High-throughput phenotyping early plant vigour of winter wheat

Abstract In contrast to high-throughput genotyping which can manage a large number of plants at relatively low cost, phenotyping of many individual genotypes in field trials is still laborious and expensive. Early plant vigour, as an early selection criterion, is a trait that is visually scored due to a lack of suitable phenotyping methods for an accurate detection of this trait in large field trials. A high-throughput phenotyping technique for scoring early plant vigour would enhance the breeding process. This study was conducted to develop a method for scoring phenotypic differences in early plant vigour of 50 winter wheat ( Triticum aestivum L.) cultivars in a 2-years experiment using a vehicle based multispectral active sensor and two commercially available active sensors, GreenSeeker and CropCircle. Pixel analysis of RGB images revealed to be the most feasible and superior method compared to other possible reference methods. A comparison between the two years 2011 and 2012 confirmed that early plant vigour was affected by genotypic differences. A novel spectral plant vigour index (EPVI) was found to accurately reflect the plant vigour at tillering. Different methods were applied to identify optimal combinations of wavelengths to predict early plant vigour, including multivariate modelling and prediction, contour maps for identifying all possible simple ratios and testing of combined indices. The EPVI and the relative amount of green pixels (RAGP) derived from digital images were significantly related with r 2  = 0.98 to each other in both years. A total of 200 plots, 12 m in length, could be measured within 75 min. The EPVI was shown to be an accurate scoring method for the high-throughput screening of large field trials. The rapidity and accuracy of this novel method may contribute to enhanced selection at early growth stages.

[1]  B. Mistele,et al.  Can changes in leaf water potential be assessed spectrally? , 2011, Functional plant biology : FPB.

[2]  J. Zadoks A decimal code for the growth stages of cereals , 1974 .

[3]  Jeffrey W. White,et al.  Field-based phenomics for plant genetics research , 2012 .

[4]  S. J. Lopes,et al.  Wheat seedling emergence estimated from seed analysis , 2011 .

[5]  U. Schmidhalter Sensing soil and plant properties by non-destructive measurements , 2005 .

[6]  B. Mistele,et al.  High‐Throughput Sensing of Aerial Biomass and Above‐Ground Nitrogen Uptake in the Vegetative Stage of Well‐Watered and Drought Stressed Tropical Maize Hybrids , 2011 .

[7]  Raphael A. Viscarra Rossel,et al.  ParLeS: Software for chemometric analysis of spectroscopic data , 2008 .

[8]  Greg J. Rebetzke,et al.  Genotypic increases in coleoptile length improves stand establishment, vigour and grain yield of deep-sown wheat , 2007 .

[9]  J. Steiner,et al.  Single and multiple vigor tests for predicting seedling emergence of wheat , 1989 .

[10]  William R. Raun,et al.  Estimating vegetation coverage in wheat using digital images , 1999 .

[11]  D. Beegle,et al.  Developing Nitrogen Fertilizer Recommendations for Corn Using an Active Sensor , 2008 .

[12]  B. Mistele,et al.  Comparison of active and passive spectral sensors in discriminating biomass parameters and nitrogen status in wheat cultivars , 2011 .

[13]  Fei Li,et al.  [Monitoring winter wheat population dynamics using an active crop sensor]. , 2011, Guang pu xue yu guang pu fen xi = Guang pu.

[14]  C. Jordan Derivation of leaf-area index from quality of light on the forest floor , 1969 .

[15]  J. P. Welsh,et al.  Exploring management strategies for precision farming of cereals assisted by remote sensing. , 2000 .

[16]  P. T. Hick,et al.  Potential of using field spectroscopy during early growth for ranking biomass in cereal breeding trials , 1993 .

[17]  R. Ellis,et al.  Effects of seed ageing on growth and yield of spring wheat at different plant-population densities , 1989 .

[18]  David C. Nielsen,et al.  Evaluating the Crop Water Stress Index and its correlation with latent heat and CO2 fluxes over winter wheat and maize in the North China plain , 2010 .

[19]  A. Huete A soil-adjusted vegetation index (SAVI) , 1988 .

[20]  C. Bredemeier,et al.  Field-scale validation of a tractor based multispectral crop scanner to determine biomass and nitrogen uptake of winter wheat , 2003 .

[21]  Georg Bareth,et al.  Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages , 2010, Precision Agriculture.

[22]  A. Klatt,et al.  The Potential of Using Spectral Reflectance Indices to Estimate Yield in Wheat Grown Under Reduced Irrigation , 2006, Euphytica.

[23]  U. Schmidhalter,et al.  Application and testing of a crop scanning instrument – field experiments with reduced crop width, tall maize plants and monitoring of cereal yield , 2001 .

[24]  R. Richards,et al.  The effect of different height reducing genes on the early growth of wheat. , 2004, Functional plant biology : FPB.

[25]  B. Mistele,et al.  Spectral high-throughput assessments of phenotypic differences in biomass and nitrogen partitioning during grain filling of wheat under high yielding Western European conditions , 2013 .

[26]  J. Campbell Introduction to remote sensing , 1987 .

[27]  B. Mistele,et al.  Estimating the nitrogen nutrition index using spectral canopy reflectance measurements , 2008 .

[28]  Urs Schmidhalter,et al.  Nitrogen status and biomass determination of oilseed rape by laser-induced chlorophyll fluorescence , 2009 .

[29]  V. Q. Souza,et al.  Seeding density in wheat genotypes as a function of tillering potential , 2009 .

[30]  Richard H. Ellis,et al.  Effects of laboratory germination, soil temperature and moisture content on the emergence of spring wheat , 1986, The Journal of Agricultural Science.

[31]  G. Mullins,et al.  Estimating Winter Wheat Tiller Density Using Spectral Reflectance Sensors for Early-Spring, Variable-Rate Nitrogen Applications , 2004 .

[32]  D. T. Booth,et al.  The Accuracy of Ground-Cover Measurements , 2006 .

[33]  F. S. Murungu Effects of seed priming and water potential on seed germination and emergence of wheat (Triticum aestivum L.) varieties in laboratory assays and in the field , 2011 .

[34]  K. Ghassemi-Golezani,et al.  Seed ageing and field performance of maize under water stress , 2011 .

[35]  Gene Stevens,et al.  Predicting Rice Yield Response to Midseason Nitrogen with Plant Area Measurements , 2008 .

[36]  John E. Sawyer,et al.  Using Active Canopy Sensors to Quantify Corn Nitrogen Stress and Nitrogen Application Rate , 2010 .

[37]  John B. Solie,et al.  In‐Season Prediction of Potential Grain Yield in Winter Wheat Using Canopy Reflectance , 2001 .

[38]  I. M. Scotford,et al.  Estimating Tiller Density and Leaf Area Index of Winter Wheat using Spectral Reflectance and Ultrasonic Sensing Techniques , 2004 .

[39]  R. Richards,et al.  Seedling vigour in wheat - sources of variation for genetic and agronomic improvement , 2002 .

[40]  W. Raun,et al.  In-Season Prediction of Corn Grain Yield Potential Using Normalized Difference Vegetation Index , 2006 .

[41]  A. Walter,et al.  REVIEW: PART OF A HIGHLIGHT ON BREEDING STRATEGIES FOR FORAGE AND GRASS IMPROVEMENT Advanced phenotyping offers opportunities for improved breeding of forage and turf species , 2012 .

[42]  M. Shibayama,et al.  Seasonal visible, near-infrared and mid-infrared spectra of rice canopies in relation to LAI and above-ground dry phytomass , 1989 .

[43]  A. Gitelson,et al.  Application of Spectral Remote Sensing for Agronomic Decisions , 2008 .

[44]  M. Tester,et al.  Phenomics--technologies to relieve the phenotyping bottleneck. , 2011, Trends in plant science.

[45]  Bodo Mistele,et al.  Tractor‐Based Quadrilateral Spectral Reflectance Measurements to Detect Biomass and Total Aerial Nitrogen in Winter Wheat , 2010 .

[46]  P. Peltonen-Sainio,et al.  Seed quality effects on seedling emergence, plant stand establishment and grain yield in two-row barley. , 2008 .

[47]  Kenneth A. Sudduth,et al.  Sensor‐Based Nitrogen Applications Out‐Performed Producer‐Chosen Rates for Corn in On‐Farm Demonstrations , 2011 .

[48]  G. Rondeaux,et al.  Optimization of soil-adjusted vegetation indices , 1996 .