INVESTIGADORES
CARCIOCHI Walter Daniel
artículos
Título:
A COMPARISON OF INDEXES TO ESTIMATE CORN S UPTAKE AND S MINERALIZATION IN THE FIELD
Autor/es:
CARCIOCHI, WALTER D.; WYNGAARD, NICOLÁS; DIVITO, GUILLERMO A.; CABRERA, MIGUEL L.; ECHEVERRÍA, HERNÁN E.
Revista:
BIOLOGY AND FERTILITY OF SOILS
Editorial:
SPRINGER
Referencias:
Lugar: Berlin; Año: 2018
ISSN:
0178-2762
Resumen:
The development of simple predictors of sulfur (S) mineralization and its correlation with field-derived data may help improving corn S availability diagnosis. The objectives of this study were (1) to compare methods to estimate soil S mineralization, (2) to develop a model to predict soil S mineralization from S mineralization indexes and edaphic variables, (3) to predict field-grown corn S uptake (Suptake) and apparent S mineralization (Smin-app) from different S mineralization indexes and edaphic-climatic variables. We evaluated 26 experimental sites where we measured edaphic variables as: soil organic carbon (SOC), organic carbon in the particulate fraction (C-PF), S mineralization potential (Smin-10wk), S mineralized during a short-term (7 d) aerobic incubation + initial inorganic S (Smin-7d+Sinorg), and nitrogen mineralized during a short-term (7 d) anaerobic incubation (Nan). Additionally, 18 field experiments were carried out to quantify Suptake and Smin-app. The C-PF, Smin-7d+Sinorg, Nan, and SOC were variables significantly correlated with Smin-10wk (r = 0.89; 0.89; 0.88 and 0.85, respectively). We developed a simple model to predict Smin-10wk from selected edaphic variables (Smin-10wk=0.038*Nan+0.106*SOC+0.74; Ra2=0.87). The Smin-10wk, C-PF and Smin-7d+Sinorg showed a liner-plateau association with Suptake (R2=0.73, 0.53, and 0.48, respectively). We modified the method to estimate Smin-app to account for S losses (Smin-app (modified)), and developed a model to predict Smin-app (modified) from C-PF (Smin-app (modified)=4.65*C-PF+9.86; R2=0.62) or Smin-10wk (Smin-app (modified)=3.0*Smin-10wk+7.4; R2=0.54). Our results demonstrate that S mineralization indexes can be used to predict corn S availability under field conditions.