).Abbreviations: GNDVI, green normalized diff erence vegetation index; LAI, leaf area index; NDVI, normalized diff erence vegetation index; NIR, near infrared; NWI, normalized water indices; NWI-1, normalized water index 1; NWI-2, normalized water index 2; NWI-3, normalized water index 3; NWI-4, normalized water index 4; PAR, photosynthetically active radiation; RIL, recombinant inbred lines; RNDVI, red normalized diff erence vegetation index; SR, simple ratio; SRI, spectral refl ectance indices; WI, water index. Published in Crop Sci. 47:1426-1440 (2007. doi: 10.2135/cropsci2006.07.0492 © Crop Science Society of America 677 S. Segoe Rd., Madison, WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. Published online July 30, 2007Reproduced from Crop Science. Published by Crop Science Society of America. All copyrights reserved.CROP SCIENCE, VOL. 47, JULY-AUGUST 2007 WWW.CROPS.ORG 1427 or thousands of segregating populations in a breeding program (Royo et al., 2003). Reynolds et al. (1999) indicated that morphological characters such as number of grains per unit area and harvest index can be used in the visual selection of breeding lines, but those traits are diffi cult to measure in a large number of small plots in early generations due to labor intensiveness and time.Yield in a given environment is directly and indirectly infl uenced by morphological, physiological, and environmental factors. Selection of breeding lines for grain yield in advanced nurseries often needs repetition to make a selection decision because commonly used statistical procedures sometimes fail to produce suffi ciently accurate results for identifying superior genotypes (Ball and Konzak, 1993). An analytical breeding strategy is an alternative breeding approach that requires a better understanding of the factors responsible for development, growth, and yield (Richards, 1982). This strategy considers morphophysiological selection criteria that have potential to make empirical selection more effi cient (Reynolds et al., 2001). The limited application of this analytical approach is probably due to the lack of an appropriate understanding of the physiological parameters, their estimation, and their true associations with grain yield (Richards, 1996). Commonly used physiological selection criteria include stomatal conductance, canopy temperature depression, and C 13 isotope discrimination of grains (Reynolds et al., 1999). Spectral properties of the plant came into focus as a potential selection tool for grain yield in more recent years (Aparicio et al., 2002;Royo et al., 2003;Babar et al., 2006).The basic principle governing canopy spectral refl ectance is that specifi c plant traits are associated with the...

S election of advanced breeding materials for grain yield is a labor-intensive procedure and sometimes produces inaccurate results due to the complex genetic behavior of yield (Ball and Konzak, 1993). Grain yield is infl uenced directly and indirectly by a number of factors, such as morphology, physiology, and especially environmental conditions. Grain yield in wheat (Triticum aestivum L.) has low heritability and shows high genotype-environment interaction, and hence, selection becomes more diffi cult in a given environment ( Jackson et al., 1996). Selection for grain yield by measuring yield itself is a classical approach, whereas selection for grain yield by considering indirect traits is an analytical approach (Richards, 1982 Abbreviations: GNDVI, green normalized diff erence vegetation index; NWI, normalized water indices; NWI-1, normalized water index 1; NWI-2, normalized water index 2; NWI-3, normalized water index 3; NWI-4, normalized water index 4; RNDVI, red normalized diff erence vegetation index; SR, simple ratio; SRI, spectral refl ectance indices; WI, water index.

The 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 oneirrigation 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.

The objectives of this study were to assess the potential of using spectral reflectance indices (SRIs) as an indirect selection tool for grain yield in wheat under irrigated conditions. This paper demonstrates the genetic correlation between grain yield and SRIs, heritability and expected response to selection for grain yield and SRIs, correlated response to selection for grain yield estimated from SRIs, and efficiency of indirect selection for grain yield using SRIs in different spring wheat populations. Four field experiments, GHIST (15 CIMMYT globally adapted genotypes), RLs1 (25 random F3-derived families), RLs2 (36 random F3-derived families), and RLs3 (64 random F5-derived families) were conducted under irrigated conditions at the CIMMYT research station in north-west Mexico in 3 different years. Spectral reflectance was measured at 3 growth stages (booting, heading, and grain filling) and 7 SRIs were calculated using average values of spectral reflectance at heading and grain filling. Five previously developed SRIs (PRI, WI, RNDVI, GNDVI, SR), and 2 newly calculated SRIs (NWI-1 and NWI-2) were evaluated in the experiments. In general, the within- and between-year genetic correlations between grain yield and SRIs were significant. Three NIR-based indices (WI, NWI-1, and NWI-2) showed higher genetic correlations (0.73–0.92) with grain yield than the other indices (0.35–0.67), and these observations were consistent in all populations. Broad-sense heritability estimates for all indices were in general moderate to high (0.60–0.80), and higher than grain yield (0.45–0.70). The realised heritability for the 3 NIR-based indices was higher than for the other indices and for grain yield itself. Expected response to selection for all indices was moderate to high (0.54–0.85). The correlated response for grain yield estimated from the 3 NIR-based indices (0.59–0.64) was much higher than the correlated response for grain yield estimated from the other indices (0.31–0.46), and the efficiency of indirect selection for these 3 NIR-based indices was 90–96% of the efficiency of direct selection for grain yield. These results demonstrate the potential for using the 3 NIR-based SRI tools in breeding programs for selecting for increased genetic gains for yield.

. 2009. Association of biomass production and canopy spectral reflectance indices in winter wheat. Can. J. Plant Sci. 89: 485Á496. Increased biomass production could be an important criterion for future grain yield improvement in wheat (Triticum aestivum L.). Quick assessment of genetic variations for biomass production may become a useful tool for wheat breeders. The potential of using canopy spectral reflectance indices (SRI) to assess genetic variation for biomass production in winter wheat was evaluated. Three experiments were conducted for 2 yr (2003Á2004 and 2004Á2005) at Oklahoma State University, Stillwater, OK. The first experiment consisted of 25 winter wheat cultivars, and the other two experiments contained two sets of 25 F 4:6 and F 4:7 recombinant inbred lines from two crosses developed by breeding programs in the great plains of the United States of America. Three groups of SRI (vegetation-based, pigment-based, and water-based) were tested for their ability to assess biomass production at three growth stages (booting, heading, and grainfilling). The water index and the normalized water indices gave stronger genetic correlations (PB0.01) and linear relationship for biomass production compared with the vegetation-based and pigment-based indices. The strong association of water-based indices with biomass was related to the canopy water content of the genotypes. Canopy water content was significantly (PB0.05) correlated with biomass production. A strong positive association (P B0.05) of grain yield and dry biomass was observed at the heading and grainfilling stages. Our study demonstrated the potential of using water-based SRI as a breeding tool to estimate genetic variability and identify genotypes with higher biomass production, and could eventually help to achieve higher grain yield in winter wheat.Key words: Wheat, biomass, grain yield, spectral reflectance index Prasad, B., Babar, M. A., Carver, B. F., Raun, W. R. et Klatt, A. R. 2009. Association entre la production de biomasse et l'indice de re´flectance spectrale chez le ble´d'hiver. Can. J. Plant Sci. 89: 485Á496. Une plus forte production de biomasse pourrait eˆtre un important crite`re dans l'ame´lioration du rendement grainier du ble´(Triticum aestivum L.) a`l'avenir. L'e´valuation rapide des variations de la production de biomasse d'origine ge´ne´tique pourrait devenir un instrument utile pour ceux qui hybrident le ble´. Les auteurs ont tente´de voir si l'indice de re´flectance spectrale (IRS) de la ve´ge´tation pourrait servir a`e´valuer la variation de la production de biomasse d'origine ge´ne´tique chez le ble´d'hiver. À cette fin, ils ont effectue´trois expe´riences en deux ans (2003Á2004 et 2004Á2005) a`l'Universite´d'É tat de l'Oklahoma, a`Stillwater (É .-U.). La premie`re portait sur 25 cultivars de ble´d'hiver et les deux autres, sur deux jeux de 25 ligne´es F 4:6 et F 4:7 autofe´conde´es venant de la recombinaison de deux croisements cre´e´s dans le cadre des programmes de se´lection des Grandes Plaines des É .-U. Trois IRS (fon...