| |
Records |
Links |
|
Author |
Bojar, W.; Knopik, L.; Żarski, J.; Kuśmierek-Tomaszewska, R. |
|
| |
Title |
Integrated assessment of crop productivity based on the food supply forecasting |
Type |
Journal Article |
| |
Year  |
2016 |
Publication |
Agricultural Economics – Czech |
Abbreviated Journal |
Agricultural Economics – Czech |
|
| |
Volume |
61 |
Issue |
11 |
Pages |
502-510 |
|
| |
Keywords |
climate changes; decision-making tools; estimation of parameters; forecasted outputs; gamma distribution; predicting yields; climate-change; emissions scenarios; impacts; potato; yield; growth; policy; scale; water |
|
| |
Abstract |
Climate change scenarios suggest that long periods without rainfall will occur in the future often causing instability of the agricultural products market. The aim of our research was to build a model describing the amount of precipitation and droughts for forecasting crop yields in the future. In this study, we analysed a non-standard mixture of gamma and one point distributions as the model of rainfall. On the basis of the rainfall data, one can estimate parameters of the distribution. Parameter estimators were constructed using a method of maximum likelihood. The obtained rainfall data allow confirming the hypothesis of the adequacy of the proposed rainfall models. Long series of droughts allow one to determine the probabilities of adverse phenomena in agriculture. Based on the model, yields of barley in the years 2030 and 2050 were forecasted which can be used for the assessment of other crops productivity. The results obtained with this approach can be used to predict decreases in agricultural production caused by prospective rainfall shortages. This will enable decision makers to shape effective agricultural policies in order to learn how to balance the food supplies and demands through an appropriate management of stored raw food materials and import/export policies. |
|
| |
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 |
0139-570x |
ISBN |
|
Medium |
Article |
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
CropM, TradeM, ft_macsur |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4644 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Gabaldón-Leal, C.; Webber, H.; Otegui, M.E.; Slafer, G.A.; Ordonez, R.A.; Gaiser, T.; Lorite, I.J.; Ruiz-Ramos, M.; Ewert, F. |
|
| |
Title |
Modelling the impact of heat stress on maize yield formation |
Type |
Journal Article |
| |
Year |
2016 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
|
| |
Volume |
198 |
Issue |
|
Pages |
226-237 |
|
| |
Keywords |
Heat stress; Maize; Zea mays (L); Crop models; HIGH-TEMPERATURE STRESS; KERNEL NUMBER; CROP GROWTH; GRAIN-YIELD; SIMULATION; CLIMATE; HYBRIDS; SET; VALIDATION; COMPONENTS |
|
| |
Abstract |
The frequency and intensity of extreme high temperature events are expected to increase with climate change. Higher temperatures near anthesis have a large negative effect on maize (Zea mays, L.) grain yield. While crop growth models are commonly used to assess climate change impacts on maize and other crops, it is only recently that they have accounted for such heat stress effects, despite limited field data availability for model evaluation. There is also increasing awareness but limited testing of the importance of canopy temperature as compared to air temperature for heat stress impact simulations. In this study, four independent irrigated field trials with controlled heating imposed using polyethylene shelters were used to develop and evaluate a heat stress response function in the crop modeling framework SIMPLACE, in which the Lintul5 crop model was combined with a canopy temperature model. A dataset from Argentina with the temperate hybrid Nidera AX 842 MG (RM 119) was used to develop a yield reduction function based on accumulated hourly stress thermal time above a critical temperature of 34 degrees C. A second dataset from Spain with a FAO 700 cultivar was used to evaluate the model with daily weather inputs in two sets of simulations. The first was used to calibrate SIMPLACE for conditions with no heat stress, and the second was used to evaluate SIMPLACE under conditions of heat stress using the reduction factor obtained with the Argentine dataset. Both sets of simulations were conducted twice; with the heat stress function alternatively driven with air and simulated canopy temperature. Grain yield simulated under heat stress conditions improved when canopy temperature was used instead of air temperature (RMSE equal to 175 and 309 g m(-2), respectively). For the irrigated and high radiative conditions, raising the critical threshold temperature for heat stress to 39 degrees C improved yield simulation using air temperature (RMSE: 221 gm(-2)) without the need to simulate canopy temperature (RMSE: 175 gm(-2)). However, this approach of adjusting thresholds is only likely to work in environments where climatic variables and the level of soil water deficit are constant, such as irrigated conditions and are not appropriate for rainfed production conditions. (C) 2016 Elsevier B.V. All rights reserved. |
|
| |
Address |
2016-11-17 |
|
| |
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 |
0378-4290, 1872-6852 |
ISBN |
|
Medium |
Article |
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
ft_macsur, CropM |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4880 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Wallach, D.; Mearns, L.O.; Ruane, A.C.; Rötter, R.P.; Asseng, S. |
|
| |
Title |
Lessons from climate modeling on the design and use of ensembles for crop modeling |
Type |
Journal Article |
| |
Year |
2016 |
Publication |
Climatic Change |
Abbreviated Journal |
Clim. Change |
|
| |
Volume |
139 |
Issue |
3-4 |
Pages |
551-564 |
|
| |
Keywords |
change projections; elevated CO2; uncertainty; wheat; water; soil; simulations; yield; rice; 21st-century; Model ensembles; Crop models; Climate models; Model weighting; Super ensembles |
|
| |
Abstract |
Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor. |
|
| |
Address |
2017-01-06 |
|
| |
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 |
0165-0009 |
ISBN |
|
Medium |
Article |
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
CropM, ft_MACSUR |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4933 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Schauberger, B.; Rolinski, S.; Müller, C. |
|
| |
Title |
A network-based approach for semi-quantitative knowledge mining and its application to yield variability |
Type |
Journal Article |
| |
Year |
2016 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
|
| |
Volume |
11 |
Issue |
12 |
Pages |
123001 |
|
| |
Keywords |
yield variability; crop models; interaction network; plant process; wheat; maize; rice; Global Food Security; Climate-Change; Crop Production; Stress Tolerance; Wheat Yields; Heat-Stress; Temperature Variability; Environmental-Factors; United-States; Elevated CO2 |
|
| |
Abstract |
Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. Asystematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields. |
|
| |
Address |
2017-04-07 |
|
| |
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 |
1748-9326 |
ISBN |
|
Medium |
Review |
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
CropM, ft_macsur |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4942 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Schönhart, M.; Nadeem, I. |
|
| |
Title |
Direct climate change impacts on cattle indicated by THI models |
Type |
Journal Article |
| |
Year |
2015 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
|
| |
Volume |
6 |
Issue |
|
Pages |
17-17 |
|
| |
Keywords |
dairy; THI; milk yield; integrated modelling; economic loss |
|
| |
Abstract |
|
|
| |
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 |
|
ISBN |
|
Medium |
Article |
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
TradeM, ft_macsur |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4811 |
|
| Permanent link to this record |
