Simulation modelling applied to grapevine is a promising tool to unravel the tight interactions between agricultural management and pedo-climatic conditions, and their impact on yield variability. This is an urgent need in current conditions, and in light of climate change, which is expected to deeply affect the performances of vine cropping systems. Here we present a BioMA software component (UNIFI.GrapeML), which is a model library of grapevine physiological processes. We used it to develop a new grapevine model considering the impact of soil water availability on yield, selecting a Spanish vineyard as case study (Chardonnay variety). We inspected its behavior with sensitivity analysis techniques, selecting the most relevant parameters to calibrate for matching reference data. The accuracy in reproducing phenology (average Pearson (r) over bar = 0.57), soil water content ((r) over bar = 0.70) and yield (r = 0.59) proved its capability to respond to weather variability, and the efficiency of BioMA software architecture in developing agricultural models.

A model library to simulate grapevine growth and development: software implementation, sensitivity analysis and field level application

Moriondo M;
2018

Abstract

Simulation modelling applied to grapevine is a promising tool to unravel the tight interactions between agricultural management and pedo-climatic conditions, and their impact on yield variability. This is an urgent need in current conditions, and in light of climate change, which is expected to deeply affect the performances of vine cropping systems. Here we present a BioMA software component (UNIFI.GrapeML), which is a model library of grapevine physiological processes. We used it to develop a new grapevine model considering the impact of soil water availability on yield, selecting a Spanish vineyard as case study (Chardonnay variety). We inspected its behavior with sensitivity analysis techniques, selecting the most relevant parameters to calibrate for matching reference data. The accuracy in reproducing phenology (average Pearson (r) over bar = 0.57), soil water content ((r) over bar = 0.70) and yield (r = 0.59) proved its capability to respond to weather variability, and the efficiency of BioMA software architecture in developing agricultural models.
2018
Istituto di Biometeorologia - IBIMET - Sede Firenze
BioMA platform
Chardonnay
Latin hypercube sampling
Simplex optimization
Sobol' total order Vineyard
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/404831
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