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Climate quality evaluation model for navel orange in Ganzhou.

XIE Yuan-yu1, WANG Pei-juan2*, ZHU Ling-jin3, CHEN Xing1, HUANG Ying1   

  1. (1Ganzhou Meteorological Bureau, Ganzhou 341000, Jiangxi, China; 2Chinese Academy of Meteorological Sciences, Beijing 100081, China; 3Ganxian District Meteorological Bureau, Ganzhou 341100, Jiangxi, China).
  • Online:2019-07-10 Published:2019-07-10

Abstract: The quality of navel orange is closely related to meteorological conditions. In this study, six indicators for the quality of navel orange, including total soluble solids (TSS), titratable acid (TA), the ratio of TSS to TA (RTT), vitamin C content (VC), edible rate (ER), and single fruit weight (SW), and daily meteorological data at corresponding meteorological stations in 11 counties in Ganzhou City were analyzed in 2008-2011. The key meteorological factors affecting six quality indicators of navel orange were quantified with correlation analysis and stepwise regression. Six climate quality evaluation models for navel orange were constructed by using principal component regression. The results showed that temperature, sunshine, and precipitation from June to November were critical factors affecting the quality of navel orange. TSS was significantly positively correlated with the average temperature from September to October, diurnal temperature variation, and sunshine in October, while it was significantly negatively correlated with the precipitation in October. VC was positively correlated with the maximum temperature, sunshine, and diurnal temperature variation in October. ER was negatively correlated with diurnal temperature variation in October, maximum temperature in July-October, and sunshine in August-October. TA was negatively correlated with average temperature from October to November, minimum temperature in October, and precipitation during July-October. SW was positively correlated with average temperature in June-November, maximum temperature in June-July, and precipitation in October. Models of six quality indices for navel orange were built based on meteorological factors during critical period. The validation results with insitu observed qualities of navel orange in 2017 showed that the average relative errors for simulated qualities of navel orange were all within 12%, with the errors of both TSS and ER being less than 5%.

Key words: Picea koraiensis, tree ring, climate warming, growth decline, soil temperature.