Canopy nitrogen (N) status relates strongly to canopy chlorophyll content and the strength of green color. Proximal photograph by RGB camera was used to select green features that has the po­tential to assess N content at leaf of plant as a function of its the greenness. We proposed the development of it as a tool for sensing nitrogen content in spring wheat (Triticum aestivum). Image processing algorithm was programed calibrated and validated wheat %N%N. Nitrogen uptake =%N × canopy dry matter was harvested and calculated using simulated dry matter by DSSAT model. The data replicated laboratory measurements. A linear Lab vs Camera model displayed a unit slope with r² = 0.93. Increase of dry matter was successfully surrogated by days after emergence and used as abscissa for inverse logistic model of critical nitrogen level. It decreased gradually from about 6% to 2% as days after emergence increased from 0 to 110 days. Maximum N uptake calculated from photo and laboratory was 324 Kg·ha⁻¹ and 318 Kg·ha⁻¹ respectively suggesting insignificant difference. Physiological N-use efficiency (i.e., canopy weight /N weight) was 52 and 78 kg canopy dry weight per 1 kg N for early and late-ripening cultivars, respectively. The determination of N application based on the smartphone photograph proved to be useful by saving on time and expenses for growers who have access to smartphones and can use them for N application and management.

中文翻译：

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春小麦对氮需求的近距离感知

冠层氮（N）的状态与冠层的叶绿素含量和绿色强度密切相关。使用RGB相机拍摄的近照来选择绿色特征，这些特征可以根据其绿色程度来评估植物叶片上的N含量。我们提出将其开发为一种用于感测春小麦（Triticum aestivum）氮含量的工具。对图像处理算法进行了编程，以校准和验证小麦％N％N。氮吸收量=％N×冠层干物质，并通过DSSAT模型使用模拟干物质进行计算。数据复制了实验室的测量值。线性Lab vs相机模型显示的单位斜率为r ²= 0.93。出苗后几天，干物质的增加就被成功地消除了，并用作临界氮水平的逆逻辑模型的横坐标。随着出苗后的天数从0天增加到110天，它从大约6％逐渐减少到2％。根据照片和实验室计算得出的最大氮吸收量分别为324 Kg·ha ^-1和318 Kg·ha ^-1，表明差异不明显。早熟和晚熟品种的生理氮利用效率（即冠层重量/ N重量）分别为每1 kg N 52和78 kg冠层干重。事实证明，基于智能手机照片确定N应用程序非常有用，因为它可以节省时间和费用，使种植者可以使用智能手机并可以将其用于N应用程序和管理。