Phosphate sorption in calcareous Moroccan soils as affected by soil properties

Citation
M. Amrani et al., Phosphate sorption in calcareous Moroccan soils as affected by soil properties, COMM SOIL S, 30(9-10), 1999, pp. 1299-1314
Citations number
28
Categorie Soggetti
Environment/Ecology
Journal title
COMMUNICATIONS IN SOIL SCIENCE AND PLANT ANALYSIS
ISSN journal
00103624 → ACNP
Volume
30
Issue
9-10
Year of publication
1999
Pages
1299 - 1314
Database
ISI
SICI code
0010-3624(199905)30:9-10<1299:PSICMS>2.0.ZU;2-2
Abstract
Phosphate sorption is one of the main factors that greatly affects phosphor us (P) availability in soils. The increased concern about precision in fert ilizer application emphasizes the importance of quantifying P sorption for better and accurate P recommendations. This study was conducted to examine P sorption by 18 contrasted soil samples of arid and semiarid regions of Mo rocco. Three isotherm models were used in this study: Langmuir, Cooke, and Freundlich models. Langmuir and Cooke equations were found to accurately de scribe P sorption isotherms in calcareous soils of Moroccan arid and semiar id zones. Maximum P adsorption (Xm) varied from 146 to 808 mg P kg(-1) soil for the soils used in our study. Averaged across regions, soils from Chaou ia adsorbed more P at maximum adsorption compared to Abda and Ben Sliman so ils, suggesting that each region has to have specific P recommendation norm s. Maximum buffering capacities (MBC) also showed large variation, the valu es ranged from 35 to 404 mg P kg(-1). This study showed that these buffer i ndices can be predicted using soil characteristics determined by routine so il analysis especially using clay (CL, %), lime (L, %), and exchangeable ca lcium (Ca, mg kg(-1)) contents: MBC=-38.1+/-3.3* CL+3.7*L+0.024*Ca (R2=0.98 **). The determination of buffer indices requires the establishment of P so rption isotherms which are difficult to adapt to routine analyses. Therefor e, this kind of relationships between buffer indices and soil properties po ssibly could be used to rapidly predict these indices for inclusion in P re commendation models.