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2022-03-24

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cc-by (c) Buchaillot, Ma. Luisa et al., 2022
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/214347

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

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https://doi.org/10.1007/s00425-022-03867-6

Abstract

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 (Vc,max) and maximum electron transport rate supporting RuBP regeneration (Jmax), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these parameters could be estimated using rapid and non-destructive leaf spectroscopy techniques. This study compared four different advanced regression models (PLS, BR, ARDR, and LASSO) to estimate Vc,max and Jmax based on leaf reflectance spectra measured with an ASD FieldSpec4. Two leguminous species were tested under different controlled environmental conditions: (1) peanut under different water regimes at normal atmospheric conditions and (2) soybean under high [CO2] and high night temperature. Model sensitivities were assessed for each crop and treatment separately and in combination to identify strengths and weaknesses of each modeling approach. Regardless of regression model, robust predictions were achieved for Vc,max (R2 = 0.70) and Jmax (R2 = 0.50). Field spectroscopy shows promising results for estimating spatial and temporal variations in photosynthetic capacity based on leaf and canopy spectral properties.

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Anàlisi de regressió, Estadística bayesiana, Fotosíntesi, Soia, Cacauet

Subject (English)

Regression analysis, Bayesian statistical decision, Photosynthesis, Soybean, Peanuts

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Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)

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BUCHAILLOT, Ma. Luisa, et al. Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models. Planta. 2022. Vol. 255, num. 1-19. ISSN 0032-0935. [consulted: 13 of August of 2026]. Available at: https://hdl.handle.net/2445/214347

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