Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models.

ABSTRACT:

Main conclusion

By combining hyperspectral signatures of peanut and soybean, we predicted V_cmax and J_max with 70 and 50% accuracy. The PLS was the model that better predicted these photosynthetic parameters. One proposed key strategy for increasing potential crop stability and yield centers on exploitation of genotypic variability in photosynthetic capacity through precise high-throughput phenotyping techniques. Photosynthetic parameters, such as the maximum rate of Rubisco catalyzed carboxylation (V_c,max) and maximum electron transport rate supporting RuBP regeneration (J_max), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these pa

SUBMITTER: Buchaillot ML 

PROVIDER: S-EPMC8948130 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature