The Potential of Using Spectral Reflectance Indices to Estimate Yield in Wheat Grown Under Reduced Irrigation

SummaryThe objectives of this research were to study the association in bread wheat between spectral reflectance indices (SRIs) and grain yield, estimate their heritability, and correlated response to selection (CR) for grain yield estimated from SRIs under reduced irrigation conditions. Reflectance was measured at three different growth stages (booting, heading and grainfilling) and five SRIs were calculated, namely normalized difference vegetation index (NDVI), simple ratio (SR), water index (WI), normalized water index-1 (NWI-1), and normalized water index-2 (NWI-2). Three field experiments were conducted (each with 30 advanced lines) in three different years. Two reduced irrigation environments were created: (1) one-irrigation level (pre-planting), and (2) two-irrigation level (pre-planting and at booting stage), both representing levels of reduced moisture. Maximum yield levels in the experimental zone were generally obtained with 4–6 irrigations. Genotypic variations for all SRIs were significant. Three NIR (near infrared radiation) based indices (WI, NWI-1, and NWI-2) gave the highest level of association (both phenotypic and genotypic) with grain yield under both reduced irrigation environments. Use of the mean SRI values averaged over growth stages and the progressive integration of SRIs from booting to grainfilling increased the capacity to explain variation among genotypes for yield under these reduced irrigation conditions. A higher level of broad-sense heritability was found with the two-irrigation environment (0.80) than with the one-irrigation environment (0.63). Overall, 50% to 75% of the 12.5% highest yielding genotypes, and 50% to 87% of the 25% highest yielding genotypes were selected when the NWI-2 index was applied as an indirect selection tool. Strong genetic correlations, moderate to high heritability, a correlated response for grain yield close to direct selection for grain yield, and a very high efficiency of selecting superior genotypes indicate the potential of using these three SRIs in breeding programs for selecting increased genetic gains in grain yield under reduced irrigation conditions.

[1]  A. Condon,et al.  Breeding for high water-use efficiency. , 2004, Journal of experimental botany.

[2]  M. Reynolds,et al.  Association between canopy reflectance indices and yield and physiological traits in bread wheat under drought and well-irrigated conditions , 2004 .

[3]  Matthew P. Reynolds,et al.  Application of physiology in wheat breeding , 2001 .

[4]  C. R. Bull,et al.  Wavelength selection for near-infrared reflectance moisture meters , 1991 .

[5]  H. Grüneberg,et al.  Introduction to quantitative genetics , 1960 .

[6]  M. Ginkel,et al.  Progress in breeding wheat for yield and adaptation in global drought affected environments , 2002 .

[7]  T. Payne,et al.  Associations among Twenty Years of International Bread Wheat Yield Evaluation Environments , 2003 .

[8]  R. A. Fischer,et al.  Wheat Yield Progress Associated with Higher Stomatal Conductance and Photosynthetic Rate, and Cooler Canopies , 1998 .

[9]  Moon S. Kim,et al.  Ratio analysis of reflectance spectra (RARS): An algorithm for the remote estimation of the concentrations of chlorophyll A, chlorophyll B, and carotenoids in soybean leaves , 1992 .

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

[11]  M. P. Reynolds,et al.  Evaluating physiological traits to complement empirical selection for wheat in warm environments , 2004, Euphytica.

[12]  Kl Regan,et al.  Use of reflectance measurements to estimate early cereal biomass production on sandplain soils , 1993 .

[13]  José Luis Araus,et al.  Relationship between Growth Traits and Spectral Vegetation Indices in Durum Wheat , 2002 .

[14]  M. Lillemo,et al.  Associations among International CIMMYT Bread Wheat Yield Testing Locations in High Rainfall Areas and Their Implications for Wheat Breeding , 2004 .

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

[16]  B. Ma,et al.  Early prediction of soybean yield from canopy reflectance measurements , 2001 .

[17]  Josep Peñuelas,et al.  Visible and Near‐Infrared Reflectance Assessment of Salinity Effects on Barley , 1997 .

[18]  J. Araus,et al.  Spectral vegetation indices as nondestructive tools for determining durum wheat yield. , 2000 .

[19]  Matthew P. Reynolds,et al.  Physiological and Genetic Changes of Irrigated Wheat in the Post–Green Revolution Period and Approaches for Meeting Projected Global Demand , 1999 .

[20]  C. Wiegand,et al.  Use of spectral vegetation indices to infer leaf area, evapotranspiration and yield. I. Rationale. , 1990 .

[21]  EVALUATING PHYSIOLOGICAL TRAITS TO COMPLEMENT EMPIRICAL SELECTION FOR WHEAT IN WARM ENVIRONMENTS , 1997 .

[22]  K. Siddique,et al.  Morphological and physiological traits associated with wheat yield increases in Mediterranean environments , 1994 .

[23]  William R. Raun,et al.  Spectral Reflectance Indices as a Potential Indirect Selection Criteria for Wheat Yield under Irrigation , 2006 .

[24]  C. Tucker Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[25]  J. L. Araus,et al.  Usefulness of spectral reflectance indices as durum wheat yield predictors under contrasting Mediterranean conditions , 2003 .

[26]  G. Slafer,et al.  Changes in physiological attributes of the dry matter economy of bread wheat (Triticum aestivum) through genetic improvement of grain yield potential at different regions of the world , 1991, Euphytica.

[27]  R. W. Leamer,et al.  Reflectance of Wheat Cultivars as Related to Physiological Growth Stages1 , 1980 .

[28]  P. Sellers Canopy reflectance, photosynthesis and transpiration , 1985 .

[29]  R. Richards,et al.  Defining selection criteria to improve yield under drought , 1996, Plant Growth Regulation.

[30]  J. Peñuelas,et al.  Assessment of photosynthetic radiation‐use efficiency with spectral reflectance , 1995 .

[31]  J. Peñuelas,et al.  The reflectance at the 950–970 nm region as an indicator of plant water status , 1993 .

[32]  R. A. Fischer,et al.  Yield potential progress in short bread wheats in Northwest Mexico , 1997 .

[33]  William R. Raun,et al.  Spectral Reflectance to Estimate Genetic Variation for In-Season Biomass, Leaf Chlorophyll, and Canopy Temperature in Wheat , 2006 .

[34]  C. Tucker,et al.  Satellite remote sensing of primary production , 1986 .

[35]  E. B. Knipling Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation , 1970 .

[36]  J. Hatfield Spectral behavior of wheat yield variety trials , 1981 .

[37]  C. Konzak,et al.  Relationship between Grain Yield and Remotely‐Sensed Data in Wheat Breeding Experiments , 1993 .

[38]  P. Sellers Canopy reflectance, photosynthesis, and transpiration. II. the role of biophysics in the linearity of their interdependence , 1987 .

[39]  F. Baret,et al.  Potentials and limits of vegetation indices for LAI and APAR assessment , 1991 .

[40]  R. Richards,et al.  Broad sense heritability and genotype × environment interaction for carbon isotope discrimination in field-grown wheat , 1992 .