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.

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