7 March 2014 High throughput imaging and analysis for biological interpretation of agricultural plants and environmental interaction
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High throughput (HT) phenotyping of crops is essential to increase yield in environments deteriorated by climate change. The controlled environment of a greenhouse offers an ideal platform to study the genotype to phenotype linkages for crop screening. Advanced imaging technologies are used to study plants’ responses to resource limitations such as water and nutrient deficiency. Advanced imaging technologies coupled with automation make HT phenotyping in the greenhouse not only feasible, but practical. Monsanto has a state of the art automated greenhouse (AGH) facility. Handling of the soil, pots water and nutrients are all completely automated. Images of the plants are acquired by multiple hyperspectral and broadband cameras. The hyperspectral cameras cover wavelengths from visible light through short wave infra-red (SWIR). Inhouse developed software analyzes the images to measure plant morphological and biochemical properties. We measure phenotypic metrics like plant area, height, and width as well as biomass. Hyperspectral imaging allows us to measure biochemcical metrics such as chlorophyll, anthocyanin, and foliar water content. The last 4 years of AGH operations on crops like corn, soybean, and cotton have demonstrated successful application of imaging and analysis technologies for high throughput plant phenotyping. Using HT phenotyping, scientists have been showing strong correlations to environmental conditions, such as water and nutrient deficits, as well as the ability to tease apart distinct differences in the genetic backgrounds of crops.
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Hyundae Hong, Hyundae Hong, Jasenka Benac, Jasenka Benac, Daniel Riggsbee, Daniel Riggsbee, Keith Koutsky, Keith Koutsky, "High throughput imaging and analysis for biological interpretation of agricultural plants and environmental interaction", Proc. SPIE 9024, Image Processing: Machine Vision Applications VII, 90240E (7 March 2014); doi: 10.1117/12.2042562; https://doi.org/10.1117/12.2042562

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