Título:	Calibration and evaluation of a carbon net primary productivity module based on the SIMPLE model.
Autor:	COLMANETTI, M. A. A. OLDONI, H. ANNIBAL, L. WOLFF, W. REJAILI, R. P. A. BARIONI, L. G. ALMEIDA, I. R. de EWING, R. P. CUADRA, S. V.
Afiliación:	MICHEL ANDERSON ALMEIDA COLMANETTI HENRIQUE OLDONI LEANDRO ANNIBAL WAGNER WOLFF, BAYER RODRIGO PEREIRA ABOU REJAILI, BAYER LUIS GUSTAVO BARIONI, CNPTIA IVAN RODRIGUES DE ALMEIDA, CNPTIA ROBERT P. EWING, BAYER SANTIAGO VIANNA CUADRA, CNPTIA.
Año:	2026
Referencia:	Agronomy Journal, v. 118, n. 2, e70309, Mar. 2026.
Descripción:	This study presents the carbon net primary productivity (CNPP) module, an imple-mentation of the simple generic crop model (SIMPLE model) that we have extendedto predict aboveground and belowground biomass production and carbon assim-ilation. The goal for this module is to predict biomass inputs at and below thesoil surface, during and at the end of crop cycles, while integrated into a broaderenvironmental carbon simulation framework, ProCarbon-Soil. CNPP was initiallyparameterized for soybean [Glycine max (L.) Merr.] and maize (Zea mays L.) usingmicrometeorological data, and for wheat (Triticum aestivum L.), bean (Phaseolusvulgaris L.), and perennial forage [Urochloa (syn. Brachiaria) brizantha (Hochstex A. Rich.) Stapf cv. Marandu] using agrometeorological experimental data and/ordata from the literature. Subsequently, calibrations for reference cultivars were per-formed, grouping cultivars by crop phenological characteristics and edaphoclimaticregions using farm-level data. CNPP accurately simulated leaf area index, evapotran-spiration, and biomass dry matter production and allocation for soybean and maizewhen evaluated at the sites with micrometeorological data (R2 > 0.76, Nash–Sutcliffeefficiency > 0.56, and relative root mean square error < 38% for all variables).Simulations for wheat, bean, and perennial forage exhibited lower performanceowing to lower availability of yield data. Nonetheless, the resulting statistics supportthis module’s efficacy in predicting crop productivity in major Brazilian agricul-tural areas. By employing a reduced and efficient parameter set, the CNPP moduleachieves enhanced performance and enables robust calibration across diverse crops,genotypes, and management schemes in multiple regions.
Thesagro:	Balanço Hídrico Simulação Trigo Feijão Milho Soja Biomassa
NAL Thesaurus:	Water balance Calibration Computer simulation Simulation models
Palabras clave:	Calibração Simulação de carbono Crop model
DOI:	10.1002/agj2.70309
Tipo de Material:	Artigo de periódico
Acceso:	openAccess
Aparece en las colecciones:	Artigo em periódico indexado (CNPTIA)