无人机叶面喷施梯度微肥对不同品种冬小麦籽粒矿质元素的影响

doi:10.13560/j.cnki.biotech.bull.1985.2020-1434

摘要/Abstract

摘要：

采用二因素裂区设计,对3个小麦品种在4种不同铁、锌、硒浓度水平下进行无人机叶面喷施,探究其对籽粒中的铁、锌、硒以及其它矿物元素含量的影响,以寻求最佳叶面喷施浓度组合及小麦品种。结果表明,郑麦0943在中浓度（2.5% FeSO₄·7H₂O + 2.5% ZnSO₄·7H₂O + 0.1% Na₂SeO₃）处理下可显著提高其籽粒铁、锌、硒含量;百农AK58及郑育麦958籽粒锌含量在不同浓度（T1：0.5% FeSO₄·7H₂O + 0.5% ZnSO₄·7H₂O + 0.02% Na₂SeO₃、T2：2.5% FeSO₄·7H₂O + 2.5% ZnSO₄·7H₂O + 0.1% Na₂SeO₃、T3：5% FeSO₄·7H₂O + 5% ZnSO₄·7H₂O + 0.2% Na₂SeO₃）处理下均可显著提高,籽粒铁、硒含量在不同浓度处理下变化均不显著。品种、叶面肥浓度及其互作对籽粒铁、锌、硒含量的影响均存在显著差异,其中品种为主要影响因素,其次是叶面肥的浓度。无人机叶面喷施不同浓度的铁、锌、硒混合微肥对3个小麦品种籽粒P、Ca、Mg、Cu、Mn的含量整体影响不大。在本实验处理下可显著提高小麦籽粒铁、锌、硒含量,达到营养强化目的,富铁小麦强化可以种植百农AK58,富锌小麦强化可以种植百农AK58及郑麦0943,富硒小麦强化可以种植郑麦0943。

关键词: 无人机, 叶面喷施, 微肥, 小麦, 矿质元素

Abstract:

A two-factor split-plot design method was adopted to conduct UAV foliar spraying in 3 wheat varieties at 4 different concentrations of iron,zinc and selenium,in order to explore their influences on the contents of iron,zinc,selenium and other mineral elements in grains,so as to seek the optimal combination of foliar spraying concentration and wheat varieties. The results showed that the grains’iron,zinc and selenium contents of Zhengmai 0943 significantly increased under medium concentration treatment（2.5% FeSO₄·7H₂O + 2.5% ZnSO₄·7H₂O + 0.1% Na₂SeO₃）. The zinc content in the grains of Bainong AK58 and Zhengyumai 958 significantly increased under different concentration treatments（T1：0.5% FeSO₄·7H₂O + 0.5% ZnSO₄·7H₂O+ 0.02% Na₂SeO₃,T2：2.5% FeSO₄·7H₂O + 2.5% ZnSO₄·7H₂O + 0.1% Na₂SeO₃,T3：5% FeSO₄·7H₂O + 5% ZnSO₄·7H₂O + 0.2% Na₂SeO₃）,while the iron and selenium contents in the grains did not vary significantly under different concentration treatments. There were significant differences in the effects of variety,concentration and interaction on the grains’iron,zinc,and selenium content,and variety was the major factor,and followed by foliar spraying concentration. Foliar spraying of different concentrations of iron,zinc,and selenium mixed micro-fertilizers by UAV demonstrated overall little effect on the P,Ca,Mg,Cu,and Mn contents of 3 wheat varieties. Under this experimental treatment,the contents of iron,zinc and selenium in the wheat grains significantly increased to achieve the purpose of nutritional enhancement. Therefore,it is recommended to plant Bainong AK58 for iron-rich wheat,Bainong AK58 and Zhengmai 0943 for zinc-rich wheat,and Zhengmai 0943 for selenium-rich wheat.

Key words: unmanned aerial vehicle, foliar spray, micro-fertilizer, wheat, mineral elements

李文宗, 李春萍, 梁鑫, 王润豪, 王磊. 无人机叶面喷施梯度微肥对不同品种冬小麦籽粒矿质元素的影响[J]. 生物技术通报, 2021, 37(9): 152-160.

LI Wen-zong, LI Chun-ping, LIANG Xin, WANG Run-hao, WANG Lei. Effects of Foliar Gradient Micro-fertilizer Sprayed by UAV on the Grain Mineral Elements of Different Winter Wheat Varieties[J]. Biotechnology Bulletin, 2021, 37(9): 152-160.

图/表 9

图1 不同处理对不同小麦品种籽粒铁含量的影响 CK：叶面喷施清水;T1: 0.5% FeSO4·7H2O + 0.5% ZnSO4·7H2O + 0.02% Na2SeO3混合溶液;T2: 2.5% FeSO4·7H2O + 2.5% ZnSO4·7H2O + 0.1% Na2SeO3混合溶液;T3: 5% FeSO4·7H2O + 5% ZnSO4·7H2O + 0.2% Na2SeO3混合溶液,不同小写字母表示在5%水平下差异显著,下同

Fig. 1 Effects of different treatments on the grain iron content of different wheat varieties CK: Foliar spraying of water; T1: 0.5% FeSO4·7H2O + 0.5% ZnSO4·7H2O + 0.02% Na2SeO3 mixed solution; T2: 2.5% FeSO4·7H2O + 2.5% ZnSO4·7H2O + 0.1% Na2SeO3 mixed solution; T3: 5% FeSO4·7H2O + 5% ZnSO4·7H2O + 0.2% Na2SeO3 mixed solution. Different lowercase letters significant differences（P<0.05）among different treatments. The same below

表1 各目标因素检验

Table 1 Tests of between-subjects effects

变异来源Source of variation	平方和SS	自由度DF	均方MS	F值F-value	P值P-value	偏Eta² Partial Eta²
校正模型Calibration model	616.355a	11	56.032	7.459	0.000	0.774
截距Intercept	46004.530	1	46004.530	6124.111	0.000	0.996
品种Variety	447.700	2	223.850	29.799	0.000	0.713
处理浓度Concentration	36.682	3	12.227	1.628	0.209	0.169
品种×处理浓度 Variety×Concentration	131.973	6	21.996	2.928	0.027	0.423
误差Error	180.289	24	7.512
总计Total	46801.174	36
校正的总计 Total calibration	796.644	35

图2 不同处理对不同小麦品种籽粒锌含量的影响

Fig. 2 Effects of different treatments on the grain zinc content of different wheat varieties

表2 各目标因素检验

Table 2 Tests of between-subjects effects

变异来源Source of variation	平方和SS	自由度DF	均方MS	F值F-value	P值P-value	偏Eta² Partial Eta²
校正模型Calibration model	1133.230a	11	103.021	62.082	0.000	0.966
截距Intercept	56969.734	1	56969.734	34330.606	0.000	0.999
品种Variety	413.602	2	206.801	124.621	0.000	0.912
处理浓度Concentration	528.310	3	176.103	106.122	0.000	0.930
品种×处理浓度 Variety×Concentration	191.318	6	31.886	19.215	0.000	0.828
误差Error	39.827	24	1.659
总计Total	58142.790	36
校正的总计 Total calibration	1173.056	35

图3 不同处理对不同小麦品种籽粒硒含量的影响

Fig. 3 Effects of different treatments on the grain selenium content of different wheat varieties

表3 各目标因素检验

Table 3 Tests of between-subjects effects

变异来源Source of variation	平方和SS	自由度DF	均方MS	F值F-value	P值P-value	偏Eta² Partial Eta²
校正模型Calibration model	0.010a	11	0.001	18.839	0.000	0.896
截距Intercept	0.112	1	0.112	2302.717	0.000	0.990
品种Variety	0.005	2	0.003	54.170	0.000	0.819
处理浓度Concentration	0.002	3	0.001	15.217	0.000	0.655
品种×处理浓度Variety×Concentration	0.003	6	0.000	8.872	0.000	0.689
误差Error	0.001	24	0.000
总计Total	0.123	36
校正的总计 Total calibration	0.011	35

图4 不同处理对百农AK58籽粒不同矿质元素含量的影响

Fig. 4 Effects of different treatments on different mineral elements content of Bainong AK58 grains

图5 不同处理对郑麦0943籽粒不同矿质元素含量的影响

Fig. 5 Effects of different treatments on different mineral elements content of Zhengmai 0943 grains

图6 不同处理对郑育麦958籽粒不同矿质元素含量的影响

Fig. 6 Effects of different treatments on different mineral elements content of Zhengyumai 958 grains

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