Updating “machine learning imagery dataset for maize crop: A case of Tanzania” with expanded data to cover the new farming season
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Date
2024-03-23
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Publisher
Elsevier Inc.
Abstract
Maize Lethal Necrosis (MLN) and Maize Streak Virus (MSV)
are among maize diseases which affect productivity in Tan-
zania and Africa at large. These diseases can be detected
early for timely interventions and minimal losses. Machine
learning (ML) has emerged as a powerful tool for automated
diseases detection, offering several advantages over tradi-
tional methods. This article presents the updated dataset of
9356 imagery maize leaves to assist researchers in develop-
ing technological solutions for addressing crop diseases. The
high-resolution imagery data presented in this dataset were
captured using smartphone cameras in farm fields which
were not selected in the previously published dataset. Also,
data collection was taken in the range of three months from
November 2022 to January 2023 to incorporate farming sea-
son not covered in the previously published dataset. The pre-
sented dataset can be used by researchers in the field of Arti-
ficial Intelligence (AI) to develop ML solutions and eliminate
the need of manual inspection and reduce human bias. De-
veloping ML solutions require large amount of data therefore,
the updated and previously published datasets can be com-
bined to accommodate diverse and wider applicability.
Sustainable Development Goals
This research article was published in the Data in Brief, Volume 54, 2024
Keywords
Machine learning, Smart agriculture, Disease monitoring, Farmers