关键词: 黔阳冰糖橙, 气象因子, 品质评价, 逐步回归

Abstract: Based on the historical meteorological observation data of Hongjiang City from 2015 to 2019 and the quality detection data of Qianyang Bingtang orange, the correlation between seven quality indexes of Qianyang Bingtang orange and meteorological factors were analyzed by Pearson correlation analysis and stepwise regression analysis. The results showed that, the key meteorological factors affecting the titratable acid content of Qianyang Bingtang orange were the daily maximum temperature in strong fruit period and the daily minimum temperature in coloring period; the ratio of solid to acid was related to sunshine hours in fruit expansion period, cloudy and rainy days in strong fruit period, average maximum temperature in picking period and precipitation in picking period; the content of soluble solids was positively correlated with the daily temperature range during fruit expansion and sunshine hours during picking, and was negatively correlated with the daily average minimum temperature in fruit expansion period and cloudy and rainy days in coloring period; the key influencing factors of VC content were daily minimum temperature and daily maximum temperature in fruit expansion period, cloudy and rainy days in coloring period and sunshine hours in picking period; the key factors affecting the edible rate were the daily range during picking and the sunshine during fruit expansion; the key meteorological factors affecting the juice yield were the average daily minimum temperature, precipitation in the picking period and the average daily maximum temperature in the strong fruit period; the transverse diameter was related to the daily average minimum temperature and daily temperature range during fruit expansion, cloudy and rainy days during coloring and sunshine during picking. Based on the correlation analysis, the climate quality evaluation model of various quality indexes was constructed, and the model was verified by using the historical meteorological data and quality detection data in 2020. The relative error range was 1.2%~16.7%. The verification results showed that the model could exactly simulate the climate quality of Qianyang Bingtang orange.

Key words: Qianyang Bingtang orange, meteorological factor, quality evaluation, stepwise regression