Injury Profile SIMulator, a Qualitative Aggregative Modelling Framework to Predict Injury Profile as a Function of Cropping Practices, and Abiotic and Biotic Environment. II. Proof of Concept: Design of IPSIM-Wheat-Eyespot

Robin, Marie-Hélène; Colbach, Nathalie; Lucas, Philippe; Montfort, Françoise; Cholez, Celia; Debaeke, Philippe; Aubertot, Jean‐Noël

doi:10.1371/journal.pone.0075829

Cited by 16 publications

(7 citation statements)

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“…Several studies, for instance in wheat [26, 38], rice [39], and coffee [7], highlight the importance of identifying production factors (environment, topography, soil, associated plant biodiversity) that influence injury profiles, but few studies related production factors directly to yield losses, with very limited exceptions—such as a yield loss assessment due to pests and diseases in rice [24]. In the case of coffee and other crops that can be grown in agroforestry systems, the associated plant biodiversity and shade cover are probably important production factors that need to be considered in crop-loss assessments due to their influence on crop growth and fruit load, pest and disease injury levels [34], and branch dieback [17].…”

Section: Discussionmentioning

confidence: 99%

Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee

et al. 2017

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The assessment of crop yield losses is needed for the improvement of production systems that contribute to the incomes of rural families and food security worldwide. However, efforts to quantify yield losses and identify their causes are still limited, especially for perennial crops. Our objectives were to quantify primary yield losses (incurred in the current year of production) and secondary yield losses (resulting from negative impacts of the previous year) of coffee due to pests and diseases, and to identify the most important predictors of coffee yields and yield losses. We established an experimental coffee parcel with full-sun exposure that consisted of six treatments, which were defined as different sequences of pesticide applications. The trial lasted three years (2013–2015) and yield components, dead productive branches, and foliar pests and diseases were assessed as predictors of yield. First, we calculated yield losses by comparing actual yields of specific treatments with the estimated attainable yield obtained in plots which always had chemical protection. Second, we used structural equation modeling to identify the most important predictors. Results showed that pests and diseases led to high primary yield losses (26%) and even higher secondary yield losses (38%). We identified the fruiting nodes and the dead productive branches as the most important and useful predictors of yields and yield losses. These predictors could be added in existing mechanistic models of coffee, or can be used to develop new linear mixed models to estimate yield losses. Estimated yield losses can then be related to production factors to identify corrective actions that farmers can implement to reduce losses. The experimental and modeling approaches of this study could also be applied in other perennial crops to assess yield losses.

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Section: Discussionmentioning

confidence: 99%

Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee

et al. 2017

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“…It also allows rules for their design and management to be formalized. With a similar objective, Herzog et al (2012) developed a core set of farmland habitat indicators estimated with a standard mapping procedure based on a generic system of habitat definitions, itself based on management intensity and Raunkiaer's plant life forms (Raunkiaer 1934). This indicator set has been used to link farmland habitats (seminatural and cultivated) to functional biodiversity, e.g., wild bees as pollinators, spiders as generalist predators, and earthworms as soil engineers, and assess the main drivers of species richness and diversity of these organisms in agroecosystems (e.g., Lüscher et al 2014;Schneider et al 2014).…”

Section: Main Advances In Ecology To Characterize Biodiversity-based mentioning

confidence: 99%

How to implement biodiversity-based agriculture to enhance ecosystem services: a review

Duru

Thérond

Martin

et al. 2015

Agron. Sustain. Dev.

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Intensive agriculture has led to several drawbacks such as biodiversity loss, climate change, erosion, and pollution of air and water. A potential solution is to implement management practices that increase the level of provision of ecosystem services such as soil fertility and biological regulation. There is a lot of literature on the principles of agroecology. However, there is a gap of knowledge between agroecological principles and practical applications. Therefore, we review here agroecological and management sciences to identify two facts that explain the lack of practical applications: (1) the occurrence of high uncertainties about relations between agricultural practices, ecological processes, and ecosystem services, and (2) the site-specific character of agroecological practices required to deliver expected ecosystem services. We also show that an adaptive-management approach, focusing on planning and monitoring, can serve as a framework for developing and implementing learning tools tailored for biodiversity-based agriculture. Among the current learning tools developed by researchers, we identify two main types of emergent support tools likely to help design diversified farming systems and landscapes: (1) knowledge bases containing scientific supports and experiential knowledge and (2) model-based games. These tools have to be coupled with well-tailored field or management indicators that allow monitoring effects of practices on biodiversity and ecosystem services. Finally, we propose a research agenda that requires bringing together contributions from agricultural, ecological, management, and knowledge management sciences, and asserts that researchers have to take the position of "integration and implementation sciences."

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“…After reviewing the literature and acquiring expertise on the subject (Supplementary data, Section 1), the IPSIM-chayote model was built using the method described on the IPSIM website (www6.inra.fr/ipsim, Robin et al, 2018) and in previous studies (e.g. Robin et al, 2013). It is based on the DEX method, implemented with the DEXi software (Bohanec, 2020).…”

Section: Model Building Processmentioning

confidence: 99%

“…IPSIM-chayote is the first IPSIM-type model made for crop pests on a tropical crop. Most of the other IPSIM models relate to temperate crops and pathogens (Robin et al, 2013(Robin et al, , 2016(Robin et al, , 2018Aubertot et al, 2016;Demesthias, 2017;Vedy-Zecchini, 2020). The model presents a close, almost perfect agreement with observations (κ QW = 0.79; McHugh, 2012) and makes it possible to accurately predict the intensity of fruit fly damage to chayote crops.…”

Section: Tablementioning

confidence: 99%

“…Models developed using the IPSIM approach can thus contribute to the design of cropping systems which can better manage pests and are therefore less dependent on pesticides. The approach is generic; it can be easily adapted to all types of pests and all crops (Robin et al, 2013(Robin et al, , 2016(Robin et al, , 2018Aubertot et al, 2016;Demesthias, 2017;Vedy-Zecchini, 2020), including fruit flies on chayote crops in Réunion. The main hypothesis of the approach is that the development of any pest is determined only by three main groups of factors: agricultural practices, pedoclimate, and landscape.…”

Section: Introductionmentioning

confidence: 99%

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Qualitative modeling of fruit fly injuries on chayote in Réunion: Development and transfer to users

et al. 2021

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Intensive chayote cultivation in Réunion almost disappeared in the 2000s due to significant yield losses from fruit fly attacks on this historically important crop (Dacus ciliatus, Zeugodacus cuurbitae and Dacus demmerezi). Since the late 2000s, the adoption of agroecological crop protection practices have led to the effective management of fruit fly populations, a significant reduction in pesticide use, an increase in chayote production and plantations, and the development of organic production. To assist in fruit fly management, a qualitative model which simulates fruit fly damage to chayote crops, known as IPSIM-chayote, was developed, providing satisfactory prediction results. It has a user-friendly interface and is now available free of charge online, in three languages (French, English and Spanish): https://pvbmt-apps.cirad.fr/apps/ipsim-chayote/?lang=en. The IPSIM-chayote modeling platform can be used by farmers as a diagnosis to simulate fruit fly damage to their crops and as a decision-making tool for their agricultural practices. The model can be used as a training resource in agroecological crop protection. Public authorities and local government can use it as a tool in planning and forecasting agricultural development. Finally, researchers can use it as a prediction tool and a resource for the exchange of information, allowing them to review scientific knowledge or identify new, relevant research areas suited to the context and challenges. IPSIM-chayote can be considered as a forum for exchange and can stimulate collaborative work between individuals. It is a flexible model, as it allows variables to be added. IPSIM-chayote is the first qualitative model developed for crop pests in a tropical environment. It could serve as a basis for the development of other similar models simulating crop pest incidence, thus contributing significantly to the development of agroecological crop protection.

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Injury Profile SIMulator, a Qualitative Aggregative Modelling Framework to Predict Injury Profile as a Function of Cropping Practices, and Abiotic and Biotic Environment. II. Proof of Concept: Design of IPSIM-Wheat-Eyespot

Cited by 16 publications

References 57 publications

Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee

Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee

How to implement biodiversity-based agriculture to enhance ecosystem services: a review

Qualitative modeling of fruit fly injuries on chayote in Réunion: Development and transfer to users

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