A quantitative approach for fertilizer recommendation under saline conditions

ABSTRACT

All existing fertility models are originally derived for non-saline conditions. Under salinity, fertilization is challenging and may lead to amelioration or deterioration of plant salt tolerance. This investigation aimed to develop new deterministic models for fertilizer recommendation in salt-affected soils integrating salinity and fertility models. Based on statistical parameters, the nutritional-salinity nonlinear-nonlinear model was the most efficient followed by the linear-nonlinear model. The latter is preferred due to its simplicity. Model parameters were expressed as functions of nutrient rates and demonstrated drastic variations under fertilization. Zinc deficiency was more limiting than salinity while salinity was more detrimental than potassium deficiency. The EC causing 50% yield reduction ($E{C}_{50}$) varied from 15 dS m⁻¹ in control treatment to, respectively, 17 and 8 dS m⁻¹ at highest zinc and potassium rates. Similarly, salinity threshold ($E{C}_{cr}$) value was altered from 5 dS m⁻¹ to 6.4 and 3 dS m⁻¹. Accordingly, application of 100 and 50 kg ha⁻¹ zinc and potassium appeared to be promising to improve cotton seedling vigor under severe salinity (15 dS m⁻¹). Although $E{C}_{50}$ and $E{C}_{cr}$ inconsistently change under fertilization, our proposed models can reasonably well estimate the required fertilizer quantity to achieve the yield goal under certain soil salinity.

KEYWORDS:

• Cotton
• modeling
• potassium
• salinity
• zinc

Acknowledgments

This research was granted by Tarbiat Modares University, Grant Number IG-39713. We thank Cotton Research Institute of Iran (AREEO) especially Dr. Kamal Ghasemi Bezdi for providing and delinting cotton seeds.

Disclosure statement

No potential conflict of interest was reported by the authors.