He Yiyin, Wang Zhao, Sun Sashuang, Zhu Lijun, Li Yu, Wang Xiaoxiao, Shi Jiang, Chen Si, Qi Dunchang, Peng Junxiang, Zhou Zhenjiang
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.
Huanan Industrial Technology Research Institute of Zhejiang University, Guangzhou, China.
Front Plant Sci. 2023 Sep 18;14:1208404. doi: 10.3389/fpls.2023.1208404. eCollection 2023.
An accurate assessment of vegetable yield is essential for agricultural production and management. One approach to estimate yield with remote sensing is via vegetation indices, which are selected in a statistical and empirical approach, rather than a mechanistic way. This study aimed to estimate the dry matter of Choy Sum by both a causality-guided intercepted radiation-based model and a spectral reflectance-based model and compare their performance. Moreover, the effect of nitrogen (N) rates on the radiation use efficiency () of Choy Sum was also evaluated. A 2-year field experiment was conducted with different N rate treatments (0 kg/ha, 25 kg/ha, 50 kg/ha, 100 kg/ha, 150 kg/ha, and 200 kg/ha). At different growth stages, canopy spectra, photosynthetic active radiation, and canopy coverage were measured by RapidScan CS-45, light quantum sensor, and camera, respectively. The results reveal that exponential models best match the connection between dry matter and vegetation indices, with coefficients of determination () all below 0.80 for normalized difference red edge (NDRE), normalized difference vegetation index (NDVI), red edge ratio vegetation index (RERVI), and ratio vegetation index (RVI). In contrast, accumulated intercepted photosynthetic active radiation () showed a significant linear correlation with the dry matter of Choy Sum, with root mean square error () of 9.4 and values of 0.82, implying that the -based estimation model performed better than that of spectral-based ones. Moreover, the of Choy Sum was significantly affected by the N rate, with 100 kg N/ha, 150 kg N/ha, and 200 kg N/ha having the highest values. The study demonstrated the potential of -based models for precisely estimating the dry matter yield of vegetable crops and understanding the effect of N application on dry matter accumulation of Choy Sum.
准确评估蔬菜产量对农业生产和管理至关重要。利用遥感技术估算产量的一种方法是通过植被指数,这些指数是通过统计和经验方法而非机理方法选择的。本研究旨在通过基于因果关系引导的截获辐射模型和基于光谱反射率的模型来估算菜心的干物质,并比较它们的性能。此外,还评估了施氮量对菜心辐射利用效率( )的影响。进行了为期两年的田间试验,设置了不同的施氮量处理(0千克/公顷、25千克/公顷、50千克/公顷、100千克/公顷、150千克/公顷和200千克/公顷)。在不同生长阶段,分别使用RapidScan CS - 45、光合有效辐射传感器和相机测量冠层光谱、光合有效辐射和冠层覆盖率。结果表明,指数模型最能匹配干物质与植被指数之间的关系,归一化差值红边(NDRE)、归一化差值植被指数(NDVI)、红边比值植被指数(RERVI)和比值植被指数(RVI)的决定系数( )均低于0.80。相比之下,累积截获光合有效辐射( )与菜心干物质呈显著线性相关,均方根误差( )为9.4,决定系数( )值为0.82,这意味着基于 的估算模型比基于光谱的模型表现更好。此外,菜心的 受施氮量显著影响,施氮量为100千克氮/公顷、150千克氮/公顷和200千克氮/公顷时 值最高。该研究证明了基于 的模型在精确估算蔬菜作物干物质产量以及理解施氮对菜心干物质积累影响方面的潜力。