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Agronomy 2019, 9(2), 65;

Prospects for Measurement of Dry Matter Yield in Forage Breeding Programs Using Sensor Technologies

Hamilton Center, Agriculture Victoria Research, Hamilton, Victoria 3300, Australia
School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Victoria 3010, Australia
Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia
School of Applied Systems Biology, La Trobe University, Bundoora, Victoria 3086, Australia
Author to whom correspondence should be addressed.
Received: 4 January 2019 / Revised: 21 January 2019 / Accepted: 31 January 2019 / Published: 1 February 2019
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Increasing the yield of perennial forage crops remains a crucial factor underpinning the profitability of grazing industries, and therefore is a priority for breeding programs. Breeding for high dry matter yield (DMY) in forage crops is likely to be enhanced with the development of genomic selection (GS) strategies. However, realising the full potential of GS will require an increase in the amount of phenotypic data and the rate at which it is collected. Therefore, phenotyping remains a critical bottleneck in the implementation of GS in forage species. Assessments of DMY in forage crop breeding include visual scores, sample clipping and mowing of plots, which are often costly and time-consuming. New ground- and aerial-based platforms equipped with advanced sensors offer opportunities for fast, nondestructive and low-cost, high-throughput phenotyping (HTP) of plant growth, development and yield in a field environment. The workflow of image acquisition, processing and analysis are reviewed. The “big data” challenges, proposed storage and management techniques, development of advanced statistical tools and methods for incorporating the HTP into forage breeding systems are also reviewed. Initial results where these techniques have been applied to forages have been promising but further research and development is required to adapt them to forage breeding situations, particularly with respect to the management of large data sets and the integration of information from spaced plants to sward plots. However, realizing the potential of sensor technologies combined with GS leads to greater rates of genetic gain in forages. View Full-Text
Keywords: forage dry matter yield; high-throughput phenotyping; automation; imaging and image analysis forage dry matter yield; high-throughput phenotyping; automation; imaging and image analysis

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Gebremedhin, A.; Badenhorst, P.E.; Wang, J.; Spangenberg, G.C.; Smith, K.F. Prospects for Measurement of Dry Matter Yield in Forage Breeding Programs Using Sensor Technologies. Agronomy 2019, 9, 65.

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