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3种综合评价法在葡萄砧穗组合环境适应性中的应用 被引量:9

Comparison of three comprehensive evaluation methods to evaluate the grape rootstock-scion combination environmental adaptability
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摘要 【目的】选择一种最适宜的数学分析方法评价设施葡萄砧穗组合的环境适应性。【方法】测定9个葡萄砧穗组合的环境适应性参数,分别用熵值法、主成分分析法、Topsis评价法3种方法进行综合评价。【结果】用熵值法进行综合评价时,‘87-1’/‘抗砧1号’组合的环境适应性最强,‘87-1’/‘华葡1号’组合最差;用主成分分析综合评价时,‘87-1’/3309C组合环境适应性最强,‘87-1’/101-14组合最差。用Topsis法进行评价时,‘87-1’/3309C组合环境适应性最强,‘87-1’/‘抗砧1号’组合最差。3种方法的结果差异主要与其计算所得的权重差异、方法理论差异、数据标准化处理差异等有关。在葡萄砧穗组合的环境适应性评价中,由于环境适应性参数数据量小,专业性强,重要参数离散程度小,结合各砧穗组合的实际表现,以Topsis评价法的评价结果更符合实际情况。【结论】葡萄砧穗组合环境适应性评价更适合采用Topsis方法,‘87-1’/3309C组合环境适应性最好。 [Objective] Using three kinds of evaluate methods including principal component analysis, entropy evaluation method and topsis method to evaluate different rootstock-scions combinations' environmental adaptability. And comparing the difference between the three evaluation methods, then selecting a kind of suitable method to evaluate the environmental adaptability of nine kinds of rootstock-scion combinations. [Methods] By measuring '87-1' grape different rootstock-scion combinations environmental adaptability indicators such as apparent quantum yield, light combination point, dark respiration rate, carboxylation efficiency, carbon dioxide combination point, net photosynthetic rate in high temperature and so on, and using principal component analysis, entropy evaluation method and topsis method to evaluate their environmental adaptability, respectively. These rootstock-scion combinations include '87-1'/' Beta', '87-1'/1103P, '87-1'/101-14, '87-1'/3309C, '87-1'/140Ru, '87-1'/5C, '87-1'/SO4, '87-1'/ 'Huapu No.l' as well as '87-1'/'Kangzhen No.1' rootstock-scions combinations. Their spacing in the rows and spacing between rows are 2.5 m×4.0 m, double plant colonization, oblique dry horizontal dragon shape with horizontal curtain, taking the integration of water and fertilizer, and other managements are routine. Trees were planted in grape center technology demonstration areas of Fruit Research Institute of Chinese Academy of Agricultural Sciences (Xingeheng, Liaoning province. What' s more, choosing the cloudless morning, using Li-6400 Photosynthesis instrument to measure the light response curves, carbon response curves and temperature response of different rootstock-scions combinations' optimal function leaf. The select of optimal function leaf is by using Li-6400 Photosynthesis instrument to mea- sure some function leaves of different rootstock-scions combinations, then chose the leaves with the largest net photosynthetic rate. After finding optimal function leaves, then began to measure three kinds of response curves. First of all, the carbon dioxide concentration is set 400 μmol · mo1-1, temperature is set 25 ℃, gas velocity is set 500 mmol· s-1, photosynthetically active radiation is set 2 000, 1 800, 1 500, 1 200, 800, 400, 200, 100, 50, 20, 0 μmol· m-2· s-1 from strong to weak, then measuring light response curve. Secondly, photosynthetically active radiation is set 1 200 μmol·m-2· s-1, temperature is set 25 ℃, gas velocity is set 500 mmol· s-1, carbon dioxide concentration is set 2 000, 1 800, 1 500, 1 200, 1 000, 800, 400, 400, 200, 150, 100, 50, 20 μmol·mol-1 from high to low, then measuring carbon dioxide response curve. Finally, photosynthetically active radiation is set 1 200 μmol· m-2· s-1, carbon dioxide concentration is set 400 μmol· mol-1, gas velocity is set 500 mmol· s-1, temperature is set 22, 25, 27, 30, 32, 35 ℃ from low to high, then measuring net photosynthetic rate. After obtain the data, employing right angle hyperbolic correction model to obtain apparent quantum yield, light combination point, carboxylation efficiency, carbon dioxide combination point, dark respiration rate. Comparing and analyzing the three kinds of comprehensive methods, selecting a kind of suitable methods to evaluate nine kinds of root- stock-scion combinations environmental adaptability. [ Results ] The results show when use entropy evaluation method to evaluate '87-1 '/'Kangzhen No.l' rootstock-scion combination environmental adaptability is the best, ' 87- 1 '/5C, ' 87- 1 '/SO4, ' 87- 1 '/1103P rootstockscion combinations are inferior to ' Kangzhen No.l' combination, the worst rootstock-scion combination is '87-1 '/'Huapu No. 1' combination. When use principal component analysis method to evaluate, '87-i '/3309C rootstock-scion combination environmental adaptability is also the best. '87-1 '/'Huapu No.1 ', '87-1 '/'Beta', '87-1 '/SO4 rootstock-scion combinations environmental adaptability are inferior to '87-1 '/3309C rootstock-scion combination. ' 87-1' / 101-14 rootstock- scion combination environmental adaptability is the worst. When use topsis method to evaluate, '87-1 '/3309C rootstock-scion combination environmental adaptability is the best, ' 87-1'/5 C, ' 87-1' / 101 - 14, ' 87-1'/' B eta' rootstock-scion combinations environmental adaptability are inferior to ' 87-1'/3309C rootstock-scion combination. ' 87-1'/' Kangzhen No.l' rootstock- scion combination is the worst. The difference of three evaluation methods mainly depend on their weight difference, method theoretical difference. In the evaluation of grape rootstock-scion combination environmental adaptability, because the environmental adaptability parameter data are not many, and they are strong professional, some important parameters discrete degree are small, topsis method is more suitable for the experimental data evaluation. [ Conclusion ] Topsis methods is better than principal component analysis and entropy evaluation method when it come to more evaluating ' 87-1 ' grape rootstock-scions combinations' environmental adaptability. And '87-1'/3309C rootstock-scion combination environmental adaptability is the best in the nine kinds of rootstock-scion combination.
出处 《果树学报》 CAS CSCD 北大核心 2017年第10期1349-1356,共8页 Journal of Fruit Science
基金 中国农业科学院科技创新工程(CAAS-ASTIP-2015-RIP-04) 国家现代农业产业技术体系建设(nycytx-30-zp) 农业部"948"重点项目(2011-G28) 国家自然科学基金(41101573)
关键词 '87-1’葡萄 砧穗组合 环境适应性 熵值法 主成分分析法 Topsis评价法 '87-1' grape Root stock-scion combination Environmental adaptability Entropy evaluation method Principal component analysis Topsis method
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