1. Maize yield gap analysis at local level: Nkoranza and Savelugu municipalities, Ghana
IMAGINE meeting
25 April 2017, Marloes van Loon
Contributors: Wim Paas, Samuel Adjei-Nsiah, Clement Akosten ,Pytrik Reidsma, Martin van Ittersum, Michiel van Dijk, Tom Morley, Katrien Descheemaeker, Roel Jongeneel
Pictures taken by: Wim, Marloes, Samuel

2. Introduction
The agricultural production in Sub-Saharan Africa has to triple to fulfil the food demand in 2050 (Van Ittersum et al 2016)
Challenging in Ghana, as the productivity of food crops has been very variable and stagnating in many areas over the recent years (MOFA, 2010)
Intensification of current production is needed
Yield gap estimations and explanations could help
(Van Ittersum et al 2016)

3. Introduction
Fertilization (timing and amount of fertilizer) is the factor which is largely explaining the yield gap for various crops in Africa (Beza et al. 2017)
But depends among others on the soil fertility status (Chapoto et al. 2015)
Risks related to fertilizer purchase (Sileshi et al. 2010; Agyare et al. 2014)
Land preparation (i.e. tillage, area per crop, previous crop, crop residue management) and soil fertility also play a major role in explaining yield gaps of various crops in Africa (Fermont et al. 2009; Beza et al. 2017)

4. Objectives
The objectives: Use different methods to study maize yield gaps in Ghana. By assessing the impact of crop management, household and soil factors on maize yields and yield gaps, based on production ecology concepts
Maize production by smallholder farmers
Case study sites: Nkoranza and Savelugu municipalities in Ghana

5. Description study sites
Nkoranza
Savelugu
Seasons
Minor: Sept. - Jan.
Major: April - August
Main: July – Nov.

6. Data: household survey 2015, 2016 seasons
Nkoranza
Savelugu
Seasons
Minor, major
1 main
Household members 5 11
TLU
0.6
4.4
Farm area (ha)
3.3
4.7
Plot distance home (km)
2.0
0.9
Tractor ownership (%) 16
Rental of land (%) 33 2
Fertilizer use (%) 78 64
Manure use (%) 3
Herbicide use (%) 99
100
Use of improved seeds (%) 10
High herbicide use: they use Atrazine, Nicogan, Nicoplus, Glyphosate

7. M&M: household & village survey
Household survey (2015, 2016 season)
90 households, 15 per community representing different wealth statuses
Information on: farm characteristics and socio- economic conditions
Determination maize yields
Soil samples

8. Methodology Take actual maize yield from household survey
Take highest farmer yield to estimate technology yield gap
Take water-limited potential yield from GYGA
Calculate yield gaps
Test which factors significantly affected maize yield:
Correlations
PCA
Multiple linear regression

9. Maize yields, and maize yield gaps
Average farmer yield = 1.9 ton ha-1
Average farmer yield = 2.6 ton ha-1
Average farmer yield = 1.8 ton ha-1 Yw
80%
3.0
ton ha-1
72%
69%
Yhf
6.5
ton ha-1
3.2
ton ha-1 Ya
20%
28%
31%
Average farmer yield = 1.9 ton ha-1
Average farmer yield = 2.6 ton ha-1
73%
81%
5.2
ton ha-1
5.9
ton ha-1
27%
19%

10. Yield per farm over the different seasons
No correlation between yields of 2015 and 2016 season

11. Significant positive correlation between planting density and yield
Nkoranza: Crop management factors affecting maize yield, PCA and correlations
Nkoranza minor season 2016
Nkoranza minor season 2015
Nkoranza major season 2016
Significant positive correlation between planting density and yield
Correlations (lumped 2015, 2016)
Yield
Planting density
0.42
Plot area
-0.15
Labour hrs weeding
0.12
Distance to homestead
-0.07
N input
K input
0.04
Only significant correlations are shown
Correlations (lumped 2015, 2016)
N input
Plot area
K input
0.5
Distance to homestead
0.31

12. Savelugu: Crop management factors affecting maize yield, PCA and correlations
Significant positive correlations between planting density, N input, plot distance to homestead and yield
Significant negative correlation between labour hours weeding and yield
 Correlations (lumped 2015, 2016)
Yield
Planting density
0.56
Labour hrs weeding
-0.4
N input
0.34
Distance to homestead
0.24
Plot area
0.19
Sowing date
-0.18
K input
0.17
Only significant correlations are shown
 Correlations (lumped 2015, 2016)
N input
K input
Labour hrs weeding
Plot distance to homestead
0.79
Plot area
-0.24
-0.26
Sowing date
0.26
-0.43
Planting density
0.28
0.22
-0.37
-0.35

13. Only planting density had a significant effect on yield
Crop management factors affecting maize yield, multiple linear regression
Positive or negative effect on yield and P-value
Only significant factors are shown
Nkoranza
Savelugu
Multiple linear regression
Minor season
Major season- 2016
Minor season- 2016
Main season
Main season
Planting density -
0.58 +
<0.01
0.87
0.01
Only planting density had a significant effect on yield

14. Planting density versus yield, regression
Significant relation planting density - yield

15. N input versus yield, regression
No relation N input - yield

16. Nutrient management affecting yield
Sandy and sandy loam soils
Soil factors + fertilizer input as predictor variables
Significant factors and interactions are shown
Nkoranza
Savelugu
Multiple linear regression
Minor season
Major season- 2016
Minor season- 2016
Main season
Main season
Base saturation +
0.92 -
0.08
0.93
0.41
0.09
CEC Ca
0.17
0.01
0.78
0.04
CEC Na
0.90
0.03
0.81
0.36
% Clay
0.56
0.47
0.63 Mn
0.29 x X
% Silt
0.20
0.13
0.12
0.02
Base saturation x CEC Na
No relation N input - yield

17. Household factors, correlations
Only significant correlations are shown
 Nkoranza (2015, 2016 lumped)
Yield
Information received
0.17
Average yrs of household education
0.16
Available family labour
0.12
% maize area
0.09
Farm area
-0.08
TLU
-0.05
Average yrs of farm experience
0.04
People in household
0.00
 Nkoranza (2015, 2016 lumped)
Farm area
People
Family labour
Education
% maize area
-0.34
Farm experience
-0.25
0.23
TLU
-0.23
Information received
0.18
No clear effect of household factors on yield
Only significant correlations are shown
 Savelugu (2015, 2016 lumped)
Yield
TLU
0.25
Average yrs of farm experience
-0.16
% maize area
0.13
Farm area
-0.10
Available family labour
-0.09
Average yrs of household education
-0.06
Information received
0.06
People
0.00
 Savelugu (2015, 2016 lumped)
People
Farm area
Farm experience
Family labour
0.57
% maize area
-0.28
-0.22
Animal
0.52
0.26
0.22
Information received
-0.23

18. Household factors affecting maize yield
Nkoranza
Savelugu
Multiple linear regression
Minor season
Major season- 2016
Minor season- 2016
Main season
Main season
Average yrs of household education -
0.18
0.93
0.62 +
0.52
0.90
Dummy variable no education
0.00
0.29
0.23
0.89
0.57
Information received
0.36
0.05
0.16
0.31
0.54
Dummy variable no information received
0.45
0.28
0.03 X x
Machine value class: high value class (compared to medium value class)
0.73
0.04
0.17
Machine value class: low value class (compared to medium value class)
0.82
0.61
0.78
0.48
Average household farm experience
0.84
0.77
0.08
No clear effect of household factors on yield

19. Discussion, part 1
No relation yield farmers obtain in one season and other season
Might cause uncertainty household factors affecting maize yield
Large yield gaps: largest part is technology yield gap
Planting density largest effect on yield

20. Discussion, part 2: fertilizer input
Unclear relationship between yield an fertilizer input
Expected positive effect
Small yield range and low yields
Soil improvements needed before getting a response (low SOM)
Acid soil
Limitation micronutrients (Zn, Fe)
Low amount of fertilizer applied
Blanket fertilizer recommendations

21. Discussion, part 3: seeding
Don’t use modern maize varieties, and reuse of improved varieties
Drought tolerant maize
Large spread in planting date
Availability tractors

22. Conclusion
Large maize yield gaps in both Nkoranza and Savelugu, technology yield gap is largest part of total yield gap
Factors affecting yield differ highly between seasons, and locations
Planting density seemed to influence yield most
Expected effect of fertilizer not found

23. Thank you for your attention
Questions?
Contributors data collection: Wim, Samuel, Clement
Pictures taken by: Wim, Marloes, Samuel

24. Description study sites
Nkoranza
Savelugu
Seasons
Minor: Sept. - Jan.
Major: April - August
Main: July – Nov.

25. Yield reported, yield measured bar plots
Nkoranza
Savelugu
Minor season
Major season- 2016
Minor season- 2016
Main season
Main season
Average standard deviation per plot from measured yields (kg/ha)
498
573
330
396
522
Average coefficient of variation per plot from measured yields (%) 29 21 19
Relation measured vs observed yields, P-value paired t-test
0.00
Correlation measured vs observed yields, R2
0.15
0.03
0.17
Yield reported, yield measured bar plots

26. Nkoranza
Savelugu
Minor season
Major season- 2016
Minor season- 2016
Main season
Main season
Soil characteristics
Mean SE pH
5.83d
0.03
6.09c
0.07
6.19c
0.08
7.10a
0.02
6.95b
0.04
Organic C (%)
0.84a
0.87a
0.82a
0.51b
0.01
N (%)
0.08a
0.00
0.07a
0.05b
Organic matter (%)
1.45a
1.49a
0.05
1.41a
0.06
0.88b
CEC Ca (cmol kg-1)
4.92a
0.09
4.10bc
0.20
4.12bc
0.21
4.41b
3.88c
0.23
CEC Mg (cmol kg-1)
1.30a
1.16ab
1.19ab
1.10b
1.09b
CEC K (cmol kg-1)
0.20c
0.45a
0.40ab
0.37ab
0.32b
CEC Na (cmol kg-1)
0.11b
0.21a
0.19a
0.14b
T.E.B. (cmol kg-1)
6.52a
0.12
5.96bc
0.17
5.88bc
0.19
6.05ab
0.13
5.46c
0.31
Exchange acidity (cmol kg-1)
0.25a
0.20b
0.19b
0.12c
0.11c
eCEC (cmol kg-1)
6.83a
6.19b
0.18
6.10bc
6.15b
5.56c
Base saturation (%)
95.6c
0.1
96.3b
0.2
96.6b
97.8a
97.4a
P (ppm)
16.8a
0.7
15.1ab
1.0
13.8b
1.2
6.7c
6.2c
0.5
K (ppm)
76.2b
2.7
125.1a
4.2
Sand (%)
68.5bc
69.4b
71.5a
0.8
66.3d
0.4
67.6cd
Clay (%)
10.3bc
10.0cd
9.6d
0.3
12.2a
10.9b
Silt (%)
21.1a
20.6a
18.9b
21.7a
21.8a
Fe (mg kg-1)
7.28c
0.29
2.93c
0.41
6.78c
0.49
105.11a
1.00
71.61b
6.73
Mn (mg kg-1)
2.47c
2.17c
0.15
1.94c
0.16
49.14a
1.30
30.58b
3.50
Zn (mg kg-1)
0.29c
0.27c
0.26c
4.93a
0.11
3.12b
0.34
Cu (mg kg-1)
1.62a
1.26b
1.15b
0.53c
0.41c

27. M&M: household & village survey
Household survey (2015, 2016 season)
90 households, 15 per community representing different wealth statuses
Information on: farm characteristics and socio- economic conditions
Determination maize yields
Soil samples
Village survey (2015 season)
Focus group discussion
Information on e.g. water resources, governmental intervention projects, outside investments by NGOs, functioning cooperatives, commodity prices and local wages