High-Throughput Analysis of Potato Vitality

Book chapter (2022)

Authors

E. Atza Numerical Analysis - EEMCS
N.V. Budko Numerical Analysis - EEMCS
Research Group
Numerical Analysis (EEMCS) (TU Delft)
Copyright: © 2022 E. Atza, N.V. Budko
DOI: https://doi.org/10.1007/978-3-031-11818-0_36
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Published Date

2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Delft Institute of Applied Mathematics

Research Group

Numerical Analysis

Abstract

Vitality is a fundamental trait for the development of a plant. It is known to depend on various factors, such as climate, soil, and the plant’s genetics, but the progressive depletion of soil nutrients make it a priority for the industry to pinpoint which of the controllable qualities of a seed have the biggest impact on vitality. This work describes techniques applied in a high-throughput phenotyping project, the first of this magnitude for a complex plant, the potato (solanum tuberosum). We also present the results of an analysis of associations between the chemical composition of the seed potatoes and field performance, solving the arising underdetermined linear systems by means of PLS regression. We show that some but not all of the chemical data is strongly associated to vitality.

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