Details

Autor(en) / Beteiligte

• Koller, Adrian A.
• Taylor, Randy K.
• Raun, William B.
• Weckler, Paul R.
• Buser, Michael D.

Titel

Modelling and validation of maize seed orientation by pushing

Ist Teil von

• Biosystems engineering, 2016-11, Vol.151, p.338-349

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2016

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Oriented planting of maize seed has the potential for yield gains because of optimized light interception in a structured canopy. While research into the agronomic aspects of seed oriented planting has progressed over the past few years, little work has been done with respect to a mechanization solution to seed oriented planting. This study was conducted to determine the feasibility of seed oriented planting by application of the part orientation by pushing concept. Three-dimensional laser scans of 15 kernels of four hybrids with differing average seed shapes ranging from cuboid to discoidal were obtained. Computational analysis of the 3D shape data was conducted to predict the seed orientation by pushing. Analysis of the radius and pushing functions showed that each kernel shape exhibits three clearly identifiable stable angular orientations. Sixty seeds of each of the hybrids from the same population were then tested in a bench-top mechanism emulating the orientation by pushing. The stable point mean directions could be predicted to within less than 1° for 8 out of 12 stable points on the four hybrid kernel shapes and to within 5° for the remaining four. Formal comparison showed that there was no significant difference between prediction and measurement for any of the stable point mean directions. Comparison across hybrids though showed that the stable point mean direction depends on the average kernel shape, which entails that some hybrids may be more or less suitable for seed orientation by pushing. •Exploration of mechanization aspects of seed oriented corn planting.•Proposed mechanization concept exploits ideas of planar part pushing.•Orientation performance predicted based on analysis of 3D kernel shape.•Predictions compared to in-mechanism test results.•Kernel orientation is highly predictable, may pose a viable mechanization approach.