Modelling Plant Responses to Sulphate and Chloride Salinity: Integrating Ion-Specific Physiology with Quantitative Crop-Response Frameworks

Abstract

Salinity models used in crop science commonly describe stress through bulk electrical conductivity, osmotic potential, or a single empirical salinity index. This simplification is operationally useful, but it can conceal biologically important differences between chloride- and sulphate-dominated environments. This critical narrative review evaluates how plant responses to sodium chloride and sodium sulphate have been measured, interpreted, and represented in quantitative models, with emphasis on the consequences of salt composition for model structure and parameter transferability. Literature published from 1977 to 30 June 2026 was examined through agricultural, biological, multidisciplinary, and open scholarly information sources, with targeted citation searching and reference verification. Comparative experiments show no universal ranking of chloride versus sulphate toxicity. Relative effects vary with species, genotype, developmental stage, concentration, exposure duration, substrate chemistry, nutrient supply, and, critically, the basis used to match treatments. Equal molarity, equal sodium concentration, equal electrical conductivity, and equal osmotic potential do not create equivalent chemical exposures. Chloride has essential and beneficial roles at moderate concentrations but can become toxic and antagonise nitrate nutrition at high tissue concentrations. Sulphate is likewise an essential nutrient, yet excessive sulphate can alter mineral balance, sulphur assimilation, redox regulation, photosynthesis, and metabolism. Current empirical yield functions and root-water-uptake models capture aggregate salinity effects effectively in many settings, but most do not represent anion identity explicitly. Consequently, parameters calibrated under chloride-dominated salinity cannot be assumed to transfer to sulphate-dominated or mixed-salt systems. A tiered modelling strategy is proposed, ranging from composition-aware empirical response functions to coupled soil-plant ion-transport models. Progress requires factorial experiments that separate osmotic, sodium, chloride, sulphate, and nutrient-interaction effects, together with field validation across realistic mixed-salt environments. Composition-aware modelling should improve physiological interpretation, phenotyping, irrigation assessment, and breeding decisions without discarding the practical value of established salinity indices.