[Defended thesis] Corentin Leroux
Accueil
The research
The #DigitAg projects
PhD students
[Defended thesis] Corentin Leroux

[Defended thesis] Corentin Leroux: Pre-processing and zoning within field yield monitor data: towards site specific nutrient balances

Corentin defended his PhD on 27 November2018 @the Institut Agro. After his PhD, he created his own start-up, Aspexit. Find more about Aspexit: https://www.aspexit.com/

Pre-processing and zoning within field yield monitor data: towards site specific nutrient balances

 

My name is Corentin Leroux, and for the past 2 years I've been working on a thesis in the field of digital agriculture. I work for SMAG, a French leader in plot management software for agriculture, and I'm supervised by a research team from UMR ITAP (Irstea-Montpellier SupAgro). I trained as an agricultural engineer at Montpellier SupAgro, and in my final year I chose a specialization called AgroTIC, which aims to train agricultural engineers with dual skills in agronomy and computer science applied to agriculture.
In the course of my internships and training, I began to be really attracted to the processing and analysis of agricultural data, and very quickly turned my attention to precision agriculture. And in my thesis, with precision agriculture, I'm working at the heart of this digital and ecological transition in agriculture.

  • Starting date: March 2016
  • University: MUSE Montpellier Université d’Excellence / Institut Agro
  • PhD school:  GAIA, Montpellier
  • Scientific field: Precision agriculture / Agronomy / Geomatics / IT
  • Thesis management: Bruno Tisseyre (Institut Agro, UMR Itap)
  • Thesis supervisors:  Hazaël Jones (Institut Agro, UMR Itap), Anthony Clenet (SMAG)
  • Funding: Cifre SMAG-Institut Agro
  • #DigitAg : Labeled PhD – Challenge 1 (Le challenge agroécologique), Challenge 5 (Les services de conseil agricole) – Axe 6 :  Modélisation et simulation (systèmes de production agricole)

Mots-clés : Precision agriculture, Manure balances, Filtering, Zoning

Abstract: Precision Agriculture makes use of geo-referenced information and communication technologies to improve agrosystems’ management. Yield datasets stemming from mounted sensors on combine harvesters were the first source of information available in Precision Agriculture. Each year, the highly spatially resolute within-field yield maps generated by these sensors help to characterize the spatial variability of the field technical management’s outcome and to make decisions with regard to the monitoring and management of the upcoming crop production. However, these yield data are not widely used by the experts of the agricultural sector because no practical application is proposed to make value of this information. Because of the low expectations coming from the agricultural sector, the yield processing chain has never really been robustified since it was created. Furthermore, yield maps are still not enough presented to the agronomy experts from an operational perspective, i.e. as zones that correspond to reliable and relevant management units, which does not help in making decisions. The thesis will focus on the proposal of methods to define variable rate application maps based on previously filtered yield datasets. The main contribution of this work is to incorporate the available agronomical expertise within the methods. This expertise takes place at two different levels : regarding the method to correct or pre-process the raw yield datasets and concerning the operational constraints related to the application that will be performed (spatial footprint of the machine, machine accuracy levels, etc) that will drive the zoning algorithm. A general methodology will be proposed and dedicated to the generation of within-field nutrient balance maps.

Contact : cleroux@apsexit.com | Voir aussi : Après la thèse : Aspexit, projet de start-up en R&D sur l’agriculture de précision

Social nretworks: ResearchGate –  LinkedIn

Communications & Papers

Read the thesis manuscript: Processing and value-adding to spatial information in Precision Agriculture: Application to within-field yield monitor data . 
> Watch the video 

Publications in international peer-reviewed journals

  • Leroux, C., Jones, H., Clenet, A., & Tisseyre, B. (2017). A new approach for zoning irregularly-spaced, within-field data. Computers and Electronics in Agriculture, 141 (C), 196-206. DOI: https://doi.org/10.1016/j.compag.2017.07.025
  • Leroux, C., Jones, H., Clenet, A., Dreux, B., Becu, M., & Tisseyre, B. (2018). A general method to filter out defective spatial observations from yield mapping datasets. Precision Agriculture. DOI :https://doi.org/10.1007/s11119-017-9555-0
  • Leroux, C., Jones, H., Taylor, J, Clenet, A., & Tisseyre, B. (2018). A zone-based approach for processing and interpreting variability in multitemporal yield data sets. Computers and Electronics in Agriculture, 148, 299-308. https://doi.org/10.1016/j.compag.2018.03.029
  • Leroux, C., Jones, H., Pichon, L., Guillaume, S., Lamour, J., Taylor, J., Naud, O., Crestey, T., Lablée, J-L., & Tisseyre, B. (2018). GeoFIS: An Open Source, Decision-Support Tool for Precision Agriculture data. Agriculture, 8, 6. https://doi.org/10.3390/agriculture8060073
  • Leroux, C., & Tisseyre, B. (2018). How to measure and report within-field variability – A review of common indicators and their sensitivity. Precision Agriculture. https://doi.org/10.1007/s11119-018-9598-x
  • Leroux, C., Jones, H., Clenet, A., & Tisseyre, B. (2018). Knowledge discovery and unsupervised detection of within-field yield defective observations. Computers and Electronics in Agriculture, 156, 645-659. https://doi.org/10.1016/j.compag.2018.12.024
  • Leroux, C., Jones, H., Clenet, A., & Tisseyre, B. (2018). Evaluation and comparison of several yield filtering approaches using simulated datasets. Disponible dans le mémoire de thèse
  • Pichon, L., Leroux, C., & Tisseyre, B. (2018). A systemic approach to identify relevant information provided by UAV in precision viticulture (Accepted – Major Revisions)
  • Roudier, P, Hedley, C., Lobsey, C.R., Viscarra-Rossel, R.A., Leroux, C. (2017). Evaluation of two methods to eliminate the effect of water from soil vis–NIR spectra for predictions of organic carbon. Geoderma, 296 (15), 98-107: https://doi.org/10.1016/j.geoderma.2017.02.014 
  • Taylor, J., Tisseyre, B., & Leroux, C. (2018). A simple index to determine if within-field spatial production variation exhibits potential management effects: Application in vineyards using yield monitor data. Precision Agriculture. https://doi.org/10.1007/s11119-018-9620-3

Publications in international conferences

  • Lamour, J., Leroux, C., Naud, O., & Tisseyre, B. (2019) Disentangling the sources of chlorophyll-content variability in banana fields. Submitted to the 12th European Conference on Precision Agriculture (ECPA 2019), Montpellier SupAgro, Montpellier, France – https://dx.doi.org/10.3920/978-90-8686-888-9_37
  • Leroux, C., Jones, H., Clenet, A., Dreux, B., Becu, M., & Tisseyre, B. (2017b). Simulating yield datasets: an opportunity to improve data filtering algorithms. Paper presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017, Advances in Animal Biosciences, 8(2), 600-605. https://doi.org/10.1017/S2040470017000899
  • Leroux, C., & Jones, H. (2019). An iterative region growing algorithm to generate fuzzy management zones within fields. Submitted to the 12th European Conference on Precision Agriculture (ECPA 2019), Montpellier SupAgro, Montpellier, France – https://hal.inrae.fr/hal-02609780

Modification date: 04 December 2023 | Publication date: 23 August 2022 | By: ZM