The invention discloses a
Candidatus Liberobacter asiaticum morbidity prediction method and
system based on multi-
source data fusion, and relates to the technical field of agricultural
disease and pest monitoring, and the method comprises the steps: obtaining the morbidity of the last growth year and day-by-day meteorological data, and completing unit matching; according to a spring
shoot period, a summer
shoot period, an autumn
shoot period and a late autumn shoot period, phenological
time windows are divided, and meteorological sequences are aligned; phenological characteristics are extracted in the corresponding
time windows; setting the morbidity of the last year as an
overwintering medium cardinal number agent and incorporating the morbidity into features; establishing a
diaphorina citri ecological mechanism sub-model and calculating a medium
population pressure index; fusing the features, the agents and the indexes to construct a morbidity prediction model, and completing regional parameter determination; and generating features and indexes according to the target annual observation or forecast data, and outputting a prediction result. Through phenological segmentation and medium mechanism
coupling, proxy variables are introduced and regionalization parameter determination is carried out so that meteorological, medium-to-
disease full-link quantification and early warning are realized and prediction accuracy,
interpretability and cross-regional applicability are increased.