Abstract:

In this study, the navel orange yield and the meteorological data from Ganzhou were collected for the period from 2000 to 2022, and the corresponding meteorological yield was separated. The key meteorological factors affecting meteorological yield were identified by fitting relationships between meteorological yield and meteorological factors at five growth stages. Finally, the relative meteorological yield model based on key meteorological factors was constructed using multiple linear regression method, and the model was validated to determine its reliability, stability and accuracy. The results indicated that: (1) the exponential smoothing method with a given weight of 0.8 was more reasonable for separating the meteorological production of navel oranges in Ganzhou from 2000 to 2022. (2) The key meteorological factors affecting the yield of navel oranges included precipitation during the overwintering period, average temperature during the budding and flowering period, average temperature during the young fruit growth period, precipitation during the fruit swelling period, and sunshine hours during the coloring and ripening period. (3) Two yield simulation models were constructed based on the key meteorology factors from December 1 to September 30 of the following year (i.e., overwintering to the end of fruit swelling) and December 1 to November 30 of the following year (i.e., overwintering to coloring and ripening), respectively. Both the model passed the 0.01 level of significance, with the relative error of 5.52% and 5.31%, and the root mean squared error of 604.85kg·ha⁻¹ and 614.86kg·ha⁻¹, respectively. The model validation accuracy from 2018 to 2022 was 97.88% and 97.84%, respectively. Overall, the two simulation models are suitable for simulating navel oranges yield in southern Jiangxi.

Key words: Gannan navel orange, Meteorological factors, Yield forecast, Model constructed