Environmental Engineering Commons^™

Impact Of Water And Nitrogen Management Strategies On Maize Yield And Water Productivity Indices Under Linear-Move Sprinkler Irrigation, Daran Rudnick, Suat Irmak

Biological Systems Engineering: Papers and Publications

With uncertainty in future irrigation water availability and regulations on nutrient application amounts, experimentally determined effects of “controllable” management strategies such as nitrogen (N), water, and their combination on crop water productivity (CWP, also known as crop water use efficiency) and actual evapotranspiration (ET_a) are essential. The effects of various N application rates (0, 84, 140, 196, and 252 kg ha^-1) under fully irrigated (FIT), limited irrigation (75% FIT), and rainfed conditions on maize (Zea mays L.) yield and various CWP indices were investigated in 2011 and 2012 growing seasons under linear-move sprinkler irrigation in south …

Maize Evapotranspiration, Yield Production Functions, Biomass, Grain Yield, Harvest Index, And Yield Response Factors Under Full And Limited Irrigation, Koffi Djaman, Suat Irmak, William R. Rathje, Derrel L. Martin, Dean E. Eisenhauer

Biological Systems Engineering: Papers and Publications

South-central Nebraska is one of the most extensively irrigated areas in the U.S., with over 65,000 active irrigation wells, and maize is the major agronomical crop produced. Maize production in this region requires supplementary irrigation for maximum productivity. Effective on-farm implementation of full and limited irrigation practices for potential improvements of crop productivity requires knowledge of locally developed crop yield response to water functions. In this study, the effects of full and limited irrigation practices on maize (Zea mays L.) plant height, leaf area index (LAI), grain yield and biomass production, actual crop evapotranspiration (ET_a), yield production functions, …

Development And Evaluation Of Ordinary Least Squares Regression Models For Predicting Irrigated And Rainfed Maize And Soybean Yields, Vivek Sharma, Daran R. Rudnick, Suat Irmak

Biological Systems Engineering: Papers and Publications

Understanding the relationships between climatic variables and soil physical and chemical properties with crop yields on large scales is critical for evaluating crop productivity to make better assessments of local and regional food security, policy, land and water resource allocation, and management decisions. In this study, ordinary least squares(OLS) regression models were developed to predict irrigated and rainfed maize and soybean yields at the county level as a

function of explanatory variables [precipitation (P), actual crop evapotranspiration (ETa), organic matter content (OMC), cation exchange capacity (CEC), clay content (CC), and available soil water capacity (ASW)] of the dominant soil type …

Transferability Of Jarvis-Type Models Developed And Re-Parameterized For Maize To Estimate Stomatal Resistance Of Soybean: Analyses On Model Calibration, Validation, Performance, Sensitivity, And Elasticity, Denis Mutiibwa, Suat Irmak

Biological Systems Engineering: Papers and Publications

In a previous study by the same authors, a new modified Jarvis model (NMJ-model) was developed, calibrated, and validated to estimate stomatal resistance (rs) for maize canopy on an hourly time step. The NMJ-model’s unique subfunctions, different from the original Jarvis model (J-model), include a photosynthetic photon flux density

(PPFD)-r_s response subfunction developed from field measurements and a new physical term, Aexp(1/LAI), where A is the minimum stomatal resistance and LAI is the green leaf area index, to account for the influence of canopy development on r_s, especially during partial canopy stage in the early season and …