丘陵山区黄桃气候品质等级评价模型

Evaluation Model of Yellow Peach Climatic Quality Rating in Hilly Mountainous Areas

  • 摘要: 利用2019—2023年罗霄山脉中段和雪峰山西侧221~1300 m海拔高度间的黄桃品质观测数据, 采用加权求和、相关系数、回归分析、多重共线性分析等方法, 构建黄桃气候品质评价指标及主要品质要素气象因子回归模型, 并进行独立样本检验, 基于模型分析不同海拔高度和采收日期条件下黄桃气候品质等级的时空变化特征。结果表明:黄桃品质要素可溶性固形物含量、可滴定酸含量、果形指数对应主要气象影响因子分别为采收前80 d平均气温、采收前40 d总降水量、5月上旬至6月上旬平均气温及总降水量与采收前10 d平均气温及总降水量, 对应气象因子模型的验证样本平均绝对偏差分别为0.397%、0.093%、0.010, 均方根误差分别为0.072%、0.014%、0.001, 相关系数分别为0.649(p=0.05)、0.718(p=0.01)、0.957(p=0.01), 品质评价等级验证完全一致的模型准确率为75%。由模型得到黄桃品质等级为特优及优的总频率随海拔升高、采收日期推移均呈先升后降的趋势, 其中600~820 m海拔地区与7月底至8月上旬采收的特优品质频率最高。

     

    Abstract: The study of evaluation indexes for yellow peach climate quality and its meteorological factor model can provide technical support to ensure high-quality production and facilitate rural revitalization. Taking "Jinxiu" variety of yellow peach as the research object, based on the yellow peach quality observations from 221-1300 m altitude and temperature and rainfall data from 13 meteorological stations near orchards at the middle section of Luoxiao Mountains and the west side of Xuefeng Mountain during 2019-2023, a climatic quality evaluation index for yellow peach and meteorological factorial regression model for its quality elements are constructed by using the methods of weighted summation, Pearson's correlation, regression analysis and multiple covariance analysis, and examined with independent samples. Effects of different altitudes and harvest dates on the climatic quality ratings of yellow peaches are further investigated based on the constructed model. Results show that the main meteorological influencing factors for yellow peach soluble solids content (SS) is the average air temperature 80 d before harvest, for titratable acid content (AT) is the total rainfall 40 d before harvest, and for fruit shape index (IS) are the average air temperature from 1 May to 10 June, total rainfall from 1 May to 10 June, the average air temperature 10 d before harvest and total rainfall 10 d before harvest. Mean absolute error between the simulated and measured values of SS, AT, and IS of validation samples is 0.397%, 0.093%, and 0.010, respectively, and the root mean square error is 0.072%, 0.014%, and 0.001, respectively, and r is 0.649 (p=0.05), 0.718 (p=0.01), and 0.957 (p=0.01), respectively. The simulated quality ratings for 75% of validation samples match the actual climatic quality ratings, while 25% differs by 1 level. Simulation based on the constructed model reveals that the total frequency of superior and excellent quality in the study area shows an increasing and then decreasing trend with both the elevation and the harvesting period, among which the best quality is found in the mid-high elevation areas of 600-820 m or the harvest from 31 July to 10 August. Fruits harvested in high elevation areas above 1300 m or harvested from 21 August to 31 August appear to have a high frequency of lower quality.

     

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