Records |
Author |
Lotze-Campen, H.; von Witzke, H.; Noleppa, S.; Schwarz, G. |
Title |
Science for food, climate protection and welfare: An economic analysis of plant breeding research in Germany |
Type |
Journal Article |
Year |
2015 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
Volume |
136 |
Issue |
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Pages |
79-84 |
Keywords |
Plant breeding; CO2 emissions; Cost–benefit analysis; Social rate of return; Agricultural research policy |
Abstract |
Highlights • We analyze the economic effects of plant breeding research in Germany. • Effects of reduced CO2 emissions due to productivity increases are being quantified. • Expansion of global agricultural area has been reduced by 1–1.5 million ha. • CO2 emissions have been reduced by 160–235 million tons. • German plant breeding research has an economic value of 10.8–15.6 billion EUR. Abstract We analyze the economic effects of plant breeding research in Germany. In addition to market effects, for the first time also effects of reduced CO2 emissions due to productivity increases are being quantified. The analysis shows that investments in German plant breeding research in the period 1991–2010 have reduced the global expansion of agricultural area by 1–1.5 million hectares. This has led to reduced CO2 emissions of 160–235 million tons. The economic value generated by plant breeding research, through increased production and reduced greenhouse gas emissions, is estimated at 10.8–15.6 billion EUR in the same period. This can be translated into a social rate of return on research investment in the range of 40–80% per year. Projections for the period 2011–2030 generate a return rate in the range of 65–140% per year. Investments into plant breeding research in Germany are highly profitable from a societal point of view. At the same time, our results show significant under-investments in agricultural research in Germany. These results provide a good justification for policy-makers to reverse funding cuts for public agricultural research over the last decades and to improve institutional conditions for private research, e.g. through better protection of intellectual property rights. |
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0308521x |
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TradeM, ftnotmacsur |
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no |
Call Number |
MA @ admin @ |
Serial |
4999 |
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Author |
Bernabucci, U.; Biffani, S.; Buggiotti, L.; Vitali, A.; Lacetera, N.; Nardone, A. |
Title |
The effects of heat stress in Italian Holstein dairy cattle |
Type |
Journal Article |
Year |
2014 |
Publication |
Journal of Dairy Science |
Abbreviated Journal |
J. Dairy Sci. |
Volume |
97 |
Issue |
1 |
Pages |
471-486 |
Keywords |
Animals; Breeding; Cattle; Dietary Fats/analysis; Dietary Proteins/analysis; Female; Genetic Variation; Heat Stress Disorders/*veterinary; *Hot Temperature; Humans; Humidity; *Lactation; Linear Models; Milk/chemistry; Parity; Phenotype; Weather; dairy cow; heritability; production trait; temperature-humidity index breaking point |
Abstract |
The data set for this study comprised 1,488,474 test-day records for milk, fat, and protein yields and fat and protein percentages from 191,012 first-, second-, and third-parity Holstein cows from 484 farms. Data were collected from 2001 through 2007 and merged with meteorological data from 35 weather stations. A linear model (M1) was used to estimate the effects of the temperature-humidity index (THI) on production traits. Least squares means from M1 were used to detect the THI thresholds for milk production in all parities by using a 2-phase linear regression procedure (M2). A multiple-trait repeatability test-model (M3) was used to estimate variance components for all traits and a dummy regression variable (t) was defined to estimate the production decline caused by heat stress. Additionally, the estimated variance components and M3 were used to estimate traditional and heat-tolerance breeding values (estimated breeding values, EBV) for milk yield and protein percentages at parity 1. An analysis of data (M2) indicated that the daily THI at which milk production started to decline for the 3 parities and traits ranged from 65 to 76. These THI values can be achieved with different temperature/humidity combinations with a range of temperatures from 21 to 36°C and relative humidity values from 5 to 95%. The highest negative effect of THI was observed 4 d before test day over the 3 parities for all traits. The negative effect of THI on production traits indicates that first-parity cows are less sensitive to heat stress than multiparous cows. Over the parities, the general additive genetic variance decreased for protein content and increased for milk yield and fat and protein yield. Additive genetic variance for heat tolerance showed an increase from the first to third parity for milk, protein, and fat yield, and for protein percentage. Genetic correlations between general and heat stress effects were all unfavorable (from -0.24 to -0.56). Three EBV per trait were calculated for each cow and bull (traditional EBV, traditional EBV estimated with the inclusion of THI covariate effect, and heat tolerance EBV) and the rankings of EBV for 283 bulls born after 1985 with at least 50 daughters were compared. When THI was included in the model, the ranking for 17 and 32 bulls changed for milk yield and protein percentage, respectively. The heat tolerance genetic component is not negligible, suggesting that heat tolerance selection should be included in the selection objectives. |
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1525-3198 (Electronic) 0022-0302 (Linking) |
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LiveM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4617 |
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Author |
De Swaef, T.; Bellocchi, G.; Aper, J.; Lootens, P.; Roldan-Ruiz, I. |
Title |
Use of identifiability analysis in designing phenotyping experiments for modelling forage production and quality |
Type |
Journal Article |
Year |
2019 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
Volume |
70 |
Issue |
9 |
Pages |
2587-2604 |
Keywords |
Breeding; grassland modelling; identifiability analysis; perennial; ryegrass; phenotyping; sensitivity analysis; pasture simulation-model; practical identifiability; crop; water; parameters; systems; carbon; uncertainty; sensitivity; emissions |
Abstract |
Agricultural systems models are complex and tend to be over-parameterized with respect to observational datasets. Practical identifiability analysis based on local sensitivity analysis has proved effective in investigating identifiable parameter sets in environmental models, but has not been applied to agricultural systems models. Here, we demonstrate that identifiability analysis improves experimental design to ensure independent parameter estimation for yield and quality outputs of a complex grassland model. The Pasture Simulation model (PaSim) was used to demonstrate the effectiveness of practical identifiability analysis in designing experiments and measurement protocols within phe-notyping experiments with perennial ryegrass. Virtual experiments were designed combining three factors: frequency of measurements, duration of the experiment. and location of trials. Our results demonstrate that (i) PaSim provides sufficient detail in terms of simulating biomass yield and quality of perennial ryegrass for use in breeding, (ii) typical breeding trials are insufficient to parameterize all influential parameters, (iii) the frequency of measurements is more important than the number of growing seasons to improve the identifiability of PaSim parameters, and (iv) identifiability analysis provides a sound approach for optimizing the design of multi-location trials. Practical identifiability analysis can play an important role in ensuring proper exploitation of phenotypic data and cost-effective multi-location experimental designs. Considering the growing importance of simulation models, this study supports the design of experiments and measurement protocols in the phenotyping networks that have recently been organized. |
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2020-02-14 |
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English |
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0022-0957 |
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LiveM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
5231 |
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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 |
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 |
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English |
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ISSN |
0014-2336 |
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Notes |
CropM, ft_macsur |
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no |
Call Number |
MA @ admin @ |
Serial |
4820 |
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Author |
Rötter, R.P.; Tao, F.; Höhn, J.G.; Palosuo, T. |
Title |
Use of crop simulation modelling to aid ideotype design of future cereal cultivars |
Type |
Journal Article |
Year |
2015 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
Volume |
66 |
Issue |
12 |
Pages |
3463-3476 |
Keywords |
Breeding/*methods; Climate Change; *Computer Simulation; Ecotype; Edible Grain/*growth & development; *Models, Theoretical; cereals; climate extremes; crop growth simulation; ensemble modelling; future cultivars; genetic modelling; ideotype breeding; model improvement; model-aided design |
Abstract |
A major challenge of the 21st century is to achieve food supply security under a changing climate and roughly a doubling in food demand by 2050 compared to present, the majority of which needs to be met by the cereals wheat, rice, maize, and barley. Future harvests are expected to be especially threatened through increased frequency and severity of extreme events, such as heat waves and drought, that pose particular challenges to plant breeders and crop scientists. Process-based crop models developed for simulating interactions between genotype, environment, and management are widely applied to assess impacts of environmental change on crop yield potentials, phenology, water use, etc. During the last decades, crop simulation has become important for supporting plant breeding, in particular in designing ideotypes, i.e. ‘model plants’, for different crops and cultivation environments. In this review we (i) examine the main limitations of crop simulation modelling for supporting ideotype breeding, (ii) describe developments in cultivar traits in response to climate variations, and (iii) present examples of how crop simulation has supported evaluation and design of cereal cultivars for future conditions. An early success story for rice demonstrates the potential of crop simulation modelling for ideotype breeding. Combining conventional crop simulation with new breeding methods and genetic modelling holds promise to accelerate delivery of future cereal cultivars for different environments. Robustness of model-aided ideotype design can further be enhanced through continued improvements of simulation models to better capture effects of extremes and the use of multi-model ensembles. |
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2016-10-31 |
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English |
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Edition |
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ISSN |
0022-0957 1460-2431 |
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Medium |
Review |
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Notes |
CropM, ft_macsur |
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no |
Call Number |
MA @ admin @ |
Serial |
4804 |
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