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a International Institute of Tropical Agriculture (IITA), c/o L.W. Lambourn (UK) Ltd., Carolyn House, 26 Dingwall Rd., Croydon, CR9 3EE, UK
b Obafemi Awolowo, Ile-Ife, Nigeria
c INRAB/CRAN-INA, Benin Republic
d IRAD, Yaounde, Cameroon
e SARI, Tamale, Ghana
f INERA, Bobo–Dioulosso, Burkina Faso
* Corresponding author (b.badu-apraku{at}cgiar.org).
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ABSTRACT |
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 TOPNOTES ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Abbreviations: ASI, anthesis-to-silking interval • ATC, average-tester coordinate • CIMMYT, International Maize and Wheat Improvement Center • DAP, days after planting • EPP, number of ears per plant • EV, experimental cultivar • GGE, genotype main effect plus genotype x environment interaction • IITA, International Institute of Tropical Agriculture • MSV, the maize streak virus • PC, principal component • RSVT, Regional Striga Variety Trial • RUVT, Regional Uniform Variety Trial • WAP, weeks after planting • WECAMAN, West and Central Africa Collaborative Maize Research Network • WCA, west and central Africa
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ACKNOWLEDGMENTS |
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NOTES |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Received for publication July 26, 2007.
a International Institute of Tropical Agriculture (IITA), c/o L.W. Lambourn (UK) Ltd., Carolyn House, 26 Dingwall Rd., Croydon, CR9 3EE, UK
b Obafemi Awolowo, Ile-Ife, Nigeria
c INRAB/CRAN-INA, Benin Republic
d IRAD, Yaounde, Cameroon
e SARI, Tamale, Ghana
f INERA, Bobo–Dioulosso, Burkina Faso
* Corresponding author (b.badu-apraku{at}cgiar.org).
Maize (Zea mays L.) production in west and central Africa (WCA) is constrained by the parasitic weed Striga hermonthica (Del.) Benth and recurrent drought. Two early maize populations, TZE-W Pop DT STR C0 (white) and TZE-Y Pop DT STR C0 (yellow), developed from diverse genetic backgrounds, were subjected to three cycles of S1 recurrent selection under artificial Striga infestation. Inbreds and synthetic cultivars were developed from the different cycles of selection. The populations (C0), derived cultivars, and check cultivars were evaluated in 2002 and 2003 under Striga-infested and Striga-free environments in WCA. The objective was to assess the performance of the derived cultivars from the different cycles of selection. Under Striga infestation, ACR 94 TZE Comp5-Y and ACR 94 TZE Comp5-W, which were not from the selection program, were the highest-yielding group (2158 and 2124 kg ha–1, respectively). The second group comprised six products of the selection program, with grain yield ranging from 1806 to 1954 kg ha–1. The third group, with grain yield of 1498 to 1759 kg ha–1 contained mostly Striga-susceptible cultivars and the C0 of the selection program. Under Striga-free conditions, the performance of several cultivars from the selection program was equal to or better than ACR 94 TZE Comp5-Y and ACR 94 TZE Comp5-W. The genotype plus genotype x environment interaction biplot analysis demonstrated that EV DT-Y 2000 STR C1 and TZE-W Pop DT STR C3 from the selection program, along with ACR 94 TZE Comp5-W, had stable grain yield under Striga-infested and noninfested conditions.
Abbreviations: ASI, anthesis-to-silking interval • ATC, average-tester coordinate • CIMMYT, International Maize and Wheat Improvement Center • DAP, days after planting • EPP, number of ears per plant • EV, experimental cultivar • GGE, genotype main effect plus genotype x environment interaction • IITA, International Institute of Tropical Agriculture • MSV, the maize streak virus • PC, principal component • RSVT, Regional Striga Variety Trial • RUVT, Regional Uniform Variety Trial • WAP, weeks after planting • WECAMAN, West and Central Africa Collaborative Maize Research Network • WCA, west and central Africa
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INTRODUCTION |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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In addition to aggravating the effect of Striga infestation, drought per se adversely affects maize growth and production. Annual maize yield loss from drought stress in the savannas of WCA is estimated at 15%, although much higher localized losses may occur in marginal areas in the northern fringes of the savanna where the annual rainfall is below 500 mm and soils are sandy or shallow (Edmeades et al., 1995). Badu-Apraku et al. (2004) compared the performance of 17 early maturing varieties, subjected to induced drought stress and Striga infestation at Ferkéssédougou (Ivory Coast) with their performance under stress-free treatment. Relative to the stress-free treatment, mean grain yield was reduced by 53% under drought stress and by 42% under Striga infestation. Unfortunately, drought occurrence is not predictable and most severely affects grain yield at flowering and grain-filling periods in maize. One strategy to tailor maize to the gradually shortening rainy season to escape drought stress is the development of maize cultivars that produce dry grain in 80 to 85 d (extra-early cultivars) or 90 to 95 d (early cultivars). The early and extra-early cultivars are particularly adapted to the northern fringes of the northern Guinea savanna and the Sudan savanna.
Recognizing the significant negative impact of S. hermonthica infestation and drought on the rapid spread of maize in the northern Guinea savanna and Sudan savanna of WCA, the International Institute of Tropical Agriculture–West and Central Africa Collaborative Maize Research Network (IITA–WECAMAN) Maize Program has emphasized the development of maize source populations and cultivars that combine earliness or extra-earliness with tolerance and/or resistance to the maize streak virus (MSV), S. hermonthica, and drought. In Striga research, tolerance refers to the ability of host plants to withstand the effects of the parasites already attached. A Striga-tolerant genotype germinates and supports as many Striga plants as the susceptible genotype but produces more grain and stover and shows fewer damage symptoms. Resistance describes the ability of a host plant to prevent attachment or reduce the number of parasites attached underground, resulting in reduced Striga emergence (Kim, 1994; Badu-Apraku et al., 2007a). Under Striga-infested conditions, the resistant genotype supports significantly fewer Striga plants and produces a higher yield than a susceptible genotype (Kim, 1994). The IITA–WECAMAN Maize Program has used S1 recurrent selection method, improved artificial field infestation with S. hermonthica, and screening under drought as strategies to develop two early-maturing source populations—TZE-W Pop DT STR (white) and TZE-Y Pop DT STR (yellow)—and several early-maturing cultivars and inbred lines, which combine tolerance to drought with moderate levels of resistance to S. hermonthica and MSV. However, no studies have been conducted to determine the effectiveness of the recurrent selection method in developing high-yielding varieties. The objective of this study was to evaluate the performance of the experimental cultivars (EVs) derived from the different cycles of selection under Striga-infested and noninfested conditions.
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MATERIALS AND METHODS |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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TZi 3 (white) and TZi 25 (yellow), two fixed inbred lines, were the sources of tolerance to S. hermonthica for the two populations. In addition to Striga tolerance, TZi 3 has good levels of resistance to the major maize diseases in WCA. TZi 25 has been found to have a low production of Striga seed-germination stimulant. It has also been reported to be tolerant to S. asiatica in North Carolina (Efron et al., 1988; Ransom et al., 1990). The two inbreds, particularly TZi 25, also support fewer Striga plants than do susceptible inbred lines.
Screening Methodology
The principal screening sites for Striga resistance for the two maize populations, TZE-W Pop DT STR C0 and TZE-Y Pop DT STR C0, were Ferkéssédougou (Ferké) and Sinématialli (Siné) in the Ivory Coast and Mokwa and Abuja in Nigeria (Table 1
). The screening method developed by IITA's Maize Program (Kim, 1991; Kim and Winslow, 1991) was used. The Striga seeds used for artificial infestation were collected from sorghum [Sorghum bicolor (L.) Moench] fields at the end of the previous growing season and mixed with finely sieved sand in the ratio 1:99 by weight. The sand served as the carrier material and provided adequate volume for rapid and uniform infestation. About 5000 germinable Striga seeds were placed in each planting hole on ridges spaced 75 cm apart with 40 cm between the holes. Three maize seeds were placed in the same hole with the Striga seeds. Screening of segregating materials derived from the two source populations was done using 5-m rows with susceptible checks planted at regular intervals of 10 rows. Plots planted to both the segregating materials and the susceptible checks were infested.
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Breeding Methodology
The development of white and yellow drought-tolerant, Striga-resistant early populations was initiated in 1994 in the Ivory Coast. Backcrossing, inbreeding, hybridization, and selection were all used in the program. The details of the procedure used to develop the two populations are presented in Table 2
and also described elsewhere (Badu-Apraku and Fakorede, 2001). The resulting populations after four cycles of random mating were designated TZE-W Pop DT STR C0 (white) and TZE-Y Pop DT STR C0 (yellow).
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Evaluation of Progress
The source populations together with the EVs and synthetic varieties derived from them were evaluated for grain yield performance, Striga resistance, and drought tolerance in three studies. A randomized complete block design with four replications was used in the evaluation trials. Each plot consisted of 2 or 4 rows, each 5 m long, spaced 0.75 m apart. Row and hill spacings were 0.75 and 0.40 m, respectively. Three maize seeds were planted per hole in each trial. The Striga infestation method developed by IITA Maize Program, which ensures uniform Striga infestation with no escapes (Kim, 1991; Kim and Winslow, 1991), was used. Fertilization of the artificially Striga-infested maize field was delayed until about 30 d after planting (DAP). At this stage of plant growth, 30 to 50 kg N ha–1 was applied as 15–15–15 NPK. The actual quantity of NPK applied depended on the fertility level of the soil. It has been observed that low levels of NPK application positively influence high levels of Striga infestation and emergence (Kling et al., 2000). Regular removal of weeds other than Striga was manually done. The maize crop was thinned to two plants per hill about 2 wk after emergence to give a final population density of 66,000 plants ha–1. Observations recorded in the STR evaluation trials included grain yield, ear number, ear rot, husk cover, plant and ear heights, and percentage root and stalk lodging in both infested and noninfested plots. In addition, host plant damage syndrome rating (Kim, 1991) and emerged Striga counts were made at 8 and 10 wk after planting (WAP) in the Striga–infested rows. Striga-tolerant plants normally retain green leaves and exhibit restricted mild purplish chlorosis, with little effect of Striga on ear and stalk development. Highly susceptible plants, on the other hand, show grayish leaf color and leaf scorching after initial leaf wilting. These symptoms are usually accompanied by poor development of stalk and ear, resulting in lodging (Kim, 1991). Although data were collected on several traits, only those on the most important traits are presented. Selection was performed using an index based on several characters (grain yield, Striga damage ratings, Striga emergence counts, ASI, EPP, and plant height) measured under infested and/or noninfested conditions. The variance of Striga counts has been found to increase with the mean, therefore, log transformation [log (counts + 1)] was used to reduce the heterogeneity of variance.
In the first study, seven elite Striga-resistant maize cultivars derived from the S1 recurrent selection program involving the yellow and white source populations (EV DT-Y 2000 STR C1, TZE-W Pop DT STR C3, TZE-Y Pop DT STR C3, TZE-W Pop x 1368 STR C1, TZE-W Pop x 1368 STR S6 F2, EV DT-W 99 STR C0, and EV DT-W 2000 STR C0) were compared with the seven best available Striga-resistant cultivars from other selection programs, a local check (the best available early variety nominated by each national collaborator), and a reference entry (a leading non-Striga-resistant/tolerant early cultivar provided by IITA-WECAMAN) in the Regional Striga Variety Trial–early (RSVT–early) in 2002 (WECAMAN, 2002). The trial, was evaluated at 15 sites in WCA. There were two rows per plot, and one row in each plot was infested artificially with about 5000 germinable S. hermonthica seeds per hole at planting. Except for Striga seed infestation, all management practices for both Striga-infested and noninfested plots were the same. About 40 to 50 kg N ha–1 was split applied at planting and at about 30 DAP. Days to silking and anthesis, plant and ear heights, EPP, and grain yield were determined for both the Striga-infested and noninfested plots. In addition, data were collected on host plant Striga damage score and the number of emerged Striga plants in the Striga-infested plots. Usable data were obtained from 6 of the 15 sites in WCA where the trials were conducted.
The second study comprised 17 elite genotypes evaluated in the Regional Uniform Variety Trials–early (RUVT–early) at 25 sites in WCA in 2002. The genotypes in the trials included TZE-W Pop DT STR C3, TZE-Y Pop DT STR C3, TZE-W Pop x 1368 STR C1, and 2000 Syn WEC derived from TZE-W Pop STR, 11 best available early cultivars from other selection programs, a local check nominated by each trial collaborator (which was the best available cultivar at each evaluation site, and which differed among locations for the trials), and a reference entry contributed by IITA–WECAMAN. The evaluations were conducted under rainfed and Striga-free conditions at all locations. The trials were planted when rainfall was established at each of the test sites. To optimize crop performance at each site, fertilizer application and pest control were performed on the basis of the recommendations for the respective sites in each country. Each plot consisted of four rows; the two center rows within each plot were sampled for grain yield, days to 50% silking, EPP, plant height, ear height, plant stand, number of plants harvested, number of ears harvested, and grain moisture content (%). Grain yield was calculated based on 80% (800 g grain kg–1 ear weight) shelling percentage and adjusted to 150 g kg–1 moisture content. Usable data were returned from only 11 of the 25 sites.
For the two studies described above, analysis of variance was done for each site and thereafter across all sites to determine if genotype x environment (GxE) interaction was significant. Subsequently, the data were subjected to genotype main effect plus genotype x environment interaction (GGE) biplot analysis to decompose the GxE interactions (Yan et al., 2000, 2001). The GGE biplot was used to obtain information on the cultivars that were suitable for Striga-infested and Striga-free environments and to investigate stability of cultivars in the various environments. The analyses were done using GGE biplot, a Windows application that fully automates biplot analysis (Yan, 2001).
The third study involved 280 S1 lines, each extracted from noninbred (S0) plants of C3 of TZE-W Pop DT STR C3 and TZE-Y Pop DT STR C3. The lines from each population were separately evaluated in single 5-m row plots, spaced 0.75 m apart under artificial Striga infestation at Mokwa and Abuja in 2003, using an incomplete block design with two replications. Striga infestation and management practices were as described for the first study. Variance components obtained from the analysis of variance of the S1 data were used to obtain broad-sense heritability (h2) estimates for grain yield and some agronomic traits (Hallauer and Miranda, 1988).
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RESULTS |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The GGE biplots for grain yield of 16 early-maturing maize cultivars evaluated at six locations under Striga infestation are shown in Fig. 1 and 2 ; Fig. 3 and 4 represent biplots under Striga-free conditions. In the GGE biplot display in Fig. 2 and 4, the single-arrow line that passes through the biplot origin and the average environment is referred to as the average-tester axis; this line points to the average environment from the biplot origin. A set of lines, parallel to the double-arrow line, spans the whole range of the entries, dividing them based on their mean performance. Under Striga infestation, the principal component (PC) axis 1 explained 38.2% of total variation, and PC2 explained 27.6%; thus, PC1 and PC2 together explained 65.8% of total variation for yield (Fig. 1 and 2). Under Striga-free conditions, PC1 accounted for 55.8% and PC2 accounted for 21.7%, explaining 77.5% of the total variation (Fig. 3 and 4). These results suggest that the biplot of PC1 and PC2 adequately approximates the environment-centered data. In the polygon view (Fig. 1 and 3), the vertex cultivar in each sector represents the highest-yielding cultivar in the location that falls within that particular sector. (The following discussion refers to the cultivars by the codes listed in Table 3 and all figures.)
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The genotypes are ranked along the average-tester axis, with the arrow pointing to a greater value based on their mean performance across all environments; the double-arrow line separates entries with below-average means from those with above-average means (Fig. 2 and 4). The average yield of the cultivars is approximated by the projections of their markers on the average-tester axis. The stability of the cultivars is measured by their projection onto the (average-tester coordinate [ATC] y axis) single-arrow line. The greater the absolute length of the projection of a cultivar, the less stable it is. Thus, under Striga infestation, KA88, and TZ5W were the most stable cultivars, followed by AC94, EY00, and CHCK. EV97, 99SY, TZF2, TZ5Y, EV00, SYNW, and TZ3W were the most-unstable cultivars. The yield of KA88 was below the general mean grain yield of the genotypes. TZ5W was the highest-yielding cultivar, and EV99 was the lowest-yielding. Under Striga-free conditions, the CHCK, 98SY, and EV99 were the least-stable cultivars and TZF2 was the most stable, followed by TZ3Y. This implies that TZF2 was the highest-yielding and most-stable cultivar under Striga-free conditions. Significantly, Fig. 2 and 4 each indicate environmental groupings, which suggest the possibility of two mega-environments each for the Striga-infested environments (Mokwa, Abuja, and Angaradebou; Nyankpala, Ina, and Garoua) and the Striga-free environments (Abuja, Ina, and Mokwa; Angaradebou, Nyankpala, and Garoua). The absolute length of the projection from the marker of an environment onto the ATC y axis is a measure of its representativeness: the longer the projection, the less representative the environment. Therefore, under Striga infestation, environment Nyankpala was the most representative (it had a near-zero projection on the ATC y axis) but not highly discriminating (it had a small projection onto the ATC x axis). Environments Mokwa, Abuja, and Garoua were discriminating (far away from the origin) but not representative of the average environment (large projection onto the ATC y axis). Environments Angaradebou and Ina were not discriminating (small distance from the origin) but representative (small projection onto the ATC y axis). Under Striga-free conditions, Ina was the most representative environment but not highly discriminating (it had a small projection onto the ATC x axis). Abuja had a small projection onto the ATC x axis but a large projection onto the ATC y axis and was, therefore, discriminating but not representative. The environment Mokwa had a large projection onto ATC x axis and a large projection on to the ATC y axis and was, therefore, discriminating but not representative.
The combined analyses of variance of the RUVT–early revealed significant cultivar and cultivar x location mean squares under rainfed, Striga-free conditions (Table 4 ). The two source populations and PO13 derived from TZE-W Pop DT STR were lower yielding than some of the best available cultivars in WCA under stress-free conditions. Therefore, the real advantage of the new cultivars clearly manifests under Striga-infested conditions. For this set of trials also, locations explained the largest proportion of the total sum of squares, about 87% (data not shown). In contrast, cultivars explained only about 4%, and cultivar x location interactions explained about 11%. For this set of trials, both the PC1 and PC2 were important and explained 52.5% of the yield variation (Fig. 5 and 6 ). The genotype AK93 was the vertex cultivar in five environments: Ina, Nyankpala, Angaradebou, Yendi, and Samanko (Fig. 5). TZ5Y was the highest-yielding genotype at Manga, Saria, Valée du Kou, Mokwa, and Maroua. TZ5W was the vertex genotype at Mokwa and Garoua, whereas 99SY was the vertex genotype at Killisi. TZ5Y was the highest-yielding genotype, whereas 99SY was the lowest (Fig. 6). However, AK93 was quite unstable in performance, whereas TZ5Y was moderately stable. TZ5W and 99SY were also among the most-unstable genotypes. The genotypes CHCK, AC97, HP97, and TZ3Y were relatively stable in grain yield performance; AC97, HP97, and TZ3Y were above average in yield, while CHCK had below-average grain yield. The locations were classified into two groups of five each and a third group containing only one location, Killisi (in Guinea). While the sole location was widely separated from the others, the two groups of five locations each were plotted into similar spaces on the biplot, except that they were on opposite ends of the horizontal line: Mokwa (Nigeria), Garoua, and Maroua (Cameroon), Saria, and Valée du Kou (Burkina Faso) were on the negative end, and Ina and Angaradebou (Benin), Yendi, Manga, and Nyankpala (Ghana) were on the positive end.
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DISCUSSION |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The outstanding performance of ACR 94 TZE Comp5-W and ACR 94 TZE Comp5-Y under Striga infestation and their failure to outyield any of the products from the recurrent selection program under Striga-free conditions are clear indications that the cultivars developed in our breeding program possess the potential to perform well under stress-free conditions. Furthermore, most of the cultivars emanating from the selection program reported in this study had a similar grain yield performance as the reference entry (Kamb 88 Pool 16 DT). In earlier studies by Badu-Apraku et al. (2004), this cultivar, which is drought tolerant but was not intentionally selected for Striga resistance, was among the top-ranking cultivars under Striga infestation. This is not surprising since the cultivar was selected from CIMMYT Pool 16, a moderately Striga tolerant population. In addition, the cultivar is known to show good performance when Striga infestation and drought conditions occur simultaneously (Badu-Apraku et al., 2004).
Differences in the GGE biplot classification of the cultivars in Striga-infested and noninfested environments, an indication of cultivar x Striga infestation interaction, were particularly striking. Under Striga-infested conditions, cultivars ACR 94 TZE Comp5-W, ACR 94 TZE Comp5-Y, and TZE-Y Pop DT STR C3 were identified as the genotypes with the highest grain yield performance in the study. Genotypes in the second group with moderately high grain yield (local check, TZE-W Pop x 1368 STR S6 F2 [set 2], and 2000 Syn WEC) were mostly improved cultivars and populations from this selection program. The third group contained mostly the cultivars with the lowest grain yield performance. Under Striga-free conditions, the check, EV DT 97 STR C1, and EV DT-Y 2000 STR C1 were among the highest-yielding cultivars. Similarly, in the RUVT conducted under Striga-free conditions, several cultivars from the recurrent selection program, such as TZE-Y Pop DT STR C3, TZE-W Pop DT STR C3, and TZE-W Pop x 1368 STR C1 were as high yielding as ACR 94 TZE Comp5-W and ACR 94 TZE Comp5-Y. Clearly, the grouping of the cultivars was greatly influenced by their response to the presence or absence of Striga infestation. In essence, therefore, it could be deduced that the breeding program was effective in developing high yielding, Striga-resistant cultivars. The cultivars, however, could be further improved for grain yield performance as well as Striga resistance.
Inclusion of the local checks in the second group containing the moderately high yielding cultivars could be misleading. In this context, the local checks were the best-available cultivar at each evaluation site, which differs among locations. Because this was a Striga-resistance evaluation trial, the local checks, in most cases, would be the most adapted and best Striga-resistant material. The data presented for local checks are, therefore, not necessarily from one cultivar but the mean of several cultivars. Inclusion of the local checks in the study showed that many of the improved cultivars from the breeding program evaluated in this study performed as well as the best-available cultivars in the national maize programs under both Striga-infested and Striga-free conditions.
Although rainfall was similar at the 11 sites in the first study, Abuja and Mokwa, which were grouped together under Striga-free conditions, were widely separated under Striga infestation. Similarly, Ina and Nyankpala, which were in the same group with Angaradebou and Garoua under Striga-free conditions, were classified into a different group. This suggests that site-specific differences, such as different strains of Striga at the sites, may have accounted for the GxE pattern.
The low-to-moderately high broad-sense heritability estimates as well as high means and ranges of traits in the genetic component analysis in the study suggested that sufficient residual genetic variability still existed in each population to allow continued gain from selection for Striga resistance, especially in TZE-W Pop DT STR. Similar findings were reported by Badu-Apraku (2007) and Badu-Abraku et al. (2007b). It is interesting that the heritability of Striga emergence of TZE-W Pop DT STR C3 was as high as that of Striga damage rating. This finding is in disagreement with the results of Berner et al. (1995) and Akanvou et al. (1997), who reported lower heritability estimates for number of emerged S. hermonthica plants relative to Striga damage. On the contrary, Striga damage rating was found to be more heritable than Striga emergence in TZE-Y Pop DT STR. In this study, epistatic effects were assumed to be absent in estimation of genetic variances. However, since epistasis is purely a statistical description and does not define a physiological function, its presence, whatever the magnitude, will bias downward the estimates of additive genetic variance, hence, narrow-sense heritability (Hallauer and Miranda (1988). Although the presence of epistatic effects could have caused the low heritability estimates obtained in this study, the values compare favorably with those reported even for late-maturing maize germplasm. For example, Kling et al. (2000) reported for TZL Comp 1 h2 estimates of 33% for Striga damage rating scores, 32% for grain yield under Striga infestation, and 14% for Striga emergence counts. Furthermore, Haussmann et al. (2000) reported high estimates of broad-sense heritability for all measured traits in sorghum and attributed these partly to the use of a large number of replications and test locations and improved plot layout. To improve the heritability of grain yield and other measured traits in the two populations, it might be desirable to increase the number of replications and locations so as to increase the accuracy of estimated entry means and thus heritability. The low heritability estimates obtained for Striga emergence counts at 8 and 10 WAP suggest that for fast progress from selection for Striga resistance, it may be advantageous to introgress novel Striga resistance genes into the population.
The two source populations are presently serving as invaluable source germplasm for breeding for combined resistance to S. hermonthica and drought stress in WCA. The national maize programs of the Ivory Coast, Ghana, and Burkina Faso are already making use of the populations and their derived inbreds in breeding for S. hermonthica resistance and drought stress. For example, the national maize program of the Ivory Coast has extracted S6 inbred lines and formed synthetics from TZE-W Pop DT STR and TZE-Y DT STR. The national maize program of Burkina Faso has introgressed genes from selected drought-tolerant and Striga-resistant inbreds derived from the source populations into other breeding populations. Kureh et al. (2004) reported that the Striga-resistant early-maturing cultivars outyielded the farmers' cultivars by 44% for ACR 94 TZE Comp5-W and 33% for EV DT-W 99 STR C0. Both cultivars supported fewer emerged Striga plants and sustained lower Striga damage in 10 on-farm trials conducted in the Striga hermonthica-endemic northern Guinea savanna ecology of Nigeria. Also, the Striga-resistant cultivar, EV DT 97 STR C1, developed in our program from Pool 16 DT x 1368 STR, has been released in Benin following several years of on-farm testing and is being vigorously promoted for adoption by farmers in the Zakpota area of that country (WECAMAN, 2003).
At present, the available maize germplasm in the breeding program has only moderate levels of resistance to S. hermonthica, which is quantitatively inherited, and no cases of immunity have been found (Kim, 1994; Kling et al., 1996). The level of resistance, therefore, is not efficacious for the control of Striga because it allows the parasite to reproduce. As a result, the Striga seed bank would increase each planting season, thus rendering host plant resistance not completely effective. The major challenge at present is to search for unique resistance genes for the maize breeding programs of the subregion. The accession of Zea diploperennis identified at IITA that supports low levels of parasitism by S. hermonthica (Kling et al., 1997, 2000) is a promising source of resistance and a program to map the genes for marker-assisted selection is in progress. Meanwhile, an integrated management approach would be invaluable to reduce the Striga seed bank progressively and maintain it at an acceptable level. There is, therefore, a need to combine host plant resistance with other control methods, such as maize–legume rotation, to ensure long-term productive maize cultivation in the savanna ecology of WCA. Rotation of maize with farmer-acceptable legumes that can stimulate suicidal germination of Striga seed in addition to improving soil productivity is of particular interest. Cowpea [Vigna unguiculata (L.) Walp.], soybean [Glycine max (L.) Merr.], and groundnut (Arachis hypogaea L.) cultivars have been found through several years of on-farm testing in WCA to possess high germination stimulant activity, resulting in increased grain yield, soil productivity, and Striga control (Ariga and Berner, 1995; Lagoke et al., 1997). These legumes are presently being promoted on farm in rotation with the Striga-tolerant early and extra-early maize cultivars developed in our program.
The authors are grateful to the IITA staff and national maize scientists of WECAMAN member countries for the excellent management of the trials reported in this article, and to USAID for financial support. We would also like to thank Professor Manjit Kang for critically reviewing this manuscript. The manuscript has been approved for publication by IITA as IITA/06/JA/16.
All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.
Received for publication July 26, 2007.
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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