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Jonathan Ojeda (Jony)

Science & Technology Executive – Carbon Markets & MRV | Scientific Founder @Terradot

[email protected]

Bio

Dynamic and results-driven Science & Technology Executive Leader with over 15 years of experience at the intersection of environmental science, carbon markets, and sustainable agriculture. Proven track record in structuring and executing complex international carbon removal transactions, leading multidisciplinary teams, and securing strategic partnerships. Extensive expertise in project management, stakeholder engagement, and MRV (Monitoring, Reporting, and Verification) implementation for large-scale carbon removal initiatives. Played a pivotal role in raising Series A funding ($58.2M) for Terradot and closing carbon offtake agreements. Strong advocate for integrating ESG (Environmental, Social, and Governance) principles into business strategy, ensuring that sustainability efforts not only drive financial performance but also deliver measurable environmental and social impact. Passionate about leveraging science and technology to accelerate decarbonization, improve land-use efficiency, and promote regenerative agricultural practices. Adept at aligning sustainability initiatives with corporate ESG goals, driving data-driven decision-making, and scaling nature-based and emerging carbon removal solutions to support a resilient and equitable low-carbon economy.

Jony has a deep interest in disentangling sources of uncertainty & spatio-temporal heterogeneity to measure farm productivity & C sequestration in Ag systems. This requires a broad understanding of how environmental factors affect crop growth, how rainfall, irrigation, and applied rock influence soils, and how soil-crop-weather processes interact. Over 15 years of experience managing large soil-crop-climate datasets (>10 years using Python), developing crop/C models & applying data pipelining and optimization towards solving large-scale C deployments. Jony collected (experiments) & analyzed data including >18 crop species (annual, perennials). Jony has 26+ published articles in high-impact journals (13 as first author) and received 18 research grants with a cash value of ~USD6M.

As part of Regrow Ag, Jony led a multicultural global team (15 people including data scientists, software developers/engineers) under the Niche project (USD4M) funded by B&MGF which focuses on the analysis of GxExM in Sub-Saharan Africa. Jony worked with multi-cultural & multi-disciplinary teams (hybrid approach - Academia & Industry) & has ground experience working in 9 countries (Argentina, Brazil, Australia, NZ, USA, The Netherlands, Germany, Rwanda & Kenya).

Interests

  • Carbon MRV
  • Climate Change
  • Decision support tools development
  • Sustainable agricultural practices
  • MRV Platforms
  • Data analytics

Education

  • PhD in Agricultural Sciences, 2017

    National University of Mar del Plata, Argentina

  • Agricultural Engineer, 2011

    National University of Entre Ríos, Argentina

KeyWords

Alfalfa APSIM APSIM Classic APSIM Next Generation Carbon Climate Change Cover crops Crop modelling Crop models Crop rotations Input uncertainty Irrigation Maize Model uncertainty Model upscaling Modelling N leaching Nitrogen Parameter uncertainty Potato Regional modelling Remote Sensing Spatial variability Water use Weather data

Skills

Python

Linux

Remote Sensing

Ubuntu

R

Markdown

GitHub

Statistics

Plotting

International Networking

Communication

Team work

Education

PhD in Agricultural Sciences (2017)

National University of Mar del Plata, Argentina (duration = 5 years; 422 credit hours)

GPA: 8.8 (out of 10) No. failed: 0 (none)

Dissertation: Precipitation use efficiency in annual forage crop sequences and perennial pastures (in Spanish)

Courses

  • Crop Eco-physiology
  • Advanced Crop Eco-physiology
  • Applied Eco-physiology to Pasture Management
  • Statistical Methods I
  • Statistical Methods II
  • Experimental Design I
  • Experimental Design II
  • Calculation Techniques and Agricultural Estimations in Extensive Crops
  • Use of DSSAT Models
  • Scientific Writing Methodologies
  • Neotyphodium (Festucosis)

About the PhD project

The growing demand for beef and dairy products requires technological options to improve the productivity and resource use efficiency of forages crops with less environmental impact. Livestock production systems based on forage crop sequences (FCS) could be more productive and efficient than those based on perennial pastures (PP). However, there are many questions about the FCS implementation related to the system stability in the long term and about the root-derived soil organic carbon in these systems. The main objective of this thesis was to provide original knowledge about the main ecophysiological aspects determining forage supply in livestock systems based on the use of FCS and PP.

The study was conducted in three steps (i) above-ground dry matter yield (AGDM) and precipitation use efficiency (PUE) were analyzed in Rafaela, Pergamino, General Villegas and Trenque Lauquen, (ii) in Balcarce were evaluated AGDM, below-ground dry matter yield (BGDM), PUE (i.e. water capture [WC] * water use efficiency [WUE]), radiation productivity (RP, i.e. radiation capture [RC] * radiation use efficiency [RUE]) and soil carbon (C) variations in different organic matter fractions. Finally, (iii) Agricultural Production Systems Simulator (APSIM) was calibrated and validated to analyze the accumulated annual precipitation, AGDM and PUE variability using a long-term climate database (30 years).

In general, the AGDM was higher for the FCS than the PP treatments, although more variable in the long term. Below-ground dry matter yield was similar for both treatments. Likewise, there was a greater association between the contribution of C and BGDM in sub-surface horizons below than 0,15 m soil depth. The PP treatments shown higher RC and similar WC than the FCS treatments. However, FCS shown higher RUE and WUE, which led to higher RP and PUE. In turn, the PP treatments shown lower inter-annual variability of PUE than FCS in the long term. The multi-environmental analysis on the impacts of different forage cropping systems on PUE, as well as on the soil C variations, provide key knowledge and information to develop management strategies to increase the sustainable productivity of livestock systems in the Argentinean Pampas.

Logical flow of the PhD thesis

image

The image shows the logical flow of the PhD thesis including the stages, chapters, scales, spatio-temporal levels of analysis, and the measured or estimated variables. DMa, Aerial Dry Matter Yield; WP, Water Productivity ; DMr, Root Dry Matter Yield; RP, Radiation Productivity; OM, Organic Matter

Agricultural Engineer (2011)

National University of Entre Ríos, Argentina (duration = 7 years; 3479 credit hours)

GPA: 8.8 (out of 10) No. failed: 0 (none) Historical GPA: 6.8 (out of 10)

Dissertation: Response to plant population density in different sunflower hybrids (in Spanish)

Courses

Basic courses

  • Introduction to Agro-productive Systems
  • Biology
  • Agricultural Microbiology
  • Computer Sciences
  • Morphological Botany
  • Systematic Botany
  • General Chemistry
  • Analytical Chemistry
  • Biological and Organic Chemistry
  • Mathematics
  • Physics
  • Experimental Statistics and Design
  • Research Methodology
  • Agricultural Policy and Legislation
Agronomic courses
  • Agricultural Climatology
  • Agricultural Automation
  • Agricultural Zoology (entomology)
  • Animal Anatomy and Physiology
  • Soil Sciences and Pedological Studies
  • Ecology of Agricultural Systems
  • Phytopathology
  • Land Technology
  • Plant Physiology
  • Plant and Animal Genetics and Improvement
  • Plant Therapeutics
Professional courses
  • Agricultural Economy
  • Geographical Information Systems
  • Business Management and Planning
  • Rural Extension and Sociology
  • Irrigation and Drainage
  • Integrated Workshop of Phytosanitary Management
  • Animal Nutrition
  • Forage Crops Management
  • Agrosilvopastoral Production
  • Grains and Oilseeds
  • Postharvest Management
  • Beef Cattle
  • Dairy Cattle
  • Small Ruminants
  • Apiculture
  • Horticulture
  • Forestry
  • Fruticulture
  • Pigs

Experience

 
 
 
 
 

Science Operations (SciOps) Lead

Terradot

Oct 2024 – Present Remote

Leadership & People Management in Carbon MRV

  • Built & led a multicultural, cross-disciplinary team of field scientists, agronomists, project managers, & data scientists to execute an MRV platform for carbon quantification (via Enhanced Rock Weathering, ERW) in agricultural fields.
  • Acted as the hiring manager, recruiting & onboarding project managers, field/data scientists, & field assistants for the SciOps Team.
  • Designed & implemented project management strategies, ensuring alignment of scientific initiatives with company goals & ERW carbon crediting methodologies.
  • Coordinated with other companies leads to ensure science & operations protocols generate useful, high-quality data for ERW carbon credit validation.

Research & Development for MRV

  • Designed scientifically robust field protocols for ERW in compliance with CDR registry requirements (Isometric, Puro.earth, Cascade).
  • Led experimental planning for site selection, deploying control & treatment plots & designing comprehensive soil & crop sampling plans across the entire CDR project lifecycle.
  • Enhanced sampling & uncertainty quantification protocols in collaboration with geochemical & soil scientists, improving measurement accuracy across the entire carbon flux in the critical zone (atmosphere, crop, soil) & at landscape scale (field, catchment, farm).
  • Managed on-field data collection, ensuring accurate monitoring of crop & soil management, spatial heterogeneity data, & carbon flux dynamics.

MRV Tech & Platform Development

  • Spearheaded the development of a digital carbon MRV Web platform, integrating 1-Geolocated fields & datasets for long-term tracking across multiple fields & farms in Brazil, cropping seasons, crop types (annual & perennials) & crop/soil management zones and 2-Automated data pipelines for weather, soil, crop, & farm management data collection.
  • Led the co-design of new ERW platform features, streamlining field & farm management data collection (sowing, harvest, tillage, lime applications, etc.).
  • Implemented operational & digital QA/QC procedures to ensure high-quality, low-uncertainty data for CDR calculations.

Stakeholder Engagement & Strategic Partnerships

  • Conducted field visits to engage with farmers, farm cooperatives & associations & mining partners, driving enrollment in carbon programs.
  • Developed strategic partnerships with public & private organizations in the carbon market sector, enhancing MRV execution & securing long-term collaborations.
  • Coordinated with commercial & operations teams to plan & execute large-scale commercial carbon sequestration deployments for ERW.

Key Achievements

  • Built a high-performing MRV team (5+ members) within four months, accelerating field execution & protocol implementation.
  • Developed & procured specialized MRV equipment, including weather stations, bulk density kits, lysimeters, soil auger samplers, soil & rock moisture sensors & lab materials.
  • Planned & executed commercial carbon sequestration ERW deployments in Brazil, ensuring efficient data collection, logistics, & field execution.
  • Led experimental pilot projects with external partners (e.g. LDC), optimizing data collection methodologies & logistics coordination.
 
 
 
 
 

Science Lead

Terradot

Jul 2023 – Oct 2024 Remote

Leadership & People Management in Carbon MRV

  • Built & led a multidisciplinary global science team (soil scientists, geologists, agronomists, geochemists, modelers, engineers, data scientists) to develop a carbon MRV platform from scratch.
  • Hired & scaled the team to 10+ experts in six months, driving carbon R&D & MRV execution.
  • Defined the strategic roadmap for improving CO₂ emissions measurement & verification in agricultural land (annual & perennial crop/pasture systems).
  • Served as the primary science lead & scientific founder, playing a key role in securing $58.2M in Series A funding to enable large-scale carbon removal projects. Joined as the third employee, following the two co-founders, & helped shape the company’s scientific vision & strategy.
  • Led the development of the Terradot Science White Paper, which was presented to buyers & played a key role in securing several carbon offtake agreements with Frontier & Google.

MRV Platform & Carbon Modeling Development

  • Led the creation of a soil carbon (organic & inorganic) & crop yield MRV platform, ensuring compliance with VERRA 0042/0053, Puro.earth, Cascade, & Isometric protocols.
  • Developed a coupled multi-scale model using MIN3P & APSIM to estimate inorganic carbon sequestration via ERW.
  • Built Python pipelines for ground ERW data storage & automated ERW calculations & modeling, improving data processing efficiency.
  • Scaled soil sampling pipelines to deploy ERW trials across multiple regions in Brazil, ensuring broad applicability of carbon removal methodologies.
  • Designed an ERW clustering tool (including climate, soil & farm management factors) to assess field suitability for carbon sequestration, improving deployment strategies.

Carbon Market Engagement & Policy Alignment

  • Worked directly with carbon registries & policymakers to align MRV methodologies with carbon market certification standards.
  • Ensured compliance with soil carbon protocols (VERRA, Puro.earth, Isometric, Cascade) by assessing uncertainties & developing strategies to minimize data variability.
  • Served as the primary liaison with the Terradot Science Advisory Board (Stanford, LBNL & UBC researchers), ensuring alignment with cutting-edge carbon removal science.
  • Engaged with government leaders & local communities to communicate scientific findings & scale adoption of carbon sequestration practices.

Scientific R&D for Carbon Sequestration

  • Conducted simulations & calibration of MIN3P-APSIM for soil carbon quantification, utilizing real-world field trial data to enhance model accuracy.
  • Directed & oversaw carbon sequestration modeling at plot, field & farm scale, improving predictions of CO₂ capture efficiency in agricultural systems.
  • Developed Python-based infrastructure to integrate model simulations into a core MRV product, ensuring seamless data-to-credit workflows.
  • Scaled up calibrated models to additional fields, expanding ERW’s role in agricultural carbon removal projects.

Key Achievements

  • Core team member in securing $58.2M in Series A funding, enabling large-scale carbon removal projects.
  • Built a global MRV & science team (10+ experts) from scratch within six months.
  • Developed & validated a coupled ERW model for predicting carbon sequestration impacts in agriculture.
  • Automated ERW modeling workflows through Python pipelines, streamlining MRV calculations & compliance.
  • Expanded soil sampling operations, deploying ERW trials across multiple Brazilian states.
  • Created an ERW clustering tool, improving field selection for high-impact carbon sequestration projects.
  • Published 3 abstracts in the AGU24 Annual Meeting.
 
 
 
 
 

Adjunct Senior Research Fellow

University of Southern Queensland

Oct 2022 – Present Remote
Research Contributions

  • Research collaborations with the Centre for Sustainable Agricultural Systems in crop modelling and remote sensing projects.
  • PhD supervision.
 
 
 
 
 

Senior Cropping Systems Scientist

Regrow Ag

Jul 2021 – Jun 2023 Remote

Leadership & Scientific Innovation in Crop & Carbon Modeling

  • Led the Niche Project (funded by Bill & Melinda Gates Foundation) to develop a predictive analytics framework improving on-farm field trials, seed profiling, & climate adaptation for small-scale Sub-Saharan African producers.
  • Managed a 15+ member global team (including 3 postdocs, data scientists, & engineers) across 4 organizations (Gates Foundation, NASA Harvest, University of Lincoln & One Acre Fund) in 4 continents.
  • Collaborated with TomorrowNow through the OSIRIS Gates project to analyze climate data impacts on APSIM outputs for sustainable crop practices.
  • Spearhead multiple field campaigns in Rwanda & Kenya, visiting maize farmers & actively engaging with local communities.
  • Led development of a Python-based APSIM platform integrating climate, soil, & crop data from APIs, global open datasets & remote sensing products (e.g. Sentinel-2 NDVI data).
  • Build automated crop model uncertainty quantification workflows to improve predictions for agriculture & carbon markets.

MRV & Carbon Modeling for Sustainable Agriculture

  • Designed new crop management algorithms for FluroSense, a digital agronomy & conservation monitoring platform, integrating Climate FieldView, Agrian, & Proagrica farm data management systems.
  • Developed multi-scale models coupling remotely sensed data & biophysical models to optimize soil sampling for large-scale conservation projects.
  • Created algorithms for APSIM & DNDC to model the effects of soil management, genetics, & climate on soil carbon, crop productivity, & environmental impact (e.g. CO2, N2O, CH4).
  • Validated Sentinel-1 SAR data for soil moisture prediction, improving soil-water balance assessments.
  • Conducted APSIM-DNDC model intercomparison, quantifying prediction errors & uncertainties in carbon & nitrogen cycling models.
  • Implemented SWIM3 to simulate solute interactions, subsurface drainage, & water table dynamics within the FluroSense Nitrogen Recommendation Tool.

Carbon Market & Policy Engagement

  • Worked with the APSIM Science Team & remote sensing experts to enhance soil-crop management best practices globally.
  • Developed soil/crop modules in DNDC, improving biomass & grain yield predictions under water & nitrogen stress conditions.
  • Submitted multiple funded proposals on satellite remote sensing, biomass & crop yield estimation, & biophysical modeling for sustainable crop-livestock systems.

Key Achievements

  • Built a Python pipeline integrating climate, soil, crop, & genotype field data & remote sensed data with APSIM modeling, enabling automated calibration & scenario analysis.
  • Developed & validated new crop cultivars in FluroSense, optimizing regional seed placement.
  • Designed crop rotation templates (corn, soybean, wheat) for soil nitrogen & water balance simulations, improving in-season nitrogen recommendations.
  • Implemented gridded soil data extraction (ASRIS database) in APSIM for Australian fields, leveraging soil order probability mapping.
  • Secured funded grants, advancing crop modeling & remote sensing applications.
  • Publications: authored 3 papers in Nature Communications, Field Crops Research & Frontiers Plant Science.
 
 
 
 
 

Scientific Advisor

Argentinian Scientific Network in Australia

Apr 2021 – Jul 2022 Brisbane, Queensland, Australia

Advancing International Scientific Collaboration

  • Facilitate networking among Argentinian researchers abroad, strengthening scientific ties with Australia.
  • Promoted bilateral research exchange, fostering collaboration between Argentine & Australian institutions while working closely with the Argentinian Ambassador in Australia.
  • Disseminate Argentinian scientific & technological advancements to an international audience, particularly in Australia.
  • Improve visibility & accessibility of highly skilled Argentinian researchers & professionals abroad. Engage Argentinian industry & NGOs to enhance science, technology, & innovation initiatives.

Key Achievements

 
 
 
 
 

Adjunct Researcher

Tasmanian Institute of Agriculture, University of Tasmania

Oct 2020 – Jul 2023 Hobart, Tasmania, Australia
Research Contributions

  • Research collaborations with the University of Tasmania and the Tasmanian Institute of Agriculture in sustainable agriculture PhD projects.
  • PhD supervision Ranju Chapagain (PhD granted) & Francesco Tacconi (PhD granted).
 
 
 
 
 

Postdoctoral Research Fellow

Queensland Alliance for Agriculture and Food Innovation, The University of Queensland

Oct 2020 – Jun 2021 Brisbane, Queensland, Australia
Research Contributions

  • Led improvement of advanced biofuel crops, specifically energy sorghum, as part of the TERRA US DOE-funded project, collaborating with Iowa State University & Purdue University. Developed a new version of pSIMS to predict biomass sorghum across U.S. environments using gridded data. Supervised PhD & Master’s students at Purdue & UQ, utilizing APSIM to simulate phenotyping of biomass sorghum based on experimental trials & environmental scenario analysis (weather, soil, & crop data).
  • Collaborated with Pacific Seeds Australia (ADVANTA) on forage sorghum biomass research. Integrated farm, drone, & satellite imagery to analyze photosynthesis & radiation use efficiency using LICOR6800 for leaf photosynthesis measurements in sorghum trials (forage & grain genotypes). Teaching & Mentorship
  • Delivered undergraduate courses in UQ’s plant & crop science program.
  • Supervised Honours & Postgraduate students. Key Achievements
  • Software Development: Developed APSIM Sorghum Module to run pSIMS at a regional scale (US-wide) using netCDF input data (climate, soil, & crop management).
  • Publications: First-authored a paper in Global Change Biology Bioenergy.
  • Granted Research Proposals:
  1. The Role of Biological Fixation in Crop Productivity, Nitrogen Use Efficiency & N₂O Emissions – Quantification at different spatio-temporal scales. Argentinian Agency for the Promotion of Research, Technological Development & Innovation (Partner).
  2. Estimation of Radiation Use Efficiency of Grassland & Its Use for Characterizing Syndromes of Ecosystem Changes – Funded by Argentinian Agency for the Promotion of Research, Technological Development & Innovation (Partner).
 
 
 
 
 

Junior Research Fellow

Tasmanian Institute of Agriculture, University of Tasmania

Nov 2017 – Nov 2020 Hobart, Tasmania, Australia

Climate Change & Agricultural Systems

  • Uncertainty Analysis: Evaluated climate change impacts on irrigated maize systems in Spain & livestock farm performance across Australia, Argentina, & Uruguay.
  • Crop Modelling & Climate Data: Developed a gridded climate data tool for APSIM using SILO climate datasets across Australia.
  • Phenology & Climate Adaptation: Modeled lentil & faba bean phenology against frost & heat stress patterns in Australia.
  • Multi-Scale Crop Modelling & Remote Sensing: Combined biophysical models with remote sensing to evaluate crop yield variability across Australia, Argentina, & Uruguay.
  • Model Development & Uncertainty Analysis: Quantified crop model uncertainties (input, structure, parameter uncertainty) using Sobol, Morris, ANOVA sensitivity analyses.
  • Potato Modelling: Developed an APSIM Next Generation potato module to simulate global potato productivity across various agricultural systems.

Applied Research & Industry Engagement

  • Decision-Support Tool: Developed a virtual scenario analysis tool for dual-purpose crops (canola & wheat) in Tasmania in collaboration with GRDC & CSIRO.
  • Industry Collaboration: Collected & structured potato agricultural datasets (climate, soil, crop management) from Simplot & McCain for modelling & scenario analysis with potato farmers.
  • Workshops & Stakeholder Engagement:
    1. Led CRC Soil workshops with Australian farming groups to evaluate soil constraints on crop productivity.
    2. Conducted foresight workshops for livestock industry decision-makers in Argentina, Uruguay & Australia, exploring climate change adaptation strategies. Teaching & Mentorship
  • Supervised PhD students in collaboration with CSIRO Brisbane & Toowoomba.
  • Guest Lecturer:
    1. Can we trust field-scale model predictions for regional agricultural systems? (TIA-UTAS Seminars, 2018).
    2. Farming Systems & Business Management (KLA312/KLA535, TIA-UTAS, 2018).
  • UTAS Data Network Co-Director (Mar 2019 – Nov 2019): Led data management discussions across UTAS research teams.

Key Achievements

  • Publications: First-authored 4 & co-authored 10 research papers.
  • Research Granted Projects:

2020

  • Mapping Potato Yield & Irrigation Variability Under Climate Change Scenarios in Tasmania – JM Roberts Seed Funding for Sustainable Agriculture (Chief Investigator).

2019

  • Biomass Estimation of Forage Resources via Remote Sensing & Crop Models – Argentinian Agency for the Promotion of Research, Technological Development & Innovation (Partner).
  • Visualizing Agricultural Uncertainties Under Climate Change – CoSE Grant Incentive Scheme, UTAS (Chief Investigator). Crop-Livestock Adaptation to Climate Change Using Modelling & Remote Sensing – Australian Govt. Council on Australia Latin America Relations Grant (Chief Investigator).

2018

  • Diversity Benefits in Agricultural Systems – Australian Sustainable Agriculture Elite. Scholarship, CSIRO-TIA (Chief Investigator).
  • Estimating Uncertainty in Crop Models – CSIRO-TIA (Chief Investigator).
  • Improving Soil Productivity Representation in Decision Support Models – CRC for High-Performance Soils (Partner).

International Research Collaborations & Conferences

2020

  • Montpellier, France – 2nd International Crop Modelling Symposium (iCROPM2020), AgMIP-Calibration & AgMIP-Ozone Workshops (Oral & Poster Presentation).
  • Muncheberg, Germany – Research stay at ZALF (3 weeks), collaboration with Dr. Webber & Kamali (UA-DAAD Project).

2019

  • Toowoomba, Australia – Research stay at USQ (1 week), meetings with Dr. Pembleton, CRC team, Dr. Huth & Holzworth (CSIRO).
  • Lincoln, New Zealand – Research stay at Plant & Food Research Institute (1 week), collaboration on potato modelling & crop modelling papers.
  • Gottingen, Germany – Research stay at University of Gottingen (3 weeks), strengthening Australia-Germany Joint Research Co-Operation (UA-DAAD).

2018

  • Wageningen, Netherlands & Germany (Gottingen, Muncheberg) – Course & Workshop: Fundamentals of Crop Physiology in a Changing World (Wageningen University, 1 week).
  • Hobart, Tasmania, Australia – Hosted Dr. Lattanzi (Director, INIA Uruguay) for a 3-day research visit.

Industry Engagement & Stakeholder Meetings 2020

  • Tasmania, Australia – Data collection across 20 potato farm enterprises linked to Simplot & McCain in Northern Tasmania. 2019
  • Devonport, Tasmania – Industry meetings with Simplot & McCain, presenting APSIM results & experiment setup discussions.
  • Smithton & Ulverstone, Tasmania – Stakeholder engagement with Simplot & McCain on modelling requirements & experimental setup.
 
 
 
 
 

Postdoctoral Research Fellow & Graduate Teaching Assistant

Research Council of Argentina, CONICET - Ecophysiology and Forage Production, National University of Entre Ríos

Apr 2017 – Nov 2017 Parana, Entre Rios, Argentina

Research Contributions

  • Research Proposal Development: Contributed to national & international research grants. Scientific Communication: First-authored 1 research paper in Agricultural & Forest Meteorology.
  • Data Analysis & Modelling: Analyzed & interpreted experimental results for scientific reports & high-impact journal publications.
  • Outreach & Dissemination: Engaged in research dissemination activities through seminars & workshops.

Teaching & Mentorship

  • Graduate & Undergraduate Teaching: Taught Crop Ecophysiology & Agricultural Systems to:
  1. Post-graduate students (~15 students).
  2. Undergraduate students (~50 students).
  • Honours Thesis Supervision: Advised a Bachelor’s thesis (Agronomy) at the National University of Entre Ríos. Thesis Topic: Impact of cover crops with different defoliation levels on soil carbon.
  • Post-Graduate Course Development: Contributed to the Crop Ecophysiology post-graduate course at the National University of Entre Ríos.
 
 
 
 
 

PhD Research Fellow & Graduate Teaching Assistant

Research Council of Argentina, CONICET - Ecophysiology and Forage Production, National University of Entre Ríos

Apr 2012 – Apr 2017 Balcarce, Buenos Aires, Argentina

PhD Research Contributions

  • Sustainable Agricultural Systems: Applied ecophysiology concepts to optimize forage & grain production while minimizing environmental impact with focus on soil carbon.
  • Climate & Crop Modelling: Utilized biophysical simulation models (APSIM) to analyze long-term productivity & stability of cropping systems.
  • Field Experimentation: Designed & conducted a 3-year field experiment in Balcarce, Argentina (2012-2015).
  • Soil & Water Probes Calibration: Calibrated soil water probes in Balcarce to understand the interaction between soil water and soil carbon dynamics, Argentina.
  • Data Management & Analysis: Organized & analyzed climate, soil, & crop data from 5 experimental sites across the Argentinean Pampas.
  • APSIM Model Development: Calibrated & validated APSIM for biomass prediction at both annual crop & rotation levels.

Teaching & Mentorship

  • Undergraduate Teaching: Courses on Grains & Oilseeds Ecophysiology, Forage Production (~50 students).
  • Honours Thesis Supervision: Advised 4 Honours theses (Bachelor’s in Agronomy & Agricultural Engineering) at the National University of Mar del Plata & Entre Ríos.
  • International Student Mentorship: Supervised agronomy trials in INTA Balcarce, Argentina.
  • Guest Lectures & Grower Outreach: Delivered talks for growers & industry stakeholders.
  • Leadership & Team Coordination: Developed skills in team management & collaborative research.

Key Achievements

  • Publications: First-authored 7 research papers.
  • PhD Completion: Successfully defended PhD dissertation on March 27, 2017. I was awarded Summa Cum Laude, the highest distinction, for my PhD dissertation.
  • Post-Graduate Course Development: Contributed to Crop Ecophysiology post-graduate course at the National University of Entre Ríos.
  • Advanced Research Instrumentation: Expertise in:
  1. Solar radiation & N content sampling: LI-COR LAI-2000, SPAD-502, LICOR 6400.
  2. Soil Water & Root Sampling: TROXLER 4300 neutron probe, DIVINER 2000 capacitance probe, Delta-T root washer.
  • Field Experimentation & Simulation: Developed experimental design & hypothesis testing skills for crop production & environmental resource management.
  • Scientific Communication: Improved presentation, publication, & lecturing skills.

International Research Collaborations

Stay 1:

Visiting Researcher (May 2015 – Mar 2016) Department of Agronomy, Purdue University, USA Funded by Fulbright Fellowship & US DOE Supervisors: Dr. J. Volenec & Dr. S. Brouder

Research Contributions

  • APSIM Model Development: Developed new APSIM sub-models for switchgrass & Miscanthus for biofuel by modifying existing lucerne & sugarcane crop models.
  • Maize Model Enhancement: Improved APSIM maize model for continuous corn & soybean-corn rotations.
  • Water Balance Modelling: Calibrated water & N flow/drainage subroutine using long-term datasets from Purdue’s Water Quality Field Station.
  • Publications: Contributed to 2 research papers published in high-impact journals.

Stay 2:

Visiting Researcher (Oct 2013 – Dec 2013) University of Sydney (Camden, NSW) & TIA-UTAS (Burnie, TAS, Australia) Funded by INNOVA-T, INTA, University of Sydney & UTAS Supervisors: Dr. S. Garcia, Dr. R. Islam, Dr. K. Pembleton

Research Contributions

  • Lucerne & Ryegrass Modelling: Evaluated APSIM performance for lucerne & annual ryegrass using Argentinian & Australian field data.
  • Yield Predictions: Simulated dry matter yields for both crops in Australian environments. Publications: Contributed to 2 research papers published in high-impact journals.
 
 
 
 
 

Industry Assistant and Agricultural Consultant

DASER AGRO S.A, Dow AgroSciences

Apr 2011 – Apr 2012 Maria Grande, Entre Rios, Argentina

Responsibilities

  • Managed & executed field experiments.
  • Assisted in seed marketing projects.
  • Provided private consulting on agricultural systems.
  • Delivered invited talks for growers.

Key Achievements

  • Developed leadership skills & team coordination.
  • Successfully solved complex, real-world agricultural challenges.
  • Fostered innovation & creativity by integrating novel approaches to improve farming solutions.
 
 
 
 
 

Undergraduate Teaching Assistant – Mathematics I & II

National University of Entre Ríos

Apr 2007 – Apr 2011 Oro Verde, Entre Rios, Argentina

Teaching Responsibilities

  • Taught Mathematics I & II to over 100 undergraduate students.
  • Assisted in research & curriculum development.

Key Achievements

  • Strengthened leadership skills & team coordination in an academic setting.
  • Gained deep expertise in mathematical functions related to crop growth & soil/climate processes.
  • Improved communication skills through lectures & academic discussions.
 
 
 
 
 

Research Fellow

Experimental Station Paraná, National Institute of Agriculture (INTA) Paraná

Apr 2007 – Apr 2011 Oro Verde, Entre Rios, Argentina

Research Responsibilities

  • Designed & conducted a one-season field experiment in Paraná, Argentina under the supervision of Drs. O. Valentinuz & L. Coll.
  • Performed data analysis & manuscript writing.

Key Achievements

  • Acquired hands-on experience in field experimentation & crop production.
  • Developed experimental design skills for on-farm research.
  • Enhanced ability to present scientific findings through written & oral communication.
  • Successfully completed Agricultural Engineering degree & authored an Honours dissertation.

Awards, Prizes & Fellowships

2021

  • Postdoctoral Fellowship (1.5 yr), The University of Queensland, Australia

2020

  • JM Roberts Seed Funding for Sustainable Agriculture (1 yr), Tasmanian Institute of Agriculture, Australia

2017

  • Junior Research Fellowship (3.5 yr), University of Tasmania, Australia
  • Postdoctoral Scholarship (2 yr), University of Pennsylvania, United States (Declined to take another scholarship)
  • Postdoctoral Scholarship (2 yr), The Swedish University of Agricultural Sciences, Sweden (Declined to take another scholarship)
  • Postdoctoral Research Fellowship (2 yr), National Research Council, Argentina

2015

  • Fulbright Fellowship (9 months), Fulbright Commission, United States

2012

  • Graduate Research Scholarship (5 yr), National Research Council, Argentina

2004

  • National Undergraduate Scholarship (6 yr), Argentinian Ministry of Education, Argentina

Grants

Ability to get own funding as chief investigator or partner to do research 💸

2022

DairyUp – Digitising forage options for intensive dairy systems

Responsibility: Collaborator

Funding body: University of Sydney

Partners: NSW Department of Primary Industries (Dr Gargiulo), University of Sydney (Drs Garcia and Islam).

2021 ($6,979,774)

Niche – Analytical framework for crop variety placement and trial site selection in Sub-Saharan Africa

Responsibility: Chief investigator

Funding body: Bill & Melinda Gates Foundation (4 yr).

Partners: University of Lincoln (Dr Grassini), NASA Harvest (Dr Inbal Becker-Reshef), Gates Foundation (Dr Hausmann), One Acre Fund (Dr Aston).

The role of biological fixation on crop productivity, nitrogen use efficiency and N2O emissions in reconfigured crop sequences. Quantification at different spatio-temporal scales (under review)

Responsibility: Chief investigator

Funding body: Argentinian Agency for the Promotion of Research, Technological Development and Innovation PICT-2020-SERIEA-III-A RAICES

Partners: University of Entre Rios, Argentina ( Dr Caviglia); PIRSA-SARDI, Australia ( Dr Sadras)

Radiation use efficiency of grasslands and its use for a better characterization of ecosystem change syndromes

Responsibility: Partner

Funding body: Argentinian Agency for the Promotion of Research, Technological Development and Innovation PICT-2019-I-D

Partners: Regional Analysis and Remote Sensing Lab, University of Buenos Aires, Argentina ( Dr Texeira & Dr Oesterheld)

2020 ($10,000)

Mapping potato yield and irrigation variability under climate change scenarios in Tasmania

Responsibility: Chief investigator

Funding body: JM Roberts Charitable Trust and the University of Tasmania

Partners: Simplot, McCain, Tasmanian Department of Primary Industries, Parks, Water and Environment (DPIPWE) & University of Sydney ( Mat Webb)

2019 ($228,803)

Biomass estimation of forage resources through remote sensing and crop growth simulation models

Responsibility: Partner

Funding body: Argentinian Agency for the Promotion of Research, Technological Development and Innovation PICT-I-A-2018

Partners: Regional Analysis and Remote Sensing Lab, University of Buenos Aires, Argentina ( Dr Irisarri & Dr Oesterheld)

Visualising agricultural uncertainties under climate change scenarios

Responsibility: Chief investigator

Funding body: College of Sciences and Engineering, University of Tasmania

Partners: Simplot, McCain and The Tasmanian Department of Primary Industries, Parks, Water and Environment (DPIPWE) & University of Sydney (Mat Webb)

Crop-livestock adaptation to climate change based on modelling and remote-sensing

Responsibility: Chief investigator

Funding body: Council on Australia Latin America Relations (COALAR) Australia’s Department of Foreign Affairs & Trade, Australian Government

Partners: University of Southern Queensland ( Assoc Prof Pembleton president of the APSIM Initiative), Regional Analysis and Remote Sensing Lab (University of Buenos Aires), National Institute of Agricultural Research (INIA; Uruguay), CREA Farmer Groups (Argentina-Uruguay)

The benefits and limits of diversity in agricultural systems

Responsibility: Chief investigator

Funding body: CSIRO-Tasmanian Institute of Agriculture

Partners: CSIRO Global Food and Nutrition Security, Australia ( Dr Katharina Waha)

Estimating Uncertainty in Crop Models

Responsibility: Chief investigator

Funding body: CSIRO-Tasmanian Institute of Agriculture

Partners: CSIRO Agriculture, Australia ( Dr Neil Huth)

2018 ($743,091)

Towards high crop productivity in agriculture based on multi-scale modelling and climate change impact studies

Responsibility: Chief investigator

Funding body: Universities Australia, German Academic Exchange Service

Partners: The University of Göttingen Prof Siebert, The Leibniz Centre for Agricultural Landscape Research (ZALF) ( Dr Rezaei, Dr Ewert), The University of Bonn ( Dr Kamali), Germany

Improving the representation of soil productivity/constraints in existing decision support systems and modelling platforms

Responsibility: Partner

Funding body: Soil CRC High-Performance Soils

Partners: University of Southern Queensland (Assoc Prof Pembleton), Federation University ( Assoc Prof Peter Dahlhaus & Dr Robinson), NSW Department of Primary Industries

Research Travel Funding Ag Systems Centre & Research Travel Funding Water for Profit Program

2004 – 2017 ($166,279)

Postdoctoral Research Fellowship (2 years)

Funding body: National Research Council, Argentina

Fulbright Fellowship (9 months)

Funding body: Fulbright Commission, United States

Fund INNOVA-T Grant

Funding body: National Research Council, Argentina

Graduate Research Scholarship (5 years)

Funding body: National Research Council, Argentina

National Undergraduate Scholarship (6 years)

Funding body: Argentinian Ministry of Education, Argentina

Research Exchange and Courses

Rwanda & Kenya

2022 - Project activities and visitor
One Acre Fund Regrow Ag

ZALF

2020 - Visiting Researcher
ZALF

University of Southern Queensland

2019 - Research Visitor
USQ CRC

University of Entre Rios

2019 - Course Coordinator
APSIM FCA-UNER

Lincoln University and P&F

2019 - Course Assistant and Visiting Researcher
Dryland Pastures Plant and Food Research Institute

University of Gottingen

2019 - Visiting Researcher
Gottingen

Wageningen University, University of Gottingen and ZALF

2018 - Course Assistant and Visiting Researcher
PDF Course Gottingen ZALF

Purdue University

2015 - Visiting Researcher
Purdue WQFS

University of Sydney and University of Tasmania

2013 - Visiting Researcher
Future Dairy TIA

Partners

International Visitors

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Bahareh Kamali

Postdoctoral Researcher

Large scale agro-hydrological modeling, Model calibration, Parameter estimation, MONICA model

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Fernando Lattanzi

Research Director

Pasture ecophysilogy, C and N dynamics, Forage crops, Dairy, Farm systems modelling

International Collaborators

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Hamish Brown

Scientist

Crop model development, Genotype-environment interactions, Crop eco-physiology, Model development, Soil-plant-climate interactions

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Gonzalo Irisarri

Senior Researcher

Remote sensing, Livestock production, Pastures, Forage crops, Climate change, Spatial variability

Avatar

Ehsan Eyshi Rezaei

Senior Researcher

Development of crop models, Crop phenology, Model up-scaling, Climate change, Heat stress, Drought stress

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Heidi Webber

Head of Integrated Crop System Analysis Group

Modelling crop stress responses, Soil and water conservation in cropping systems, Develop modelling approaches, Integrated biophysical, economic and policy assessment

Collaborators in Australia

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Yunru (Chloe) Lai

Postdoctoral Research Fellow

Pedometrics, Geostatistics, Plant-soil-climate-management interactions, Soil constraints, Agricultural systems modelling

Avatar

Keith Pembleton

Associate Professor

Farming systems, Decision support systems, Crop modelling, Whole-farm analysis, Systems modelling, Dairy systems

Avatar

Katharina Waha

Team Leader Food Systems and Global Change

Regional and global climate change, Model uncertainty analysis, Cross-scale spatial analysis and data integration, Agricultural Systems modelling

Crop Modelling

Niche - Optimising Crop Variety Placement in Sub-Saharan Africa

2021-ongoing

Towards high crop productivity in agriculture based on multi-scale modelling and climate change impact studies

2019-ongoing

APSIM Potato model development - Mapping potato yield variability under diferent GEM scenarios in Tasmania

2018-2020

Improving the representation of soil productivity/constraints in existing DSS and modelling platforms

2019-ongoing

Bestiapop - A python package for climate data extraction, processing and visualisation in crop models

2019-ongoing

Uncertainty decomposition in crop models

2019-ongoing

Linking Crop Modelling & Remote Sensing

Radiation use efficiency and its use for a better characterization of ecosystem change syndromes in grasslands

2021-ongoing

Quantifying the effects of G×E×M on the spatial variability of crop biomass in the US

2020-ongoing

Biomass estimation of forage resources through remote sensing and process-based crop models

2020-ongoing

Crop-livestock adaptation to climate change based on modelling and remote-sensing

2020-ongoing

Bestiapop

A python package to automate the extraction, processing and visualisation of climate data for crop modelling

Developers

  • Jonathan Ojeda (QAAFI, The University of Queensland)
  • Diego Perez (Data Analytics Specialist & Cyber Security Expert)

Overview

Bestiapop (a spanish word that translates to pop beast), is a Python package which allows climate and agricultural data scientists to automatically download SILO’s (Scientific Information for Land Owners) or NASAPOWER gridded climate data and convert this data to files that can be ingested by Crop Modelling Software like APSIM or DSSAT. The package offers the possibility to select a range of grids (0.05° x 0.05° for SILO and 0.5° x 0.5° for NASAPOWER) and years producing various types of output files: CSV, MET (for APSIM), WTH (for DSSAT) and soon JSON (which will become part of Bestiapop’s API in the future). Users can also visualise data statistics (mean, standard deviation, CV, etc) spatially for any selected region in the world.

If you would like to use Bestiapop in Jupyter Notebook, you can see here! You can also try it live in Binder Project without the need to install any software in your computer (Yes! 😄 you do not need to know about Python, Anaconda, etc. to use this tool).

Links

Read more about this project
Pypi
GitHub
readthedocs

Data Science

Making art with Python 🌾 💻 👨‍🌾

Operating systems

Windows, Linux (Ubuntu), Unix.

Programming languages

Python, .NET (medium, APSIM Classic, APSIM Next Generation), C#, Markdown (advanced), R Studio, Shell.

Data analysis and exploration

Python (pandas, statsmodels, sqlite3, json, glob, os, functools, lxml [handling of XML and HTML files], csv).

Machine learning, optimization, linear algebra and statistics

Python (numpy, scipy, scikit-learn [e.g. KMeans used for data clustering], pandas, matplotlib, math).

Data visualization and mapping

Python (seaborn, dask, xarray, cartopy, pyproj, shapefile, netCDF4, geopandas, rasterio, GDAL), remote sensing imagery in vegetation and soil moisture mapping (MODIS, Sentinel2, Sentinel1-SAR), ArcGIS, QGis, netCDF file format, and relational databases. pSIMS (gridded crop model simulations), nco operators (manipulates and analyzes data stored in netCDF in Linux), FluroSense (Regrow Ag cloud-based crop management and analytics platform that drives planting and growing decisions).

Cloud computing, parallel computing and storage

Google Cloud Platform, Docker, Singularity, Amazon Web Services, GitHub repositories, APIs, Swift, SQL tools (Database Client, SQL editor, Visual Query Builder, e.g. DBeaver).

Software development and collaboration tools

Bestiapop (Python package to automate the extraction and processing of climate data for crop modelling, >3000 downloads), Atlassian (Jira and Confluence), Buddy (The DevOps Automation Platform), GitHub operations, Jupyter Notebook/Lab, Spyder, Anaconda, PostMan, Visual Studio.

Mechanistic models and decision support tools

APSIM Next Generation, APSIM Classic, DSSAT, SIMPLACE, MONICA, CropWat, pSIMS, DNDC

Tools development for automated data processing

pSIMSv2

Developers

  • Jonathan Ojeda (QAAFI, The University of Queensland)
  • Pete deVoil (QAAFI, The University of Queensland)

Collaborators

  • Isaiah Huber (Iowa State University)
  • Chris James (School of Agriculture and Food Sciences, The University of Queensland)
  • Diego Perez (Data Analytics Specialist & Cyber Security Expert)

Overview

The original Parallel System for Integrating Impact Models and Sectors (pSIMS) was developed by Elliot et al. (2014) in Python 2, we updated pSIMS to pSIMSV2 which is able to run the APSIM sorghum module at a regional scale (US-wide) using netCDF input data (climate, soil and crop management). pSIMSV2 has the ability to run APSIM using a singularity image which avoid the need to install the soft dependencies manually.

MappingTools

Developer

  • Jonathan Ojeda (QAAFI, The University of Queensland)

Overview

Visualisation tools to map crop features and environmental variables across regions. Main functionalities include: import shp and tif files, use Basemap, edit legend and work with iso_3 codes, plot categories by country, edit legends in the map, inset charts in the map, read netCDF using xarray, explore and plot multidimensional files using xarray, create maps using xarray and dataframes, create 2D dataframe from xarray, create multi-dimensional xarray from 2D pandas dataframe, work with NASS API for crop statistics, etc…

RemoteSensingApplications

Developer

  • Jonathan Ojeda (QAAFI, The University of Queensland)

Overview

Tools to use remote sensing data (MODIS, Sentinel2, NASA-POWER, etc) to validate crop models. These include the data curation and data analysis of remote sensing products before being used to validate models. Examples for linking APSIM Classic and Next Generation outputs with RS products are included.

VarianceDecomposition

Developers

  • Jonathan Ojeda (QAAFI, The University of Queensland)
  • Bahareh Kamali (University of Bonn)

Overview

This tool allows calculating the variance contribution of several factors on different crop model outputs. The theory developed by Monod 2006 was converted to a single Jupyter Notebook through Python. This tool produces a series of plots that allow the user to see the weight of each factor on the variance of crop yield.

WebsiteBuilder

Developer

  • Jonathan Ojeda (QAAFI, The University of Queensland)

Overview

During my free time, I enjoy writing my own webpage (the page you are reading right now!) in Markdown using the Hugo platform. Hugo is a popular static site generator written in the Go programming language. Hugo is jam-packed with features, but one of its main selling points is speed — Hugo takes mere seconds to generate a site with thousands of pages. By default, Hugo uses the Goldmark Markdown processor which is fully CommonMark-compliant.

APSIM Applications

Series of tools to develop and test APSIM using Python and C# 🤓

Variance decomposition of model outputs using APSIM Next Generation

Developers

  • Jonathan Ojeda (Regrow Ag)
  • Bahareh Kamali (University of Bonn)

Video - Tutorial

Overview

This code is able to retrieve APSIM Next Generation outputs and carried out a variance decomposition analysis to identify the main contributors to the variance in selected model outputs (e.g. crop yield). This code calculates the main (ME) and total effect (TE) of a series of factors on the variability of a selected variable (in this example crop biomass).

ME explains the share of the components to model output variability without interactions, i.e. if ME=1, the assessed factors explain the entire proportion of model output variability, but if ME<1, residuals exist which means additional factors are required to explain this variability. TE represents the interaction of a given factor with other factors, i.e. high TE values for a given factor denote high interactions of that factor with other factors, therefore, TE does not include residuals.

APSIMClassicTools & APSIMNextGenTools

Developer

  • Jonathan Ojeda (QAAFI, The University of Queensland)

Overview

Series of tools that allow users to interact between two APSIM versions (Classic and Next Generation) and Python through Jupyter Notebook. Main functionalities include: read .out files and .db files, create new variables, clean model outputs, create time series plots and XY plots, etc.

Data visualization for input model configuration

Developers

  • Jonathan Ojeda (QAAFI, The University of Queensland)
  • Hamish Brown (Plant & Food Research, New Zealand)

Overview

Crop models are usually developed using a test set of data and simulations representing a range of environment, soil, management and genotype combinations. Previous studies demonstrated that errors in the configuration of test simulations and aggregation of observed data sets are common and can cause major problems for model development. However, the extent and effect of such errors are not usually considered as a source of model uncertainty. This code presents a systematic method for testing simulation configuration using extensive visualisation approaches. A crop model – potato (Solanum tuberosum L.) is described to demonstrate the main sources of uncertainty from simulation configuration and data collation. A test set of 426 experiments conducted from 1970 to 2019 in 19 countries were run using the APSIM Next Generation model. Plots were made comparing simulation configuration across the entire test set . This identified a surprising number of errors and inappropriate assumptions that had been made which were influencing model predictions. The approach presented here moved the bulk of the effort from fitting model processes to setting up broad simulation configuration testing and detailed interrogation to identify current gaps for further model development.

APSIM Classic Miscanthus &

APSIM Classic Switchgrass

Developer

  • Jonathan Ojeda (as Fulbright scholar at Purdue University)

Overview

APSIM Classic was modified so that it could accurately predict growth and yield of switchgrass and Miscanthus; two plant species that were not represented in this large, multi-species model. Two existing APSIM sub-models (lucerne, sugarcane) were altered using knowledge of species-specific differences in growth, development and agronomic practices. Large databases for soils and weather were assembled for subsequently association with site-specific yield data of both species and successfully calibration and validation. These NEW APSIM sub-models predict the yield of both species across broad geographies from the East Coast to the Great Plains of the US.

Read the paper in Global Change Biology Bionenergy here

Publications

Field and in-silico analysis of harvest index variability in maize silage

Can we predict maize forage quality as a function of harvest index predictions?
PDF DOI

Calibrating APSIM for forage sorghum using remote sensing and field data under sub-optimal growth conditions

Can we used remote sensing to calibrate crop models?
PDF DOI

Uncertainty in climate change impact studies for irrigated maize cropping systems in southern Spain

Uncertainty decomposition of maize yield in Spain.
PDF DOI

Yield gaps of lucerne (Medicago sativa L.) in livestock systems of Argentina

Lucerne Yield Gaps in Argentina.
Jáuregui J, Ojeda JJ, Berone GD, Lattanzi FA, Baudracco J, Fariña SR, Moot DJ
PDF DOI

Decomposing crop model uncertainty: A systematic review

Crop Model Uncertainty Decomposition.
PDF DOI
See all publications

Conference and poster presentations

Niche - A scalable modelling tool to assess G×E×M interactions at continental scales (oral presentation)

Modelling approaches to select best genotypes by environment
Nov 2, 2022 2:55 PM — 3:15 PM Brisbane Australia

BestiaPop - A Python package to automatically generate and visualise gridded climate data for crop model applications (oral presentation)

Bestiapop functionality and applications
Sep 20, 2022 4:15 PM — 4:25 PM Toowoomba Australia
Slides Video

The importance of simulation configuration to crop model development (oral presentation)

Model uncertainty decomposition and importance of input uncertainty quantification.
Sep 20, 2022 11:25 AM — 11:35 AM Toowoomba Australia
Slides Video

Variance decomposition of model outputs using APSIM Next Generation (video)

Identify the main contributors to the variance in model outputs
Nov 29, 2021 9:00 AM — 10:00 AM Brisbane Australia
Code Video

Multi-resolution analysis of aggregated spatial data to simulate yield and irrigation water demand at regional scales (oral presentation)

We explored the implications of using coarse resolution input data on model outputs
Feb 3, 2020 5:20 PM — 6:00 PM Le Corum Montpellier France
PDF Slides
See all talks

Talks List

Invited talks and guest lectures around the world 🌎

2023

Automation in Weather Data Extraction for Crop Modeling Applications and Environmental Analysis.

Ciclo de Seminarios Ciencia de Datos Aplicada a la Gestión Agronómica, FCA UNMdP – INTA (Remote) – 15 Sep 2023

A Python Package to Automatically Generate and Visualize Gridded Climate Data for Crop Model Applications.

ARD23 Satellite Data Interoperability Workshop, San Francisco, USA (Remote) – 17 May 2023

2022

Niche - A scalable modelling tool to assess G×E×M interactions at continental scales

TropAg International Conference, Brisbane, Queensland, Australia. 31 October-2 November 2022

The importance of simulation configuration to crop model development

20th Australian Agronomy Conference, Toowoomba, Queensland, Australia. 18-22 September 2022

A Python package to automatically generate and visualise gridded climate data for crop model applications

20th Australian Agronomy Conference, Toowoomba, Queensland, Australia. 18-22 September 2022

2021

BestiaPop: A Python Package to Automatically Generate and Visualize Gridded Climate Data for Crop Model Applications

5th Annual Crops in silico Symposium & Hackathon, University of Illinois, USA (online)

Variance Decomposition applied to crop models

APSIM monthly training YouTube videos, Brisbane, Australia

2020

Quantifying data aggregation effects of model inputs on simulate yield and irrigation water demand

at regional scales APSIM Symposium 2020, Brisbane, Australia (cancelled due to COVID19)

Multi-resolution analysis of aggregated spatial data to simulate yield and irrigation water demand

at regional scales iCROPM2020 International Symposium, Montpellier, France

2019

Can we trust in model predictions to assess questions at farm/regional levels?

Workshop Lucerne, Lincoln, New Zealand.

Minimum data requirements for modelling purposes

Simplot/McCain workshop, Devonport, Australia

APSIM Course Workshop

University of Entre Rios, Oro Verde, Argentina

Collaborations and data sharing to improve research outcomes: modelling across scales as a case of study

Data Network Hobart Teas and Workshop, University of Tasmania, Australia

The model up-scaling workshop

University of Gottingen, Germany

Improving the representation of soil productivity/constraints in existing decision support systems

and modelling platforms Soil CRC Conference, Newcastle, Australia

2018

Can we trust in field-scale model predictions to assess the complexity of the agricultural

system at regional levels? Guest Lecture, TIA seminars, University of Tasmania, Australia

A modeller’s life. Guest Lecture, KLA312/KLA535: Farming Systems and Business Management

Guest Lecture, University of Tasmania, Australia

2017

Precipitation use efficiency in annual forage crop sequences and perennial pastures

PhD Dissertation defense. National University of Mar del Plata, Argentina

2016

Water productivity of annual cropping sequences and perennial pastures in Balcarce, Argentina

Crop Sequences Workshop. INTA General Villegas, Argentina

2015

Biomass production and environmental resources use in annual forage crops sequences and perennial pastures in the Argentinian Pampas

University Seminar 2015. National University of Entre Rios, Argentina

Biomass production and environmental resources use in annual forage crops sequences and perennial pastures in the Argentinian Pampas

Oral and public defense of PhD Dissertation Project 2015. National University of Mar del Plata, Argentina

2013

Evaluation of the Agricultural Production Systems Simulator simulating dry matter yield of forage crops sequences in the Argentinean Pampas

Postgraduate Seminar. Faculty of Veterinary Science. The University of Sydney, Australia

2012

Sustainable intensification of forage production

Research Seminar, Instituto Nacional de Tecnologia Agropecuaria, Paraná, Argentina

Sustainable intensification of forage production

Forage Workshop, National Northwest University of Buenos Aires, Argentina

Eco-physiological assessment and analysis of different crops and pasture sequences Animal Production

Research Conference for PhD students. Instituto Nacional de Tecnologia Agropecuaria, Balcarce, Argentina

Production, quality and sustainable management of temperate and mega-thermal grasslands. Forage

Research Workshop for PhD students. Instituto Nacional de Tecnologia Agropecuaria, Rafaela, Argentina

PhD Supervision

The role of biological nitrogen fixation on crop productivity, nitrogen use efficiency and nitrous oxide emissions in reconfigured crop rotations. Quantification at different spatio-temporal scales

Daian Francia Laurenzo
Last updated on Jul 24, 2023

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

Pablo Barbera
Last updated on Jul 24, 2023

Linking remote sensing and crop models to estimate the aboveground biomass of annual and perennial forage crops

Facundo Della Nave
Last updated on Jul 24, 2023

Modelling the effects of farming intensification on the productivity, profitability, greenhouse gas emissions and ecosystems services in livestock systems

Demlie Gebresellassie Zelelew
Last updated on Jul 24, 2023

The benefits and limits of diversity in agricultural systems

Francesco Tacconi
Last updated on Jul 24, 2023

Estimating Uncertainty in Crop Models

Ranju Chapagain
Last updated on Jul 24, 2023

Honours supervision

Agricultural Engineers

National University of Entre Ríos

Agr. Eng. Rodrigo Girard (2018)

Impact of cover crops with different defoliation levels on soil carbon

National University of Mar Del Plata

Agr. Eng. Ariel De Sarro (2017)

Comparative analysis of root production and root distribution in oats (Avena sativa) and tall fescue (Festuca arundinacea Schreb.)

Agr. Eng. Cecilia Gutheim (2015)

Effects of previous crop, additives and pre-wilted in the nutritional quality of oat silage (Avena sativa)

Agr. Eng. Gabriel Eriksen (2014)

Comparative analysis of water productivity between oats (Avena sativa) and tall fescue (Festuca arundinacea Schreb.)

Agr. Eng. Agustin Galleano (2014)

Nutritional evaluation of silage maize-soybean intercropping

Contact