Bayesian functional regression as an alternative statistical analysis of high-throughput phenotyping data of modern agriculture.

ABSTRACT:

Background

Modern agriculture uses hyperspectral cameras with hundreds of reflectance data at discrete narrow bands measured in several environments. Recently, Montesinos-López et al. (Plant Methods 13(4):1-23, 2017a. 10.1186/s13007-016-0154-2; Plant Methods 13(62):1-29, 2017b. 10.1186/s13007-017-0212-4) proposed using functional regression analysis (as functional data analyses) to help reduce the dimensionality of the bands and thus decrease the computational cost. The purpose of this paper is to discuss the advantages and disadvantages that functional regression analysis offers when analyzing hyperspectral image data. We provide a brief review of functional regression analysis and examples that illustrate the methodology. We highlight critical elements of model specification: (i)

SUBMITTER: Montesinos-Lopez A 

PROVIDER: S-EPMC5994840 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature