title: "Rolled-upness": phenotyping leaf rolling in cereals using computer vision and functional data analysis approaches.
abstract: BACKGROUND
  The flag leaf of a wheat (Triticum aestivum L.) plant rolls up into a cylinder in response to drought conditions and then unrolls when leaf water relations improve. This is a desirable trait for extending leaf area duration and improving grain size particularly under drought. But how do we quantify this phenotype so that different varieties of wheat or different treatments can be compared objectively since this phenotype can easily be confounded with inter-genotypic differences in root-water uptake and/or transpiration at the leaf level if using traditional methods?
  
  
  RESULTS
  We present a new method to objectively test a range of lines/varieties/treatments for their propensity of leaves to roll. We have designed a repeatable protocol and defined an objective measure of leaf curvature called "rolled-upness" which minimises confounding factors in the assessment of leaf rolling in grass species. We induced leaf rolling by immersing leaf strips in an osmoticum of known osmotic pressure. Using micro-photographs of individual leaf cross-sections at equilibrium in the osmoticum, two approaches were used to quantify leaf rolling. The first was to use some properties of the convex hull of the leaf cross-section. The second was to use cubic smoothing splines to approximate the transverse leaf shape mathematically and then use a statistic derived from the splines for comparison. Both approaches resulted in objective measurements that could differentiate clearly between breeding lines and varieties contrasting genetically in their propensity for leaf rolling under water stress. The spline approach distinguished between upward and downward curvature and allowed detailed properties of the rolling to be examined, such as the position on the strip where maximum curvature occurs.
  
  
  CONCLUSIONS
  A method applying smoothing splines to skeletonised images of transverse wheat leaf sections enabled objective measurements of inter-genotypic variation for hydronastic leaf rolling in wheat. Mean-curvature of the leaf cross-section was the measure selected to discriminate between genotypes, as it was straightforward to calculate and easily construed. The method has broad applicability and provides an avenue to genetically dissect the trait in cereals.
authors.affiliation: Research School of Biology, Australian National University, GPO Box 475, Canberra, ACT 2601 Australia ; CSIRO Agriculture, GPO Box 1600, Canberra, ACT 2601 Australia.
authors.forename: X R R
authors.initials: XR
authors.lastname: Sirault
authors.affiliation: CSIRO Agriculture, GPO Box 1600, Canberra, ACT 2601 Australia.
authors.forename: A G
authors.initials: AG
authors.lastname: Condon
authors.affiliation: Fenner School of Environment and Society, Australian National University, Canberra, ACT 0200 Australia.
authors.forename: J T
authors.identifier: 0000-0001-7404-0046
authors.initials: JT
authors.lastname: Wood
authors.affiliation: Research School of Biology, Australian National University, GPO Box 475, Canberra, ACT 2601 Australia.
authors.forename: G D
authors.initials: GD
authors.lastname: Farquhar
authors.affiliation: CSIRO Agriculture, GPO Box 1600, Canberra, ACT 2601 Australia.
authors.forename: G J
authors.initials: GJ
authors.lastname: Rebetzke
keywords: Convex hull; Digital phenotyping; Leaf water potential; Mean curvature; Polyethylene glycol (PEG); Spline analysis