# Modeling of Cotton Yield Estimation Based on Canopy Sun-Induced Chlorophyll Fluorescence
## 3 Results
### Construction of the Cotton Yield Estimation Model
#### 3.3.2 Construction of Cotton Yield Estimation Model Based on Canopy SIFy  
The variation in canopy SIFy with respect to the cotton yield estimation model R\({}^{2}\) is shown in Figure 10. In the four key growth periods, the effect of the cotton yield model constructed with RF was the best, and the R\({}^{2}\) was basically 0.90 in each period. The R\({}^{2}\) of the cotton yield model constructed using Ada Boost and Bagging had a significant peak at 14:00-15:00, and the range of R\({}^{2}\) was 0.75-0.85. The model of cotton yield based on BPNN had the worst effect, with an R\({}^{2}\) of less than 0.5. The model R\({}^{2}\) was at its maximum during all four reproductive periods at 14:00-15:00. This indicates that the canopy-based cotton yield model utilizing SIFy at 14:00-15:00 worked best.  
Figure 8: Yield estimation model of cotton based on canopy SIF from 14:00 to 15:00 using Bagging for different growth periods. (**a**): budding period; (**b**): flowering period; (**c**): flowering and boll period; (**d**): boll period. Black samples represent the results of the training set, and blue samples represent the results of the verification set.  
Figure 7: Yield estimation model of cotton based on canopy SIF from 14:00 to 15:00 using RF for different growth periods. (**a**): budding period; (**b**): flowering period; (**c**): flowering and boll period; (**d**): boll period. Black samples represent the results of the training set, and blue samples represent the results of the verification set.  
Figure 9: Yield estimation model of cotton based on canopy SIF from 14:00 to 15:00 using BPNN for different growth periods. (**a**): budding period; (**b**): flowering period; (**c**): flowering and boll period; (**d**): boll period. Black samples represent the results of the training set, and blue samples represent the results of the verification set.  
Yield estimation models for constructing cotton canopy SIFy were based on 14:00-15:00 in the different growth periods (Figures 11-14). Comparison of the four modeling methods demonstrated that the cotton yield model constructed using RF was the most effective (Figure 12). The best modeling effect was achieved by using the RF algorithm in the flowering and boll period (R\({}^{2}\) = 0.9612, RMSE = 66.27 kg.ha\({}^{-1}\), RPD = 4.264, Figure 12c), followed by the flowering period (R\({}^{2}\) = 0.9590, Figure 12b). The modeling effect of the BPNN algorithm in each growth period was not very good (Figure 14), with the maximum R\({}^{2}\) value being 0.4377 (Figure 14a). The Ada Boost algorithm was used to achieve the best modeling effect in the flowering and boll period (R\({}^{2}\) = 0.8796, RMSE = 110.1 kg.ha\({}^{-1}\), RPD = 2.452, Figure 11c), along with the Bagging algorithm which also achieved the best modeling effect in the flowering and boll period (R\({}^{2}\) = 0.8898, RMSE = 102.7 kg.ha\({}^{-1}\), RPD = 2.760, Figure 13c). In the cotton yield model constructed by the four algorithms, the modeling effect was the best in the flowering and boll period, followed by the flowering period, and was the worst in the boll period. A comparison of the modeling results of the different algorithms for the different growth periods revealed that the optimal model was the one that was applied during the cotton flowering and boll period using the RF algorithm.  
Figure 11: Yield estimation model of cotton based on canopy SIFy from 14:00 to 15:00 using Ada Boost for different growth periods. (**a**): budding period; (**b**): flowering period; (**c**): flowering and boll period; (**d**): boll period. Black samples represent the results of the training set, and blue samples represent the results of the verification set.  
Figure 10: Variations in the yield estimation model R\({}^{2}\) of canopy SIFy for cotton in different time periods. (**a**): budding period; (**b**): flowering period; (**c**): flowering and boll period; (**d**): boll period.