水稲の生体情報と穀実重量をレッドエッジポジションから推定するためのハイパースペクトルデータ解析

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タイトル別名
  • Spectrum analysis of hyperspectral red edge position to predict rice biophysical parameters and grain weight

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Rice canopy hyperspectral reflectance data were perpetually measured to analyze the red edge position (REP) corresponded to grain weight during growing season in Java Island, Indonesia. Reflectance measurements were conducted concurrently with biomass sampling of three rice cultivars and four nitrogen application levels (N level) whose were involved in this study. The potential of narrow bands in the red edge region were investigated to predict nitrogen content (N content), plant chlorophyll index (SPAD value) and grain weight with applying the inverted Gaussian (IG) and modified linear extrapolation (LE) methods. Spectral data was smoothed into five nm interval. The first derivative reflectance that derived from reflectance data subsequently used in analysis of REP. The REP moved to longer wavelength until close to heading stage and otherwise shifted to shorter wavelength after heading stage. The correlation REP-IG (R2=0.849) was stronger than REP-LE (R2=0.767) attributed to N content, while the correlation REP with SPAD value, REP-LE (R2=0.800) demonstrated slightly higher than that of REP-IG (R2=0.731) . Subsequently, REP-LE represented slightly more significant correlation with grain weight (R2= 0.884) when compared to REP-IG (R2=0.847) . The REP shift can act as quick and precise prediction for biophysical parameters and grain weight status. Its prediction capability can support crop farming management.

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