Early indicators of declining pasture persistence: sensor-based tools for paddock-scale identification
Chinthaka Jayasinghe
A * , Anna Thomson B , Kevin Smith A C and Joe Jacobs B C D
A
B
C
D
Abstract
Pasture persistence is the ability to maintain plant density and dry matter production of sown species throughout the life of a sward, and it is important for the long-term productivity and sustainability of pasture-based animal production systems. Identifying early indicators of declining pasture persistence enables livestock farmers to implement timely management strategies to use their land more productively and sustainably. However, there are significant gaps in current knowledge in which early indicators of pasture decline should be monitored, when, and at what scale. Traditionally, persistence assessment rely on manual pasture measurements, which are either subjective and labour-intensive or lack timeliness for decision making and are unlikely to allow livestock producers to identify the symptoms of decline in sown pasture before it becomes a significant issue. With the rapid development of sensors and image processing algorithms, remote sensing platforms show promise in reducing the time frame for phenotyping early indicators of declining pasture persistence. This review discussed which dynamic morphological, and physiological traits, along with biological processes, could be considered reliable early indicators of persistence risk in sown pastures, as well as risk factors that are likely to put a sward at a disadvantage with regards to longevity, and how high-throughput phenotyping (HTP) can measure these indicators and risk factors. This study addressed the knowledge gap on monitoring early indicators of declining pasture persistence using remote sensing technologies, and may provide valuable insights that could be used to establish an early warning system for persistence risk.
Keywords: high throughput phenotyping, pasture-based livestock systems, pasture decline, pasture persistence, pasture risk factors, persistence indicators, remote sensing, sensors.
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