Nuclear Agriculture and Biotechnology Division, Mumbai-400085, India.


Identification, validation, and use of molecular markers for combining quality with durable rust resistance in Indian wheat. [p. 33]

B.K. Das and S.G. Bhagwat (Nuclear Agriculture & Biotechnology Division) and A. Saini and N. Jawali (Molecular Biology Division).

Genetic improvement of wheat for quality and rust resistance is continuing. The HMW-glutenin subunits are being used as a criterion for selection. Rust resistance genes such as Sr31 and Sr24/Lr24 are being combined with high yielding ability. Selections made on the basis of good agronomic characters are being advanced.

Marker-assisted selection for pyramiding stem rust resistance genes Sr31 and Sr24 in Indian wheat is being carried out. SCAR markers that identify the Sr31 gene in homozygous or heterozygous condition were developed. DNA markers reported in literature for the Sr24/Lr24 gene (SCS73719) was validated in Indian wheat cultivars and segregating populations. Phenotypic scoring for stem rust reaction and a cosegregation study with the marker was made in an F2 population from the cross 'Kalyansona (-Sr24/Lr24)/Vaishali (+Sr24/Lr24)'. The SCAR marker for the Sr24 gene, along with the SCAR markers for Sr31, are being used for pyramiding these two genes.

Selections for Glu-D1d (coding for HMW-glutenin subunits 5+10), Sr24, and Sr31 are being made from intercultivar crosses by use of molecular markers.


Identification of DNA markers for stem rust resistance gene Sr26. [p. 33]

Ruchi Rai, B.K. Das, and S.G. Bhagwat (Nuclear Agriculture and Biotechnology Division).

The stem rust-resistance gene Sr26 has the potential to provide durable resistance to stem rust if it is pyramided with other Sr gene(s). Two markers, one based on a RAPD marker and the other based on an AP-PCR marker associated with stem rust resistance conferred by Sr26, were identified. Linkage analysis was done by studying cosegregation of the markers with resistant phenotype in a F2 population from a cross between Kalyansona and the Australian cultivar Kite (Sr26).


Thermotolerance in wheat. [p. 33-34]

Suman Sud and S.G. Bhagwat (Nuclear Agriculture and Biotechnology Division).

High temperature stress is a major environmental constraint that lowers wheat productivity in warmer areas. In India, wheat cultivars are developed for different agroclimatic zones and, thus, show wide variability. We explored the cultivated germ plasm to mine genes for thermotolerance for further utilization. Fifty-six Indian bread wheat genotypes were assayed for acquired thermotolerance at the seedling stage. Ten-day-old seedlings were hardened and then subjected to membrane thermostability (MTS) and cell viability (TTC reduction) assays. Six thermotolerant genotypes identified from the assays and one relatively nontolerant genotype were grown in the field till maturity. Flag leaf area was estimated 10 days after emergence, and flag leaf senescence was recorded 17, 24, and 31 days after flag leaf emergence. Daily maximum and minimum air temperatures were recorded throughout the crop season. Variability was detected among the 56 genotypes for acquired thermotolerance. Significant correlation was observed between MTS and TTC values. The TTC assay, which measured cell viability after heat shock treatment, showed significant positive association with grain yield/plant and yield/meter. Variation among the thermotolerant genotypes for yield and yield components was observed. Because the TTC assay showed positive correlation with yield under high temperature stress, it can be used as a selection criterion in breeding for warmer areas. To improve the productivity in warmer areas selection for heat stress tolerance accompanied by superior yield components will be needed. The tolerant genotypes identified in this study can serve as parents in improvement of thermotolerance of wheat.


Agronomic characterization, Rht genotyping, and high-molecular-weight glutenin subunit profiling of oligo-derived lines. [p. 34]

Suman Sud and S.G. Bhagwat (Nuclear Agriculture & Biotechnology Division).

Wheat is cultivated world wide in cooler environments. There is increasing interest in cultivation of wheat in nontraditional areas, including warmer environments. Also, a growing problem concerns the rise and fluctuation in temperature at the time when wheat is cultivated. Higher temperature during early phase of growth affects tillering, number of spikelets/spike, and biomass production. Oligoculm wheat is known to have high vigor and Gigas features. The vigor of oligoculm wheat expressed as long culms, thick stem, large leaves, long spikes with a high number of spikelets, and large grains. A set of 14 oligoculm derivatives obtained from the cross 'oligoculm wheat/Kundan//selection 212' was evaluated for their field performance under high temperature stress conditions. Grain yield/spike were higher in 10 derivatives, whereas on area basis the derivatives were poorer. Biomass/plant and biomass/meter were significantly higher in many of the oligoculm derivatives indicating their superior ability to accumulate biomass. The spikelet number/spike and flag leaf area were significantly higher than the checks, hence the derivatives can be used as a source of these yield components for improvement in warm environment. Harvest index in the derivatives was generally lower. The oligoculm derivatives lacked major dwarfing gene as observed by their responsiveness to gibberellin and by use of perfect markers, as a result these were taller than the semidwarf check cultivars. The oligo derivatives were found to vary in their HMW-glutenin subunit composition. Two derivatives, 8-44-1 and 8-44-2, had the subunit composition N, 7+9, and 2+12 (Glu-1 score 5). Ten derivatives showed subunit composition N, 13+16, 2+12 (Glu-1 score 6). One line each showed subunit composition 1, 7+8, 2+12, and 1, 7+9, 2+12 (Glu-1 scores 8 and 7, respectively). The variability in Glu-1 scores offers scope to select for strong or weak dough. The oligo derivatives lacked tolerance to heat stress as indicated by their rapid leaf senescence. The performance of the derivatives may be improved by introduction of semidwarfing gene(s) and by improving tolerance to high temperature.


Identification of Rht genes and pin a and pin b status of Indian wheat cultivars. [p. 34]

E. Nalini (Molecular Biology Division), S.G. Bhagwat (Nuclear Agriculture & Biotechnology Division), and N. Jawali (Molecular Biology Division).

The semi dwarfing genes Rht1 and Rht2 are common among Indian wheat cultivars. Forty-five cultivars were analyzed using PCR-based, allele-specific perfect markers. Thirteen had Rht-B1b and 24 had Rht-D1a. Grain hardness is an important quality related trait. Sixty bread wheat cultivars were analyzed for their status of pin a and pin b genes. The null form of pin a was found to be most frequent among the hard Indian bread wheats. Mapping of wheat genome using a intervarietal cross between cultivars Kalyansona and Sonalika is in progress.

Artificial neural network for identification of wheat grains. [p. 34-35]

B.P. Dubey (Reactor Control Division), S.G. Bhagwat (Nuclear Agriculture & Biotechnology Division), S.P. Shouche (Computer Division), and J.K. Sainis (Molecular Biology Division).

Observing the shape, size and color of grains is normally employed for identification of a wheat cultivar. Use of computer based image analysis may be a good alternative to visual identification. Grain shape and size are considerably influenced by changes in environment. The Artificial Neural Network (ANN), when combined with digital imaging, may have the potential for cultivar identification. Three bread wheat varieties were grown in different environments to create variation in the grain shape and size. Morphometric features of these grains were quantified using Comprehensive Image Processing Software. Data on 45 parameters were used to train ANN with different combinations of nodes and iterations. Similar samples were used for testing. A commercial and an in-house developed ANN software packages were used in this study. Best results were obtained with the resilient back propagation architecture for both. The success of correct identification was about 88 % for all the grains together and ranged from 84-94 % for individual varieties. The results showed that ANN, combined with image analysis has excellent potential for wheat cultivar identification.


Publications. [p. 35]




Cytogenetics Laboratory, Department of Botany, Coimbatore-641 046, India.


Breeding for rust resistance in some Indian hexaploid wheat cultivars. [p. 35-38]

Specific genes for rust (stem, leaf, and stripe) resistance were transferred from hexaploid wheat stocks into the Indian hexaploid wheat cultivars HW 2084, PDSN-32, and K 9107. Among the three recipient wheat parents, HW 2084 and K 9107 were free from leaf rust and stem rust, respectively, however, both were susceptible to the other two wheat rusts. The third cultivar, PDSN-32, was susceptible to all the three rusts. Thus, we improved these Indian wheat cultivars by incorporating the respective rust-resistance genes for which they are susceptible. The donor parents included 10 hexaploid wheat stocks carrying a total of five leaf rust-resistance genes (Lr19, Lr24, Lr26, Lr28, and Lr37), six stem rust-resistance genes (Sr24, Sr25, Sr27, Sr31, Sr36, and Sr38), and seven stripe rust-resistance genes (Yr8, Yr9, Yr11, Yr13, Yr15, Yr16, and Yr17), present either singly or in combinations (linked condition). Transfers were made using a simple backcross-breeding method followed by selection.

Selection was made in the BC2/BC3 and/or BC5 generations, and one NIL each in the BC2F5/BC3F5 and BC5F5 was selected from all 29 cross combinations. All the lines were screened against individual rust races at the seedling stage in the glasshouse with a mixture of rust races and at the adult-plant stage in natural and artificial conditions in the field. An immune to moderately resistant reaction at the seedling stage and a highly resistant reaction at the adult-plant stage provided by the incorporated genes strongly advocate the use of specific rust-resistance genes for durable resistance.

All the rust resistance genes used provided a moderate to high degree of resistance under field conditions (Table 1). Specific rust resistance from single genes included Lr19, Lr24, Lr28, Lr37, Sr27, Sr38, Yr9, Yr11, Yr13, Yr15, and Yr16. Other rust-resistance genes, Lr26, Sr24, Sr25, Sr31, Yr8, and Yr17, were useful in combination with other resistance genes already present in the genetic background of recurrent parents.

Table 1. Adult plant reactions of Indian wheat cultivars and constituted near-isogenic lines against wheat rusts.

 Indian wheat cultivars / NILs ( BC2F5 / BC3F5 and BC5F5)    Rust reaction
 Stem  Leaf  Stripe
 HW 2084 / Veery'S' (Sr31 + Lr26 + Yr9)  40MS  F  100S
 HW 2084 (Lr19 + Sr25)  F  F  F
 HW 2084 / Joss Chambier (Yr11)  40MS  F  F
 HW 2084 / Longbow (Yr13)  40MS  F  F
 HW 2084 / G 25 (Yr15)  F  F  F
 HW 2084 / Cap - 5BL - 7BL (Yr16)  5R  F  F
 HW 2084 / RL 6081 (Sr38 + Lr37 + Yr17)  TR  F  15MS
 HW 2084 / WRT 238-5 (Sr27)  F  F  40MS
 HW 2084 /Cook*6/C 80-1 (Lr19 + Sr25 + Sr36)  F  F  F
 HW 2084 / Darf*6 / 3 Ag / Kite (Lr24 + Sr24)  F  F  10S
 HW 2084 / CS 2A/2M # 4/2 (Lr28 + Sr34 + Yr8)  40MS  F  10RMR
 PDSN-32 / (Sr7b, Sr9 , Lr14)  60S  70S  90S
 PDSN-32 / Veery'S' (Sr31 + Lr26 + Yr9)  10R  10MS  F
 PDSN-32 / Joss Chambier (Yr11)  70S  50S  F
 PDSN-32 / Longbow (Yr13)  70S  60S  F
 PDSN-32 / G 25 (Yr15)  F  20R  F
 PDSN-32 / Cap-5BL-7BL (Yr16)  20S  F  F
 PDSN-32 / RL 6081 (Sr38 + Lr37 + Yr17)  5RMR  TR  15MS
 PDSN-32 / Cook*6/C 80-1 (Lr19 + Sr25 + Sr36)  F  F  F
 PDSN-32 / Darf*6/3 Ag/Kite (Lr24 + Sr24)  10RMR  F  10S
 PDSN-32 / WRT 238-5 (Sr27)  TR  20RMR  40MS
 PDSN-32 / CS 2A/2M#4/2 (Lr28 + Sr34 + Yr8)  60S  F  5RMR
 K 9107 (Sr2, Sr5, Sr8b, Sr11, Lr13, Yr2)  F  40S  80S
 K 9107 / Veery'S' (Sr31 + Lr26 + Yr9)  F  F  F
 K 9107 / Joss Chambier (Yr11)  F  10MR  F
 K 9107 / Longbow (Yr13)  F  10MR  F
 K 9107 / G 25 (Yr15)  F  5R  F
 K 9107 / Cap-5BL­7BL (Yr16)  F  F  F
 K 9107 / RL 6081 (Sr38 + Lr37 + Yr17)  F  F  F
 K 9107 / Cook*6/C 80-1 (Lr19 + Sr25 + Sr36)  F  F  F
 K 9107 / Darf*6/3 Ag/Kite (Lr24 + Sr24)  F  F  10S
 K 9107 / CS 2A / 2M # 4/2 (Lr28 + Sr34 + Yr8)  F  F  TMR

Yield performance of the NILs was tested under rust-free conditions. Many of the NILs were significantly higher in grain yield than the chemically treated control plants. In general, the agronomic performance of the plants at the BC2F5/BC3F5 was superior to those of BC5F5-selected plants for plant height, tiller number/plant, spike length, number of spikelets/spike, 1,000-kernel weight, and grain yield. However, the various agronomic characters recorded in the BC5F5 also were comparatively superior to those of the untreated recurrent parents (Table 2). The NILs of the BC2F5/BC3F5 had very good agronomic characteristics, but the seed quality (plumpness, weight, size, and color) was not improved in many lines. Based on seed quality coupled with good agronomic characters and yield, 20 lines were finally selected for commercial purposes, and the remaining nine lines were grouped as genetic stocks for use in breeding programs.

Table 2. Comparative mean grain yield (Q/ha) performance of Indian hexaploid wheat cultivars (untreated and chemically treated controls) and the constituted NILs in the BC2F5/BC3F5 and BC5F5 generations.

 Control / Constituted lines  Generation  Constituted lines
 HW 2084  PDSN-32  K 9107
 Control (untreated)  ---  32.68  30.92  31.26
 Control (chemically treated)  ---  41.96  39.47  38.62
 Veery'S' (Sr31+Lr26+Yr9)  BC2F5  46.82  43.62  45.78
 BC5F5  45.79  42.80  44.95
 Joss Chambier (Yr11)  BC2F5  41.88  40.16  39.36
 BC5F5  41.81  39.74  39.04
 Longbow (Yr13)  BC2F5  42.16  39.52  40.98
 BC5F5  41.99  38.81  40.12
 G - 25 (Yr15)  BC3F5  40.26  35.34  38.87
 BC5F5  38.12  34.59  38.72
 Cap-5BL-7BL (Yr16)  BC2F5  43.14  40.75  41.45
 BC5F5  42.78  40.46  41.08
 RL-6081 (Sr38+Lr37+Yr17)  BC3F5  44.66  41.45  42.93
 BC5F5  43.47  40.87  41.68
 Cook*6/C 80-1 (Lr19+Sr25+Sr36)  BC2F5  46.45  43.12  45.16
 BC5F5  45.63  42.56  44.08
 Darf *6 / 3Ag / Kite (Lr24+Sr24)  BC2F5  39.95  37.34  38.95
 BC5F5   35.82  36.18  38.68
 CS 2A/2M# 4/2 (Lr28+Sr34+Yr8)  BC2F5  40.38  39.26  40.24
 BC5F5  36.45  38.42  39.87
 WRT 238-5 (Sr27)  BC2F5  42.74  39.84  ---
 BC5F5  41.69  39.49  ---
     SEM  CD (0.05%)  
 Population    0.342 **  0.243 **  0.276 **
 Treatment    0.573**  0.438 **  0.524 **
 P x T interaction    0.768 NS  0.597 NS   0.746 NS

Confirming the transfer of rust-resistance genes to Indian wheat cultivars. Transfer of rust-resistance genes into Indian wheats was confirmed through morphological, genetical, biochemical, and molecular markers. The presence of morphological markers of the donor parents, such as awnless spike (Darf*6/3Ag/Kite, Sr24+Lr24; Joss Chambier, Yr11; Longbow, Yr13; and Cap-5BL-7BL, Yr16), lax spike (RL 6081, Sr38+Lr37+Yr17), reduced yellow pigment in the seed flour (Cook*6/C 80-1, Lr19+Sr25+Sr36), clubby tip (G-25, Yr15), waxy color (Veery'S', Sr31+Lr26+Yr9), and powdery mildew severity in the F1 hybrid derivatives of different crosses between Indian wheats and donor parents suggests the successful transfer of these morphological characters along with rust-resistance genes from the donor parents to recipient Indian wheats.

Inheritance studies in the NILs for Yr9; Lr24 (HW 2084); Yr11, Yr13 (PDSN-32); and Lr19, Sr27 (K 9107); which involved crossing each of the NILs with the universally susceptible wheat cultivar Agra Local, showed that rust resistance in the NILs was due to a single, dominant gene. The F1 hybrids exhibited complete rust resistance, whereas the F2 plants segregated as 3 resistant : 1 susceptible to the respective rusts. Similarly, the BC1 hybrids segregated 1 resistant : 1 susceptible to respective rusts. These results confirm the transfer of rust-resistance genes into Indian wheats.

The F2 segregation data of the monosomic and disomic F1 hybrids of crosses between the complete set of CS monosomics and the NILs for Sr27 (HW 2084), Lr24 (PDSN-32), and Lr19 (K 9107) were studied for their respective rust resistance. A segregation ration of 3:1 (resistant:susceptible) except for lines 3A, 3D, and 7D in HW 2084, PDSN-32, and K 9107, respectively, confirmed the successful incorporation of these genes on to the respective chromosomes of the recipient wheat parents.

We studied changes in enzymatic activities of peroxidase, polyphenol oxidase, catalase, and lipoxygenase in the leaves of 25-day-old plants of rust-susceptible wheat parents and rust-resistant NILs inoculated with respective rust pathogens and found altered activity. The constituted lines had a higher peroxidase activity compared to healthy controls 2-7 days after inoculation. Polyphenol oxidase activity increased in all NILs 3-7 days post inoculation, whereas activity declined in the susceptible parents. Catalase activity was higher in susceptible wheat parents than the resistant NILs. Lipoxygenase activity increased in both the susceptible wheat parents and their NILs 2 days after inoculation but subsequently declined 7 days after inoculation in resistant plants. A consistent increase was noticed in plants of the susceptible parents. Esterase activity increased in all the NILs 3-7 days after inoculation but declined activity was observed in the susceptible parents.

The total lipid content of the leaves increased in both susceptible and rust-resistant NILs 2 days after inoculation but subsequently decreased with an increase in post inoculation time. The percent decrease was greater in the susceptible parents than in the resistant NILs. Soluble protein content increased in resistant NILs 24 hours after inoculation but decreased during later stages of infection. The percent decrease was more in susceptible than resistant lines 7 days after inoculation. Specific activities of ribonuclease-I and combined ribonuclease-II and nuclease-I was high at day15 compared to day 10 in susceptible and resistant lines. Resistant NILs had relatively higher chlorophyll content than that of the susceptible parents. Total free amino acid content increased up 8 days after inoculation in both susceptible and resistant lines followed by a slight reduction in both the cases. Respiration rate increased to a greater extent in the resistant NILs compared to susceptible parents. On the third day after inoculation, the reduction in respiration rate was drastic in the susceptible parents, whereas in resistant NILs, respiration was more or less constant. A significant increase in total free phenols and tannin content was observed in the NILs over their respective recurrent parents. The NILs had significantly higher nuclear DNA than their respective susceptible parents.

A change in the intensity of isoenzyme bands of polyphenol oxidase, peroxidase, esterase, and superoxide dismutase in susceptible and their resistant NILs were noted with Rf values. Isozyme analysis of polyphenol oxidase shows some specific bands only in NILs with different rust-resistance genes. Esterase activity of some specific esterase activity bands was present only in rust-resistant NILs, whereas these specific bands were absent in the susceptible lines. Specific SOD activity bands were observed only in resistant lines and were missing in susceptible lines. SDS-PAGE analysis of soluble protein did not show any major qualitative difference in the protein profiles in the leaves of susceptible parents and its resistant NIL. However, quantitative changes were observed in the intensity of the banding pattern; some of the major protein bands were found to increase in intensity in NILs with rust-resistance genes Yr9, Sr27, Yr17 (HW 2084); Lr19, Sr27, Yr9 (PDSN-32); and Lr19, Lr28, Yr16 (K 9107) over their susceptible (recurrent) parents. The intensity of specific protein bands with Rf values of 0.13, 0.26, 0.29, 0.36, 0.74, 0.78, 0.82, and 0.85 decreased in the leaves of susceptible plants. SDS-PAGE analysis of seed-storage proteins, under reduced conditions for the presence to Sec-1, revealed that all Veery 'S' derivatives, Veery'S', and Kavakaz (aºknown standard for the T1B·1R translocation) showed a Sec-1 band with an Rf value of 0.56, which is a characteristic feature of T1B·1RS lines. This result confirmed the successful incorporation of rye segment carrying the gene complex Sr31+Lr26+Yr9.

Molecular screening of NILs for Yr15 with the RAPD primers OPA-19 and OPB-13 confirmed the transfer of Yr15. The RAPD primers OPA-19 and OPB-13 amplified the diagnostic fragments at 1,420 bp and 1,500 bp and resulted in one additional band in the resistant NIL. This band was absent in susceptible parent.


Distribution of necrosis genes and evaluation of resistance to rusts in some bread wheats. [p. 38-42]

S. Premalatha, V.R.K. Reddy, K. Thamayanthi, and R. Kannan.

Introduction. Hybrid necrosis are frequently met with inter and intraspecific wheat crosses and are serious barriers to the transfer of genes in a planned hybridization program. Hybrid necrosis, causing gradual death or debility of F1 hybrids is often noticed in wheat crosses and this kind of weakness can be clearly distinguished phenotypically. The genetic trait of hybrid necrosis is governed by two complementary genes, Ne1 and Ne2 (Caldwell and Compton 1943; Hermsen 1963), located on chromosomes 2BS and 2BL (Tsunewaki 1960; Nisikawa et al. 1974), respectively. Hybrid necrosis proves to be a hurdle in the process of gene transfers from alien or other diverse sources of resistance to disease. Thus, documenting information on the different genes for resistance to diseases relevant to India as well as the information about the genes in wheat stocks is important. The present study determines the genes for necrosis. Stocks also were e valuated for resistance to rusts in wheats.

Materials and methods. Eighty-two T. aestivum cultivars were crossed to two T. aestivum subsp. aestivum testers, C306 (Ne1ne2) and Klein Lucero (ne1Ne2). The F1 hybrids and parents were raised in field as well as in greenhouse under optimal conditions for the expression of Ne genes. The genotypes of the parents with respect to Ne were determined from the phenotype of the F1 hybrids. The stocks were also evaluated for resistance to rusts under high incidence of natural infection.

Results and discussion. Study of hybrid necrosis. Eighty-two wheat stocks were tested for the presence or absence of necrosis gene(s). The results are presented in Table 3 and indicate that out of 82 cultivars, eight stocks were Ne1 carriers, 35 stocks were Ne2 carriers, and the remaining 39 were noncarriers for the necrosis genes (ne1, ne2). Tsunewaki (1971) tested two strains of T. aestivum subsp. sphaerococcum and reported on of them as Ne1 carrier, whereas Zeven (1971) recorded one strain that had the gene Ne1. Cultivars of T. turgidum subsp. dicoccum, like other tetraploid species of wheat, are either Ne1 carriers or noncarriers (Nishikawa 1967; Tsunewaki 1969). The Ne2 gene, found restricted to the western 6X wheats, is presumed to have originated by mutation at the hexaploid level in Europe (Tsunewaki and Kihara 1962). Zeven (1966) and Tsunewaki and Nakai (1973) reported high frequencies of Ne1 and Ne2 carriers in the hexaploid wheats of Asian and Western populations, respectively.

Similarly, eight Ne1 carriers, 35 Ne2 carriers, and 39 noncarriers of the necrosis genes were found among the 82 stocks of T. aestivum subsp. aestivum. Pukhal'skii (1980) found that Ne2 occurred especially in winter wheat and Ne1 in spring wheat, but Zeven (1981) suggested that spring and winter wheats were possibly derived from two different groups, one carrying the necrosis gene Ne1 and the other Ne2. Narula et al. (1971) and Kochumadhavan et al. (1980) have reported that the Indian bread wheat cultivars predominantly have Ne1, whereas the western European and North American wheats are mainly Ne2 carriers. Tsunewaki (1971) studied 22 accessions of compactum wheats from the U.S. and reported 5 % Ne1 carriers, 18 % Ne2 carriers, and 77 % noncarriers, whereas 34 strains of T. aestivum subsp. compactum from Asia were either Ne1 carriers (32 %) or noncarriers (68 %). Similarly, (9.76 %) Ne1 carriers, (42.68 %) Ne2 carriers, and (47.56 %) noncarriers were found among the 82 stocks of T. aestivum subsp. aestivum.

Disease resistance. This study reveals that the alien genes Lr9, Lr28, Lr32, and Lr37 and Lr19, Lr24, Sr24, Sr25, Sr26, Sr27, Lr25, and Sr31 condition a high degree of resistance. The gene Lr37 showed a high degree of resistance at the adult-plant stage, and this resistance gene, linked with Sr38 and Yr17, provides a high degree of resistance. The genes Lr21 and Sr33 conferred moderate resistance. Sr30 and Sr37 showed moderate resistance to stem rust. Sr36 and SrAgi conferred high degree of resistance to stem rust. The gene Yr9 is associated with Lr26 and Sr31, Yr9 has resistance to stripe rust, and Lr26 was found to be susceptible to leaf rust. Genes Lr19, Lr24, Lr25, and Lr28 confer effective seedling resistance to different pathotypes of leaf rust (Sawhney and Goel 1983) and also APR. Gene Lr24 is known to be linked with Sr24 (McIntosh et al. 1977), and this linkage confers a high level of resistance to both leaf and stem rusts in India. Gene Lr25 is effective against 10 important pathotypes of leaf rust in seedling stage (Sawhney and Goel 1983). The gene Lr37 showed a high degree of resistance in adult-plant stage, and this resistance gene is linked with Sr38 and Yr17, both providing high degree of resistance (Bariana and McIntosh 1993). The gene Lr21 from Ae. tauschii confers a moderate degree of resistance to leaf rust at adult-plant stage. This gene was reported to be susceptible to most of the virulent pathotypes of leaf rust in seedling (Rajendra Kumar et al. 1988) but exhibited adult-plant resistance. The gene SrAgi is the only stem rust-resistance gene present in the partial amphidiploid TAF 46 (2n = 56) generated by Cauderon et al. (1973). SrAgi is highly effective against stem rust. Gene Sr36 derived from T. timopheevii subsp. timopheevii and SrAgi conferred high degree of resistance, whereas Sr30 from common wheat and Sr37 derived from alien gene of T. timopheevii subsp. timopheevii was moderately resistant to stem rust. The genes Sr26, Sr27, Sr31, Sr36, and SrAgi confer a high degree of resistance to stem rust, and Sr25, Sr30, Sr37, and Sr38 confer a moderate degree of resistance. Gene Sr24 is completely ineffective to stem rust. Sr26, Sr27, and Sr31 confer seedling resistance to 19 pathotypes occurring in India and effective in adult-plant stage as well (Sawhney and Goel 1981). Genes Sr26, Sr27, Sr31, Sr32, Sr36, and SrAgi confer a high degree of resistance, whereas Sr25, Sr30, Sr33, Sr37, and Sr30 are moderately resistance. The genes Sr24, Sr20, and Sr34 were reported to be ineffective (Menon and Tomar 2001).



Publications. [p. 42]




Department of Agricultural Botany, Meerut - 250 004, India.


P.K. Gupta, H.S. Balyan, R. Bandopadhyay, J. Kumar, A. Mohan, N. Kumar, P.L. Kulwal, S. Rustgi, R. Singh, A. Goyal, A. Kumar, N. Girdharwal, V. Kumar, and R. Rouf Mir.

Development and use of molecular markers for wheat genomics and breeding. [p. 43-46]

Updating and construction of framework linkage map(s) using trait specific intervarietal RIL populations. Three framework linkage maps using three mapping populations are being prepared in our laboratory for QTL interval mapping of various agronomically important traits. These three mapping populations were originally prepared for the following three traits: (i) grain protein content (GPC), (ii) grain weight (GW), and (iii) preharvest sprouting tolerance (PHST).

Updating the framework linkage map of GPC population. We have prepared a framework linkage map for GPC population using 171 SSR markers (Prasad et al. 2003). The map spanned a genetic distance of 3,272.4 cM and had large gaps in certain regions, which adversely affected the precision of QTL mapping studies. In view of this, following two exercises were undertaken.

(a) The genotypic data used was on a set of 39 markers (including ISSR, SSR, and RAPD markers) recorded at NCL, Pune (India) under a network project, which allowed integration of 18 new markers to the available genetic map, giving a total of 189 markers on the map that is available with us at present.
(b) An additional set of 75 SSRs was used to study polymorphism between parents of GPC population (WL711 and PH132). Twenty-nine of the above 75 SSRs showed polymorphism. Genotyping of RILs with these 29 polymorphic markers is in progress, and the data generated will be used for filling the gaps in the available genetic map. Additional markers will be subsequently used to increase further the density of markers on the map.

Framework maps for GW population. A framework linkage map for four different chromosomes (1A, 2A, 2B, and 7A) was initially prepared using genotyping data for 453 molecular markers (34 SSR, 299 AFLP, and 120 SAMPL) on 100 RILs of GW population. Only 68 of the above 453 markers could be assigned to the above four chromosomes, and an average genetic distance of 13.37 cM to 19.74 cM between any two markers was observed (Kumar et al. 2006).

With a view of developing the whole-genome framework linkage map of GW population, an additional set of 259 SSRs was screened for polymorphism between the parents of GW (Rye Selection 111 and Chinese Spring) population. One hundred thirty (50.19 %) of the above 259 SSRs were found polymorphic. Genotyping of 100 RILs with a total of 53 of 130 polymorphic SSRs has already been completed and for the remaining 80 SSRs is in progress. As soon as the genotyping is complete, a framework map will be prepared and used for QTL interval mapping.

Framework maps for PHST population. A framework linkage map for a solitary chromosome (3A) was earlier prepared for PHST population, using genotyping data for 124 molecular markers (11 SSR, 76 AFLP and 37 SAMPL) on 100 RILs of the above population. Only 13 of the above 124 marker could be assigned to 3A, and an average genetic distance of 21.47 cM between any two markers was observed (Kulwal et al. 2005). A map of 3A was prepared for QTL interval mapping, since 3A was known to carry genes for PHST.

To develop the whole-genome framework linkage map of PHST population, additional 362 (149 gwm and 213 wmc) SSRs were screened for polymorphism between the parents of the PHST mapping population (HD2329 and SPR8198). One hundred thirty-four (37.02 %) SSRs of the above 362 SSRs were found to be polymorphic. Genotyping of 100 RILs with a total of 56 polymorphic SSRs has been completed and genotyping with the remaining 78 SSRs is underway. The genotypic data will be used for construction of a framework map for QTL interval mapping.

Single locus QTL analyses for growth and yield traits (using grain weight mapping population). QTL analysis for agronomically important traits in bread wheat was conducted following SMA, SIM, and CIM using an intervarietal RIL population derived from a cross between Rye Selection 111 (high GW) and CS (low GW). The parents and the above RILs were grown in six different environments, and the data on different agronomic traits were recorded in each case. For conducting single-marker regression analysis, genotypic data of 419 markers (299 AFLP and 120 SAMPL) were used with phenotypic data for different agronomic traits recorded in each of the six different environments, and also with the data pooled over different environments (total seven environments). QTL interval mapping also was conducted using framework linkage maps prepared for chromosomes 1A, 2A, 2B, and 7A (see above for map details).

Single-marker analysis (SMA) for growth and yield traits. Using the intervarietal RIL population for GW, single-marker analysis was conducted for four growth related traits (days to heading (DH), days to maturity (DM), early growth habit (EGH), and plant height (PH)) and seven yield and yield-contributing traits (tillers/plant (TPP), biological yield (BY), grain yield (GY), harvest index (HI), spike length (SL), spikelets/spike (SPS), and grains/spike (GPS)). For three growth traits, 28 markers showed significant association (4 with DM, 7 with DH, and 17 with PH). Similarly, for yield traits, 38 markers showed significant association with five of the seven yield and yield-contributing traits (2 with BY, 3 with SL, 10 each with GY and TPP, and 13 with GPS), in at least four of the above seven environments. The PV explained by the associated markers for individual growth related traits ranged from 3.86­16.81%, and for yield and yield-contributing traits, it ranged from 3.90­14.53 %.

QTL interval mapping for growth related traits. A total of 64 QTL were detected following SIM and CIM, which included 24 QTL for four growth related traits (DH, DM, EGH, and PH) and 40 QTL for seven yield contributing traits (TPP, BY, GY, HI, SL, SPS, and GPS). All these QTL were detected above a threshold LOD of 2.00-4.50 following both SIM and CIM. The PV explained by an individual QTL ranged from 7.42­32.16%.

Two-locus QTL analysis for yield and yield-contributing traits.
Population for grain protein content (GPC). Two-locus QTL analysis was conducted (QTLNetwork V2.0) for seven different yield and yield contributing traits (TPP, BY, GY, HI, SL, SPS, and GPS) using phenotypic data of 100 RILs (GPC population) recorded at six different environments. As many as 35 QTL (including, main effect QTL (M-QTL) and interacting QTL (QE, QQ, and QQE)) were detected for five (TPP, BY, GY, HI, and SL) of the above seven yield and yield-contributing traits, with minimum and maximum number of QTL detected for TPP/HI and SL, respectively. Out of the above 35 QTL, 10 M-QTL were distributed on nine different chromosomes (1A, 1D, 2B, 4A, 5A, 6A, 6B, 7A, and 7B); four M-QTL were involved in 'Q x E' interactions. The remaining 25 QTL were E-QTL, which were either involved in digenic interactions (Q x Q) or digenic environmental interactions (Q x Q x E).

International Triticeae Mapping Initiative population (ITMIpop). ITMI population was also used for two-locus QTL analysis (QTLNetwork V2.0) using data for the above seven yield and yield-contributing traits, recorded at four different environments. As many as 41 QTL (including M-QTL and interacting QTL (QE, QQ, and QQE)) were detected for all the seven yield and yield-contributing traits, with a minimum number of QTL (one) detected for BY/HI and maximum number of QTL (four) detected for GY. Out of the above 41 QTL, 16 QTL were M-QTL distributed on seven different chromosomes (1A, 2A, 2D, 4A, 4B, 5A, and 6D); eight M-QTL were involved in 'Q x E' interactions. Twenty-eight of the above 41 QTL (including both M-QTL and E-QTL) were either involved in digenic interactions (Q x Q) or digenic environmental interactions (Q x Q x E).

High resolution mapping of the genomic regions containing important QTL for GPC and PHST.
QTL for high GPC (QGpc.ccsu-2D.1) on 2DL. A population of about 2,000 F2 plants was derived from a cross between the two extreme RILs for high GPC versus low GPC. By analyzing the above population with markers flanking the QTL (QGpc.ccsu-2D.1) of interest 40 F2/F3 homozygous recombinants were identified.

In order to develop more markers to enrich the interval (11.4 cM) carrying QGpc.ccsu-2D.1, 64 AFLP primer combinations (8 Eco RI x 8 Mse I) were used, to identify chromosome arm (2DL)-specific AFLP markers (using nullisomic tetrasomic and ditelosomic lines of 2D), which could detect polymorphism among extreme RILs, representing parents of the above mapping population. Only seven AFLP markers specific to 2DL detected polymorphism among the parental genotypes and will be used for genotyping of the above 40 F2/F3 plants. An additional set of 960 AFLP primer combinations (unmapped) and 17 SSR primers (known to be mapped in the region of interest) are being used to identify an additional set of 2DL specific polymorphic markers. All these markers, identified as above, will be used for high resolution mapping of the region carrying the QTL of interest.

QTL for PHST (QPhs.ccsu-3A.1) on 3AL. A population of about 1,600 F2 plants was derived from a cross between SPR8198 (PHS tolerant) and HD2329 (PHS susceptible), with the objective of enriching the region carrying the QTL of interest (QPhs.ccsu-3A.1). The above population is being screened for the presence of recombinants using flanking markers of the region carrying QPhs.ccsu-3A.1. The recombinants identified as above will be genotyped using chromosome arm specific markers showing polymorphism between the genotypes representing parents of the above population. For this purpose, a set of 144 markers (19 SSRs and 125 STS) was developed using a chromosome arm (3AL)-specific genomic DNA library of bread wheat (see Gupta et al. 2005 for details). In addition to the above markers, a set of 1024 AFLP primer (16 Eco RI x 64 Mse I) combinations will be utilized to identify chromosome arm specific polymorphic markers.

Physical mapping of SSRs on 21 chromosomes of bread wheat. In bread wheat, a total of 485 SSRs including 325 gSSRs and 160 EST-SSRs were tried with 192 deletion lines, leading to successful mapping of 228 loci including 161 gSSR loci and 67 EST-SSR loci covering all the 21 chromosomes. A maximum number of 92 (40 %) loci were assigned to B genome followed by 68 (30 %) loci to A-genome and 68 (30 %) loci to D-genome. Except for eight discrepancies, a high degree of collinearity of gSSRs was observed between the physical and genetic maps. As many as 75 loci (including 32 gSSR and 43 EST-SSRs) were never used earlier for genetic mapping.

Marker-assisted selection for high GPC. In order to transfer a segment carrying a QTL for high GPC, 10 Indian cultivars were crossed with Yecora Rojo (seeds of Yecora Rojo was procured from J. Dubcovsky), a high grain protein content genotype. The F1 plants were backcrossed with their corresponding recurrent parents to obtain BC1 seeds during Rabi, 2004-05. The above BC1 seed were used to raise BC1F1 population in phytotron (IARI, New Delhi) during summer of 2005. Genomic DNA was extracted from the above BC1F1 plants to perform three-step selection (see below) using molecular markers, which will give plants carrying desirable allele for high GPC along with a genomic background similar to their respective recurrent parents. Different steps involved in the selection process are as follows:

Step-one selection. Selection of BC1F1 plants was exercised using molecular markers (SSR (gwm193) and an allele specific amplification (ASA) marker) flanking the QTL of interest. Eleven BC1F1 plants showed the presence of the desirable alleles at both the marker loci that flank the QTL of interest.
Step-two selection. Background selection on the above, 11 BC1F1 plants was exercised using 20 SSR markers specific to chromosome 6B, carrying the QTL of interest. All 11 BC1F1 plants showed the presence of recipient parent alleles at 5 to 14 marker loci.
Step-three selection. All of the above 11 BC1F1 plants were subjected to the whole-genome background selection using 80 SSR markers, scattered throughout the genome. This selection identified seven of the above 11 BC1F1 plants that better represent the genomes of their recurrent parents. These plants were backcrossed with their recurrent parents and the backcross hybrid seeds were used for raising BC2F1 population in 2005­06.

Development and use of EST-SNPs in bread wheat. Under the aegis of the international Wheat SNP Consortium (WSC), we undertook discovery, validation, and genotyping of SNPs in a set of 48 wheat EST contigs (each having 20-89 EST from 2 to 11 different genotypes), assigned to our group. Contigs were classified into subcontigs belonging to three individual subgenomes (A, B, and D) of the hexaploid wheat, to avoid confusion between homoeologous sequence variants (HSVs) among related genomes and SNPs. As many as 230 putative SNPs were detected in 155 such subcontigs (representing homoeoloci) belonging to 42 EST contigs. STS primers were designed for the above 42 EST-contigs and were used to amplify genomic DNA from 30 elite wheat genotypes. Only 10 of the above 42 primers were used for resequencing and allowed validation of seven SNPs (1 SNP/520 bp) out of 30 putative SNPs detected in silico in the amplifiable region (amplicon) of the above 10 primers in corresponding EST contigs. Allele-specific primers also were designed for the seven validated SNPs and were used for genotyping of 50 elite wheat genotypes (including 30 genotypes used for validation of SNPs) to study the occurrence of these SNPs. Of the above seven validated SNPs, four belonged to a solitary locus (PKS37), thus allowing discrimination of haplotypes at this locus. Altogether, the results suggested that EST-SNPs constitute an important source of molecular markers and could be developed and used in large number for studies on wheat genomics.

Identification of natural variants of the Agp-L gene through EcoTILLING. In order to identify variants of genes involved in starch biosynthesis and to develop functional markers (FMs) for early identification of desirable genotypes through MAS, we initiated an EcoTILLING program in bread wheat, involving large subunit of ADP-glucose pyrophosphorylase (Agp-L), a key enzyme in starch biosynthesis pathway. For this purpose, genome specific primers developed for B and D sub-genomes of bread wheat (Blake et al. 2004) are being used on a set of 52 elite wheat genotypes available with us.

Use of C0t fractionation (CF) and methyl filtration (MF) for genomics research in bread wheat. Gene-enrichment strategies of methyl-filtration and reassociation kinetics were used to generate and analyze 2,000 hypomethylated (MF), 1,026 high C0t (HC), and 1,253 reassociated DNA (RD) sequences of bread wheat, which together constituted 1.61 Mb of genomic sequences. Comparison of each of the above fractions with each of the other two fractions revealed large compositional/structural variations among the three groups of sequences. About 30 % of sequences from MF and 17 % of sequences from HC still represented repeat elements. SSRs also were detected in all the above three (MF, HC, and RD) fractions. A density of 1SSR/3.11 kb in MF was comparable to known SSR density in wheat genomic sequences. A density of 1SSR/2.27 kb in HC was comparable to that of SSRs in ESTs and a density of 1SSR/2.45 kb in RD was intermediate. In MF and RD sequences, the frequency of noncoding (nc) RNA genes was higher than that of protein coding genes but in HC sequences, the frequency of protein coding genes was relatively higher. Altogether, the frequencies of protein-coding genes relative to ncRNA genes varied from high to low in the following order HCÆRDÆMF, and those for ncRNA genes relative to protein coding genes varied in the following order RDÆMFÆHC. When matching was done with ESTs, large proportion of matching ESTs in the databases was found to represent transcripts encoded by transposable elements (TEs) and rRNA sequences; this was true with each of the three groups of sequences analyzed. Putative functions were also assigned to genes predicted from MF, HC and RD fractions. Genes encoding proteins conferring resistance against biotic stresses (mostly represented by gene families) were more frequent in MF sequences, and the genes encoding proteins involved in different metabolic pathways (perhaps housekeeping genes) were more frequent in HC sequences. However, the genes predicted in RD sequences largely matched proteins encoded by TEs. Matching with physically mapped wheat ESTs, allowed assignment of 58 MF sequences to 238 loci on 21 bread wheat chromosomes, of which 145 (60.9 %) loci reside in the distal halves of chromosomes. Also, while looking for synteny with rice sequences, synteny of 140 MF sequences was detected with rice genome sequences spread over all the 12 rice pseudochromosomes, with maximum number of loci on chromosome 3 and minimum number of loci on chromosome 12. A small proportion of MF and HC sequences also showed similarity with maize MF and HC sequences, suggesting that these sequences were conserved during evolution of cereals. Altogether, the above study suggests that the two gene-enriched fractions of wheat genome (MF, HC) differ significantly from each other and also differ from wheat ESTs, so that MF and HC sequences (along with wheat ESTs and RD sequences) should be used together to study the composition of wheat genome.



Publications. [p. 46-47]



Department of Plant Pathology, Hisar-125004, India.


The effect of sowing date on the interaction of loose smut and ear cockle in Indian wheat cultivars. [p. 47-48]

Rajender Singh, M.S. Beniwal, and S.S. Karwasra.

Summary. All cultivars except WH896 and Raj 1555 were susceptible to loose smut having 17.71 to 43.33 % disease incidence. With delayed sowing, all cultivars had reduced disease incidence. Conversely, ear cockle incidence was drastically increased in HD2285 and Raj1555 from 28.35 to 48.88 % and 3.83 to 10.35 %, respectively.

Introduction. The simultaneous occurrence of Ustilago segetum var. tritici with Anguina tritici in wheat has been reported by various workers (Bedi et al. 1959; Pruthi and Gupta 1986). During the croping season of wheat, this type of association between Anguina tritici and Ustilago segetum var tritici has been observed in plant pathology research area. Such type of concomitant association of the fungus and nematode has different level of incidence on different wheat varieties cultivated in India and which among two predominant in different cultivars. Therefore, an attempt has been made to study the effect of concomitant occurrence of loose smut and ear cockle on different varieties at different sowing date.

Materials and methods. A field experiment was conducted at Plant Pathology research area of CCSHAU-Hisar during 1997-2000 crop season. In each plot, 25 cultivars inoculated with loose smut spores in previous crop season were sown in 6 rows 2-m long. Each row received 10 nematode gall. Sowing dates of 25 November, 15 December, and 30 December were used for all treatments. Each cultivar has a subplot separated by 1 m distance by another one. Disease incidence was noticed on tiller basis in each cultivars. Tillers having both diseases were counted separately for both diseases.

Results and discussion. We noticed that two-thirds of the spikes constituting the lower part had almost been totally transformed into black sori of the loose smut fungus. The upper portion of this spike was infected by ear cockle nematode and black gall, which were clearly visible from distended glumes. All cultivars except WH896 and Raj 1555 were susceptible to loose smut with 17.71-43.33 % disease incidence. With a delay in sowing, all susceptible cultivars showed drastic reduction in disease expression (Table 1). In the highly susceptible cultivar Sonalika, disease incidence was decreased from 43.33 to23.66%. A reduction in chlamydospore germination/mycelial inactivation along with fall in temperature may have caused this. Conversely, ear cockle incidence was drastically enhanced in HD2285 (from 28.35 to 48.88 %) and Raj 1555 (3.83 to 10.35 %). Sonalika and HD2285 had the maximum amount of disease. A. tritici had more time for infection and prolonged germination time of seed along with fall in temperature. Pruthi and Gupta (1986) reported that the presence of a fungus with a nematode has an adverse effect on the number, motility, and development of larvae at the normal sowing time.

Table 1. The effect of three sowing dates on the interaction of loose smut and ear cockle of wheat cultivars.

 Cultivar     Percent disease incidence
  25 November   15 December  30 December
 Loose smut  Ear cockle  Loose smut  Ear cockle  Loose smut  Ear cockle
 C306  37.27  17.47  33.95  28.66  27.69  33.07
 Sonalika  43.52  17.05  38.46  23.84  30.83  39.16
 WH 147  39.75  18.64  31.43  25.88  28.44  31.11
 WH 157  35.33  21.33  29.41  28.57  24.28  40.33
 WH 283  38.69  17.39  32.44  24.66  23.71  29.42
 WH 291  36.08  18.11  30.22  24.83  21.33  31.42
 WH 416  35.00  15.00  28.14  20.37  20.77  26.66
 WH 533  31.16  22.93  26.66  29.83  20.66  35.28
 WH 542  32.33  20.96  28.14  27.33  21.33  33.33
 WH 896  0.00  11.38  0.00  16.16  0.00  21.57
 Sonak  31.66  22.77  24.33  30.16  18.83  38.83
 HD 2009  38.75  20.91  29.33  27.71  23.37  34.57
 HD 2285  36.48  24.83  26.83  30.83  19.77  41.33
 HD 2329  30.00  18.33  22.22  24.77  16.66  30.96
 HD 2687  36.66  18.16  29.83  23.83  23.66  28.71
 PBW 175  31.42  18.77  26.83  26.42  21.66  31.88
 PBW 343  39.53  14.83  29.83  22.37  21.77  29.83
 PBW 373  33.33  18.66  26.71  24.16  20.16  30.57
 PBW 435  37.66  20.00  29.33  26.66  23.66  32.22
 Raj 1555  0.00  14.28  0.00  18.22  0.00  23.22
 Raj 3077  36.66  16.66  28.83  24.77  22.22  30.33
 Raj 3765  34.44  18.16  27.66  23.71  21.33  29.33
 Raj 3777  32.33  20.33  25.16  26.66  19.66  32.66
 UP 2338  33.83  19.14  26.57  25.66  20.44  31.33
 UP 2425  36.66  18.44  28.33  24.33  22.22  29.66
 C.D. (0.5 %)  2.54  1.95  1.92  2.32  2.62  2.16





Post Box 158, Agrasain Marg, Karnal 132001, India.


Participatory varietal selection for high yield and faster spread of wheat genotypes in Indo-Gangetic plains of India. [p. 48-50]

Ravish Chatrath, Gyanendra Singh, Randhir Singh, B.S. Tyagi, S.K. Singh, Jag Shoran, Divakar Rai, Sarvan Kumar, and Surendra Singh.

Introduction. Wheat is the leading grain crop in India and is cultivated under a wide range of climatic conditions. The most extensive production of wheat is in areas where the winters are cool and the summers are comparatively hot. The total area under wheat production in India is around 26 x 10^6^ ha with total production hovering around 70 x 10^6^ tons for the last decade. The bread wheat crop accounts for 84 % of the area; durum wheat occupies ~14 %. The productivity, duration, resistance, end product use, and suitability of bread wheat for the economically viable cropping systems of the farming community are some of the reasons that make durum wheat a second priority in the major wheat-growing zones of India. We now realize that yield gains in the Indo-Gangetic Plains area need to be further improved to meet the increased demand of wheat. Two feasible options are to improve yield potential of the genotypes and at the same time reduce the yield gaps between achieved and achievable. Researchers are making efforts to bridge yield gaps by advocating and demonstrating new technology, including cultivars, along with matching production technology in the farmers' field. The concept, methodology, results, and future thrusts for making use of a participatory varietal selection (PVS) approach in the Indo-Gangetic Plains of India are discussed below.

The concept of PVS for yield improvement and adoption. Participatory varietal selection involves the selection of a nonsegregating, characterized product from plant breeding programs by farmers. Such material includes released cultivars, those in advanced stages of testing, and advanced nonsegregating lines. In contrast, participatory plant breeding (PPB) involves selecting genotypes from genetically variable, segregating material by the farmers. The difference between PVS and PPB may not appear to be great at first sight. However, PPB requires more resources than PVS, and PVS identifies material that can be adopted more rapidly by the formal seed sector. The majority of farmers in India, particularly in the eastern, far eastern, and warmer regions, are still growing very old cultivars, local types, or land races even four decades after the beginning of the green revolution and, hence, fail to reap the benefits of modern technologies such as new, improved cultivars and resource conservation technologies. The wheat crop area, which is nearly half a million hectares in the far eastern state, is believed to have the potential of producing about 3.5 t/ha under optimum conditions, provided suitable genotypes resistant to leaf blight and with a 100-day maturity time with recommended agronomic practice are available.

PVS in wheat for Indo-Gangetic plains of India. To deal with such issues as dominance of a single cultivar in a region, slow rate of cultivar replacement, or low yield, a farmer participatory research project entitled 'Participatory Research to Increase the Productivity and Sustainability of Wheat Cropping systems in the Eastern sub Continents of South Asia' funded by DFID has been initiated at the Directorate of Wheat Research, Karnal, through the South Asia Regional Office of CIMMYT in Kathmandu, Nepal, with objectives of increasing wheat productivity and sustainability in this region. The DWR Karnal was assigned to work on material development for PVS at the Shillongani and Ranchi centers under this project. The following activities were conducted during 2003-04 by DWR, Karnal, and the salient features of the progress under the period are given.

Design of PVS. PVS attempts to cover a large number of farmers, especially the resource-poor. Farmers who are risk-averse or limited due to small land holding can, therefore, still afford large plots. Being poor, they also may not have the capacity to use purchased inputs. PVS targets the existing environment to identify suitable cultivars, which means that the field designs have to be simple and adaptable. The project document specifies three approaches for PVS for farmer-managed participatory research (FAMPAR).

Mother trials. Under the PVS program, researcher-designed and farmer-managed trials having a single replication of mainly farmer-selected cultivars conducted by few farmers representing the target area. In such cases, these selected farmers also serve as replicates for data analysis. These trials also aim to produce quantitative data involving the selected farmers at each site. To evaluate and multiply, a set also was grown at the Research Station of DWR, Karnal. Based on the information generated from these trials, surveys, and opinion polls, ranking for the cultivars and traits of choice were estimated. These data will represent the adaptive research area for fine tuning the breeding program at large.

Baby trials. This set of trials was designed by researchers involved in the program but are managed by the farmers at their sites. These are single-entry trials, in which newly selected and proposed entries are grown alongside the farmer's check cultivar under similar management conditions. The individual farmer may serve as a replicate for analyzing the data from each site. For each site or location, the number of baby trials conducted cover the whole range of prevailing conditions of farmers' field in the target area. At each location, data are collected as perceptions of farmers covering that particular locality, and the results obtained again represent the adaptive area of research for future planning.

PVS as an approach. The PVS approach was thought to be a promising strategy of increasing the rate of adoption for new cultivars among farmers in this area. Under this approach a wide range of recently released, high yielding, short duration, modern cultivars are tested in the farmers' field. The step-wise implementation of the following interlinked activities at various sites improves the productivity of wheat in this area to supplement the ongoing wheat improvement program.

1. Planting promising cultivars in the farmers' field to identify need-based cultivars through PVS.
2. Popularizing the farmer's selected cultivars in the targeted area through demonstration.
3. Educating farmers, extension agencies, and nongovernmental organizations through training, field days, farmers' meals, and roving seminars creates awareness for new technology.
4. Conducting base line and impact assessment surveys to get the feedback on farmer perception and fine tuning the technology to come.

Material and methods. Under this program, we organized 8­9 one-acre sized, PVS demonstrations of improved wheat cultivars to convince and educate farmers about new technological advancements that now are available. Selected experimental sites were Darer, Janeshro (Karnal), Mathana, and Kishangarh (Kurukshtra). Eight mother trials consisting of eight cultivars, PBW 343, HD 2687, WH 711, WH 542, UP 2425, PBW 373, RAJ 3765, and UP2338, were sown in farmers' fields for participatory selection. These cultivars also were sown under different tillage options, such as no-till, raised bed, and conventional tillage. To popularize the cultivars other than PBW 343 in this area, eight 'Farmer Days' were organized in Mathana, Kishangarh, Janeshro, and Darer; four were organized in March 2004, before maturity, and four at maturity, in April 2004.

Results and discussion. The results of PVS experiments at the eight sites in two districts in the state of Haryana were analyzed and are presented in Tables 1 and 2. In addition to recording yield data at each site, the selected farmers were also asked to express their preferences. The economic importance of various parameters was assessed on a three-point continuum, very important (3), somewhat important (2), and not important (1) by the farmers in the Farmers Group Discussion mode. The characteristics-wise economic importance score of all the 18 parameters are given in Table 1.

Table 1. Economic importance score for 18 parameters (N = 100) for evaluating wheat cultivars under PVS.

 Parameter  Score
 Germination 3.00
 Number of effective tillers   2.96
 Days to flowering  1.88
 Days to maturity   1.87
 Plant height   2.72
 Lodging resistance   2.84
 Disease resistancetal profit  2.88
 Insect resistance   2.31
 Threshability  2.02
 Grain color  2.24
 1,000-kernel weight  2.73
 Cooking quality  2.07
 Chapatti quality  2.35
 Spike length  2.51
 Grains / spike  3.00
 Grain type  2.95
 Grain yield  2.96
 Straw yield  2.47

Table 2. Matrix ranking of different wheat cultivars for 18 parameters under PVS (N = 100). Figures in parentheses indicate the total score, where total score = 'mean economic importance score' x 'evaluation score of the same parameter'. The overall score = sum of the scores of all parameters of a cultivar.

 Parameter  HD2687  PBW 343  PBW 373  RAJ 3765  UP 2338  UP2425  WH 542  WH 711
 Germination  2 (7.89)  1 (8.76)  4 (7.53)  6 (6.81)  5 (7.08)  8 (6.24)  7 (6.66)  3 (7.80)
 Effective tillers  2 (7.90)  1 (8.23)  6 (6.81)  7 (6.01)  4 (7.16)  8 (5.65)  6 (6.33)  3 (7.84)
 Days to maturity  1 (4.96)  2 (4.92)  8 (4.81)  4 (4.90)  7 (4.84)  6 (4.86)  5 (4.88)  3 (4.92)
 Plant height  3 (7.21)  1 (7.75)  4 (7.15)  8 (6.47)  5 (6.99)  6 (6.83)  7 (6.52)  2 (7.23)
 Lodging resistance  2 (7.72)  1 (8.09)  5 (6.79)  8 (6.22)  6 (6.53)  4 (6.84)  7 (6.42)  2 (7.61)
 Disease resistance  5 (6.22)  2 (6.83)  4 (6.39)  3 (6.42)  6 (6.22)  7 (6.11)  8 (5.73)  1 (7.03)
 Insect resistance  4 (5.71)  1 (6.24)  5 (5.64)  6 (5.47)  3 (5.80)  7 (5.34)  8 (5.43)  2 (5.86)
 Spike length  1 (6.80)  2 (6.80)  4 (6.25)  7 (5.37)  5 (6.17)  6 (6.12)  8 (5.25)  3 (6.73)
 Grains/spike  3 (7.98))  1 (8.37)  4 (6.90)  6 (6.33)  5 (6.72)  7 (6.33)  8 (6.21)  2 (8.01)
 Grain type  2 (7.85)  3 (7.67)  4 (6.96)  7 (6.11)  5 (6.76)  6 (6.76)  8 (5.96)  1 (8.05)
 Grain yield  1 (8.58)  2 (8.55)  7 (5.65)  8 (5.39)  4 (6.48)  5 (5.74)  6 (5.74)  3 (7.87)
 Straw yield  1 (7.21)  2 (6.92)  5 (5.06)  6 (5.04)  3 (6.64)  7 (4.45)  4 (5.29)  8 (4.32)
 Rank and overall score  2 (86.03)  1 (89.13)  5 (75.94)  7 (70.54)  4 (77.40)  6 (71.27)  8 (70.42)  3 (83.38)

The parameters assessed were germination, number of effective tillers, days to maturity, plant height, lodging resistance, insect and disease resistance, ear head length, grains per spike, grain yield, straw yield, and grain type. The two traits namely germination and grains/ spike with score three were the first priority of all the farmers surveyed. Days-to-flowering and maturity did not receive much attention as evident by the score less then two. Some yield contributing traits like number of effective tillers, grain type, and 1,000-kernel weight were preferred by the farmers and matter while selecting wheat genotype for commercial cultivation at these sites. This type of ranking also is practiced by the researchers and, hence, are in the similar order. During the farmers' days, the participants were briefed about the objectives of the DFID project. More than 1000 farmers participated in this program. However, for the purpose of perception a total 100 farmers were randomly selected from the adapted sites. O n the basis of farmers' responses, the varieties were ranked. All the cultivars sown were evaluated by individual farmers in the field before and at maturity on a three point continuum, very good (3), good (2), and not good (1). The matrix ranking along with the evaluation score of all the genotypes used for study were estimated and are given in Table 2.
Matrix ranking of wheat cultivars on the basis of evaluation score and economic importance score of parameters. The cultivars were ranked on the basis of economic importance of the parameter and the evaluation score. Thereafter, the scores of all the parameters were summed for a cultivar to arrive at a composite score. On the basis of the composite score, PBW 343 ranked first, followed by HD 2687, WH 711, UP 2338, PBW 373, UP 2425, RAJ 3765, and WH 542.

Conclusion. The Participatory Varietal Selection programs in the high potential production system in India successfully identified new, nonrecommended cultivars that farmers preferred and adopted. The farmer participatory approach could be helpful in at least two ways. First, farmers would benefit by adopting new technologies and, second, a strong linkage would be established between researchers, farmers, and other sources of new technology such as the State Agriculture Department and seed certification agency, which, in turn, would increase production, productivity, and profitability of farmer and also help to meet our estimated demand of 109 x 106 t of wheat production by the year 2020.

Acknowledgment. The authors would like express their gratitude to authorities at ICAR, New Delhi; Project Director, DWR, Karnal; Dr. G.O. Ferrara, CIMMYT, SARO, Kathmandu, Nepal; and the DIFD Agency for technical and financial support provided for the present study. We also thankfully acknowledge the support from the coöperators in India.



Effect of etherel on seed set, outcrossing, pollen sterility, and yield traits in wheat. [p. 51-56]

S.K. Singh and R.M. Singh, A.K. Joshi, and Ram Dhari (Institute of Agricultural Sciences, Banaras Hindu University, Varanasi-221005, India).

Abstract. We studied the effect of etherel at different concentrations on various floral and yield traits, the crop growth stage for chemical spray, and sowing time for their possible use in development of wheat hybrids. Two genotypes, HD 2285 and Raj 3765, were included in the study and data were recorded on reduction in seed number/spike as % of control, outcrossing %, pollen sterility %, plant height (cm), spike length (cm), and spikelet length (mm). Etherel at 12,000 ppm was observed effective for maximum reduction in grain number/spike with increased pollen sterility and outcrosing (%). The reduction in plant height, spike length and spikelet length was observed due to phytotoxic effects of chemicals. Late sowing and chemical spray at early boot stage were found more effective for etherel treatment.

Introduction. Wheat is a strictly self-pollinated crop (Percival 1921). Conventional breeding methods have contributed significantly in increasing wheat production. We need to explore new approaches to break the yield barriers and make wheat cultivation more remunerative. Among the possible alternatives, an important approach has been to exploit hybrid vigor at commercial level. Hybrids in wheat may cause a quantum jump in production at the global level, but the main bottleneck is the floral structure of wheat, which has very small florets, necessitating hand emasculation and pollination, labor oriented and tedious work, which ultimately results in higher cost for hybrid seed. The limitations of genetic and/or cytoplasmic male sterility, i.e., unstable nature, undesirable linkages, and need for use of maintainers, have prompted breeders to develop simple and more efficient methods to create male sterility by other means like use of chemical hybridizing agents (CHAs) and mutagens. Male sterility induced by CHAs (Moore 1950; Naylor 1950) is relatively more convenient to use because there is no need to maintain it (McRae 1985). These chemicals induce male sterility by inhibiting the early stages of sporogenous cell formation to the inhibition of anther dehiscence (McRae 1985). Law and Stoskopf (1973) and Hughes et al. (1974) suggested the use of etherel for creating male sterility in plants. The present investigation was aimed at the effect of different doses of etherel, the stage of crop for spray, and sowing time of genotypes on various floral and yield parameters.

Materials and methods. The wheat cultivars HD 2285 and Raj 3765 were used as experimental material. The field experiments were conducted in randomized block design with three replications during 1998-99 crop season at Agricultural Research Farm at Banaras Hindu University, Varanasi, India (25^o^18' N latitude and 82^o^03' longitude), which falls under semiarid to subhumid climate. The annual average rainfall is 1,081.4 mm, and mean relative humidity is 62 %. The maximum and minimum temperatures range between 23.2-46.4 C and 9.3-24.5 C, respectively. Wheat cultivars were sown on two dates to evaluate timely and late-sown conditions. Each plot had six 2.5-m rows with inter- and intrarow spacing of 25 cm and 10 cm, respectively. The inner two rows were treated as females and the outer four rows as males. A gap of 1 week was kept between the male and female rows to synchronize the pollen release and stigma receptivity; female rows were sown first. Etherel (6,000, 9,000, and 12,000 ppm) was sprayed at two crop growth stages. First spraying was done when spike length was 11­13 mm and was still inside the whorl. This stage of spike length was achieved at around 35 days after germination when the plant height was slightly less than one foot and the second at boot stage prior to spike emergence. Control plants were sprayed with water. Chemicals were sprayed in the evening to give sufficient time for their absorption by the wheat plant. At flowering, the male rows were shaken with the help of a rope pulled across the field. Control plants were also grown and sprayed with water. The data was recorded on reduction in grain number/spike as percent of control, out crossing (%), pollen sterility (%), plant height (cm), spike length (cm), and spikelet length (mm). The data were recorded as per the procedure followed by Mahajan et al. (1997). Analysis of variance was done using factorial randomized block design analysis. The computer program INDOSTAT was used for this purpose.

Results and discussion. The ANOVA (Table 3) revealed that variation in sowing dates, genotypes, chemical concentrations, and spray stages were highly significant for the traits of reduction in grain number/spike (%), plant height (cm), spike length (cm), and spikelet length (mm). Out crossing (%) and pollen sterility (%) had highly significant differences due to genotype and chemical concentrations, indicating that these two traits were unaffected due to change in sowing time as well as spray of chemical in different stages.

Table 3. Analysis of variance (ANOVA) for various traits following a spray of etherel in wheat. * and ** indicate significance at the 0.05 and 0.01 levels, respectively.

 Source  d.f.  Reduction in grain #/spike (%)  Outcrossing (%)  Pollen sterility (%)  Plant height (cm)  Spike length (cm)  Spikelet length (mm)
 Replication  2  0.061  1.894*  0.538  0.303*  0.002  0.002
 Treatment  31  4,672.097**  352.992**  4,540.879**  582.965**  2.310**  16.997**
 Factor A (sowing date)  1  16.129**  45.128**  0.461  36.236**  0.776**  5.120**
 Factor B (spray)  1  2.145**  1.092  0.210  3.977**  0.173**  1.443**
 AB (sowing date x spray)  1  0.137*  0.007  0.002  0.078  0.002  0.003
 Factor C (genotype)  1  14.750**  142.301**  3.701**  167.059**  0.159**  0.178**
 AC (sowing date x genotype)  1  0.010  1.260  0.790*  1.972**  0.071**  0.410**
 BC (spray x genotype)  1  0.069  0.186  0.077  0.002  0.015  0.098**
 ABC (sowing date x spray x genotype)  1  0.011  0.182  0.007  0.096  0.005  0.001
 Factor D (Concentration)  3  48,262.271**  3,553.475**  46,916.510**  5,940.677**  22.667**  169.326**
 AD (sowing date x concentration)  3  2.341**  4.792**  0.410  2.706**  0.049**  0.382**
 BD (spray x concentration)  3  0.344**  0.674  0.184  0.638**  0.018**  0.086**
 ABD (sowing date x spray x concentration)  3  0.072*  0.167  0.406  0.022  0.006  0.005
 CD (Genotype x concentration)  3  1.923**  22.078**  2.733**  9.579**  0.669**  3.336**
 ACD (sowing date x genotype x concentration)  3  0.051  2.459**  0.296  0.419**  0.048**  0.062**
 BCD (spray x genotype x concentration)  3  0.167**  0.455  0.110  0.095  0.012  0.010
 ABCD (Sowing date x spray x genotype x concentration)  3  0.082**  0.105  0.017  0.034  0.003  0.008
 Error  62  0.020  0.596  0.183  0.076  0.006  0.008
 Total  95            

Effect on seed set, out crossing, and pollen sterility. The results (Table 4) indicated that the seed setting in the genotype HD 2285 was more adversely affected due to etherel treatment as it showed more than 93 % reduction in seed setting compared to control at higher concentrations. Maximum reduction (93.91 %) was observed at 12,000 ppm concentration in HD 2285 when etherel was sprayed at boot stage in late sown crop. A similar trend also was observed in the Raj 3765. The range of out crossing in the control (untreated) in both the genotypes was 1.35 to 1.63 %. An increase in the outcrossing percent was noticed when these genotypes were treated with etherel and was higher with increased concentration. More than 28 % outcrossing was observed at higher concentrations in both the genotypes. Significant differences were observed between various combinations of sowing time and spray stage within the genotype. Both the genotype showed about 7-8 % pollen sterility in the untreated population. Because etherel works as chemical hybridizing agent that causes male sterility in plant system, it induced more than 97 % pollen sterility in both the genotypes. More pollen sterility at high concentrations may be a probable reason for poor seed set in these genotypes.

Effect on yield traits (plant height, spike length, and spikelet length). Plant height, spike length, and spikelet length are the traits that significantly contribute to yield. A drastic reduction was noticed in these traits due to etherel treatment in both the genotypes (Table 4). In Raj 3765, more than a 47 % reduction in plant height was observed at 12,000 ppm, whereas it was little less in HD 2285 (46.46 %). This reduction was particularly due to phytotoxic effects of the etherel that reduced internode length. Reduction in plant height due to etherel also was observed by Rathgeb et al. (1982), Barbosa et al. (1987), Savchenko et al. (1989), and Zhao et al. (1993). Spike length was less affected in Raj 3765 compared to HD 2285. At 12,000 ppm, maximum reduction (29.71 %) in spike length was observed in timely sown treatment of HD 2285 when spraying was done at early boot stage. In Raj 3765 about 22 % reduction was recorded at highest concentration. The spikelet length was ranged from 7.50-11.37 mm in treated populations. The quantum of reduction in spikelet length was more than 44 % in both the genotypes compared to untreated control population when late sown crop was sprayed with 12,000 ppm etherel at early boot stage.

Table 4. The effect of different doses of etherel on various traits in wheat. SD1 = Timely sown conditions and SD2 = Late-sown conditions; S1 = crop stage when spike is 11-13 mm long (about 35 days after sowing) and S2 = early boot stage.

 Sowing date  Spray sstage  HD2285  Baj 33765
 Control  6,000  9,000  11,000  Control  6,000  9,000  11,000
 Reduction in seed set (%)  
 SD1  S1  0.00  85.04  89.28  93.18  0.00  84.27  88.32  91.99
 S2  0.00  86.16  89.78  93.37  0.00  84.40  89.01  92.38
 SD2  S1  0.00  86.64  90.77  93.69  0.00  85.32  89.98  92.87
 S2  0.00  87.28  90.92  93.91  0.00  85.75  90.07  93.12
     SE ± 0.08  CD (5 %) = 0.16
 Outcrossing (%)  
 SD1  S1  1.53  23.69  27.43  28.60  1.41  20.87  22.43  25.89
 S2  1.63  23.88  27.56  27.40  1.35  21.28  21.67  25.50
 SD2  S1  1.58  25.51  29.16  29.29  1.37  21.87  25.05  28.42
 S2  1.61  25.52  28.56  28.72  1.35  21.90  24.63  28.62
     SE ± 0.45  CD (5 %) = 0.90
 Pollen sterility (%)
 SD1  S1  8.24  95.85  96.00  97.01  7.54  93.98  96.17  97.27
 S1  8.10  95.53  95.67  97.55  7.47  93.92  95.33  97.67
 SD2  S1  7.72  95.52  95.88  97.70  7.54  94.60  96.49  97.64
 S1  7.77  95.45  96.10  97.46  7.39  94.58  96.22  97.45
     SE ± 0.25  CD (5 %) = 0.50
 Plant height (cm)
 SD1  S1  75.01  45.47  43.45  40.80  70.60  44.80  41.05  38.65
 S1  75.01  44.80  42.80  40.50  70.72  44.20  40.80  38.20
 SD2  S1  74.48  44.35  41.90  40.20  70.27  42.80  38.95  37.50
 S2  74.52  43.75  41.20  39.90  70.17  41.60  38.50  37.10
     SE ± 0.16  CD (5 %) = 0.32
 Spike length (cm)
 SD1  S1  8.70  7.53  7.10  6.25  8.63  7.25  6.90  6.75
 S2  8.75  7.35  6.80  6.15  8.62  7.15  6.85  6.70
 SD2  S1  8.65  7.25  6.55  6.10  8.55  7.05  6.80  6.65
 S2  8.60  7.15  6.40  6.05  8.49  6.95  6.75  6.60
     SE ± 0.04  CD (5 %) = 0.08
 Spikelet length (mm)
 SD1  S1  13.83  11.37  9.45  8.40  14.70  10.25  9.05  8.65
 S2  13.70  10.90  9.10  8.10  14.63  9.87  8.95  8.40
 SD2  S1  13.57  10.30  8.90  7.90  14.60  9.65  8.80  8.20
 S2  13.50  9.85  8.60  7.50  14.50  9.45  8.65  8.00
     SE ± 0.05  CD (5 %) = 0.10

Effect of sowing date and crop stage. The effect of sowing date and crop stage for etherel spray on various traits in wheat genotypes was studied. The effect of chemical spray on various traits was observed in timely as well as late sown condition and the results indicated more reduction in seed setting in late sown genotypes (Table 5). The late-sown crop was more responsive to the etherel treatment for increasing out crossing rate. In late-sown conditions, the outcrossing rate was 5.66-8.39 % more when compared to timely sown crop. A significant increase in outcrossing was observed in Raj 3765 with increased concentrations. Pollen sterility % was similar in timely and late-sown conditions, which also was indicated from the ANOVA. Plant height, spike length, and spikelet length showed more reduction in late-sown conditions. These findings indicated that the late sown crop was more responsive to CHA treatment for induction of male sterility, enhanced out crossing rate and reduced seed setting in selfed spikes (Mahajan et al. 1997; Singh et al. 2000), but the extent of phytotoxic effects in terms of reduction in plant height, spike length, and spikelet length should be considered because significant reduction in these traits was observed compared to timely sown crop.

Table 5. The effect of different doses of etherel on various traits in wheat. SD1 = Timely sown conditions and SD2 = Late-sown conditions; S1 = crop stage when spike is 11-13 mm long (about 35 days after sowing) and S2 = early boot stage.

 Sowing date  HD2285  Baj 33765
 Control  6,000  9,000  11,000  Control  6,000  9,000  11,000
 Reduction in seed set (%)
 SD1  0.00  85.60  89.53  93.28  0.00  84.34  88.67  92.19
 SD2  0.00  86.96  90.84  93.80  0.00  85.53  90.02  92.99
   SE = ±0.06  CD (5 %) = 0.12
 Outcrossing (%)
 SD1  1.58  23.79  27.50  28.00  1.38  21.08  22.05  25.70
 SD2  1.89  25.52  28.86  29.16  1.36  21.89  24.84  28.52
   SE = ±0.32  CD (5 %) = 0.64
 Pollen sterility (%)
 SD1  8.17  95.69  95.83  97.28  7.51  93.95  95.75  97.47
 SD2  7.75  95.48  95.99  97.58  7.47  94.59  96.36  97.55
   SE = ±0.18  CD (5 %) = 0.36
 Plant height (cm)
 SD1  75.01  45.13  43.13  40.65  70.66  44.50  40.93  38.43
 SD2  74.50  44.05  41.55  40.05  70.22  42.20  38.73  37.30
   SE = ±0.11  CD (5 %) = 0.22
 Spike length (cm)
 SD1  8.72  7.44  6.95  6.20  8.62  7.20  6.88  6.73
 SD2  8.63  7.20  6.48  6.08  8.52  7.00  6.78  6.63
   SE = ±0.03  CD (5 %) = 0.06  
  Spikelet length (mm)
 SD1  13.77  11.14  9.28  8.25  14.67  10.09  9.00  8.53
 SD2  13.53  10.08  8.75  7.70  14.55  9.55  8.73  8.10
   SE =±0.04  CD (5 %) = 0.08

The effect of etherel on these two genotypes was observed in relation to crop growth stage for spray of the chemical (Table 6). Spray at early boot stage showed more reduction in seed setting than the spray when spike length was 11-13 mm. Outcrossing rate and pollen sterility were almost similar in both the cases and these traits are not affected by the crop stage for spray. Plant height, spike length, and spikelet length were the traits that are more adversely affected by the chemical spray at early boot stage. These have relatively less reduction when etherel was sprayed at stage when spike length was 11-13 mm. From these findings, early boot stage might be the appropriate stage of chemical spray provided the chemicals has less phytotoxic effects at the proper concentration for complete pollen sterility.

Table 6. The effect of spray stage on various traits at different doses of etherel in wheat. S1 = crop stage when spike is 11-13 mm long (about 35 days after sowing) and S2 = early boot stage.

 Sowing date  HD2285  Baj 33765
 Control  6,000  9,000  11,000  Control  6,000  9,000  11,000
 Reduction in seed set (%)
 S1  0.00  85.84  90.02  93.44  0.00  84.80  89.15  92.43
 S2  0.00  86.72  90.35  93.64  0.00  85.07  89.54  92.75
   SE ± 0.06  CD (5 %) = 0.12
 Outcrossing (%)
 S1   1.75  24.60  28.30  29.10  1.39  21.37  23.74  27.15
 S2   1.72  24.70  28.06  28.06  1.35  21.59  23.15  27.06
   SE ± 0.32  CD (5 %) = 0.64
 Pollen sterility (%)
 S1  7.98  95.68  95.94  97.35  7.54  94.29  96.33  97.46
 S2  7.94  95.49  95.88  97.50   7.43  94.25  95.78  97.56
   SE ± 0.18  CD (5 %) = 0.36
 Plant height (cm)
 S1  74.74  44.91  42.68  40.50  70.44  43.80  40.00  38.08
 S2  74.76  44.28  42.00  40.20  70.45  42.90  39.65  37.65
   SE ± 0.11  CD (5 %) = 0.22
 Spike length (cm)
 S1  8.68  7.39  6.83  6.18  8.59  7.15  6.85  6.70
 S2  8.68  7.25  6.60  6.10  8.55  7.05  6.80  6.65
   SE ± 0.03  CD (5 %) = 0.06
 Spikelet length (mm)
 S1  13.70  10.84  9.12  8.15  14.65  9.95  8.93  8.43
 S2  13.60  10.38  8.85  7.80  14.57  9.66  8.80  8.20
   SE ± 0.04  CD (5 %) = 0.08

From the above findings and discussion, we concluded that the etherel at higher concentrations may create perfect male sterility. Spraying at early boot stage is advantageous in late sown conditions for getting more sterility. In the future, the chemical that causes 100 % male sterility at lower concentration with minimum phytotoxic effects will make hybrid wheat a success.

Acknowledgment. Indian Council of Agricultural Research (ICAR), New Delhi, is acknowledged for financial assistance as Senior Research Fellowship to the first author.



Determining the optimum row ratio for hybrid seed production in wheat. [p. 56-57]

S.K. Singh and R.M. Singh (Institute of Agricultural Sciences, Banaras Hindu University, Varanasi-221005, India).

Determining the optimum male:female row ratio is important for having economically viable, hybrid seed production program. An optimum row ratio not only reduces the cost of production of hybrid seed but also helps in better utilization of the available resources. This experiment determined the optimum row ratio (male and female) for hybrid seed production in wheat.

Four cultivars, HD2285, HD2329, HUW 234, and HUW 206, were used as experimental material. HD 2285 and HD 2329 were female parents and HUW 234 and HUW 206 were males. The female and male rows (3-m long) were sown in at 1:1, 2:1, and 3:1 ratios in a randomized block design with three replications at the Agri Research Farm, Banaras Hindu University, Varanasi, India. Recommended practices were adopted for raising a good crop. The inter- and intrarow spacings were 25 cm and 10 cm, respectively. Etherel was sprayed in the female rows at 7,000 ppm at the stage when spike was about to emerge out of the leaf sheath to induce male sterility in those rows. This concentration created more than 90 % male sterility. A rope was pulled across the row at flowering for three consecutive days to promote outcrossing. At maturity, all female rows were harvested and the yield/female row was calculated. The data was subjected to two-factor factorial randomized block design analysis. Factors A and B were row ratio and crosses, respectively. To test significance, the calculated F values were compared with Table F values at an error d.f. of 5 % and 1 % level of significance.

Yield levels were measured at three male:female ratios, 1:1, 1:2, and 1:3. The ANOVA showed that treatments and crosses differed significantly (Table 7). However, ANOVA did not indicate a significant difference for the row ratios, indicating that all the row ratios are comparable. The mean values of yield/female row in variable row ratios (male:female) of four crosses have been shown in Table 8. Comparing yield of individual crosses at variable row ratios, the results indicated that 1:1 was significantly superior to 1:2 and 1:3 ratios in 50 % of the cases. Thus, the results in general have indications for the superiority of 1:1 row ratio than the other two ratios. In the cross 'HD2285/HUW234', a 1:3 ratio yielded more than a 1:2 ratio. Among the cross combinations, 'HD2329/HUW234' had maximum yield/female row in the entire row ratios followed by 'HD2285/HUW206' and 'HD2285/HUW234'. However, all row ratios were comparable in the cross 'HD2329/HUW206'. Earlier studies in row ratio are lacking, but these also suggest comparable performance at 1:1, 1:2 and 1:3 row ratios (Wilson 1968; Miller and Lucken 1976; Briganti et al. 1981; Warner 1985). From the results it is concluded that all the row ratios were comparable from yield point of view. Although the highest yield was obtained from 1:1 male:female ratio, 1:3 male:female ratio can be utilized for economic seed production.

Table 7. Analysis of variance (ANOVA) for yield/female row (g) in wheat (** indicates significance at the 1 % level).

 Source  d.f.  Mean square
 Replication  2  33.94
 Treatment  11  172.15**
 Factor A (Row ratio)
 2  90.11
 Factor B (crosses)
 3  559.59**
 AB (Row ratio x crosses)
 6  5.78
 Error  22  27.91
 Total  35  

Table 8. Grain yield/row (g) of female parent in different male:female ratios of four wheat crosses (C.D. 1 %; row ratio = 4.31; crosses = 4.98).

   Cross  Yield / female row
 1:1  1:2  1:3
 HD2285 / HUW234  37.38  30.83  31.66
 HD2285 / HUW206  39.37  34.67  33.21
 HD2329 / HUW234  52.33  48.00  46.11
 HD2329 / HUW206  32.44  32.17  29.44

Acknowledgment. The first author is thankful to the Indian Council of Agricultural Research (ICAR), New Delhi for financial assistance in the form of Senior Research Fellowship.


Prebreeding to pyramid genes for yield and quality component traits in Indian wheats. [p. 57-59]

B.S. Tyagi, Gyanendra Singh, Jag Shoran, D. Dutta, Ravish Chatrath, and S.K. Singh.

Wheat occupies an area of nearly 27 x 10^6^ ha in India and now stands second next to China at the global level. During the last three decades, wheat production has continued to increase at a rate of about 1.0 % per annum. However, this is not enough to feed the ever increasing population of India, which will need around 109 x 10^6^ t of wheat by 2020 AD. From the onset of the Green Revolution in India, the program has had diverse material and cultivars were released for different agro-climatic and production conditions. Now, the yield potential of modern cultivars has not shown expected increases after the release of a very popular cultivar PBW 343, probably due to exhausting genetic diversity. We now need the proper gene combinations responsible for higher yields and end-product quality. Because genetic variability is directly linked with selection efficiency not only for yield but for biotic and abiotic factors, efforts were initiated about a decade ago to mobilize the genes from unconventional sources such as synthetic wheats, buitre types, and wild species. Long spike buitre material developed by Ricardo Rodriguez has a robust stem, a long spike, more spikelets and grains/spike, a large leaf area, and broad leaves. A large number of synthetic hexaploids developed at CIMMYT (Mujeeb Kazi 1996) are endowed with genetic richness for high grain weight, delayed senescence (stay green), HMW-glutenin content, and resistance to KB and yellow rust. However, this germ plasm had certain inherent limitations, such as susceptibility to rust diseases and seed shriveling in buitre types, hard threshing, red grain color, and delayed heading and maturity. Several selections of recombination and mild selection may be required to develop a gene pool that adequately will allow further progress using wild relatives. Prebreeding efforts in using the wild species is very essential.

Donor lines were identified for major economic traits such as tillering, spike length, grain size, protein content, and b-carotene content. A number of crosses involving these lines were attempted with promising released cultivars (Table 9). The F1 seed was sown, but only a few germinated. In some cross combinations no seed was set, whereas in others a few seeds were obtained. Cytological observations revealed a large number of cells showed aneuploidy and asynapsis between the chromosomes of the two different genomes resulting in sterile pollen. A few plants survived and set seed in the F2 generation and are in advanced generations. Some plants from these crosses had good spike length with more spikelets/spike (Table 10). Plants from the cross 'Ae. kotchyii / HI 8498' had a spike length of 17.2 cm compared to 9.2 cm for the durum wheat check. Similarly, progeny of 'Ae peregrina / Exo 48' also have a very long spike. These lines have been back crossed with recurrent parent.

Table 9. Crosses attempted with wild relatives and F2 seeds available.

 Wild species  Promising cultivars  # F2 seed obtained
 Ae. peregrina  Raj 1555, HI 8498, PBW 343  1-2
 T. urartu  HI 8498, Gulab, PDW 233  2
 Ae. speltoides  Raj 1555, HI 8498  3
 Ae. tauschii  HI 8498  3
 Ae. cylindrica  PDW 233  10
 Long ear buitre type  HI 8498, C306, Raj 1555  5
 T. turgidum subsp. polonicum  PBW 343, HI 8498  Seeds with deformed embryo

Table 10. Wide crosses showing promising traits in advanced generations.

 Genotype  Ear length (cm)  Spikelets/spike  Tillers/plant
 T. urartu / WH 542  14.2-15.4  9.5  20
 Ae. kotschyi / HI 849  15.8-17.2  8.0  24
 Ae peregrina / Exo 48  5.0-16.3  8.0  23
 HI 8498 (d)  8.5-9.2  6.0  21

To widen the adaptability to various stress conditions, synthetic lines involving Ae. tauschii in their pedigree are being used in our hybridizing program with promising cultivars such as WH 542, PBW 343, and HD 2687. Crosses attempted using synthetics are listed below:

68112 / Ward / Ae. tauschii / WH542
PBW114 /Ae. tauschii / PBW343
68112 / Ward / Ae. tauschii / PBW343
PBW114 / Ae. tauschii / HD2687
CROC-1 / Ae. tauschii / WH542
Gan / Ae. tauschii / PBW343
CROC-1 / Ae. tauschii / HD2687
Gan / Ae. tauschii / WH542

Segregating lines have shown improvement in tillering (up to 43 %), spike length (27 %), and grain size (23 %) compared to PBW 343, PDW 233, PBW 34, HD 2687, and C 306.

The beta-carotene (~6 ppm) and protein content (~12%) in promising cultivars are comparatively low and, therefore, some donors possessing high b-carotene (> 9 ppm) and protein content (> 15 %) were identified and crossed with well-adapted modern cultivars to improve their end-product quality (Table 11). As a result, improvement for these characters was very apparent. We recorded increase for these two traits up to 14 ppm and 18 %, for b-carotene and protein content, respectively. This material is now in advanced stages (F5, F6, and F7) of testing and also is being shared with active wheat-breeding centers in India. Some lines were even better than the best check for b-carotene and test weight and comparable with the check for heading and grain yield. One such genotype, DDW 06, which was evaluated at the national level, was in the first nonsignificant group in the Peninsular Zone and is being used for further improvement with respect to disease resistance, particularly black rust. Identified sources and promising cultivars used are in Table 12.

Table 11. Trait-specific parents and characteristics identified for quality improvement of Indian wheat cultivars.

 Characteristic  Stock parent  Low-value parent
 beta-carotene  NGSN 6, DDW 01  PBW 34, HD 4502
 1,000-kernel weight  Bawaji, CDW 03  PDW 233
 Protein  Winter durums  PDW 233

Table 12. Identified sources for certain traits and promising cultivars used for improvement.

 Trait  Sources
 beta-carotene (>9 ppm)  DDW 01, NGSN 6, NGSN 7, DBP 01-16
 Protein content (>14 %)  SABIL, Terter, NP 404
 Kernel size (>55 g /TG)  Bawaji, DDW 02, CDW 03
 Elite cultivars to be improved  HD4502, PDW233, HI8498, A-9-30-1

We also have noticed that some of the lines coming out of crosses made with synthetics need improvement in threshability and duration. Backcrossing with an agronomically useful parent is being attempted. In crosses involving wide sources, the negative effect of grain shriveling, which might be due to asynapsis, is being complemented by manipulating the ph locus. This scheme has helped develop and identify sources of economic and quality traits and also to widen the genetic base to some extent. Utilizing unconventional sources for improving these traits seems a very viable option to achieve the anticipated yield gains in wheat crop.



Screening of wheat genotypes for root aphid (Rhopalosiphum rufiabdominalis) resistance. [p. 59-60]

K.S. Babu, N.V.P.R. Ganga Rao, and S.K. Singh.

At present, in the IPR system the emphasis in the Indian wheat program is on creating new genetic variability through unexploited germ plasm, such as long-spike buitre plant types, synthetic hexaploids, Chinese subcompact ear germ plasm, and wild relatives. The long-spike Buitre material developed by Rodriguez Ricardo has a robust stem, a long spike, more spikelets and grains per spike, a large leaf area, and broad leaves. A large number of synthetic hexaploids developed at CIMMYT by Mujeeb Kazi are genetically rich for high grain weight, delayed senescence (stay green), HMW glutenins, and resistance to KB and yellow rust. The subcompact Chinese germ plasm has a robust stem, more grains/spike, and is a new source of yellow rust resistance genes. However, these synthetic hexaploid lines have certain inherent limitations, such as susceptibility to rust and seed shriveling in the Buitre types, hard threshing, red grain color, and delayed heading and maturity. Likewise, the very soft grains in the Chinese germ plasm are very prone to insect damage.

Cereal aphid infestation of the wheat crop has not been dealt with in detail in India so far because of their limited importance in wheat production. But changes in the environment and new crop production practices are changing the pest spectrum. Of the four major species of aphids reported in India, the rice root aphid (Rhopalosiphum rufiabdominalis) is becoming a regular pest in northwestern plains on wheat during the last 3 years (Figure 1). The rice root aphid remained an obscure species in the Indian wheat program because of its limited occurrence in central India until now. The activity of root aphid starts during first fortnight of December and continues until temperatures are slightly warmer, sometime up to the first week of January.

Although little work has assessed the impact of this pest on yield and yield-contributing characteristics, Kindler et al. (2003) suggested it will cause economic damage and transfer BYDV. Keeping this in view, we screened wheat genotypes selected from various national and international nurseries having good agronomic background and disease resistance against rice root aphid.

Material and methods. Thirty-nine wheat genotypes which were found resistance to rust diseases and having good grain strength and better performance for various yield traits were taken for the study (Table 13). These genotypes were planted in the field in a double row plot of 3.0 m length during two consecutive crop seasons, Rabi 2004-05 and 2005-06. These genotypes were grown in two replications, and 30 random plants were selected for screening under natural conditions against root aphids. The standard screening procedure of the All India Coordinated Wheat and Barley Improvement Project was followed to screen these genotypes (Table 14).

Table 13. Genotypes screened for resistance to the rice root aphid (Rhopalosiphum rufiabdominalis) at Karnal, India, during the 2004-05 and 2005-06 rabi seasons.

 Genotype  Parentage
 PB03-1  VS1065 / PBW 343
 PB03-2  VS 433 / RAJ 3777
 PB03-3  HTWYT 6 / ESWYT 38
 PB03-4  VS 433 / RAJ 3777
 PB03-5  NTWYT 6 / ESWYT 38
 PB03-6  PBW 343 / HE 1 / 5XCN079BM95
 PB03-7  PBW 343 / HE 1 / 5XCN079BM95
 PB03-8  VS 433 / RAJ 3777
 PB03-9  FASAN /2*TEPOCA /3/ CHEN / Ae. tauschii // BCN
 PB03-10  DL 321
 PB03-11  PGW 21
 PB03-12  KYZ 0144
 PB03-13  PBW 343 / FIOS 1
 PB03-14  PSN/BOW // SITTA /3/ RDWG
 PB03-15  RAJ 3765 / K9107 / JOB 79
 PB03-16  RAJ 3765 / K9107 / JOB 79
 PB03-17  F3BMESTE 57
 PB03-18  CHIL / PRL
 PB03-19  CMH83.2517 / GW 190
 PB03-20  CHEN / Ae. tauschii // FCT /3/
 PB03-21  WR 783
 PB03-22  LONG 94 444 / WH542
 PB03-23  LOK BOLD
 PB03-24  SGH 15
 PB03-25  SGH 30
 PB03-26  MUNIA / CHTO /3/ PFAU / BOW / VEE#9 /4/ CHEN /. . .
 PB03-27  CROC_1 / Ae. tauschii (213) // PGO /3/ CMH81.38/ . . .
 PB03-28  CROC_1 / Ae. tauschii (213) // PGO /3/ CMH81.38/ . . .
 PB03-29  CROC_1 / Ae. tauschii (213) // PGO /3/ CMH81.38/ . . .
 PB03-30  ATTILA / 3*BCN
 PB03-31  XIANG 82.2661 / 2*KAUZ
 PB03-32  YUMAI 13 / 2*KAUZ
 PB03-33  BCN/CROC 1 / Ae. tauschii (662)
 PB03-34  BABAX*2 / PRL
 PB03-35  ALTAR 84 / Ae. tauschii (219) // SERI
 PB03-36  ALTAR 84 / Ae. tauschii (219) // 2*LOXIA /3/ KAUZ
 PB03-37  CHEN / Ae. tauschii // BCN /3/ KAUZ
 PB03-38  BOW // BUC /3/ WEAVER /4/ STAR

Table 14. Criteria for scoring of resistance against root aphid.

  Category   No. of root aphids/plant
 Immune  0
 Highly resistant  1-5
 Resistant  6-10
 Susceptible  > 11

Results and discussion. The genotypes screened against root aphid represented diverse groups. Grown in natural conditions, no insect control measures were used. Among the genotypes, six were highly resistant (PB03-16, PB03-17, PB03-23, PB03-24, PB03-34, and PB03-39), which included indigenously developed material and exotic lines that have BABAX, PRL, SITE, and MILAN in their pedigrees. Similarly, four synthetic hexaploid genotypes selected from various international nurseries were found to be resistant (4PB03-20, PB03-28, PB03-35, and PB 03-36).

None of the genotype was immune to the root aphid, whereas the remainder of the genotypes had aphid populations of more than 11 insects/plant and were categorized as susceptible. The genotypes with resistant reactions may be utilized in wheat improvement programs when the need arises.




Division of Genetics, New Delhi-110012, India.

Genetic diversity among bread wheat germ plasm for yield and its attributes. [p. 61-62]

B.S. Malik.

Introduction. Knowledge of genetic divergence, geographic diversity, and ancestory of parents is important for initiating a breeding strategy. The degree of heterosis as a result of hybridization is generally believed to be correlated with genetic divergence between the parents used (Ramanujam et al. 1974). The use of diverse parents in breeding program to obtain transgressive segregants has been emphasized (Jatsara and Paroda 1983; Cox and Murphy 1990). Geographical diversity and place of origin do not favor that the selected plants are necessarily genetically diverse (Murty and Arunachalam 1966; Lee and Kaltsikes 1972; Garg and Gautam 1988). The characterization of genetic divergence for selection of suitable and diverse genotypes should be based on sound D2 statistics. Mahalanobis' (1936) generalized distance has been successfully and extensively used to cluster genotypes in different group based on morphological characters in crop plants (Jatasara and Paroda 1978; Joshi and Singh 1979; Rao 1952). In this study, an attempt was made to evaluate 90 genotypes of bread wheat to identify genetically diverse and suitable parents for crossing program through the dispersion in different groups/clusters.

Materials and methods. Ninety genotypes of bread wheat from the Indian wheat program and those of exotic origin were used. These genotypes were grown in randomized block design with three replications at the Research Farm of Indian Agricultural Research Institute, New Delhi, during Rabi 2003-04, to assess genetic divergence using Mahalanobis' D2 statistics. Each genotype was sown in paired rows 3.0-m long with a between row distance of 23 cm and seed-to-seed spacing of 10 cm. The recommended amount of fertilizer and other inputs were applied to raise a successful crop. Five randomly selected plants from each plot were selected for recording observation on nine quantitative traits, days-to-heading, days-to-maturity, plant height, tiller number/plant, grains/spike, grain weight/ear, 1,000-kernel weight, total biomass, and grain yield/plant. Mahalanaobis' D2 statistics were used to assess the genetic diversity. Genotypes were grouped on the basis of minimum generalized distance/minimum generalized closeness using Tocher's method as described by Rao (1952).

Results and discussion. Genetic divergence among 90 wheat genotypes was worked out on basis of nine morphological characters. Based on the similarity of characters, the genotypes grouped into eight clusters (Table 1). Considerable genetic diversity in germ plasm exists for the characters studied as the number of genotypes varied from two to nineteen in these clusters. No similar pattern of characters was observed if two or more clusters were considered together. These genotypes seem to have been developed at different national wheat research centers. The exchange of wheat germ plasm s a result of international cooperation has played a very important role in the genetic amelioration of this crop. Genotypes used were developed at CIMMYT (Mexico), Australia, Canada, the U.S., Pakistan, and Brazil. The genotypes of different breeding centers grouped together in the same cluster. Genotypes from one place, HD, WR, DL, and DW (Delhi); UP (Pantnagar); WH (Hisar); HUW (Varanasi); PBW (Ludhiana); Triumph, Maxipak, Super X, and Siete Cerros (Mexico); and the Raj series (Rajasthan) were scattered in different clusters with cultivars of different geographical regions/origin indicating that pattern of clustering of genotypes was independent of their geographical region. These findings are in accordance with those of Murty and Arunachalam (1966), Bhatt (1970), Sethi et al. (1992), and Garg and Gautam (1988).

Table 1. Distribution pattern of 90 genotypes of wheat into eight clusters.

 Cluster No.   No. of genotypes  Genotype name
 I  19  HW2002A, HP1731, HD2258, HD2428, CIANO F67, DL932, SERI-82, RAJ4016, WH741, HW2046, HW2044, J492, WH712, HW2045, WH737, UP2586, LOK45, Super X, UP2425
 II  10  HUW327, DW1133, J908, HD2646, WH739, DW1182, HW2031, HD2705, HD2772, Kalyansona
 III  17  HD2270, HD2285, HD2307, RAJ3765, HD2877, J1316, HD2631, HD2637, HD2643, DL69, UP2338, HD2402, PBW343, NIAW34, LOK45, HI977, DWR162
 IV  14  Kavkaz, Nainari 60, DW1062, HD2687, HD2760, HD2733, HD2735, HW2002, HD2590, K9453, WR180, Triumph, CPAN1436, PBW502
 V  9  DL-784-3, Pavan, UP2504, RAJ4004, HD2670, HD2849, NP852, Mexipak, HD2160
 VI  16  Chil, PDW299, DW1192, K9704, HUW206, K9107, Parula 'S', HD2329, WH542, Siete Cerros, CPAN 3004, WR1038, DL50, Girija, C306, C217
 VII  3  DL-788-2, NI 8289, CPAN 1517

Divergence is an outcome of several factors namely genetic drift and selection intensity over the time that have resulted to cause genetic diversity rather than their geographical distance among genotypes. Any cultivars/genotypes may have a common place of development, but breeders may have used diverse germ plasm derived originally from widely separated geographical regions. No relationship between genetic diversity and place of origin of the genotypes could be ascertained. Somayajulu et al. (1970), Upadhyay and Murty (1970), Jatsra and Paroda (1978) also support this conclusion. The distribution of genotypes into different clusters was independent, because of the lack of relationship between the pedigree of genotypes and genetic divergence between them. Wheat genotypes with a common pedigree were grouped into different clusters having cultivars with different parentages. For example, Super X, Kalyansona, Mexipak, and Siete Cerros are derived from the cross II-8156 with the common pedigree 'Penjaino 'S'/Gabo55)' and were grouped in clusters I, II, V, and VI, respectively. Similarly PBW343, UP2338, PBW502, HD2687, HD2733, and HUW206 were derived from a Vee 'S' cross with T1B·1R were dispersed in clusters III, V, and VI. This substantiates the fact that these genotypes have become varying genetically different due to recombination and selection for traits in segregating generations. Furthermore, most of the genotypes grouped in cluster III were suitable for late-sowing conditions and were developed by different wheat research centers. Dependence on directional selection pressure that lead to the mechanism may favor accumulation of desired traits resulting in indiscriminate clustering (Redhu et al. 1993).

Grain yield shows the highest contribution towards genetic divergences followed by biological yield, tiller number, and grain/spike. Biological yield and harvest index cannot be considered as independent characters because their main component is through the economic yield, i.e., grain yield. In this study, the major characters contributing to genetic divergence are grain yield and tiller number with a moderate contribution from grain/spike, 1,000-kernel weight, and plant height. Jagshoran and Tandon (1995) observed grain yield, biological yield, and 1,000-kernel weight contributed more towards genetic divergence in winter wheat. Tillers/plant and grain yield have sizeable individual contribution (Kumar and Singh 1997). Mean values of nine morphological characters indicated considerable difference among mean values for all the characters and between the clusters (Table 2). Cluster III had the highest grain weight/spike (2.63 gm), 1,000-kernel weight (42.39 gm), and grain yield/plant (40.8 gm), whereas Cluster I had the maximum number of grain/spike (53.47) and biological yield (99.13 gm). The greatest number of tillers/plant were observed in Cluster IV (19.32). The three major yield-contributing traits, 1,000-kernel weight, grain/spike, and tillers/plant were dispersed in genotypes of clusters III and IV. If these traits are brought together through crossing, novel recombinants are possible in the succeeding generations.

Table 2. Mean values of different clusters for nine characters in bread wheat.

 Cluster  Days to heading  Days to maturity  Plant height (cm)  Tillers/plant  Grains/spike  Grain weight/spike (g)  1,000-kernel weight (g)  Biomass (g)  Grain yield/plant (g)
 I  86.95  127.26  96.43  19.27  53.47  2.32  39.36  99.13  36.79
 II  90.00  123.57  97.83  16.84  51.35  2.13  39.73  83.27  37.37
 III  85.30  118.42  103.57  18.74  53.27  2.63  42.39  93.16  40.89
 IV  90.32  129.32  100.37  19.32  49.79  2.24  40.34  90.89  36.38
 V  85.43  127.42  88.37  17.69  52.79  2.01  36.73  80.78  33.27
 VI  84.43  131.57  90.57  16.65  51.73  2.17  38.17  63.41  36.78
 VII  84.23  130.72  115.37  15.89  51.32  2.53  41.32  78.57  34.83
 VIII  85.00  126.82  133.67  17.40  50.70  1.98  37.31  73.10  30.13
 GM  86.45  126.88  103.27  17.72  51.80  2.25  39.41  82.78  35.80
 SE (M)±  1.21   1.73  2.11  - 1.32  2.44  0.18  2.01  4.01  2.11

Genotypes of one cluster are considered similar in respect to the combine effects of the characters studied. Cluster means and coefficients of variation provide information on the nature of diversity. The highest intercluster distance indicated greater diversity whereas minimum distance indicated less diversity or close relationship. The parent for a crossing program should be selected from a diverse cluster characterized by large intercluster distance. The better performing genotypes among the different clusters, HD2329 (VI), HD2160 (V), Lok 45 (III), Raj3765 (III), PBW343 (III), CPAN 3004 (VI), WR180 (IV), DL69 (III), and DL784-3 (V), were picked for their use in a crossing program aimed at obtaining superior segregants, because these parents possessed diverse yield.





Wellington - 643 231, the Nilgiris, Tamilnadu, India.


A rust-resistant, high-yielding bread wheat cultivar HD 2833 (Pusa wheat-105) released for Peninsular India likely to improve farm economy. [p. 63-64]

M. Sivasamy, A.J. Prabakaran, S.M.S. Tomar (Division of Genetics, Indian Agricultural Research Institute, New Delhi-12), K.A. Nayeem, and R.N. Brahma.

An early maturing wheat cultivar HD 2833 (Pusa wheat-105) developed jointly by IARI, RS, Wellington, and the Division of Genetics, IARI, New Delhi; exhibiting a high degree of resistance to all the Indian leaf rust pathotypes with best chapati-making quality recently was released for commercial cultivation by the CVIRC. This cultivar has been released for irrigated, late-sown situations occurring in the Peninsular Zone of India.

The area under late-sown conditions in Peninsular Zone has increased. The sowing of wheat now extends until mid-December. Because of the short duration of winter, farmers need early maturing cultivars that can withstand high temperatures at the time of anthesis and maturity. Thus, the Peninsular Zone demands early maturing and thermotolerant cultivars. The Peninsular Zone is an established route for uredospore transport to central India. The prominent pathotypes of stem rust in the Peninsular Zone are 40A, 40-1, and 122. Prominent leaf rust pathotypes are 77-5, 104-2, and 104B. Puccinia pathotypes could be interrupted by diversification of cultivars having different genetic composition of rust resistance genes in this epidemiological important zone. Because HD 2833 has a high degree of seedling and adult-plant resistance to the prevalent pathotypes of all the three rusts, cultivation would consequently avert the likelihood occurrence of epidemic(s).

HD 2833 has shown superior performance over all the checks and qualifying cultivars. HD 2833 was in the top nonsignificant group in all years of testing. The cultivar has a high degree of adult-plant resistance to all the three rusts and also is listed as resistant in the seedling stage to brown and block rusts. Yield response of HD 2833 in agronomic trials is higher than that of the check and qualifying cultivars under late and very late sown conditions. Thus, HD 2833 fulfils all the requirements of a successful late-sown wheat cultivar for Peninsular Zone.

HD 2833 recorded the highest grain yield of 34.5 q/ha and 31.2 q/ha under late-sown and very late sown conditions, respectively. These yields were superior to the checks and other cultivars. The data clearly demonstrate the agronomic superiority of HD 2833 under varying production conditions. HD 2833 produces lustrous grains with a higher appearance score than those of the check and other qualifying cultivars. The average hectoliter weight of HD 2833 is higher (80.9) than those of the checks HI 977 (78.0), NIAW 34 (79.3), and LOK 45 (76.0).

During quality testing in 2002-03 and 2004-05, HD 2833 was identified as one of the best cultivars for chapati making characteristics (Score >8/10) and was nutritionally rich with >13 % protein. This cultivar will have definite market preference, because this part of the world consumes the majority of wheat in the form of chapati and will play active roll in addressing the malnutrition problem as well.

With good grain appearance, high hectoliter weight, a high chapati-making score, and a desirable protein content, we expect that HD 2833 will become the consumer's preference. Rust resistance and good yield performance under late and very late sowing conditions will help farmers adopt HD 2833. For future wheat export, this cultivar will be one of the best choices, because it meets maximum quality parameters for both bread- and chapati-making quality with high protein content (13.12 %).

One of the parents involved in the pedigree has rust-resistance genes. A high degree of rust resistance is likely due to the presence of an alien segment. HD 2833 is postulated to have Sr2+gene(s), which provide durable resistance to stem rust. The Peninsular Zone is prone to have stem rust infections. HD 2833 is likely to occupy more area in near future even under nontraditional wheat belts in the Southern Hill Plains (in the states of Karnataka and Tamilnadu), where a sizable area is farmed by resource-poor farmers. Thus, this cultivar is likely to improve the livelihood of farmers and their farm economy.


Genetic enhancement and diversity of genetic composition in wheat cultivars by introgression of rust-resistance genes into popular Indian bread wheat cultivars. [p. 64-66]

M. Sivasamy, A.J. Prabakaran, K.A. Nayeem, R.N. Brahma, M.K. Menon, and S.M.S. Tomar (Division of Genetics, Indian Agricultural Research Institute, New Delhi-12).

Introduction. Yield loss caused by various rust diseases (stem, leaf, and stripe) are reported by several workers from time to time. To combat the disease, using the available genetic sources in wheat-improvement programs and developing rust-resistant wheats are the most effective means of control worldwide. The effective leaf rust genes Lr19, Lr24, Lr28, Lr32, and Lr37, and stem rust genes Sr24, Sr25, Sr31, and Sr38, have already been utilized by various workers worldwide and at IARI, Wellington (a hot-spot for rust and other foliar diseases), in particular. We have already initiated the process to utilize the newer rust-resistance gene sources.

Introgression of newer rust-resistance genes. Wheat is cultivated on about 26 x 10^6^ ha in India with present day wheat production of 72 x 10^6^ tons. The wheat crop is grown in various macro- and microclimatic zones and production conditions. The entire region is under the threat of stem and leaf rust epidemics, and yellow rust also is a problem in the North Western and Hill Regions. The scientific and systematic management of the wheat program in India has not allowed a rust epidemic in the recent past because of diversification of gene sources for rust resistance and releasing such cultivars for commercial cultivation. To avoid further epidemics, one has to deploy new cultivars with diverse genetic sources to curtail the evolution and spread of new rust pathotypes. We are making a continuous effort to introgress newer rust-resistance genes in several popular bread wheat cultivars that were carefully chosen from each zone and production conditions (see Table 1). The developed NILs and lines developed by hybridization will play a very effective roll in combating rust in India. Introgression and selection are made under natural epiphytotic conditions at Wellington and further confirmed on seedlings by using differentials at DWR, Regional Station, Shimla. We also use MAS by developing markers that are then used for further confirmation in a network with IARI, New Delhi, and DWR, Karnal. Similar work already has been done for Lr19, Lr24, Lr28, Lr32, Lr37, Sr24, Sr25, and Sr31.

Table 1. A comprehensive back cross program for transfer of newer effective rust resistance genes at IARI, Regional Station, Wellington. An * indicates newer genes used in the program.
 Disease  Genes used  Source  Chromosomal location
 Leaf rust  Lr19+Sr25  A. elongatum  7DL
 Lr24  A. elongatum  3DL
 Lr28  Ae. speltoides  4AL
 Lr32  Ae. tauschii  3D
 Lr35 *  Ae. speltoides  2B
 Lr37+Sr38+Yr17  Ae. ventricosa  2AS
 Lr39 *  Ae. tauschii  2DS
 Lr40 *  Ae. tauschii  1D
 Lr41 *  Ae. tauschii  2DS
 Lr42 *  Ae. tauschii  1D
 Lr44 *  T. aestivum subsp. spelta 7881  1BL
 Lr45 *  S. cereale  2AS
 Lr48 *  CSP44  
 Lr49 *  VL404  
 Stem rust  Sr24, Sr25, Sr38Sr26  A. elongatum  6AL
 Sr27 *  Imperial rye  3A
 Sr31+Lr26+Yr9+Pm8 *  Petkus rye  T1BL·1RS
 Sr36 *  T. timopheevii subsp. timopheevii  3AL
 Stripe rust  Yr6 *  Heines Kolben  7BS
 Yr10 *  Moro  1BS
 Yr15 *  Dippes, Triumph, T. turgidum subsp. dicoccoides  1BL
 Yr16 *  Capelle-Desprez  2DS
 Yr17  Ae. ventricosa  2AS
 Powdery mildew  Pm6 *    
 Pm8 *  Petkus rye  T1BL·1RS

Wheat cultivars used in the program include C 306, Sonalika, Kalyansona, WL 711, WH147, HD 2285, HD 2329, HD2402, HD2687, HS240, HUW234, K9107, Lok1, Lok bold, Lok-45, Lok 50, Lok 55, .MACS 2496, NI 5439, PBW226, PBW 343, WH542, HD2733, NIAW34, UP262, UP2338, HI1077, HI977, RAJ3077, PBN54, KRL99, and HD2009. The transfer and introgression of newer genes is now in at BC3, and material will be available from 2007 rabi onwards.

Traits associated with some of alien rust-resistance genes based on our field observation rather than effectiveness.
Lr19 + Sr25. Yellow pigmentation in the endosperm. We used a mutant devoid of it developed by Knott and Sharma, Cook 19, and Sunstar. Strongly associated with slow leaf senescence, Lr19 + Lr25 gives a significant yield advantage, however, new virulence for this gene was reported recently in India.

Lr24 + Sr24. Tightly linked genes. Sr24 is not effective in India (40-1). No yield loss has been observed on the lines with this gene. We used an amber grain derivative.

Lr28. A very effective gene but associated with fast stem rusting. In combination with Sr31, Lr28 gives a 5-10 % yield advantage over the recurrent parent (needs further investigation). An increased number of tillers and spikelets/spike are seen in this combination (results are in press). Lines with Lr28 are less susceptible to powdery mildew.

Lr32. A very effective gene but associated with fast rusting to stem rust. In combination with Sr31 gives 5-10 % yield advantage over recurrent parent (needs further investigation). Increased tillers and spikelets/spike is seen in this combination (results to be published).

Sr31+Lr26+Yr9+Pm8. Slow leaf senescence and a 10 % yield advantage, but linked to slight red tinge in the grain, and increased susceptibility to powdery mildew.

Lr37. Thermosensitive gene under increased minimum temperature shows susceptibility to brown rust in the seedling stage and under certain background gives susceptibility to yellow rust. Associated with lower incidence of powdery mildew.

Lr44. Fast rusting to stem rust.

Lr45. Tightly linked to pink awn (phenotypical marker) and waxiness in the spike, peduncle, stem, and leaf

Sr27. Tightly linked to the apical claw or club tip to the spike (phenotypic marker). Careful selection for Sr27 results in lines with significant yield potential over the recurrent parents.


HW 1095 Pusa dwarf dicoccum has high yield performance across the Indian zones. [p. 66-67]

K.A. Nayeem and M. Sivasamy.

To improve the lodging resistance in high yielding T. tugidum subsp. dicoccum, an exhaustive program was undertaken at IARI, Wellington, in collaboration with Bhabha Atomic Research Institute, Mumbai. One semidwarf plant with profuse tillering in the M2 was selected and designated as HW 1095.

HW 1095 (Filler) was tested with T. turgidum subsp. dicoccum lines DDK 1025, DDK 1028, DDK 1029, DDK 1030, MACS 2956, MACS 2947, MACS 2961 NP 200 and DDK 1009 using MACS 2846 (T. turgidum subsp. durum) and MACS 2496 (T. aestivum subsp. aestivum) as checks. The results are presented in the Table 2. Across all locations, MACS 2496 (bread wheat) ranked first, followed by HW 1095 (Filler) 40 q/ha. Both lines constituted the first nonsignificant group of entries. The new type HW 1095, MACS 2961, and DDK 1029 were significantly superior to the dicoccum check DDK 1009 at the national level. HW 1095 (Filler) gave the highest grain yield and was first in Karnataka and Maharashtra with 43.3 and 49.1 q/ha, respectively (Table 3). HW 1095 ranked fourth in Gujarat with 29.0 q/ha compared to the dicoccum check DDK 1009 (23.5 q/ha). In Tamil Nadu, HW 1095 yielded 21.6 q/ha. Considering the overall average from three zones, Central, Peninsular, and South, HW 1095 ranked second (40.0 q/ha) and surpassed all dicoccum and durum checks and was equal to the bread wheat check MACS 2496 (40.4 q/ha). The results clearly indicate a high yielding ability with resistance to black (5MS) and brown rust (tMS).


Two Sonalika recombinant lines confirmed transfer of rust-resistance genes Sr24 and Lr24. [p. 68]

K.A. Nayeem and M. Sivasamy.

In 2001, Menon and Tomar successfully transferred the tightly liked genes Sr24 + Lr24 from A. elongatum into several Indian cultivars by the backcross method. The presence of the genes was confirmed at DWR, Flowerdale, Shimla. Two recombinant lines, HW 2001 and HW 2001-A, were inoculated with all the virulent pathotypes of black, brown, and yellow rust. We postulated total resistance to leaf rust for the tightly linked genes, however the most virulent races of black rust, 62G29, 62G29-1, and 37G79, were virulent on Sr24 (Table 4). Thus, only Lr24 is very effective for brown rus in our investigation. HW 2001 and HW 2001-A are sister lines differing only in glume color (Table 5). HW 2001 is brown and HW 2001-A is white glumed. HW 2001 has been released as the cultivar Sonak for the state of Haryana.

Table 4. Seedling and adult-plant reaction at Directorate of Wheat Research, Shimla, to different wheat rusts.

   Brown rust isolates  Black rust isolates  Yellow rust isolates
 1RS  42.1R 63-1  21R 31-1  21R 55  62G29  62G29-1  37G79  7G11  46S103  46S 119  46S10
 Sonalika  1P3  3+  1P0; 1P3  1P0; 1P2  2+  2  X  2-  3+  3C  --
 HW 2001  1P2  0;  0;  0;  3+  3+  3  2  3+  3C  --
 HW 2001A  0;  ;  ;  0;          3+  3+  ;
 Sr24 + Lr24  0;  ;  ;1  0;  2  2  0;  2  3+  3+  --
 Recurrent parent/backcross line  New line  Gene(s) present  Reaction to rust
 Brown  Black  Yellow
 Sonalika  --  --  80S  60S  60S
 Sonalika*5//TR 380-14*7/3 Ag#14  HW 2001  Sr24 + Lr24  F  40S  60S