Predictive models of drought tolerance indices based on physiological,morphological and biochemical markers for the selection of cotton(Gossypium hirsutum L.)varieties

摘要

The use of tolerant crop varieties is a strategy that mitigates the water deficit effect in a sustainable way.The generation of these varieties is more efficient when variables associated with this tolerance have been identified,since they can facilitate the breeding processes.This study aimed to establish the relationships between water deficit tolerance of four cotton varieties(Nevada-123,Oasis-129,Guatapuri,and Festivalle)and morphological variables(monopodial branches,boll weight,root/shoot ratio,and leaf and root dry matter),physiological variables(relative water content,net photosynthesis,stomatal conductance,electron transport rate,photochemical quenching,photochemical efficiency of PSII,chlorophyll a/b ratio(Chl a/b),C^(12)/C^(13)isotope ratio,and electrolyte leakage),and biochemical variables(contents of sugars,proline,carotenoids,and malondialdehyde).Furthermore,calibrated predictive models of the drought tolerance indices were developed based on the key variables identified.For this purpose,a pot experiment was established where plants were subjected to a moderate or severe water deficit during the blooming stage for 12 days.The stress tolerance index(STI)and mean productivity(MP)were calculated.For the evaluated variables,the differences between well-watered and water deficit plants(Δ)were calculated and ANOVA,partial least squares,Pearson’s correlation,and multiple linear regression analyzes were performed.A model was generated that explained 95% of the STI and was composed of Δmalondialdehyde,Δproline,and Δboll weight.For MP,the model was comprised of Δstomatal conductance,Δroot/shoot ratio,and ΔChl a/b,and explained 89% of the MP.The analysis of the assessed variables allowed the identification of key variables and the development of calibrated predictive models that can be used in screening to obtain cotton varieties with different levels of water deficit tolerance.