Estimation of aboveground biomass of a megathermic pasture (Setaria sphacelata) based on process-based crop models with different structure

About Pablo

Pablo is a Zootechnical Engineer graduated from the National University of Lomas de Zamora in 2004 with a master’s degree in animal production from the National University of Mar del Plata in 2010. He worked on numerous projects related to the production and use of forage resources for cattle, with an emphasis on subtropical environments. Currently his work is focused on the modeling of the growth of megathermic grasses and their adaptation to different environments in Corrientes, Argentina. It also works on the generation of stable forage chains for breeding and wintering systems, carrying out an experimental module of short wintering and participating in an intensive breeding unit. Another line of work is the evaluation of genotypes and management practices in winter grasses, with an emphasis on nutrition and adaptation to future environments. He also has experience with tropical and temperate forage legumes, summer forage grasses and temperate perennial grasses. His publication record includes more than 90 scientific and end-user publications, and he participated as a speaker in numerous conferences, congresses, and meetings with farmers. His teaching experience includes 5 years as head of the forage production module in the Higher Diploma in Ruminant Animal Production [INTA-National University of the Northeast UNNE-Argentina], and he gave various talks in the Agricultural engineering unit of UNNE. He also participated in numerous international projects related to meat production, both in Southeast Asia and Latin America.

Contact: [email protected]

About the project

The aboveground biomass production is key to define pasture management and maximize pastoral use. Having information on this variable for different forage resources and different environmental conditions continues to be one of the main challenges in this area of knowledge. One way to ameliorate this gap is through crop modeling. Crop models allow us to understand and predict the processes that involve biomass inputs and output in livestock systems (growth, senescence, decline, and consumption). The growth estimates from crop models are more accurate when there are no limitations on the nutrient provision, which is very rare in most livestock systems, particularly in subtropical regions of the world. It is currently difficult to predict some components of the canopy structure in perennial C4 grasses, such as the tiller number and the amount of standing crop dead material. This is because the level of development of crop models for these species has been poorer than that available for temperate crops or pastures. This PhD thesis will address the modeling of the aerial biomass of Setaria sphacelata (tall African grass, also known as South African pigeon grass and African bristlegrass), a cultivated megathermic grass used in humid subtropical environments. The objective of the project is to predict aerial biomass and its components using forage crop models to simulate the effect of different levels of pasture intensification under different future climate scenarios. Two contrasting models will be parameterized in terms of their level of complexity and structure (i.e. interactions in their algorithms and equations), a simple model (McCall) and a more complex model (APSIM). Emphasis will be placed on the ability of both models to detect the effect of nutrient availability on pasture growth, biomass partitioning into stems and leaves, and the senescence dynamics of these components. The effect of the animal on the aerial biomass and the disappearance of the standing dead material will also be quantified and calibrated, using APSIM. Trials will be carried out in plots and measurements under pastoral conditions that will allow model calibration and validation. Once the models have been validated, the impact of changes in the climate on primary productivity under a NPK fertility gradient and different stocking rates will be quantified to identify the best intensification strategies to maximize the economic return to farmers under changing climate.


EPG-FAUBA University of Buenos Aires. INTA EEA Corrientes, Argentina




Dr Gonzalo Irisarri (primary supervisor), Dr Martin Oesterheld, Dr German Berone and Dr Jonathan Ojeda

Jonathan Ojeda (Jony)
Crop Ecophysiologist - Cropping Systems Modeller - Data Scientist

I use crop models to understand GxExM interactions and quantify sources of uncertainties in agricultural predictions.