Records |
Author |
Jing, Q.; Bélanger, G.; Baron, V.; Bonesmo, H.; Virkajärvi, P.; Young, D. |
Title |
Regrowth simulation of the perennial grass timothy |
Type |
Journal Article |
Year |
2012 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
Volume |
232 |
Issue |
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Pages |
64-77 |
Keywords |
biomass; carbohydrate; leaf area index; n uptake; reserve-dependent growth; temperature; nutritive-value; carbohydrate reserves; phleum-pratense; catimo model; leaf-area; nitrogen-fertilization; spring harvest; meadow fescue; tall fescue; growth |
Abstract |
Several process-based models for simulating the growth of perennial grasses have been developed but few include the simulation of regrowth. The model CATIMO simulates the primary growth of timothy (Phleum pratense L), an important perennial forage grass species in northern regions of Europe and North America. Our objective was to further develop the model CATIMO to simulate timothy regrowth using the concept of reserve-dependent growth. The performance of this modified CATIMO model in simulating leaf area index (LAI), biomass dry matter (DM) yield, and N uptake of regrowth was assessed with data from four independent field experiments in Norway, Finland, and western and eastern Canada using an approach that combines graphical comparison and statistical analysis. Biomass DM yield and N uptake of regrowth were predicted at the same accuracy as primary growth with linear regression coefficients of determination between measured and simulated values greater than 0.79, model simulation efficiencies greater than 0.78, and normalized root mean square errors (14-30% for biomass and 24-34% for N uptake) comparable with the coefficients of variation of measured data (1-21% for biomass and 1-25% for N uptake). The model satisfactorily simulated the regrowth LAI but only up to a value of about 4.0. The modified CATIMO model with its capacity to simulate regrowth provides a framework to simulate perennial grasses with multiple harvests, and to explore management options for sustainable grass production under different environmental conditions. Crown Copyright (C) 2012 Published by Elsevier B.V. All rights reserved. |
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0304-3800 |
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CropM, LiveM |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4473 |
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Author |
Siebert, S.; Ewert, F.; Rezaei, E.E.; Kage, H.; Grass, R. |
Title |
Impact of heat stress on crop yield-on the importance of considering canopy temperature |
Type |
Journal Article |
Year |
2014 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
Volume |
9 |
Issue |
4 |
Pages |
|
Keywords |
heat stress; crop yield; temperature; soil moisture; modelling; wheat; rye; harvest index; wheat yields; climate-change; winter-wheat; grain number; extreme heat; maize; variability; irrigation; drought |
Abstract |
Increasing crop productivity while simultaneously reducing the environmental footprint of crop production is considered a major challenge for the coming decades. Even short episodes of heat stress can reduce crop yield considerably causing low resource use efficiency. Studies on the impact of heat stress on crop yields over larger regions generally rely on temperatures measured by standard weather stations at 2 m height. Canopy temperatures measured in this study in field plots of rye were up to 7 degrees C higher than air temperature measured at typical weather station height with the differences in temperatures controlled by soil moisture contents. Relationships between heat stress and grain number derived from controlled environment studies were only confirmed under field conditions when canopy temperature was used to calculate stress thermal time. By using hourly mean temperatures measured by 78 weather stations located across Germany for the period 1994-2009 it is estimated, that mean yield declines in wheat due to heat stress during flowering were 0.7% when temperatures are measured at 2 m height, but yield declines increase to 22% for temperatures measured at the ground. These results suggest that canopy temperature should be simulated or estimated to reduce uncertainty in assessing heat stress impacts on crop yield. |
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2016-10-31 |
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English |
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Series Volume |
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Edition |
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ISSN |
1748-9326 |
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CropM, ftnotmacsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4814 |
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Author |
Mansouri, M.; Dumont, B.; Leemans, V.; Destain, M.-F. |
Title |
Bayesian methods for predicting LAI and soil water content |
Type |
Journal Article |
Year |
2014 |
Publication |
Precision Agriculture |
Abbreviated Journal |
Precision Agric. |
Volume |
15 |
Issue |
2 |
Pages |
184-201 |
Keywords |
crop model; bayes; data assimilation; extended kalman filtering; particle filtering; variational filtering; leaf-area index; parameter-estimation; crop models; moisture; instruments; management; sensors; state |
Abstract |
LAI of winter wheat (Triticum aestivum L.) and soil water content of the topsoil (200 mm) and of the subsoil (500 mm) were considered as state variables of a dynamic soil-crop system. This system was assumed to progress according to a Bayesian probabilistic state space model, in which real values of LAI and soil water content were daily introduced in order to correct the model trajectory and reach better future evolution. The chosen crop model was mini STICS which can reduce the computing and execution times while ensuring the robustness of data processing and estimation. To predict simultaneously state variables and model parameters in this non-linear environment, three techniques were used: extended Kalman filtering (EKF), particle filtering (PF), and variational filtering (VF). The significantly improved performance of the VF method when compared to EKF and PF is demonstrated. The variational filter has a low computational complexity and the convergence speed of states and parameters estimation can be adjusted independently. Detailed case studies demonstrated that the root mean square error of the three estimated states (LAI and soil water content of two soil layers) was smaller and that the convergence of all considered parameters was ensured when using VF. Assimilating measurements in a crop model allows accurate prediction of LAI and soil water content at a local scale. As these biophysical properties are key parameters in the crop-plant system characterization, the system has the potential to be used in precision farming to aid farmers and decision makers in developing strategies for site-specific management of inputs, such as fertilizers and water irrigation. |
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Edition |
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ISSN |
1385-2256 |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
CropM, ftnotmacsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4629 |
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Author |
Ferrise, R.; Toscano, P.; Pasqui, M.; Moriondo, M.; Primicerio, J.; Semenov, M.A.; Bindi, M. |
Title |
Monthly-to-seasonal predictions of durum wheat yield over the Mediterranean Basin |
Type |
Journal Article |
Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
Volume |
65 |
Issue |
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Pages |
7-21 |
Keywords |
yield predictions; seasonal forecasts; analogue forecasts; stochastic weather generator; empirical forecasting models; durum wheat; crop modelling; mediterranean basin; general-circulation model; scale climate indexes; crop yield; grain-yield; forecasts; simulation; region; precipitation; australia; europe |
Abstract |
Uncertainty in weather conditions for the forthcoming growing season influences farmers’ decisions, based on their experience of the past climate, regarding the reduction of agricultural risk. Early within-season predictions of grain yield can represent a great opportunity for farmers to improve their management decisions and potentially increase yield and reduce potential risk. This study assessed 3 methods of within-season predictions of durum wheat yield at 10 sites across the Mediterranean Basin. To assess the value of within-season predictions, the model SiriusQuality2 was used to calculate wheat yields over a 9 yr period. Initially, the model was run with observed daily weather to obtain the reference yields. Then, yield predictions were calculated at a monthly time step, starting from 6 mo before harvest, by feeding the model with observed weather from the beginning of the growing season until a specific date and then with synthetic weather constructed using the 3 methods, historical, analogue or empirical, until the end of the growing season. The results showed that it is possible to predict durum wheat yield over the Mediterranean Basin with an accuracy of normalized root means squared error of <20%, from 5 to 6 mo earlier for the historical and empirical methods and 3 mo earlier for the analogue method. Overall, the historical method performed better than the others. Nonetheless, the analogue and empirical methods provided better estimations for low-yielding and high-yielding years, thus indicating great potential to provide more accurate predictions for years that deviate from average conditions. |
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Edition |
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ISSN |
0936-577x 1616-1572 |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
CropM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4696 |
Permanent link to this record |
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Author |
Semenov, M.A.; Stratonovitch, P.; Alghabari, F.; Gooding, M.J. |
Title |
Adapting wheat in Europe for climate change |
Type |
Journal Article |
Year |
2014 |
Publication |
Journal of Cereal Science |
Abbreviated Journal |
J. Ceareal Sci. |
Volume |
59 |
Issue |
3 |
Pages |
245-256 |
Keywords |
A, maximum area of flag leaf area; ABA, abscisic acid; CV, coefficient of variation; Crop improvement; Crop modelling; FC, field capacity; GMT, Greenwich mean time; GS, growth stage; Gf, grain filling duration; HI, harvest index; HSP, heat shock protein; Heat and drought tolerance; Impact assessment; LAI, leaf area index; Ph, phylochron; Pp, photoperiod response; Ru, root water uptake; S, duration of leaf senescence; SF, drought stress factor; Sirius; Wheat ideotype |
Abstract |
Increasing cereal yield is needed to meet the projected increased demand for world food supply of about 70% by 2050. Sirius, a process-based model for wheat, was used to estimate yield potential for wheat ideotypes optimized for future climatic projections for ten wheat growing areas of Europe. It was predicted that the detrimental effect of drought stress on yield would be decreased due to enhanced tailoring of phenology to future weather patterns, and due to genetic improvements in the response of photosynthesis and green leaf duration to water shortage. Yield advances could be made through extending maturation and thereby improve resource capture and partitioning. However the model predicted an increase in frequency of heat stress at meiosis and anthesis. Controlled environment experiments quantify the effects of heat and drought at booting and flowering on grain numbers and potential grain size. A current adaptation of wheat to areas of Europe with hotter and drier summers is a quicker maturation which helps to escape from excessive stress, but results in lower yields. To increase yield potential and to respond to climate change, increased tolerance to heat and drought stress should remain priorities for the genetic improvement of wheat. |
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English |
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Edition |
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ISSN |
0733-5210 |
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Review |
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CropM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4543 |
Permanent link to this record |