Modelling grass yields in northern climates – a comparison of three growth models for timothy

During the past few years, several studies have compared the performance of crop simulation models to assess the uncertainties in model-based climate change impact assessments and other modelling studies. Many of these studies have concentrated on cereal crops, while fewer model comparisons have bee...
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Autor*in:	Korhonen, Panu [verfasserIn] Palosuo, Taru [verfasserIn] Persson, Tomas [verfasserIn] Höglind, Mats [verfasserIn] Jégo, Guillaume [verfasserIn] Van Oijen, Marcel [verfasserIn] Gustavsson, Anne-Maj [verfasserIn] Bélanger, Gilles [verfasserIn] Virkajärvi, Perttu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Forage grass Model comparison Timothy Uncertainty Yield

Übergeordnetes Werk:	Enthalten in: Field crops research - Amsterdam : Elsevier, 1978, 224, Seite 37-47
Übergeordnetes Werk:	volume:224 ; pages:37-47

DOI / URN:	10.1016/j.fcr.2018.04.014

Katalog-ID:	ELV002510243

Internformat


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245	1	0	\|a Modelling grass yields in northern climates – a comparison of three growth models for timothy
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520			\|a During the past few years, several studies have compared the performance of crop simulation models to assess the uncertainties in model-based climate change impact assessments and other modelling studies. Many of these studies have concentrated on cereal crops, while fewer model comparisons have been conducted for grasses. We compared the predictions for timothy grass (Phleum pratense L.) yields for first and second cuts along with the dynamics of above-ground biomass for the grass simulation models BASGRA and CATIMO, and the soil-crop model STICS. The models were calibrated and evaluated using field data from seven sites across Northern Europe and Canada with different climates, soil conditions and management practices. Altogether the models were compared using data on timothy grass from 33 combinations of sites, cultivars and management regimes. Model performances with two calibration approaches, cultivar-specific and generic calibrations, were compared. All the models studied estimated the dynamics of above-ground biomass and the leaf area index satisfactorily, but tended to underestimate the first cut yield. Cultivar-specific calibration resulted in more accurate first cut yield predictions than the generic calibration achieving root mean square errors approximately one third lower for the cultivar-specific calibration. For the second cut, the difference between the calibration methods was small. The results indicate that detailed soil process descriptions improved the overall model performance and the model responses to management, such as nitrogen applications. The results also suggest that taking the genetic variability into account between cultivars of timothy grass also improves the yield estimates. Calibrations using both spring and summer growth data simultaneously revealed that processes determining the growth in these two periods require further attention in model development.
650		4	\|a Forage grass
650		4	\|a Model comparison
650		4	\|a Timothy
650		4	\|a Uncertainty
650		4	\|a Yield
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700	1		\|a Jégo, Guillaume \|e verfasserin \|4 aut
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700	1		\|a Bélanger, Gilles \|e verfasserin \|4 aut
700	1		\|a Virkajärvi, Perttu \|e verfasserin \|4 aut
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936	b	k	\|a 48.00 \|j Land- und Forstwirtschaft: Allgemeines
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Indexfelder

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publishDate	2018
allfields	10.1016/j.fcr.2018.04.014 doi (DE-627)ELV002510243 (ELSEVIER)S0378-4290(17)30966-8 DE-627 ger DE-627 rda eng 630 640 DE-600 48.00 bkl Korhonen, Panu verfasserin aut Modelling grass yields in northern climates – a comparison of three growth models for timothy 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier During the past few years, several studies have compared the performance of crop simulation models to assess the uncertainties in model-based climate change impact assessments and other modelling studies. Many of these studies have concentrated on cereal crops, while fewer model comparisons have been conducted for grasses. We compared the predictions for timothy grass (Phleum pratense L.) yields for first and second cuts along with the dynamics of above-ground biomass for the grass simulation models BASGRA and CATIMO, and the soil-crop model STICS. The models were calibrated and evaluated using field data from seven sites across Northern Europe and Canada with different climates, soil conditions and management practices. Altogether the models were compared using data on timothy grass from 33 combinations of sites, cultivars and management regimes. Model performances with two calibration approaches, cultivar-specific and generic calibrations, were compared. All the models studied estimated the dynamics of above-ground biomass and the leaf area index satisfactorily, but tended to underestimate the first cut yield. Cultivar-specific calibration resulted in more accurate first cut yield predictions than the generic calibration achieving root mean square errors approximately one third lower for the cultivar-specific calibration. For the second cut, the difference between the calibration methods was small. The results indicate that detailed soil process descriptions improved the overall model performance and the model responses to management, such as nitrogen applications. The results also suggest that taking the genetic variability into account between cultivars of timothy grass also improves the yield estimates. Calibrations using both spring and summer growth data simultaneously revealed that processes determining the growth in these two periods require further attention in model development. Forage grass Model comparison Timothy Uncertainty Yield Palosuo, Taru verfasserin (orcid)0000-0003-4322-3450 aut Persson, Tomas verfasserin aut Höglind, Mats verfasserin aut Jégo, Guillaume verfasserin aut Van Oijen, Marcel verfasserin aut Gustavsson, Anne-Maj verfasserin aut Bélanger, Gilles verfasserin aut Virkajärvi, Perttu verfasserin aut Enthalten in Field crops research Amsterdam : Elsevier, 1978 224, Seite 37-47 Online-Ressource (DE-627)32050316X (DE-600)2012484-3 (DE-576)090954912 1872-6852 nnns volume:224 pages:37-47 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-FOR GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 48.00 Land- und Forstwirtschaft: Allgemeines AR 224 37-47
spelling	10.1016/j.fcr.2018.04.014 doi (DE-627)ELV002510243 (ELSEVIER)S0378-4290(17)30966-8 DE-627 ger DE-627 rda eng 630 640 DE-600 48.00 bkl Korhonen, Panu verfasserin aut Modelling grass yields in northern climates – a comparison of three growth models for timothy 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier During the past few years, several studies have compared the performance of crop simulation models to assess the uncertainties in model-based climate change impact assessments and other modelling studies. Many of these studies have concentrated on cereal crops, while fewer model comparisons have been conducted for grasses. We compared the predictions for timothy grass (Phleum pratense L.) yields for first and second cuts along with the dynamics of above-ground biomass for the grass simulation models BASGRA and CATIMO, and the soil-crop model STICS. The models were calibrated and evaluated using field data from seven sites across Northern Europe and Canada with different climates, soil conditions and management practices. Altogether the models were compared using data on timothy grass from 33 combinations of sites, cultivars and management regimes. Model performances with two calibration approaches, cultivar-specific and generic calibrations, were compared. All the models studied estimated the dynamics of above-ground biomass and the leaf area index satisfactorily, but tended to underestimate the first cut yield. Cultivar-specific calibration resulted in more accurate first cut yield predictions than the generic calibration achieving root mean square errors approximately one third lower for the cultivar-specific calibration. For the second cut, the difference between the calibration methods was small. The results indicate that detailed soil process descriptions improved the overall model performance and the model responses to management, such as nitrogen applications. The results also suggest that taking the genetic variability into account between cultivars of timothy grass also improves the yield estimates. Calibrations using both spring and summer growth data simultaneously revealed that processes determining the growth in these two periods require further attention in model development. Forage grass Model comparison Timothy Uncertainty Yield Palosuo, Taru verfasserin (orcid)0000-0003-4322-3450 aut Persson, Tomas verfasserin aut Höglind, Mats verfasserin aut Jégo, Guillaume verfasserin aut Van Oijen, Marcel verfasserin aut Gustavsson, Anne-Maj verfasserin aut Bélanger, Gilles verfasserin aut Virkajärvi, Perttu verfasserin aut Enthalten in Field crops research Amsterdam : Elsevier, 1978 224, Seite 37-47 Online-Ressource (DE-627)32050316X (DE-600)2012484-3 (DE-576)090954912 1872-6852 nnns volume:224 pages:37-47 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-FOR GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 48.00 Land- und Forstwirtschaft: Allgemeines AR 224 37-47
allfields_unstemmed	10.1016/j.fcr.2018.04.014 doi (DE-627)ELV002510243 (ELSEVIER)S0378-4290(17)30966-8 DE-627 ger DE-627 rda eng 630 640 DE-600 48.00 bkl Korhonen, Panu verfasserin aut Modelling grass yields in northern climates – a comparison of three growth models for timothy 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier During the past few years, several studies have compared the performance of crop simulation models to assess the uncertainties in model-based climate change impact assessments and other modelling studies. Many of these studies have concentrated on cereal crops, while fewer model comparisons have been conducted for grasses. We compared the predictions for timothy grass (Phleum pratense L.) yields for first and second cuts along with the dynamics of above-ground biomass for the grass simulation models BASGRA and CATIMO, and the soil-crop model STICS. The models were calibrated and evaluated using field data from seven sites across Northern Europe and Canada with different climates, soil conditions and management practices. Altogether the models were compared using data on timothy grass from 33 combinations of sites, cultivars and management regimes. Model performances with two calibration approaches, cultivar-specific and generic calibrations, were compared. All the models studied estimated the dynamics of above-ground biomass and the leaf area index satisfactorily, but tended to underestimate the first cut yield. Cultivar-specific calibration resulted in more accurate first cut yield predictions than the generic calibration achieving root mean square errors approximately one third lower for the cultivar-specific calibration. For the second cut, the difference between the calibration methods was small. The results indicate that detailed soil process descriptions improved the overall model performance and the model responses to management, such as nitrogen applications. The results also suggest that taking the genetic variability into account between cultivars of timothy grass also improves the yield estimates. Calibrations using both spring and summer growth data simultaneously revealed that processes determining the growth in these two periods require further attention in model development. Forage grass Model comparison Timothy Uncertainty Yield Palosuo, Taru verfasserin (orcid)0000-0003-4322-3450 aut Persson, Tomas verfasserin aut Höglind, Mats verfasserin aut Jégo, Guillaume verfasserin aut Van Oijen, Marcel verfasserin aut Gustavsson, Anne-Maj verfasserin aut Bélanger, Gilles verfasserin aut Virkajärvi, Perttu verfasserin aut Enthalten in Field crops research Amsterdam : Elsevier, 1978 224, Seite 37-47 Online-Ressource (DE-627)32050316X (DE-600)2012484-3 (DE-576)090954912 1872-6852 nnns volume:224 pages:37-47 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-FOR GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 48.00 Land- und Forstwirtschaft: Allgemeines AR 224 37-47
allfieldsGer	10.1016/j.fcr.2018.04.014 doi (DE-627)ELV002510243 (ELSEVIER)S0378-4290(17)30966-8 DE-627 ger DE-627 rda eng 630 640 DE-600 48.00 bkl Korhonen, Panu verfasserin aut Modelling grass yields in northern climates – a comparison of three growth models for timothy 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier During the past few years, several studies have compared the performance of crop simulation models to assess the uncertainties in model-based climate change impact assessments and other modelling studies. Many of these studies have concentrated on cereal crops, while fewer model comparisons have been conducted for grasses. We compared the predictions for timothy grass (Phleum pratense L.) yields for first and second cuts along with the dynamics of above-ground biomass for the grass simulation models BASGRA and CATIMO, and the soil-crop model STICS. The models were calibrated and evaluated using field data from seven sites across Northern Europe and Canada with different climates, soil conditions and management practices. Altogether the models were compared using data on timothy grass from 33 combinations of sites, cultivars and management regimes. Model performances with two calibration approaches, cultivar-specific and generic calibrations, were compared. All the models studied estimated the dynamics of above-ground biomass and the leaf area index satisfactorily, but tended to underestimate the first cut yield. Cultivar-specific calibration resulted in more accurate first cut yield predictions than the generic calibration achieving root mean square errors approximately one third lower for the cultivar-specific calibration. For the second cut, the difference between the calibration methods was small. The results indicate that detailed soil process descriptions improved the overall model performance and the model responses to management, such as nitrogen applications. The results also suggest that taking the genetic variability into account between cultivars of timothy grass also improves the yield estimates. Calibrations using both spring and summer growth data simultaneously revealed that processes determining the growth in these two periods require further attention in model development. Forage grass Model comparison Timothy Uncertainty Yield Palosuo, Taru verfasserin (orcid)0000-0003-4322-3450 aut Persson, Tomas verfasserin aut Höglind, Mats verfasserin aut Jégo, Guillaume verfasserin aut Van Oijen, Marcel verfasserin aut Gustavsson, Anne-Maj verfasserin aut Bélanger, Gilles verfasserin aut Virkajärvi, Perttu verfasserin aut Enthalten in Field crops research Amsterdam : Elsevier, 1978 224, Seite 37-47 Online-Ressource (DE-627)32050316X (DE-600)2012484-3 (DE-576)090954912 1872-6852 nnns volume:224 pages:37-47 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-FOR GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 48.00 Land- und Forstwirtschaft: Allgemeines AR 224 37-47
allfieldsSound	10.1016/j.fcr.2018.04.014 doi (DE-627)ELV002510243 (ELSEVIER)S0378-4290(17)30966-8 DE-627 ger DE-627 rda eng 630 640 DE-600 48.00 bkl Korhonen, Panu verfasserin aut Modelling grass yields in northern climates – a comparison of three growth models for timothy 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier During the past few years, several studies have compared the performance of crop simulation models to assess the uncertainties in model-based climate change impact assessments and other modelling studies. Many of these studies have concentrated on cereal crops, while fewer model comparisons have been conducted for grasses. We compared the predictions for timothy grass (Phleum pratense L.) yields for first and second cuts along with the dynamics of above-ground biomass for the grass simulation models BASGRA and CATIMO, and the soil-crop model STICS. The models were calibrated and evaluated using field data from seven sites across Northern Europe and Canada with different climates, soil conditions and management practices. Altogether the models were compared using data on timothy grass from 33 combinations of sites, cultivars and management regimes. Model performances with two calibration approaches, cultivar-specific and generic calibrations, were compared. All the models studied estimated the dynamics of above-ground biomass and the leaf area index satisfactorily, but tended to underestimate the first cut yield. Cultivar-specific calibration resulted in more accurate first cut yield predictions than the generic calibration achieving root mean square errors approximately one third lower for the cultivar-specific calibration. For the second cut, the difference between the calibration methods was small. The results indicate that detailed soil process descriptions improved the overall model performance and the model responses to management, such as nitrogen applications. The results also suggest that taking the genetic variability into account between cultivars of timothy grass also improves the yield estimates. Calibrations using both spring and summer growth data simultaneously revealed that processes determining the growth in these two periods require further attention in model development. Forage grass Model comparison Timothy Uncertainty Yield Palosuo, Taru verfasserin (orcid)0000-0003-4322-3450 aut Persson, Tomas verfasserin aut Höglind, Mats verfasserin aut Jégo, Guillaume verfasserin aut Van Oijen, Marcel verfasserin aut Gustavsson, Anne-Maj verfasserin aut Bélanger, Gilles verfasserin aut Virkajärvi, Perttu verfasserin aut Enthalten in Field crops research Amsterdam : Elsevier, 1978 224, Seite 37-47 Online-Ressource (DE-627)32050316X (DE-600)2012484-3 (DE-576)090954912 1872-6852 nnns volume:224 pages:37-47 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-FOR GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 48.00 Land- und Forstwirtschaft: Allgemeines AR 224 37-47
language	English
source	Enthalten in Field crops research 224, Seite 37-47 volume:224 pages:37-47
sourceStr	Enthalten in Field crops research 224, Seite 37-47 volume:224 pages:37-47
format_phy_str_mv	Article
bklname	Land- und Forstwirtschaft: Allgemeines
institution	findex.gbv.de
topic_facet	Forage grass Model comparison Timothy Uncertainty Yield
dewey-raw	630
isfreeaccess_bool	false
container_title	Field crops research
authorswithroles_txt_mv	Korhonen, Panu @@aut@@ Palosuo, Taru @@aut@@ Persson, Tomas @@aut@@ Höglind, Mats @@aut@@ Jégo, Guillaume @@aut@@ Van Oijen, Marcel @@aut@@ Gustavsson, Anne-Maj @@aut@@ Bélanger, Gilles @@aut@@ Virkajärvi, Perttu @@aut@@
publishDateDaySort_date	2018-01-01T00:00:00Z
hierarchy_top_id	32050316X
dewey-sort	3630
id	ELV002510243
language_de	englisch
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author	Korhonen, Panu
spellingShingle	Korhonen, Panu ddc 630 bkl 48.00 misc Forage grass misc Model comparison misc Timothy misc Uncertainty misc Yield Modelling grass yields in northern climates – a comparison of three growth models for timothy
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title	Modelling grass yields in northern climates – a comparison of three growth models for timothy
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title_full	Modelling grass yields in northern climates – a comparison of three growth models for timothy
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author_browse	Korhonen, Panu Palosuo, Taru Persson, Tomas Höglind, Mats Jégo, Guillaume Van Oijen, Marcel Gustavsson, Anne-Maj Bélanger, Gilles Virkajärvi, Perttu
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title_sort	modelling grass yields in northern climates – a comparison of three growth models for timothy
title_auth	Modelling grass yields in northern climates – a comparison of three growth models for timothy
abstract	During the past few years, several studies have compared the performance of crop simulation models to assess the uncertainties in model-based climate change impact assessments and other modelling studies. Many of these studies have concentrated on cereal crops, while fewer model comparisons have been conducted for grasses. We compared the predictions for timothy grass (Phleum pratense L.) yields for first and second cuts along with the dynamics of above-ground biomass for the grass simulation models BASGRA and CATIMO, and the soil-crop model STICS. The models were calibrated and evaluated using field data from seven sites across Northern Europe and Canada with different climates, soil conditions and management practices. Altogether the models were compared using data on timothy grass from 33 combinations of sites, cultivars and management regimes. Model performances with two calibration approaches, cultivar-specific and generic calibrations, were compared. All the models studied estimated the dynamics of above-ground biomass and the leaf area index satisfactorily, but tended to underestimate the first cut yield. Cultivar-specific calibration resulted in more accurate first cut yield predictions than the generic calibration achieving root mean square errors approximately one third lower for the cultivar-specific calibration. For the second cut, the difference between the calibration methods was small. The results indicate that detailed soil process descriptions improved the overall model performance and the model responses to management, such as nitrogen applications. The results also suggest that taking the genetic variability into account between cultivars of timothy grass also improves the yield estimates. Calibrations using both spring and summer growth data simultaneously revealed that processes determining the growth in these two periods require further attention in model development.
abstractGer	During the past few years, several studies have compared the performance of crop simulation models to assess the uncertainties in model-based climate change impact assessments and other modelling studies. Many of these studies have concentrated on cereal crops, while fewer model comparisons have been conducted for grasses. We compared the predictions for timothy grass (Phleum pratense L.) yields for first and second cuts along with the dynamics of above-ground biomass for the grass simulation models BASGRA and CATIMO, and the soil-crop model STICS. The models were calibrated and evaluated using field data from seven sites across Northern Europe and Canada with different climates, soil conditions and management practices. Altogether the models were compared using data on timothy grass from 33 combinations of sites, cultivars and management regimes. Model performances with two calibration approaches, cultivar-specific and generic calibrations, were compared. All the models studied estimated the dynamics of above-ground biomass and the leaf area index satisfactorily, but tended to underestimate the first cut yield. Cultivar-specific calibration resulted in more accurate first cut yield predictions than the generic calibration achieving root mean square errors approximately one third lower for the cultivar-specific calibration. For the second cut, the difference between the calibration methods was small. The results indicate that detailed soil process descriptions improved the overall model performance and the model responses to management, such as nitrogen applications. The results also suggest that taking the genetic variability into account between cultivars of timothy grass also improves the yield estimates. Calibrations using both spring and summer growth data simultaneously revealed that processes determining the growth in these two periods require further attention in model development.
abstract_unstemmed	During the past few years, several studies have compared the performance of crop simulation models to assess the uncertainties in model-based climate change impact assessments and other modelling studies. Many of these studies have concentrated on cereal crops, while fewer model comparisons have been conducted for grasses. We compared the predictions for timothy grass (Phleum pratense L.) yields for first and second cuts along with the dynamics of above-ground biomass for the grass simulation models BASGRA and CATIMO, and the soil-crop model STICS. The models were calibrated and evaluated using field data from seven sites across Northern Europe and Canada with different climates, soil conditions and management practices. Altogether the models were compared using data on timothy grass from 33 combinations of sites, cultivars and management regimes. Model performances with two calibration approaches, cultivar-specific and generic calibrations, were compared. All the models studied estimated the dynamics of above-ground biomass and the leaf area index satisfactorily, but tended to underestimate the first cut yield. Cultivar-specific calibration resulted in more accurate first cut yield predictions than the generic calibration achieving root mean square errors approximately one third lower for the cultivar-specific calibration. For the second cut, the difference between the calibration methods was small. The results indicate that detailed soil process descriptions improved the overall model performance and the model responses to management, such as nitrogen applications. The results also suggest that taking the genetic variability into account between cultivars of timothy grass also improves the yield estimates. Calibrations using both spring and summer growth data simultaneously revealed that processes determining the growth in these two periods require further attention in model development.
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title_short	Modelling grass yields in northern climates – a comparison of three growth models for timothy
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author2	Palosuo, Taru Persson, Tomas Höglind, Mats Jégo, Guillaume Van Oijen, Marcel Gustavsson, Anne-Maj Bélanger, Gilles Virkajärvi, Perttu
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up_date	2024-07-07T00:58:06.924Z
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Modelling grass yields in northern climates – a comparison of three growth models for timothy

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