Construction and Application of Climate Quality Evaluation Model for Indian Jujube
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摘要: 基于2015—2016年福建、广东青枣主产区田间试验的62个鲜果样本主要品质要素,采用相关分析、加权指数求和法,结合文献查阅、专家调研以及常规农业气象条件定量化等级评价标准,筛选影响青枣品质的关键气候因子,构建青枣气候品质等级评价模型,并利用2014—2019年青枣产区36个独立样本进行验证,分析福建主产区青枣气候品质时空分布规律。结果表明:影响青枣品质的3个关键气候因子分别为采收前90 d平均气温、采收前30 d气温日较差和采收前30 d日照时数,模型准确率达86.1%,青枣气候品质等级评价模型可客观反映气候条件对青枣品质影响。由模型分析可知:福建青枣气候品质前中期采摘的果实优于后期,通过青枣产期调节可提升全产期优质青枣比例;基于模型绘制的福建青枣主要采摘期气候品质空间分布图显示福建青枣产区南部优于中北部,增加南部种植面积、减少北部种植面积的布局调整有利于提升全区域优质青枣比例。Abstract: In order to adapt and fully utilize climate resources, improve the quality of Indian jujube, and increase the income and economic benefits of fruit farmers, 62 samples of fresh fruit weight, soluble sugar, soluble solids, vitamin C, hardness and other main quality factors are obtained from the field experiments in main production areas of Indian jujube in Fujian and Guangdong from 2015 to 2016. Combining literature review, expert investigation and quantitative grade evaluation standard of conventional agrometeorological conditions, the key climatic factors affecting the quality of Indian jujube are selected, and the grade evaluation model of climatic quality of Indian jujube is established. The temporal and spatial distribution of climate quality of Indian jujube in Fujian is analyzed based on 36 independent samples of main quality and meteorological data in major Indian jujube producing areas of Fujian and Guangdong, Guangxi from 2014 to 2019. The results show that three key climatic factors affecting the quality of Indian jujube are the 90-day average temperature 90 days before harvest, daily temperature range and sunshine hours 30 days before harvest. The accuracy of this evaluation model is 86.3%. The evaluation model can objectively reflect the influence of climate conditions on the quality of Indian jujube. Based on the model analysis, the results show that the climate quality of Indian jujube in Fujian picked in the early and middle stages is better than those picked in the later stages, and the proportion of high-quality jujube in the whole production period can be improved by adjusting the production period. Based on the spatial distribution map of climate quality of Indian jujube in the main picking period obtained from Fujian by the model, the climate quality of Indian jujube in southern region is better than that in central and northern regions. Therefore, the proportion of high-quality Indian jujube in the whole region can be improved by increasing the planting area in the south and reducing the planting area in the north. The results have been applied in the evaluation of climate quality grade of Indian jujube in Fujian for three years.
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表 1 青枣野外观测站点概况
Table 1 Field observation sites for Indian jujube
站点 观测年份 树龄/a 地理位置 海拔高度/m 平和县山格镇 2014—2019 10 24.4°N,117.4°E 29.4 南靖县船场镇 2014—2019 15 24.5°N,117.4°E 152.7 长泰县陈巷镇 2014—2019 8 24.7°N,117.8°E 13.0 漳浦县石榴镇 2014—2019 10 24.0°N,117.4°E 63.0 丰顺果园 2014—2019 12 23.9°N,116.3°E 45.4 潮州铁铺 2014—2019 10 23.8°N,116.6°E 10.9 表 2 福建、广东主产区青枣品质要素
Table 2 Quality factors of Indian jujube in Fujian and Guangdong
统计量 单果重/g 可溶性固形物/% 可溶性糖/% 硬度/(kg/cm2) pH值 平均值 88.89 11.36 10.83 10.99 4.75 最大值 154.77 14.21 13.78 14.87 5.72 最小值 47.76 8.42 7.89 8.18 4.22 表 3 青枣品质分级
Table 3 Quality grade of Indian jujube
指标 特优(等级值为3) 优(等级值为2) 良(等级值为1) 一般(等级值为0) W/g W≥100 100>W≥75 75>W≥50 W<50 SS/% SS≥12.0 12.0>SS≥10.5 10.5>SS≥9.0 SS<9.0 表 4 青枣气候品质评价指标分级赋值
Table 4 Grade assignment of evaluating indicator of Indian jujube
M 采收前90 d平均气温Tavg/℃ 采收前30 d平均日较差ΔT/℃ 采收前30 d平均日照时数S/h 3 Tavg≥18.5 ΔT≥9.0 S≥5.0 2 15.5≤Tavg<18.5 6.5≤ΔT<9.0 3.5≤S<5.0 1 13.0≤Tavg<15.5 4.0≤ΔT<6.5 2.0≤S<3.5 0 Tavg<13.0 ΔT<4.0 S<2.0 表 5 等级划分与气候品质评价指数
Table 5 Grade and climate quality index
评价等级 气候品质评价指数IQ 品质等级对应参考值 单果重W/g 可溶性固形物含量SS/% 特优 IQ≥2.5 W≥100 SS≥12.0 优 1.5≤IQ<2.5 75≤W < 100 10.5≤SS<12.0 良 0.5≤IQ<1.5 50≤W<75 9.0≤SS<10.5 一般 IQ<0.5 W<50 SS<9.0 表 6 2014—2019年青枣品质对气候品质等级评价模型的验证
Table 6 Validation of climate quality evaluation model of Indian jujube from 2014 to 2019
采果日期 地点 单果重/g 可溶性固形物含量/% 实际品质 IQ 气候品质 等级对比 2016-12-12 漳浦 89.72 9.60 良+ 2.1 优 符合 2016-12-28 漳浦 91.08 11.37 优 2.4 优 符合 2017-01-19 漳浦 90.67 12.37 特优- 2.1 优 符合 2017-11-13 漳浦 82.69 11.63 优 2.4 优 符合 2017-12-14 漳浦 75.63 10.03 良+ 2.4 优 符合 2018-01-23 漳浦 82.41 14.00 特优- 2.3 优 符合 2018-02-06 漳浦 80.41 11.07 优 1.6 优 符合 2017-01-19 平和 99.10 11.13 优 2.0 优 符合 2016-12-12 南靖 62.37 7.97 一般+ 2.4 优 不符合 2016-12-28 南靖 104.26 8.57 良+ 2.7 特优 不符合 2017-01-19 南靖 86.94 12.27 特优- 2.4 优 符合 2017-02-09 南靖 82.51 12.23 特优- 2.0 优 符合 2017-02-27 南靖 73.79 13.23 优+ 2.3 优 符合 2018-01-23 南靖 87.89 11.87 优 2.6 特优 不符合 2018-02-06 南靖 90.31 10.47 良+ 2.0 优 符合 2018-03-12 南靖 83.06 12.33 特优- 1.9 优 符合 2019-02-13 南靖 80.11 10.80 优 1.7 优 符合 2019-02-26 南靖 77.08 10.90 优 1.4 良 不符合 2014-01-22 长泰 96.00 12.80 特优- 2.0 优 符合 2015-01-26 长泰 110.00 11.80 优+ 2.0 优 符合 2017-02-09 长泰 86.42 10.97 优 2.0 优 符合 2017-02-27 长泰 87.54 14.13 特优- 2.3 优 符合 2017-03-14 长泰 88.65 12.93 特优- 2.0 优 符合 2018-02-06 长泰 101.96 11.87 优+ 2.0 优 符合 2018-03-12 长泰 89.86 11.73 优 1.6 优 符合 2019-02-13 长泰 78.42 11.50 优 1.7 优 符合 2019-02-26 长泰 70.79 11.60 优- 1.4 良 符合 2019-01-29 梅州 83.72 11.90 优 2.0 优 符合 2019-02-16 梅州 86.31 12.90 特优- 2.3 优 符合 2019-03-10 梅州 56.42 9.30 良 1.4 良 符合 2019-01-26 埔寨 76.99 10.50 优 2.0 优 符合 2019-01-20 南宁 89.35 9.50 良+ 1.7 良 符合 2019-02-14 南宁 95.40 10.90 优 1.3 良 不符合 2019-03-15 南宁 52.52 12.60 优+ 1.3 良 不符合 2019-02-15 武鸣 49.81 12.50 优- 0.7 良 符合 2019-03-16 武鸣 46.62 12.80 优- 0.7 良 符合 表 7 2018年1月初采摘的青枣关键气象因子及青枣气候品质评级
Table 7 Climate quality grade and key meteorological factors for Indian jujube harvested in early Jan 2018
漳州地区 采收前90 d平均气温/℃ 采收前30 d平均日较差/℃ 采收前30 d平均日照时数/h IQ 评级 东山 20.6 4.3 6.6 2.4 优 华安 19.4 10.7 5.7 3.0 特优 龙海 20.9 8.7 5.4 2.7 特优 南靖 20.0 10.6 5.6 3.0 特优 平和 19.6 10.3 5.7 3.0 特优 芗城 21.1 8.8 4.7 2.4 优 云霄 21.3 8.7 5.8 2.7 特优 漳浦 20.0 9.2 5.8 3.0 特优 长泰 20.7 9.1 6.1 3.0 特优 表 8 2019年1月初采摘的青枣关键气象因子及青枣气候品质评级
Table 8 Climate quality grade and key meteorological factors for Indian jujube harvested in early Jan 2019
漳州地区 采收前90 d平均气温/℃ 采收前30 d平均日较差/℃ 采收前30 d平均日照时数/h IQ 评级 东山 19.2 3.8 3.9 1.8 优 华安 18.1 7.6 2.6 1.7 优 龙海 19.6 6.0 2.5 2.1 优 南靖 19.1 6.8 2.5 2.1 优 平和 18.7 6.6 2.2 1.7 优 芗城 19.8 6.0 2.5 2.1 优 云霄 20.0 6.0 2.5 2.1 优 漳浦 18.8 6.5 2.4 1.7 优 长泰 19.3 6.2 2.4 2.1 优 -
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