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United States Department of Agriculture

Agricultural Research Service

Research Project: MECHANISTIC PROCESS-LEVEL CROP SIMULATION MODELS FOR ASSESSMENT OF AGRICULTURAL SYSTEMS

Location: Crop Systems & Global Change

Title: Plasticulture to SPAR chamber technology: a survey of recent CSGCL activities

Authors
item FLEISHER, DAVID
item Resop, Jonathan
item TIMLIN, DENNIS
item REDDY, VANGIMALLA

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: February 12, 2013
Publication Date: N/A

Technical Abstract: Research at the USDA-ARS Crop Systems and Global Change Laboratory (CSGCL) addresses complex agricultural problems using a combination of modeling and experimental approaches. Recent experimental activities were conducted in a variety of controlled environment systems. At the most technologically intensive level, our soil-plant-atmosphere research (SPAR) growth chambers were used to investigate crop responses to climate change and management factors. Potato gas exchange and carbohydrate partitioning, including harvest index, were positively influenced by elevated CO2 level under drought conditions, suggesting some potential for water-stress mitigation under future climate change scenarios. At a much simpler technology level, the utility of low-tunnel plasticulture for extending the strawberry production growing season in Mid-Atlantic States was investigated in collaborative work. Detailed micro-climate data indicated substantial differences in thermal and radiative environments inside and outside the tunnels, and are being utilized to develop a predictive modeling tool for growers. In a different application, plywood growth chambers were constructed to evaluate plant response under more energy efficient induction lamps as compared to traditional HID and CWF lighting systems. Initial results using strawberry as a model system indicated similar growth and development responses under the different lighting regimes. This presentation will address these recent activities, divided according to the level of controlled environment complexity, in additional detail.

Last Modified: 8/19/2014
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