应用气象学报 (Jul 2024)

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

  • Wang Tianying,
  • Li Minhua,
  • Wu Zhongchi,
  • Huang Anfeng,
  • Yang Changshun,
  • Yang Pinling,
  • Wang Tianke

DOI
https://doi.org/10.11898/1001-7313.20240406
Journal volume & issue
Vol. 35, no. 4
pp. 456 – 466

Abstract

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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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