A digital solution for yield data acquisition, management and sharing to structure fruit value chains in Africa - PixFruit
Measuring, estimating and predicting yields is a major challenge in agriculture. Uncertainty and a lack of information have serious logistic, organisational, agronomic and economic repercussions. Several levels are impacted, from the orchard to the production area.
The development of fruit value chains in Africa is currently severely hampered by the lack of factual or predictive advisory tools, which can be used to assess yields in time and space. In this context, PixFruit will meet the operational needs of sector stakeholders while addressing the related research and development issues. The project will thus contribute to structuring tropical fruit value chains and increasing food security in West Africa.
The PixFruit solution, applied to mango value chains in the first phase, is a data management tool for mango yields, including:
- The participatory acquisition of field data via a smartphone application used to count fruit in trees and orchards;
- Analysis of yields using yield models on remote servers;
- Processing of these model outputs by a web app, giving sector stakeholders (producers, exporters, support services, policymakers, scientists, etc.) access to processed data with high added value (orchard yields, average yields in the area, yield potential, fruit availability, yield monitoring, etc.)
Through its activities conducted in partnership with the company SOWIT, the PixFruit project will contribute to developing operational products such as tools to:
- Count the number of fruit per tree, to estimate mango production at the orchard level,
- Monitor the evolution of yields over time on a web app,
- Access agricultural statistics at the level of a production area.
These solutions, developed by CIRAD and SOWIT, in collaboration with stakeholders, will be adopted and used (to a certain extent) by mango sector stakeholders in West Africa, from producers and buyers to the authorities and state organisations (identified needs). The PixFruit project will thus enable practice and organisational changes within the sectors: it will provide new knowledge and improve interactions between stakeholders at different levels of the sector (structuring of the sector).
The positive direct and indirect results of these changes will be as follows:
1) A precise spatio-temporal quantification of mango yields in Sub-Saharan production areas will be available to answer numerous research and development questions,
2) The relationships between sector stakeholders will be based on objective and reliable yield estimates, which will enable the structuring of the value chains,
3) Regional and national agricultural statistics will help to guide agricultural policies and the research and development actions to be undertaken,
4) Sub-Saharan fruit value chains will be more efficient and profitable for all stakeholders (which especially concerns mango producers).
A database on mango yields will be available for the scientific partners of the project. PixFruit will thus meet the operational needs of stakeholders and will answer research and development questions, contributing to the structuring of tropical fruit value chains and increasing food security in West Africa.
PixFruit will contribute to:
1) Informing producers about actual yields in order to guide their decisions,
2) Facilitating links between sector stakeholders based on measured yields,
3) Feeding an enhanced and spatialised database on fruit yields in West Africa.
Contract PartnerThe SOWIT company , CIRAD’s main partner for the PixFruit project, develops decision support tools for African farmers. The goal is to enable them to optimise their most critical operations, such as fertilisation, irrigation or estimation of harvest time. SOWIT markets solutions to provide farmers with precise, appropriate information based on expertise in remote sensing and machine learning. SOWIT’s ambition is thus to address the isolation of African farmers, who do not always have access to reliable information.