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

Corentin Leroux is one of the #DigitAg labeled PhDs

PhD thesis defence: 27 November 2018, 13h30 – 2 place Pierre Viala, 34000 Montpellier – Amphi 208 (Montpellier SupAgro)

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

  • Start Date: March 2016
  • Defence: 27 November 2018
  • University: MUSE Montpellier University of Excellence / Montpellier SupAgro
  • PhD School:  GAIA, Montpellier (France)
  • Field(s): Precision Agriculture / Agronomy / Geomatics / Informatics
  • Doctoral Thesis Advisor:  Bruno Tisseyre (Montpellier SupAgro)
  • Co-supervisors :  Hazaël Jones (Montpellier SupAgro, ITAP), Anthony Clenet (SMAG)
  • Funding: Cifre Agreement Montpellier SupAgro-SMAG
  • #DigitAg: Labeled PhD – Challenge 1 (ICT and the agroecology challenge), Challenge 5 (ICT and new farm advisory services), Axis 6 (Multiscale modelling and simulation)

Keywords: Filtering, Precision Agriculture, Site-specific nutrient balance, 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 [AT] aspexit.com – See also: After the thesis: Aspexit, a start-up project in R&D for precision agriculture

Networks: ResearchGate –  LinkedIn

Papers /Communications

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

Tisseyre, B., Leroux, C., Pichon, L., Géraudie, V., Sari, T. (2018). How to define the optimal grid size to map high resolution spatial data? Precision Agriculture. https://doi.org/10.1007/s11119-018-9566-5

Pichon L., Leroux C., Macombe C., Taylor J., Tisseyre B. (2019)What relevant information can be identified by experts on unmanned aerial vehicle in precision viticulture Precision Agriculture- https://link.springer.com/article/10.1007/s11119-019-09634-0

Leroux C., Jones H., Pichon L., Taylor J., Tisseyre B.(2019) Automatic harmonization of heterogeneous agronomic and environmental spatial data, Precision Agriculture – https://www.researchgate.net/publication/331913490_Automatic_harmonization_of_heterogeneous_agronomic_and_environmental_spatial_data

Papers at 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., Taylor, J., & Tisseyre, B. (2019).Production gap analysis – an operational approach to yield gap analysis using historical yield datasets, Submitted to the 12th European Conference on Precision Agriculture (ECPA 2019), Montpellier SupAgro, Montpellier, France.

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

Tisseyre, B., & Leroux, C. (2017). How significantly different are your within field zonesPaper 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), 620-624. https://doi.org/10.1017/S2040470017000012
Pichon L., Leroux C., Geraudie V., Taylor J., Tisseyre B. ( 2019) Investigating the harmonization of highly noisy heterogeneous datasets hand collected, Precision Agriculture 2019 – Papers Presented at the 12th European Conference on Precision Agriculture – https://www.wageningenacademic.com/doi/10.3920/978-90-8686-888-9_91