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Agriculture Domain

Lacuna Fund agriculture datasets unlock the power of machine learning to alleviate food security challenges, spur economic opportunities, and give researchers, farmers, communities, and policymakers access to superior agricultural datasets. Learn more and download released datasets below.

2020 Awards

Description: This machine learning dataset of smallholder farmer’s fields includes georeferenced crop images along with labels on input use, crop management, phenology, crop damage, and yields, collected across 8 counties in Kenya.

Authors: Lilian Waithaka, Koen Hufkens, Berber Kramer and Benson Njuguna

Dataset: access here

Description: This dataset includes corrected geolocations of fields, improving the usability of the most expansive Eastern Africa crop cut yield estimation. Collected by the non-profit One Acre Fund from 2015 – 2019, this dataset covers major crop producing regions in Kenya, Rwanda, and Tanzania.

Dataset: access here

Description: This project built a remotely monitored and controlled Internet of Things (IoT) fish pond water quality management system for the generation of labeled datasets both for conventional ponds and the aquaponic pond systems.

Authors: Udanor Collins, Blessing Ogbuokiri, and Nweke Onyiny

Dataset: access here

Description: This dataset contains a repository of image and spectrometry datasets for five main food security crops in Sub-Saharan Africa: cassava, maize, beans, bananas, and cocoa. Collected and curated in collaboration with the in-country agricultural experts, the datasets deliver a wide range of machine learning applications, including classification, object detection, early crop disease detection, and spatial analysis. The team collected and annotated 127,046 images and 39,300 spectral data points. 

Authors: Joyce Nakatumba-Nabende, Andrew Katumba, Claire Babirye, Jeremy Francis Tusubira, Godliver Owomugisha, Neema Mduma, Darlington Akogo, Blessing Sibanda

Dataset: access here

All Lacuna Fund datasets are licensed under the CC-BY 4.0 International license unless otherwise noted.