasitic capacitance Seeds with smaller volumes do not generate detectable variation in the dielectric coefficient [13][14][15][16][17] Machine vision…”

“…Several studies have reported that machine vision and image processing methods achieved different degrees of success [13,14]. However, these methods suffer many disadvantages, such as the need for complex calibration and data processing operations, expensive cameras and software, high labor requirements, artificially lit environments, and long process times [15][16][17]. The machine vision method can effectively monitor two or more simultaneously falling seeds, but the method is extremely demanding in terms of the monitoring environment, thus limiting its application in agricultural production [11].…”

The Application of Optoelectronic Elements to Control the Sowing Process

“…There have been scientific, patent and specialist publications giving examples of solutions based on optical sensors [8]. The detectability of various sensors was tested in earlier studies [9][10][11]. A linear image intensifier could be used as an alternative, but this solution is still expensive and requires complex software for image analysis [12].…”