Marie Launay

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

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Iñaki García de Cortázar Atauri

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

ÉJ

Éric Justes

Centre de Coopération Internationale en Recherche Agronomique pour le Développement

Samuel Buis

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

Dominique Ripoche

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

Patrice Lecharpentier

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

Marie‐Odile Bancal

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

Bruno Mary

Institut Charles Viollette

Julie Caubel

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

Nadine Brisson

Biologie et Gestion des Risques en Agriculture

Kurt Christian Kersebaum

Leibniz Centre for Agricultural Landscape Research

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Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

219

Institut National de la Recherche Agronomique

112

Centre National de la Recherche Scientifique

AgroParisTech

Centre de Coopération Internationale en Recherche Agronomique pour le Développement

Université de Montpellier

Agroécologie

Département Environnement et Agronomie

Institut National de la Recherche Agronomique du Niger

Université Paris-Saclay

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Recent advances in intercropping modelling: the new version of the STICS soil-crop model simulates consistently a wide range of bi-specific annual intercrops.

HAL (Le Centre pour la Communication Scientifique Directe) (2021)

Éric Justes Rémi Vézy Sebastian Munz Kirsten Paff Laurent Bedoussac

STICS is a dynamic soil-crop model capable of simulating diverse crop rotations over short and long-term (Brisson et al., 2003). Intercropping increases the complexity of the system by adding inter-species competition. Crop models are useful tools for analyzing complex systems, as they allow the user far more control over individual variables than is possible in field experiments. An initial version of the STICS intercrop model was created by Brisson et al. (2004) from the standard version (Brisson et al., 2003). Recently Vezy et al. (2020) improved this initial version [STICS-Intercrop_v2020] by adding new formalisms and replacing some equations which were not found relevant during the first step of testing with our database. The aim of paper is to present the STICS-Intercrop_v2020 functions and to show the quality of simulations obtained for a wide range of winter and spring intercrop mixtures of durum wheat - winter pea and barley - spring pea. STICS-Intercrop_v2020 was tested for two sites in France using various plant densities and N-fertilizer rates in order to determine its relevance and validity domain for simulating intercropping. This research work was done in 3 main steps: 1) improving the existing formalisms and introducing new equations in the model algorithm for improving the light sharing and nitrogen competition between the two species, and then creating the new version STICS-Intercrop_v2020; 2) parameterising the model for sole crops only; and 3) independently evaluating the quality of predictions for intercrops without any re-parametrisation. The results of parametrisation were satisfactory with low Root Mean Square Errors and high Model Efficiencies, illustrating the robustness and accuracy for sole crops, as already shown for many crops, pedoclimatioc conditions and agronomic managements (Brisson et al., 2003). STICS-Intercrop_v2020 was reliably and efficient to simulate inter-specific interactions, development and growth variables, and provided coherent results for predicting yield and grain protein content for the two species, in winter and spring bi-specific cereal-legume intercrops, without any specific parameterization for intercropping. This illustrates the relevance of the formalisms to simulate dynamically both intra and inter-specific plant interactions. These results are very encouraging for using the STICS-intercrop model for future work where virtual experiments will help us to analyse the performance (LER, level of production in low inputs systems, etc.) and resilience of sole crops versus intercrops according to management practices, pedoclimatic variability and climate change scenarios. This work was part of the ReMIX project funded by EU H2020 program.

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Accuracy, robustness and behavior of the STICS soil–crop model for plant, water and nitrogen outputs: Evaluation over a wide range of agro-environmental conditions in France

Environmental Modelling & Software (2014)

Elsa Coucheney Samuel Buis Marie Launay Julie Constantin Bruno Mary

Robustness

Precision Agriculture

10.1016/j.envsoft.2014.11.024

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Citations (169)

STICS: a generic and robust soil-crop model for modelling agrosystems response in various climatic conditions

HAL (Le Centre pour la Communication Scientifique Directe) (2015)

Nicolas Beaudoin Samuel Buis Dominique Ripoche Éric Justes Patrick P. Bertuzzi

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Agroclimatic study of climate change in the Luberon AOC

Renan Le Roux Carina Furusho‐Percot Marie Launay Garcia de Cortazar Atauri

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Does intercropping winter wheat (Triticum aestivum) with red fescue (Festuca rubra) as a cover crop improve agronomic and environmental performance? A modeling approach

Field Crops Research (2010)

I. Shili-Touzi Stéphane de Tourdonnet Marie Launay Thierry Doré

Intercropping

10.1016/j.fcr.2009.11.007

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Citations (47)

Pea-barley intercrops use nitrogen sources 20-30% more efficiently than the sole crops

Henrik Hauggaard‐Nielsen Per Ambus Nadine Brisson Yves Crozat C. Dahlmann

Field pea (Pisum sativum L.) and spring barley (Hordeum vulgare L) were intercropped and sole cropped to compare the effects of crop diversity on the use of nitrogen sources in European organic crop-ping systems. Across a wide range of growing condi-tions pea-barley intercropping showed that nitrogen sources were used from 17 to 31% more efficiently by the intercrop than by the sole crops. Intercropping technologies offers the opportunity for organic cropping systems to utilize N complementarity between component crops, without compromising total crop N yield levels

Intercropping

Field pea

Monoculture

Cropping system

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Developing a Method to Simulate and Evaluate Effects of Adaptation Strategies to Climate Change on Wheat Crop Production: A Challenging Multi-Criteria Analysis

Christophe Gigot Doriane Hamernig Violaine Deytieux Ibrahima Diallo Olivier Deudon

Adaptation of cropping management strategies is necessary to ensure the sustainability of our agriculture, which is facing threats arising from climate change. A methodology is proposed to find out and compare the most promising adaptation strategies in this context considering both biotic and abiotic stresses. A set of pre-selected strategies were evaluated based on economic, plant health and environmental criteria. A dedicated workflow combining the STICS crop model, epidemiological models and multi-criteria analysis was designed, implemented and tested for a wheat production situation. Flexible by design, this methodology can consider different criteria weights to be used as an exchange support with stakeholders.

Crop Production

Crop Management

10.3390/engproc2021009021

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Modelling intercrops functioning to advance the design of innovative agroecological systems

Research Square (Research Square) (2022)

Rémi Vézy Sebastian Munz Noémie Gaudio Marie Launay Patrice Lecharpentier

Abstract The growing demand for sustainable agriculture is raising interest in intercropping for its multiple potential benefits. Predicting the existence and magnitude of those benefits remains a challenge given the numerous interactions between the plants, their environment and the agricultural practices. Crop models are crucial to understand and predict such interactions, yet few are able to simulate bi-specific intercrops correctly, mainly because they contradict assumptions used to simulate sole crops.In this study, we propose simple and generic formalisms for key interactions in intercropping systems that can be readily included into existing dynamic crop models. We provide an implementation into the STICS soil-crop model with an independent evaluation of the consistency and genericity of the combined formalisms under a wide range of conditions. Simulations were close to observations for all situations (nRMSE = 25% for max. LAI, 22% for shoot biomass at harvest, and 17% for yield), which showed the consistency and accuracy of the proposed formalisms despite their relative simplicity.

Intercropping

Agroecology

Simplicity

10.21203/rs.3.rs-1930394/v1

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Long-term nitrogen dynamics in various catch crop scenarios: Test and simulations with STICS model in a temperate climate

Agriculture Ecosystems & Environment (2011)

Julie Constantin Nicolas Beaudoin Marie Launay John R. Duval Bruno Mary

Arable land

Nitrogen Cycle

DSSAT

10.1016/j.agee.2011.06.006

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Citations (95)

Data, code and software to reproduce the article entitled "Modelling intercropping functioning to support sustainable agriculture"

Zenodo (CERN European Organization for Nuclear Research) (2022)

Rémi Vezy Sebastian Munz Noémie Gaudio Marie Launay Patrice Lecharpentier

This is the data, code and software to reproduce the article entitled "Modelling intercropping functioning to support sustainable agriculture". Here is a summary of the paper: The growing demand for sustainable agriculture is raising interest in intercropping for its multiple potential benefits, including decreasing nitrogen and pesticide inputs while maintaining, or even surpassing the productivity of sole crops. Yet, predicting the existence and magnitude of those benefits remains difficult due to the numerous interactions between plants, their environment and agricultural practices. Crop models are efficient tools used to understand and predict the trends of crop development, growth and yield, under various pedoclimatic conditions, management practices, and climate change scenarios. However, few of those models are able to simulate bi-specific intercropping systems, mainly because it would break assumptions generally used to simulate homogeneous sole crops, such as spatially homogeneous structure and plant-plant interactions only via density. In this study, we improved the STICS soil-crop model to account for bi-specific intercrops (STICS-IC), and proposed new formalisms when needed, i.e. to simulate correctly dynamic interspecific plant-plant interactions. We proposed simple, generic formalisms that can readily be calibrated and further integrated into other crop models. The improved formalisms of STICS-IC concern mainly light interception, plant and root density effects, nitrogen (N) uptake and N stress assessment in intercrop. We provide an example of simulations for bi-specific intercrops with an evaluation of the consistency and genericity of the model to simulate a wide range of species and intercropping designs, and then determine its validity domain. The genotypic parameters of STICS-IC were calibrated using only the sole crops and the model was evaluated independently on intercropping systems with the same parameters’ values. The simulated daily variables representing the soil-crop interactions in intercrops, i.e. LAI, plant height, shoot dry mass, nitrogen uptake, and yield were assessed with a dataset of various types of intercrops. Simulations were close to the observed values over all situations (nRMSE = 30% for LAI, 10% for final height, 22% for final shoot dry mass, and 17% for yield), which showed the consistency of the STICS-IC model despite the relative simplicity of the formalisms and their calibration on sole crops only.

Intercropping

Code (set theory)

10.5281/zenodo.6803363

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Citations (1)