Biomass database for energy conversion in Madagascar. [PDF]
Rakotoarivelo AM, Randrianantenaina NN.
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State formation across cultures and the role of grain, intensive agriculture, taxation and writing. [PDF]
Opie C, Atkinson QD.
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Crop GraphRAG: pest and disease knowledge base Q&A system for sustainable crop protection. [PDF]
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Correction: Genetic variations associated with adaptation in Acrocomia palms: A comparative study across the Neotropics for crop improvement. [PDF]
PLOS One Staff.
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Integration of X-Ray CT, Sensor Fusion, and Machine Learning for Advanced Modeling of Preharvest Apple Growth Dynamics. [PDF]
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Implementing the CROP reference architecture
Proceedings of the 19th Panhellenic Conference on Informatics, 2015We examine the issue of adaptation of learning services to particular learner needs. We argue that offering custom learning services involves two aspects of the commodities of the services: offering custom services before their execution and during their execution.
Maria Tsiakmaki, Chrysafis Hartonas
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Forecasting of reference crop evapotranspiration
Agricultural Water Management, 1993Abstract The first step in the determination of irrigation water requirements for use in project planning, design, and operation commonly involves the prediction of the reference crop evapotranspiration. This paper presents a simple mathematical model for forecasting reference crop evapotranspiration at three stations in California that represent ...
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Reference Crop Evapotranspiration from Temperature
Applied Engineering in Agriculture, 1985MEASURED lysimeter evapotranspiration of Alta fescue grass (a cool season grass) is taken as an index of reference crop evapotranspiration (ETo). An equation is presented that estimates ETo from measured values of daily or mean values of maximum and minimum temperature. This equation is compared with various other methods for estimating ETo.
null George H. Hargreaves +1 more
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Forecasting weekly reference crop evapotranspiration series
Hydrological Sciences Journal, 1995Abstract Evapotranspiration (ET) is an important process in the hydrological cycle and needs to be accurately quantified for proper irrigation scheduling and optimal water resources systems operation. The time variant characteristics of ET necessitate the need for forecasting ET. In this paper, two techniques, namely a seasonal ARIMA model and Winter's
S. MOHAN, N. ARUMUGAM
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