Salt tolerance mechanisms in the Lycopersicon clade and their trade-offs

Abstract

Salt stress impairs growth and yield in tomato, which is mostly cultivated in arid and semi-arid areas of the world. A number of wild tomato relatives (Solanum pimpinellifolium, S. pennellii, S. cheesmaniae and S. peruvianum) are endemic to arid coastal areas and able to withstand higher concentration of soil salt concentrations, making them a good genetic resource for breeding efforts aimed at improving salt tolerance and overall crop improvement. However, the complexity of salt stress response makes it difficult to introgress tolerance traits from wild relatives that could effectively increase tomato productivity under high soil salt concentrations. Under commercial production, biomass accumulation is key for high fruit yields, and salt tolerance management strategies should aim to maintain a favourable plant water and nutrient status. In this review, we first compare the effects of salt stress on the physiology of the domesticated tomato and its wild relatives. We then discuss physiological and energetic trade-offs for the different salt tolerance mechanisms found within the Lycopersicon clade, with a focus on the importance of root traits to sustain crop productivity.

Keywords: Crop improvement; salinity stress; tomato wild relatives.

Figure 1.

Root (A) and shoot (B) dry weight and root-to-shoot ratio (C) from a salt tolerance screening of the tomato wild relatives S. chilense (accessions LA2931, LA3115), S. galapagense (accessions LA1400, LA1401) and S. pimpinellifolium (accessions LA1618, LA1629, LA2983), a commercial tomato cultivar (‘BHN589’) and three commercial rootstocks (DRO-141TX, Estamino, Maxifort). Three levels of salinity were applied (0, 60 and 120 mM NaCl, corresponding to ~1.5, 6 and 12 dS m⁻¹). Data were analysed with two-way ANOVA using anova function in R 3.6.3 (R Core Team 2021). Data were transformed as necessary when ANOVA assumptions were not met. For all models, the alpha for the main effect was set at 0.05 level. When the calculated P-value was lower than our chosen alpha, the null hypothesis was rejected and a post hoc multiple-comparison procedure was conducted with the multcomp function (emmeans package) using the Bonferroni method. Mean comparisons are within genotype. Values are mean ± standard error (n = 3–9).