Fig 1.
A schematic diagram of the image analysis process.
Fig 2.
A schematic diagram of the RGB color image structure.
Table 1.
Differential classification of different Chinese cabbage varieties.
Fig 3.
Population basic seedling classification.
Fig 4.
Population quality classification process in different periods.
Fig 5.
Structure of population quality evaluation BPNN model.
Fig 6.
Performance comparison results of different algorithms.
Fig 7.
Correlation results of image feature values and agricultural parameters.
Note: DW refers to the dry weight of the above-ground portion of the crop, TN represents the number of shoots in the field, LAI is the leaf area index, NC is the leaf area index, SS, RS, and HS stand for the seedling stage, rosette stage, and heading stage, respectively.
Fig 8.
Cumulative correlation between each indicator and nitrogen.
Fig 9.
Correlation between image color features and various indicators.
Fig 10.
Estimation effects of multiple regression model on DW, LAI, TN, and NC.
Table 2.
Estimation effects of the multiple regression model.
Fig 11.
The relationship between the predicted and actual values of agricultural parameters at different nitrogen levels.
Fig 12.
The correlation between planting density and yield.
Fig 13.
The relationship between agricultural parameters and output in the seedling stage.
Fig 14.
The relationship between agricultural parameters and output in the rosette stage.
Fig 15.
The relationship between agricultural parameters and output in the heading stage.
Fig 16.
Population quality evaluation results in the seedling stage.
Fig 17.
BPNN model evaluation results of population quality in different periods.