Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-10T05:36:30.341Z Has data issue: false hasContentIssue false
  • English
  • Français

Automated Measurement of Maize Stalk Diameter and Plant Spacing

Published online by Cambridge University Press:  01 June 2017

J. S. Schepers ,
K. H. Holland  and
D. D. Francis
J. S. Schepers*
Affiliation:
USDA-ARS retired, 3820 Loveland Dr., Lincoln, Nebraska 68506, USA
K. H. Holland
Affiliation:
Holland Scientific, 6001 S. 58th St., Lincoln, Nebraska 68506, USA
D. D. Francis
Affiliation:
USDA-ARS retired, 3820 Loveland Dr., Lincoln, Nebraska 68506, USA
*
†E-mail: james.schepers@gmail.com
Get access

Abstract

Crop phenotype is usually expressed in terms of characteristics like plant height, leaf architecture and leaf area index (LAI). In the case of maize, stalk diameter is seldom quantified because its measurement does not readily lend itself to automation. Justification for automating the measurement of stalk diameter and plant spacing is based on the finding that stalk diameter was able to account for about 65% of the variability in maize yield per plant in three irrigated field studies. A high-speed reflectance sensor and simulation apparatus was developed to explore the potential for automating maize stalk diameter assessment. The prototyped system accurately measured both stalk diameter and plant spacing in the laboratory at simulated velocities up to 12 km/h.

Keywords

maizestalk diameterplant spacingelectronic sensing
Type
Crop Sensors and Sensing
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 220 - 223
Copyright
© The Animal Consortium 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Gitelson, AA and Merzlyak, MN 1998. Remote sensing of chlorophyll concentration in higher plant leaves. Advances in Space Research 22, 689–692.Google Scholar
Hummel, JW, Drummond, ST, Sudduth, KA and Krumpelman, MJ 2002. Sensing systems for site-specific assessment of corn plants. In: Proc. 6th Intl. Conf. on Precision Agriculture (cd-rom). ASA, CSSA, and SSSA, Madison, WI.Google Scholar
Kelly, JP, Crain, JL and Raun, WR 2015. By-plant prediction of corn (Zea mays L.) grain yield using height and stalk diameter. Communications in Soil Science and Plant Analysis 46, 564–575.CrossRefGoogle Scholar
Kovács, P and Vyn, TJ 2014. Full-season retrospectives on causes of plant-to-plant variability in maize grain yield response to nitrogen and tillage. Agronomy Journal 106, 1746–1757.Google Scholar
Luck, JD, Pitla, SK and Shearer, SA 2008. Sensor ranging technique for determining corn plant population. ASABE Meeting Presentation Paper No. 084573, Jun. 29-Jul. 2, 2008.Google Scholar
Searle, CL, Kocher, MF, Smith, JA and Blankenship, EE 2008. Field slope effects on uniformity of corn seed spacing for three precision planter metering systems. Biological Systems Engineering: Papers and Publications. Paper 151.Google Scholar
Shi, Y, Wang, N, Taylor, RK and Raun, WR 2015. Improvement of a ground-LiDAR-based corn plant population of spacing measurement system. Computers and Electronics in Agriculture 112, 93–103.CrossRefGoogle Scholar
Sudduth, KA, Birrell, SJ and Krumpelman, MJ 2000. Field evaluation of a corn population sensor. In: Proc. 5th Intl. Conf. on Precision Agriculture (cd-rom). ASA, CSSA, and SSSA, Madison, WI, USA.Google Scholar
Tang, L and Tian, LF 2008. Real-time crop row image reconstruction for automatic emerged corn plant spacing measurement. American Society of Agricultural and Biological Engineers 5 (3), 1079–1087.Google Scholar