Easy Leaf Area: Automated digital image analysis for rapid and accurate measurement of leaf area.

UnlabelledPremise of the studyMeasurement of leaf areas from digital photographs has traditionally required significant user input unless backgrounds are carefully masked. Easy Leaf Area was developed to batch process hundreds of Arabidopsis rosette images in minutes, removing background artifacts and saving results to a spreadsheet-ready CSV file. •Methods and resultsEasy Leaf Area uses the color ratios of each pixel to distinguish leaves and calibration areas from their background and compares leaf pixel counts to a red calibration area to eliminate the need for camera distance calculations or manual ruler scale measurement that other software methods typically require. Leaf areas estimated by this software from images taken with a camera phone were more accurate than ImageJ estimates from flatbed scanner images. •ConclusionsEasy Leaf Area provides an easy-to-use method for rapid measurement of leaf area and nondestructive estimation of canopy area from digital images

The effects of rising atmospheric carbon dioxide on shoot-root nitrogen and water signaling.

Terrestrial higher plants are composed of roots and shoots, distinct organs that conduct complementary functions in dissimilar environments. For example, roots are responsible for acquiring water and nutrients such as inorganic nitrogen from the soil, yet shoots consume the majority of these resources. The success of such a relationship depends on excellent root-shoot communications. Increased net photosynthesis and decreased shoot nitrogen and water use at elevated CO2 fundamentally alter these source-sink relations. Lower than predicted productivity gains at elevated CO2 under nitrogen or water stress may indicate shoot-root signaling lacks plasticity to respond to rising atmospheric CO2 concentrations. The following presents recent research results on shoot-root nitrogen and water signaling, emphasizing the influence that rising atmospheric carbon dioxide levels are having on these source-sink interactions

The physiological basis for genetic variation in water use efficiency and carbon isotope composition in Arabidopsis thaliana.

Ecologists and physiologists have documented extensive variation in water use efficiency (WUE) in Arabidopsis thaliana, as well as association of WUE with climatic variation. Here, we demonstrate correlations of whole-plant transpiration efficiency and carbon isotope composition (δ(13)C) among life history classes of A. thaliana. We also use a whole-plant cuvette to examine patterns of co-variation in component traits of WUE and δ(13)C. We find that stomatal conductance (g s) explains more variation in WUE than does A. Overall, there was a strong genetic correlation between A and g s, consistent with selection acting on the ratio of these traits. At a more detailed level, genetic variation in A was due to underlying variation in both maximal rate of carboxylation (V cmax) and maximum electron transport rate (Jmax). We also found strong effects of leaf anatomy, where lines with lower WUE had higher leaf water content (LWC) and specific leaf area (SLA), suggesting a role for mesophyll conductance (g m) in variation of WUE. We hypothesize that this is due to an effect through g m, and test this hypothesis using the abi4 mutant. We show that mutants of ABI4 have higher SLA, LWC, and g m than wild-type, consistent with variation in leaf anatomy causing variation in g m and δ(13)C. These functional data also add further support to the central, integrative role of ABI4 in simultaneously altering ABA sensitivity, sugar signaling, and CO2 assimilation. Together our results highlight the need for a more holistic approach in functional studies, both for more accurate annotation of gene function and to understand co-limitations to plant growth and productivity

Easy Leaf Area: Automated digital image analysis for rapid and accurate measurement of leaf area

Premise of the study: Measurement of leaf areas from digital photographs has traditionally required significant user input unless backgrounds are carefully masked. Easy Leaf Area was developed to batch process hundreds of Arabidopsis rosette images in minutes, removing background artifacts and saving results to a spreadsheet-ready CSV file. Methods and Results: Easy Leaf Area uses the color ratios of each pixel to distinguish leaves and calibration areas from their background and compares leaf pixel counts to a red calibration area to eliminate the need for camera distance calculations or manual ruler scale measurement that other software methods typically require. Leaf areas estimated by this software from images taken with a camera phone were more accurate than ImageJ estimates from flatbed scanner images. Conclusions: Easy Leaf Area provides an easy-to-use method for rapid measurement of leaf area and nondestructive estimation of canopy area from digital images

The effects of rising atmospheric carbon dioxide on shoot-root nitrogen and water signaling.

Terrestrial higher plants are composed of roots and shoots, distinct organs that conduct complementary functions in dissimilar environments. For example, roots are responsible for acquiring water and nutrients such as inorganic nitrogen from the soil, yet shoots consume the majority of these resources. The success of such a relationship depends on excellent root-shoot communications. Increased net photosynthesis and decreased shoot nitrogen and water use at elevated CO2 fundamentally alter these source-sink relations. Lower than predicted productivity gains at elevated CO2 under nitrogen or water stress may indicate shoot-root signaling lacks plasticity to respond to rising atmospheric CO2 concentrations. The following presents recent research results on shoot-root nitrogen and water signaling, emphasizing the influence that rising atmospheric carbon dioxide levels are having on these source-sink interactions

Easy Leaf Area: Automated digital image analysis for rapid and accurate measurement of leaf area.

Measurement of leaf areas from digital photographs has traditionally required significant user input unless backgrounds are carefully masked. Easy Leaf Area was developed to batch process hundreds of Arabidopsis rosette images in minutes, removing background artifacts and saving results to a spreadsheet-ready CSV file. • Easy Leaf Area uses the color ratios of each pixel to distinguish leaves and calibration areas from their background and compares leaf pixel counts to a red calibration area to eliminate the need for camera distance calculations or manual ruler scale measurement that other software methods typically require. Leaf areas estimated by this software from images taken with a camera phone were more accurate than ImageJ estimates from flatbed scanner images. • Easy Leaf Area provides an easy-to-use method for rapid measurement of leaf area and nondestructive estimation of canopy area from digital images

The physiological basis for genetic variation in water use efficiency and carbon isotope composition in Arabidopsis thaliana.

Ecologists and physiologists have documented extensive variation in water use efficiency (WUE) in Arabidopsis thaliana, as well as association of WUE with climatic variation. Here, we demonstrate correlations of whole-plant transpiration efficiency and carbon isotope composition (δ(13)C) among life history classes of A. thaliana. We also use a whole-plant cuvette to examine patterns of co-variation in component traits of WUE and δ(13)C. We find that stomatal conductance (g s) explains more variation in WUE than does A. Overall, there was a strong genetic correlation between A and g s, consistent with selection acting on the ratio of these traits. At a more detailed level, genetic variation in A was due to underlying variation in both maximal rate of carboxylation (V cmax) and maximum electron transport rate (Jmax). We also found strong effects of leaf anatomy, where lines with lower WUE had higher leaf water content (LWC) and specific leaf area (SLA), suggesting a role for mesophyll conductance (g m) in variation of WUE. We hypothesize that this is due to an effect through g m, and test this hypothesis using the abi4 mutant. We show that mutants of ABI4 have higher SLA, LWC, and g m than wild-type, consistent with variation in leaf anatomy causing variation in g m and δ(13)C. These functional data also add further support to the central, integrative role of ABI4 in simultaneously altering ABA sensitivity, sugar signaling, and CO2 assimilation. Together our results highlight the need for a more holistic approach in functional studies, both for more accurate annotation of gene function and to understand co-limitations to plant growth and productivity