Sadly, M
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PREDIKSI KANDUNGAN NITROGEN DAUN PADI DENGAN ANALISIS PERGESERAN TEPI KANAL MERAH (RED EDGE SHIFT) DATA HIPERSPEKTRAL nadirah, nadirah; Muljosukojo, Bangun; Hariyanto, Teguh; Sadly, M; Evri, M; mulyono, Sidik
Jurnal Sains dan Teknologi Indonesia Vol. 11 No. 3 (2009)
Publisher : Badan Pengkajian dan Penerapan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (151.733 KB) | DOI: 10.29122/jsti.v11i3.838

Abstract

Canopy hyperspectral with various growth stages measured by using field spectroradiometer (350 - 1000 nm) corresponded to leaf Nitrogen content of three rice cultivars (Ciherang, Cilamaya and IR64) during growth season in Java Island,Indonesia. Coinciding with hyperspectral measurement, biochemical parameter such as leaf Nitrogen content (g/100 gr) was analyzed from destructive biomass sample through laboratory analysis. The potential narrow band in the red edgeregion was investigated to predict leaf nitrogen content (N content) with applying modified polynomial interpolation (MPI) and modified four points linear interpolation (MFLI) methods. First derivative reflectance derived from reflectance data andsubsequently used in analysis of Red Edge Position (REP). The correlation REPMFLI was generally stronger than REP-MPI attributed to leaf N content for several level of N application that indicated by value of R2. The response of REP-MFLItoward N level 69 kg/ha exhibited the most significant correlation (R2 = 0.754) than other correlations. Meanwhile, the response of REP-MPI toward N level 161 kg/ha denoted the most significant correlation (R2 = 0.8) than other correlations. The highest correlation using REP-MPI (R2 = 0.8) to predict leaf N contentdemonstrated slightly higher than that of REP- MFLI (R2 = 0.754). In general both REP-MFLI and REP-MPI represented somewhat similar response toward N levels, such as 103.5 kg/h, 115 kg/ha. The exploration of characteristics of red edge shiftis a fundamental point in developing rapid and precise prediction for biochemical parameter. In addition, its prediction capability was promising to support crop farming management.