Appropriate application of nitrogen (N) fertilizer promotes plant growth, inflorescence yield, and flower quality of orchids. In this study, we used the near-infrared spectroscopy (NIRS) technique to develop a prediction model of the N content in the leaf of Dendrobium orchid, which is an essential indicator for monitoring plant health. The Dendrobium orchid samples were foliar sprayed in rotation between 20N–20P–20K and 30N–10P–10K fertilizers at a frequency of once or twice a week to create a diverse amount of leaf N content. An application of water was used as the control treatment. After nine months of fertilizer treatments, 150 fresh orchid leaf samples, containing various N contents, were scanned using Fourier-transform near-infrared spectroscopy (FT-NIRS). Then the samples were dried and ground to a fine powder and were again scanned. The absorbance spectra were collected at the 12,000–4000 cm −1 (800–2500 nm) region. Total N content was determined by using the combustion method. The result showed a high proficiency in the estimation of N in leaf powder with the correlation coefficient of prediction (R p ), the root mean square error of prediction (RMSEP), and the ratio of standard deviation of reference data of prediction set to standard error of prediction (RPD) being 0.9882, 0.0637% dry weight (DW), and 6.53, respectively. The fresh leaf sample was successfully predicted with R p , RMSEP, and RPD of 0.8874, 0.207% DW, and 2.13, respectively. Additionally, external validation confirmed the high reliability of using leaf powder since the correlation coefficient of external validation (r p ) and RMSEP of the external validation achieved 0.9651 and 0.1405% DW, respectively, while the external validation of fresh leaf should be improved with r p = 0.7438 and RMSEP = 0.2652% DW. The overall results suggested that NIRS can be used for monitoring the N status in orchids, especially in leaf powder, with high accuracy.

中文翻译：

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近红外光谱法测定石斛兰鲜叶和叶粉总氮含量

适当施用氮肥可促进兰花的植物生长、花序产量和花质量。在这项研究中，我们使用近红外光谱 (NIRS) 技术开发了石斛兰叶片中 N 含量的预测模型，这是监测植物健康的重要指标。石斛兰花样品在 20N-20P-20K 和 30N-10P-10K 肥料之间轮流喷洒，每周一次或两次，以产生不同数量的叶子 N 含量。使用水作为对照处理。经过九个月的肥料处理后，使用傅里叶变换近红外光谱 (FT-NIRS) 扫描了 150 份含有不同氮含量的新鲜兰花叶子样品。然后将样品干燥并研磨成细粉并再次扫描。在 12,000–4000 cm -1 (800–2500 nm) 区域收集吸收光谱。总氮含量采用燃烧法测定。结果表明，通过预测相关系数（R p ）、预测均方根误差（RMSEP）、预测集参考数据与标准的标准差比值，能够准确估算叶粉中的氮含量。预测误差 (RPD) 分别为 0.9882、0.0637% 干重 (DW) 和 6.53。鲜叶样品成功预测，R p 、RMSEP 和 RPD 分别为 0.8874、0.207% DW 和 2.13。此外，外部验证证实了使用叶粉的高可靠性，因为外部验证的相关系数 (rp ) 和外部验证的 RMSEP 分别达到了 0.9651 和 0.1405% DW，而新鲜叶的外部验证应改进为 rp = 0.7438 和 RMSEP = 0.2652% DW。总体结果表明，近红外光谱技术可用于监测兰花，尤其是叶粉中的氮状态，具有较高的准确度。