Images carried before the fire: The power, promise, and responsibility of latent phenotyping in plants. Issue 1 (3rd September 2021)

• Record Type: Journal Article
• Authors: Feldmann, Mitchell J.; Gage, Joseph L.; Turner‐Hissong, Sarah D.; Ubbens, Jordan R.
• Is Part Of: Plant phenome journal. Volume 4:Issue 1(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-03
• Subjects: Phenotype -- Periodicals; Plant genetics -- Periodicals; Periodicals; 581.35
• DOI: 10.1002/ppj2.20023
• Languages: English
• ISSNs: 2578-2703

Abstract

Abstract: Understanding the genetic basis of plant traits requires comprehensive and quantitative descriptions of the phenotypic variation that exists within populations. Cameras and other sensors have made high‐throughput phenotyping possible, but image‐based phenotyping procedures involve a step where a researcher selects the traits to be measured. This feature selection step is inherently prone to human biases. Recently, a set of phenotyping approaches, which are referred to collectively as latent phenotyping techniques, have arisen in the literature. Latent phenotyping techniques isolate a latent source of variance in the data, such as stress or genotype, and then quantify the effect of this latent source of variance using latent variables without defining any conventional traits. In this review, we discuss the differences between, and challenges of, both traditional and latent phenotyping. Core Ideas: Latent phenotyping is an emerging field that captures fine scale variation in plants. Latent phenotypes can minimize the effect of human bias when describing plant form from high dimensional data. Predictions and inferences from latent phenotyping are useful for crop improvement and basic biology.