Welcome to the Crop Decision Support Tool
To be able to feed ourselves and our families we need farming
systems that create high yields. In these online web pages
(AfriCropDST) we have developed methods to help you, the
small to medium hold farmer, get the best yields for your
There are a number of important issues to understanding the
use of the information presented.
- The information is a guide only. It is not possible to
predict all outcomes in a farming exercise because there
are too many factors involved.
- You must rely on your own knowledge of farming first.
This guide might assist in your decision make process.
There are many important methods that can increase
crop yields. Many of these were passed down from your
ancestors and can be very valuable tools in your decision
making. For example, predicting which day to best plant
your crops can be based on the movements of birds or
insects, which can be very valid in terms of the effect of
climate on these factors. Trust your own knowledge.
- As all farmers know the most important factor is
rainfall. We have shown in our research that two
things are important, the amount of seasonal rainfall
overall and how this rainfall is distributed across the
days of the season. For this reason we have used daily
rainfall estimated locally over the last 30 years to
calculate yields. We also use predicted rainfall as part
of the advice presented.
- Overall the important factors in crop farming include
planting date, sowing density, variety, weeding, soils and
fertiliser. Our research using computer models showed that
computer models are best used in understanding the
interactions between rainfall, soil condition and
fertiliser application. This does not mean that the other
factors are unimportant. In fact they are very important.
In our information pages we give some advice on some of
these other factors.
- Many useful methods can help improve crop yields. Examples
include mulching, crop rotation, inter cropping, using
manure etc. However, there are potential drawbacks to
these methods. These methods are also discussed on our
Improving crop yields
information page. It is important to read through these to
understand the potential issues.
- Finally, our interactive pages allow one to assess the
potential yields for staple crops for your farm. For this
you must choose the crop, the soil type, and select your
location on the map. Then a graph of predicted yields for
that crop under your conditions for the predicted rainfall
for that season will be shown. More information on how to
use this tool is given under the button
How to use the AfriCropDST tool.
Growing Staple Crops under Small-Scale Agriculture in
This advice is based on our research, other references and
to some extent on what is referred to as Conservation
- Tillage. Tillage
is the aerating of soil with an implement such as a plough
to counter the negative effects of soil compaction.
Soil compaction has several negative effects on crop growth.
It can reduce soil aeration, rainfall infiltration and water
movement through the soil and increase soil nitrogen loss.
It can also limit the ability of crop roots to explore the
soil to obtain water and nutrients. Several methods can be
used to reduce soil compaction, ploughing and ripping being
the most common.
However, natural soils have their own structure and this
provides aeration. Thus, while tillage can provide an instant
reduction in soil compaction, in the long-term it can also
increase soil compaction. Practices such as no (zero) and
minimum tillage sometimes result in an initial increase in
soil compaction, but in the long-term are beneficial due to
improvements in soil structure. This is the approach
suggested by Conservation Agriculture where they advise
planting in holes made in the ground without tillage.
- Mulching. This is
the use of plant material to cover the soil in an effort to
improve the soil conditions such as moisture retention and
increasing soil organic content. However, for farmers with
limited resources in Africa it is neither economical nor
practical to move composted fresh plant materials into their
fields. In addition, biomass production is often too low to
produce enough for mulching and for other purposes such as
for feeding livestock and cooking fuel (Motis and Berkelaar).
For dry and low rainfall (2-5mm) areas, mulching retains
moisture for long periods; however, more rainfall is needed
for the moisture to seep into the ground (Motis and Berkelaar).
Hence, it is generally not advisable to mulch dry soils in
very low rainfall areas.
- Animal manure. This
can also be used to increase the nutrient content in the
soil, however, its availability and quality has been found
to be limited in Africa (Solomon et al, 2000; Tittonell
et al, 2005; Mafongoya et al, 2006a).
To combat the challenge of limited availability of mulch
and animal manure, "strip" mulching can be practiced whereby,
the mulch is only applied as a strip on the planting row or
"precision" mulching where the mulch is only placed a few
centimetres below the seed (Motis and Berkelaar).
- Cover crops and green manure
crops. Cover crops are crops that are grown around
the edges of the field. Green manure crops are crops that
are grown with the intention of adding organic nutrients
in the soil. Cover crops and green manure crops have been
found to contribute between 50 and 140 t/ha of organic matter
(Motis and Berkelaar). Cover crops also aid in reducing soil
erosion, weeding operations and provide shade to reduce the
"burnout" of soil caused by direct sunlight. Furthermore,
studies have shown how cover crops can help maintain
biodiversity by reducing the effects of pests and diseases
(Reeves, 1997; Tsubo et al, 2003; Kariaga, 2004;
Seran and Brintha, 2010; Motis and Berkelaar).
- Fertilizer application.
When the soil organic content is depleted or there is nutrient
imbalance in the soil, mineral fertilizer can be used to
supplement the deficient nutrients in the soil for the crops.
Under poor, average and optimal soil conditions, the
application of fertilizer generally increases yields given
that all other factors are optimal (Masere and Duffy, 2014).
However, fertilizer is costly and should therefore be applied
correctly in conjunction with good rainfall conditions to
realise its full benefits. In situations of poor and average
soil conditions coupled with below optimum total seasonal
rainfall, fertilizer generally, has reduced effects on crop
yields (Masere, 2011; Masere and Duffy, 2014). Irregular or
unusual rainfall distributions within a season can also
negatively affect the productiveness of applied fertilizer,
despite the fact that the total rainfall amount is considered
optimal (Masere and Duffy, 2015). Therefore, fertilizer
application must be practiced with caution and control.
- Intercropping. This
is the practice of growing more than one crop simultaneously
in alternating rows of the same field. Intercropping decisions
depend mainly on the onset, amount and duration of the
rainfall season (Ofori-sarpong, 2001). Examples of typical
combinations are cowpea-sorghum for poor rainfall situations
and maize-beans for moderate rainfall situations (Mapanda
et al, 2016). Hirpa (2014) states that in Ethiopia,
maize-bean intercropping is not only used to supplement
income and diet variety, it also increases the yield per
unit area and lessens the chances of crop failure due to
irregular climatic changes. Intercropping creates a variety
of rooting systems, which binds the soil together with
reducing water loss due to surface runoff. The increased
leaf cover from the one crop can provide shade and physical
support to the other crop and this cools the soil, hence
reducing moisture loss (Innis, 1997). The shade canopy from
leaves also aids in control of weeds (Mapanda et al,
2016). Intercropping also offers plant diversity, which aids
in the mitigation of pest and disease outbreaks by increasing
the distance between plants of the same kind. Nonetheless,
intercropping can present difficulties in harvesting because
the different crops are harvested differently. However, the
benefits of intercropping can outweigh the challenges.
- Controlling weeds and pests
For small hold farmers weed control is often best done by
hand and using local knowledge on how and when to weed for
a particular crop (Masere and Duffy, 2014). For example,
for maize up to three weeding events can be optimal.
For pest control, farmers may use either natural or chemical
methods or both to limit infestations. Natural control
method often utilizes other organisms such as plants or
insects to control pests in an agricultural environment.
Examples include companion planting or planting other
crops to draw the insects away from the main crops, or
cultivating insects or small animals, which feed on the
pests (Pest Control Methods, 2012). These methods have
little or no harmful effect on humans and agriculture, thus
making it useful where other animals such as pets and
livestock are present in the surroundings.
Chemical control methods involve the use of harsh pesticides
that instantly eliminate pests upon application. These can
either be applied systematically (targeting where plants are
commonly ingested by pests) or to the entire crops as in
the case of aerial spraying. While pesticides can be effective
on large crops and within households, they can be harmful
with residual effects on both human and animals (Pest Control
Controlling diseases requires cost. When to introduce
controls can be important to optimise results and thus costs.
Our analyses suggest that introducing a control measure at
the outset of the outbreak can reduce the spread of the
diseases (Collins and Duffy, 2017).
Aziz, I., T. Mahmood and K.R. Islam. 2013. Effect of long-term
no-till and conventional tillage practices on soil quality.
Soil and Tillage Research 131: 28-35.
Collins, O.C. and Duffy, K.J. 2016. Optimal control of maize
foliar diseases using the plants population dynamics.
Acta Agriculturae Scandinavica, Section B Soil & Plant Science 66: 20-28.
Hirpa, T. 2014. Effects of Intercropping Row Arrangement on
Maize and Haricot Bean Productivity and the Residual Soil.
School of Plant and Horticultural Sciences, Hawass University,
College of Ethiopia.
Innis, D.O. 1997. Intercropping and Scientific Basis of
Traditional Agriculture.London: Intermediate Technology
Kariaga, B.M.2004. Intercropping maize with cowpeas and
beans for soil and water management in Western Kenya. ISCO
2004 - 13th International Soil Conservation Organisation
Conference: Conserving Soil and Water for Society: Sharing
Solutions - Brisbane, July 2004.
Knowler, D. and B. Bradshaw. 2007. Farmers' adoption of
conservation agriculture: A review and synthesis of recent
research. Food Policy 32:25-48.
Mafongoya, P.L., A. Bationo, J. Kihara and B.S. Waswa. 2006a.
Appropriate technologies to replenish soil fertility in southern
Africa. Nutrient Cycling in Agroecosystems 76: 137-151.
Mapanda, S.,Chitja J.M., Duffy K. 2016. Indigenous strategies
and empirical models for adaptability of the maize-bean
intercropping system to climate change. Indilinga-African
Journal of Indigenous Knowledge Systems 15(3); 328-347.
Masere, T.P., Duffy K.J. 2014. 'Factors cost effectively
improved using computer simulations of maize yields in
semi-arid Sub-Saharan Africa', South African Journal of
Agricultural Extension, Vol 42, No 2, pp 39-50.
Masere ,T.P., Duffy K.J. 2015. Effect os within-season daily
rainfall distribution on maize crop yields. SAGE Journals 44.
Motis, T.N., Berkelaar, D.R. 2012. Agricultural options for
Ofori F. and Stern, W.R. 1987. Cereal-legume Intercropping
System. Aokane in Agronomy, 41:41-90.
Pest Control Methods. (2012). Pest control methods: Natural
vs. Chemical. Available at
. Accessed 14 March 2017.
Seran, T.H. and I. Brintha. 2010. Review on maize based
intercropping. Journal of Agronomy 9: 135-145.
Solomon, D., J. Lehmann and W. Zech. 2000. Land use effects
on soil organic matter properties of chromic luvisols in
semi-arid northern Tanzania: carbon, nitrogen, lignin and
carbohydrates. Agriculture, Ecosystems and Environment
Reeves, D.W. 1997. The role of soil organic matter in
maintaining soil quality in continuous cropping systems.
Soil and Tillage Research 43: 131-167.
Tilman, D. Cassman, K.g., Matson A.P., Naylor, R.,
Polasky, S. 2002. Agricultural sustainability and intensive
production practices. Nature publishing group 418: 671-677.
Tittonell, P., B. Vanlauwe, P.A. Leffelaar, E.C. Rowe and
K.E. Gille. 2005. Exploring diversity in soil fertility
management of smallholder farms in western Kenya I.
Heterogeneity at region and farm scale. Agriculture,
Ecosystems and Environment 110: 149-165
Tsubo, M. E. Mukhala, H.O. Ogindo and S. Walker. 2003.
Productivity of maize-bean intercropping in a semi-arid
region of South Africa. Water SA 29:381-388.
Vanlauwe, B. and Giller, K. E.: Popular myths around soil
fertility management in sub-Saharan Africa, Agric. Ecosyst.
Envir., 116, 34-46, 2006.
How to use the AfriCropDST tool
This tool is primarily aimed at improving certain African
crop staples through assistance with decisions on how much
fertiliser and which broad cultivar type to use based on the
predicted rainfall and soil type in your particular region
and farm. Other useful information on improving crop yields
can be found on the Improving crop yields
To use the online tool:
- Choose your crop from the drop down
tab on the left.
- Choose your soil type by marking the
tab choices under texture, fertility and
Texture: Clay, Loam, Sand.
If you are not sure a simple test is to take a small handful
of soil and test it:
- Collect a small sample of soil at a depth of 10cm
below the soil surface.
- Take about two teaspoons of this soil and moisten it
in the palm of your hand adding a few drops of water at
a time. Continue adding water and kneading the soil
until the soil is like putty, but not so wet that the
soil sticks to your hand. Try rolling this soil into a
ball (approximately the size of a fist).
- If it forms a ball, put the ball down. If you cannot
form a ball or the ball falls apart when you put it down,
the soil has a sandy texture.
- If neither occurs, roll the ball on a flat surface
(like a chopping board) into a sausage shape approximately
the length of a hand. If the sausage breaks apart, the
soil can also be considered predominantly sandy.
If the soil stays in the sausage shape proceed to the
- Continue to roll the sausage until it is approximately
twice as long. Then gently bend the soil sausage into a
"U" shape. If cracks appear at either stage, the soil
has a loam texture.
- If no cracks appear, gently bend it further into a
circle. If a circle cannot be formed and the soil falls
apart, the soil has a loam texture. If
not, proceed to the next step.
- If the soil can be bent into a circle and even if a
few surface cracks appear in the soil around the edge
it is a clay soil.
Fertility - soil organic carbon content
Low: less than 0.7 %
Medium: between 0.7 and 1.2 %
High: greater than 1.2 %
(For this you could have a laboratory test done. Otherwise
make an educated guess based on your yield history and past
management of the farm regarding fertilizer and other methods.)
Shallow: less than 90 cm
Medium: between 90 and 150 cm
Deep: deeper than 150 cm
- Find the rainfall that is predicted
for the coming season. This prediction is found by clicking
on the blue Predicted Rain button. This
takes you to another page with a rain prediction map. The
information page (click the
the Blue button) explains how to use this page.
- When you locate your farm position
on the rainfall map the predicted rainfall will be one of:
You then return to the original page and select the
Predicted rain from the drop-down list. Use
the predicted rain from the map or your own predictions.
You can also compare results using different predictions.
- Above normal – in the highest 33% of historicrainfall for that location
- Normal – in the middle 33% of historic rainfall for that location
- Below normal – in the lowest 33% of historic rainfall for that location
- Now place your cursor on your location.
Locate the region close to your farm by zooming in on the
map. Zooming is done using the
buttons in the upper left hand corner of the map. Otherwise
use your mouse.
- Click the mouse and graphs will
appear. If no graph appears either that location has not
been covered by our project or it is a region not entirely
suitable for that crop.
The graphs show crop yields possible under the chosen
conditions of soil and predicted rain for different
fertiliser applications and using different cultivars.
To read these graph, first understand that they are box
plots. Thus, the dark horizontal line is the median (the
middle value of the data). The blue boxes are where 50% of
the data is found and the other horizontal lines bound all
(or most) of the data results.
Three cultivars are presented: early, medium, and late
maturing cultivars. These graphs can be compared directly.
For nitrogen fixing plants such as beans only cultivar
applications are compared and adding nitrogen is not
recommended as a cost effective measure (see technical notes).
To read the graphs compare the medians (dark horizontal
lines) and the overlap of the boxes. If the medians and
boxes do not overlap then the highest yields are more
likely for a particular fertiliser application. The boxes
represent the risk because there is a chance that conditions
will give as little (or more) yield in the range provided.
THE LARGER THE SPREAD THE MORE THE RISK. You need to weigh
up the possibility of a better yield against the cost of
the added fertiliser. Keep in mind that other less costly
methods can improve yields (see our pages on
Improving crop yields).
Two examples are given here:
- For maize, using an early maturing
cultivar with a clay, medium texture and medium depth soil
and an above normal expected rainy season in the Ladysmith
region of South Africa, the following graph is predicted:
From this graph fertiliser improves yields. If one uses
50kgN (per hectare) of fertiliser then one can expect yields
in the range of 1400 kg/ha to 2000 kg/ha for 50%
of the season and between 750 kg/ha to 2000 kg/ha
for most seasons.
However, apart from the lowest fertiliser application, the
size of the boxes do not increase much with increased
fertiliser so the risks are proportional.
Assume that fertiliser cost USD 60 (R 900) kg per
ha and after the season you get 1400 kg/ha of maize.
Assuming it would cost USD 0.16 (R 2.50) to buy
a kg of maize then in order to buy the same yield per
hectare would cost USD 233 (R 3500) with a net
profit of USD 173 (R 2600). This is a significant
However, a yield of 750 kg/ha is possible and then
only USD 125 (R 1875) would be recovered with a
net profit of USD 65 (R 975). Furthermore,
although predicted to be above normal, the rains could
actually be below normal. Then the expected yields would be:
Now as little as 50 kg/ha maize is possible for the
50 kgN. This would result in only USD 8 (R 125),
which is much less with a net loss of USD 52 (R 775).
Notice also that here the boxes are spread wider with
increasing fertiliser and so this represents increasing
- Now consider the same conditions in
region of South Africa. Even for above normal predicted
rains the predictions are:
From this graph it is obvious that very little fertiliser
(and perhaps none based on natural organic carbon, given
here as 5 kgN/ha) will give similar yields as when
fertiliser is applied. There could be better results but
it would be risky. Also, the risk increases with fertiliser
- All calculations in these examples are based on rough
estimates of prices and exchange rates.
- All the results are meant as a guide only. A lot of other
knowledge must be taken into account. For example, see the
pages on Improving
crop yields. Also, these results depend on the predictions
of the conditions and these can always be wrong.
- For cases where the predicted rainfall is equally below
normal, normal or above normal (white areas on the IRI
climate forecast pages) we suggest that a farmer could
hedge his/her options. For example, the farmer could add
the suggested fertilizer amounts for each of the results
(above average, below average and normal) and divide by 3
(option 1) or divide the land available by 3 and apply
each amount suggested (option 2).
The following technical documents are available for download:
Data sources for the map layers:
AgMERRA Weather Data:
Ruane, A.C., R. Goldberg, and J. Chryssanthacopoulos, 2015:
AgMIP climate forcing datasets for agricultural modeling:
Merged products for gap-filling and historical climate
series estimation, Agr. Forest Meteorol., 200, 233-248,
HC27 Soil Data:
Koo, Jawoo; Dimes, John, 2013, "HC27 Generic Soil Profile Database",
http://hdl.handle.net/1902.1/20299, Harvard Dataverse, V4
Please click on a location using the AfriCropDST Tool
to display model results for that location.