Estimating the Protein Concentration in Rice Grain Using UAV Imagery Together with Agroclimatic Data
Estimating the Protein Concentration in Rice Grain Using UAV Imagery Together with Agroclimatic Data
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DOI：
10.3390/agronomy10030431
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发表时间：
2020-03
期刊：
影响因子：
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通讯作者：
A. Hama;Kei Tanaka;A. Mochizuki;Y. Tsuruoka;A. Kondoh
中科院分区：
文献类型：
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作者：
A. Hama;Kei Tanaka;A. Mochizuki;Y. Tsuruoka;A. Kondoh
全球变暖和气候变化不仅可能改变大米产量，还可能改变大米的营养含量。为了使依赖水稻的国家的农业适应气候变化的影响，有必要评估和监测气候变化对农业构成的潜在风险。本研究的目的是通过无人机遥感和气象测量来阐明水稻籽粒蛋白质含量(GPC)与气象变量的关系。在此基础上，提出了一种将遥感数据与气象变量相结合的GPC估算方法。研究结论如下：(1)利用抽穗期绿色归一化植被指数(GNDVI)评价氮素营养状况，利用灌浆期日均太阳辐射(SRR)评价光合作用，提高了GPC估算模型的准确性和稳健性。在GNDVI型抽穗的基础上，考虑灌浆的GPC估计能够估计出不同条件下观测到的GPC。(2)在极端温度不引起热胁迫的情况下，移栽期至抽穗期温度升高会影响GPC的升高。
Global warming and climate change can potentially change not only rice production but also rice nutrient content. To adapt a rice-dependent country’s farming to the impacts of climate change, it is necessary to assess and monitor the potential risk that climate change poses to agriculture. The aim of this study was to clarify the relationship between rice grain protein content (GPC) and meteorological variables through unmanned aerial vehicle remote sensing and meteorological measurements. Furthermore, a method for GPC estimation that combines remote sensing data and meteorological variables was proposed. The conclusions of this study were as follows: (1) The accuracy and robustness of the GPC estimation model were improved by evaluating the nitrogen condition with the green normalized difference vegetation index at the heading stage (GNDVIheading) and evaluating photosynthesis with the average daily solar radiation during the grain-filling stage (SRgrain-filling). GPC estimation considering SRgrain-filling in addition to GNDVIheading was able to estimate the observed GPC under the different conditions. (2) Increased temperature from the transplantation date to the heading stage can affect increased GPC when extreme temperature does not cause the heat stress.