Potato Crop Coefficient (
 ) Prediction Based on Encoder-Decoder Graph Learning Model

doi:10.1016/j.jafr.2026.103292

Potato Crop Coefficient ( ) Prediction Based on Encoder-Decoder Graph Learning Model

2026-09-17

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Aitazaz A. Farooque *

Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

DOI：10.1016/j.jafr.2026.103292

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Abstract

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• An accurate prediction model of Potato crop coefficients ( ) is designed. • Probabilistic dynamic graph deep learning model (PDGDL) is employed to predict . • An encoder and decoder strategies are involved to learn the dynamic graph representations. • Province of Prince Edward Island (PEI) is chosen to evaluate the proposed model.

Keywords:

Kc

dynamic graph

PDGDL

PEI

encoder

decoder

Potato crop

Agro-meteorological

Potato Crop Coefficient ( ) Prediction Based on Encoder-Decoder Graph Learning Model

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