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Masaru Mizoguchi

Department of Global Agricultural Sciences, The University of Tokyo

Author-ID : 3980426

Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Engineering

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Penentuan Kelembaban Tanah Optimum Untuk Budidaya Padi Sawah SRI (System Of Rice Intensification) Menggunakan Algoritma Genetika Chusnul Arif; Budi Indra Setiawan; Masaru Mizoguchi
Jurnal Irigasi Vol 9, No 1 (2014): Jurnal Irigasi
Publisher : Balai Teknik Irigasi

In this study, an optimal soil moisture level that maximizes both yield and water productivity of system of rice intensification (SRI) paddy field was simulated by genetic algorithms (GA) model. The GA model was performed to find an optimal combination of soil moisture levels according to the empirical data during three cropping seasons at Nusantara Organic SRI Center (NOSC), Nagrak Sukabumi, West Java. Here, we classified soil moisture level into three levels i.e. wet (W), medium (M) or dry (D) based on the soil water retention curve. As the results, the optimal soil moisture was a combination of wet, wet, medium, and dry levels of soil moisture for initial, crop development, mid-season and late season growth stages, respectively. The wet level in the initial and crop development growth stages should be achieved providing enough water for the plant to develop root, stem and tiller, and then the field can be drained into the medium level with the irrigation threshold of field capacity to avoid spikelet sterility in the mid-season stage, and finally, let the field in the dry level to save more water in the late season stage when plant water requirement is minimum. By this scenario, it was simulated that the yield can be increased up to 4.40% and water productivity up to 8.40% with saving water up to 12.28% compared to the empirical data.

Pengembangan Model Jaringan Saraf Tiruan untuk Menduga Emisi Gas Rumah Kaca dari Lahan Sawah dengan berbagai Rejim Air Chusnul Arif; Budi Indra Setiawan; Slamet Widodo; - Rudiyanto; Nur Aini Iswati Hasanah; Masaru Mizoguchi
Jurnal Irigasi Vol 10, No 1 (2015): Jurnal Irigasi
Publisher : Balai Teknik Irigasi

The paper proposes the artificial neural networks (ANN) model to predict methane (CH4) and Nitrous Oxide (N2O) emissions under different irrigation system based on easily measurable environmental biophysics parameters such as soil moisture, soil temperature and soil electrical conductivity. To verify the model, two experiments were conducted in the pot experiments in two different locations. The first location was in the greenhouse of Meiji University, Kanagawa Prefecture, Japan from 4 June to 21 September 2012, and the second location was in water resources engineering laboratory, Department of Civil and Environmental Engineering-IPB from 2 July to 10 October 2014. In each location, there were three different irrigation systems adopted with the System of Rice Intensification (SRI) principles. We called the experiment as SRI Basah (SRI B1 and SRI B2 for the first and second locations, respectively), SRI Sedang (SRI S1 dan SRI S2) dan SRI Kering (SRI K1 dan SRI K2). Each treatment has different water level during growth stages. As the results, the developed ANN model can predict CH4 and N2O emissions accurately with determination coefficients of 0.93 and 0.70 for CH4 and N2O prediction, respectively. From the model, characteristics of those greenhouse gas emissions can be well identified. For the mitigation strategy, SRI B1 and SRI B2 treatments in which the water level was kept at nearly soil surface are the best strategy with highest yield production and lowest GHG emission.

Potensi Pemanasan Global dari Padi Sawah System of Rice Intensification (SRI) dengan Berbagai Ketinggian Muka Air Tanah Chusnul Arif; Budi Indra Setiawan; Deka Trisnadi Munarso; Muhammad Didik Nugraha; Pradha Wihandi Sinarmata; Ardiansyah Ardiansyah; Masaru Mizoguchi
Jurnal Irigasi Vol 11, No 2 (2016): Jurnal Irigasi
Publisher : Balai Teknik Irigasi

System of Rice Intensification (SRI) is known as alternative rice farming for the mitigation of greenhouse gas (GHG) emissions. There are two main gasses emitted from paddy fields, i.e., methane (CH4) and nitrous oxide (N2O). Both of these gases have different characteristics as response on water availability in the fields which is represented by groundwater levels. Global Warming Potential (GWP) is used as an index that allowed comparisons of the global warming impacts of different gases at specific time period to warm the earth and it is equivalent to the value of the potential of CO2. This study aimed to analysis the global warming potential from different water regimes with SRI practices. Achieving the objective, rice cultivation with three water regimes was carried out during one planting season (14 April until 5 August 2016) in experimental plots of Department of Civil and Environmental Engineering IPB, Bogor, Java West. The regimes were continous flooding, moderate and dry regimes, respectively. The results showed that dry regime has the lowest global warming potential than those others regimes. Its potential was 34% and 41% lower than those for flooding and moderate regimes, respectively. In addition, dry regime produced more grain yield. Its productivity was 21% greater than that flooding regime. These results were obtained from specific climate and location. To corroborate the results, further research is needed under different weather conditions and multi-locations.

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