Potassium management in rice-maize systems in South Asia

Potassium (K) availability in soils is largely governed by their mineralogical composition. The extent of weathering of primary K-bearing minerals, the chemical pathways through which weathering takes place, as well as the dynamic equilibrium between various K fractions in soils are factors which determine different soil types of varying K-supplying capacity. The marked variability of K availability in soils in South Asia needs to be taken into account when formulating K-management strategies in intensive cereal-based systems in response to K application. Evidence from long-term fertilizer experiments in ricerice (R-R) or ricewheat (R-W) systems strongly indicates significant yield responses to K application and negative K balances where K application is either omitted or applied suboptimally. However, K-fertilizer recommendations in South Asia are generalized over large areas while farmers neglect K application to crops and remove crop residues from fields. These practices may strongly affect yield and soil K-fertility status in the emerging ricemaize (R-M) systems in different locations of South Asia. The dry-matter yield of the R-M system is usually much higher than that of the R-R or R-W system causing high withdrawal of nutrients from the soil. The current review assesses various K forms and K availability in diverse soil types of South Asia supporting rice-based systems. Aspects considered include: long-term crop yield and its response to added nutrients, K balance for intensive rice-based systems, and the role of crop residues in supplying K to crops. Emerging data from either completed or on-going experiments on the R-M systems in India and Bangladesh have revealed very high system productivity and variable responses and agronomic K-use efficiency of maize and rice. Potassium responses of maize are extremely high and variable for soils in Bangladesh. Finally, a plant-based strategy for field-specific nutrient management is presented and the need for models and decision support systems for developing efficient K management of the R-M system is also discussed.