Abstract:
Climate change has been affecting negatively agriculture in various regions of the world. In the
valleys of southern Sonora, Mexico, there have been changes in climate like frost and heat
waves, which have aggravated the presence and incidence of pests and diseases on different
crops. This has also affected crops’ phenological development, with the consequent impact on
yield and quality. Through the technological development of data collection systems of
climatological variables through weather stations, it has been possible to generate large amounts
of climate data in the Yaqui and Mayo valleys. Advances in computing systems have made it
possible to manage, analyze, and interpret climate data. This work aims at applyinga datum
mining technique to create zones of climate influence by using the temperature and relative
humidity of 23 weather stations located in the Yaqui and Mayo valleys during the years 2015 to
2019. Inclusion criteria for the weather stations were data consistency and their representative
location within the region. The data mining technique used was clustering under the principal
components method, by which four zones of climate influence in the region were identified. The
first zone was located in the central part of the region; the second zone in the western part of the
Yaqui Valley; the third zone consists of three of the four stations located in the mountainous
zone of the region; and the fourth zone comprises stations located near the coastal area.
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