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Author Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F.
Title (up) A comparison of within-season yield prediction algorithms based on crop model behaviour analysis Type Journal Article
Year 2015 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology
Volume 204 Issue Pages 10-21
Keywords stics crop model; climate variability; lars-wg; yield prediction; log-normal distribution; convergence in law theorem; central limit theorem; weather generator; nitrogen balances; generic model; wheat; simulation; climate; stics; variability; skewness; efficiency
Abstract The development of methodologies for predicting crop yield, in real-time and in response to different agro-climatic conditions, could help to improve the farm management decision process by providing an analysis of expected yields in relation to the costs of investment in particular practices. Based on the use of crop models, this paper compares the ability of two methodologies to predict wheat yield (Triticum aestivum L.), one based on stochastically generated climatic data and the other on mean climate data. It was shown that the numerical experimental yield distribution could be considered as a log-normal distribution. This function is representative of the overall model behaviour. The lack of statistical differences between the numerical realisations and the logistic curve showed in turn that the Generalised Central Limit Theorem (GCLT) was applicable to our case study. In addition, the predictions obtained using both climatic inputs were found to be similar at the inter and intra-annual time-steps, with the root mean square and normalised deviation values below an acceptable level of 10% in 90% of the climatic situations. The predictive observed lead-times were also similar for both approaches. Given (i) the mathematical formulation of crop models, (ii) the applicability of the CLT and GLTC to the climatic inputs and model outputs, respectively, and (iii) the equivalence of the predictive abilities, it could be concluded that the two methodologies were equally valid in terms of yield prediction. These observations indicated that the Convergence in Law Theorem was applicable in this case study. For purely predictive purposes, the findings favoured an algorithm based on a mean climate approach, which needed far less time (by 300-fold) to run and converge on same predictive lead time than the stochastic approach. (C) 2015 Elsevier B.V. All rights reserved.
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ISSN 0168-1923 ISBN Medium Article
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4647
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Author Dumont, B.; Leemans, V.; Ferrandis Vallterra, S.; Vancutsem, F.; Seutin, B.; Bodson, B.; Destain, J.-P.; Destain, M.-F.
Title (up) A first step towards a real-time predictive yield support system Type Conference Article
Year 2012 Publication Abbreviated Journal
Volume Issue Pages
Keywords CropM
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Area Expedition Conference CIGR-AgEng 2012, International Conference on Agricultural Engineering, Valencia (Spain)., 2012-07-07 to 2012-07-12
Notes Approved no
Call Number MA @ admin @ Serial 2403
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Author Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F.
Title (up) A Site-Specific Grain Yield Response Surface : Computing the Identity Card of a Crop Under Different Nitrogen Management Scenarios Type Conference Article
Year 2013 Publication Abbreviated Journal
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Keywords CropM
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Area Expedition Conference Proceedings of the EFITA-WCCA-CIGR 2013 - Sustainable Agriculture through ICT innovation, 2013-11-03 to 2013-11-06, Torino
Notes Approved no
Call Number MA @ admin @ Serial 2408
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Author Dumont, B.; Leemans, V.; Ferrandis Vallterra, S.; Vancutsem, F.; Seutin, B.; Bodson, B.; Destain, J.-P.; Destain, M.-F.
Title (up) Assessing the potential of an algorithm based on mean climatic data to predict wheat yield Type Conference Article
Year 2012 Publication Abbreviated Journal
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Keywords CropM
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Area Expedition Conference 11th International Conference on Precision Agriculture. Indianapolis (USA)., 2012-07-15 to 2012-07-18
Notes Approved no
Call Number MA @ admin @ Serial 2404
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Author Dumont, B.; Leemans, V.; Ferrandis, S.; Bodson, B.; Destain, J.-P.; Destain, M.-F.
Title (up) Assessing the potential of an algorithm based on mean climatic data to predict wheat yield Type Journal Article
Year 2014 Publication Precision Agriculture Abbreviated Journal Precision Agric.
Volume 15 Issue 3 Pages 255-272
Keywords stics model; yield prediction; real-time; proxy-sensing; stochastic weather generator; crop yield; mediterranean environment; simulation-model; variability; nitrogen; ensembles; forecasts; demeter; europe
Abstract The real-time non-invasive determination of crop biomass and yield prediction is one of the major challenges in agriculture. An interesting approach lies in using process-based crop yield models in combination with real-time monitoring of the input climatic data of these models, but unknown future weather remains the main obstacle to reliable yield prediction. Since accurate weather forecasts can be made only a short time in advance, much information can be derived from analyzing past weather data. This paper presents a methodology that addresses the problem of unknown future weather by using a daily mean climatic database, based exclusively on available past measurements. It involves building climate matrix ensembles, combining different time ranges of projected mean climate data and real measured weather data originating from the historical database or from real-time measurements performed in the field. Used as an input for the STICS crop model, the datasets thus computed were used to perform statistical within-season biomass and yield prediction. This work demonstrated that a reliable predictive delay of 3-4 weeks could be obtained. In combination with a local micrometeorological station that monitors climate data in real-time, the approach also enabled us to (i) predict potential yield at the local level, (ii) detect stress occurrence and (iii) quantify yield loss (or gain) drawing on real monitored climatic conditions of the previous few days.
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Language English Summary Language Original Title
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ISSN 1385-2256 1573-1618 ISBN Medium Article
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Notes CropM Approved no
Call Number MA @ admin @ Serial 4621
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