This project aims at investigating the effect of CO2 enrichment on the growth and gas exchange of C3, C3-C4 and C4 Panicum grasses. Potted plants were grown in soil under well watered conditions, in artificially lit environmentally controlled cabinets or naturally lit greenhouses at varying levels of CO2 enrichment. CO2 enrichment enhanced the dry weight of C3 and C4 Panicum species under optimal light and N supplies, but had no effect on the total leaf N or TNC concentrations. The high-CO2 induced photosynthetic reaction in the C3 species was accompanied by a reduced Rubisco concentration and was related to the conservation of the relative growth rate of the plant. Elevated CO2 had no effect on the photosynthetic capacity of the C4 species, but enhanced its CO2 assimilation rates under high light and N supplies. The effect of elevated CO2 on the leaf and stem anatomy reflected increased carbon supply at high CO2 in the C3 grass, and reduced transpiratory demand at high CO2 in C4 grasses. Consequently, it is clear that both C3 and C4 grasses are likely to be more productive under rising atmospheric CO2 concentrations. / Doctor of Philosophy (PhD)

Diss. (sammanfattning) Alnarp : Sveriges lantbruksuniv. / Härtill 5 uppsatser.

Atmospheric CO₂ enrichment is employed by greenhouse tomato growers to increase fruit yields, and CO₂ applications are managed according to atmospheric set points or CO₂ injection rates. These methods do not immediately focus on the targets of CO₂ applications: plant performance and the regulation of plant carbon status. This thesis explores several plant-based approaches that may have potential for use in the management of CO₂ in greenhouse tomato production. Three plant-based approaches to CO₂ management were explored in commercial and experimental tomato greenhouses. These were: (1) simulation modeling, (2) non-destructive analysis of growth and (3) the status of plant carbon reserves. A cost and benefit analysis (c/b) using simulation modeling was carried out using grower-collected greenhouse environment and yield data. Simulation modeling was useful for retrospectively determining c/b of several CO₂ scenarios. The model was effective in predicting long term yields, but not short term yield variations, which limits its application for CO₂ management. Non-destructive measures of growth: stem length and diameter, leaf area and fruit load were found to be too sluggish for daily CO₂ dosing decision-making. Finally, plants growing under CO₂ enrichment can deposit substantial carbon as starch in their leaves. Plant carbon status was evaluated by determining the spatial distribution of leaf starch in the shoot and by following its variation diurnally and after the onset of CO₂ enrichment. As starch is difficult to measure by a grower, leaf mass per unit area (LMA) was also monitored for assessment as a surrogate measure for starch. Leaves in positions 7 to 9 were identified as the most meaningful in the shoot to sample. Diurnal profiles indicated these leaves carryover substantial starch from one day to the next. Monitoring starch at its peak time of accumulation (14 h to 16 h), at sunset and sunrise will indicate how much the peak starch reserves are used overnight. If starch remains high between peak and sunrise the following day, then the plants are in a carbon-surplus state and CO₂ enrichment could be postponed. For upper canopy leaves LMA is substantially influenced by starch and thus is a promising surrogate.

Atmospheric CO₂ enrichment is employed by greenhouse tomato growers to increase fruit yields, and CO₂ applications are managed according to atmospheric set points or CO₂ injection rates. These methods do not immediately focus on the targets of CO₂ applications: plant performance and the regulation of plant carbon status. This thesis explores several plant-based approaches that may have potential for use in the management of CO₂ in greenhouse tomato production. Three plant-based approaches to CO₂ management were explored in commercial and experimental tomato greenhouses. These were: (1) simulation modeling, (2) non-destructive analysis of growth and (3) the status of plant carbon reserves. A cost and benefit analysis (c/b) using simulation modeling was carried out using grower-collected greenhouse environment and yield data. Simulation modeling was useful for retrospectively determining c/b of several CO₂ scenarios. The model was effective in predicting long term yields, but not short term yield variations, which limits its application for CO₂ management. Non-destructive measures of growth: stem length and diameter, leaf area and fruit load were found to be too sluggish for daily CO₂ dosing decision-making. Finally, plants growing under CO₂ enrichment can deposit substantial carbon as starch in their leaves. Plant carbon status was evaluated by determining the spatial distribution of leaf starch in the shoot and by following its variation diurnally and after the onset of CO₂ enrichment. As starch is difficult to measure by a grower, leaf mass per unit area (LMA) was also monitored for assessment as a surrogate measure for starch. Leaves in positions 7 to 9 were identified as the most meaningful in the shoot to sample. Diurnal profiles indicated these leaves carryover substantial starch from one day to the next. Monitoring starch at its peak time of accumulation (14 h to 16 h), at sunset and sunrise will indicate how much the peak starch reserves are used overnight. If starch remains high between peak and sunrise the following day, then the plants are in a carbon-surplus state and CO₂ enrichment could be postponed. For upper canopy leaves LMA is substantially influenced by starch and thus is a promising surrogate.

Lic.-avh. Umeå : Sveriges lantbruksUniversity. / Härtill 2 uppsatser.

Atmospheric CO₂ enrichment is employed by greenhouse tomato growers to increase fruit yields, and CO₂ applications are managed according to atmospheric set points or CO₂ injection rates. These methods do not immediately focus on the targets of CO₂ applications: plant performance and the regulation of plant carbon status. This thesis explores several plant-based approaches that may have potential for use in the management of CO₂ in greenhouse tomato production. Three plant-based approaches to CO₂ management were explored in commercial and experimental tomato greenhouses. These were: (1) simulation modeling, (2) non-destructive analysis of growth and (3) the status of plant carbon reserves. A cost and benefit analysis (c/b) using simulation modeling was carried out using grower-collected greenhouse environment and yield data. Simulation modeling was useful for retrospectively determining c/b of several CO₂ scenarios. The model was effective in predicting long term yields, but not short term yield variations, which limits its application for CO₂ management. Non-destructive measures of growth: stem length and diameter, leaf area and fruit load were found to be too sluggish for daily CO₂ dosing decision-making. Finally, plants growing under CO₂ enrichment can deposit substantial carbon as starch in their leaves. Plant carbon status was evaluated by determining the spatial distribution of leaf starch in the shoot and by following its variation diurnally and after the onset of CO₂ enrichment. As starch is difficult to measure by a grower, leaf mass per unit area (LMA) was also monitored for assessment as a surrogate measure for starch. Leaves in positions 7 to 9 were identified as the most meaningful in the shoot to sample. Diurnal profiles indicated these leaves carryover substantial starch from one day to the next. Monitoring starch at its peak time of accumulation (14 h to 16 h), at sunset and sunrise will indicate how much the peak starch reserves are used overnight. If starch remains high between peak and sunrise the following day, then the plants are in a carbon-surplus state and CO₂ enrichment could be postponed. For upper canopy leaves LMA is substantially influenced by starch and thus is a promising surrogate. / Land and Food Systems, Faculty of / Graduate

This dissertation analyzes the impact of climate, and atmospheric carbon dioxide (CO2) on crop yields and grain transportation. The analysis of crop yields endeavors to advance the literature by statistically estimating the effects of atmospheric carbon dioxide (CO2) on observed crop yields. This is done using an econometric model estimated over pooled historical data for 1950-2009 and data from the free air CO2 enrichment experiments. The main findings are: 1) yields of soybeans, cotton, and wheat directly respond to the elevated CO2, while yields of corn and sorghum do not; 2) the effect of crop technological progress on mean yields is non-linear; 3) ignoring atmospheric CO2 in an econometric model of crop yield likely leads to overestimates of the pure effects of climate change and technological progress on crop yields; and 4) average climate conditions and climate variability contribute in a statistically significant way to average crop yields and their variability. To examine climate change impacts on grain transportation flows, this study employs two modeling systems, a U.S. agricultural sector model and an international grain transportation model, with linked inputs/outputs. The main findings are that under climate change: 1) the excess supply of corn and soybeans generally increases in Northern U.S. regions, while it declines in Central and Southern regions; 2) the Corn Belt, the largest producer of corn in the U.S., is anticipated to ship less corn; 3) the importance of lower Mississippi River ports, the largest current destination for U.S. grain exports, diminishes under the climate change cases, whereas the role of Pacific Northwest ports, Great Lakes ports, and Atlantic ports is projected to increase; 4) the demand for grain shipment via rail and truck rises, while demand for barge transport drops.