Showing 581 - 600 results of 1,609 for search '"Rice"', query time: 0.07s Refine Results
  1. 581

    Production Cost Efficiency and Profitability of <i>Abakaliki Rice</i> in Ihialia Local Government Area of Anambra State, Nigeria by J Egbodion, J Ahmadu

    Published 2015-07-01
    “…The study focused on the production cost efficiency and profitability of Abakaliki rice in Ihialia Local Government Area of Anambra State, Nigeria.. …”
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    Article
  2. 582

    Feeding behavior and prey characteristics of great egrets (Ardea alba) in eco-friendly and conventional rice fields in South Korea by Green Choi, Min Seock Do, Seok-Jun Son, Hyung-Kyu Nam

    Published 2025-01-01
    “…Abstract Rice fields are important wildlife habitats; however, intensive agricultural practices have reduced the population of farmland birds. …”
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    Regulating N Application for Rice Yield and Sustainable Eco-Agro Development in the Upper Reaches of Yellow River Basin, China by Aiping Zhang, Ruliang Liu, Ji Gao, Shiqi Yang, Zhe Chen

    Published 2014-01-01
    “…High N fertilizer and flooding irrigation applied to rice on anthropogenic-alluvial soil often result in N leaching and low recovery of applied fertilizer N from the rice fields in Ningxia irrigation region in the upper reaches of the Yellow River, which threatens ecological environment, food security, and sustainable agricultural development. …”
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  7. 587
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    Ultrasensitive Chemiresistive Gas Sensors Based on Dual-Mesoporous Zinc Stannate Composites for Room Temperature Rice Quality Monitoring by Jinyong Xu, Xuxiong Fan, Kaichun Xu, Kaidi Wu, Hanlin Liao, Chao Zhang

    Published 2025-01-01
    “…An innovative real-time method was developed for analyzing characteristic biomarkers of rice aging, enabling accurate and timely monitoring of rice quality.…”
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  9. 589

    The Phase-Formation Behavior of Composite Ceramic Powders Synthesized by Utilizing Rice Husk Ash from the Biomass Cogeneration Plant by Wenjie Yuan, Mingyu Fan, Chengji Deng, Jun Li, Hongxi Zhu

    Published 2015-01-01
    “…The development and utilization of biomass as a vital source of renewable energy were stimulated in order to reduce the global dependency on fossil fuels. A lot of rice husk ashes (RHA) were generated as the waste after the rice husk as the main fuel was burnt in the biomass cogeneration plant. …”
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    Assessing the establishment risk for parthenogenetic populations of Lissorhoptrus oryzophilus in global rice-growing areas and potential economic impact in China by Luoyuan Li, Luoyuan Li, Zhenan Jin, Ming Li, Yantao Xue, Jianyang Guo, Dong Jia, Ruiyan Ma, Zhichuang Lü, Xiaoqing Xian, Wanxue Liu

    Published 2025-01-01
    “…The rice water weevil, Lissorhoptrus oryzophilus Kuschel (Coleoptera: Curculionidae), threatens global rice production, with invasion events driven by its parthenogenetic populations. …”
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    Article
  14. 594

    Evaluating 28-Days Performance of Rice Husk Ash Green Concrete under Compression Gleaned from Neural Networks by Sharanjit Singh, Harish Chandra Arora, Aman Kumar, Nishant Raj Kapoor, Kennedy C. Onyelowe, Krishna Kumar, Hardeep Singh Rai

    Published 2023-01-01
    “…Cement, coarse aggregates, fine aggregates, water, rice husk ash, superplasticizer, and type of sample are used as input parameters to predict CS at 28 days. …”
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    Replacing rice straw with peanut vine and Broussonetia papyrifera silage in beef cattle feed reduced the use of soybean meal by Xin Yi, Yueming Li, Yue Liu, Minzhe Zhang, Zhenming Zhou, Qingxiang Meng, Hao Wu

    Published 2025-03-01
    “…In conclusion, replacing rice straw with PEV and BPS reduced the use of soybean meal but had no adverse effects on growth performance. …”
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  17. 597

    Simulation and Analysis of Water Consumption for Rice Production in Downstream Lancanng-Mekong River Basin under the Influence of Climate Change by XIE Shimeng, LIU Dengfeng, LIU Hui, HU Hongchang, DONG Zhiqiang, WANG Tianci, MING Guanghui

    Published 2024-01-01
    “…Agriculture water consumption is the main sector of socio-economic water consumption.The impact of climate change on agriculture water consumption may change the situation of water supply and demand in a region.The downstream Lancang-Mekong River Basin is selected as the study area.Based on the ERA5-Land dataset and the latest CMIP6 climate projection data,three emission scenarios (SSP1-2.6,SSP2-4.5,and SSP5-8.5) are selected in this study,and the AquaCrop model is used to separate non-productive soil evaporation from productive crop transpiration.The total transpiration during the rice growth period is taken as water consumption for rice production,and the historical and subsequent water consumption for rice production in the downstream Lancang-Mekong River Basin is simulated.The changes in water consumption for rice production and its correlation with temperature,precipitation,and CO<sub>2</sub> concentration are analyzed.The results show that the water consumption for rice production in the downstream Lancang-Mekong River Basin is manifested as more water consumption in the north and less water consumption in the south and has an overall decreasing trend annually.The trend is more obvious under the SSP5-8.5 scenario.In the SSP5-8.5 scenario,water consumption for rice production will reduce by 29.7% in the downstream Lancang-Mekong Basin in the far future.Compared with temperature and precipitation,the strongest correlation is found between water consumption for rice production and CO<sub>2</sub> concentration.In the far future of the SSP5-8.5 scenario,the correlation coefficient is-0.875 in Thailand and less than-0.9 in other countries in all seasons.…”
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    Pixel-wise navigation line extraction of cross-growth-stage seedlings in complex sugarcane fields and extension to corn and rice by Hongwei Li, Hongwei Li, Xindong Lai, Yongmei Mo, Deqiang He, Tao Wu, Tao Wu

    Published 2025-01-01
    “…Meanwhile, the generalization capacity of the proposed algorithm has been further verified on corn and rice datasets. Experimental results showed that for seedlings at different growth stages and diverse field environments, the mean error angle (MEA) ranges from 0.844° to 2.96°, the root mean square error (RMSE) ranges from 1.249° to 4.65°, and the mean relative error (MRE) ranges from 1.008% to 3.47%. …”
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