Aceh’s local rice is one of the plasma nutfah’s wealth in Indonesia. However, the availability and awareness of the people in Aceh to utilize the quality seed of Aceh’s rice are still very low due to pathogenic fungi that infected the seeds. The objective of this study is to identify the type of pathogenic fungi that carried out by the seeds of Aceh’s rice. A Completely Randomized Design (CRD) consisting of the four varieties local of Aceh was designed with the parameter including the present pathogens that attack the rice seed and germination. The four varieties Aceh’s seed namely: Sigupai variety (v1), Cantek maneh variety (v2), Cantek kuning variety (v3) dan Room kuning varietiy (v4). Data were analysed using ANOVA at 5% significant level and continued with the DMRT. The Results summarized that the Sigupai variety (v1) is the best low percentage of germination, approximately 45%, followed by room kuning (48.3%), maneh (56.7%), and cantek kuning (58.7%). These were caused by the pathogenic attacks which carried out in the form of Aspergilus sp and Fusarium sp.

Perkembangan kemajuan ekonomi pedesaan tergantung pada daya dukung serta  keberagaman komoditas pertanian yang ada. Tantangan dan hambatan sektor pertanian di pedesaan masih menjadi masalah yang paling prioritas untuk segera diselesaikan. Upaya keberadaan dari sektor pertanian diharapkan dapat memberikan dampak yang meluas bagi perkembangan ekonomi dan sosial masyarakat pedesaan.Tujuan penelitian untuk menganalisis determinan pendapatan petani padi sawah di Kecamatan Tanjung Morawa. Dalam penelitian ini yang dijadikan responden adalah petani padi. Metode analisis data dalam penelitian menggunakan analisis regresi linier berganda. Dari hasil penelitian dalam menganalisis determinan pendapatan petani padi sawah, ada beberapa faktor yang secara signifikan mempengaruhi pendapatan petani padi yaitu luas panen, hasil produksi dan biaya produksi.

Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and the internal drivers of change in the system, such as deforestation and land use change. A model framework of dynamic TOPMODEL, DECIPHeR v1—considering the flexibility, modularity, and portability—and Generalized Likelihood Uncertainty Estimation (GLUE) method are both used in this study. They reveal model performance for the streamflow simulation in a tropical catchment, i.e., the Kelantan River in Malaysia, that is prone to flooding and experiences high rates of land use change. Thirty-two years’ continuous simulation at a daily time scale simulation along with uncertainty analysis resulted in a Nash Sutcliffe Efficiency (NSE) score of 0.42 from the highest ranked parameter set, while 25.35% of the measurement falls within the uncertainty boundary based on a behavioral threshold NSE 0.3. The performance and behavior of the model in the continuous simulation suggests a limited ability of the model to represent the system, particularly along the low flow regime. In contrast, the simulation of eight peak flow events achieves moderate to good fit, with the four peak flow events simulation returning an NSE > 0.5. Nonetheless, the parameter scatter plot from both the continuous simulation and analyses of peak flow events indicate unidentifiability of all model parameters. This may be attributable to the catchment modeling scale. The results demand further investigation regarding the heterogeneity of parameters and calibration at multiple scales.

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