Open AccessData Descriptor

Long-Term Outdoor Cultivation of Nannochloropsis in California, Hawaii, and New Mexico

Alina A. Corcoran

^1,2,*,

Marcela Saracco Alvarez

Taryn Cornell

⁴,

Isidora Echenique-Subiabre

⁴

Julia Gerber

³,

Stephanie Getto

Ahlem Jebali

²,

Heather Martinez

²,

Jakob O. Nalley

⁵,

Charles J. O’Kelly

³,

Aidan Ryan

⁴,

Jonathan B. Shurin

⁴ and

Shawn R. Starkenburg

⁶

Department of Biology, New Mexico State University, Las Cruces, NM 88003, USA

New Mexico Consortium, Los Alamos, NM 87544, USA

Cyanotech Corporation, Inc., Kailua-Kona, HI 96740, USA

⁴

Corcoran Laboratory, University of California San Diego, San Diego, CA 92093, USA

⁵

Qualitas Health, 1707 Post Oak Blvd, Houston, TX 77056, USA

⁶

Los Alamos National Laboratory, Los Alamos, NM 87545, USA

Author to whom correspondence should be addressed.

Data 2024, 9(11), 126; https://doi.org/10.3390/data9110126

Submission received: 20 August 2024 / Revised: 27 September 2024 / Accepted: 29 September 2024 / Published: 29 October 2024

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Abstract

The project “Optimizing Selection Pressures and Pest Management to Maximize Cultivation Yield” (OSPREY, award #DE-EE08902) was undertaken to enhance the annual productivity, stability, and quality of algal production strains for biofuels and bioproducts. The foundation of this project was the year-round cultivation of a Nannochloropsis strain across three outdoor systems in California, Hawaii, and New Mexico. We aimed to leverage environmental selection pressures to drive strain improvement and use metagenomic techniques to inform pest management tools. The resulting dataset includes environmental and biological parameters from these cultivation campaigns, captured in a single CSV file. This dataset aims to serve a wide range of end users, from biologists to algal farmers, addressing the scarcity of publicly available data on algae cultivation. Further data releases will include 16S rRNA amplicon sequencing and shotgun sequencing datasets.

Dataset: Data are contained within the article or Supplementary Materials.

Dataset License: CC0

Keywords:

algae; productivity; raceway ponds; miniponds; biofuel; bioproducts

1. Summary

The project that generated these data, Optimizing Selection Pressures and Pest Management to Maximize Cultivation Yield (OSPREY, Award #DE-EE08902 to the New Mexico Consortium), was proposed in response to AOI 1, Cultivation Intensification Processes for Algae, within the FY19 Bioenergy Technologies Office Multi-Topic Funding Opportunity Announcement (FOA Number: DE-FOA-0002029). This work was designed to address a critical industry need to improve the annualized productivity, stability, and quality of algal production strains for biofuels and bioproducts. Our overall project goals were to generate process innovations rooted in established outdoor systems for strain selection, improvement, maintenance, and cultivation as well as pest detection and tracking. Our project’s technical components were built on a single foundation: the year-round cultivation of a Nannochloropsis strain in three outdoor systems. We envisioned that the unique environmental selection pressures of each outdoor system would allow us to develop robust cultivars and would facilitate process innovations with broad geographic applicability. We have previously published manuscripts that use these data, including one that addresses the role of the local climate and weather on productivity across sites [1]. Still, there may be opportunities for further analyses of this dataset. As there are few publicly available datasets on algae cultivation—the ATP3 data being the main exception [2]—we aim to make these data available to potential end users. The dataset consists of environmental and biological parameters associated with the outdoor cultivation campaigns at each of the field sites. Additional releases of 16S rRNA amplicon sequencing and shotgun sequencing datasets are planned.

2. Data Description

Observations are arranged in a single CSV file with one unique observation per row. Columns are organized into the following categories: sample information (columns 1–7), environmental data (columns 8–21), pond management data (columns 22–32), and biological data (columns 33–42). Additional notes are found in column 43.

2.1. Sample Information

“Pond ID” (categorical) lists a site-specific identifier for each pond. Identifiers were devised by local operators, so there are different naming conventions across sites. Cyanotech used existing pond numbers as identifiers, whereas NMSU and UCSD combined both the pond start date and pond number as the identifier.
“Replicate” (numerical) indicates the pond replicate number. Typically, three ponds were maintained at each of the sites at any given point. However, there were instances when different ponds came online for additional experimental work. As such, pond replicate can vary from one to six.
“Field Site” (categorical) refers to the site of the ponds: Cyanotech, NMSU, or UCSD.
“Date” (numerical, continuous) is the date of the observation and sample collection. It is formatted as MM/DD/YY.
“Sampling Time” (numerical, continuous) is the sampling time of the observation and sample collection. It is formatted as HH:MM AM/PM.
“Date & Time” (numerical, continuous) is concatenated from the previous two columns.
“Sampler” (categorical) lists the initials of the person or people collecting the sample and taking measurements.

2.2. Environmental Data

“PLC pH” and “PLC Temperature (°C)” (numerical, continuous) are the pH and temperature (in °C), read from the Programmable Logic Computer or Apex Controller within each pond.
“HH pH”, “HH Temperature (°C)”, “HH Salinity (ppt)”, and “HH TDS (g/L)” (numerical, continuous) are the pH, temperature (°C), salinity (ppt), and total dissolved solids (g/L), read from handheld meters at each site.
“Refractometer Salinity (ppt)” (numerical, continuous) is the salinity (ppt), read from a refractometer.
“Test Strip NO₃ (ppm)”, “Test Strip NO₂ (ppm)”, and “Test Strip PO₄ (ppm)” (numerical, discrete) are nitrate, nitrite, and phosphate concentrations measured with Hach nutrient test strips. NO₃ was measured on a scale from 0 to 50 ppm (increments of 0, 1, 2, 5, 10, 20, and 50 ppm); NO₂ was measured on a scale from 0 to 3 ppm (increments of 0, 0.15, 0.3, 1.0, 1.5, and 3.0 ppm); and PO₄ was measured on a scale from 0 to 50 ppm (increments of 0, 5, 15, 30, and 50 ppm).
“TKN (mg/L)”, “NH₃-N (mg/L)”, and “NO₃-N (mg/L)” (numerical, continuous) are the Total Kjeldahl Nitrogen, Ammonia Nitrogen, and Nitrate Nitrogen (mg/L) measured on samples pre-filtered through 0.2 µm polycarbonate membrane filters. Analyses were conducted within the NMSU College of Agriculture, Consumer & Environmental Sciences (Plant & Environmental Sciences Department).
“Min Air Temperature (°C)” is the minimum daily temperature in degrees C. All temperature and solar radiation data were acquired on 11/2020, 9/2020, and 10/2020 for Cyanotech, NMSU, and UCSD, respectively.
“Max Air Temperature (°C)” is the maximum daily temperature in degrees C.
“Mean Air Temperature (°C)” is the average (mean) daily temperature in degrees C.
“Sum Solar Radiation (W/m²)” is the sum of solar radiation for each site.
“Weather” (text) is a description of the weather, with the following abbreviations: S is for Sunny, R is for Rainy, C is for Cloudy, PC is for Partly Cloudy, W is for Windy, D is for a Dust Event, and F is for Freeze.

2.3. Pond Management Data

“Pre-Top Off Depth (mm)”, “Post-Top Off Depth (mm)”, “Pre-Top Off Volume (L)”, and “Post-Top Off Volume (L)” (numerical, continuous) are pond depths (mm) and volumes (L) before and after adding water to ponds to account for losses from evaporation.
“Harvest Volume (L)” (numerical, continuous) is the volume removed from a pond to simulate a harvest.
“NaCl Added (g)”, “N Added (ppm)”, “PO₄ Added (ppm)”, “Trace Metal Stock Added (mL)”, and “Fe Stock Added (mL)” (numerical, continuous) are the amounts of salt, nitrogen, phosphate, and iron added to a pond to either bring salinity up to the target range or replenish nutrients.
“Chemical Dose (ppm)” (numerical, continuous) is the amount of sodium hypochlorite (ppm) added to a pond to treat pests.

2.4. Biological Data

“OD₇₅₀” (numerical, continuous) is the optical density at 750 nm of pond samples.
“Chlorophyll Fluorescence” (numerical, continuous) is the chlorophyl fluorescence, read using excitation and emission wavelengths of 430 and 685.
“Fo”, “Fm”, and “Fv/Fm” (numerical, continuous) are the minimum fluorescence, maximum fluorescence, and photosynthetic yield, measured with a miniPAM Fluorometer. An AquaPen was used in lieu of the miniPAM during instances of instrument issues.
“DW (g/L)” and “AFDW (g/L)” (continuous, numerical) are the dry weight and ash-free dry weight (in g/L) of filtered pond samples on harvest days. The DW and AFDW were always measured on harvest days and were sometimes measured at additional points.
“% Ash” (continuous, numerical) is the percent ash of pond samples, derived from DW and AFDW values.
“Productivity (g m⁻² d⁻¹)” (continuous, numerical) is the AFDW-based productivity of cultures.
“Scope Observations” (text) describes semi-quantitative observations made on pond samples. Scope observations were standardized across observers within, but not across, field sites.

Extra information, capturing the troubleshooting of ponds, weather conditions, reasons for outliers in the data, absence of data, or any other observation worth noting, is listed in the final column under “Notes”.

3. Methods

We cultivated a strain of Nannochloropsis [3] in triplicate outdoor ponds (Figure 1, Table 1) at each of the three field sites, Cyanotech Corporation in Kailua-Kona, HI (19.734593, −156.053035); New Mexico State University (NMSU) in Las Cruces, NM (32.279262, −106.771913); and the University of California San Diego (UCSD) in San Diego, CA (32.885575, −117.230162), between 2020 and 2023. Cultures were grown in a minimal cultivation medium [4] using locally sourced water, supplemented with nitrogen, phosphorus, trace metals, and iron. Nitrogen was supplied using a commercial fertilizer with a mix of nitrogen sources, whereas phosphorus was supplied as 10-34-0 (NH₄)3PO₄ (Ammonium Polyphosphate). Trace metals, CoSO₄, MnSo₄, and Na₂MoO₄, and iron as FeSO₄ were acquired from scientific vendors (e.g., VWR, Radnor, PA, USA and Fischer Scientific, Hampton, NH, USA) and were supplied from stock solutions. The pH was maintained at 7.4 ± 0.2, with deviations outside this range being due to CO₂ solenoid malfunctions, the CO₂ tanks emptying, or site power issues. A chemical agent was used as a crop-protection strategy at each site. The frequency and amount of doses varied across the sites due to different pest pressures. The ponds employed programmable logic controllers or Apex Controllers to maintain the CO₂ and to record environmental data. On sample-collection days, measurements were read both off the controllers as well as with separate instruments. Measurements of the temperature (°C), salinity (ppt), and depth (mm) were taken daily, Monday through Friday. A YSI 1030 was used at NMSU and a Cole-Parmer PC100 pH/Conductivity Meter at UCSD and Cyanotech. Salinity was recorded with a handheld probe at NMSU and UCSD and a refractometer at Cyanotech.

The site-wide metrics of biomasses included an optical density of 750 nm and an ash-free dry weight. Additional metrics collected at NMSU were a chlorophyll fluorescence with an excitation wavelength of 430 nm and an emission wavelength of 685 nm. Additional metrics collected at Cyanotech and NMSU were metrics of photosynthetic health (Fo, Fm, and Fv/Fm). Optical density (and chlorophyll fluorescence at NMSU) was measured using a microtiter plate reader (SpectraMax M2, Molecular Devices, San Jose, CA, USA) at NMSU; a cuvette modular fluorometer/spectrophotometer (Turner Trilogy, Turner Designs, San Jose, CA USA) at UCSD; and a cuvette UV/Vis spectrophotometer (UV-1600PC, VWR, Radnor, PA, USA) at Cyanotech. Two-fold (1:1) and twenty-fold (1:20) ratios were used for optical density and chlorophyll measurements, respectively, to ensure the linear range of the analytical method. The ash-free dry weight was measured pre- and post-harvest, following standard techniques [5], with an additional step of rinsing the filters with deionized water to remove salts. The AFDW-based productivity (aerial productivity in g m² d⁻¹) was calculated as follows:

\frac{(A F D W p r e - A F D W p o s t) * V}{A * t}

where AFDW_pre and AFDW_post are the ash-free dry weights at the end and at the beginning of a growth cycle (g L⁻¹) respectively; V is the pond volume (L); A is the pond area (m²); and t is the duration of the growth cycle (days). Fo, Fm, and Fv/Fm were measured using Mini-PAM (Walz Version 2.00) in Las Cruces, NM and in Kailua-Kona, HI.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/data9110126/s1.

Author Contributions

Conceptualization—A.A.C. and S.R.S.; methodology, A.A.C., S.R.S., J.O.N. and C.J.O.; investigation—M.S.A., T.C., I.E.-S., J.G., S.G., A.J., H.M. and AR; resources—A.A.C., J.O.N., C.J.O. and J.B.S.; data curation—M.S.A., T.C., I.E.-S., J.G., S.G., A.J., H.M. and A.R.; writing initial draft—A.A.C., H.M., A.J. and I.E.-S.; writing, review and editing—A.A.C., M.S.A., I.E.-S., A.J., H.M. and J.O.N., visualization—I.E.-S.; supervision—C.J.O., A.A.C. and J.B.S.; project administration—A.A.C. and S.R.S.; funding acquisition—A.A.C. and S.R.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE), under the FY19 Bioenergy Technologies Office Multi-Topic Funding Opportunity Announcement award number DE-EE0008902.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are being made available as a Supplementary file.

Acknowledgments

We acknowledge the following individuals for supporting the maintenance of the pond, sample collection, and data logging: Keeley Lanigan, Pablo Corcoran, Ugbad Farah, Madison Toyama, Louis Choy, Rachel Bedi, Nathan Fang, Ashley Miller, Brynn Werner, Joaquin Felix Rosell, Xinyu Lin, Evan Zhou, Erin Go, and Chaewon Ham.

Conflicts of Interest

Marcela Saracco Alvarez, Julia Gerber and Charles J. O’Kelly were employed by the company Cyanotech Corporation. Jakob O. Nalley was employed by the company Qualitas Health. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

Echenique-Subiabre, I.; Greene, J.M.; Ryan, A.; Martinez, H.; Balleza, M.; Gerber, J.; Jebali, A.; Getto, S.; O’Kelly, C.J.; Mandal, S.; et al. Site-specific factors override local climatic conditions in determining microalgae productivity in open raceway ponds. Algal Res. 2023, 74, 103235. [Google Scholar] [CrossRef]
McGowen, J.; Knoshaug, E.P.; Laurens, L.M.L.; Dempster, T.A.; Pienkos, P.T.; Wolfrum, E.; Harmon, V.L. The Algae Testbed Public-Private Partnership (ATP3) framework; establishment of a national network of testbed sites to support sustainable algae production. Algal Res. 2017, 25, 168–177. [Google Scholar] [CrossRef]
Sanchez, M.R.; Biondi, T.C.; Kunde, Y.A.; Eng, W.; Nalley, J.O.; Ganuza, E.; Hovde, B.T.; Corcoran, A.A.; Starkenburg, S.R. The Genome Sequence of an Algal Strain of Nannochloropsis QH25. Microbiol. Resour. Announc. 2022, 11, e0092122. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. Outdoor cultivation ponds at Cyanotech (a), NMSU (b), and UCSD (c).

Table 1. Characteristics of the cultivation ponds used at each of the field sites.

	Cyanotech	NMSU	UCSD
Material	Plastic	Fiberglass	Plexiglas (painted white)
Length	1.8 m	3.0 m	1.3 m
Area (m²)	1.195	1.987	0.7961
Volume (L)	200.6	260	150
Depth (cm)	17	20	19
Paddle wheels	Horizontal	Horizontal	Vertical
Rotation (cm/s)	30	15	15
Start date	12 November 2020	1 September 2020	17 October 2020

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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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MDPI and ACS Style

Corcoran, A.A.; Alvarez, M.S.; Cornell, T.; Echenique-Subiabre, I.; Gerber, J.; Getto, S.; Jebali, A.; Martinez, H.; Nalley, J.O.; O’Kelly, C.J.; et al. Long-Term Outdoor Cultivation of Nannochloropsis in California, Hawaii, and New Mexico. Data 2024, 9, 126. https://doi.org/10.3390/data9110126

AMA Style

Corcoran AA, Alvarez MS, Cornell T, Echenique-Subiabre I, Gerber J, Getto S, Jebali A, Martinez H, Nalley JO, O’Kelly CJ, et al. Long-Term Outdoor Cultivation of Nannochloropsis in California, Hawaii, and New Mexico. Data. 2024; 9(11):126. https://doi.org/10.3390/data9110126

Chicago/Turabian Style

Corcoran, Alina A., Marcela Saracco Alvarez, Taryn Cornell, Isidora Echenique-Subiabre, Julia Gerber, Stephanie Getto, Ahlem Jebali, Heather Martinez, Jakob O. Nalley, Charles J. O’Kelly, and et al. 2024. "Long-Term Outdoor Cultivation of Nannochloropsis in California, Hawaii, and New Mexico" Data 9, no. 11: 126. https://doi.org/10.3390/data9110126

APA Style

Corcoran, A. A., Alvarez, M. S., Cornell, T., Echenique-Subiabre, I., Gerber, J., Getto, S., Jebali, A., Martinez, H., Nalley, J. O., O’Kelly, C. J., Ryan, A., Shurin, J. B., & Starkenburg, S. R. (2024). Long-Term Outdoor Cultivation of Nannochloropsis in California, Hawaii, and New Mexico. Data, 9(11), 126. https://doi.org/10.3390/data9110126

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