Using numerical plant models and phenotypic correlation space to design achievable ideotypes

Numerical plant models can predict the outcome of plant traits modifications resulting from genetic variations, on plant performance, by simulating physiological processes and their interaction with the environment. Optimization methods complement those models to design ideotypes, i.e. ideal values of a set of plant traits resulting in optimal adaptation for given combinations of environment and management, mainly through the maximization of a performance criteria (e.g. yield, light interception). As use of simulation models gains momentum in plant breeding, numerical experiments must be carefully engineered to provide accurate and attainable results, rooting them in biological reality. Here, we propose a multi-objective optimization formulation that includes a metric of performance, returned by the numerical model, and a metric of feasibility, accounting for correlations between traits based on field observations. We applied this approach to two contrasting models: a process-based crop model of sunflower and a functional-structural plant model of apple trees. In both cases, the method successfully characterized key plant traits and identified a continuum of optimal solutions, ranging from the most feasible to the most efficient. The present study thus provides successful proof of concept for this enhanced modeling approach, which identified paths for desirable trait modification, including direction and intensity.Comment: 25 pages, 5 figures, 2017, Plant, Cell and Environmen

ICROFS news 3/2010 - newsletter from ICROFS

Contents: - Organic RDD application deadline: 13. September 2010 - DARCOF III project, SEED, finalized - VOA3R project website is published - New project: Transparent Food: Quality & Integrity in Food - Why Danish Organic Farming Policy has been succesful - Quality of foraging material and effect on hens feed intake - Chinese organic export model & a Danish future perspective - The climate heroes of the future? - Course: ‘Organic agriculture in a development perspective’ - Brief news on congresses and publication

Global Governance for Environmentally Sustainable Food Systems: Certified Organics in a North – South and South-South Perspective

Challenged to consume with less environmental impact, consumers buy certified organic products to “proxy” environmental governance. The paper explores how far certified organic agriculture is institutionally embedded in Brazil, China, and Egypt. The three case studies illustrate how regulation, including standard-setting and certification processes differ between south and north, in terms of the evolution and nature of certification, as well as stakeholders and agency involved in shaping the regulation. A comparative analysis is presented on south-south differences in this regard along with some possible explanations of these. The paper finally discusses the perspectives in the global success of organic certification and whether it has potential to transform global agriculture towards higher overall levels of sustainability

Simulating Rural Environmentally and Socio-Economically Constrained Multi-Activity and Multi-Decision Societies in a Low-Data Context: A Challenge Through Empirical Agent-Based Modeling

Development issues in developing countries belong to complex situations where society and environment are intricate. However, such sites lack the necessary amount of reliable, checkable data and information, while these very constraining factors determine the populations' evolutions, such as villagers living in Sahelian environments. Beyond a game-theory model that leads to a premature selection of the relevant variables, we build an individual-centered, empirical, KIDS-oriented (Keep It Descriptive & Simple), and multidisciplinary agent-based model focusing on the villagers\' differential accesses to economic and production activities according to social rules and norms, mainly driven by social criteria from which gender and rank within the family are the most important, as they were observed and registered during individual interviews. The purpose of the work is to build a valid and robust model that overcome this lack of data by building a individual specific system of behaviour rules conditioning these differential accesses showing the long-term catalytic effects of small changes of social rules. The model-building methodology is thereby crucial: the interviewing process provided the behaviour rules and criteria while the context, i.e. the economic, demographic and agro-ecological environment is described following published or unpublished literature. Thanks to a sensitivity analysis on several selected parameters, the model appears fairly robust and sensitive enough. The confidence building simulation outputs reasonably reproduces the dynamics of local situations and is consistent with three authors having investigated in our site. Thanks to its empirical approach and its balanced conception between sociology and agro-ecology at the relevant scale, i.e. the individual tied to social relations, limitations and obligations and connected with his/her biophysical and economic environment, the model can be considered as an efficient "trend provider" but not an absolute "figure provider" for simulating rural societies of the Nigrien Sahel and testing scenarios on the same context. Such ABMs can be a useful interface to analyze social stakes in development projects.Rule-Based Modelling, Rural Sahel, Confidence Building, Low-Data Context, Social Criteria

Water and energy footprint of irrigated agriculture in the Mediterranean region

Irrigated agriculture constitutes the largest consumer of freshwater in the Mediterranean region and provides a major source of income and employment for rural livelihoods. However, increasing droughts and water scarcity have highlighted concerns regarding the environmental sustainability of agriculture in the region. An integrated assessment combining a gridded water balance model with a geodatabase and GIS has been developed and used to assess the water demand and energy footprint of irrigated production in the region. Modelled outputs were linked with crop yield and water resources data to estimate water (m3 kg−1) and energy (CO2 kg−1) productivity and identify vulnerable areas or 'hotspots'. For a selected key crops in the region, irrigation accounts for 61 km3 yr−1 of water abstraction and 1.78 Gt CO2 emissions yr−1, with most emissions from sunflower (73 kg CO2/t) and cotton (60 kg CO2/t) production. Wheat is a major strategic crop in the region and was estimated to have a water productivity of 1000 t Mm−3 and emissions of 31 kg CO2/t. Irrigation modernization would save around 8 km3 of water but would correspondingly increase CO2 emissions by around +135%. Shifting from rain-fed to irrigated production would increase irrigation demand to 166 km3 yr−1 (+137%) whilst CO2 emissions would rise by +270%. The study has major policy implications for understanding the water–energy–food nexus in the region and the trade-offs between strategies to save water, reduce CO2 emissions and/or intensify food production