Watch It Grow, an innovative platform for a sustainable growth of the Belgian potato production.

Belgium is the largest exporter of frozen potato products in the world. Each year, Belgian companies process over four million tons of potatoes into French fries, potato chips and other products. To ensure a sustainable growth of the potato sector, a higher potato production is needed. In this context, expansion of agricultural land is not an option.Potato processors, traders and packers largely work with potato contracts. The close follow up of contracted parcels is important to improve the quantity and quality of the crop and reduce risks related to storage, packaging or processing. The use of geo-information by the sector is limited, notwithstanding the great benefits that this type of information may offer. At the same time, new sensor-based technologies continue to gain importance and farmers increasingly invest in these technologies.The combination of geo-information and crop modelling might strengthen the competitiveness of the Belgian potato chain in a global market.In the frame of the iPot project, financed by the Belgian Science Policy Office (BELSPO), a commercial webtool called Watch iT Grow helping potato traders, the processing industry as well as farmers to monitor the potato growth has been developed.By using weather data, satellite images, aerial images (taken with drones) and data from ground measurements, users are for instance able to follow whether the crops emerge properly from the ground, how the growth is developing, whether diseases might be present or when farmers can start harvesting. The collected data are combined into crop growth models allowing the webtool to propose as well yields estimations and predictions per plot

Process-based modelling of the nutritive value of forages: a review

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Potential performances of remotely sensed LAI assimilation in WOFOST model based on an OSS experiment

An Observing System Simulation Experiment (OSSE) has been defined to assess the potentialities of assimilating winter wheat leaf area index (LAI) estimations derived from remote sensing into the crop growth model WOFOST. Two assimilation strategies are considered: one based on Ensemble Kalman Filter (EnKF) and the second on recalibration/re-initialisation of uncertain model parameters and initial state conditions. The main objective of the OSS Experiment is to estimate the requisites for the remotely sensed LAI, in terms of accuracy and sampling frequency, to reach target of either 25 or 50% reduction of errors on the final estimation of grain yields. Our results demonstrate that EnKF is not suitable for assimilating LAI in WOFOST as the average error on final grain yields estimation globally increases. These poor results can be explained by the possible differences of phenological development existing between assimilated and modelled LAI values (difference called “phenological shift” in our study) which is not corrected by the EnKF-based assimilation strategy. On the contrary, a recalibration-based assimilation approach globally improves the estimation of final grain yields in a significant way. On average, such improvement can reach up to approximately 65% when observations are available all along the growing season. Improvements on the order of 20% can be already be attained early in the season, which is of great interest in a crop yield forecasting perspective. If the first objective (25%) of error reduction on final grain yields can be reached in a quite high number of assimilated LAI observations availabilities and uncertainty levels, the field of possibilities is significantly restricted for the second objective (50%) and implies to have LAI observations available all along the growing season, at least on a weekly basis and with an uncertainty level equal or ideally lower than 10%. These requirements are not currently met from neither a technological nor an operational point of view but the results presented here can provide guidelines for future missions dedicated to crop growth monitoring. -------------------------------------------------------------------------------

The B-CGMS project : evaluation after 5 years of monitoring and prediction

The B-CGMS project, started in 1998, is the adaptation to Belgian Conditions of the European Crop Growth Monitoring System (CGMS). This project involved 3 Belgian scientific institutes: the Walloon agricultural research Centre (CRA-W), the Flemish Institute for Technological Research (VITO) and the University of Liège (ULg). The main difference with the European system is that more detailed inputs (meteorological, soil and NUTS inputs) are used. Crop yields predictions are realised on a monthly basis during the growing season (from April to September) for 6 crops (winter wheat, winter barley, maize, Potato, sugar beet, winter rapeseed). Yields predictions as well as analyses of meteorological situation of the month and RS information on the state of the crops are published in agrometeorological bulletins sent by e-mail since 2002. The information is also available on the Internet website of the project (http://.b-cgms.cra.wallonie.be). Crop yields predictions are produced through a combination of linear regression models which may include different categories of yield indicators (trend, meteo, RS and agrometeorological model outputs). Crop yields predictions procedure is currently semi-automated by the use of a statistical calibration toolbox (StatCaT). The evaluation of the project after 5 years of monitoring and prediction has first shown that final yields predicted B-CGMS as well as the ones predicted by MARS are coherent compared with official yields: no significant differences are observed. As far as the accuracy according to the month for which the prediction is made is concerned, we can notice that at agricultural circumscriptions level and for winter crops a lower precision of B-CGMS is observed before June and that there is no improvement in July (in comparison with June). The same evolution is observed for summer crops before July but in August and September, the prediction accuracy decreases. Even if calibration models present high adjusted coefficient of determination, the technological trend explains an important part of the variability and it is therefore necessary to consider the effect of a year factor on the quality of prediction in order to clearly the interest of the agrometeorological model. For some crops (as potato), adding agrometeorological yield outputs to models including already the technological trend allow to improve the quality of prediction especially for “extreme” year i.e. years where official yields move away significantly from the technological trend. For others crops as winter wheat, this improvement of the quality of prediction is not observed. However, fortunately, adding other yield indicators as meteo indicators can improve in general the quality of prediction and once again especially for “extreme” years

Bulletin agrométéorologique - Avril 2005

L’hiver météorologique (décembre 2004 à février 2005) peut être caractérisé de normal, tout comme les mois de mars et avril qui lui ont succédé. La situation des cultures d’hiver est également normale, avec des rendements qui s’annoncent généralement supérieurs à ceux de 2003 et de 2004 pour le froment d’hiver. Dans le cas de l’orge d’hiver, les estimations de rendements n’atteignent pas les résultats de 2004 mais dépassent largement les rendements observés en 2003. Il est prématuré d’émettre des prévisions pour les cultures printanières

Bulletin agrométéorologique - Mai 2006

Des précipitations fortement excédentaires ont été enregistrées au mois de mai, particulièrement dans la deuxième quinzaine. Le rayonnement fut très anormalement inférieur à la moyenne et les températures, bien qu’en moyenne proche de la normale, ont été basses dans la dernière décade. Le retard accusé par la végétation depuis le début de la saison n’a pas encore été entièrement résorbé. La situation des cultures est globalement favorable, laissant entrevoir des rendements généralement supérieurs à la moyenne des cinq années précédentes

Bulletin agrométéorologique - Avril 2006

L’hiver météorologique (décembre 2005 à février 2006) peut être caractérisé de normal. Les mois de mars et avril furent plus froids que la normale et cela a pour conséquence un retard phénologique évalué à 10 – 15 jours selon les endroits. Les prévisions de rendement annoncent pour les cultures d’hiver, des rendements équivalent ou légèrement supérieurs à 2005 mais inférieurs à ceux de 2004. Il est prématuré d’émettre des prévisions pour les cultures printanières

Bulletin agrométéorologique - Juin 2006

Le mois de juin fut chaud permettant à la plupart des cultures de bénéficier de très bonnes conditions de croissance. Le retard de croissance observé depuis le début du suivi des cultures a quasi complètement disparu. La faible pluviométrie constatée au mois de juin n’a pour l’instant que peu de conséquences pour les cultures bien installées vu les réserves en eau accumulées le mois précédent. La situation des cultures est globalement favorable, laissant entrevoir des rendements généralement supérieurs à la moyenne des cinq années précédentes. Toutefois, cette prévision pourrait être revue à la baisse si la période sèche observée en juin se prolongeait en juillet