In Sub-Saharan Africa, population growth, associated food demand and pressure on natural areas have all increased greatly. Agricultural intensification – more production from the same acreage – remains a key solution to these challenges. One of the cornerstones of intensification is that of a higher and more productive use of inputs, such as fertilizer and water. So far, the average production has remained low and a significant yield gap still exists, mainly among small scale producers (SSPs). The limiting factors are (partly) caused by weather and climatic changes but also by a lack of agronomical knowledge, proper inputs, fertilizers and (climate smart) irrigation techniques. Thanks to the digital revolution Africa is going through, many commercial farmers already have access to a wide range of agricultural services. However, such solutions are not yet accessible to SSPs due to their costs.

To leapfrog the transformation of African agriculture, FutureWater, HiView, Holland Greentech (HGT) and ThirdEye Kenya bundle their strengths by merging key frontier technologies into an agronomic advisory service that allows improving the productivity and profitability of maize, tea and coffee farmers in five districts in Kenya. State-of-art technologies that will be developed and packaged into one integrated solution are low-cost flying sensors (drones), soil testing, climate smart inputs, farmer coaching and an interactive online planning & monitoring portal. Our unique Climate Smart Farming technology is disruptive as it collects data at low cost and links directly with the solutions to close the yield gap of farmers.

Over the past years FutureWater and HiView managed to develop a low-cost agricultural drone technology which revolutionized the applicability of geo-information services for African farmers. With the flying sensor service successful local enterprises were established that provide a low-cost drone service to small- and largescale farmers, both in Mozambique and Kenya. ThirdEye’s young agronomist-drone operators support farm decisions based on the flying sensor crop mapping that is viewed on a tablet. Integrating crop nutrition advisory and other improved agronomic practices into the ThirdEye service will bring the (extension) service up to the next level. In this project, we complement the work of flying sensors by ThirdEye with the agronomic service model of Holland Greentech including input distribution, demonstrations and field days, farmer training and coaching and soil testing.

By merging agronomic advisory services making use of low-cost flying sensors, soil testing, climate smart inputs, farmer coaching and an interactive online planning & monitoring portal, the farmer is able to improve his/her:

  • Planning: What crop to grow in the season based on expected weather, crop prices and market demand;
  • Cropping: When to sow the seed based on the type of crop and predicted weather
  • Management: When and where to irrigate, fertilize and apply pesticide. This can help reduce the amount of inputs used in the farm and increase yields, thus helping with profitability.
  • Harvest: When to harvest the crop based on market prices and predicted weather.
  • Market linkage: The ability to make informed decisions on where to sell their produce, which may increase their income.
  • Climate resilience: Option to order climate smart inputs and technologies from different suppliers. These technologies include hybrid seeds, propagation units and greenhouses, (drip) irrigation equipment, soil analysis, biological soil enhancers and biological pest control products.

The service comprises of (i) drone flights executed by AgroPilots (functioning as both pilots and agronomic advisor), (ii) soil tests and soil fertility advisory, (iii)  aerial imagery processing & interpretation, (iv) agronomical advisory on inputs & irrigation and (v) advisory on sourcing plans and access to market. Flying sensors and state-of-art data analysis will be used to monitoring the progress of the newly applied practices. By identifying field specific limiting factors that currently constrain productivity of maize, tea and coffee farmers (using flying sensors) and by providing concrete climate smart solutions, farmers can better adapt to climate change and can increase their field production, leading to more profitable farmers and an improved food security for the future to come.

Flying sensor data will be gathered, processed and analyzed during the first growing season, which serves as a baseline (reference) for the rest of the project period. The imagery acquired with the flying sensors (at regular intervals) will also be used in combination with FAO’s AquaCrop crop growth model to make estimations of crop yield (or land productivity). This will require additional activities in crop surveying and field observations and further imagery processing to achieve maps of the vegetation status and canopy cover. The approach for calculating land productivity is based on light use efficiency models which converts canopy cover to biomass production and is tailored to potato with crop-specific parameters. The end result will give information on the crop yields achieved from each plot, as shown in the figure below.

Map of dry yield (left) and yield gap based on the difference with the best performing plot (right) for maize plots in a previous study in Mozambique.

After the initial data gathering and analysis process, the findings will be translated into action plans for the lead farmers. They will be trained and coached to improve their farming practices and use climate-smart agricultural (CSA) practices. Following this step, we will facilitate access to inputs and conceptualize distribution systems for agro-inputs for the lead farmers. After providing the farmers with this valuable advice, data will be gathered again using flying sensors and soil samples over the course of the next growing seasons. Implementation of the farmer action plans, training of farmers, and advisory services directly based on the flying sensor vegetation status maps are expected to contribute to an increase in crop productivity. Crop yield calculations will be done at the end of each season.

In Angola, more and better-quality data is required to improve crop suitability assessments over large extensions of arable land to ensure sustainable food and income security. For example, environmental data on soil texture, soil water storage capacity, vegetation growth, terrain slopes, rainfall and air temperature are key to develop reliable crop suitability assessments. These datasets are available from state-of-the-art satellite-based products and machine learning observations (de Boer, 2016; Funk et al., 2015; Hengl et al., 2014, 2017). The benefit of these data products is that data can be obtained for any province, municipality, or farm in Angola. On top of that, data can be shown in maps to easily visualize spatial variation and identify the most suitable location and area to grow desired crops. Land-crop suitability maps are obtained by calculating a weighted average of the environmental variables that influence crop growth (e.g. rainfall, air temperature, soil water storage capacity), providing an integrated and complete assessment on where to plant. Also, potential crop yields are determined for desired cropping seasons using the FAO AquaCrop model to provide more information about potential income.

Irrigated agriculture in Angola has been developed in commercial farms using mainly central pivot and drip irrigation systems. The installation of new irrigation systems is foreseen in large extensions of land over 5000 hectares. Irrigated agriculture results in higher crop yields and allows higher incomes to farmers. However, commercial farms must invest in high energy supply to operate irrigation systems with water pumping stations. The challenge for irrigation system operators is to know exactly when and how much to irrigate during the cropping season. If better information about irrigation volumes and intervals are provided a significal reduction in energy costs could be achieved. The objective is to predict irrigation demand volumes during the cropping season and provide a user-friendly decision tool to irrigation operators. To achieve this, weather forecasts, remote sensing, and the SPHY model will be used.

For smallholder farming systems, there is a huge potential to increase water productivity by improved (irrigated) water management, better access to inputs and agronomical knowledge and improved access to markets. An assessment of the opportunities to boost the water productivity of the various agricultural production systems in Mozambique is a fundamental precondition for informed planning and decision-making processes concerning these issues. Methodologies need to be employed that will result in an overall water productivity increase, by implementing tailored service delivery approaches, modulated into technological packages that can be easily adopted by Mozambican smallholder farmers. This will not only improve the agricultural (water) productivity and food security for the country on a macro level but will also empower and increase the livelihood of Mozambican smallholder farmers on a micro level through climate resilient production methods.

This pilot project aims at identifying, validating and implementing a full set of complementary Technological Packages (TP) in the Zambezi Valley, that can contribute to improve the overall performance of the smallholders’ farming business by increasing their productivity, that will be monitored at different scales (from field to basin). The TPs will cover a combination of improvement on water, irrigation, and agronomical management practices strengthened by improved input and market access. The goal is to design TPs that are tailored to the local context and bring the current family sector a step further in closing the currently existing yield gap. A road map will be developed to scale up the implementation of those TPs that are sustainable on the long run, and extract concrete guidance for monitoring effectiveness of interventions, supporting Dutch aid policy and national agricultural policy. The partnership consisting of Resilience BV, HUB, and FutureWater gives a broad spectrum of expertise and knowledge, giving the basis for an integrated approach in achieving improvements of water productivity.

The main role of FutureWater is monitoring water productivity in target areas using an innovative approach of Flying Sensors, a water productivity simulation model, and field observations. The flying sensors provide regular observations of the target areas, thereby giving insight in the crop conditions and stresses occurring. This information is used both for monitoring the water productivity of the selected fields and determining areas of high or low water productivity. Information on the spatial variation of water productivity can assist with the selection of technical packages to introduce and implement in the field. Flying sensors provide high resolution imagery, which is suitable for distinguishing the different fields and management practices existent in smallholder farming.

In May 2020, FutureWater launched an online portal where all flying sensor imagery from Mozambique, taken as part of the APSAN-Vale project, can be found: futurewater.eu/apsanvaleportal