Judul: Pendeteksian Tumpahan Minyak di Laut Timor dengan Metode Filter Frost dan Gamma Terhadap Citra ALOS PALSAR di Ladang Minyak Montara
Abstrak: Aktifitas manusia di daratan dan sekitar pesisir lautan akan menghasilkan limbah yang akan dibuang ke lingkungan. Menurut Group of Expert on Scientific Aspect of Marine Pollution (GESAMP) bahwa 6,44 juta ton/ tahun hidrokarbon masuk ke dalam perairan yang berasal dari kegiatan transportasi laut, pengoperasian pertambangan minyak di anjungan serta kegiatan industri oleh manusia (Hartanto, 2008). Kegiatan operasional pertambangan minyak di lepas pantai memiliki kemungkinan terjadinya kecelakaan yang menyebabkan munculnya tumpahan minyak berupa kegiatan (1) pengoperasian kapal tanker da lam proses deballasting (sistem kestabilan kapal menggunakan bongkar-muat air) (2) kecelakaan kapal maupun tanker dan (3) munculnya semburan sumur minyak yang disebabkan oleh kerusakan struktur platform ataupun peralatan. Kejadian tumpahan minyak yang dikaji pada penelitian ini terjadi di Laut Timor pada tanggal 21 Agustus 2009–3 November 2009 tepatnya di sekitar lepa s pantai utara dari Australia bagian Barat dan berada di perairan bagian selatan dari Indo nesia. Kejadian tumpahnya minyak ke perairan ini dapat memberikan dampak negatif terhadap ekosistem lingkunga n laut beserta biota di dalamnya . Oleh karena itu dibutuhkan penelitian dengan memanfaatkan teknologi penginderaan jauh untuk mengidentifikasi dan memantau penyebaran tumpahan minyak di wilayah Republik Indonesia.
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Judul: Deteksi Tumpahan Minyak Montara di Laut Timor Menggunakan Citra MODIS dengan Berbagai Algoritma
Abstrak: Oil Spill in the Timor Sea that occurring in 2009 has caused oil expansion to an area of 10.842.81 km2. The Oil spill was successfully detected by MODIS imagery. The purpose of this study was to compare the detection of oil results from various algorithms with MODIS imagery and it’s visual appearances. The algorithm used is Oil Spill Index, Flourecence Index, Sea Surface Temperature (SST) Callison, Principal Component Analysis (PCA), and Normalized Difference Vegetation Index (NDVI). The appearance of oil spill in MODIS image extracted using oil spill index and flourecence index was brighter than the surrounding water bodies and has higher pixel values, while the appearance of oil spill on PCA and NDVI algorithms appeared darker than the surrounding water bodies and has a lower pixel value. The test accuracy of the algorithms are, 41%, 46%, 41%, and 60%, respectively.
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Judul: Evaluation of Influenza Antibody Titers in Serum and Egg Yolk of Layers Vaccinated with Influenza Vaccines.
Abstrak: Influenza belongs to the Orthomyxoviridae family which causes upper and lower respiratory tract infection. The aim of this study was to evaluate influenza-A specific antibody titers from serum and egg yolk of hens vaccinated with quadrivalent influenza vaccines. Three Hy-line Brown layers were vaccinated with quadrivalent influenza type A and B inactivated vaccines. Vaccination was carried out three times at a dose of 0.25 ml/chicken via the intramuscular route. The first vaccination was carried out at 24 weeks of age, then boosters were performed at 28 and 32 weeks of age. Serum and egg yolk were collected every week for 20 weeks since the first vaccination. Influenza A H3N2 and H1N1 antibody titers were determined using hemagglutination-inhibition (HI) test and agar-gel-precipitation (AGP) test. Influenza-A H3N2 and H1N1 specific antibodies were detected in both serum and egg yolk from the first to twenty weeks after the initial vaccination. Highest HI geometric mean titer (GMT) of H1N1 antibody reached 26.67 HIU at nine weeks post first vaccination (p.f.v), while H3N2 antibody reached 26 HIU at six weeks p.f.v. Our result showed that influenza antibodies can be produced in layers using quadrivalent vaccines and layer chickens are able to produce equivalent antibody levels for each influenza subtype.
Keyword: antibody, egg yolk, influenza, layer chickens, serum