Estimation in the Field of Individual Perennial Ryegrass Plant Position and Dry Matter Production Using a Custom‐Made High‐Throughput Image Analysis Tool

• Published in: Crop science Vol. 55; no. 6; pp. 2910 - 2917
• Main Authors: Hunt, Chris L., Jones, Chris S., Hickey, Michael J., Koolaard, John P., West, John, Hatier, Jean‐Hugues B.
• Format: Journal Article
• Language: English
• Published: The Crop Science Society of America, Inc 01-11-2015
• ISSN: 0011-183X; 1435-0653
• DOI: 10.2135/cropsci2015.02.0125

ABSTRACT
Perennial ryegrass (Lolium perenne L.) is widely used in grazing systems across the temperate world. Continued persistence of ryegrass pastures depends on our ability to further our understanding of the key traits or attributes responsible for improved plant performance. To this end, plant improvement is highly dependent on precise phenotyping capabilities. However, in‐field phenotyping is labor intensive, relies on experienced operators, and is often considered cost prohibitive. The aim of this study was to determine the accuracy of an image analysis tool developed to locate and estimate dry matter (DM) production of individual plants growing in the field. Fifty plants were used to develop the image analysis tool and another 1100 to determine its accuracy. Dry matter was measured by weighing oven‐dried harvested plant material and estimated both with the image analysis tool and by visual scoring. The image analysis tool was faster and estimates of plant area were more highly correlated with measured DM values, potentially capturing 25% more of the variation, than those from visual growth scores. The tool was able to effectively locate and distinguish between neighboring plants. The accuracy of the tool was greatest for production values below 15 g, and the tool would benefit from further development to improve accuracy above this threshold.