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Active Optical Sensing for Production Agriculture and High-Throughput Phenotyping.
See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Symposium--Evolution of Biophysical Measurements: Legacy of the US Water Conservation Lab and Advances in Rapid Phenotyping
Monday, November 7, 2016: 2:55 PM
Phoenix Convention Center North, Room 231 C
Kyle H. Holland, Holland Scientific, Lincoln, NE
Abstract:
Active Optical Sensor (AOS) technology has a long history that spans for almost eight decades. Early use of AOS technology was primarily driven by production agriculture, mainly for selectively thinning plant density in vegetable crops. However, the last decade has seen AOS technology adopted for use in agronomic research. Most recently, AOS technology has evolved for use in high throughput phenotypic sensing applications. These applications require rapid acquisition of plant canopy physical and physiological parameters at plot and field scales. While AOS technologies can provide useful information relating to plant biophysical characteristics, simultaneous measures of other descriptive parameters (upwelling/downwelling PAR, humidity, canopy/ambient temperature, fAPAR, etc…) help provide a clearer picture of plant response to biotic and abiotic stressors. Additionally, information obtained can assist in early identification of desired genetic traits and the degree to which they are expressed. Identifying these traits and their expression can provide higher efficiency in genetic selection for breeding programs and define better management practices for genetics and agrochemicals currently on the market. While the extensive amount of data recorded by these sensing systems is efficacious for early trait identification and differentiation, it is imperative that integrated management platforms be implemented in conjunction with sensing systems. Effectively managing geospatial multi-parameter time series data acquired with high-throughput AOS sensing technologies require a complex geographical information system database. This system should rapidly process collected geospatial data assigned to defined zones with specific field characteristics or plots of known treatment. Acquired data can then be utilized to gain insight through a wide variety of integrated exploratory analytics. Integrating big data in multi-dimension will provide greater understanding of genetic and/or treatment response to micro field environments and the trial plot alike.
See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Symposium--Evolution of Biophysical Measurements: Legacy of the US Water Conservation Lab and Advances in Rapid Phenotyping