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Investigating data-driven approaches to optimize nitrogen recommendations for winter wheat., , , , , , , и . Comput. Electron. Agric., (2024)Designing future barley ideotypes using a crop model ensemble, , , , , , , , , и 11 other автор(ы). European Journal of Agronomy, (2017)Improving wheat yield prediction integrating proximal sensing and weather data with machine learning., , , , , , , , , и . Comput. Electron. Agric., (2022)Modeling spatial and temporal optimal N fertilizer rates to reduce nitrate leaching while improving grain yield and quality in malting barley., , , , , и . Comput. Electron. Agric., (2021)Machine Learning-Based Approaches for Predicting SPAD Values of Maize Using Multi-Spectral Images., , , , , , и . Remote. Sens., 14 (6): 1337 (2022)Response of wheat growth, grain yield and water use to elevated CO2 under a Free-Air CO2 Enrichment (FACE) experiment and modelling in a semi-arid environment, , , , , , , , , и 3 other автор(ы). GLOBAL CHANGE BIOLOGY, (июля 2015)Assessing the Robustness of Vegetation Indices to Estimate Wheat N in Mediterranean Environments., , , и . Remote Sensing, 6 (4): 2827-2844 (2014)Response of wheat growth, grain yield and water use to elevated CO2under a Free-Air CO2Enrichment (FACE) experiment and modelling in a semi-arid environment, , , , , , , , , и 3 other автор(ы). Global Change Biology, 21 (7): 2670--2686 (февраля 2015)Evaluating the precision of eight spatial sampling schemes in estimating regional means of simulated yield for two crops., , , , , , , , , и 19 other автор(ы). Environ. Model. Softw., (2016)Integrated UAV-Based Multi-Source Data for Predicting Maize Grain Yield Using Machine Learning Approaches., , , , , , и . Remote. Sens., 14 (24): 6290 (декабря 2022)