Crop Model Parameterisation of Three Important Pearl Millet Varieties for Improved Water Use and Yield Estimation

Pearl millet is an important crop for food security in Asia and Africa’s arid and semi-arid regions. It is widely grown as a staple cereal grain for human consumption and livestock fodder. Mechanistic crop growth and water balance models are useful to forecast crop production and water use. However,...

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Published inPlants (Basel) Vol. 11; no. 6; p. 806
Main Authors Ausiku, Petrus A., Annandale, John G., Steyn, Joachim Martin, Sanewe, Andrew J.
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 18.03.2022
MDPI
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ISSN2223-7747
2223-7747
DOI10.3390/plants11060806

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Abstract Pearl millet is an important crop for food security in Asia and Africa’s arid and semi-arid regions. It is widely grown as a staple cereal grain for human consumption and livestock fodder. Mechanistic crop growth and water balance models are useful to forecast crop production and water use. However, very few studies have been devoted to the development of the model parameters needed for such simulations for pearl millet. The objectives of the study were to determine crop-specific model parameters for each of three pearl millet varieties (landrace, hybrid, and improved), as well as to calibrate and validate the Soil Water Balance (SWB) model for predicting pearl millet production and water use based on weather data. The SWB was chosen because it is widely used in southern Africa; however, the developed parameters should benefit other models as well. The presented crop-specific parameter values were derived from field observations and literature. Varieties with different phenology, maturity dates and tillering habits were grown under well-watered and well-fertilised conditions for calibration purposes. The calibrated model was used to predict biomass production, grain yield and crop water use. The hybrid’s water use efficiency was higher than that of the landrace and improved variety.
AbstractList Pearl millet is an important crop for food security in Asia and Africa’s arid and semi-arid regions. It is widely grown as a staple cereal grain for human consumption and livestock fodder. Mechanistic crop growth and water balance models are useful to forecast crop production and water use. However, very few studies have been devoted to the development of the model parameters needed for such simulations for pearl millet. The objectives of the study were to determine crop-specific model parameters for each of three pearl millet varieties (landrace, hybrid, and improved), as well as to calibrate and validate the Soil Water Balance (SWB) model for predicting pearl millet production and water use based on weather data. The SWB was chosen because it is widely used in southern Africa; however, the developed parameters should benefit other models as well. The presented crop-specific parameter values were derived from field observations and literature. Varieties with different phenology, maturity dates and tillering habits were grown under well-watered and well-fertilised conditions for calibration purposes. The calibrated model was used to predict biomass production, grain yield and crop water use. The hybrid’s water use efficiency was higher than that of the landrace and improved variety.
Pearl millet is an important crop for food security in Asia and Africa's arid and semi-arid regions. It is widely grown as a staple cereal grain for human consumption and livestock fodder. Mechanistic crop growth and water balance models are useful to forecast crop production and water use. However, very few studies have been devoted to the development of the model parameters needed for such simulations for pearl millet. The objectives of the study were to determine crop-specific model parameters for each of three pearl millet varieties (landrace, hybrid, and improved), as well as to calibrate and validate the Soil Water Balance (SWB) model for predicting pearl millet production and water use based on weather data. The SWB was chosen because it is widely used in southern Africa; however, the developed parameters should benefit other models as well. The presented crop-specific parameter values were derived from field observations and literature. Varieties with different phenology, maturity dates and tillering habits were grown under well-watered and well-fertilised conditions for calibration purposes. The calibrated model was used to predict biomass production, grain yield and crop water use. The hybrid's water use efficiency was higher than that of the landrace and improved variety.Pearl millet is an important crop for food security in Asia and Africa's arid and semi-arid regions. It is widely grown as a staple cereal grain for human consumption and livestock fodder. Mechanistic crop growth and water balance models are useful to forecast crop production and water use. However, very few studies have been devoted to the development of the model parameters needed for such simulations for pearl millet. The objectives of the study were to determine crop-specific model parameters for each of three pearl millet varieties (landrace, hybrid, and improved), as well as to calibrate and validate the Soil Water Balance (SWB) model for predicting pearl millet production and water use based on weather data. The SWB was chosen because it is widely used in southern Africa; however, the developed parameters should benefit other models as well. The presented crop-specific parameter values were derived from field observations and literature. Varieties with different phenology, maturity dates and tillering habits were grown under well-watered and well-fertilised conditions for calibration purposes. The calibrated model was used to predict biomass production, grain yield and crop water use. The hybrid's water use efficiency was higher than that of the landrace and improved variety.
Author Annandale, John G.
Steyn, Joachim Martin
Sanewe, Andrew J.
Ausiku, Petrus A.
AuthorAffiliation 1 Department of Plant and Soil Sciences, University of Pretoria, Private Bag X20, Pretoria 0028, South Africa; john.annandale@up.ac.za (J.G.A.); martin.steyn@up.ac.za (J.M.S.); adrew.sanewe@gmail.com (A.J.S.)
2 Department of Crop Production and Agriculture Technologies, University of Namibia, Private Bag 13301, Windhoek 9000, Namibia
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– name: 2 Department of Crop Production and Agriculture Technologies, University of Namibia, Private Bag 13301, Windhoek 9000, Namibia
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/35336688$$D View this record in MEDLINE/PubMed
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Issue 6
Keywords radiation use efficiency
Pennisetum glaucum
dry matter production
partitioning
extinction coefficient
crop growth
modelling
SWB
Language English
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Snippet Pearl millet is an important crop for food security in Asia and Africa’s arid and semi-arid regions. It is widely grown as a staple cereal grain for human...
Pearl millet is an important crop for food security in Asia and Africa's arid and semi-arid regions. It is widely grown as a staple cereal grain for human...
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SubjectTerms Agricultural production
Agriculture
Arid regions
Arid zones
Asia
Biomass
biomass production
Calibration
Cenchrus americanus
Crop growth
crop models
Crop production
Crop yield
Crops
cultivars
dry matter production
Economic forecasting
extinction coefficient
Food
Food security
Food supply
Forage
Grain
grain yield
Growth models
humans
hybrids
Irrigation
landraces
Livestock
Mathematical models
Meteorological data
Millet
modelling
Moisture content
Parameterization
Parameters
partitioning
Pennisetum glaucum
phenology
Precipitation
Production planning
Rain
Semi arid areas
Semiarid zones
Soil water
soil water balance
Southern Africa
tillering
Water balance
Water use
Water use efficiency
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Title Crop Model Parameterisation of Three Important Pearl Millet Varieties for Improved Water Use and Yield Estimation
URI https://www.ncbi.nlm.nih.gov/pubmed/35336688
https://www.proquest.com/docview/2642455732
https://www.proquest.com/docview/2644018671
https://www.proquest.com/docview/2648877757
https://pubmed.ncbi.nlm.nih.gov/PMC8951074
https://doaj.org/article/8512d783b3c54c9f981fa9dce511934e
Volume 11
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