Applications of systems simulation for understanding and increasing yield potential of wheat and rice

Understanding and increasing yield potential of cereals is essential to meet the growing food demand in Asia. A crop growth simulation model -WTGROWS- was developed to quantify the climatically determined potential grain yields and yield gaps in wheat in tropics and sub-tropics. The model written in PCSMP simulates daily dry matter production as a function of solar radiation, maximum and minimum temperatures, and water and nitrogen stresses. Comparison of simulated and measured quantities indicated satisfactory performance of the model in reference to water and nitrogen uptake, dry matter growth and grain yield in potential as well as water- and N-limited environments. The wheat yield potential in India varied between 2.6 and 8.3 t ha -1depending upon the location. Economically optimal yields in irrigated environments were estimated for all locations based on current price ratios of N fertilizer and grain, native soil fertility, simulated crop response to N fertilizer and other costs related to transport, harvesting and market forces. Yield gaps were found to be small in irrigated regions of northwestern India but significantly large in eastern regions. Almost 35 - 50% of the gap could be ascribed to delayed sowing. Crop simulation with different amounts of nitrogen and irrigation showed significant interaction between water and N availability and climatic variability, particularly with low inputs. The effect of climate change was more pronounced in central India where yield potential is already low.The model was also used to explore the opportunities for growing wheat in irrigated and rainfed tropical southeastern Asia. The results indicated that potential yields exceed 3 t ha -1at all places and increased further with latitude and elevation. At sea level, between equator and 8°N latitude, potential grain yield was 3 t ha -1. It increased to 5 t ha -1at 21°N and 4.5 t ha -1at 10°S latitudes. Realization of the yield potential of the presently available varieties may be limited because of several agronomic constraints.A simulation framework has been developed to determine the relative importance of different plant traits in isolation or in combination for increasing yield potential. In this approach, hypothetical genotypes are 'created' by changing the specific crop parameters of a crop simulation model. The impact of simultaneous change in many traits is assessed by randomly combining different traits in the hypothetical genotype. The approach is illustrated with examples for rice in tropics. No trait individually or in combination provides more than 5% advantage in yield at the level of management typically practiced by breeders. In such environments, even though genotypes may possess traits for higher yield potential, they will not be able to express them. Another framework is presented for using crop simulation models and statistical analysis together to increase the efficiency of multi-environment genotype testing.

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Main Author: Aggarwal, P.K.
Other Authors: Kropff, M.J.
Format: Doctoral thesis biblioteca
Language:English
Subjects:breeding, climatic change, crop yield, factors of production, india, quantitative analysis, simulation models, triticum, uncertainty, yields, zea mays, gewasopbrengst, klimaatverandering, kwantitatieve analyse, onzekerheid, opbrengsten, productiefactoren, simulatiemodellen, veredelen,
Online Access:https://research.wur.nl/en/publications/applications-of-systems-simulation-for-understanding-and-increasi
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spelling dig-wur-nl-wurpubs-658192024-10-23 Aggarwal, P.K. Kropff, M.J. Rabbinge, R. Doctoral thesis Applications of systems simulation for understanding and increasing yield potential of wheat and rice 2000 Understanding and increasing yield potential of cereals is essential to meet the growing food demand in Asia. A crop growth simulation model -WTGROWS- was developed to quantify the climatically determined potential grain yields and yield gaps in wheat in tropics and sub-tropics. The model written in PCSMP simulates daily dry matter production as a function of solar radiation, maximum and minimum temperatures, and water and nitrogen stresses. Comparison of simulated and measured quantities indicated satisfactory performance of the model in reference to water and nitrogen uptake, dry matter growth and grain yield in potential as well as water- and N-limited environments. The wheat yield potential in India varied between 2.6 and 8.3 t ha -1depending upon the location. Economically optimal yields in irrigated environments were estimated for all locations based on current price ratios of N fertilizer and grain, native soil fertility, simulated crop response to N fertilizer and other costs related to transport, harvesting and market forces. Yield gaps were found to be small in irrigated regions of northwestern India but significantly large in eastern regions. Almost 35 - 50% of the gap could be ascribed to delayed sowing. Crop simulation with different amounts of nitrogen and irrigation showed significant interaction between water and N availability and climatic variability, particularly with low inputs. The effect of climate change was more pronounced in central India where yield potential is already low.The model was also used to explore the opportunities for growing wheat in irrigated and rainfed tropical southeastern Asia. The results indicated that potential yields exceed 3 t ha -1at all places and increased further with latitude and elevation. At sea level, between equator and 8°N latitude, potential grain yield was 3 t ha -1. It increased to 5 t ha -1at 21°N and 4.5 t ha -1at 10°S latitudes. Realization of the yield potential of the presently available varieties may be limited because of several agronomic constraints.A simulation framework has been developed to determine the relative importance of different plant traits in isolation or in combination for increasing yield potential. In this approach, hypothetical genotypes are 'created' by changing the specific crop parameters of a crop simulation model. The impact of simultaneous change in many traits is assessed by randomly combining different traits in the hypothetical genotype. The approach is illustrated with examples for rice in tropics. No trait individually or in combination provides more than 5% advantage in yield at the level of management typically practiced by breeders. In such environments, even though genotypes may possess traits for higher yield potential, they will not be able to express them. Another framework is presented for using crop simulation models and statistical analysis together to increase the efficiency of multi-environment genotype testing. en application/pdf https://research.wur.nl/en/publications/applications-of-systems-simulation-for-understanding-and-increasi 10.18174/197264 https://edepot.wur.nl/197264 breeding climatic change crop yield factors of production india quantitative analysis simulation models triticum uncertainty yields zea mays gewasopbrengst india klimaatverandering kwantitatieve analyse onzekerheid opbrengsten productiefactoren simulatiemodellen triticum veredelen zea mays Wageningen University & Research
institution WUR NL
collection DSpace
country Países bajos
countrycode NL
component Bibliográfico
access En linea
databasecode dig-wur-nl
tag biblioteca
region Europa del Oeste
libraryname WUR Library Netherlands
language English
topic breeding
climatic change
crop yield
factors of production
india
quantitative analysis
simulation models
triticum
uncertainty
yields
zea mays
gewasopbrengst
india
klimaatverandering
kwantitatieve analyse
onzekerheid
opbrengsten
productiefactoren
simulatiemodellen
triticum
veredelen
zea mays
breeding
climatic change
crop yield
factors of production
india
quantitative analysis
simulation models
triticum
uncertainty
yields
zea mays
gewasopbrengst
india
klimaatverandering
kwantitatieve analyse
onzekerheid
opbrengsten
productiefactoren
simulatiemodellen
triticum
veredelen
zea mays
spellingShingle breeding
climatic change
crop yield
factors of production
india
quantitative analysis
simulation models
triticum
uncertainty
yields
zea mays
gewasopbrengst
india
klimaatverandering
kwantitatieve analyse
onzekerheid
opbrengsten
productiefactoren
simulatiemodellen
triticum
veredelen
zea mays
breeding
climatic change
crop yield
factors of production
india
quantitative analysis
simulation models
triticum
uncertainty
yields
zea mays
gewasopbrengst
india
klimaatverandering
kwantitatieve analyse
onzekerheid
opbrengsten
productiefactoren
simulatiemodellen
triticum
veredelen
zea mays
Aggarwal, P.K.
Applications of systems simulation for understanding and increasing yield potential of wheat and rice
description Understanding and increasing yield potential of cereals is essential to meet the growing food demand in Asia. A crop growth simulation model -WTGROWS- was developed to quantify the climatically determined potential grain yields and yield gaps in wheat in tropics and sub-tropics. The model written in PCSMP simulates daily dry matter production as a function of solar radiation, maximum and minimum temperatures, and water and nitrogen stresses. Comparison of simulated and measured quantities indicated satisfactory performance of the model in reference to water and nitrogen uptake, dry matter growth and grain yield in potential as well as water- and N-limited environments. The wheat yield potential in India varied between 2.6 and 8.3 t ha -1depending upon the location. Economically optimal yields in irrigated environments were estimated for all locations based on current price ratios of N fertilizer and grain, native soil fertility, simulated crop response to N fertilizer and other costs related to transport, harvesting and market forces. Yield gaps were found to be small in irrigated regions of northwestern India but significantly large in eastern regions. Almost 35 - 50% of the gap could be ascribed to delayed sowing. Crop simulation with different amounts of nitrogen and irrigation showed significant interaction between water and N availability and climatic variability, particularly with low inputs. The effect of climate change was more pronounced in central India where yield potential is already low.The model was also used to explore the opportunities for growing wheat in irrigated and rainfed tropical southeastern Asia. The results indicated that potential yields exceed 3 t ha -1at all places and increased further with latitude and elevation. At sea level, between equator and 8°N latitude, potential grain yield was 3 t ha -1. It increased to 5 t ha -1at 21°N and 4.5 t ha -1at 10°S latitudes. Realization of the yield potential of the presently available varieties may be limited because of several agronomic constraints.A simulation framework has been developed to determine the relative importance of different plant traits in isolation or in combination for increasing yield potential. In this approach, hypothetical genotypes are 'created' by changing the specific crop parameters of a crop simulation model. The impact of simultaneous change in many traits is assessed by randomly combining different traits in the hypothetical genotype. The approach is illustrated with examples for rice in tropics. No trait individually or in combination provides more than 5% advantage in yield at the level of management typically practiced by breeders. In such environments, even though genotypes may possess traits for higher yield potential, they will not be able to express them. Another framework is presented for using crop simulation models and statistical analysis together to increase the efficiency of multi-environment genotype testing.
author2 Kropff, M.J.
author_facet Kropff, M.J.
Aggarwal, P.K.
format Doctoral thesis
topic_facet breeding
climatic change
crop yield
factors of production
india
quantitative analysis
simulation models
triticum
uncertainty
yields
zea mays
gewasopbrengst
india
klimaatverandering
kwantitatieve analyse
onzekerheid
opbrengsten
productiefactoren
simulatiemodellen
triticum
veredelen
zea mays
author Aggarwal, P.K.
author_sort Aggarwal, P.K.
title Applications of systems simulation for understanding and increasing yield potential of wheat and rice
title_short Applications of systems simulation for understanding and increasing yield potential of wheat and rice
title_full Applications of systems simulation for understanding and increasing yield potential of wheat and rice
title_fullStr Applications of systems simulation for understanding and increasing yield potential of wheat and rice
title_full_unstemmed Applications of systems simulation for understanding and increasing yield potential of wheat and rice
title_sort applications of systems simulation for understanding and increasing yield potential of wheat and rice
url https://research.wur.nl/en/publications/applications-of-systems-simulation-for-understanding-and-increasi
work_keys_str_mv AT aggarwalpk applicationsofsystemssimulationforunderstandingandincreasingyieldpotentialofwheatandrice
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