Tesi etd-09302025-143625
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Tipo di tesi
Dottorato
Autore
TRIACCA, ALESSANDRO
URN
etd-09302025-143625
Titolo
Intercropping in silico: a process-based modelling framework to harness agrobiodiversity from field evidence to future scenarios
Settore scientifico disciplinare
AGR/02
Corso di studi
Istituto di Scienze della Vita - PH.D. IN AGROBIODIVERSITY
Relatori
relatore Prof.ssa MOONEN, ANNA CAMILLA
Parole chiave
- intercropping
- crop model
- process-based modelling
- climate change
Data inizio appello
06/02/2026;
Disponibilità
parziale
Riassunto analitico
Feeding a growing population within planetary boundaries requires cropping systems that couple
productivity with ecosystem-service delivery. Intercropping, particularly cereal–grain legume
mixtures, offers such potential but remains underused in Europe due to design sensitivity, data
gaps, and modelling limitations that hinder credible decision support. This thesis advances field-
scale diversification by developing a generic, robust, and simple intercrop modelling framework to
underpin a farmer-oriented decision support system (DSS).
The research proceeds along three strands. First, to ground modelling in evidence and fill key gaps,
we designed and implemented harmonized field trials over two seasons (2023–2024) at two
contrasting European sites (Mediterranean Italy; continental Germany), testing durum wheat and
oat with lentil and chickpea under low-input/organic management. High-frequency observations
(phenology, biomass, LAI, canopy structure, soil water and mineral N, weeds, grain yield and
quality) generated an extensive dataset for process understanding and model evaluation.
Second, we adapted a structured, multi-variable calibration protocol to parameterize the MONICA
crop model for lentil and chickpea using literature, direct measurements, and
sequential/simultaneous optimization against multi-environment datasets, with an independent
Europe-wide yield dataset for evaluation. This delivers transferable parameter sets for “minor”
legumes and identifies priorities for improvement (e.g., biomass partitioning, maturity, soil detail).
Third, we introduce MONICoSMo, which couples MONICA with a suitability-weighted community
formalism (CoSMo) to simulate intercrops using one calibrated sole-crop instance per species
interacting through a shared soil. Daily suitability functions partition light, water, and mineral N by
suitability-weighted demand, adding only one structural parameter (inertia) while preserving sole-
crop behaviour and avoiding dominant-crop allocation biases. The framework is evaluated across
multiple species pairings and spatial arrangements (mixed, relay, row), with sensitivity analyses
treating initial relative abundance and driver hierarchy as structural uncertainties.
Together, these contributions establish the foundations of an operational intercrop DSS: (i) rich,
multi-variable datasets; (ii) calibrated legume modules; and (iii) a parsimonious, mechanism-
based framework capable of reproducing observed competition/facilitation patterns and screening
intercrop designs for yield, land-use efficiency, and associated ecosystem services. The thesis
closes by outlining co-design steps with farmers and data/model developments needed to scale
decision support for Europe’s agroecological transition.
productivity with ecosystem-service delivery. Intercropping, particularly cereal–grain legume
mixtures, offers such potential but remains underused in Europe due to design sensitivity, data
gaps, and modelling limitations that hinder credible decision support. This thesis advances field-
scale diversification by developing a generic, robust, and simple intercrop modelling framework to
underpin a farmer-oriented decision support system (DSS).
The research proceeds along three strands. First, to ground modelling in evidence and fill key gaps,
we designed and implemented harmonized field trials over two seasons (2023–2024) at two
contrasting European sites (Mediterranean Italy; continental Germany), testing durum wheat and
oat with lentil and chickpea under low-input/organic management. High-frequency observations
(phenology, biomass, LAI, canopy structure, soil water and mineral N, weeds, grain yield and
quality) generated an extensive dataset for process understanding and model evaluation.
Second, we adapted a structured, multi-variable calibration protocol to parameterize the MONICA
crop model for lentil and chickpea using literature, direct measurements, and
sequential/simultaneous optimization against multi-environment datasets, with an independent
Europe-wide yield dataset for evaluation. This delivers transferable parameter sets for “minor”
legumes and identifies priorities for improvement (e.g., biomass partitioning, maturity, soil detail).
Third, we introduce MONICoSMo, which couples MONICA with a suitability-weighted community
formalism (CoSMo) to simulate intercrops using one calibrated sole-crop instance per species
interacting through a shared soil. Daily suitability functions partition light, water, and mineral N by
suitability-weighted demand, adding only one structural parameter (inertia) while preserving sole-
crop behaviour and avoiding dominant-crop allocation biases. The framework is evaluated across
multiple species pairings and spatial arrangements (mixed, relay, row), with sensitivity analyses
treating initial relative abundance and driver hierarchy as structural uncertainties.
Together, these contributions establish the foundations of an operational intercrop DSS: (i) rich,
multi-variable datasets; (ii) calibrated legume modules; and (iii) a parsimonious, mechanism-
based framework capable of reproducing observed competition/facilitation patterns and screening
intercrop designs for yield, land-use efficiency, and associated ecosystem services. The thesis
closes by outlining co-design steps with farmers and data/model developments needed to scale
decision support for Europe’s agroecological transition.
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