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All Journal BANGUNAN (Jurnal Berkala Jurusan Teknik Sipil UM) Jurnal Veteriner Zuriat Innofarm : Jurnal Inovasi Pertanian TEFLIN Journal: A publication on the teaching and learning of English QUALITY WARTAZOA Indonesian Bulletin of Animal and Veterinary Sciences Forum Geografi Jurnal Ilmiah Manajemen dan Bisnis (JIMB) BERITA BIOLOGI JITEK (Jurnal Ilmiah Teknosains) Bangunan Jurnal Mirai Management IKRA-ITH Humaniora : Jurnal Sosial dan Humaniora JURNAL ILMIAH MAHASISWA AGROINFO GALUH International Journal of Supply Chain Management JURIKOM (Jurnal Riset Komputer) Menara Perkebunan JURNAL HUKUM MEDIA JUSTITIA NUSANTARA PANCANAKA Jurnal Kependudukan, Keluarga, dan Sumber Daya Manusia RESEARCH AND DEVELOPMENT JOURNAL OF EDUCATION (RDJE) Cakrawala Repositori Imwi Jurnal Ilmiah Wahana Pendidikan Jurnal Esensi Infokom: Jurnal Esensi Sistem Informasi dan Sistem Komputer Abdi Geomedisains Jurnal Pendidikan Teknik dan Vokasional Prosiding University Research Colloquium Jurnal Pendidikan dan Pengabdian Masyarakat Jurnal Intelek Dan Cendikiawan Nusantara Jurnal Intelek Insan Cendikia Jurnal Rekayasa Informasi International Journal of Industrial Innovation and Mechanical Engineering
Priyono Priyono
Universitas Mataram
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Journal : Menara Perkebunan

 1 
Potensi electronic nose 118 untuk mendeteksi penyakit busuk pangkal batang pada kelapa sawit Agustin Sri MULYATNI; Irma KRESNAWATY; Deden Dewantara ERIS; Tri PANJI; Wita KIMBERLY; Happy WIDIASTUTI; Priyono PRIYONO; Chotimah CHOTIMAH; Kuwat TRIYANA
E-Journal Menara Perkebunan Vol 90, No 1 (2022): April, 2022
Publisher : INDONESIAN RESEARCH INSTITUTE FOR BIOTECHNOLOGY AND BIOINDUSTRY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22302/iribb.jur.mp.v90i1.472

Abstract

AbstractBasal stem rot (BSR) disease caused by Ganoderma sp. is a major disease in oil palm. One of the keys to successfully control BSR disease is to detect the pathogenic infections as early as possible. Early detection technique has been developed in this study was using volatile compounds sensors known as an electronic nose, specifically Electronic Nose 118. Plant samples were obtained from roots, stems, leaves, and soils of four plant categories, which were midly, moderately, and severely infected by Ganoderma, and healthy plants. The test results showed that Electronic Nose was able to record the profile of volatile organic compounds (VOC) produced by Ganoderma sp. The Linear Discriminant Analysis (LDA) results showed that the root and stem samples were differentiated in fairly high level of discrimination with values of 89.66% and 94.59% respectively, while for internal validation value were 98.18% and 89.18%. However, for leaf and soil samples, Electronic Nose 118 resulted in low discriminations. The test results show that Electronic Nose 118 can distinguish samples of roots and stems of healthy plant and Ganoderma-infected plant with a high accuracy.[Keywords: Ganoderma, linier discriminant analysis (LDA), pathogen infection, sensor, volatile organic compound] AbstrakPenyakit busuk pangkal batang (BPB) yang disebabkan oleh Ganoderma sp. merupakan  penyakit utama pada kelapa sawit. Salah satu kunci keberhasilan pengendalian penyakit BPB adalah diketahuinya infeksi patogen sedini mungkin. Teknik deteksi dini yang saat ini dikembangkan dalam penelitian ini adalah menggunakan sensor senyawa volatil yang dikenal dengan electronic nose, khususnya Electronic Nose 118. Sampel tanaman diperoleh dari akar, batang, daun, dan tanah dari empat kondisi tanaman, yaitu tanaman yang terinfeksi Ganoderma ringan, sedang, berat dan tanaman sehat. Hasil pengujian menunjukkan bahwa profil senyawa organik volatil yang dihasilkan oleh infeksi Ganoderma sp. dapat ditangkap oleh Electronic Nose 118 dengan baik. Hasil analisis Linear Discriminat Analysis (LDA) menunjukkan bahwa sampel akar dan batang terbedakan dengan tingkat diskriminasi yang cukup tinggi dengan nilai secara berurutan yaitu 89,66% dan 94,59%, sedangkan untuk validasi internal masing-masing 98,18% dan 89,18%. Namun demikian, untuk sampel daun dan tanah, pengujian dengan Electronic Nose 118 menghasilkan tingkat diskriminasi yang rendah. Hasil pengujian menunjukkan Electronic Nose 118 dapat membedakan sampel akar dan batang dari tanaman sehat dan tanaman terserang Ganoderma dengan akurasi tinggi.[Kata kunci : Ganoderma, LDA, infeksi patogen, sensor, senyawa organik volatil]
Potensi electronic nose 118 untuk mendeteksi penyakit busuk pangkal batang pada kelapa sawit Agustin Sri MULYATNI; Irma KRESNAWATY; Deden Dewantara ERIS; Tri PANJI; Wita KIMBERLY; Happy WIDIASTUTI; Priyono PRIYONO; Chotimah CHOTIMAH; Kuwat TRIYANA
Menara Perkebunan Vol. 90 No. 1 (2022): 90 (1), 2022
Publisher : INDONESIAN OIL PALM RESEARCH INSTITUTE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22302/iribb.jur.mp.v90i1.472

Abstract

AbstractBasal stem rot (BSR) disease caused by Ganoderma sp. is a major disease in oil palm. One of the keys to successfully control BSR disease is to detect the pathogenic infections as early as possible. Early detection technique has been developed in this study was using volatile compounds sensors known as an electronic nose, specifically Electronic Nose 118. Plant samples were obtained from roots, stems, leaves, and soils of four plant categories, which were midly, moderately, and severely infected by Ganoderma, and healthy plants. The test results showed that Electronic Nose was able to record the profile of volatile organic compounds (VOC) produced by Ganoderma sp. The Linear Discriminant Analysis (LDA) results showed that the root and stem samples were differentiated in fairly high level of discrimination with values of 89.66% and 94.59% respectively, while for internal validation value were 98.18% and 89.18%. However, for leaf and soil samples, Electronic Nose 118 resulted in low discriminations. The test results show that Electronic Nose 118 can distinguish samples of roots and stems of healthy plant and Ganoderma-infected plant with a high accuracy.[Keywords: Ganoderma, linier discriminant analysis (LDA), pathogen infection, sensor, volatile organic compound] AbstrakPenyakit busuk pangkal batang (BPB) yang disebabkan oleh Ganoderma sp. merupakan  penyakit utama pada kelapa sawit. Salah satu kunci keberhasilan pengendalian penyakit BPB adalah diketahuinya infeksi patogen sedini mungkin. Teknik deteksi dini yang saat ini dikembangkan dalam penelitian ini adalah menggunakan sensor senyawa volatil yang dikenal dengan electronic nose, khususnya Electronic Nose 118. Sampel tanaman diperoleh dari akar, batang, daun, dan tanah dari empat kondisi tanaman, yaitu tanaman yang terinfeksi Ganoderma ringan, sedang, berat dan tanaman sehat. Hasil pengujian menunjukkan bahwa profil senyawa organik volatil yang dihasilkan oleh infeksi Ganoderma sp. dapat ditangkap oleh Electronic Nose 118 dengan baik. Hasil analisis Linear Discriminat Analysis (LDA) menunjukkan bahwa sampel akar dan batang terbedakan dengan tingkat diskriminasi yang cukup tinggi dengan nilai secara berurutan yaitu 89,66% dan 94,59%, sedangkan untuk validasi internal masing-masing 98,18% dan 89,18%. Namun demikian, untuk sampel daun dan tanah, pengujian dengan Electronic Nose 118 menghasilkan tingkat diskriminasi yang rendah. Hasil pengujian menunjukkan Electronic Nose 118 dapat membedakan sampel akar dan batang dari tanaman sehat dan tanaman terserang Ganoderma dengan akurasi tinggi.[Kata kunci : Ganoderma, LDA, infeksi patogen, sensor, senyawa organik volatil]
Co-Authors Achmad Tavip Junaedi Adi Rahayu Adilia Galuh Pramantari AF Kurniawan Agung Putra Leksana Agus Anggoro Sigit Agustin Sri MULYATNI Ahmad Dardiri Alfiyyah Nurlaili Sukma Alif Noor Anna andi gunawan Antelas Eka Winahyo Atien Priyanti Aulia Aulia Baradista Dimas Leotman Bram Brahmantiyo Budiyanto Budiyanto Choirul Amin Chotimah Chotimah Damianus Manesi Danardono Danardono Danis Novianto Darwin Rio Budi Syaka Deden Dewantara ERIS Dewi Liesnoor Setyowati Dilahur Dilahur Dina Syafrianingsih Dwi ASTUTI Dwi Priyanto Edy Suprapto Eka Fitriana Elin Karlina Endang Sri Sudalmi Endang Sri Suldalmi evelyn wijaya Evy Khuriyana Fadila Fitria Wulandari Fadrul Fadrul Fahrizal Fahrizal Gunawarman Gunawarman H. Sutanto Hadi Wasito HAPPY WIDIASTUTI Henny Soepriyanti I Nurhasanah Ihwan Susilo Intan Apriadi Irma KRESNAWATY Isnandar Isti’ana Maftuchah Jumadi Jumadi K. S. Firdausi Kartika Cindi Wulandari Karyono Karyono Krisma Dwi Rohana Kuswaji Dwi Priyono Kuwat Triyana Laksono Trisnantoro Lina Ayu Widyastuti Linuwih Adhi Anggoro M. Rizal At-Thariq Made Wena Maria Erviana Klau Meliana Ida Pingki Rukmana Mochamad Soelton Mochamad Sofwan Muhammad Faisal Muhammad Farid Aminudin Nini Daniah Novita Eka Kumalasari Nur Fadjrih Asyik Nuzuliarini Nuris Pepri Pratama Pribadi Pribadi R. Mahmud Sugandi Rachmat Suryadithia Rian Rosartio Riyanti Sinaga Rizki Ardianto Nugroho Rizky Handayani Rudiyanto Rudiyanto Ruska Wati Saiful Bahri Sapto Riyadi Sigit Widiyarto Siswadi Siswadi Siti Maryam Sri Indriyanti Stefani Chandra Sudirman Wilian Sugiyanto Sugiyanto Sukarya Danimihardja Teddy Chandra Tegar Dadang Dadang Tri Kuncoro Tri Panji Triyono, Kharis U Kaltsum Udin Udin Untung Waluyo Wita KIMBERLY Wofrid E. Bianome Yohana Natalia Attik Primastuti Yuli Priyana Yusmarnida Yusmarnida Zempi, Chairun Nisa