|   | 
Details
   web
Records
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 (up) 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.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1385-2256 ISBN Medium Article
Area Expedition Conference
Notes CropM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4629
Permanent link to this record
 

 
Author Van Oijen, M.; Höglind, M.
Title Toward a Bayesian procedure for using process-based models in plant breeding, with application to ideotype design Type Journal Article
Year 2016 Publication Euphytica Abbreviated Journal Euphytica
Volume 207 Issue 3 Pages 627-643
Keywords BASGRA; cold tolerance; genotype-environment interaction; plant breeding; process-based modelling; yield stability; grassland productivity; timothy regrowth; climate-change; water-deficit; forest models; late blight; leaf-area; calibration; growth; tolerance
Abstract (up) Process-based grassland models (PBMs) simulate growth and development of vegetation over time. The models tend to have a large number of parameters that represent properties of the plants. To simulate different cultivars of the same species, different parameter values are required. Parameter differences may be interpreted as genetic variation for plant traits. Despite this natural connection between PBMs and plant genetics, there are only few examples of successful use of PBMs in plant breeding. Here we present a new procedure by which PBMs can help design ideotypes, i.e. virtual cultivars that optimally combine properties of existing cultivars. Ideotypes constitute selection targets for breeding. The procedure consists of four steps: (1) Bayesian calibration of model parameters using data from cultivar trials, (2) Estimating genetic variation for parameters from the combination of cultivar-specific calibrated parameter distributions, (3) Identifying parameter combinations that meet breeding objectives, (4) Translating model results to practice, i.e. interpreting parameters in terms of practical selection criteria. We show an application of the procedure to timothy (Phleum pratense L.) as grown in different regions of Norway.
Address 2016-10-31
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0014-2336 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4820
Permanent link to this record
 

 
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 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 (up) 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.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0304-3800 ISBN Medium Article
Area Expedition Conference
Notes CropM, LiveM Approved no
Call Number MA @ admin @ Serial 4473
Permanent link to this record
 

 
Author De Pascale, S.; Orsini, F.; Caputo, R.; Palermo, M.A.; Barbieri, G.; Maggio, A.
Title Seasonal and multiannual effects of salinisation on tomato yield and fruit quality Type Journal Article
Year 2012 Publication Functional Plant Biology Abbreviated Journal Functional Plant Biology
Volume 39 Issue 8 Pages 689-698
Keywords fruit ions concentration; fruit lipophilic and hydrophilic antioxidant; capacities; leaf water potentials; leaf stomatal conductance; short- and; long-term salinisation; salinity tolerance; water-stress; antioxidant activity; irrigation; growth; plants; soils; carotenoids; responses; crops
Abstract (up) The effects of short-and long-term salinisation were studied by comparing tomato growth on a soil exposed to one-season salinisation (short term) vs growth on a soil exposed to >20 years salinisation (long term). Remarkable differences were associated to substantial modifications of the soil physical-chemical characteristics in the root zone, including deteriorated structure, reduced infiltration properties and increased pH. Fresh yield, fruit number and fruit weight were similarly affected by short-and long-term salinisation. In contrast, the marketable yield was significantly lower in the long-term salinised soil-a response that was also associated to nutritional imbalance (mainly referred to P and K). As reported for plants growing under oxygen deprivation stress, the antioxidant capacity of the water soluble fraction of salinised tomato fruits was enhanced by short-term salinisation, also. Overall, long-term salinisation may cause physiological imbalances and yield reductions that cannot be solely attributed to hyperosmotic stress and ionic toxicity. Therefore, the ability of plants to cope with nutritional deficiency and withstand high pH and anoxia may be important traits that should be considered to improve plant tolerance to long-term salinised soils.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1445-4408 ISBN Medium Article
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4583
Permanent link to this record
 

 
Author Jing, Q.; Bélanger, G.; Baron, V.; Bonesmo, H.; Virkajärvi, P.
Title Simulating the Nutritive Value of Timothy Summer Regrowth Type Journal Article
Year 2013 Publication Agronomy Journal Abbreviated Journal Agronomy Journal
Volume 105 Issue 3 Pages 563
Keywords varying n nutrition; cation-anion difference; spring growth; swine manure; leaf-area; nitrogen; yield; model; digestibility; dynamics
Abstract (up) The process-based grass model, CATIMO, simulates the spring growth and nutritive value of timothy (Phleum pratense L.), a forage species widely grown in Scandinavia and Canada, but the nutritive value of the summer regrowth has never been simulated. Our objective was to improve CATIMO for simulating the N concentration, neutral detergent fiber (NDF), in vitro digestibility of NDF (dNDF), and in vitro true digestibility of dry matter (IVTD) of summer regrowth. Daily changes in summer regrowth nutritive value were simulated by modifying key crop parameters that differed from spring growth. More specifically, the partitioning fraction to leaf blades was increased to increase the leaf-to-weight ratio, and daily changes in NDF and dNDF of leaf blades and stems were reduced. The modified CATIMO model was evaluated with data from four independent experiments in eastern and western Canada and Finland. The model performed better for eastern Canada than for the other locations, but the nutritive value attributes of the summer regrowth across locations (range of normalized RMSE = 8-25%, slope < 0.17, R-2 < 0.10) were not simulated as well as those of the spring growth (range of normalized RMSE = 4-16%, 0.85 < slope < 1.07, R-2 > 0.61). These modeling results highlight knowledge gaps in timothy summer regrowth and prospective research directions: improved knowledge of factors controlling the nutritive value of the timothy summer regrowth and experimental measurements of leaf-to-weight ratio and of the nutritive value of leaves and stems.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0002-1962 ISBN Medium Article
Area Expedition Conference
Notes CropM, LiveM Approved no
Call Number MA @ admin @ Serial 4493
Permanent link to this record