000			02566nab|a22003377a|4500
001			64500
003			MX-TxCIM
005			20211108145059.0
008			202112s2021||||xxk|||p|op||||00||0|eng|d
022			_a2048-7010 (Online)
024	8		_ahttps://doi.org/10.1186/s40066-021-00314-9
040			_aMX-TxCIM
041			_aeng
100	1		_aAl-Gunaid, M.A. _924671
245	1	0	_aForecasting potential yields under uncertainty using fuzzy cognitive maps
260			_aUnited Kingdom : _bBioMed Central, _c2021.
500			_aPeer review
500			_aOpen Access
520			_aBackground: The aim of the study is identification of factors influencing the reduction of the potential maximum yield of winter wheat in weather conditions of dry farming in European part of Russia, Volgograd region. The novelty of the work is forecasting potential yields under uncertainty that allows to assess the risks and potential threats that can influence and maximize the potential yield. To solve this problem, the tool for formalization, analysis and modeling of semi-structured systems and processes Fuzzy Cognitive Maps (FCM) is used. Results: Based on disparate and heterogeneous information about the multitude of external influences on crop formation during plant photosynthesis, a model for analyzing the level of influencing factors on the target factor is constructed and an effective control impact scenario is developed. This model is used to identify the factors, where each one of them iteratively passes from the initial value to the stable one according to the chosen formula, based on which, the influence of the factors on each other are determined. Conclusions: The conclusions obtained as a result of the work confirm the concept of precision farming: the quantity and quality of innovation in agriculture depends on the ability to apply it effectively in the field. Developed method of predicting potential yield levels can be used not only to model future agricultural performance, but also to estimate harvested yields.
546			_aText in English
650		7	_aForecasting _2AGROVOC _92701
650		7	_aAgriculture _2AGROVOC _91007
650		7	_aMaps _2AGROVOC _915980
700	1		_aSalygina, I.I. _924672
700	1		_aShcherbakov, M.V. _924673
700	1		_aTrubitsin, V.N. _924674
700	1		_aGroumpos, P.P. _924675
773	0		_tAgriculture and Food Security _gv. 10, art. 32 _dUnited Kingdom : BioMed Central, 2021. _x2048-7010
856	4		_yClick here to access online _uhttps://doi.org/10.1186/s40066-021-00314-9
942			_cJA _n0 _2ddc
999			_c64500 _d64492