A comparison of bivariate classification and segmentation approaches to delineating and interpreting grain yield-protein management units - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Access content directly
Conference Papers Year : 2013

A comparison of bivariate classification and segmentation approaches to delineating and interpreting grain yield-protein management units

Une comparaison de la classification à deux variables et d'une approche de segmentation pour délimiter et interpréter des zones de gestion du rendement et des protéines du blé

Abstract

A univariate segmentation algorithm has recently been developed for precision agricultural applications. This algorithm is adapted to a bivariate analysis to investigate zoning based on both yield and protein responses in an eastern Australian wheat field. The intention is to provide a zone-by-zone interpretation of the agronomic response to N. The segmentation algorithm provided management zone results comparable with the more widely used k-means classification. The algorithm is still under development but allows expert-knowledge to be incorporated into the zone delineation process.
No file

Dates and versions

hal-02599422 , version 1 (16-05-2020)

Identifiers

Cite

James Taylor, Brigitte Charnomordic, S. Guillaume, B. Tissseyre, B.M. Whelan. A comparison of bivariate classification and segmentation approaches to delineating and interpreting grain yield-protein management units. 9th European Conference on Precision Agriculture, Jul 2013, Lleida, Spain. pp.483-490. ⟨hal-02599422⟩
30 View
0 Download

Share

Gmail Mastodon Facebook X LinkedIn More