Demand-Driven Technologies for Sustainable Maize ... - IITA

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19Table 4. Maize varieties transferred across countries and researchsystems through networking, 1994–2005.Improved varieties Countries adopting varietites Source of varietiesDMR-ESR-Y Cameroon, Mali, Chad, Guinea, Togo IITADMR-ESR-W Bénin, Côte d’Ivoire, Cameroon IITAPool 16 DT Cameroon, Bénin, Togo, Ghana, Côted’Ivoire, Senegal, Tchad, Burkina FasoWECAMAN / IITA/CIMMYTEV DT 97 STRC 1Bénin, Togo,and Chad IITA-WECAMANACR 94 TZE COMP Nigeria, Côte d’Ivoire, MaliIITA5-WObantapaCameroon, Bénin, Togo, Ghana, Côte Ghanad’Ivoire, Senegal, Tchad, Burkina Faso,Nigeria, Mali, Guinea, Zimbabwe, Swaziland,Ethiopia, Mozambique.TZESR-W x Gua Togo, Côte d’Ivoire, NigeriaIITA-WECAMAN314DMR-ESR-W QPM Côte d’Ivoire, Togo.95 TZEE-Y 1Nigeria, Senegal, Togo, Tchad IITA-WECAMAN95 TZEE-W 1Nigeria, Senegal, Togo IITA-WECAMAN99 TZEE-Y STR C 0Nigeria, Bénin, Togo IITA-WECAMAN2000 Syn EE-W Bénin, Nigeria IITA-WECAMANImproved cultural practices exchanged among WECAMANcountries through networking, 1994–2005.Culturalpractice1. Increased plant populationfor higher grain yield of earlyand extra-early varieties2. Earlier date of fertilizerapplication (top dressing) forincreased yield of early andextra-early varieties3. Use of maize–legumerotation for improved soil fertilityand/or Striga control andmaize grain yieldCountry adoptingtechnologyGhana, BéninTogo, Cameroon,Burkina Faso, Nigeria, Mali, Côted’Ivoire, Senegal.Bénin, Togo,Burkina Faso,Ghana, Cameroon, Senegal,Nigeria, Mali,Bénin, Ghana,Cameroon, Mali, Burkina Faso,Nigeria, TogoSource oftechnologyCameroonNigeriaBéninCameroonBéninBénin,Ghana Cameroon
20DiscussionResults of the analyses carried out in this study clearly demonstratethat the network approach was effective in tackling the formidableconstraints of maize production in the subregion of WCA. WECAMANhas three key partners: the donor agencies, the NARS collaborators,and the IARCs which served as the facilitators. One of the objectives ofthe present study was to evaluate the performance of each partner overthe 20-year period of existence of the Network. Although the fundsmade available for network activities fl uctuated over the years, theywere released faithfully and promptly by the donors and distributedappropriately by the Steering Committee through the NetworkCoordinator. It is often said, “Who pays the piper dictates the tune.”This does not seem applicable in the case of WECAMAN activities.The donors gave the Network a free hand to conduct research onthe identifi ed constraints of maize production in the subregion. This ishighly commendable, and is perhaps one of the factors that contributedto the success of the Network.The analyses presented herein also showed clearly that the NARScollaborators worked hard to make WECAMAN achieve much of thepurpose for which it was put in place. Although initially, USAID wasthe only donor agency, UNDP and IFAD provided additional fundingthrough the Africa Maize Stress (AMS) Project to combat some specifi cconstraints to maize production in the subregion. Specifi cally, theproject’s goal was to develop resistance or tolerance to Striga, low soilN, drought, and stem borers. In addition, Nippon Foundation has beenfunding the Quality Protein Maize (QPM) Project in the subregion. Withthe addition of the AMS and QPM projects, WECAMAN expandedthe coverage of its activities from 8 to 11 countries and from theGuinea savanna to all agroecologies in the countries.As noted in earlier reports, the Network developed and transferredto farmers many technologies that have contributed greatly to themaize revolution in the subregion. Among these are early and extraearlymaturing varieties that have made the cultivation of maize possiblein ecologies traditionally thought to be unsuitable. Availability of thesevarieties has greatly facilitated the production of green maize throughoutthe year in most ecological zones of WCA countries. Earliness and extraearlinessare a drought-escaping mechanism that is effective only ifterminal drought occurs towards the end of the season. Unfortunately,the recurrent droughts of WCA are unpredictable and are, therefore, besttackled with drought tolerant varieties. Striga is a major constraint in muchof the savannas while low soil-N and stem borers are major constraints inmost ecologies. The AMS project provided funds to develop screeningsites for resistance or tolerance to all of these constraints, thus facilitatingthe creation of working groups to better solve breeding problems and
Page 2 and 3: iDemand-Driven Technologies forSust
Page 4 and 5: iiiContentsPrefacePréfaceForewordA
Page 6 and 7: vAssessment of Striga infestation i
Page 8 and 9: viiPrefaceThe West and Central Afri
Page 10 and 11: ixendosperm maize varieties, 95 TZE
Page 12 and 13: Les agriculteurs de la savane guin
Page 14 and 15: xiiiForewordMaize (Zea mays L) is o
Page 16 and 17: xvAvant proposLe maïs (Zea mays L)
Page 18 and 19: xviiFifth Biennial West and Central
Page 20 and 21: xixNigeria26 Abdullahi, Y.M. NAERLS
Page 22: 1Section1Breeding, SeedSystems and
Page 25 and 26: 4skills of the scientists and impro
Page 27 and 28: 6collaborating scientists. This is
Page 29 and 30: 8fi ndings to their peers. They are
Page 31 and 32: 10Figure 3. Funds received by indiv
Page 33 and 34: 12Percentage PercentageYearFigure 5
Page 35 and 36: 14Figure 9. Coefficient of variatio
Page 37 and 38: 16Figure 15. Total maize grain prod
Page 39: 18Table 2. Capacity Building of NAR
Page 43 and 44: 22the Lead Country Concept was not
Page 45 and 46: 24Badu-Apraku, B., M.A.B. Fakorede,
Page 47 and 48: 26et des lignées dotées de résis
Page 49 and 50: 28Overview of the strategy for deve
Page 51 and 52: 30Table 1. Characteristics of extra
Page 53 and 54: 32Table 2. Performance of extra-ear
Page 55 and 56: 34Table 3. cont’dInbredlineParent
Page 57 and 58: 36different germplasm and for placi
Page 59 and 60: 38Figure 1. Clustering of 35 extra-
Page 61 and 62: 40Table 4. Number of inbred lines i
Page 63 and 64: 42M’Boob, S.S., 1986. A regional
Page 65 and 66: 44sur la performance de leurs hybri
Page 67 and 68: 46Table 1. Mean grain yield (Mg ha
Page 69 and 70: 48Table 2. Means for grain yield an
Page 71 and 72: 50Table 4. Estimates of GCA effects
Page 73 and 74: 52employed to exploit non-additive
Page 75 and 76: 54deux traitements de sol (O, T). L
Page 77 and 78: 56Table 1. Characteristic of 15 par
Page 79 and 80: 58Table 4. Diallel analysis of vari
Page 81 and 82: 60Table 6. Number of adapted x adap
Page 83 and 84: 62ConclusionThe results of this stu
Page 85 and 86: 64Combining ability of diverse maiz
Page 87 and 88: 66S. hermonthica and S. asiatica. Y
Page 89 and 90: 68Table 2.Mean squares of grain yie
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70Table 4. Mean squares of grain yi
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72Table 5. Estimates of general com
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74Table 7. Estimates of general com
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76yield under Striga infestation. T
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78Kim, S.K., V.O. Adetimirin and A.
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80Maize accounts for between 30 and
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82VII, XI and V that had grain yiel
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84Table 3. Inter- and intra-cluster
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86interest, including early, medium
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88IntroductionThe multi-environment
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90Table 1: Sums of squares (SS) exp
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922Table 3: Average proportion of t
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94genotypes within the target sets.
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96residual interaction matrix has b
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98Effects of farmers’ seed source
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100known. The objective of this stu
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102AFigure 1. (A) Percentage seeds
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104zFigure 5. Mean days to 50% silk
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106ReferenceAsiedu, E.A., Twumasi-A
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108Mexique et les USA. Dans les ann
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110In collaboration with the Intern
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112to farmers. Recommendations had
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114maize, the highest grain yield a
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116Figure 1. Trend of land area cul
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118ConclusionIn conclusion, the Ins
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120Valencia, J.A. and S.A. Breth. u
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122
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124chimique. L’effet relatif de l
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126Figure 1: Rainfall pattern in Sa
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128Percentage PercentageFigure 2: M
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130Table 2. Effect of organic mater
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132Yield increase and relative yiel
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134Table 5. Relative grain and stov
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136Dudal, R., 2002. Forty years of
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138Residual benefits of soybean gen
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140The cultivation of leguminous cr
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142(IITA), natural fallow and a lat
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144on exchangeable Ca, exchangeable
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146Table 4. Rotation† and fertili
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152in the top 0-15 cm layer and als
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154inoculation and nitrogen fertili
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156RésuméLes besoins du maïs en
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158Table 1. Monthly distribution an
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160was applied about 5 cm deep, mad
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162Table 3. Effects of legumes and
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164Figure 3: Grain yield of maize a
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166ConclusionFrom the results of th
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168Tarawali, G., 1991. The residual
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170la variété de maïs tolérant
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172It is necessary to validate that
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174Table 2. Effects of previous cro
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176of cowpea, than in the farmers
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178AcknowledgementsThe authors than
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180Potential of drought-tolerant ma
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182potential in comparison to the t
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184ha -1 . Fields were planted on J
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186Table 3. Means for days to silki
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188DiscussionThe observed effects o
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190the yield potential of the genot
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192Edmeades, G.O., J. Bolanos, M. H
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194Genotypic variation of soybean f
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1962002). Therefore, high BNF in so
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198Experimental layout, planting an
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200At 8 WAP, fi ve plants were rand
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202Figure 1. Relationships between
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204signifi cant correlation (P ≤
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206Table 4. Total N accumulation (k
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208Table 5. Total P in grain (kg ha
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210Table 6. Grain yield (kg ha -1 )
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212colonization in previous RP plot
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214(Table 8). However, within speci
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216maize-after-soybean plots over t
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218The observed trends in grain yie
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220in soybean than in maize grain d
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222IITA (International Institute of
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224Snedecor G.W., Cochran G. (1980)
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226irrigated conditions in the Sahe
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228Figure 1: Variation des tempéra
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230L’espérance de la matrice de
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232Tableau 3. Moyennes des caractè
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234Tableau 6. Table d’ANOVA du mo
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236Tableau 8. Table d’ANOVA du mo
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238seconde stratégie répond bien
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240
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242
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244RésuméDes enquêtes sur les ma
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246Field surveysField surveys were
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248Table 1.PathogensMean incidence
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250Table 3. Correlation matrix betw
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252Table 8. Correlation matrix betw
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254Signifi cant correlations were f
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256NCRE, 1994. Annual Report Camero
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258faibles réactions qui indiquent
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260(b) A no-choice situation. In th
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262Table 2. Ovipositional responses
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264Table 5. Larval feeding response
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266Figure 1. Profiles of colonizing
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268on moderately resistant and susc
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270CCE, (Commission des Communauté
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272RésuméLe Striga est une contra
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274the baseline for environmental m
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276Table 1. Percentage of crop and
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278(Emechebe et al. 1991) may have
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280ReferencesAnonymous, 1996. Stati
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282The use of spicy plant oils agai
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284The objectives of the present st
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286% mortality100908070605040302010
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288saturated atmosphere in the dark
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290(Gyllenhal) in stored chick-peas
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292intercropped with groundnut, and
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294du Striga. Les observations ont
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296Tableau 1. Incidence des plants
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298Tableau 4. Contd.LibellésUnité
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300soudure. Le traitement maïs ass
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302Herbicide resistant maize: a nov
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304Figure 1. Striga-prone areas in
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306developed herbicide resistant li
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308geo-referenced data from a farm-
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310Table 2: Grain yield and Striga
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312AcknowledgementsThis research wa
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314Effects of maize-cowpea intercro
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316In Cameroon, maize is commonly i
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318Table 1. Relative abundance and
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320Table 4. Maize stem borers’ st
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322were the predominant predator sp
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324on insect infestation and the as
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326Kareiva, P.M., 1983. Finding and
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328
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330impliquées dans la production d
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332Table 1: Scores assigned for fac
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334Table 2. Characteristics of wome
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336Table 5. Spearman rank correlati
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338farmers are given the appropriat
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340RésuméUne étude combinée de
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342ZamfaraStateKatsinaStateFigure 1
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344Table 1. Relative radii of the f
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346Table 4. Number of crops grown i
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348Figure 3: Concentric circles ref
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350No. Maize farmersFigure 4: Facto
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352Table 8. Trend of farmers rating
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354Gyasi, K.O, L.N. Abateisina, T.
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356Bénin. Seed quality was determi
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358Tableau 1. Moyenne des différen
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36070000Nombre de plants à I’hec
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362ISTA (International Seed Testing
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364Togolese Institute of Agricultur
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366variété améliorée et un tém
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368Tableau 2. Cycle des différente
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370Tableau 6. Rendement des variét
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372Tableau 7. Evolution des rendeme
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374300000250000Maïs Mais purMaïs/
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376- Au niveau des tests associatio
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378à base de maïs dans le Nord de
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380Two States (Kaduna and Katsina),
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382Table 1. Percentage of farm hous
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384Table 3. Socio-economic factors
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386AcknowledgementThe authors are g
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388Unexploited yield and profitabil
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390and input combinations. A number
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392The production function in equat
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394host of socio-economic and insti
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396Table 3. Frequency distribution
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398The adjusted R-squared value and
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400Assefa, A., 1995. Analysis of pr
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402Socio-economics of community-bas
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404seed at affordable price to farm
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406Table 1. Socio-economic profiles
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408Table 3. Average labor costs and
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410ReferencesAhmed, B., 1994. Econo
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412communautaire de semences de ma
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414producing QPM seed at the commun
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416Table 1. Cost elements (N/ha) in
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418Table 3. Gross income (N/ha) fro
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420Conclusion and RecommendationsTh
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422Effets de la rotation et de l’
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424Tableau 1. Caractéristiques phy
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426Tableau 3. Composition chimique
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428Figure 1. Evolution des rendemen
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430Maïs-grain (kg.ha -1 )Maïs-gra
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432Tableau 9. Successions culturale
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434Maïs-grain (kg.ha -1 )350030002
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436
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438
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440ont été analysés pour leur co
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442A=(M’-M) x 100/M + A o(1)where
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444Table 1. Physicochemical composi
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446Table 2. Steeping time and varie
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448germination. In general, the pea
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450after cooking of maize malted fl
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452Marero, L. M., E.M. Payuma, A.R.
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454Effects of wheat flour replaceme
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456considerably and this is attribu
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458resulting products (fl ours, dou
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460Table 1. Physico-chemical proper
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462CMS 8806 CMS 8704CMS 9015 CMS 85
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46439.8We ight(g)39.639.439.2390%10
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466He, H. and R.C. Hoseney, 1991. D
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468Adaptation et utilisation de var
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470Figure 1. Distribution mensuelle
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472chaque semaine. L’essai a dur
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474Resultats et DiscussionsTests ag
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476Tableau 2. Proportions des ingr
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478Tableau 5. Composition de l’al
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480Tableau 7. Coûts financiers de
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482des demandeurs à payer et est d
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484ConclusionNotre étude montre qu
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486
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488
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490Breeding, Seed Production and St
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4921. Propose approaches/innovation
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494identifi cation, planning and im
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496
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