Location: Adaptive Cropping Systems Laboratory2010 Annual Report
1a. Objectives (from AD-416)
The overall objective is to refine and improve existing simulation models for corn and potato by developing new, and improving existing functional relationships between physiological processes and nutrients in the soil and plant tissues. Results of this research will be used to address existing knowledge gaps in the models. The modified models will be evaluated by testing simulated responses at plant component and whole plant levels. The specific sub-objectives are to improve simulation of the above- and below-ground potato and corn processes in the areas of: (1) water and nutrient stress effects on growth, development, morphology, and yield, and (2) response of root growth and activity (water and nutrient uptake) to soil nutrients (N, P and K), and water. The model and new components will be evaluated using experimental data. The potato and corn models, along with a rye cover crop model and existing models for soybean and corn, will then be used for assessment of the environmental consequences of agricultural management practices on carbon sequestration and nutrient balances. These practices include fertilizer applications, rotations, and cover crops.
1b. Approach (from AD-416)
Mechanistic models for soybean (GLYCIM), cotton (GOSSYM), corn (MAIZSIM) and potato (SPUDSIM) have been developed in previous projects by this group. The proposed research will broaden the capabilities of the corn and potato models by utilizing data from experiments carried out in unique, state-of-the-art sun-lit growth chambers and field plots. Short and long term experiments will be employed to test hypotheses and develop algorithms for plant processes to be used in the computer models. Data collected by collaborators will be used to test and evaluate the models. A simple Rye model will be developed to simulate a cover crop during the fall-winter season. A computer graphical user interface will be developed using components from the existing software program, GUICS, to allow a user to simulate long term crop rotations over multiple growing seasons. Advanced data management capabilities will be added to the interface to help with interpretation and management of input and output data. Tools for weather generation and estimation of soil hydraulic properties will be added to the interface to provide a wide range of environmental conditions for assessment. All crop models will be used within the new interface to assess the environmental and economic impacts of climate change on carbon sequestration, and nitrogen and water balances for relevant production systems.
3. Progress Report
Experiments were carried out in outdoor growth chambers to quantify the effects of nutrient deficiency (nitrogen and phosphorus) and water stress on growth, development, and photosynthesis in corn and potato under elevated and ambient CO2 levels. No interaction of CO2 and phosphorus was observed in potato for most responses, but main effects of P deficiency and CO2 enrichment on dry matter production, partitioning, and leaf level gas exchange were observed. A submodel to quantify nitrogen demand as a function of plant growth was added to the corn model, MAIZSIM. Additional algorithms were added to the corn model to estimate the effect of nitrogen deficit on carbon assimilation and leaf growth. Preliminary tests indicate the model was producing results consistent with literature values. Algorithms were added to the potato model, SPUDSIM, to indirectly simulate effects of nitrogen excess and deficiency on carbon allocation, photosynthetic rate, and leaf expansion. A collaborative research project to investigate interactions among plant and weed densities, and percent cover of rye mulch was carried out with the Sustainable Agricultural Systems Laboratory (SASL). Data on leaf area, biomass, soil temperature, and water use in soybean were collected from a field experiment. The collected data will be used to parameterize and test the soybean model GLYCIM for application in quantifying mulch cover and weed effects on soybean growth and yield. We also continued collaboration with scientists from SASL to collect data on rye crop development. Data on water use and nitrogen uptake/leaching was collected from a field experiment in collaboration with the two scientists from SASL, and another scientist from the Environmental Management & Byproduct Utilization Laboratory (EMBUL). The goal is to quantify the fate of labeled nitrogen planted to rye and wheat cover crops. Continued work with the NRCS to evaluate the APEX model for use in the CEAP program. The progress is fully described in the project report for project 1265-61660-006-01R Conservation Effects Assessment Project. Continued collaboration with scientists at the Agricultural Systems Research Laboratory in Ft. Collins, Colorado for the corn model evaluation and implementation. Also continued an ongoing collaboration with the Vegetable Crops Research Unit in Prosser, Washington to validate and test the potato model. During the last six years, several experiments were conducted by varying genotypes, nitrogen, irrigation and a plant growth regulator, PIX (4 levels) either alone or in combination at Mississippi State. The objective of this project is to assemble the weather, crop, and cultural database in a form that we can utilize for cotton model (GOSSYM) calibration and validation efforts so that the cotton model performance can be tested against more recently collected field data. Experiments on CO2 and temperature interactions on rice were carried out in indoor growth chambers by a visiting scientist from India. Three temperatures and two CO2 levels were applied. Leaf photosynthesis, seed formation, leaf area, and biomass data were collected for analysis.
1. Scientists in Beltsville, MD developed and tested an improved mathematical model of photosynthesis for the potato crop that is responsive to sunlight, temperature, and the carbon dioxide content of the atmosphere. Mathematical crop models have been developed over the past forty years as assessment and farm management tools. In spite of the efforts made in improving these crop models, there still exists the need to make their predictions more accurate. A new potato model called SPUDSIM, that incorporates new procedures and mathematics based on recent scientific findings, was developed and tested over a wide range of conditions. The results of this study suggest SPUDSIM will be able to help farmers with their operations, as well as scientists, and food policy planners interested in studying possible climate change effects and conservation.
2. An improved method to monitor fertilizer movement in agricultural soils was developed by scientists in Beltsville, MD. Over application of nitrogen fertilizer when mixed in irrigation water can pollute groundwater and result in economic losses when nutrients move past the root zone. Therefore, the ability to monitor the depth of fertilizer application is of great benefit to agricultural managers. We tested an easy-to-use soil water measuring tool that also measures soil salinity, an estimate of fertilizer content in the soil. In laboratory experiments, the instrument was found to provide good estimates of fertilizer content of the soil water after excess water drained from the soil profile. This information will be useful to agricultural managers and scientists who apply fertilizer with irrigation water.
3. The variability of plant growth and plant functions, such as carbon dioxide uptake between sunlit outdoor growth chambers, was assessed by scientists in Beltsville, MD. In order to ensure the highest quality plant research, it is critical to detect and characterize statistical differences in soil-bin chamber environmental characteristics and resultant plant performance when multiple chambers are used. Scientists measured plant growth and carbon dioxide uptake in 12 outdoor, sunlit growth chambers with soil compartments where environmental conditions, experimental protocols and plant populations were similar. The variability in plant growth between chambers was less than variability within a chamber. The results of this study indicate that researchers using outdoor sunlit soil-bin growth chambers are justified in using minimal replications so long as appropriate protocols are followed. These findings will benefit researchers in the design and analysis of their experiments utilizing sun-lit growth chambers.
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