CCAFS Science Meeting presentation by Dave Harris - "Limits to agricultural development from a smallholder household perspective: The profitability of rainfed crop production and how it affects intensification."

1. Limits to agricultural development from a smallholder household perspective:
The profitability of rainfed crop production and how it affects intensification.
Dave Harris
ICRISAT Nairobi

2. We all concentrate on increasing the productivity of (rainfed) crops.
However, it is the net benefit (profitability) from investments (cash, labour,
time, etc) that may be important to a farming household and could influence
adoption of new technologies.

3. Net returns* are expressed on a ‘per hectare’ basis.
However, poverty levels are generally expressed on a per person, per day basis, e.g.
the widely used threshold value of “$ 1 per person per day”
*’income’, ‘gross margins’ and ‘net returns’ in this analysis include monetized benefits such as food
consumed directly.

4. The amount of land required for any household to achieve a given value of income
per person from crop production depends on:
The profitability of any cropping enterprise, and;
The number of people in the household.
To achieve $1 / person / day, the relationship is:
y = (365/x) * n
Where:
y = land required per HH (hectares)
x = net returns from the enterprise ($ / ha)
n = number of persons in the HH

5. Land per HH required to give $ 1 per person per day for a given net return (per hectare)
from crop production, for various HH sizes.
(Note: one season per year)
50
45
6 persons / HH
Land per HH (hectares)
40
35
30 Relation holds for ANY crop, combination of crops or ANY
land-based enterprise.
25
4 persons / HH
20
15
2 persons /HH
10
5
1 person / HH
0
0 50 100 150 200 250 300 350 400
Net returns from crop production ($ per hectare per year)

6. How much can new agricultural
technology raise income?

7. Literature survey - criteria for inclusion in the analysis:
1. Published since 2000.
2. Rainfed cropping – no irrigation.
3. Gross margins (benefits minus variable costs) reported for entire
enterprise (or data available to calculate).
4. Cost of labour (including family labour) included.
5. A comparison of a ‘base’ case (farmers’ current practice or an
experimental control) and one or more improved technologies.

8. Sixty-nine cases reported in the literature since 2000
Including the following crops:
Barley, blackgram, chickpea, cocoa, coffee, common bean, cotton, cowpea,
fodder, groundnut, lentil, maize, mungbean, mustard, niger, pearl millet, peas,
pineapple, rapeseed, rice, sesame, sorghum, soybean, sunflower, toria, vanilla,
vetch, wheat, yam.
And technologies:
Tillage, rotations, fallows, intercropping, relay cropping, agroforestry,
fertilizers, soil amendments, foliar sprays, pest- and disease control, new
varieties, etc.
From the following countries:
Burkina Faso, Benin, Cameroon, India, Kenya, Malawi, Niger, Nigeria, Sudan,
Syria, Tanzania, Turkey, Uganda, Zambia, Zimbabwe.

9. Effect of improved technology on rainfed crop profitability
$ per hectare per season
800
700
600
500
USD/ha/season
400
300
200
100
0
-100
-200
Improved Current
From: Dave Harris and Alastair Orr (2012).
Is Rainfed Agriculture Really a Pathway from
Poverty? Agricultural Systems (submitted).

10. Median value for the ‘base’ case = $84 per hectare per season
Median value for the ‘improved’ case = $268 per hectare per season (220 % increase)
Median value for the B:C ratio of the improved technologies = 2.1
Upper limit around $700 per hectare per season?

11. 80 % of farms in SSA are now below 2 ha (Nagayets, 2005).

12. Land per HH required to give $ 1 per person per day for a given net return ($268 ha-1)
from crop production, for various HH sizes and countries.
(Note: one season per year)
40
HH=20
35 Mali (20.3 HH-1)
13.3 ha
Land per HH (hectares)
30 Ethiopia (6-4 HH-1 )
HH=15 2.4 ha
Nigeria (9.4 HH-1)
25 8.4 ha
Malawi (4.8 HH-1)
20 HH=10 1.05 ha
15
HH=6
10 HH=4
5 HH=2
HH=1
0
0 100 200 300 400 500 600 700
Net returns from crop production ($ per hectare per year)

13. There are not many rural households that
are entirely dependent on their own
agricultural production.

14. Land required to produce an individual income of $1 per day, as a function of net returns from
crop production, for two proportions of the contribution of crop production to total household
income. Values calculated using Equation 1 and assuming household size = 5.

15. ‘ DIRT POOR: The key to tackling
hunger in Africa is enriching its soil.
The big debate is about how to do
it.’
29 MARCH 2012 | VOL 483 | NATURE | 525
“Eneless Beyadi appears through a forest of maize clutching an armful of
vegetables and flashing a broad smile. Beyadi cultivates about half a hectare of
plots in the village of Nankhunda, high on the Zomba plateau in southern
Malawi. She gets up at 4 a.m. every day to tend her gardens, as she lovingly
calls them, before heading off to teach at a school.”

16. Intensification?
Depends on where you are and who you
are (or what you have).

17. 80
Response to increasing
70 net returns - four
contrasting sites
HHs with $1/person/day (%)
60
50
Limuru
40
Matopos
30 Makueni
Kaffrine
20
10
0
0 200 400 600 800
Net return ($/ha/season)
Site Makueni Limuru Matopos Kaffrine
HH size - mean 6.2 4.7 6.4 17.4
Farm size - mean 3.55 0.54 1.34 14.60
HHs with less than 2 ha (%) 39 99 81 0
Rainfall (mm/year) 611 854 567 593
No of seasons 2 2 1 1

18. high value
80 maize x = $520
x = $300
70
sorghum/millet
60 x = $176
HHs with $1/person/day (%)
50
Limuru
40 Matopos
Makueni
30
Kaffrine
20
10
0
0 100 200 300 400 500 600 700 800
Net return ($/ha/season)

19. Conclusions (1)
With a range of technologies in a wide variety of crops and countries, agricultural
research can substantially increase (by 220%) the net returns from rainfed crop
production, from a median of $84 / ha / season to $268 / ha /season ( n = 69)
There seems to be an upper limit of net returns from rainfed crop production of around
$700 / ha / season. Returns near this limit are rare.
Given the limited range of profitability of rainfed cropping enterprises and the small
farm sizes that are characteristic of resource-poor farm households, absolute values of
income will remain small for the majority of smallholders even if there is widespread
adoption of improved technologies.
For any given level of return, farmers in areas where there are two- or three seasons
per year can potentially gain more benefit from crop production than those in single-
season areas. Irrigation can facilitate additional cropping seasons.

20. Conclusions (2)
Adaptation requires adoption. We must not continue to assume that our target HHs are
full-time farmers. The available additional returns to investment in crop production are
small, and their decisions may be influenced by other, non-farm, opportunities (trade-
offs).
The potential for impact from agricultural intensification depends on HH characteristics
as well as agro-ecological potential. Some communities in high potential areas will never
be able to benefit directly from agricultural intensification. This should be taken into
account when targeting interventions.

21. Effect of a technology package on productivity and gross margins of sorghum in Uganda (Tororo, Pallisa, and
Soroti Districts). Data from Sorghum Production Technology Transfer Project in Eastern and Northern Uganda: A
Baseline Survey. Final Report, May 2011, by Gabriel Elepu, J. Mark Erbaugh and Donald W. Larson.
Variable Non-participant Participant Difference
farmers farmers (Participants-
Non)
Household size 7 8 1
Annual farm income ($/HH)ƚ 131 150 19
Annual off-farm income ($/HH)ƚ 47 119 71
Total HH income ($/HH)ƚ 178 269 90
Total land per HH (ha) 1.21 1.78 0.57
Land area planted to sorghum (ha/HH) 0.36 0.45 0.08
Sorghum output (kg/HH) 164 351 187 (114%)
Sorghum yield (kg/ha) 504 739 235 (47%)
Total value ($/ha) 40.31 55.31 15.00 (37%)
Production costs ($/ha)§ 36.39 45.65 9.26 (25%)
Gross margin ($/ha) 3.92 9.66 5.74 (146%)
Gross margin ($/HH) 1.43 4.30 2.87 (200%)
Per capita income from sorghum ($/day) 0.0006 0.0015 0.0009 (150%)