Increasing Crop Productivity in the West African Savannas: Experiences from northern Nigeria

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Increasing Crop Productivity in the West

African Savannas: Experiences from

northern Nigeria

A.Y. KamaraSavanna Systems

Agronomist

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Outline

1. Biophysical constraints in the West African Savannas

2. Research to provide technological solutions to the

constraints

3. Highlights of some impacts on beneficiaries of

research activities

4. Emerging issues to address in the future

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West Africa agroecological zones

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Agroecological zones in Nigeria

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Savanna Production Constraints

Parasitic weed infestation of cereal and legume

fields

Poor soil fertility

Drought

Poor access to inputs (seeds, agro-chemicals)

Crop pests and diseases

Poor crop management

Ineffective extension systems

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Production Constraints continued

Poor access to information

Low access to animal feeds

Dysfunctional market

Post-harvest losses

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Highlights of biophysical constraints

Striga effect on sorghum

Striga effect on maize

Striga effect on cowpea

Striga effect on rice

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Alectra effect on cowpea

Striga effect on cowpea Drought effect on maize

Drought effect on soybean


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Poor soil fertility

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Research to identify and disseminate

technological solutions to the identified

constraints-some examples Exploiting compatible genotype X fertilizer interactions

for different crops

Matching crops to soils and environments (e.g. maize

variety X planting date interactions in the savannas)

Integrating crop management practices to control pests

in cowpea

Assessing farm-level impact of cropping systems on

parasitic weeds and grain yields of component crops

Adapting improved crop varieties to farmer

circumstances (e.g cowpea)

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Influence of phosphorus application on growth and yield of soybean genotypes

2362 1468 2732 285922331041

P-levels

1993

Miringa (NGS) Azir (SS)

P-levels

Variety 0 20 40 0 20 40

TGX-1485-1D 1028 2114 2098 1368 2579 2401

TGX-1904 6F 1002 2306 2737 1380 2786 2727

TGX- 1830-20E 1037 1974 1299 2728 2652

TGX-1448-2E 1099 2519 2641 1824 2835 3656

Mean

SED 56.6 56.6 56.6 394 394 394

2362 1468 2732 285922331041

P-levels

1993


P-levels

Variety 0 20 40 0 20 40

TGX-1485-1D 1028 2114 2098 1368 2579 2401

TGX-1904 6F 1002 2306 2737 1380 2786 2727

TGX- 1830-20E 1037 1974 1299 2728 2652

TGX-1448-2E 1099 2519 2641 1824 2835 3656

Mean

SED 56.6 56.6 56.6 394 394 394

2362 1468 2732 285922331041

P-levels

1993


P-levels

Variety 0 20 40 0 20 40

TGX-1485-1D 1028 2114 2098 1368 2579 2401

TGX-1904 6F 1002 2306 2737 1380 2786 2727

TGX- 1830-20E 1037 1974 1299 2728 2652

TGX-1448-2E 1099 2519 2641 1824 2835 3656

Mean

SED 56.6 56.6 56.6 394 394 394

Kamara, et al. (2007). Archives of Agronomy and Soil Science, 53(5):539-552.

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There was no significant

interaction effect between N

and P fertilizer on grain yield

and yield components

Nitrogen fertilizer had no

significant effect on grain

yield and yield attributes.

Application of P fertilizer

increased yield and yield

components

No significant yield

difference between 20 and

40 kg of P fertilizer ha-1

0 N, 0 P

20kg P/ha,0N

20 P, 20 kg N/ha40 kg P/ha, 20 N

Soybean response to N and P

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Performance of drought-tolerant Maize under three N levels in soils of the West African Savannas

Kamara et al (2005). Experimental Agriculture, (Cambridge) 41(2): 199-212

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Stay green trait under 30kg N/ha

Drought-tolerant maize

cultivars performed better

than or similar to varieties

selected for low-N tolerance

Selection for tolerance to

drought may confer tolerance

to low-nitrogen stress

High grain yield under severe

N stress was associated with

stay green ratings, increased

number of ears per plant,

reduced days to silking and

reduced ASI

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Effect of N fertilization on Strigadamage of maize genotypes N levels (kg/ha)

0 30 60 120

Variety Striga rating (1-9)*

8331-1-1 8.3 6.8 7.0 6.2

9022-13STR 6.7 5.0 4.0 3.2

ACR 97 TZL COMP1-W 4.7 3.8 4.3 3.3

IWDC2 SYN F2 6.0 4.7 4.2 3.0

TZB-SR 6.3 5.3 4.8 4.5

TZL COMP1 SYN-W 4.5 4.3 3.5 3.3

TZL COMP1 SYN-Y 5.3 4.8 4.7 3.5

TZL COMP1-W C6 F2 4.2 4.5 4.3 3.5

Zea-dplo 5.3 3.7 4.2 3.5

Mean 5.7 4.8 4.6 3.7

SED N levels

SED N levels x variety

0.25

0.74

*1 = no damage, 9 = 100% firing of maize leaves

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Nitrogen and cultivar effect on grain yield of maize under natural infestation with Striga Nitrogen levels (kg ha

-1)

0 30 60 120 Mean

Variety Grain yield kg ha-1

8331-1-1 538.9 1297.4 1596.2 3171.1 1650.9

9022-13STR 1396.0 2594.2 2653.2 4667.3 2827.7

ACR 97 TZL COMP1-W 1465.2 2005.4 3650.4 4253.6 2843.6

IWDC2 SYN F2 1139.0 2050.7 2458.9 4567.7 2554.1

TZB-SR 828.8 2114.0 1853.1 3105.6 1975.4

TZL COMP1 SYN-W 1452.7 2313.1 2514.8 3981.7 2565.6

TZL COMP1 SYN-Y 1984.5 1597.0 3349.3 3702.0 2658.2

TZL COMP1-W C6 F2 2417.1 2816.7 38.26.1 4336.4 3349.1

Zea-dplo 1754.1 2004.9 2847.0 4826.3 2858.1

Mean 1441.8 2088.2 2749.9 4068.0

SED L x N 187.32**

SED L x V 280.98**

SED L x N x V 561.96

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Effect of maize varieties and N fertilization on grain

yield, Striga emergence and damage score

Grain yield of all varieties

increased with increasing

rates of N

Striga count and damage scores

were more reduced on resistant

verieties compared with

susceptible varieties even at the

same N level

Grain yield was 85% higher at 60

kg N ha-1 and 144% higher at 120

kg N ha-1 than without added N

Application of 60-120 kg N ha-1 to

Striga resistant or tolerant maize

varieties may reduce damage and

increase grain yield

60 kg N/ha 60 kg N/ha

30 kg N/ha 30 kg N/ha

Kamara et al (2009) Archives of Agronomy and Soil Science; 55(2):125-145

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Performance of improved cowpea varieties under conditions of natural infestation of Striga gesnerioides

Grain yield (kg/ha) Grain yield (kg/ha)

Variety Damboa Tilla Mean Damboa Tilla Mean

Borno brown 513.2 995.3 754.2 1458.3 1833.3 1645.83

IT89KD-288 1121.3 988.0 1054.7 1277.8 1333.3 1305.56

IT90K-277-2 739.3 1091.7 915.5 1236.1 1611.1 1423.61

IT90K-82-2 1013.8 971.1 992.4 1069.4 1166.7 1118.06

IT97K-499-35 1164.9 1296.0 1230.5 1986.1 2666.7 2326.39

IT97K-568-18 574.1 983.9 779.0 875.0 1000.0 937.5

TVX-3236 424.2 969.8 697.0 1222.2 1305.6 1263.89

Mean 793.0 1042.2 1303.6 1559.5

SED (location)

SED (year)

SED (variety)

SED (location x variety)

56.14

56.14

105.04

79.40

101.79

101.79

190.43

269.32

Kamara et al. (2008). International Journal of Pest Management, 54 (3): 189-195.

Fodder yield (kg/ha)

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Reaction of different cowpea cultivars to

Striga gesnerioides Some improved varieties,

reported previously to be

resistant were found to

support moderate levels of

emerged Striga

Suggesting that there may be

a different race of Striga in the

zone

Two varieties, IT97K-499-35

and IT90K-82-2 were

confirmed to be resistant to

Striga

Yield gain from IT97K-499-35

over the local variety was over

78%

Susceptible varieties

Resistant varieties

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Planting Date and Cultivar

effects on Grain Yield in Dry

Land Maize ProductionPlanting Date Variety

Grain Yield (kg/ha)

29 June TZB-SR 3800.7 TZE COMP4 C3 3853.7 TZEE-W 4230.2 13 July TZB-SR 3169.8 TZE-COMP4-C3 3309.7 TZEE-W 3758.9 21 July TZBSR 2269.4 TZE COMP4 C3 2600.6 TZEE-W 3510.6 28 July TZB-SR 1889.4 TZE COMP4 C3 2158.4 TZEE-W 2778.0

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Key findings Delaying planting generally reduce yield and yield

components

In Sudan savanna, planting of maize on July 21 and July

28 reduced grain yield by 19 and 28.5%.

No significant interaction between cultivars and planting

date

The extra-early maturing cultivar, 95 TZEE-W, produced

highest grain yield at all planting dates

To reduce risk of drought stress, we recommend that

extra-early maturing maize cultivars should be planted in

the Sudan savanna between last week of June and the

first week of July.Kamara et al. (2009). Agronomy Journal, 101(1):91-98.]

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Integrating planting date with insecticide spraying regimes to manage insect pest of cowpea

Kamara et al. (2009) (Submitted to International Journal of Pest Management)

133.0SED (P x S)

111.2SED (Plant date)

638.91331.01049.567.6107.7August 15

556.91237.1690.4180.1119.8August 9

Planting date

719.51520.11189.687.780.6August 21

Variety

54.3SED (Variety)

76.7SED (Spray)

108.6SED (S x V)

Spray levels

Mean3210Treatment

1362.8976.5111.8102.7Mean

697.21409.91090.7165.2123.1IT89KD - 391

579.71315.6862.458.482.3IT89KD - 288

133.0SED (P x S)

111.2SED (Plant date)

638.91331.01049.567.6107.7August 15

556.91237.1690.4180.1119.8August 9

Planting date

719.51520.11189.687.780.6August 21

Variety

54.3SED (Variety)

76.7SED (Spray)

108.6SED (S x V)

Spray levels

Mean3210Treatment

1362.8976.5111.8102.7Mean

697.21409.91090.7165.2123.1IT89KD - 391

579.71315.6862.458.482.3IT89KD - 288

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Key findings No significant difference in insect pest population and grain yield

when insecticides was applied once each at bud initiation,

flowering, and podding and when applied once each at flowering

and podding stages

Yield of the medium maturing variety IT89KD-391 was significantly

higher when planted on August 15 and sprayed two times than

when planted on the other dates

Yield of the indeterminate late-maturing variety ITKD89-288 was

higher when planted on August 9 and sprayed three times

Early and medium maturing cowpea varieties should therefore be

planted in mid August and sprayed two times

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Putting research into use

Development of strong partnerships (e.g critical role

of partners in participatory agronomic research)

The use of participatory approaches

Strengthening of community based organisations

Production for the market

Gender mainstreaming

Use of research knowledge and proven

technologies for innovation

25

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A linear approach

Research

Extension

Farmer

26

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Knowledge generation

Build farmers’ capacity to source, evaluate

and apply information in decision-making

Putting knowledge into use (innovation)

Information markets

StakeholdersPartnersInnovationplatforms

27

Supply

Demand

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Training-PREA

Technical

backstopping

Training

Training

Exchange visitsExtension material

PREA

Participatory Research and Extension Approach

PROSAB

IITA

BOSADP

UNIMAID

Training

End seasonevaluation

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No o

f household

s involv

ed

Time

On-station trials – breeding, plant screening, etc

Mother trials (PROSAB)

On-farm research – variety trials, management practices

Farmer Groups

Lead farmer trials, local seed production,

Farmer testing and learning, adoption/adaptation

Input and output marketing

Scaling out

Farmer-to-farmer extension

Further farmer testing,

adoption, adaptation

Pre

20042004-5 2006-7 2007-8

PROSAB’s development approach

KnowledgePartnerships PREA Strong CBOs Gender

29

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Participatory evaluation of

improved cowpea cultivars in the

Guinea and Sudan savanna

zones of north east Nigeria

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On-farm performance of some cowpea varieties

35831162Farmer variety

40551435IT89KD-288SS

42161897IT89KD-391

42391742IT97K-499-35

269192SED

209128SED


SGS

NGS

AEZ

194333SED


44861841IT89KD-391

48471519IT89KD-288

35091346IT97K-499-35

32011258IT89KD-391

34541143IT89KD-288

Fodder (kg/ha)Grain yield (kg/ha)Variety


40551435IT89KD-288SS

42161897IT89KD-391

42391742IT97K-499-35

269192SED

209128SED


SGS

NGS

AEZ

194333SED


44861841IT89KD-391

48471519IT89KD-288

35091346IT97K-499-35

32011258IT89KD-391

34541143IT89KD-288

Fodder (kg/ha)Grain yield (kg/ha)Variety

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Marginal returns averaged over two years in the NGS and SS ($ ha-1)

-100

0

100

200

300

400

500

600

700

IT9

8K

-13

1-2

IT9

0K

-27

7-2

IT8

9K

D-3

91

IT9

3K

-45

2-1

IT9

7K

-49

9-3

5

IT9

7K

-56

8-1

8

IT8

9K

D-2

88

Bo

rno

Bro

wn

Ka

nn

an

ad

o

Bro

wn

IT9

8K

-13

1-2

IT9

0K

-27

7-2

IT8

9K

D-3

91

IT9

3K

-45

2-1

IT9

7K

-49

9-3

5

IT9

7K

-56

8-1

8

IT8

9K

D-2

88

Bo

rno

Bro

wn

Ka

nn

an

ad

o

Bro

wn

NGS SS

Varieties in each AEZ

Ma

rgin

al

retu

rn f

or

sp

ray

ing

($

pe

r h

a)

Two sprays

One spray

No spray

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Cowpea evaluation criteria

Production

Early maturity

Good for relay cropping

High yield

Pest resistance

Striga tolerant

Utilisation

Large grain size

Colour (brown for market)

Good fodder value

High market value

Cooking time

Taste

Post harvest pest resistance

Kamara et al, (2009) Archives of Agronomy and Soil Science, In Press

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Participatory evaluation - cowpeas 3=best or highest, 2=average, 1=worst or lowest

Evaluation criteria 288 391 568-

18

131-1 B Brown K Brown

Production criteria

Early maturity 2.4 3.0 2.9 2.8 1.1 1.7

Good for relay cropping 3.0 3.0 1.2 1.1 3.0 3.0

High yield 2.6 2.6 2.8 2.9 2.0 2.3

Pest resistance 1.8 1.6 1.9 1.4 1.8 1.7

Striga tolerant 2.0 1.0 1.8 1.9 1.1 1.1

Utilisation criteria

Large seed size 2.6 3.0 1.8 1.6 2.9 3.0

Brown colour 1.4 2.9 2.8 3.0 3.0 3.0

Good fodder value 2.4 1.3 1.3 1.6 2.6 2.6

High market value 2.6 1.7 2.1 2.1 2.9 3.0

Cooking time/taste 2.8 2.4 2.7 2.6 2.3 2.3

Total score 23.6 22.4 21.2 21.0 22.6 23.7

Rank 2 4 5 6 3 1

Number of groups evaluating 5 7 9 8 8 9

% intending to plant 64% 30% 44% 49% 45% 100%

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Cereal-legume rotation

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On-farm performance of maize in rotation systems (NGS and SGS)

Crop history

Ecological

zone

2006 2007 Yield

(kg/ ha)Striga/ha

NGS FC FC 2490 208493

FC TZECOMP5 2794 239684

TGx1448 TZECOMP5 3309 149954

S.E. 239 45554

SGS FC TZECOMP3DT 1911 164012

TGx1448 TZECOMP3DT 2986 102221

FC TZL COMP1W 2789 211902

TGx1448 TZL COMP1W 3213 72824

FC FC 2292 155720

S.E 122. 42319

Crop history

Ecological

zone

200 Yield

(kg/ ha)Striga/ha

NGS FC FC 2490 208493

FC TZECOMP5 2794 239684

TGx1448 TZECOMP5 3309 149954

S.E. 239 45554

SGS FC TZECOMP3DT 1911 164012

TGx1448 TZECOMP3DT 2986 102221

FC TZL COMP1W 2789 211902

TGx1448 TZL COMP1W 3213 72824

FC FC 2292 155720

S.E 122. 42319

Crop historyCrop history

Ecological Ecological Yield

(kg/ ha)

Yield

(kg/ ha)Striga/haStriga/ha

NGSNGS FCFC FCFC 24902490 208493208493

FCFC TZECOMP5TZECOMP5 27942794 239684239684

TGx1448TGx1448 TZECOMP5TZECOMP5 33093309 149954149954

S.E.S.E. 239239 4555445554

SGSSGS FCFC TZECOMP3DTTZECOMP3DT 19111911 164012164012

TGx1448TGx1448 TZECOMP3DTTZECOMP3DT 29862986 102221102221

FCFC TZL COMP1WTZL COMP1W 27892789 211902211902

TGx1448TGx1448 TZL COMP1WTZL COMP1W 32133213 7282472824

FCFC FCFC 22922292 155720155720

S.ES.E 122.122. 4231942319

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Mean ISC-Soybean maize yields (kg per ha) ISC

Year 1 Soybean Y2-maize

FP Year 1 Maize Year 2 maize

Increase in yield % increase

SS (n=6) Year 1 975 1125 Year 2 1913 1425 Maize equivalents

1

Year 1 1176 1125 51 5% Year 2 1913 1425 488 34% Overall 3088 2550 538 21%

NGS (n=49) Year 1 1935 2077 Year 2 3295 1298 Maize equivalents

1


SGS (n=57) Year 1 2088 2395 Year 2 3104 1948 Maize equivalents

1


Kamara et. al (2008) Experimental Agriculture 44(3):349-364

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Seed systems

Up to 1988 certified seed produced, processed and

distributed by ADPs

– Largely discontinued due to funding problems

– Some ADPs contracting with farmer outgrowers to produce

certified seed,

– NASC producing some foundation seed

Few functional seed companies, concentrating

largely on hybrid varieties,

Few new varieties of other crops available and

mainly local varieties were grown.

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Strategy to promote community seed

production Farmer groups select

credible individuals to

produce seed

Training provided in seed

production and marketing

Community seed

producers linked to seed

companies and

encouraged to form seed

associations/cooperatives

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Yield and value of seed crop produced in 2007 (Naira)

100%7,699,674246,354151Total

0%30010003Fodder crop

30%2,310,6305501574240Soybean

5%413,3481589840324Groundnuts

6%485,5681798433623Cowpeas

3%262,2004370011884Sorghum

6%486,8802864037617Rice

49%3,740,74885017254940Maize

% of

total

Total-all

producers

Mean value of

seed per

producer

Mean

quantity

kg

No of

producers

100%7,699,674246,354151Total

0%30010003Fodder crop

30%2,310,6305501574240Soybean

5%413,3481589840324Groundnuts

6%485,5681798433623Cowpeas

3%262,2004370011884Sorghum

6%486,8802864037617Rice

49%3,740,74885017254940Maize

% of

total

Total-all

producers

Mean value of

seed per

producer

Mean

quantity

kg

No of

producers

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Seed disposals during 2008

50%

19%

10%

4%

4%

4%

4%

1%

Amount sold for seed

Amount consumed as food

Amount sold for food

Amount retained for own use as seed

Amount given away as food

Amount given away for seed

Total quantity remaining in store

Credit retrieval

0% 10% 20% 30% 40% 50% 60%

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Lead farmer crop yields 2005-8 (tonnes/ha)

Crop Baseline 2005 2006 2007 2008

Maize 1.0 1.4 3.0 3.2 3.2

Rice 2.6 - 3.3 3.0 3.2

Sorghum 1.0 2.0 2.2 1.5 2.6

Cowpeas 0.4 0.6 1.3 0.8 1.4

Groundnuts 1.0 1.0 1.9 1.7 1.9

Soybean 0 2.5 2.7 2.3 2.4

Some impact

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Adopting farmers crop yields 2008 tonnes/ ha

Crop

Main or Sole crop Relay crop

Imp-

roved

Local %

Increase

Imp-

roved

Local %

Inc-

rease

Maize 2.4 1.4 77%

Rice 2.7 1.6 70%

Sorghum 2.1 1.5 38%

Cowpea 2.0 1.4 40% 0.5 0.5 0%

G nuts 2.6 1.4 93%

Soybean 2.1

46

Some impact

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Adoption (PASS – 2008)

200976 % for soybean

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Emerging issues Shortages of labour and draught

animals

– Zero tillage, conservation

agriculture

Scaling out

– GIS, modelling

Long term effect of cereal-legume

rotations

– Beneficial effects beyond N

Integrating improved crop varieties

into cropping systems

Utilizing crop management x

genotype interactions to manage

the effect of climate change

Measured grain yield (kg ha-1

)

0 1000 2000 3000 4000 5000

Sim

ula

ted g

rain

yie

ld (

kg h

a-1

)

0

1000

2000

3000

4000

5000

TZB-SR (Azir 2007)

RMSE = 1269d = 0.8298

R 2 = 0.9944

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Emerging issues (modelling)

Planting date

Jun-29 Jul-13 Jul-21 Jul28

Gra

in y

ield

(kg h

a-1

)

0

1000

2000

3000

4000

5000

Measured

Simulated

TZE COMP4C2 (Azir 2007)

RMSE =1269

d = 0.8298

R2 = 0.9949

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Planting date

Jun-29 Jul-13 Jul-21 Jul28

Gra

in y

ield

(kg h

a-1

)

0

1000

2000

3000

4000

5000

Measured

Simulated

TZB-SR (Azir 2007)

RMSE =1269

d = 0.8298

R2 = 0.9949

Emerging issues (modelling)

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Emerging issues The CERES-Maize model of DSSAT was used to evaluate the

performance of maize planted at different dates in Sudan savanna

Statistics used in the model were :

-Root mean square error, RMSE

-An index of agreement, d

-R2 value of linear relationships between measured and predicted yields

Results showed that yield values were found near the 1:1 line and the d and R2 values were very significant

Obtained RMSE, d and R2 values showed that DSSAT could be widely used to accurately predict maize performance at different planting dates in the savannas

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Influence of tillage systems on the performance of some cowpea varieties in a Sudano-Sahelian ecology after three years of cultivation

No significant interaction between tillage practices and cowpea varieties after 3 years

There were significant differences among tillage practices after 3 years but not in the first 2 years

There were significant differences among cowpea varieties after 3 years but not in the first 2 years

The beneficial effects of zero or reduced tillage may be more visible after many years of continuous practices

A long-term tillage research is envisioned

Variety Zero Flat Ridge Mean

IT89KD-391

IT90K-277-2

IT97K-461-4

IT97K-499-35

IT98K-131-2

IT98K-506-1

Mean

SED Tillage

SED Variety

SED T x V

1035.0

1448.8

1302.1

1072.5

1605.4

1200.4

1277.4

103.16**

145.89*

252.68 (NS)

1105.4

1915.0

1564.2

1633.8

1375.8

1307.9

1483.7

875.4

1307.9

998.3

860.4

1121.3

1037.5

1033.5

1005.3

1557.2

1288.1

1188.9

1367.5

1181.9

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Effect of tillage systems on cowpea

performance Zero tillage

produced higher

biomass than flat

tillage

Flat tillage produced

higher biomass than

ridge tillage

Ridge tillage

produced less

biomass and earlier

maturity

FLAT TILLAGE

ZERO TILLAGE

RIDGE TILLAGE

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Grain yield response of semi-determinate and

indeterminate cowpea genotypes relay-cropped under

maize with different plant populationsGrain yield

(kg/ha)

Cowpea genotype

Cropping system TZE Comp. 5 W IT97K-499-35 IT89KD-288

53333 maize plants/ha



Cowpea sole crop

SED Cropping system (df=12)

SED Cowpea genotype (df=12)

SED Cropping system x cowpea genotype (df=12)

5562.9

3405.1

2167.5

698.9

1326.7

1528.9

1375.34

97.42

63.69

120.09

871.1

1017.8

1130.0

1282.0

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Effect of cropping systems on cowpea genotype

IT97K-499-35

Sole

IT97K-499-35 53333

maize

plants/ha

26666

maize

plants/ha17777

maize

plants/ha

Sole

IT89KD-288

53333

maize

plants/ha

Cropping system x cowpea genotype interaction was significant indicating differential response of the cowpea varieties to different cropping systems

At 53333 maize plants/ha, grain yield of IT97K-499-35 was reduced by up to 50%

Grain yield of IT89KD-288 was reduced by up to 32%

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Response of contrasting soybean

varieties to different plant populations

Higher grain yields

were obtained at

higher population

than lower

populations

266666 plant/ha

666666 plants/ha

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Grain yield (kg/ha) of four soybean varieties grown at different plant populations in Nigerian northern Guinea savanna

Plant population ha-1

Variety 266666 333333 533333 666666 Mean

TGX 1448-2E 2501.8 2739.4 3355.9 3924.1 3130.3

TGX 1904-6F 3289.9 2615.1 3780.1 4436.1 3530.3

TGX 1830-20E 2166.2 2119.7 2533.5 2680.1 2374.9

TGX 1835-10E 1046.2 1010.3 1616.7 1723.8 1349.2

Mean 2251 2121.1 2821.5 3191

SED Population 80.0720

SED Variety

SED P x V

80.0720

160.14

Late maturing varieties produced higher grain yield than the early maturing ones

Significantly higher grain yields were obtained at 533,333 and 666,666 plants per ha

Despite the additional seed cost planting soybean at high populations of 533,333 and 666,666 per ha was more profitable than planting at lower populations

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Some practical lessons learnt

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Thank you

Technology

Increasing Crop Productivity in the West African Savannas: Experiences from northern Nigeria