Development of a crop knowledge base for Europe

Russell, G.; Muetzelfeldt, Robert; Taylor, Karen W.; Terres, Jean‐Michel

doi:10.1016/s1161-0301(99)00030-1

Cited by 10 publications

(2 citation statements)

References 6 publications

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“…Russell et al [35] reviewed the Barley Knowledge Base and AIS system for the European Community. Janssen et al [36] demonstrated the need of Integrated Database System by combining both remote sensing satellite data and ground truth data in order to establish Pan-European agricultural database system to support EU CAP objectives.…”

Section: Introductionmentioning

confidence: 99%

Cereal Yield Modeling in Finland Using Optical and Radar Remote Sensing

et al. 2010

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Optical VGI yield estimates were validated with CropWatN crop model yield estimates using SPOT and NOAA data (mean R 2 0.71, RMSE 436 kg/ha) and with composite SAR/ASAR and NDVI models (mean R 2 0.61, RMSE 402 kg/ha) using both reflectance and backscattering data. CropWatN and Composite SAR/ASAR & NDVI model mean yields were 4,754/4,170 kg/ha for wheat, 4,192/3,848 kg/ha for barley and 4,992/2,935 kg/ha for oats.

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Section: Introductionmentioning

confidence: 99%

Cereal Yield Modeling in Finland Using Optical and Radar Remote Sensing

et al. 2010

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“…The development of a hybrid numerical-symbolic approach to crop modeling is useful for knowledge specification and reasoning about locations having similar meteorological and agricultural conditions (Russell et al, 1999). Using meteorological data and soil characteristics, it is possible to deduce some properties from contextual information and domain knowledge about the main crop cycles and traditional winemaking present in worldwide with associated specified requirements (Pinney, 2012).…”

Section: Introductionmentioning

confidence: 99%

Knowledge engineering approach for the analysis of viticulture

Kamsu-Foguem

Flammang²,

Tchuenté-Foguem

2015

Ecological Informatics

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International audienceThe sustainable development of agricultural regions requires a methodical approach that will make a viable land management system policy in practice. In this regard, distinctive contextual characteristics of a country (remarkable areas for raising the regional products) could be taken into account in order to promote the good character of agricultural outputs and to increase the added value of considered lands. The manuscript primarily describes in qualitative and quantitative terms a mechanism for synthesizing information about wine production characteristics and therefore provides sufficient substantive treatment of agricultural or other system interactions. Firstly, the manuscript presents a discussion about many factors that affect wine production, and secondly, the focus is more on the development of an integrated approach using numerical and symbolic reasoning. The Geoviticulture Multicriteria Climatic Classification (MCC) System is engaged with a methodology comprising three viticultural climatic indexes of different natures: hydric type (dryness index), heliothermal type (Huglin index), and Nictothermal type (Cold Night Index). The knowledge representation is symbolized with the conceptual graphs formalism and the reasoning mechanisms are based on graph operations. A visual reasoning development focuses more on the decision process that would seem more appropriate for a practice on decision support. In addition, the Decision Support System (DSS) component is illustrated with a case study of Croatia republic in very broad characterizations of its main regional grape varieties

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A knowledge base model for evaluation of bio-physical tendency of dryland

Jana

Khire

2004

J. Geogr. Sci.

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Development of a crop knowledge base for Europe

Cited by 10 publications

References 6 publications

Cereal Yield Modeling in Finland Using Optical and Radar Remote Sensing

Cereal Yield Modeling in Finland Using Optical and Radar Remote Sensing

Knowledge engineering approach for the analysis of viticulture

A knowledge base model for evaluation of bio-physical tendency of dryland

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