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

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...

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Autores principales: Cerda, Rolando, Avelino, Jacques, Gary, Christian, Tixier, Philippe, Lechevallier, Esther, Allinne, Clémentine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5207401/
https://www.ncbi.nlm.nih.gov/pubmed/28046054
http://dx.doi.org/10.1371/journal.pone.0169133
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author Cerda, Rolando
Avelino, Jacques
Gary, Christian
Tixier, Philippe
Lechevallier, Esther
Allinne, Clémentine
author_facet Cerda, Rolando
Avelino, Jacques
Gary, Christian
Tixier, Philippe
Lechevallier, Esther
Allinne, Clémentine
author_sort Cerda, Rolando
collection PubMed
description 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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spelling pubmed-52074012017-01-19 Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee Cerda, Rolando Avelino, Jacques Gary, Christian Tixier, Philippe Lechevallier, Esther Allinne, Clémentine PLoS One Research Article 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. Public Library of Science 2017-01-03 /pmc/articles/PMC5207401/ /pubmed/28046054 http://dx.doi.org/10.1371/journal.pone.0169133 Text en © 2017 Cerda et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Cerda, Rolando
Avelino, Jacques
Gary, Christian
Tixier, Philippe
Lechevallier, Esther
Allinne, Clémentine
Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee
title Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee
title_full Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee
title_fullStr Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee
title_full_unstemmed Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee
title_short Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee
title_sort primary and secondary yield losses caused by pests and diseases: assessment and modeling in coffee
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5207401/
https://www.ncbi.nlm.nih.gov/pubmed/28046054
http://dx.doi.org/10.1371/journal.pone.0169133
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