山东省冬小麦产量差与氮肥利用效率差形成机理解析

doi:10.3864/j.issn.0578-1752.2022.16.004

摘要/Abstract

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。

关键词: 冬小麦, 产量差, 氮肥偏生产力差, 产量性能分析

Abstract:

【Objective】 Four planting patterns were designed based on survey data to simulate four different yield levels of winter wheat to quantify the yield gap and nitrogen use efficiency gap in Shandong province, to analyze the relationship between yield gap and nitrogen use efficiency gap, and to clarify the contribution of the environment, cultivation conditions and physiological parameters to the yield gap, so as to explore possible ways to synergistically narrow yield gap and increase resource utilization efficiency. 【Method】 This experiment was carried out in Jining, Dezhou, Yantai and Zibo in Shandong from 2016 to 2020. Four treatments were set through comprehensive management measures, such as selection of varieties, fertilizer input, planting density, and irrigation level, which were super-high yield level (SH), high-yield and high-efficiency level (HH), farmer level (FP), and basic yield level (ISP). The yield gap and nitrogen use efficiency gap between different yield levels were analyzed quantitatively to explore the influencing factors of yield gap and nitrogen use efficiency gap and the way to narrow yield gap and increase nitrogen use efficiency. 【Result】 The yield gap between the current high-yield record of wheat in Shandong and SH, SH and HH, HH and FP, FP and ISP were 2 729.1, 674.3, 1 042.9 and 4 349.8 kg·hm^-2, respectively. The partial production efficiency gap of nitrogen between SH and HH, HH and FP were -13.54 and 15.67 kg·kg^-1, respectively. There was a quadratic equation between the yield and the partial production efficiency of nitrogen. The contribution rate of the current uncontrollable factors (precipitation, temperature, etc.) and controllable factors (resource input, etc.) to the yield gap were 31.16% and 68.84%, respectively. The results showed that the gap of mean leaf area index (MLAI), mean net assimilation rate (MNAR), ear number per unit area (EN) and grain weight (GW) were significantly positively correlated with the yield gap between SH and HH (YG_Ⅱ). The gap of harvest index (HI), grain number per spike (GN) and grain weight (GW) were positively correlated with the yield gap between HH and FP (YG_Ⅲ). SH and HH treatments had higher aboveground biomass, number of ears per plant and percentage of earring-tillers than FP treatment. 【Conclusion】 At present, the yield level of winter wheat of farmers in Shandong had only achieved 64.34% of the highest recorded yield. Cultivation measures, such as optimizing fertilizer and water input, increasing the proportion of topdressing, and increasing the application of organic fertilizer and zinc fertilizer, could reduce the yield gap by 23.46%, and increase the partial production efficiency of nitrogen by 56.99%. The post-anthesis material production capacity was still the limiting factor for wheat yield improvement. However, when ensuring the light contract after anthesis, increasing the re-transportation of pre-anthesis stored dry matter to improve the harvest index was an effective measure to synergistically improve yield and nitrogen use efficiency.

Key words: winter wheat, yield gap, nitrogen fertilizer partial productivity gap, yield performance analysis

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.

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管理措施 Management pattern		种植模式 Planting pattern
管理措施 Management 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 (×10⁴plant·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

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

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
		当前不可控因素 Uncontrolled 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

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
MLAI_FP-ISP	YG_IV	y=0.647x+0.102	0.4825 **	EN_FP-ISP	YG_IV	y=0.568x+0.166	0.3828 **
MLAI_HH-FP	YG_III	y=0.077x+0.554	-0.0620	EN_HH-FP	YG_III	y=-0.196x+0.388	-0.0149
MLAI_SH-HH	YG_II	y=0.779x+0.023	0.4861 **	EN_SH-HH	YG_II	y=0.868x+0.192	0.8343 **
				EN_HR-SH	YG_I	y=0.447x+0.354	0.1586
MNAR_FP-ISP	YG_IV	y=0.888x-0.132	0.7237 **	GN_FP-ISP	YG_IV	y=0.715x+0.244	0.5825 **
MNAR_HH-FP	YG_III	y=-0.055x+0.437	-0.0676	GN_HH-FP	YG_III	y=0.794x-0.001	0.7256 **
MNAR_SH-HH	YG_II	y=0.890x+0.176	0.5283 **	GN_SH-HH	YG_II	y=0.543x+0.334	0.1322
				GN_HR-SH	YG_I	y=-0.521x+0.963	0.2778
HI_FP-ISP	YG_IV	y=-0.295x+0.586	0.1028	GW_FP-ISP	YG_IV	y=0.365x+0.402	0.1051
HI_HH-FP	YG_III	y=1.042x+0.141	0.6837 **	GW_HH-FP	YG_III	y=0.755x+0.184	0.4593 **
HI_SH-HH	YG_II	y=0.084x+0.496	-0.0645	GW_SH-HH	YG_II	y=0.592x+0.016	0.3585 **
				GW_HR-SH	YG_I	y=0.843x+0.018	0.5874 **