中国农业科学 ›› 2015, Vol. 48 ›› Issue (20): 4021-4032.doi: 10.3864/j.issn.0578-1752.2015.20.004

• 耕作栽培·生理生化·农业信息技术 • 上一篇    下一篇

水稻生产目标产量确定的理论与方法探讨

邹应斌,夏冰,蒋鹏,谢小兵,黄敏   

  1. 湖南农业大学农学院,长沙 410128
  • 收稿日期:2014-07-07 出版日期:2015-10-20 发布日期:2015-10-20
  • 通讯作者: 邹应斌,E-mail:ybzou123@126.com
  • 作者简介:邹应斌,E-mail:ybzou123@126.com
  • 基金资助:
    国家水稻产业技术体系栽培与土肥岗位专家项目(CARS-01-34)

Discussion on the Theory and Methods for Determining the Target Yield in Rice Production

ZOU Ying-bin, XIA Bing, JIANG Peng, XIE Xiao-bing, HUANG Min   

  1. College of Agronomy, Hunan Agricultural University, Changsha 410128
  • Received:2014-07-07 Online:2015-10-20 Published:2015-10-20

摘要: 【目的】分析探讨水稻生产目标产量确定的理论与方法。【方法】根据2012—2013年在海南澄迈、广东怀集、广西宾阳、湖南长沙和贵州兴义5个地点进行的不同施氮量(不施氮;中氮:161—176 kg·hm-2;高氮:225 kg·hm-2)、不同品种(杂交稻品种两优培九、Y两优1号和常规稻品种黄华占、玉香油占)大田试验的结果,结合国内外相关文献报道进行分析探讨。【结果】大田试验表明,即使同一基因型水稻品种的产量也存在显著或极显著地点间差异。在施氮条件下(中氮和高氮),各试验地点的平均产量以兴义点最高(两优培九:13.20—13.54 t·hm-2,Y两优1号:13.50—13.78 t·hm-2,黄华占:11.26—11.42 t·hm-2,玉香油占:11.32—11.45 t·hm-2),其次为长沙、澄迈、宾阳,而怀集点最低(两优培九:6.66—6.71 t·hm-2,Y两优1号:6.96—7.20 t·hm-2,黄华占:6.96—7.11 t·hm-2,玉香油占:7.35—6.86 t·hm-2)。同样,各试验地点的平均基础地力产量(不施氮处理)也是以兴义点最高(10.52 t·hm-2),其次为长沙、澄迈、宾阳,怀集点最低(4.53 t·hm-2)。水稻施肥产量(YF)极显著地依赖于基础地力产量(YS),中氮和高氮条件下的回归方程分别为YF﹦0.814YS3.337R2﹦0.824)和YF﹦0.864YS3.094R2﹦0.839),5个地点和4个品种基础地力产量贡献率(基础地力产量占施肥产量的百分率)平均为64.8%—85.5%和72.7%—79.3%。对国内外相关文献中数据(n= 315)进行分析也显示,水稻施肥产量与基础地力产量呈显著正相关关系(YF﹦1.031YS+2.421,R2=0.523),基础地力产量贡献率平均达到67.7%。此外,研究结果还显示,施肥增产量与基础地力产量贡献率呈极显著的负相关关系;水稻产量与植株氮素吸收量和施氮量呈显著或极显著的二次曲线关系。【结论】水稻目标产量的制定应因地而异,即“因地定产”。基础地力产量是土壤肥力和气候生产力的综合反映,可作为水稻生产目标产量确定的依据,通过基于基础地力产量的回归方程来确定水稻高产栽培的目标产量。培肥土壤地力是实现水稻目标产量栽培的重要举措。

关键词: 水稻, 基础地力产量, 基础地力产量贡献率, 目标产量

Abstract: 【Objective】The aim of this study was to discuss the theory and methods for determining the target yield in rice production. 【Methods】The discussion and analysis were based on the results of field experiments conducted in five locations (Chengmai of Hainan Province, Huaiji of Guangdong Province, Binyang of Guangxi Province, Changsha of Hunan Province, and Xingyi of Guizhou Province) in South China with different N application rates (zero N application; moderate N rate: 161—176 kg·hm-2; high N rate: 225 kg·hm-2) and varieties (hybrid varieties Liangyoupeijiu and Y-liangyou 2 and inbred varieties Huanghuazhan and Yixiangyouzhan ) in 2012 and 2013, and the reports of relevant literature in China and abroad.【Results】The field experiments showed that the yield performance of even the same rice variety exhibited significant or extremely significant differences among the five locations. Under N application conditions (moderate and high N rates), Xingyi had the highest average yield (Liangyoupeijiu: 13.20-13.54 t·hm-2, Y-liangyou 1: 13.50-13.78 t·hm-2, Huanghuazhan: 11.26-11.42 t·hm-2, Yuxiangyouzhan: 11.32-11.45 t·hm-2), followed by Changsha, Chengmai, Binyang, and Huaiji had the lowest average yield (Liangyoupeijiu: 6.66-6.71 t·hm-2, Y-liangyou 1: 6.96-7.20 t·hm-2, Huanghuazhan: 6.96-7.11 t·hm-2, Yuxiangyouzhan: 7.35-6.86 t·hm-2). Similarly, the highest average soil-based yield (yield of no N application treatment) was recorded in Xingyi (10.52 t·hm-2), followed by that in Changsha, Chengmai and Binyang, and the lowest average soil-based yield was recorded in Huaiji (4.53 t·hm-2). The rice yield under fertilized conditions (namely fertilized yield) (YF) depended extremely significantly on the soil-based yield (YS). The regression equations under moderate and high N rates were YF=0.814YS+3.337 (R2=0.824) and YF﹦0.864YS+3.094 (R2=0.839), respectively. The contributions of the soil-based yield (the percentage of the soil-based yield in the fertilized yield) ranged from 64.8% to 85.5% on the average of five locations and from 72.7% to 79.3% on the average of four varieties. The analysis of the data (n=315) collected from previous studies also indicated that there was a significant positive linear relationship between the soil-based yield and the fertilized yield (YF=1.031YS+2.421, R2=0.523), and the average contribution of the soil-based yield was 67.7%. In addition, the results showed that yield increased by fertilization was tightly negatively related with soil-based yield contribution; grain yield was significantly quadratically related to plant N uptake and N application rate.【Conclusions】Target yield should be varied from site to site. Soil-based yield comprehensively reflects the paddy soil fertility and the climate productivity, and therefore can be used as the basis to determine the target yield in rice production. The target yield for high yielding cultivation of rice can be determined by the regression equation based on the soil-based yield. Improving soil fertility is an important approach for achieving the target yield.

Key words: rice, soil-based yield, soil-based yield contribution, target yield