考虑植株氮垂直分布的夏玉米营养诊断敏感位点筛选

Selecting the sensitive position of maize leaves for nitrogen status diagnosis of summer maize by considering vertical nitrogen distribution in plant

探明夏玉米氮素营养生化指标(叶绿素a、叶绿素b、类胡萝卜素、叶片氮含量和叶片氮积累量)与叶片SPAD值垂直分布特征及两者间定量回归关系,确立基于叶绿素仪的夏玉米氮营养无损诊断敏感叶位和叶片部位,以实现氮营养时空变化的快捷和精准监测。利用2018-2019年连续2季不同氮营养水平下夏玉米关键生育期主茎各叶位(顶1叶~顶12叶,TL1~TL12)和叶片部位(每张叶片从叶片基部开始根据叶片长度每20%分为1个测试区间) SPAD值及氮营养指标数据,研究基于偏最小二乘(partial least square, PLS)回归模型的夏玉米不同位点SPAD值与氮营养指标间关系,确定可稳定指示夏玉米氮营养空间异质性变化的敏感叶位及叶片部位。结果表明,不同叶位间夏玉米叶片SPAD值和氮营养指标于植株间分布均呈典型的"钟型"特征,至TL5或TL6时达至峰值。同一叶位不同部位间SPAD值由20%至100%位点时则逐步升高,且80%~100%位点间无显著差异(P>0.05)。PLS分析结果显示,夏玉米不同叶位SPAD值与氮营养指标间模型精度决定系数(coefficient of determination, R2)和相对分析误差(relative percent deviation,RPD)范围分别为0.693~0.821和1.425~2.744。不同测试位点R2和RPD值范围则分别为0.660~0.847和1.607~2.451,满足模型精确诊断需求。此后,基于PLS模型中各叶位和叶片部位无量纲评价指标变量重要性投影值(variable importance for projection,VIP),确定顶4叶(TL4)完展叶60%~80%区间为夏玉米氮营养诊断的敏感区域,VIP值均高于临界值1.40,预测效果较为理想。研究可为实现氮营养的高效、快捷诊断和精准施氮提供参考。

Rapid and accurate assessment of temporal and spatial variations of crop nitrogen(N) status is important to help farmers improve site-specific N management in sustainable agriculture. However, current studies place little emphasis on crop N estimations by taking N’s vertical distribution into consideration, leading to limited accuracy of the results. The main goal of this study was to quantitatively analyze the vertical distribution characteristics of N nutrition indices(leaf chlorophyll concentration, leaf N content and leaf N accumulation) and SPAD value of different leaves, and determine the sensitive leaf position for N diagnosis with a portable SPAD-502 chlorophyll meter(Konica Minolta Sensing, Osaka, Japan) of summer maize. Two field experiments were conducted over two consecutive growing seasons(2018-2019) with three growth stages(large bell stage, silking stage and filling stage) at two sites(Wenxian county and Hebi city) in Henan province, North China.The same cultivar of summer maize, i. e., Zhengdan No. 958, was used during the two growing seasons. The detailed N fertilization treatments in the two growing seasons were as follows:(i) no N application(N0);(ii) N fertilizer application rate of 75 kg/hm^2, applied as urea(N75);(iii) N fertilizer application rate of 150 kg/hm^2(N150);(iv) N fertilizer application rate of225 kg/hm^2(N225);and(v) N fertilizer application rate of 300 kg/hm^2(N300). All the N nutritional resources were used as base fertilizer prior to sowing. The SPAD value from the 1 st to 12 th leaf from the top on the main stem(TL1-TL12) and different sites on the same leaf(20%, 40%, 60%, 80% and 100%, respectively;0-100% are ratio of leaf length from each measurement point to base to the total leaf length of each leaf) of summer maize were measured at aforementioned three growth stages. Meanwhile, chemical assays of these summer maize samples(N nutrition indices) were performed in the laboratory. In total, ninety samples were used for building spectral monitoring models of N estimation. A partial least square(PLS) regression analysis was employed to quantitatively describe the relationship between the SPAD value at different leaf position and leaf sites and N indices. The prediction accuracy of the monitoring models was evaluated by comparing coefficient of determination(R2), root mean square error(RMSE) and relative percent deviation(RPD) between the observed and predicted N nutrition indicators values. Results showed that a vertical distribution pattern of the above N parameters existed and the pattern was bell-shaped from the upper to lower layer of the plant. The variable importance for projection(VIP) resulted from the PLS regression model were used to determine the sensitive leaves and reduce the dimensionality of the SPAD value data. The sensitive location for N nutritional diagnosis was the 60%-80% position of the 4 th fully expanded leaf(TL4) from the top of the main stem, the VIP value was above 1.40 based on the PLS model, respectively. Our results indicated that estimation of N status using SPAD-502 chlorophyll meter data was most effective for the 60%-80% region on the TL4 of summer maize leaves. The model, which considered the vertical distribution patterns of the N and the optimal leaf position and location, has demonstrated great potential to estimate the N status of the whole summer maize canopy. The results suggested that the sensitive leaves from the main stem of summer maize were satisfactory for inversion of the N vertical distribution.