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氮素的吸收、同化与运转直接影响着作物的生长发育状况,对作物生长至关重要。传统计算植株氮质量分数的方法需要破坏性取样,且要进行室内化学分析,具有一定程度上的滞后性和缓慢性。叶绿素仪具有快速、简便和无损的特点,常被用来监测诊断作物氮素营养[1]。前人基于作物高产条件下建立的土壤、作物分析仪器开发(SPAD)值与产量的关系确定了适宜SPAD值[2-4]。近年来,在小麦Triticum aestivum,玉米Zea mays,茅草Imperata cylindrica,水稻Oryza sativa等作物上利用SPAD值估算作物氮质量分数快速无损诊断氮素营养状况已经被广泛应用[3],但传统的叶片氮营养诊断方法有不少的缺点,例如准确度低,诊断费时费力,且破坏样本和诊断相对滞后[5-7]。若采用SPAD测量仪诊断氮素营养方法则较为省时省力且能够实时监测,但SPAD测量仪所测量出的数据受很多环境因素影响,在某些情况下会出现准确度低和稳定性较差等缺点。前人主要以单叶SPAD作为诊断方法进行研究[8],凌启鸿等[9]研究表明顶3叶与顶4叶的叶色差可以准确诊断水稻植株氮素的丰亏,李刚华等[8]研究表明顶3叶可作为较为理想指示叶诊断水稻氮素营养状况,姜继萍等[10]研究表明水稻顶4叶和顶3叶间的差值与施氮水平之间存在明显的相关性,李杰等[11]研究表明顶3叶SPAD值乘顶4叶SPAD值/顶部4张叶片平均SPAD值与田块表观供氮量之间具有显著的线性关系。前人大都基于顶3叶与顶4叶对水稻氮素营养诊断进行研究,而不同叶位构建归一化SPAD指数(normalized differential SPADij,INDSPADij)与氮素营养之间关系的研究较少。本研究通过不同叶位建立归一化SPAD指数与水稻氮素营养之间的定量关系,通过归一化SPAD值估算氮质量分数,从而快速精确地诊断水稻氮素营养,并通过不同叶位与氮素营养状况的相关性高低判定更能指示水稻植株氮质量分数的叶位,以期为水稻氮素营养诊断提供参考。
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于2015年在浙江省德清县浙江农林大学现代农业科技园,选用2个水稻品种:‘甬优538’‘Yongyou 358’,5月28日播种,大田用种量为18.0 kg·hm-2,秧龄为25 d,2本·丛-1,移栽稻密度为18.0万穴·hm-2;行距28.0 cm ×株距20.0 cm。‘秀水134’‘Xiushui 134’,5月28日播种,大田用种量为45.0 kg·hm-2,秧龄25 d,4本·丛-1,移栽稻密度为25.5万穴·hm-2。行距28.0 cm ×株距14.0 cm。2品种独立试验,设置5个氮肥水平,重复3次,采用随机区组设计,小区15个·品种-1。小区之间以田埂相隔,埂上覆膜,独立排灌。南北行向,小区东西长8.0 m,南北宽4.0 m,面积为32.0 m2。耕作层土壤有机质为20.10 g·kg-1,全氮为1.19 g·kg-1,碱解氮为104.64 mg·kg-1,速效磷为46.45 mg·kg-1,速效钾为81.49 mg·kg-1。
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设置5个氮肥水平,施肥量分别为0(N0对照),70.0(N1),140.0(N2),210.0(N3),280.0(N4)kg·hm-2。m(基肥):m(糵肥):m(穗肥)=4:2:4(表 1)。在施用基肥时,一次性施入过磷酸钙990.0 kg·hm-2;氯化钾基肥用175.0 kg·hm-2,穗肥用175.0 kg·hm-2,所有小区水平一致。
表 1 不同时期氮肥用量
Table 1. Nitrogen consumption at different stages
编号 氮肥/(kg·hm-2) 组成/(kg·hm-2) 基肥 蘖肥 穗肥 N0 0 0 0 0 N1 70.0 28.0 14.0 28.0 N2 140.0 56.0 28.0 56.0 N3 210.0 84.0 42.0 84.0 N4 280.0 112.0 56.0 112.0 -
通过分析顶部4张叶片SPAD值的变化特征,明确叶位SPAD归一化指数与植株氮质量分数的定量关系,构建最优的叶位SPAD组合指数,实时可靠地反映水稻植株氮素营养状况。
叶位SPAD组合指数的计算方法如下:叶位SPAD归一化指数INDSPADij=(ISPADi-ISPADj)/(ISPADi+ISPADj)。其中:ISPADi和ISPADj分别代表水稻冠层主茎第i和j叶位的SPAD值,i,j≤4。
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用MINOLTA产SPAD-502型叶绿素计,在水稻拔节前期、拔节期、孕穗期、抽穗期、开花期和灌浆前期,选取4株健康主茎测定其顶部4张完全展开叶上部1/3处、中部和下部1/3处的SPAD值,取平均值作为各叶片的SPAD值[8]。
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水稻拔节前期、拔节期、孕穗期、抽穗期、开花期、灌浆前期、灌浆中期和成熟期,分别选取代表性水稻植株4株·小区-1,根据植株器官发育情况,将样品植株分离为叶、茎和穗,放入恒温干燥箱内烘干,在105 ℃杀青30 min,80 ℃烘干48 h至恒量后称量。样品粉碎后使用半微量凯氏定氮法测定水稻植株不同器官的全氮质量分数。
Characteristics and diagnosis of nitrogen nutrition for rice canopy leaf SPAD value changes
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摘要: 建立水稻Oryza sativa氮营养诊断模型,实时反映水稻植株氮素营养状况,对水稻田间管理至关重要。于2015年在浙江省德清市开展田间试验,选择‘甬优538’‘Yongyou 538’和‘秀水134’‘Xiushui 134’作为代表品种,设置5个施氮水平0(N0),70.0(N1),140.0(N2),210.0(N3),280.0(N4)kg·hm-2,通过研究不同施氮水平下2个水稻品种冠层叶片作物分析仪器开发值(SPAD)变化规律,探究5个不同施氮水平下植株氮质量分数的变化趋势,并利用归一化SPAD指数(INDSPAD14)估算植株氮质量分数。结果表明:顶4叶相较其他叶片更能指示水稻植株氮质量分数,归一化SPAD指数与N0~N4所有不同施氮量组别之间冠层叶片氮质量分数呈显著正相关(P < 0.05),‘甬优358’水稻品种决定系数为0.69~0.96,‘秀水134’品种决定系数为0.64~0.94。该指数可以对水稻冠层叶片氮质量分数快速估测。Abstract: Nitrogen(N) is important for rice growth. To establish a rice (Oryza sativa) nitrogen nutrition diagnostic model that could reflect the N status of a rice organism and that could be convenient for rice field management, a rice community test was conducted in Deqing City, Zhejiang Province in 2015. Oryza sativa 'Yongyou 538' and 'Xiushui 134' were taken as the representative cultivars. Five levels of N were established:0(N0)(ck), 70.0(N1), 140.0(N2), 210.0(N3), and 280.0(N4) kg·hm-2. Measurement of rice SPAD (soil and plant analyzer development) values were made using a portable SPAD-502 meter and followed by a correlation analysis. Results showed that the fourth leaf from the top was a good indication of plant nutrition status. There was a significant positive correlation between the normalized SPAD index (INDSPAD14) and N content in canopy leaves with the N0-N4 treatments. The coefficients of determination for 'Yongyou 358' r2=0.69-0.96 and for 'Xiushui 134' r2=0.64-0.94. By analyzing the relationship between INDSPAD14 and plant N content, a diagnostic model of rice N concentration was established.
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Key words:
- botany /
- Oryza sativa /
- canopy leaf /
- SPAD value /
- nitrogen
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表 1 不同时期氮肥用量
Table 1. Nitrogen consumption at different stages
编号 氮肥/(kg·hm-2) 组成/(kg·hm-2) 基肥 蘖肥 穗肥 N0 0 0 0 0 N1 70.0 28.0 14.0 28.0 N2 140.0 56.0 28.0 56.0 N3 210.0 84.0 42.0 84.0 N4 280.0 112.0 56.0 112.0 -
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链接本文:
https://zlxb.zafu.edu.cn/article/doi/10.11833/j.issn.2095-0756.2019.05.014