Laboratory measurement of seed drill seed spacing and velocity of fall of seeds using high-speed camera system

Karayel, Davut; Wiesehoff, Marcel; Özmerzi, Aziz; Müller, Joachim

doi:10.1016/j.compag.2005.05.005

Cited by 114 publications

(76 citation statements)

References 15 publications

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“…They use the common technique of measuring time interval between seed drops and location where each seed drops from the seeding unit. Nevertheless, the performance of these systems was evaluated with the same seed spacing measurements obtained using the sticky belt test stand as a reference method (Kocher et al, 1998;Lan et al, 1999;Panning et al, 2000;Karayel et al, 2006;Navid et al, 2011). Considering the fact that the proposed acoustic system uses the same technique, which is used by sticky belt stand as a reference method, in comparison with above mentioned systems, better performance of the acoustic system is expected.…”

Section: Discussionmentioning

confidence: 99%

“…A 2-cm narrow trajectory was settled on the belt to predistribution of seeds is measured with a digital camera for recording of passing seeds and a computer for data processing and monitoring. Results from this machine vision technique have shown a good accuracy (Alchanatis et al, 2002;Karayel et al, 2006;Navid et al, 2011), but machine vision systems require defined and consistent lighting and advanced calibration (Brosnan & Sun, 2004). In addition, results of computer vision are influenced by the quality of the captured images and artificial lighting might be required for the proper imaging (Singh et al, 2013).…”

Section: Testing Rigmentioning

confidence: 99%

“…Moreover, significant simplicity and low cost of proposed acoustic system is also expected in comparison with opto-electronic and machine vision systems; such that opto-electronic seeds spacing determination systems are costly and include complex hardware and software (Önal & Önal, 2009). Also, the machine vision systems require package of software and hardware to capture the images of seeds, to segment the seeds from the background of the image, and to calculate the spacing between two seeds (Alchanatis et al, 2002;Karayel et al, 2006;Navid et al, 2011).…”

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

Karimi

Navid

Mahmoudi

2015

Span. j. agric. res.

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Testing Rigmentioning

confidence: 99%

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confidence: 99%

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

Karimi

Navid

Mahmoudi

2015

Span. j. agric. res.

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“…For this purpose, they used a high-speed camera and image processing system for measuring the seed uniformity of the seeder. Karayel et al (2006) determined the in-row seed distribution uniformity of wheat and soybean with 96% accuracy using a 750 frames per second (fps) speed camera compared to sticky belt measurements under laboratory conditions.…”

Section: Introductionmentioning

confidence: 99%

Determination of in-row seed distribution uniformity using image processing

Çakır¹,

Aygün²,

Yazgi³

et al. 2016

Turk J Agric For

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The objective of this study was to determine the seed distribution uniformity of seeding machines using a low sensitivity (maximum 300 frames per second (fps)) high-speed camera and image processing method for corn, cotton, and wheat seeds under laboratory conditions. For this purpose, a high-speed camera with 100, 200, and 300 fps was used to measure the seed drop from the seeding tube onto the sticky belt. Video images then were transferred to the image processing algorithm, from which seed distribution can be calculated. The calculated measurements were compared statistically with the measurements obtained from sticky belt tests. According to the results for determining corn and cotton seed spacing by high-speed camera, the camera was successful only for corn seeds. For cotton seeds, camera readings were significantly different from the readings from the sticky belt due to the fact that capturing the cotton seed trajectory was not sufficient compared to the corn seed trajectory. Measuring the wheat seed spacing by high-speed camera was impossible with lower speeds of the camera. Wheat kernels could not be captured successfully by the camera at speeds of 100 and 200 fps. Therefore, only 300 fps speed was used to measure the seed spacing of wheat.

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“…Kocher et al (1998) and Lan et al (1999) used opto-electronic sensor system to measure sugar beet seed spacing. On the other hand, Karayel et al (2006) used a high speed camera system to measure the spacing for wheat seeds which flow in much higher rates than sugar beets.…”

Section: Introductionmentioning

confidence: 99%

Estimation of mass flow of seeds using fibre sensor and multiple linear regression modelling

Al-Mallahi

Kataoka

2013

Computers and Electronics in Agriculture

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A new methodology to estimate the mass of grain seeds, which flow in the shape of clumps, was suggested in this paper. The methodology used an off-the-shelf digital fibre sensor to detect the behaviour of the clumps and multiple linear regression modelling to estimate the mass by the parameters detected by the sensor which were the length and the density of the clumps.An indoor apparatus was used for modelling which resembled the sowing process using the grain drill. A fluted roller was installed in the apparatus to regulate the flow of seeds. It was rotated by a motor at 2, 4 and 6 rpm to cover all the possible mass flow rates which might occur during actual sowing. Modelling was based on several assumptions, such as the linearity between the sensor parameters and the mass.Although errors were observed while estimating each clump independently, the methodology was able to estimate the mass of a continuous flow of seed clumps. The average difference in estimation at 4 rpm was 0.9%, while there was overestimation at 2 rpm and underestimation at 6 rpm resulting in an overall estimation error of 5.3%.These results showed that the digital fibre sensor could be used for estimating mass flow of seeds at variable sowing rates within the speed limits of the grain drill.

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Laboratory measurement of seed drill seed spacing and velocity of fall of seeds using high-speed camera system

Cited by 114 publications

References 15 publications

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

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

Determination of in-row seed distribution uniformity using image processing

Estimation of mass flow of seeds using fibre sensor and multiple linear regression modelling

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