Suppr超能文献

利用无人机图像从稻田土壤有效氮分布预测水稻倒伏风险

Predicting Rice Lodging Risk from the Distribution of Available Nitrogen in Soil Using UAS Images in a Paddy Field.

作者信息

Sato Nozomi Kaneko, Tsuji Takeshi, Iijima Yoshihiro, Sekiya Nobuhito, Watanabe Kunio

机构信息

Graduate School of Bioresources, Mie University, Tsu 5148507, Japan.

Office SoilCares, Yokkaichi 5100035, Japan.

出版信息

Sensors (Basel). 2023 Jul 17;23(14):6466. doi: 10.3390/s23146466.

Abstract

Rice lodging causes a loss of yield and leads to lower-quality rice. In Japan, Koshihikari is the most popular rice variety, and it has been widely cultivated for many years despite its susceptibility to lodging. Reducing basal fertilizer is recommended when the available nitrogen in soil (SAN) exceeds the optimum level (80-200 mg N kg). However, many commercial farmers prefer to simultaneously apply one-shot basal fertilizer at transplant time. This study investigated the relationship between the rice lodging and SAN content by assessing their spatial distributions from unmanned aircraft system (UAS) images in a Koshihikari paddy field where one-shot basal fertilizer was applied. We analyzed the severity of lodging using the canopy height model and spatially clarified a heavily lodged area and a non-lodged area. For the SAN assessment, we selected green and red band pixel digital numbers from multispectral images and developed a SAN estimating equation by regression analysis. The estimated SAN values were rasterized and compiled into a 1 m mesh to create a soil fertility map. The heavily lodged area roughly coincided with the higher SAN area. A negative correlation was observed between the rice inclination angle and the estimated SAN, and rice lodging occurred even within the optimum SAN level. These results show that the amount of one-shot basal fertilizer applied to Koshihikari should be reduced when absorbable nitrogen (SAN + fertilizer nitrogen) exceeds 200 mg N kg.

摘要

水稻倒伏会导致产量损失并降低稻米品质。在日本,越光稻是最受欢迎的水稻品种,尽管它易倒伏,但多年来一直被广泛种植。当土壤有效氮(SAN)超过最佳水平(80 - 200毫克氮/千克)时,建议减少基肥用量。然而,许多商业农户更喜欢在插秧时一次性施用基肥。本研究通过评估在施用一次性基肥的越光稻田中无人机系统(UAS)图像的空间分布,研究了水稻倒伏与SAN含量之间的关系。我们使用冠层高度模型分析倒伏严重程度,并在空间上明确了严重倒伏区域和未倒伏区域。对于SAN评估,我们从多光谱图像中选择绿色和红色波段像素数字,并通过回归分析建立了SAN估算方程。将估算的SAN值进行栅格化处理并编制成1米网格,以创建土壤肥力图。严重倒伏区域大致与较高的SAN区域重合。观察到水稻倾斜角度与估算的SAN之间呈负相关,并且即使在最佳SAN水平内也会发生水稻倒伏。这些结果表明,当可吸收氮(SAN + 肥料氮)超过200毫克氮/千克时,应减少施用于越光稻的一次性基肥用量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b318/10383411/cc19697380bd/sensors-23-06466-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验