光化学反射指数在比较葡萄叶片耐霜冻能力中的应用

doi:10.11983/CBB16123

摘要/Abstract

摘要： 以12个葡萄(Vitis vinifera)品种为试材, 在秋季采集叶片, 进行霜冻处理, 测定了霜冻过程中叶片光化学反射指数(PRI)的变化。提取有效参数, 采用隶属函数法比较了不同叶片的耐霜冻能力。结果表明, 随着温度的降低, 叶片光化学反射指数呈下降趋势。在-8-0°C范围内, PRI及其相对值R_t与温度都存在显著的线性关系; 叶片PRI在0°C、-8°C时的相对值R₀、R_-8, 以及-8-0°C范围中, R_t与温度的回归直线斜率SLP都具有品种特异性, 可以反映不同品种的耐霜冻能力。隶属函数法结合聚类分析结果显示, 在12个候选品种中, 抗霜冻能力最好的是Cabernet Sauvignon, 其R₀、R_-8和SLP分别为72.3%、50.19%和2.78。

关键词: 光化学反射指数, 秋季霜冻, 叶片, 葡萄

Abstract: Leaves of 12 grapevine cultivars were selected as materials and collected in the fall. The photochemical reflectance index (PRI) in leaves was measured after frost treatment. Effective parameters were calculated and used in functional value analysis to compare the cold hardiness of leaves. Cooling temperature led to a trend of declining PRI. PRI and its relative value (R_t) had a good linear relationship with temperature in the range of -8 to 0°C. Relative values at both 0°C and -8°C (R₀, R_-8) differed among cultivars, as did the slope of regressions in the range of -8 to 0°C and can be used as parameters to reflect the cold hardiness of leaves. Functional value analysis and cluster analysis showed that the most cold-hardiness cultivar in leaves was Cabernet Sauvignon (Vitis vinifera), with R₀, R_-8, and SLP values at 72.3%, 50.19%, and 2.78, respectively.

Key words: Photochemical reflectance index, autumn frost, leaf, grapevine

孙鲁龙, 宋伟, 杜远鹏, 翟衡. 光化学反射指数在比较葡萄叶片耐霜冻能力中的应用. 植物学报, 2017, 52(5): 543-549.

Lulong Sun, Wei Song, Yuanpeng Du, Heng Zhai. Application of Photochemical Reflectance Index in Comparing Frost Resistance of Grapevine Cultivars. Chinese Bulletin of Botany, 2017, 52(5): 543-549.

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链接本文: https://www.chinbullbotany.com/CN/10.11983/CBB16123

https://www.chinbullbotany.com/CN/Y2017/V52/I5/543

图/表 5

图1 不同葡萄品种叶片低温处理温度-PRI的关系(A)-(L) 分别为葡萄种质Kyoho、Summer black、Muscat、Moldova、Tangwei Butao、Cabernet Sauvignon、Merlot、Frontenac、Vidal Blanc、Shan Butao、White Riesling和Pinot Chardonnay, 图2同。采用-8-0°C之间的数据进行回归直线拟合, 显著水平为α=0.05。

Figure 1 Temperature-PRI relationships in leaves of different grapevine cultivars (A)-(L) Indicate grapevine cultivars Kyoho, Summer black, Muscat, Moldova, Tangwei Butao, Cabernet Sauvignon, Merlot, Frontenac, Vidal Blanc, Shan Butao, White Riesling and Pinot Chardonnay, respectively, the same as Figure 2. All regressions were conducted for the range of -8°C to 0°C and significant difference at 0.05 levels.

图2 不同葡萄品种叶片温度-Rt的关系(A)-(L)见图1。Rt (%)=PRIt/PRI4°C×100, t=0、-2、-4、-6、-8°C。采用-8-0°C之间的数据进行回归直线拟合, 显著水平为α=0.05。

Figure 2 Temperature-Rt relationships in different grapevine cultivars (A)-(L) See Figure 1. Rt (%)=PRIt/PRI4°C×100, t=0, -2, -4, -6, -8°C. All regressions were conducted for the range of -8°C to 0°C and significant difference at 0.05 levels.

表1 12个葡萄品种叶片R0、R-8和1/SLP比较

Table 1 Comparison of R0, R-8, 1/SLP among 12 grapevine cultivar leaves

	1	2	3	4	5	6	7	8	9	10	11
R₀
1. Kyoho
2. Summer black	*
3. Muscat	*	*
4. Moldova	*	*	*
5. Tangwei Butao	*	*	*	*
6. Cabernet Sauvignon	*	*	*	*	*
7. Merlot	*	*	*	*	*	*
8. Frontenac	*	*	*	*	*	*	*
9. Vidal Blanc	*	*	*	*	*	*	*	*
10. Shan Butao	*	*	*	*	*	*	*	*	*
11. White Riesling	*	*	*	*	*	*	*	*	*	*
12. Pinot Chardonnay	*	*	*	*	*	*	*	*	*	*	*
R_-8
1. Kyoho
2. Summer black	*
3. Muscat	*	*
4. Moldova	*	*	*
5. Tangwei Butao	*	*	*	*
6. Cabernet Sauvignon	*	*	*	*	*
7. Merlot	*	*	*	*	*	*
8. Frontenac	*	*	*	*	*	*	*
9. Vidal Blanc	*	*	*	*	*	*	*	*
10. Shan Butao	*	*	*	*	*	*	*	*	*
11. White Riesling	*	*	*	*	*	*	*	*	*	*
12. Pinot Chardonnay	*	*	*	*	*	*	*	*	*	*	*
1/SLP
1. Kyoho
2. Summer black	*
3. Muscat	*	n
4. Moldova	*	*	*
5. Tangwei Butao	*	*	*	*
6. Cabernet Sauvignon	*	*	*	*	*
7. Merlot	*	*	n	*	*	*
8. Frontenac	*	*	*	*	*	*	*
9. Vidal Blanc	*	*	*	n	*	*	*	*
10. Shan Butao	*	*	n	*	*	*	n	*	*
11. White Riesling	*	*	*	*	*	*	*	*	*	*
12. Pinot Chardonnay	*	*	*	*	*	*	*	*	*	*	*

图3 根据隶属函数值对12个葡萄品种叶片抗冻能力聚类

Figure 3 Cluster analysis of cold hardiness of 12 grapevine cultivar leaves according to functional values

表2 12个葡萄品种叶片的抗寒性隶属函数分析

Table 2 Affiliation function analysis of cold hardiness in lea- ves of 12 grapevine cultivars

Cultivar	R₀	R_-8	1/SLP	Means
Kyoho	0.667	0.644	0.083	0.464
Summer black	0.668	0.298	0	0.322
Muscat	0.513	0.151	0.006	0.223
Moldova	1	0.930	0.023	0.651
Tangwei Butao	0	0	1	0.333
Cabernet Sauvignon	0.977	1	0.057	0.678
Merlot	0.839	0.661	0.012	0.504
Frontenac	0.772	0.591	0.041	0.468
Vidal Blanc	0.874	0.713	0.024	0.537
Shan Butao	0.828	0.623	0.011	0.487
White Riesling	0.946	0.973	0.066	0.662
Pinot Chardonnay	0.525	0.486	0.123	0.378

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