APSIM: a novel software system for model development, model testing and simulation in agricultural systems research

McCown, R. L.; Hammer, Graeme; Hargreaves, J. N. G.; Holzworth, Dean; Freebairn, D. M.

doi:10.1016/0308-521x(94)00055-v

Cited by 707 publications

(252 citation statements)

References 20 publications

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“…Regarding decision support software in general, several authors stress the users' lack of involvement in the design process to explain their less frequent adoption of models developed by agronomists acting as decision support system designers McCow et al 1996;Prost et al 2012). The most common reasons cited for these failures are inadequate consideration of the concerns and challenges users encounter, their technical or organizational constraints, and their expectations about the accuracy of results for decisionmaking.…”

Section: Role and Place Of The Participatory Approach During The Desimentioning

confidence: 99%

Guidelines to design models assessing agricultural sustainability, based upon feedbacks from the DEXi decision support system

Craheix¹,

Bergez²,

Angevin³

et al. 2015

Agron. Sustain. Dev.

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New agricultural systems are required to satisfy societal expectations such as higher quantity and quality of agricultural products, reducing environmental impacts, and more jobs. However, identifying and implementing more suitable agricultural systems is difficult due to conflicting objectives and to the wide diversity of scientific disciplines required to solve agricultural issues. Therefore, designing models to assess the sustainability of agricultural systems requires multicriteria decision aid methods. The French agronomist community has recently developed 11 hierarchical and qualitative models to assess sustainability using the DEXi decision aid software. Here, we give guidelines to help designers to build their own specific models. First, we present the principles and applications of the DEXi software. Then, we provide guidance on the following steps of model designing: (1) initial analysis and planning of the design process, (2) selection and hierarchy of sustainability criteria, (3) indicator selection and building, (4) parameterization, (5) evaluation, and (6) model dissemination and uses. We then discuss advantages and drawbacks of this kind of modeling formalism, the role of a participatory approach, and the main properties to consider during the design process.

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Section: Role and Place Of The Participatory Approach During The Desimentioning

confidence: 99%

Guidelines to design models assessing agricultural sustainability, based upon feedbacks from the DEXi decision support system

Craheix¹,

Bergez²,

Angevin³

et al. 2015

Agron. Sustain. Dev.

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“…Se utilizaron dos modelos matemáticos: uno para predicción del rendimiento de los cultivos denominado APSIM (McCown, 1996;Keating et al, 2003), y otro para evaluación del sistema lechero completo, denominado e-Dairy (Baudracco et al, 2013). Los modelos se utilizaron para realizar simulaciones determinísticas y simulaciones estocásticas.…”

Section: Modelos De Simulación Utilizadosunclassified

Productividad, Resultado Económico Y Riesgo De Sistemas Lecheros en El Centro-Norte De Argentina

Baudracco

Maiztegui

Jáuregui

et al. 2017

Chil. j. agric. anim. sci.

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RESUMENLas variaciones en el precio de la leche y de los alimentos concentrados y el efecto del clima sobre la producción de cultivos afectan la productividad rentabilidad y riesgo de los sistemas lecheros. El objetivo del estudio fue investigar la productividad, el resultado económico y el riesgo de diversos sistemas de producción de leche en la región Centro-Norte de Argentina. Se investigaron sistemas lecheros alternativos al sistema representativo de la región, explorando el efecto de incrementos en carga animal, incrementos en suplementación con alimentos concentrados y el efecto de utilizar diferentes sistemas de alimentación sobre la productividad y la rentabilidad. El enfoque elegido para el análisis fue la simulación con el uso de dos modelos matemáticos: uno para predicción del rendimiento de cultivos y otro para evaluación del sistema lechero completo. Se realizaron simulaciones determinísticas y estocásticas, i.e., con variación aleatoria del precio de la leche, de los concentrados y el rendimiento de los cultivos. Los resultados muestran que el sistema actual de la región no es rentable. Los sistemas alternativos con mayor carga animal y mayor suplementación resultaron en mayor producción de leche por hectárea y mayor resultado económico que el sistema regional actual. Sin embargo, la intensificación a partir del incremento de la carga animal y de la suplementación aumentó la exposición al riesgo. El efecto de la variación de precio de leche y concentrado fue mayor que el efecto del clima sobre el resultado económico.Palabras clave: estocástico, carga animal, modelo, precios, clima, leche. ABSTRACTVariations in milk and concentrate feed prices and the effect of climate on crop production affect productivity and profitability of dairy systems. The objective of this study was to evaluate productivity and economic results, and assess the risk of different dairy systems in the Central-Northern region of Argentina. Alternative dairy systems (other than the traditional system of this region) were studied, evaluating the effects of increases in stocking rate and use of supplementary feed, as well as the effect of using different feeding systems on productivity and profitability. Two mathematical models were used in this analysis: one model to predict crop and pasture production, and the other to evaluate the performance of the whole dairy system. Deterministic and stochastic simulations, i.e., with random variation in milk and concentrate feed prices, and crop yield, were performed. Results showed that the current production system of this region is not profitable. The alternative systems 152-162.

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“…Modelling tools that have the capability to incorporate seasonal forecasting into grazing (GRASP; McKeon et al 1990) and farming (APSIM; McCown et al 1996) systems enable whole-ofsystem simulations to compare the factors that influence agricultural productivity. In this way the value of using a seasonal forecast can be identified and used to help decision making.…”

Section: Develop Tools That Enable Analysis Of Decision Options In Comentioning

confidence: 99%

Summative evaluation of climate application activities with pastoralists in western Queensland

Cobon¹,

Bell²,

Park³

et al. 2008

Rangel. J.

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Abstract. Survey methods were engaged to measure the change in use and knowledge of climate information by pastoralists in western Queensland. The initial mail survey was undertaken in 2000-01 (n = 43) and provided a useful benchmark of pastoralists climate knowledge. Two years of climate applications activities were completed and clients were re-surveyed in 2003 (n = 49) to measure the change in knowledge and assess the effectiveness of the climate applications activities. Two methods were used to assess changes in client knowledge, viz., self-assessment and test questions. We found that the use of seasonal climate forecasts in decision making increased from 36% in 2001 (n = 42) to 51% in 2003 (n = 49) (P = 0.07). The self-assessment technique was unsatisfactory as a measure of changing knowledge over short periods (1-3 years), but the test question technique was successful and indicated an improvement in climate knowledge among respondents. The increased levels of use of seasonal climate forecasts in management and improved knowledge was partly attributed to the climate applications activities of the project.Further, those who used seasonal forecasting (n = 25) didn't understand key components of forecasts (e.g. probability, median) better than those who didn't use seasonal forecasts (n = 24) (P > 0.05). This identifies the potential for misunderstanding and misinterpretation of forecasts among users and highlights the need for providers of forecasts to understand the difficulties and prepare simply written descriptions of forecasts and disseminate these with the maps showing probabilities.The most preferred means of accessing climate information were internet, email, 'The Season Ahead' newsletter and newspaper. The least preferred were direct contact with extension officers and attending field days and group meetings. Eighty-six percent of respondents used the internet and 67% used ADSL broadband internet (April 2003). Despite these findings, extension officers play a key role in preparing and publishing the information on the web, in emails and newsletters. We also believe that direct contact with extension officers trained in climate applications is desirable in workshop-like events to improve knowledge of the difficult concepts underpinning climate forecasts, which may then stimulate further adoption.

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APSIM: a novel software system for model development, model testing and simulation in agricultural systems research

Cited by 707 publications

References 20 publications

Guidelines to design models assessing agricultural sustainability, based upon feedbacks from the DEXi decision support system

Guidelines to design models assessing agricultural sustainability, based upon feedbacks from the DEXi decision support system

Productividad, Resultado Económico Y Riesgo De Sistemas Lecheros en El Centro-Norte De Argentina

Summative evaluation of climate application activities with pastoralists in western Queensland

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