中国农业科学 ›› 2022, Vol. 55 ›› Issue (16): 3110-3122.doi: 10.3864/j.issn.0578-1752.2022.16.004
韩守威1,2(),司纪升1,余维宝1,2,孔令安1,张宾1,王法宏1,张海林2,赵鑫2,李华伟1(),孟鈺1
收稿日期:
2022-01-20
接受日期:
2022-04-14
出版日期:
2022-08-16
发布日期:
2022-08-11
通讯作者:
李华伟
作者简介:
韩守威,E-mail: 基金资助:
HAN ShouWei1,2(),SI JiSheng1,YU WeiBao1,2,KONG LingAn1,ZHANG Bin1,WANG FaHong1,ZHANG HaiLin2,ZHAO Xin2,LI HuaWei1(),MENG Yu1
Received:
2022-01-20
Accepted:
2022-04-14
Online:
2022-08-16
Published:
2022-08-11
Contact:
HuaWei LI
摘要:
【目的】量化山东省冬小麦产量差及氮肥利用效率差,分析产量差和效率差之间的关系,明确环境、栽培条件及生理因素对产量差的贡献,探讨协同缩差增效的可能途径,为冬小麦产量差缩减和资源利用效率提升提供理论依据。【方法】本试验于2016—2020年在山东济宁、德州、烟台和淄博4市进行,综合肥料投入、播种密度和灌溉水平等管理措施,设置了超高产水平(SH)、高产高效水平(HH)、农户水平(FP)和基础产量水平(ISP)4种模式,定量分析不同产量水平冬小麦产量差和氮肥利用效率差,分析产量差和效率差之间关系,讨论产量差和效率差形成的影响因素及缩差增效的可能途径。【结果】当前山东冬小麦高产纪录与SH、SH与HH、HH与FP以及FP与ISP之间的产量差分别为2 729.1、674.3、1 042.9和4 349.8 kg·hm-2,SH与HH、HH与FP之间的氮肥偏生产力差分别为-13.54和15.67 kg·kg-1;产量和氮肥偏生产力之间存在着二次抛物线关系。当前降水、光温等不可控因素和肥水投入等可控因素对产量差的贡献率分别为31.16%和68.84%。结果显示,平均叶面积指数(MLAI)、平均净同化率(MNAR)、单位面积穗数(EN)和粒重(GW)差与SH和HH之间的产量差呈显著正相关关系;而收获指数(HI)、穗粒数(GN)和粒重(GW)差与HH和FP之间的产量差呈显著正相关。SH和HH处理较FP处理有更高的地上部生物量、单株分蘖数以及分蘖成穗率。【结论】当前山东省冬小麦农户产量只实现了最高纪录产量的64.34%,通过优化水肥投入量、提高追肥比例、增施有机肥和锌肥等栽培措施可使冬小麦产量差缩减23.46%,氮肥偏生产力提高56.99%。花后物质生产能力仍然是小麦产量提升的限制因素,在保证花后光合同化的同时,提高花前物质的再转运以提高收获指数是农户模式向高产高效发展的有效途径。
韩守威,司纪升,余维宝,孔令安,张宾,王法宏,张海林,赵鑫,李华伟,孟鈺. 山东省冬小麦产量差与氮肥利用效率差形成机理解析[J]. 中国农业科学, 2022, 55(16): 3110-3122.
HAN ShouWei,SI JiSheng,YU WeiBao,KONG LingAn,ZHANG Bin,WANG FaHong,ZHANG HaiLin,ZHAO Xin,LI HuaWei,MENG Yu. Mechanisms Analysis on Yield Gap and Nitrogen Use Efficiency Gap of Winter Wheat in Shandong Province[J]. Scientia Agricultura Sinica, 2022, 55(16): 3110-3122.
表1
不同种植模式冬小麦种植密度及肥料运筹"
管理措施 Management pattern | 种植模式 Planting pattern | ||||
---|---|---|---|---|---|
SH Super-high yield level | HH High-yield and high-efficiency level | FP Farmer level | ISP Basic yield level | ||
基本苗Basic seedlings (×104 plant·hm-2) | 375 | 300 | 450 | 450 | |
肥料运筹 Fertilizer management | 氮肥 N (kg·hm-2) | 270 | 210 | 360 | 0 |
磷肥 P (kg·hm-2) | 150 | 120 | 120 | 0 | |
钾肥 K (kg·hm-2) | 150 | 120 | 120 | 0 | |
基追比Dressing ratio | 5﹕5 | 4﹕6 | 6﹕4 | 0 | |
锌肥ZnSO4(kg·hm-2) | 30 | 30 | 0 | 0 | |
有机肥 Organic fertilizer (kg·hm-2) | 7500 | 3000 | 0 | 0 |
表2
2016年试验地0—20 cm土壤及部分调研超高产地块土壤理化性质"
类别 Class | 年份 Year | 地点 Site | 全氮 Total nitrogen (g·kg-1) | 碱解氮 Available nitrogen (mg·kg-1) | 速效磷 Available phosphorus (mg·kg-1) | 速效钾 Available potassium (mg·kg-1) | 有机质 Organic matter (g·kg-1) |
---|---|---|---|---|---|---|---|
试验地块 Test plot | 2016 | 济宁 Jining | 1.45 | 89.09 | 54.42 | 117.85 | 11.02 |
德州 Dezhou | 1.36 | 81.29 | 49.88 | 127.44 | 10.61 | ||
烟台 Yantai | 1.29 | 75.66 | 62.51 | 102.31 | 11.82 | ||
淄博 Zibo | 1.40 | 78.99 | 53.44 | 109.81 | 10.29 | ||
最高产量地块 Highest yield plot | 2018 | 烟台 Yantai | 1.53 | 92.33 | 61.19 | 139.98 | 20.81 |
2019 | 济宁 Jining | 1.61 | 90.88 | 58.88 | 137.71 | 21.93 | |
2019 | 淄博 Zibo | 1.49 | 95.42 | 59.34 | 145.98 | 23.22 |
表3
各因素对产量差贡献率"
年份 Year | 地点 Site | 贡献率 Contribution rate (%) | |||
---|---|---|---|---|---|
当前不可控因素 Uncontrolled factor | 可控因素 Controllable factor | ||||
大量资源投入 Excess nutrients input | 优化栽培措施 Optimized cultivation measure | 当前农艺水平 Current crop management | |||
2016-2017 | 济宁 Jining | 26.38 | 10.87 | 9.66 | 53.09 |
德州 Dezhou | 34.16 | 10.81 | 12.31 | 42.73 | |
烟台 Yantai | 31.68 | 1.73 | 38.71 | 27.88 | |
淄博 Zibo | 37.31 | 4.32 | 14.82 | 43.56 | |
2017-2018 | 济宁 Jining | 37.29 | 8.61 | 21.58 | 32.52 |
德州 Dezhou | 39.27 | 4.26 | 7.88 | 48.59 | |
烟台 Yantai | 43.78 | 3.20 | 4.42 | 48.59 | |
淄博 Zibo | 41.84 | 7.69 | 7.93 | 42.54 | |
2018-2019 | 济宁 Jining | 38.54 | 7.31 | 9.41 | 44.74 |
德州 Dezhou | 29.67 | 8.88 | 16.06 | 45.39 | |
烟台 Yantai | 21.55 | 14.90 | 4.26 | 59.30 | |
淄博 Zibo | 26.19 | 11.32 | 4.37 | 58.12 | |
2019-2020 | 济宁 Jining | 19.47 | 7.80 | 13.83 | 58.91 |
德州 Dezhou | 18.16 | 7.79 | 12.21 | 61.85 | |
烟台 Yantai | 25.96 | 3.26 | 11.74 | 59.04 | |
淄博 Zibo | 27.41 | 10.25 | 5.43 | 56.92 | |
平均 Average | 31.16 | 7.69 | 12.16 | 48.99 |
表4
产量差与产量性能参数差的相关关系"
光合性能参数差 Photosynthetic performance parameter gap (x) | 产量差 Yield gap (y) | 相关方程 Correlation equation | 相关系数 Correlation coefficient | 产量构成参数差 Yield composition parameter gap (x) | 产量差 Yield gap (y) | 相关方程 Correlation equation | 相关系数 Correlation coefficient | |
---|---|---|---|---|---|---|---|---|
MLAIFP-ISP | YGIV | y=0.647x+0.102 | 0.4825 ** | ENFP-ISP | YGIV | y=0.568x+0.166 | 0.3828 ** | |
MLAIHH-FP | YGIII | y=0.077x+0.554 | -0.0620 | ENHH-FP | YGIII | y=-0.196x+0.388 | -0.0149 | |
MLAISH-HH | YGII | y=0.779x+0.023 | 0.4861 ** | ENSH-HH | YGII | y=0.868x+0.192 | 0.8343 ** | |
ENHR-SH | YGI | y=0.447x+0.354 | 0.1586 | |||||
MNARFP-ISP | YGIV | y=0.888x-0.132 | 0.7237 ** | GNFP-ISP | YGIV | y=0.715x+0.244 | 0.5825 ** | |
MNARHH-FP | YGIII | y=-0.055x+0.437 | -0.0676 | GNHH-FP | YGIII | y=0.794x-0.001 | 0.7256 ** | |
MNARSH-HH | YGII | y=0.890x+0.176 | 0.5283 ** | GNSH-HH | YGII | y=0.543x+0.334 | 0.1322 | |
GNHR-SH | YGI | y=-0.521x+0.963 | 0.2778 | |||||
HIFP-ISP | YGIV | y=-0.295x+0.586 | 0.1028 | GWFP-ISP | YGIV | y=0.365x+0.402 | 0.1051 | |
HIHH-FP | YGIII | y=1.042x+0.141 | 0.6837 ** | GWHH-FP | YGIII | y=0.755x+0.184 | 0.4593 ** | |
HISH-HH | YGII | y=0.084x+0.496 | -0.0645 | GWSH-HH | YGII | y=0.592x+0.016 | 0.3585 ** | |
GWHR-SH | YGI | y=0.843x+0.018 | 0.5874 ** |
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