1. Sensor-based algorithms to improve barley nitrogen efficiency in Queensland
- Author
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Madan Gupta and Paul Theophile Epee Misse
- Subjects
0106 biological sciences ,Canopy ,Nutrient management ,Crop yield ,food and beverages ,chemistry.chemical_element ,Forage ,04 agricultural and veterinary sciences ,01 natural sciences ,Nitrogen ,Normalized Difference Vegetation Index ,Crop ,chemistry ,040103 agronomy & agriculture ,0401 agriculture, forestry, and fisheries ,BARLEY GRAIN ,General Agricultural and Biological Sciences ,Algorithm ,010606 plant biology & botany ,Mathematics - Abstract
The low efficiency of nitrogen (N) fertilizers impels the innovation of current N management strategies in cereal production. Site specific N management is an emerging field providing novel alternatives to current nutrient management practices through canopy sensing. Barley N use efficiency can be enhanced with GreenSeeker proximal sensors, whose optimal utilization requires algorithms. The design of such algorithms required four N rates (0, 50, 100 and 150 kg N ha-1) and in-season sensing of barley canopy reflectance using a handheld GreenSeeker sensor as well as crop N analysis. The N rates produced enough variability in yields, N uptake and normalized difference vegetation index (NDVI) readings together with strong determination coefficients between in-season NDVI values on one hand and on the other hand in-season N uptake (R2=0.68, p
- Published
- 2018
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