| 基于RAGA的PPC模型评价水分胁迫对寒区水稻生长和产量的影响 |
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| 引用本文： | 徐淑琴,付 强,董淑喜,季 飞,王克全.基于RAGA的PPC模型评价水分胁迫对寒区水稻生长和产量的影响[J].农业工程学报,2009,25(13):29-33. |
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| 作者姓名： | 徐淑琴 付 强 董淑喜 季 飞 王克全 |
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| 作者单位： | 东北农业大学水利与建筑学院，哈尔滨 150030;东北农业大学水利与建筑学院，哈尔滨 150030;东北农业大学水利与建筑学院，哈尔滨 150030;东北农业大学水利与建筑学院，哈尔滨 150030;东北农业大学水利与建筑学院，哈尔滨 150030 |
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| 基金项目： | 黑龙江省农垦总局科技攻关项目（HNKSV-13）；黑龙江省科技攻关项目（GB06B106-7）；东北农业大学创新团队项目 |
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| 摘 要： | 针对水分胁迫对水稻生育和产量的综合影响很难直观判断的问题，该文提出了评价水稻综合指标的投影寻踪方法，该方法可以依据样本自身的数据特性寻求最佳投影方向，利用最佳投影方向判断各评价指标对综合评价目标的贡献大小。采用实码加速遗传算法进行PPC建模，简化了投影寻踪技术的实现过程，克服了投影寻踪技术计算复杂、编程实现困难的缺点。评价结果表明，拔节期受旱对生育综合指标影响较大，分蘖期受旱由于时间较长，生育综合指标也较差。水稻生育期连旱对生理指标以及产量影响最为严重。应用RAGA算法的PPC模型评价水稻水分胁迫情况下生育综合指标排序结论比较可靠，这对制定水稻调亏灌溉制度具有应用价值。
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| 关 键 词： | 干旱，模型，灌溉，水稻，水分胁迫，生育指标，RAGA-PPC，调亏灌溉 |
| 收稿时间： | 2008/1/22 0:00:00 |
| 修稿时间： | 2009/9/14 0:00:00 |
Evaluation of effects of water stress on growing and yield of paddy based on RAGA-PPC model in cold area |
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| Xu Shuqin,Fu Qiang,Dong Shuxi,Ji Fei and Wang Kequan.Evaluation of effects of water stress on growing and yield of paddy based on RAGA-PPC model in cold area[J].Transactions of the Chinese Society of Agricultural Engineering,2009,25(13):29-33. |
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| Authors: | Xu Shuqin Fu Qiang Dong Shuxi Ji Fei and Wang Kequan |
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| Institution: | College of Water Conservancy and Architecture, Northeast Agricultural University, Harbin 150030, China,College of Water Conservancy and Architecture, Northeast Agricultural University, Harbin 150030, China,College of Water Conservancy and Architecture, Northeast Agricultural University, Harbin 150030, China,College of Water Conservancy and Architecture, Northeast Agricultural University, Harbin 150030, China and College of Water Conservancy and Architecture, Northeast Agricultural University, Harbin 150030, China |
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| Abstract: | In order to solve the difficulty of judging the comprehensive effects of water stress on the growing and yield of rice, projection pursuit classification (PPC for short) model was presented. It could calculate the best projection direction based on the sample data characteristics. Through the best projection direction, the contributions of each evaluation index to the comprehensive evaluation target could be judged. The PPC model based on real coded accelerating genetic algorithm (RAGA-PPC for short) can simplify the realized process of PPC model, and overcome the shortcomings of complex calculation and difficulty of programming in traditional PPC model. The results showed that comprehensive growing index was influenced greatly by drought in jointing stage. It was also worse because of the long time drought in tillering stage. At the same time, continuous drought in growth duration of rice had most serious effects on the physiological parameters and yield. It was reliable to apply the RAGA-PPC model to evaluate the order result of comprehensive growing index under water stress conditions. The model has great significance in establishing regulated deficit irrigation system of rice. |
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| Keywords: | drought models irrigation rice water stress growing index RAGA-PPC regulated deficit irrigation |
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