ESTIMATION OF THE GENETIC COEFFICIENTS OF THE CERES-MAIZE MODEL FOR THE SIMULATION OF YIELD BY NON-DESTRUCTIVE METHODS

Autores/as

DOI:

https://doi.org/10.47163/agrociencia.v57i2.2505

Palabras clave:

Keywords: Dynamic crop models, model parameters, leaf area index–LAI, days to anthesis, days to physiological maturity.

Resumen

The Crop Environment Resource Synthesis-Maize (CERES-Maize) mechanistic model, included in the Decision Support System for Agrotechnology Transfer (DSSAT), is a useful and powerful tool that simulates the growth and grain yield of maize in different environments. The qualitative and quantitative information provided to the CERES-Maize model guarantees reliability in the simulations obtained. However, it requires a lot of information, including soil characteristics, daily climate, crop characteristics and management, and six genetic coefficients. The objective of this research was to assess a non-destructive methodology for estimating the six genetic coefficients P1, P2, P5, G2, G3 (associated with plant maturity stages) and Phyllochron interval (PHINT), based on the maize physiology and measured by the Growing Degree Days (GDD), base 10. Two experiments were established at the International Maize and Wheat Improvement Center (CIMMYT) experimental station in Tlaltizapan, Morelos, Mexico, where 27 white and 14 yellow maize hybrids were manually sown in an irrigation conservation tillage system. Once the maize growth and grain yield simulations were obtained with CERES-Maize model, the genetic coefficients were calibrated using the Generalized Likelihood Uncertainty Estimation (GLUE). After calibration of the six genetic coefficients for all hybrids, average values of P1, G2, and G3 were within the typical range, while P2 and P5 were greater than the typical range and PHINT was below typical range. However, the simulation model showed good performance after calibration, with an average R2 of 0.9809 and 0.9730 between measured and simulated grain yields for white and yellow hybrids, respectively. The coefficients estimated in this study can be used in the CERES-Maize model to simulate grain yields for the hybrids used in different regions of the country.

 

Biografía del autor/a

José Luis Noriega Navarrete , Universidad Autónoma Chapingo

José Luis Noriega-Navarrete is an  agricultural engineer  graduated from “Universidad Nacional Autónoma de México” , completed a master's degree in horticulture and doctoral degree in Agricultural Engineering and Integrated Water Use at “Universidad Autónoma Chapingo”. Currently he works as a professor at the “Universidad para el Bienestar Benito Juárez”.

Raquel Salazar Moreno, Universidad Autónoma Chapingo

Raquel Salazar-Moreno obtain her Ph.D  in Agricultural and Biosystems Engineering at University of Arizona. Currently, she is a Professor-Researcher at the  Agricultural Mechanical Engineering Department and at the  Graduate Program in Agricultural Engineering and Integrated Water Use at the Universidad Autónoma Chapingo, in Mexico.  She is a member of the National System of Researchers of CONACYT (level I). She is doing research related to water and energy use efficiency, urban agriculture, crop modelling and  artificial neural networks applied to agricultural problems.

Juan Andrés Burgueño-Ferreira , CIMMYT

Juan Andrés Burgueño-Ferreira is an agricultural engineer  graduated from “Universidad de la República Uruguay”. He completed a master's degree and doctoral degree in Socioeconomics and Statistics Institute at Colegio de Posgraduados in Mexico. He has been working at International Maize and Wheat Improvement Center (CIMMYT) since 2011. He has multiple publications in various journals among which stand out “ Effects of conservation agriculture on physicochemical soil health in 20 maize‐based trials in different agro‐ecological regions across Mexico” , “Rapid Cycling Genomic Selection in a Multiparental Tropical Maize Population”.

Irineo Lorenzo Cruz, Universidad Autónoma Chapingo

Irineo López Cruz obtain his Ph.D  in Agricultural Engineering from Wageningen University,  his master's degree in Artificial Intelligence from the Arturo Rosenblueth Foundation.  Currently, he is a Professor-Researcher at the  Agricultural Mechanical Engineering Department and at the  Graduate Program in Agricultural Engineering and Integrated Water Use at the Universidad Autónoma Chapingo, in Mexico.  He is a member of the National System of Researchers of CONACYT (level II). Member of the Mexican Academy of Sciences. Chairman of the Greenhouse Environment and climate control working group of the Horticultural Engineering commission of the International Society for Horticultural Science (ISHS).

César Daniel Petroli , CIMMYT

César Daniel Petroli  got his Ph. D at Universidad de Brasilia, in colaboration with  EMBRAPA (Agricultural Enterprise in  Brasil). Currently he is a high-throughput Genotyping Specialist at International Maize and Wheat Improvement Center (CIMMYT).

Dr. Petroli and his team have the ability to determine the genetic makeup of up to 2,500 corn samples per week, both for CIMMYT and its collaborators, and generate vast amounts of data in the process. He determined the genetic configuration of varieties and collections of corn and wheat, which  helps corn breeders to identify in DNA.

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Publicado

15-03-2023

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Fitociencia