RT info:eu-repo/semantics/article
T1 Humidity forecasting in a potato plantation using time-series neural models
A1 Yartu González, Mercedes Esther de
A1 Cambra Baseca, Carlos
A1 Navarro González, Milagros
A1 Rad Moradillo, Juan Carlos
A1 Arroyo Puente, Ángel
A1 Herrero Cosío, Álvaro
K1 Precision irrigation
K1 Potato crop
K1 Time series forecast
K1 Supervised learning
K1 Neural networks
K1 Interpolation
K1 Agricultura
K1 Agriculture
K1 Informática
K1 Computer science
AB It is widely acknowledged that, under the frame of sustainable farming, using the minimum water resources is a relevant requirement. In order to do that, precision irrigation aims at identifying the irrigation needs of plantations and irrigate accordingly. Artificial intelligence is a promising solution in this field as intelligent models are able to learn the soil moisture dynamics in the soil-plant-atmosphere system and then generating appropriate irrigation scheduling. This is a complex task as the phenology of plants and its water demand vary with soil properties and weather conditions. The present research contributes to this challenging task by proposing the application of neural networks in order to learn the time-series evolution of irrigation needs associated to a potato plantation. Several of such models are thoroughly compared, together with different interpolation methods, in order to find the best combination for accurately forecasting water needs. In order to predict the soil water content in a potato field crop, in which soil humidity probes were installed at 15, 30, and 45 cm depth during the whole cycle of a potato crop. This innovative study and its promising results provide with significant contributions to address the problem of predicting and managing groundwater for agricultural use in a sustainable way.
PB Elsevier
SN 1877-7503
YR 2022
FD 2022-03
LK http://hdl.handle.net/10259/6388
UL http://hdl.handle.net/10259/6388
LA eng
NO Lab-Ferrer (METER Group) and the UBUCOMP research group at the University of Burgos.
DS Repositorio Institucional de la Universidad de Burgos
RD 25-abr-2024