Müller J, Braune H, Diepenbrock W (2009) Complete parameterization of photosynthesis
models, an example for barley. Crop Model Decis Support 8:12–23
Murray J (2002) Mathematical biology. Springer, New York
Park SJ, Hwang CS, Vlek PLG (2005) Comparison of adaptive techniques to predict crop yield
response under varying soil and land management conditions. Agric Syst 85:59–81
Paul V, Srivastava GC (2006) Role of surface morphology in determining the ripening behaviour
of tomato (Lycopersicon esculentum Mill.) fruits. Sci Hortic 110:84–92
Prudent M, Bertin N, Genard M, Munos S, Rolland S, Garcia V, Petit J, Baldet P, Rothan C,
Causse M (2010) Genotype-dependent response to carbon availability in growing tomato fruit.
Plant Cell Environ 33:1186–1204
Quilot B, Génard M, Kervella J, Lescourret F (2004) Analysis of genotypic variation in fruit flesh
total sugar content via an ecophysiological model applied to peach. Theor Appl Genet
109:440–449
Rahimikhoob A (2010) Estimation of evapotranspiration based on only air temperature data using
artificial neural networks for a subtropical climate in Iran. Theoret Appl Climatol 101:83-91
Román-Román P, Torres-Ruiz F (2012) Modelling logistic growth by a new diffusion process:
Application to biological systems. BioSystems 110:9–21
Ríos-Moreno GJ, Trejo-Perea M, Castañeda-Miranda R, Hernández-Guzmán VM, Herrera-Ruíz
G (2006) Modelling temperature in intelligent buildings by means of autoregressive models.
Autom Constr 16(5):713–722
Seginer I, Ioslovich I (1998) A single state variable model to mimic tomgro for control
applications. Acta Hortic 456:93–100
Shier DR, Wallenius KT (1999) Applied mathematical modeling a multidisciplinary approach.
Chapman and Hall/CRC, Boca Raton
Sinclair TR, Seligman N (1996) Crop modeling: from infancy to maturity. Agron J 88:698–704
Sinclair TR, Seligman N (2000) Criteria for publishing papers on crop modeling. Field Crops Res
68:165–172
Sloof M, Tijskens LMM, Wilkinson EC (1996) Concepts for modelling the quality of perishable
products. Trends Food Sci Technol 7:165–171
Soltani A, Sinclair TR (2012) Modeling physiology of crop development, growth and yield. CAB
International, Egham. ISBN 978-1-84593-970-0
Soltani A, Robertson MJ, Torabi B, Yousefi-Daz M, Sarparast R (2006) Modeling seedling
emergence in chickpea as influenced by temperature and sowing depth. Agric For Metheorol
138:156–167
Soltani A, Galeshi S, Attarbashi MR (2004) Comparison of two methods for estimating
parameters of harvest index increase during seed growth. Field Crops Res 89:369–378
Sousa SIV, Martins FG, Pereira MC, Alvim-Ferraz MCM, Ribeiro H, Oliveira M, Abreu I (2010)
Use of multiple linear regressions to evaluate the influence of O 3 and PM 10 on biological
pollutants. Int J Civil Environ Eng 2(2):107–112
Sumpter BG, Getino C, Noid DW (1994) Theory and applications of neural computing in
chemical science. Annu Rev Phys Chem 45:439–481
Stein OR, Towler BW, Hook PB, Biederman JA (2007) On fitting the k-C* first order model to
batch loaded sub-surface treatment wetlands. Water Sci Technol 56(3):93–99
Tap F (2000) Economics-based optimal control of greenhouse tomato crop production, Phd
Thesis, Wageningen Agricultural University, Wageningen The Netherlands, p. 127
Tardieu F (2003) Virtual plants: modelling as a tool for the genomics of tolerance to water deficit.
Trends Plant Sci 8:9–14
Teh CBS (2006) Introduction to mathematical modeling of crop growth. Brown Walker Press,
Boca Raton
Thornley JHM, France J (2007) Mathematical models in agriculture quantitative methods for the
plant, animal and ecological sciences. CABI, Wallingford
Tijskens LMM, Schijevens EPHM, Biekman ESA (2001) Modelling the chargein color of
broccoli and beans during blaching. Innovative Food Sci Emerg Technol 2:303–313
2 Mathematical Modeling of Biosystems
75
models, an example for barley. Crop Model Decis Support 8:12–23
Murray J (2002) Mathematical biology. Springer, New York
Park SJ, Hwang CS, Vlek PLG (2005) Comparison of adaptive techniques to predict crop yield
response under varying soil and land management conditions. Agric Syst 85:59–81
Paul V, Srivastava GC (2006) Role of surface morphology in determining the ripening behaviour
of tomato (Lycopersicon esculentum Mill.) fruits. Sci Hortic 110:84–92
Prudent M, Bertin N, Genard M, Munos S, Rolland S, Garcia V, Petit J, Baldet P, Rothan C,
Causse M (2010) Genotype-dependent response to carbon availability in growing tomato fruit.
Plant Cell Environ 33:1186–1204
Quilot B, Génard M, Kervella J, Lescourret F (2004) Analysis of genotypic variation in fruit flesh
total sugar content via an ecophysiological model applied to peach. Theor Appl Genet
109:440–449
Rahimikhoob A (2010) Estimation of evapotranspiration based on only air temperature data using
artificial neural networks for a subtropical climate in Iran. Theoret Appl Climatol 101:83-91
Román-Román P, Torres-Ruiz F (2012) Modelling logistic growth by a new diffusion process:
Application to biological systems. BioSystems 110:9–21
Ríos-Moreno GJ, Trejo-Perea M, Castañeda-Miranda R, Hernández-Guzmán VM, Herrera-Ruíz
G (2006) Modelling temperature in intelligent buildings by means of autoregressive models.
Autom Constr 16(5):713–722
Seginer I, Ioslovich I (1998) A single state variable model to mimic tomgro for control
applications. Acta Hortic 456:93–100
Shier DR, Wallenius KT (1999) Applied mathematical modeling a multidisciplinary approach.
Chapman and Hall/CRC, Boca Raton
Sinclair TR, Seligman N (1996) Crop modeling: from infancy to maturity. Agron J 88:698–704
Sinclair TR, Seligman N (2000) Criteria for publishing papers on crop modeling. Field Crops Res
68:165–172
Sloof M, Tijskens LMM, Wilkinson EC (1996) Concepts for modelling the quality of perishable
products. Trends Food Sci Technol 7:165–171
Soltani A, Sinclair TR (2012) Modeling physiology of crop development, growth and yield. CAB
International, Egham. ISBN 978-1-84593-970-0
Soltani A, Robertson MJ, Torabi B, Yousefi-Daz M, Sarparast R (2006) Modeling seedling
emergence in chickpea as influenced by temperature and sowing depth. Agric For Metheorol
138:156–167
Soltani A, Galeshi S, Attarbashi MR (2004) Comparison of two methods for estimating
parameters of harvest index increase during seed growth. Field Crops Res 89:369–378
Sousa SIV, Martins FG, Pereira MC, Alvim-Ferraz MCM, Ribeiro H, Oliveira M, Abreu I (2010)
Use of multiple linear regressions to evaluate the influence of O 3 and PM 10 on biological
pollutants. Int J Civil Environ Eng 2(2):107–112
Sumpter BG, Getino C, Noid DW (1994) Theory and applications of neural computing in
chemical science. Annu Rev Phys Chem 45:439–481
Stein OR, Towler BW, Hook PB, Biederman JA (2007) On fitting the k-C* first order model to
batch loaded sub-surface treatment wetlands. Water Sci Technol 56(3):93–99
Tap F (2000) Economics-based optimal control of greenhouse tomato crop production, Phd
Thesis, Wageningen Agricultural University, Wageningen The Netherlands, p. 127
Tardieu F (2003) Virtual plants: modelling as a tool for the genomics of tolerance to water deficit.
Trends Plant Sci 8:9–14
Teh CBS (2006) Introduction to mathematical modeling of crop growth. Brown Walker Press,
Boca Raton
Thornley JHM, France J (2007) Mathematical models in agriculture quantitative methods for the
plant, animal and ecological sciences. CABI, Wallingford
Tijskens LMM, Schijevens EPHM, Biekman ESA (2001) Modelling the chargein color of
broccoli and beans during blaching. Innovative Food Sci Emerg Technol 2:303–313
2 Mathematical Modeling of Biosystems
75