ARS | Publication request: Development of Leaf Spectral Models for Evaluating Large Numbers of Sugarcane Genotypes

Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 3, 2012
Publication Date: June 15, 2012
Citation: Zhao, D., Glynn, N.C., Glaz, B.S., Comstock, J.C., Johnson, R.M. 2012. Development of Leaf Spectral Models for Evaluating Large Numbers of Sugarcane Genotypes. Crop Science. 52:1837-1847.

Interpretive Summary: Nondestructive measurements of leaf hyperspectral reflectance have been used to estimate crop leaf chemical and physiological characters. Sugarcane (Saccharum spp.) leaf nitrogen, carbon and chlorophyll levels are important physiological traits of plant nitrogen status that are essential for high yields and perhaps useful for genotype evaluation. This research proposed to clarify if leaf reflectance measurements could be useful for improving genotype selection in the Canal Point (CP) sugarcane cultivar development program The specific objectives of this study were to: (1) identify sugarcane genotypic variation in leaf hyperspectral (400 – 2500 nm) reflectance, leaf chlorophyll (SPAD readings), nitrogen and carbon contents, stalk juice sucrose content, commercial recoverable sucrose, cane yield, and sucrose yield and (2) determine relationships between leaf reflectance and these chemical and yield traits across a large number of genotypes. In Stage 2 (approximately 1500 genotypes) of the CP sugarcane cultivar development program, we measured reflectance and the chemical traits on three leaves of the top visible dewlap from each of 87 randomly selected genotypes in December 2008 and 208 and 124 randomly selected genotypes in May, July, September, and October in 2009 and 2010, respectively. Yield traits were determined on mature plants in October. Genotypic variation of leaf reflectance mainly occurred from 540-1200 nm. Overall, leaf chlorophyll, nitrogen, carbon, and carbon to nitrogen ratio varied among genotypes and during the growing season. Highly significant calibrations were developed for leaf chemical traits using leaf reflectance values (P<0.0001). Coefficients of variation for juice sucrose, commercial recoverable sucrose, cane yield, and sucrose yield among genotypes were 9.6, 11.1, 26.0, and 28.5%, respectively, averaged across years. Correlations of yield traits with leaf reflectance were poor. Measurement of leaf reflectance is a promising tool for estimating leaf chemical traits, but not for predicting yield traits across a large number of diverse genotypes in early selection stages of a sugarcane cultivar development program.

Technical Abstract: Leaf reflectance has been used to estimate crop leaf chemical and physiological characters. Sugarcane (Saccharum spp.) leaf N, C, and chlorophyll levels are important traits for high yields and perhaps useful for genotype evaluation. The objectives of this study were to identify sugarcane genotypic variation in leaf hyperspectral reflectance, leaf chemical (chlorophyll, N and C), and yield [juice sucrose content, commercial recoverable sucrose (CRS), cane yield (TCH), and sucrose yield (TSH)] traits and to determine relationships between leaf reflectance and these chemical and yield traits. In Stage II of the Canal Point, FL, sugarcane cultivar development program, we measured spectral reflectance and chemical traits on three leaves of the top visible dewlap from each of 87 genotypes in December in 2008 and 208 and 124 genotypes in May, July, September, and October in 2009 and 2010, respectively. Yield traits were determined on mature plants. Genotypic variation of leaf reflectance mainly occurred in 540-1200 nm. Leaf relative chlorophyll, N, C, and C:N ratio varied among genotypes and during the growing season. Highly significant calibrations were developed for leaf chemical traits using leaf reflectance (P<0.0001). Correlations of juice sucrose, CRS, TCH, and TSH with leaf reflectance were poor. Measurement of leaf reflectance is a promising tool for estimating leaf chemical traits, but not for predicting yield traits across a large number of diverse genotypes in early selection stages of a sugarcane breeding program.