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Drought and high temperature are two major factors limiting maize productivity in sub-Saharan Africa. An increase in temperature above 30 • C reduces yield by 1% under optimal rain-fed condition and by 1.7% under drought stress (DS) and up to 40% under combined drought and heat stress (DSHTS). Approaches that improve performance under the two stresses are essential to sustain productivity. The objectives of this study were to (i) assess the extent of variation in tolerance to DSHTS from among the existing best drought tolerant (DT) hybrids; (ii) examine the response patterns of the hybrids to DSHTS; (iii) identify traits that contributed to better performance under DSHTS; and (iv) select the best hybrids with tolerance to DSHTS stress. We evaluated 40 DT hybrids under DSHTS, DS, and well-watered (WW) conditions for three years. Highly significant (p < 0.001) differences were found among hybrids for grain yield and other traits. Moderately to low repeatability values were detected for grain yield under DS (0.63) and under DSHTS (0.48). Grain yield under DS was not correlated with grain yield under DSHTS (r = 0.29; p = 0.06), but it was correlated with grain yield under WW (r = 0.74; p < 0.001). Grain yield was strongly correlated with ears per plant, ear and pant aspects, days to anthesis and silking under both DS and DSHTS. Tassel blast accounted for 28% of the yield reduction under DSHTS. The top five DT hybrids produced 9 to 26% more grain yields than the best commercial hybrid. Three hybrids produced high grain yields under DTHTS and DS as well as under WW. These hybrids will be tested further in collaboration with partners for possible release.

The management of the fall armyworm Spodoptera frugiperda in maize field necessitates the use a big quantities of insecticides and sometimes the use of multiple types and formulations of chemicals. The use of insecticides in crops is associated with environmental risks and health hazards to both producers and consumers. This study was designed to evaluate the residue of 11 insecticides that were used to control high population of the fall armyworm in maize field in Mokwa, Nigeria. Maize and soil samples were collected from an experimental field to investigate the residue level using high performance liquid chromatography (HPLC, Agilent Technologies, Santa Clara, CA, USA) analysis techniques. Results revealed the presence of five insecticide compounds (Cypermethrin, Deltamethrin, Lambda-Cyhalothrin, Permethrin, and Chorpyrifos) in soil samples with possible adverse effects on soil born organisms and other non-targeted species. In contrast, no residue was found in maize stems and seeds. From these results, we conclude that the treated maize remains safe for consumption and the producers may not get any serious risk of contamination from the chemical control of the fall armyworm.

RESEARCHM aize (Zea mays L.) and other cereals like sorghum [Sorghum bicolor (L.) Moench] and pearl millet [Pennisetum glaucum (L.) R. Br.] are the major staple food crops for millions of people in sub-Saharan Africa. Striga hermonthica (Del.) Benth has been recognized as one of the most destructive parasitic weeds, with its haustorial cells penetrating roots of maize and the other cereals to derive the resources for its growth and development (Parker and Riches, 1993). Since the 1980s, maize production in West and Central Africa has expanded considerably into the savannas, which are high-production zones, where this endemic obligate root hemiparasite poses a serious threat to maize cultivation (Ejeta, 2007). The area infested with S. hermonthica and its negative impact continue to increase because of diverse parasite seed dispersal mechanisms, including contaminated crop seeds, animals, farm implements, wind, and surface water (Berner et al., 1995;Ejeta, 2007). Climate change may further increase the geographic distribution and invasive potential of S. hermonthica, as habitats suitable for its growth might expand (Mohamed et al., 2007). Growth and yields of maize are adversely affected by the withdrawal of water, nutrients, and assimilates by this root parasite from the host to sustain its development (Gurney et al., 1999), causing yield losses that can reportedly reach up to 100% in severely infested smallholder farmer fields in Africa (Kim et al., 2002;Ejeta, 2007).Many control methods, including hand pulling, crop rotation, trap and catch crops, and the use of herbicides and N fertilizer,

Marker-assisted recurrent selection (MARS) is a breeding method used to accumulate favorable alleles that for example confer tolerance to drought in inbred lines from several genomic regions within a single population. A bi-parental cross formed from two parents that combine resistance to Striga hermonthica with drought tolerance, which was improved through MARS, was used to assess changes in the frequency of favorable alleles and its impact on inbred line improvement. A total of 200 testcrosses of randomly selected S1 lines derived from the original (C0) and advanced selection cycles of this bi-parental population, were evaluated under drought stress (DS) and well-watered (WW) conditions at Ikenne and under artificial Striga infestation at Abuja and Mokwa in Nigeria in 2014 and 2015. Also, 60 randomly selected S1 lines each derived from the four cycles (C0, C1, C2, C3) were genotyped with 233 SNP markers using KASP assay. The results showed that the frequency of favorable alleles increased with MARS in the bi-parental population with none of the markers showing fixation. The gain in grain yield was not significant under DS condition due to the combined effect of DS and armyworm infestation in 2015. Because the parents used for developing the bi-parental cross combined tolerance to drought with resistance to Striga, improvement in grain yield under DS did not result in undesirable changes in resistance to the parasite in the bi-parental maize population improved through MARS. MARS increased the mean number of combinations of favorable alleles in S1 lines from 114 in C0 to 124 in C3. The level of heterozygosity decreased by 15%, while homozygosity increased by 13% due to the loss of some genotypes in the population. This study demonstrated the effectiveness of MARS in increasing the frequency of favorable alleles for tolerance to drought without disrupting the level of resistance to Striga in a bi-parental population targeted as a source of improved maize inbred lines.

Striga hermonthica and drought are the major stresses limiting maize yields in sub‐Saharan Africa. The search for diverse maize lines’ tolerance to drought and resistance to S. hermonthica (DTSTHR) is very crucial for yield improvement in areas affected by the two stresses. Understanding the genetic diversity among the lines is important to develop cultivars resistant to S. hermonthica and tolerant to drought. The lines were developed from biparental crosses of drought‐tolerant and Striga‐resistant lines. A total of 128 DTSTHR maize lines were characterized using single‐nucleotide polymorphism (SNP) markers. Results of the cluster analysis based on 3297 SNP markers showed four distinct groups consistent with the pedigrees of the lines. Furthermore, model‐based analysis also formed the same groups of the DTSTHR lines. Integrating the pedigree information with combining ability and the SNP analyses may provide defined heterotic groups for maize improvement work in West and Central Africa. These results also help breeders to utilize DTSTHR lines present at IITA for developing biparental crosses without disrupting the heterotic groups they have established in their breeding programmes.

Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe Striga infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers’ lands. Diverse methods have been proposed for Striga management; however, host plant resistance is considered the most effective and affordable to small-scale famers. Thus, conducting a genome-wide association study to identify quantitative trait nucleotides controlling S. hermonthica resistance and mining of relevant candidate genes will expedite the improvement of Striga resistance breeding through marker-assisted breeding. For this study, 150 diverse maize inbred lines were evaluated under Striga infested and non-infested conditions for two years and genotyped using the genotyping-by-sequencing platform. Heritability estimates of Striga damage ratings, emerged Striga plants and grain yield, hereafter referred to as Striga resistance-related traits, were high under Striga infested condition. The mixed linear model (MLM) identified thirty SNPs associated with the three Striga resistance-related traits based on the multi-locus approaches (mrMLM, FASTmrMLM, FASTmrEMMA and pLARmEB). These SNPs explained up to 14% of the total phenotypic variation. Under non-infested condition, four SNPs were associated with grain yield, and these SNPs explained up to 17% of the total phenotypic variation. Gene annotation of significant SNPs identified candidate genes (Leucine-rich repeats, putative disease resistance protein and VQ proteins) with functions related to plant growth, development, and defense mechanisms. The marker-effect prediction was able to identify alleles responsible for predicting high yield and low Striga damage rating in the breeding panel. This study provides valuable insight for marker validation and deployment for Striga resistance breeding in maize.

Aims: To evaluate genetic variability of five soybean genotypes, and assess genotype × environment effect on seed yield and yield related traits. Study Design: Split-plot, replicated three times. Genotypes were fixed effect while plots (main 60 m² and subplot 12 m²) were random effects. The sub-plot consists of 4 rows 5 m long with 60 cm and 10 cm inter and intra-row spacing. A strain of Rhizobium japonicum was used for inoculation at a rate of 10 g per kg of soybean seed using a sugary solution in 2009. Inoculation was not carried out due to the assumption that the field had the remnant of inoculum effect in 2010. All the recommended soybean agronomic practices were equally applied. Number of days to 50% flowering was recorded on plot basis when almost half of the sub-plot flowers. Ten plants were randomly selected on plot basis to quantify these traits: Plant height was measured as from ground surface to the base of meri-stem of the mother plant. Number of branches was computed as an average count of branches per plant. Leaf area was computed using Iamauti [12] empirical relationship. The first pod height was measured at full bloom. Number of seeds per pod was counted at physiological Research ArticleAmerican Journal of Experimental Agriculture, 3(4): 977-987, 2013 978 maturity of the crop. 100-seed weight was determined randomly from a seed bulk using a digital weighing machine. Seed yield was quantified after harvest and converted into kg/hectare. Results: The effect of genotype (G), environment (E) and G × E interactions on pod number per plant; plant height, first pod height, number of branches per plant, leaf area, number of days to 50% flowering and seed yield were found significant at P=0.05. The highest mean seed yield was obtained from TGx 1937-1F (0.98 t/ha). Beside TGx 1740-2F, TGx 1904-6F and Soja were significantly higher than NA 5009 RG in all environments for seed yield. TGx 1937-1F was an intermediate maturing and best in terms of number of pods per plant, number of branches per plant, and leaf area. Correlation coefficient for seed yield showed significant association with days to 50% flowering and leaf area. Conclusion: The best genotype for seed yield across the environments was TGx 1937-1F and TGx 1740-2F, TGx1904-6F and Soja were intermediate and NA 5009 RG was the least. Thus, partitioning G × E into adaptability and phenotypic stability will positively address the information gap on association of traits to yield.