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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Predicting lettuce canopy photosynthesis with statistical and neural network models

An artificial neural network (NN) and a statistical regression model were developed to predict canopy photosynthetic rates (Pn) for 'Waldman's Green' leaf lettuce (Latuca sativa L.). All data used to develop and test the models were collected for crop stands grown hydroponically and under controlled-environment conditions. In the NN and regression models, canopy Pn was predicted as a function of three independent variables: shootzone CO2 concentration (600 to 1500 micromoles mol-1), photosynthetic photon flux (PPF) (600 to 1100 micromoles m-2 s-1), and canopy age (10 to 20 days after planting). The models were used to determine the combinations of CO2 and PPF setpoints required each day to maintain maximum canopy Pn. The statistical model (a third-order polynomial) predicted Pn more accurately than the simple NN (a three-layer, fully connected net). Over an 11-day validation period, average percent difference between predicted and actual Pn was 12.3% and 24.6% for the statistical and NN models, respectively. Both models lost considerable accuracy when used to determine relatively long-range Pn predictions (> or = 6 days into the future).

Non-NASA Center↗
NASA NTRS1998

The origin and evolution of oxygenic photosynthesis

The evolutionary developments that led to the ability of photosynthetic organisms to oxidize water to molecular oxygen are discussed. Two major changes from a more primitive non-oxygen-evolving reaction center are required: a charge-accumulating system and a reaction center pigment with a greater oxidizing potential. Intermediate stages are proposed in which hydrogen peroxide was oxidized by the reaction center, and an intermediate pigment, similar to chlorophyll d, was present.

Review, Tutorial↗
NASA NTRS2021

Single-Turnover Variable Chlorophyll Fluorescence as a Tool for Assessing Phytoplankton Photosynthesis and Primary Productivity: Opportunities, Caveats and Recommendations

Phytoplankton photosynthetic physiology can be investigated through single-turnover variable chlorophyll fluorescence (ST-ChlF) approaches, which carry unique potential to autonomously collect data at high spatial and temporal resolution. Over the past decades, significant progress has been made in the development and application of ST-ChlF methods in aquatic ecosystems, and in the interpretation of the resulting observations. At the same time, however, an increasing number of sensor types, sampling protocols, and data processing algorithms have created confusion and uncertainty among potential users, with a growing divergence of practice among different research groups. In this review, we assist the existing and upcoming user community by providing an overview of current approaches and consensus recommendations for the use of ST-ChlF measurements to examine in-situ phytoplankton productivity and photo-physiology. We argue that a consistency of practice and adherence to basic operational and quality control standards is critical to ensuring data inter-comparability. Large datasets of inter-comparable and globally coherent ST-ChlF observations hold the potential to reveal large-scale patterns and trends in phytoplankton photo-physiology, photosynthetic rates and bottom-up controls on primary productivity. As such, they hold great potential to provide invaluable physiological observations on the scales relevant for the development and validation of ecosystem models and remote sensing algorithms.

variable chlorophyll fluorescence↗
DOE OSTI2025

The Elements of Life, Photosynthesis and Genomics

I am a Professor of Biochemistry, Biophysics and Structural Biology and Plant and Microbial Biology at the University of California in Berkeley. I was born and raised in India, emigrated to the United States to attend university, earning a B.S. in Molecular Biology and a Ph.D. in Biochemistry at the University of Wisconsin in Madison. Following post-doctoral studies with Lawrence Bogorad at Harvard University where I became interested in genetic control of trace element quotas, I joined the department of Chemistry and Biochemistry at UCLA. One of the first to appreciate essential trace metals as potential regulators of gene expression, I articulated the details of the nutritional Cu regulon in Chlamydomonas. In parallel, I used genetic approaches to discover the genes governing missing steps in tetrapyrrole metabolism, including the attachment of heme to apocytochromes in the thylakoid lumen and the factors catalyzing the formation of ring V in chlorophyll. After biochemistry and classical genetics, I embraced genomics, taking a leadership role on the Joint Genome Institute’s efforts on the Chlamydomonas genome and more recently, contributing to high quality assemblies of several genomes in the green algal radiation, and large transcriptomic and proteomic datasets — focusing on the diel metabolic cycle in synchronized cultures and acclimation to key environmental and nutritional stressors — that are well-used and appreciated by the community. Finally, a new venture in Berkeley is the promotion of Auxenochlorella protothecoides as the true “green yeast” and as a platform for engineering algae to produce useful bioproducts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Photosynthesis of CO from CO 2 with an iron polypyridyl catalyst at a passivated silicon photoelectrode

A first-row transition metal catalyst, [Fe(tpy)(Mebim-py)(NCCH 3 )] 2+ (tpy = 2,2′:6′,2′′-terpyridine, Mebim-py = 1-methylbenzimidazol-2-ylidene-3-(2′-pyridine)) mediates CO 2 reduction to CO at passivated p-Si photoelectrodes with applied potentials 240 mV positive of the standard CO 2 /CO reduction potential. The molecular catalyst's selectivity for CO was retained under photoelectrochemical conditions, with negligible direct proton reduction promoted by the photoelectrode. The faradaic efficiency for CO (44 ± 6%) was slightly enhanced relative to the catalyst performance in the dark (33%). A photosynthetic cell based on this photocathode system, coupled with ferrocene oxidation at the anode, successfully operated at a cell voltage of −1.2 V. The photovoltage generated by illumination of p-Si–CH 3 met and surpassed the potential required for CO 2 reduction when coupled with ferrocene oxidation. By leveraging a low-overpotential CO 2 reduction electrocatalyst, a photo-assisted electrochemical efficiency of 0.15% and applied bias photon-to-current efficiency of 0.05% was achieved for this single-junction cell, ultimately storing 46 kJ mol −1 (11 kcal mol −1 ) of photon energy.

Carbon Dioxide Reduction↗