Judul: Uji Kinerja Alat Pengering Tipe Efek Rumah dengan Energi Surya dan Tungku Biomassa sebagai Sistem Pemanas Tambahan untuk Proses Pengeringan
Abstrak: Energi memainkan peranan yang penting bagi manusia untuk memenuhi kebutuhan hidupnya. Sebelum terjadinya krisis energi, umumnya penggunaan bahan bakar fosil menjadi primadona dan terIihat berlebihan dalam hal pemanfaatannya. Namun setelah krisis energi terjadi, dimana menurut analisa Foell (1983) dengan kurva Hubert untuk produksi BBM terutama di Indonesia pada tahun 2010 cadangan minyak burni hanya 30 milyar barel dan eenderung menurun (Abdullah,K. et al., 1 996) sedangkan kebutuhan akan konsumsi energi tersebut cenderung meningkat, hal tersebut menjadi masalah yang cukup serius. Untuk itu perlu dieari sumber energi altematif yang dapat memberikan sumber energi tambahan bagi manusia dengan syarat bersih, murah dan tersedia dalam jumlah yang banyak.
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Judul: Rancangan dan Kinerja Sistem Pengeringan Berenergi Surya, Biomassa dan Angin
Abstrak: Salah satu pemanfaatan energi terbarukan di bidang pertanian yaitu untuk proses pengeringan produk pertanian. Secara tradisional, para petani memanfaatkan energi surya untuk pengeringan produk pertanian. Seiring dengan perkembangan teknologi, beberapa inovasi teknologi pengeringan produk pertanian telah dikembangkan terutama di negara-negara berkembang bahkan negara maju. Di Indonesia, beberapa inovasi telah dilakukan oleh BPPT dan beberapa perguruan tinggi salah satunya IPS. Penelitian yang dilakukan Kamaruddin et al (1995) diantaranya pengering tipe efek rumah kaca untuk pengeringan biji-bijian dan buah-buahan. Selain itu telah dilakukan pula penggabungan sumber energi terbarukan untuk pengeringan salah satunya dengan energi biomassa.
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Judul: Quantitative Trait Loci Mapping for Trait in Categorical Scale
Abstrak: Genes or regions on chromosome underlying a quantitative trait are called Quantitative Trait Loci (QTL). Characterizing genes controlling quantitative trait on their position in chromosome and their effect on trait is through a process called QTL mapping. In estimating the QTL position and its effect, QTL mapping basically utilize the association between QTL and DNA markers. However, many important traits are obtained in categorical scale, such as resistance from certain disease. From a theoretical point of view, QTL mapping method assuming continuous trait could not be applied to categorical trait. This research was focusing on the assessment of the performance of Maximum Likelihood (ML) and Regression (REG) approach employed in QTL mapping as well as the performance of Lander and Botstein (LB) and Piepho method in determining critical value in testing the existence of QTL for binary and ordinal trait by means of simulation study. The simulation study to evaluate the performance of ML and REG approach was conducted by taking into account several factors that may affecting the performance of both approaches. The factors are: (1) marker density; (2) QTL effect; (3) sample size; (4) shape of phenotypic distribution; (5) number of categories; and (6) number of QTL. Moreover, the simulation study for evaluating LB and Piepho method in determining critical value was conducted by generating distribution of the test statistic under null hypothesis. From simulation study, it was obtained that LB and Piepho method showing similar performance in determining critical value in testing the existence of QTL for binary and ordinal trait. The simulation study also indicating that both methods could be used in determining critical value in QTL mapping analysis for binary trait as well as for ordinal trait if the REG approach is used but not if ML approach is used due to their poor performance. In assessing the performance of ML and REG approach in QTL mapping analysis for binary trait, the two approaches showing comparable performance; whereas for ordinal trait REG approach showing poor performance compared with ML approach in estimating thresholds. As a result, in QTL mapping analysis, ML and REG approach could be used when dealing with binary trait, whereas ML approach is suggested when dealing with ordinal trait.
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