Anabelle Laurent

Accueil
CV
Anabelle Laurent

Anabelle Laurent

Doctorante

Anabelle Laurent
Coordonnées

Mails:

alaurent@iastate.edu

anabelle.laurent@inrae.fr

Key words: on-farm research network, yield analysis, data visualization, crop production

The analysis of data from on-farm research network: Statistical approaches to test the efficacy of new management practices and data visualization

Supervisors: Fernando Miguez (Iowa State University) & David Makowski

Thèse en cotutelle ISU et ABIES

Abstract

On-farm research can be defined as research carried out on farmers’ fields and farmers’ environment (FAO, 2017). Experiments are conducted by the farmers themselves, under the guidance of the research team. Working under the farmers’ environment means that not all the variables can be controlled, such as seeding conditions or soil texture, for example. Therefore, it can be challenging to analyze on-farm data among other reasons because explanatory variables are unbalanced. In order to test a treatment, the experimental design and the environment have to be controlled to minimize the possibility to affect the results and the conclusion. For example, working under greenhouse conditions or with small plot research, both typically performed in a university setting, are two ways to control the environment as much as possible. The main shortcomings of these experiments are that they do not represent the range of conditions observed in growers’ fields and yield is often overestimated. This is why on-farm research has become more common in recent years. An extension of this is an on-farm research network which is a way to share useful information and knowledge across a group of farmers and also with industry and academia.

The statistical analysis of on-farm trials raises two important issues. First, on-farm networks may vary in terms of numbers of trials, numbers of years where data are collected and include different numbers of replicates. Second, trials from an on-farm research network usually covers contrasting environments corresponding to different soils, climates, and cropping systems (crop sequence and managements technique over time for a trial). There is a pressing need to develop approaches that can deal with data from an on-farm research network far and beyond those available from individual reports. In fact, individual reports cannot provide an estimate of the probability that a new management practice will or will not perform for many farmers. As several trials across a state or a region are included in an on-farm network, a more general analysis of the efficacy of a practice or product should be provided.

This project will demonstrate the importance of identifying appropriate statistical methods for analyzing on-farm research network data. It will also provide recommendations to create protocols for standardizing data, formatting datasets, conducting statistical analyses, and producing visual representations of the results (through a web application tool).

Education

M.S., Agroecology, Ecole Supérieure d'Agriculture (Angers, France), 2012

Links

Researchgate

Linkedin

Google Scholar

Voir aussi

Scientific papers

Ranking yields of energy crops: a meta-analysis using direct and indirect comparisons

A Laurent, E Pelzer, C Loyce, D Makowski

Renewable and Sustainable Energy Reviews 46, 41-50

 

Using site-specific data to estimate energy crop yield

A Laurent, C Loyce, D Makowski, E Pelzer

Environmental Modelling & Software 74, 104-113

 

Co-design and ex ante assessment of cropping system prototypes including energy crops in Eastern France

C Lesur-Dumoulin, A Laurent, R Reau, L Guichard, R Ballot, MH Jeuffroy, C Loyce

Biomass and Bioenergy 116, 205-215

Oral communications

  • Ranking yields of energy crops: A meta-analysis using direct and indirect comparisons. A. Laurent, E. Pelzer, C. Loyce, D. Makowski. 106th ASA Annual Meeting 59th CSSA Annual Meeting 78th SSSA Annual Meeting, 2-5 November 2014, Long Beach, USA.
  • Analysis of on-farm data using a Bayesian hierarchical model. Anabelle Laurent, Peter Kyveryga, David Makowski, Fernando Miguez. ASA, CSSA & SSSA International meeting, October 22-25, 2017 Tampa, Florida
  • Mastering agronomic decisions through on-line summaries on on-farm replicated strip trials. Fernando Miguez & Anabelle Laurent (2 speakers), Peter Kyveryga. ISA Farmers Research Conference, February 6-7 2018, Des Moines, IA.
  • Share and summarize data from on-farm research network through a web application: a way to make agronomic decision. Anabelle Laurent, Fernando Miguez, David Makowski, Peter Kyveryga. Production Agriculture Symposium, February 15th 2018, University of Minnesota, Minneapolis
  • Analysis of soybean data from on-farm research network to assess the efficacy of new management practices. Anabelle Laurent, Peter Kyveryga, David Makowski, Fernando Miguez. Research Seminar “Recent advances in soybean agronomic research”, June 28th 2018, Paris
  • Interactive graphics and analysis of on-farm research network data. Anabelle Laurent, Fernando Miguez, David Makowski, Peter Kyveryga. ASA, CSSA & SSSA International meeting, November 04-07, 2018 Baltimore, Maryland
  • Assessing yield of Miscanthus x Giganteus and Miscanthus sinensis grown under several planting methods: results from a multi-environment trial in the North of France. Chantal Loyce, Anabelle Laurent, Magali Berthou, Elsa Borujerdi, Arnaud Butier, Dominique Romelot, Pierre Malvoisin. ASA, CSSA & SSSA International meeting, November 04-07, 2018 Baltimore, Maryland

Posters

  • Iterative design and ex ante assessment of cropping systems including energy crops in Dijon plain (France). A. Laurent, C. Lesur, R. Reau, L. Guichard, M. Soulié, C. Loyce. 5th International Symposium for Farming Systems Design, 7-10 September 2015, Montpellier, France.
  • On-line summaries of the ISA On-farm network: How to make agronomic decisions from on-farm trials? Anabelle Laurent, Fernando Miguez, Peter Kyveryga. Production Agriculture Symposium, February 15th 2018, University of Minnesota, Minneapolis

Date de modification : 05 juillet 2023 | Date de création : 23 mai 2014 | Rédaction : UMR Agronomie