Crop Decision Support Tool for Africa

Welcome to the Crop Decision Support Tool for Africa

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 staple crops.

There are a number of important issues to understanding the use of the information presented.

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.

Please read the Introduction if this is your first time using the tool.

Select Crop & Rain

 

Describe your Soil Type

Depth indicates Rooting Depth (cm)
Shallow: < 90 cm
Medium: 90 to 150 cm
Deep: ≥150 cm

Fertility is the Soil Organic Carbon % of the top soil
Low: < 0.7%
Medium: 0.7 to 1.2%
High: ≥ 1.2%

More information is available on the How to use the AfriCropDST tool page.
 

Click your Location on the map

Use the  +  and  -  buttons or the mouse wheel to zoom in or out on the map. To zoom in double-click on the map or press Shift and draw a rectangle. Click and hold the mouse button to drag the map around.

Growing Staple Crops under Small-Scale Agriculture in sub-Saharan Africa

This advice is based on our research, other references and to some extent on what is referred to as Conservation Agriculture (CA).

  1. 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.
  2. 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.
  3. 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).
  4. 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).
  5. 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.
  6. 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.
  7. 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 Methods, 2012).

    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).

References

  • 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 Publications.
  • 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 small-scale farmers.
  • 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 www.pestcontrolmethods.org . 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 78: 203-213
  • 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 page.

To use the online tool:

  1. Choose your crop from the drop down tab on the left.
  2. Choose your soil type by marking the tab choices under texture, fertility and depth:

    Texture: Clay, Loam, Sand.
    If you are not sure a simple test is to take a small handful of soil and test it:
    1. Collect a small sample of soil at a depth of 10cm below the soil surface.
    2. 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).
    3. 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.
    4. 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 next step.
    5. 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.
    6. 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.
    7. 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.)

    Rooting Depth
    Shallow: less than 90 cm
    Medium: between 90 and 150 cm
    Deep: deeper than 150 cm
  3. 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 next to the Blue button) explains how to use this page.
  4. When you locate your farm position on the rainfall map the predicted rainfall will be one of:
    1. Above normal – in the highest 33% of historicrainfall for that location
    2. Normal – in the middle 33% of historic rainfall for that location
    3. Below normal – in the lowest 33% of historic rainfall for that location
    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.
  5. 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 and buttons in the upper left hand corner of the map. Otherwise use your mouse.
  6. 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:

  1. 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 saving.
    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 risk.
  2. Now consider the same conditions in the Grahamstown 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 application.

Notes:

  1. All calculations in these examples are based on rough estimates of prices and exchange rates.
  2. 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.
  3. 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).

Technical Information

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, doi:10.1016/j.agrformet.2014.09.016. https://data.giss.nasa.gov/impacts/agmipcf/
  • HC27 Soil Data:
    Koo, Jawoo; Dimes, John, 2013, "HC27 Generic Soil Profile Database", http://hdl.handle.net/1902.1/20299, Harvard Dataverse, V4

Model results

Please click on a location using the AfriCropDST Tool to display model results for that location.

© 2020 AfriCropDST
This work was funded by the African Union Research Grant (supported by the European Union): AURG/090/2012 and the South African Department of Science and Technology