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引用本文:宋子凡,吴凤平,王 辉,等.增氧与补肥对洞庭湖区旱涝急转下水稻减产规律的影响[J].灌溉排水学报,2024,43(5):22-29.
SONG Zifan,WU Fengping,WANG Hui,et al.增氧与补肥对洞庭湖区旱涝急转下水稻减产规律的影响[J].灌溉排水学报,2024,43(5):22-29.
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增氧与补肥对洞庭湖区旱涝急转下水稻减产规律的影响
宋子凡,吴凤平,王 辉,黎小东,贺翠华,欧阳赞
1.湖南农业大学 水利与土木工程学院,长沙 410128; 2.湖南省水利水电勘测设计规划研究总院有限公司,长沙 410007
摘要:
【目的】阐明增氧和补肥对旱涝急转条件下水稻产量的影响。【方法】基于桶栽试验,以当地广泛种植的晚稻品种(野湘优航1573)为供试材料,设置干旱(X1,土壤含水率占田间持水率百分比)、淹涝(X2,淹没植株的高度)、增氧(X3,灌溉水溶氧量)、补肥(X4,复合肥施用量)4个因素,以当地农户水肥管理(CK)和单一旱涝急转处理(DF)为对照,采用二次饱和D-最优设计建立了四因素与产量的二次回归模型,研究了4个因素对水稻产量影响的主效应、单因素效应、交互效应及最优方案。【结果】影响水稻产量的主效应排序依次为:淹涝>增氧>补肥>干旱;交互效应强弱依次为:增氧-补肥?干旱-增氧?干旱-淹涝?干旱-补肥?淹涝-增氧?淹涝-补肥,轻旱有利于发挥增氧和补肥措施的减损效果,重度干旱与重度淹涝对水稻具有叠加减产作用。水稻产量随干旱和补肥水平的增加呈先增后减的变化趋势,随淹涝程度增加总体呈下降趋势,随增氧水平增加总体呈上升趋势。基于模型寻优得到了不同目标产量下的各因素最佳组合方案,与CK相比,增氧和补肥条件下的水稻产量平均降低了39.47%,而DF处理下的水稻产量平均降低了49.01%。【结论】4个因素与产量的二次回归模型具有良好的拟合效果(R2=0.978,F=118.55,P<0.01),可为洞庭湖区水稻应对旱涝急转灾害提供理论依据。
关键词:  旱涝急转;水稻产量;增氧;补肥;交互作用
DOI:10.13522/j.cnki.ggps. 2023415
分类号:
基金项目:
Efficacy of oxygenation and fertilization in ameliorating rice yield reduction due to rapid shift from drought to flooding in Dongting Lake area
SONG Zifan, WU Fengping, WANG Hui, LI Xiaodong, HE Cuihua, OUYANG Zan
1. College of Water Resources and Civil Engineering, Hunan Agricultural University, Changsha 410128, China; 2. Hunan Provincial Water Resources and Hydropower Survey, Design and Planning Research Institute Co., Ltd, Changsha 410007, China
Abstract:
【Objective】 Prolonged drought followed by flooding is a phenomenon facing rice production in southern China. This paper investigates the efficacy of fertilization and oxygenation in mitigating rice yield reduction induced by a rapid shift from drought to flooding.【Method】 The experiment was conducted in pots, with the locally grown late rice variety Yexiangyouhang 1 573 used as the model plant. The severity of drought was mimicked by controlling the soil water content at a percentage of the field capacity, and the flooding was mimicked by keeping a water level on the soil surface; oxygenation was to dissolve oxygen into the irrigation water. Conventional irrigation and fertilization used locally was taken as the control. All treatments considered a single shift from drought to flooding, and they differed only in drought and flooding severity. A quadratic regression model was used to describe the relationship between rice yield and the four factors, with model coefficients being estimated by the quadratic saturated D-optimal design. 【Result】① The effect of a single factor on the rice yield was ranked in the order of: flooding > oxygenation > fertilization > drought. The two-factor effect on the rice yield was ranked in the order of: oxygenation -fertilization > drought-oxygenation > drought-flooding > drought-fertilization > flooding-oxygenation > flooding-fertilization. A light drought can improve the efficacy of oxygenation and fertilization in mitigating the yield reduction, but severe drought and flooding substantially reduced the rice yield. ② With the increase in drought and fertilization, rice yield increased first and then declined; increasing flooding severity led to a yield reduction; increasing oxygenation increased yield. ③ Optimization calculation showed, compared to the CK, oxygenation and fertilization can ameliorate the yield reduction to 39.47% on average, compared with the average yield reduction of 49.01% without fertilization and oxygenation.【Conclusion】The proposed model accurately describes the effect of drought, flooding, fertilization and oxygenation on rice yield, with R2=0.978, F=118.55 and P<0.01. It can be used to assess the efficacy of different methods for mitigating rice yield reduction caused by a rapid shift from drought to flooding under different conditions in the Dongting Lake area.
Key words:  rapid changes in drought and flood; rice yield; oxygen; fertilizer; interaction