期刊
AGRICULTURAL SYSTEMS
卷 193, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.agsy.2021.103209
关键词
Digital agriculture; Vineyard management; Decision support; Process-based model
资金
- Wine Australia
- Riverland Wine
This paper reviews process-based models that can simulate key vineyard outcomes and their sensitivity to decisions and exogenous factors, highlighting their ability to bridge the gap between data and decisions. The models are most advanced in supporting decisions related to water management and least advanced in terms of nutrient management, with a better suitability for decisions regarding yield compared to grape composition attributes.
Context: Effective vineyard decision making at strategic and operational timescales requires consideration of many factors, including vineyard design and management options, exogenous factors that are outside of the decision maker's control such as climate/weather, and desired outcomes such as yield and grape composition attributes. Process-based models enable prediction of vineyard outcomes in response to different decisions and with respect to exogenous factors. Objective: We present a review of process-based models that can simulate both key vineyard outcomes and their sensitivity to decisions and exogenous factors, and highlight how these models can 'bridge the gap' between data and decisions. Methods: We assess the suitability of process-based models to water, canopy and nutrient management contexts using a conceptual systems framework. Results and Conclusions:Currently available process-based models are most advanced in terms of supporting decisions regarding water management, and least advanced regarding nutrient management. They are also better suited to support decisions with respect to yield, compared to grape composition attributes. Significance: This paper provides guidance to modelling practitioners regarding appropriate process-based models for a range of vineyard decision contexts and assists viticulturists and decision makers in understanding how these models can support decisions for improved outcomes.
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