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| Filter results8 paper(s) found. |
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1. Site-specific Management For Biomass Feedstock Production: Development Of Remote Sensing Data Acquisition SystemsEfficient biomass feedstock production supply chain spans from site-specific management of crops on field to the gate of biorefinery. Remote sensing data acquisition systems have been introduced for site-specific management, which is a part of the engineering solutions for biomass feedstock production. A stand alone tower remote sensing platform was developed to monitor energy crops using multispectral imagery. The sensing system was capable of collecting RGB and CIR images during the crop growing... T. Ahamed, L. Tian, Y. Zhang, Y. Xiong, B. Zhao, Y. Jiang, K. Ting |
2. A Non-Destructive Method of Estimating Red Tip Disease in PineappleRed Tip disease typically reduces pineapple yields by up to 50%. At present, the causal agent of Red Tip disease is still unconfirmed. B... F. Abu kassim, G. Vadamalai, A. Mohd hanif, S.K. Balasundram |
3. Near-Real-Time Remote Sensing And Yield Monitoring Of Biomass CropsThe demand for bioenergy crops production has increased tremendously by the biofuel industry for substitution of traditional fuels due to the economic availability and environmental benefits. Pre-Harvest monitoring of biomass production is necessary to develop optimized instrumentation and data processing systems for crop growth, health and stress monitoring; and to develop algorithms for field operation scheduling. To cope with the problems of missing critical... Y. Zhao, L. Li, K.C. Ting, L.F. Tian, T. Ahamed |
4. Design of a Greenhouse Monitoring System Based on GSM TechnologiesNowadays, internet and mobile technologies are developing and being used in everyday life. Systems based on mobile technologies and IoT (Internet of Things) are being popular in every area of life and science. Innovative IoT applications are helping to increase the quality, quantity, sustainability and cost effectiveness of agricultural production. In this study; a system which monitors temperature, relative humidity and PAR (Photosynthetically Active Radiation) and warns the farmer... G.T. Seyhan, U. Yegul, M. Ayık |
5. Canopy Temperature Mapping with a Vineyard RobotThe wine industry is a strategic sector in many countries worldwide. High revenues in the wine market typically result in higher investments in specialized equipment, so that producers can introduce disruptive technology for increasing grape production and quality. However, many European producers are approaching retirement age, and therefore the agricultural sector needs a way for attracting young farmers who can assure the smooth transition between generations; digital technology offers an opportunity... V. Saiz-rubio, M. Diago, J. Tardaguila, S. Gutierrez, F. Rovira-más, F. Alves |
6. Using an Unmanned Aerial Vehicle with Multispectral with RGB Sensors to Analyze Canola Yield in the Canadian PrairiesIn 2017 canola was planted on 9 million hectares in Canada surpassing wheat as the most widely planted crop in Canada. Saskatchewan is the dominant producer with nearly 5 million hectares planted in 2017. This crop, seen both as one of the highest-yielding and most profitable, is also one of most expensive and input-intensive for producers on the Canadian Prairies. In this study, the effect of natural and planted shelterbelts on canola yield was compared with canola yield... K. Hodge, L. Bainard, A. Smith, F. Akhter |
7. Precision Irrigation Management Through Conjunctive Use of Treated Wastewater and Groundwater in OmanAgriculture under arid environment is always become a challenge due to water scarcity and salinity problems. With average rainfall of 100 mm, agriculture in Oman is limited due to the arid climate and limited arable lands. More than 50 percent of the arable lands are located in the 300 km northern coastal belt of Al-Batinah region. In addition, country is facing severe problem of sea water intrusion into the groundwater aquifers due to undisciplined excessive groundwater (GW) abstraction... H. Jayasuriya, A. Al-busaidi, M. Ahmed |
8. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and VisionAdvancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor. While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collecting,... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi |