The use of high-throughput phenotypic systems and non-destructive imaging is widely regarded as key technologies for solving excellent gen-phenotype interaction research in crops, which can allow scientists and breeders to carry out crop phenotypes under different environmental conditionsResearch.Many phenotypic studies have used the model plant Arabidopsis to perform optimization experiments.Below we mainly take the C4 model classic plants - corn and sorghum as examples to conduct a specific analysis of phenotypic cases.
Corn (scientific name: Zea mays) is an annual herbaceous plant of the family Grass family and is the most important food crop with the highest total output in the world.In order to expand corn production in modern times, private companies have developed the ability to transform corn growth and face the environment through genetic reordering, and evolved super corn with huge yields.Make the United States the world's largest exporter of corn.Use: Genetically modified corn is used as feed to feed cattle and pigs, and is made into corn starch and indirectly made into food and seasonings for human consumption.High-throughput imaging systems can accurately identify and distinguish specific phenotypic traits related to corn growth.The software provides powerful and minimalist R scripts to allow other users' imaging systems to easily extract useful data, thereby alleviating bottlenecks in phenotypic screening and faster follow-up analysis of multiple genotypes for important crops.
Parameters that focus on the field of corn plant type research:Plant canopy width, vertical height, density, symmetry, projected leaf area, spatial volume, plant structure, leaf angle, internode length, leaf length
Parameters that focus on the field of corn response to biological stress:Vertical height, projected leaf area, spatial volume, leaf color, leaf lesions, plant structure, leaf angle, internode length, leaf length
Parameters that focus on the field of corn response to abiotic stress:The relative moisture content distribution of the whole plant, plant structure, leaf angle, internode length, leaf length, vertical height, projected leaf area, spatial volume, leaf color, projected leaf area, spatial volume
Parameters that focus on the field of corn yield research:Plant canopy width, vertical height, spatial volume (biomass), corn shaft diameter, corn shaft thickness, corn seed maturity, and traits.
Corn can be calculated as the leaf length and direction of a single leaf, as shown in the figure below.
Source: Lloren, Cabrera-BosquetETA., new pH should be mentioned by log i (2016)
The above article analyzes and extracts the skeleton data of different varieties of corn plant through 3D imaging on the top and sides, and further calculates a variety of parameters including leaf inclination.
In another study, PlantAccelerator at the University of Adelaide, Australia®A phenotypic study of sorghum was conducted, which is similar to corn and is also a C4 plant.They performed N treatments and water-controlled treatments at varying concentrations, using imaging and found parameters related to stress tolerance, such as diurnal leaf curls and leaf area index.Imaging at different spectral ranges was used to monitor plant composition, chlorophyll and moisture content.Phenotype image analysis accurately measures plant biomass.Data collection also obtained responses from different sorghum varieties to experimental treatment and modeled.
According to various correlation analyses, the projected area of the plant showed a positive correlation with biomass.
Different concentrations of NPhenotypic images of sorghum (plant size, color analysis)
Phenotype of sorghum under drought treatment (plant morphology, biomass, leaf area, leaf curl)
Near infrared reflection
(NIR) Analysis is a good predictor of moisture content and leaf thickness, and is related to plant moisture content.
Color analysis images show that the foliar color and chlorophyll content are related
If it is an ex vivo ear, we can take rice as an example to accurately separate each seed and then perform further phenotypic analysis.
If the ears of the plant are measured in bulk, laser 3D can be usedmethod combined with RGBImaging, typing spike shape, spike angle and other parameters.
