基于气象因子的赣南脐橙气候品质指标评价模型

生态学杂志

基于气象因子的赣南脐橙气候品质指标评价模型

谢远玉¹,王培娟^2*,朱凌金³,陈星¹,黄莹¹

（¹江西省赣州市气象局，江西赣州 341000；²中国气象科学研究院，北京 100081；³赣州市赣县区气象局，江西赣县 341100）

出版日期:2019-07-10 发布日期:2019-07-10

Climate quality evaluation model for navel orange in Ganzhou.

XIE Yuan-yu¹, WANG Pei-juan^2*, ZHU Ling-jin³, CHEN Xing¹, HUANG Ying¹

(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

摘要/Abstract

摘要： 基于江西省赣州市11个脐橙主产县2008—2011年脐橙品质和气象数据，采用相关普查、逐步回归和主成分回归分析等方法筛选影响脐橙品质的关键气象因子，建立脐橙气候品质指标评价模型。结果表明：6—11月的温度、日照、降水是影响脐橙品质形成的关键气象因子；可溶性固形物与9—10月平均气温、10月气温日较差和日照呈极显著正相关，与10月降水量呈极显著负相关；VC含量与10月最高气温、日照、气温日较差呈显著正相关；可食率与10月气温日较差、7—10月最高气温和8—10月日照呈显著负相关；总酸含量与10—11月平均气温、10月最低气温、7—10月降水量呈显著负相关；单果重与6—11月平均气温、6—7月最高气温和10月降水量呈显著正相关；分别建立了基于气象因子的可溶性固形物、总酸、固酸比、VC、可食率、单果重等6个脐橙品质指标的评价模型，模型验证结果表明，各品质指标模拟的平均相对误差均小于12%，其中可溶性固形物和可食率的平均相对误差小于5%。

关键词: 红皮云杉, 树轮, 气候变暖, 生长衰退, 土壤温度

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.

谢远玉,王培娟,朱凌金,陈星,黄莹. 基于气象因子的赣南脐橙气候品质指标评价模型[J]. 生态学杂志.

XIE Yuan-yu, WANG Pei-juan, ZHU Ling-jin, CHEN Xing, HUANG Ying. Climate quality evaluation model for navel orange in Ganzhou.[J]. cje.

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