Jeff Melkonian

Evaluation of the PNM model for simulating drain flow nitrate-N concentration under manure-fertilized maize

Mathematical models may be used to develop management strategies that optimize the use of nutrients from complex sources such as manure in agriculture. The Precision Nitrogen Management (PNM) model is based on the LEACHN model and a maize N uptake/growth and yield model and focuses on developing more precise N management recommendations. The PNM model was evaluated for simulating drain flow nitrate-nitrogen (NO3-N) in a 3-yr study involving different times of liquid manure application on two soil textural extremes, a clay loam and a loamy sand under maize (Zea mays, L.) production. The model was calibrated for major N transformation rate constants including mineralization, nitrification and denitrification, and its performance was tested using two different calibration scenarios with increasing levels of generalization: (i) separate sets of rate constants for each individual soil type and (ii) a single set of rate constants for both soil types. When calibrated for each manure application treatment for each soil type, the model provided good simulations of monthly and seasonal drain flow NO3-N concentrations. The correlation coefficient (r) and Willmott’s index of agreement (d) ranged from 0.63 to 0.96 and 0.72 to 0.92, respectively. The calibrated model performed reasonably well when rate constant values averaged over manure application treatment for each soil type were used, with r and d values between 0.54 and 0.97, and 0.70 and 0.94, respectively, and greater accuracy for the clay loam soil. When rate constant values were averaged over manure application treatments and soil types, model performance was reasonably accurate for the fall time manure application on the clay loam (r and d of 0.60 and 0.91 and 0.72 and 0.92, respectively) and satisfactory for the spring time on the clay loam and the fall and spring times for the loamy sand soil (r and d between 0.56 and 0.90 and 0.58 and 0.84, respectively). The use of the model for predicting N dynamics under manure-fertilized maize cropping appears promising.

Gas exchange and co-regulation of photochemical and nonphotochemical quenching in bean during chilling at ambient and elevated carbon dioxide

The effects of elevated (700 µmol mol−1) and ambient (350 µmol mol−1) CO2 on gas exchange parameters and chlorophyll fluorescence were measured on bean (Phaseolus vulgaris) during 24 h chilling treatments at 6.5 °C. Consistent with previous research on this cultivar, photosynthetic decline during chilling was not significantly affected by CO2 while post-chilling recovery was more rapid at elevated compared to ambient CO2. Our primary focus was whether there were also CO2-mediated differences in demand on nonphotochemical quenching (NPQ) processes during the chilling treatments. We found that photosystem II quantum yield and total NPQ were similar between the CO2 treatments during chilling. In both CO2 treatments, chilling caused a shift from total NPQ largely composed of qE, the protective, rapidly responding component of NPQ, to total NPQ dominated by the more slowly relaxing qI, related to both protective and damage processes. The switch from qE to qI during chilling was more pronounced in the elevated CO2 plants. Using complementary plots of the quantum yields of photochemistry and NPQ we demonstrate that, despite CO2 effects on the partitioning of NPQ into qE and qI during chilling, total NPQ was regulated at both CO2 levels to maximize photochemical utilization of absorbed light energy and dissipate only that fraction of light energy that was in excess of the capacity of photosynthesis. Photodamage did occur during chilling but was repaired within 3 h recovery from chilling in both CO2 treatments.

Separating heat stress from moisture stress: analyzing yield response to high temperature in irrigated maize

Several recent studies have indicated that high air temperatures are limiting maize (Zea mays L.) yields in the US Corn Belt and project significant yield losses with expected increases in growing season temperatures. Further work has suggested that high air temperatures are indicative of high evaporative demand, and that decreases in maize yields which correlate to high temperatures and vapor pressure deficits (VPD) likely reflect underlying soil moisture limitations. It remains unclear whether direct high temperature impacts on yields, independent of moisture stress, can be observed under current temperature regimes. Given that projected high temperature and moisture may not co-vary the same way as they have historically, quantitative analyzes of direct temperature impacts are critical for accurate yield projections and targeted mitigation strategies under shifting temperature regimes. To evaluate yield response to above optimum temperatures independent of soil moisture stress, we analyzed climate impacts on irrigated maize yields obtained from the National Corn Growers Association (NCGA) corn yield contests for Nebraska, Kansas and Missouri. In irrigated maize, we found no evidence of a direct negative impact on yield by daytime air temperature, calculated canopy temperature, or VPD when analyzed seasonally. Solar radiation was the primary yield-limiting climate variable. Our analyses suggested that elevated night temperature impacted yield by increasing rates of phenological development. High temperatures during grain-fill significantly interacted with yields, but this effect was often beneficial and included evidence of acquired thermo-tolerance. Furthermore, genetics and management—information uniquely available in the NCGA contest data—explained more yield variability than climate, and significantly modified crop response to climate. Thermo-acclimation, improved genetics and changes to management practices have the potential to partially or completely offset temperature-related yield losses in irrigated maize.

Drainage and Nitrate Leaching from Artificially Drained Maize Fields Simulated by the Precision Nitrogen Management Model

Environmental nitrogen (N) losses (e.g., nitrate leaching, denitrification, and ammonia volatilization) frequently occur in maize ( L.) agroecosystems. Decision support systems, designed to optimize the application of N fertilizer in these systems, have been developed using physically based models such as the Precision Nitrogen Management (PNM) model of soil and crop processes, which is an integral component of Adapt-N, a decision support tool providing N fertilizer recommendations for maize production. Such models can also be used to estimate N losses associated with particular management practices and over a range of current climates and future climate projections. The objectives of this study were to update the PNM model to include an option for simulating soil-water processes in artificially drained soils, and to calibrate the revised PNM model and test it against multiyear field studies in New York and Minnesota with different soils and management practices. Minimal calibration was required for the model. Denitrification rate constants were calibrated by minimizing the error between simulated and observed nitrate leaching for each study site. The normalized root mean squared error of cumulative daily drainage for the validation sets ranged from 10 to 23%. For cumulative daily nitrate leaching, the normalized root mean squared error ranged from 11 to 28% for the validation sets. The minimal calibration required and relatively simple data inputs make the PNM model a broadly applicable tool for simulating water and N flows in maize systems.

Effects of elevated carbon dioxide on gas exchange and photochemical and nonphotochemical quenching at low temperature in tobacco plants varying in Rubisco activity.

AbstractElevated (700 μmol mol−1) and ambient (350 μmol mol−1) CO2 effects on total ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) activity, photosynthesis (A), and photoinhibition during 6 d at low temperature were measured on wild type (WT), and rbcS antisense DNA mutants (T3) of tobacco (Nicotiana tabacum L.) with 60% of WT total Rubisco activity (Rodermel et al. (1988) Cell 55: 673–681). Prior to the low temperature treatment, A and quantum yield of PSII photochemistry in the light adapted state (φPSII) were significantly lower in T3 compared to WT at each CO2 level. At this time, total nonphotochemical quenching (NPQTotal) levels were near maximal (0.75–0.85) in T3 compared to WT (0.39–0.50). A was stimulated by 107% in T3 and 25% in WT at elevated compared to ambient CO2. Pre-treatment acclimation to elevated CO2 occurred in WT resulting in lower Rubisco activity per unit leaf area and reduced stimulation of A. At low temperature, A of WT was similar at elevated and ambient CO2 while stimulation of A by elevated CO2 in T3 was reduced. In addition, at low temperature we measured significantly lower photochemical quenching at elevated CO2 compared to ambient CO2 in both genotypes. NPQTotal was similar (0.80–0.85) among all treatments. However, a larger proportion of NPQTotal was composed of qI,d, the damage subcomponent of the more slowly relaxing NPQ component, qI, in both genotypes at elevated compared to ambient CO2. Greater qI,d, at elevated CO2 during and after the low temperature treatment was not related to pre-treatment differences in total Rubisco activity.

Subsurface Drainage Nitrogen Discharges Following Manure Application: Measurements and Model Analyses

Increasing concentrations of nitrate-nitrogen (NO3-- N) in surface and groundwater resources are a major water quality concern. A five year experiment to examine NO3-- N leaching losses to subsurface drains under continuous maize (Zea mays L.) was carried out, where mineral N and two separate liquid dairy manure applications under different conditions were applied following current agronomic N management guidelines. Yearly cumulative drainage and mass of NO3-- N leached varied from 118 mm – 353 mm, and 10.9 – 30.9 kg ha-1, respectively, over the five years. The timing and extent of N losses were associated with antecedent soil moisture conditions, soil temperature, preferential flow, precipitation, tillage and timing/rate/method of manure application. Well-calibrated dynamic simulation models can be used to integrate these factors, and predict the impact of different manure N management practices for maize production on N losses. We have developed such a model, the Precision Nitrogen Management (PNM) model, composed of LEACHN, the N module of LEACHM linked to a maize N uptake, growth and yield model. We compared PNM model predictions of daily drainage, mass of NO3-- N leached and NO3-- N concentration exiting the root zone with measured values in subsurface drains over the course of the study. The model predictions provided a good fit to the observed data. The adjusted R2 were 0.82 and 0.80, and the Wilmott’s index of agreement was 0.93 and 0.94, respectively, for drainage and mass of NO3-- N leached.

Soil and atmosphere exchange: simulating evapotranspiration with GLOBE measurements and NDVI

The GLOBE program is an international partnership of K-12 students, teachers, and scientists working together to study and understand the global environment. Through its suite of data collection and extensive network, GLOBE provides a valuable resource for initializing and validating SVAT models across different ecosystems. The General Purpose Simulation Model of the Atmosphere-Plant-Soil System(GAPS), a menu-driven capacitance SVAT model with multiple soil layers, was used to simulate daily water fluxes at one GLOBE site. Soil, climate, and land cover measurements made by students from Reynolds Junior and Senior High School in Greenville, PA, USA, coupled with normalized difference vegetation index(NDVI) data, derived from SPOT4 Vegetation Imagery, were used to parameterize and validate model simulations. Simulated daily soil water within the root zone for 1998 through 2001 showed a reasonable fit with soil water field measurements collected by students for that time period. A further refinement of the evapotranspiration algorithm is being investigated for improving model simulations. This revised algorithm incorporates derived phonological metrics (e.g. start and end of season, time of maximum photosynthetic activity) from temporal NDVI data and uses those metrics as input parameters for the model.