Theses and Dissertations

ORCID

https://orcid.org/0000-0001-7951-866X

Advisor

Jha, Prakash Kumar

Committee Member

Musser, Madhurima

Committee Member

Dhillon, Jagmandeep

Committee Member

Rangappa, Raju Bheemanahalli

Date of Degree

12-12-2025

Original embargo terms

Embargo 2 years

Document Type

Graduate Thesis - Open Access

Major

Plant and Soil Sciences (Agronomy)

Degree Name

Master of Science (M.S.)

College

College of Agriculture and Life Sciences

Department

Department of Plant and Soil Sciences

Abstract

Maize (Zea mays L.) productivity in U.S is increasingly vulnerable to climate variability and resource inefficiencies. In Mississippi, limited cultivar-specific modeling hinders resilient production, threatening yield stability and long-term food and economic security. This study calibrated and validated the CERES-Maize model for two hybrids (DK 70-27 and DK 70-45) using 2024-2025 field data from North Farm, Starkville, MS, and MAFES trials. Genetic coefficients were estimated via GENCALC and GLUE, and model performance was evaluated using R2, RMSE, MBE, and d-index. Results showed high model accuracy (above 0.9 R2 and 0.9 d-index), highlighting its potential as a robust tool for enhancing decision-making in crop management. Simulations under RCP 2.6 and RCP 8.5 (2026 – 2100) showed stable yields under RCP 2.6, while RCP 8.5 led to accelerated growth and increased crop failure risk. These findings support cultivar-specific modeling for climate resilient maize production in Mississippi.

Sponsorship (Optional)

Mississippi Agricultural and Forestry Experiment Station

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