• ISSN 1008-505X
  • CN 11-3996/S
李娟, 章明清, 章赞德, 许文江, 姚宝全. 三元非结构肥效模型提高水稻施肥推荐的可靠性[J]. 植物营养与肥料学报, 2019, 25(2): 311-320. DOI: 10.11674/zwyf.18104
引用本文: 李娟, 章明清, 章赞德, 许文江, 姚宝全. 三元非结构肥效模型提高水稻施肥推荐的可靠性[J]. 植物营养与肥料学报, 2019, 25(2): 311-320. DOI: 10.11674/zwyf.18104
LI Juan, ZHANG Ming-qing, ZHANG Zan-de, XU Wen-jiang, YAO Bao-quan. Increasing precision of fertilizer recommendation using ternary non-structural fertilizer response model[J]. Journal of Plant Nutrition and Fertilizers, 2019, 25(2): 311-320. DOI: 10.11674/zwyf.18104
Citation: LI Juan, ZHANG Ming-qing, ZHANG Zan-de, XU Wen-jiang, YAO Bao-quan. Increasing precision of fertilizer recommendation using ternary non-structural fertilizer response model[J]. Journal of Plant Nutrition and Fertilizers, 2019, 25(2): 311-320. DOI: 10.11674/zwyf.18104

三元非结构肥效模型提高水稻施肥推荐的可靠性

Increasing precision of fertilizer recommendation using ternary non-structural fertilizer response model

  • 摘要:
    目的 针对三元二次多项式肥效模型的设定偏误和多重共线性危害导致建模成功率低的问题,研发三元非结构肥效模型,扩大模型适用性。
    方法 在福建省平和县和仙游县选择了13个水稻氮磷钾田间肥效试验结果作为研究案例。田间试验均采用“3414”设计方案,即:1) N0P0K0;2) N0P2K2;3) N1P2K2;4) N2P0K2;5) N2P1K2;6) N2P2K2;7) N2P3K2;8) N2P2K0;9) N2P2K1;10) N2P2K3;11) N3P2K2;12) N1P1K2;13) N1P2K1;14) N2P1K1。其中,“2”水平为试验前当地氮磷钾推荐施肥量,“0”水平表示不施肥,“1”水平和“3”水平的施肥量分别为“2”水平的50%和150%。在一元非结构肥效模型基础上,利用氮磷钾田间肥效试验结果,在每个试验点分别构建了三元二次多项式肥效模型和三元非结构肥效模型。利用已有的668个水稻“3414”田间试验结果,比较验证了两种模型的拟合效果和推荐施肥量的可靠性。
    结果 在构建的13个三元二次多项式肥效模型中,有2个模型的结果未达到统计显著水平,3个肥效模型属于非典型式,而构建的13个三元非结构肥效模型均得到了典型式。通过668个水稻氮磷钾田间肥效试验结果验证表明,三元二次多项式肥效模型未能通过显著性检验的比例达到30.1%,而三元非结构肥效模型未能通过的比例下降到23.4%。在推荐施肥量外推的非典型式中,三元二次多项式肥效模型的比例为4.0%,而三元非结构肥效模型则提高到30.7%。在系数符号不合理和无最高产量点的两种非典型式类型中,三元二次多项式肥效模型的比例分别达到32.3%和14.4%,而三元非结构肥效模型则分别降低到6.9%和0。三元二次多项式肥效模型的典型式比例仅为19.5%,而三元非结构肥效模型典型式比例则提高到39.1%,是前者的2.0倍,明显提高了田间试验结果的建模成功率。
    结论 大样本田间试验充分证明,相比三元二次多项式肥效模型,采用三元非结构肥效模型进行早、中、晚稻推荐施肥,提高了建模的成功效率和模型的实用性,是可靠性更高的模型。

     

    Abstract:
    Objectives Ternary quadratic polynomial fertilizer response model (TPFM) has low success rate due to setting bias and multicollinearity. A ternary non-structural fertilizer response model (TNFM) was established to expand the model applicability and precision of fertilizer recommendation in rice production.
    Methods Thirteen rice field NPK fertilizer experiments were chosen in Pinghe County and Xianyou County, Fujian Province. Design of “3414” was used in all the thirteen experiments, the treatments were as following: 1) N0P0K0; 2) N0P2K2; 3) N1P2K2; 4) N2P0K2; 5) N2P1K2; 6) N2P2K2; 7) N2P3K2; 8) N2P2K0; 9) N2P2K1; 10) N2P2K3; 11) N3P2K2; 12) N1P1K2; 13) N1P2K1; 14) N2P1K1. Of them, “2” represented current recommended nutrient levels, “1” and “3” represented 50% and 150% of those, and “0” represented no nutrient input. The TPFM and TNFM were established for each experiment. Extra 668 rice field results were collected all over Fujian Province, and used for the verification of the fitting effect and the reliability of fertilization recommendation of the two kinds of models.
    Results Among the established 13 TPFMs, two failed to achieve statistical significance levels and three resulted in non-typical model. While all the 13 TNFMs were typical models, showing less setting bias and multicollinearity. The TPFMs recommended higher nutrient rates than the practical ones, while the TNFMs verified with the 668 field experiments results, 30.1% of the TPFMs failed to pass the significance test, but 23.4% of the TNFMs did not. In the non-typical model that made the recommended fertilization rate by extrapolation, the proportion of the TPFMs was only 4.0%, while that of the TNFMs was increased to 30.7%. In the two types of non-typical models of unreasonable coefficient symbol and without maximum yield point, the proportion of the TPFMs reached to 32.3% and 14.4%, respectively. However, the TNFMs were reduced to 6.9% and zero, respectively, and the proportion of typical model by the TPFMs was only 19.5%. In contrast, using the TNFMs made the proportion of the typical model increase to 39.1%, which was twice of the TPFMs. Hence, the new model significantly improved the modeling success rate.
    Conclusions The ternary non-structural fertilizer response model (TNFM) has a higher fitting accuracy and wider application scope in the modeling of nitrogen, phosphorus and potassium fertilization response of paddy rice.

     

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