Progress 08/01/19 to 12/31/20

Outputs
Target Audience:Since the start of the grant, we have had a number of personal communications with Florida hatcheries and farm operators about their interest in increased automation of algal cultivation for production of live algae as larvae feed. All contacted see the value in having access to high quality algae, but yet have been unable to dedicate the resources required to develop this as algae feed is not their core competency. The current status quo is frozen algae paste which offers consistent and suitable results. However, with frozen algae the survival rate of larvae is still poor and preliminary experiments show that a fresh algae provided by our system increases survival rate. Developing a technology to produce live algae at the cost of frozen paste due to lower operating costs has been well received by all as a value proposition. If this technology has the potential to be positioned on site at the hatcheries is even better. All stakeholders contacted would prefer to have a fully automated cultivation solution available that includes media production and minimizes labor cost. Though this need is not fully addressed with the SBIR Phase I low cost biomass sensor we are developing, the sensor is seen by all as a significant improvement to the current methods. The developed sensor used in conjunction with our high productivity reactor appears to be a desirable addition to the stakeholders contacted. Changes/Problems:Once the wavelength and orientation of the light and sensor combinations was established using iterative testing, two major hurdles were encountered. The first was that the sensitivity of the sensor was too high for the ambient light levels and thus required the data collection to be conducted at hight. The next issue was biofouling which was expected but the level of growth was not known. This was solved using commercially available hydrophobic surface treatments. What opportunities for training and professional development has the project provided?In order to operate the low cost biomass probe, a correlation between the optical data (voltage from light sensors) and the target metric (optical density at specific wavelengths and biomass density) had to be established. The correlation is species dependent and needs to be established in the lab before starting any type of algae based aquaculture farm. Analyzing the samples to create the correlation can be readily performed by someone trained in common analytical chemistry techniques. In order to accomplish this, the technician at Dr. Philippidis' laboratory received a refresher training led by Dr. Meiser (co-PI of Culture Fuels). ). After becoming familiar with the operation of the biomass probe in situ, the technician was able to train one other person in its operation to assist in data collection. In the future, while automation of bioreactor operation will lower the amount of required manual labor, it will increase the technical requirements for such operation. The operator will still require training in the various aspects of reactor operation to include: setup and assembly, fluid control, cooling system maintenance, fluid management, and extensive troubleshooting for multiple systems. We expect this can come from both on-the-job training as well as some specialized technical education. How have the results been disseminated to communities of interest?Dissemintation to Florida hatcheries was done by one of Culture Fuels' management Mr. Julian Fiorentino due to his work with the University of Miami's Rosenstiel Marine School. He personally knows several of the owners of Florida hatcheries and he described our success and confirmed their interest in being a location for the Phase 2 commercialization deployment. Dissemination has also targeted students (workforce development), scientists, and industry. The results of the work have been shared by Dr. George Philippidis with the scientific community at the University of South Florida (USF) and in class as part of the module on algae technologies in his graduate course "Renewable Transportation Fuels" (IDS 6207) at USF's Patel College of Global Sustainability. He has also held discussions on the subject of automation in algae cultivation with (1) algae colleagues during a visit to the Arizona Center for Algae Technology and Innovation at Arizona State University and (2) other companies in the algae industry (Algafeed of Jupiter, FL), who are keenly interested in automation for cost-reduction purposes. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? IMPACT: There is compelling value to feeding live algae in fish hatcheries as the current survival rate of larvae fed frozen paste is relatively low resulting in higher production costs and hence selling prices for the consumers. However, the complexity and costs of existing photobioreactors and the logistical costs of shipping live material over distances are barriers to the widespread deployment of live algae as feed. Culture BioSystems has successfully grown and sold live concentrated Nannochloropsis to Florida hatcheries using an innovative low-cost photobioreactor. Further reduction in production cost requires automating functions in the bioreactor operation, such as culture harvest and refill. The objective of this Phase I grant was to develop a low-cost, real time in-situ biomass probe, to enable the automatic harvest of industrial algae photobioreactors to grow feed for aquaculture. This objective was successfully accomplished. We designed, tested, revised, refined and manufactured a probe combining laser diode and ambient light sensors to determine the algae biomass density based on the sensor voltage that is inversely proportional to the density of the culture. A low cost data logger was developed to further automate reactor operation by recording data from the sensor, thus allowing for downstream processing and subsequent process logic control. We anticipate that automation of algae concentration measurements will significantly reduce operating (labor) costs, eliminate human error, and optimize the harvest/refill cycles during algae cultivation, hence reducing the cost of produced algae for hatcheries and fish farms. The development of an automated and modular photobioreactor that can produce low-cost algae benefits hatchery farmers by granting them access to fresh feed of higher nutritional value at a lower cost than they pay today. This increases the survival rate of harder to grow fish species, like snapper, grouper and barramundi. By providing these fish with higher quality live algae the aquaculture industry is better able to provide protein to a growing US and world population. ACCOMPLISHMENTS Goal 1: Develop a light sensor Major activities completed / experiments conducted: Objective was to create a short list of light sensor options that worked in the lab Variables were: type of sensor (optical, chemical, other), light wavelength (red or green light), distance between light emitter and sensor, angle between light emitter and sensor, accuracy with increasing algae density. We tested 3 angles between the light emitter and sensor (0 degree, 90 degrees, 180 degrees) for both red and green light using a glass algae container. We measured the output voltage of the sensor at a range of algae densities. 2) Data collected: Graphs of algae density versus output voltage for 6 different combinations of light angle and color of light. The sensor's voltage was correlated to the culture's optical density (OD). 3) Summary statistics and discussion of results: All the graphs produced curves that were steep (most sensitive) at lower algae density and flat (less sensitive) at highest algae density. Hence, we assessed the aforementioned variables to arrive at curves that had the highest sensitivity at highest density, since the primary purpose is to know when the algae is mature enough to harvest. 4) Key outcomes or other accomplishments realized: The most promising system consisted of red light at a 90 degree angle to the light emitter. That is, the light beam aimed downwards, whereas the light sensor was positioned to the side of the light beam picking up the light that was being scattered by the algae culture. This combination had the highest sensitivity at high algae density. Goal 2: Real world outdoor test Major activities completed / experiments conducted: Objective: Construct a sensor that can operate in outdoor conditions and then demonstrate. Worked with a local small business manufacturer (Pi Designs) to optimize the design and manufacture our lab-scale sensor. There was close interaction between the manufacturer and our technical team. We purchased the components and Pi Designs created a molded sensor. We successfully tested this sensor in an indoor lab unit. Installed the sensor in the outdoor bioreactor. After a number of runs we concluded that we needed additional sensitivity at the lower algae density as well to accurately monitor algae growth, so we added a second light sensor at a different angle calibrated for lower density. Currently running outdoors cultivation with the new system (dual sensor). Data collected: Multiple voltage vs. OD graphs using the original single sensor in the laboratory and then outdoors. Multiple voltage vs. OD graphs using the final dual sensor in the laboratory and then outdoors. Summary statistics and discussion of results: Initial results show that the dual sensor outdoors is working well and reproducibly. The graph follows the same curve as that established indoors. By monitoring the voltage of the sensor, through the established "algae concentration-voltage" curve, we can derive the algae density and therefore initiate harvesting at the appropriate density. Key outcomes or other accomplishments realized: Realized that although the sensor is inside the enclosed manifold of the bioreactor, there is still some background ambient light reaching the sensor and interfering with the readings. After trying several ways to shield from the light, we realized that the simplest solution is to take the readings at night! This methodology seems to work well. Tested the dual sensor with this methodology, and achieved the same growth pattern that we achieve with traditional manual cultivation methods. This is a significant technical development that will help automate algae cultivation and hence reduce operating costs, thus benefitting the entire aquaculture and agricultural supply chain by allowing more reliable and lower cost production of live algae as a feedstock.

Publications

Progress 08/01/19 to 07/31/20

Outputs
Target Audience:Since the start of the grant we have had a number of personal communications with Florida hatcheries and farm operators about their interest in increased automation of algal cultivation. All contacted see the value in having access to high quality algae, but yet have been unable to dedicate the resources required to develop this as algae feed is not their focus area. The current status quo is frozen algae paste which offers consistent and suitable results. However, with frozen algae the survival rate of larvae is still poor and first experiments show that a fresh algae provided by our system will increase survival rate. Developing a technology to produce live algae at the cost of frozen paste due to lower operating costs has been well received by all. If this technology has the potential to be positioned on site is even better. All stakeholders contacted would prefer to have a fully automated cultivation solution available that includes media production. Though this need is not fully addressed with the SBIR Phase 1 low cost biomass sensor we are developing, the sensor is seen by all as a significant improvement to the current methods. The developed sensor used in conjunction with our high productivity reactor is a desirable addition to the stakeholders contacted. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?In order to operate the low cost biomass probe, a correlation between the optical data (voltage from light sensors) and the target metric (optical density at specific wavelengths and biomass density) had to be established. The correlation is species dependent and needs to be established in the lab before starting any type of algae based aquaculture farm. Analyzing the samples to create the correlation can be readily performed by someone trained in common analytical chemistry techniques. In order to accomplish this, the technician at Dr. Philippidis' laboratory received a refresher training led by Dr. Meiser (co-PI of Culture Fuels). ). After becoming familiar with the operation of the biomass probe in situ, the technician was able to train one other person in its operation to assist in data. In the future, while automation of reactor operation will lower the amount of required manual labor, it will increase the technical requirements for such operation. The operator will still require training in the various aspects of reactor operation to include: setup and assembly, fluid control, cooling system maintenance, fluid management, and extensive troubleshooting for multiple systems. We expect this can come from both on-the-job training as well as some specialized technical education. How have the results been disseminated to communities of interest?Dissemination has targeted students (workforce development), scientists, and industry. The results of the work have been shared by Dr. George Philippidis with the scientific community at the University of South Florida (USF) and in class as part of the module on algae technologies in his graduate course "Renewable Transportation Fuels" (IDS 6207) at USF's Patel College of Global Sustainability. He has also held discussion on the subject of automation in algae cultivation with (1) algae colleagues during a visit to the Arizona Center for Algae Technology and Innovation at Arizona State University and (2) other companies in the algae industry (Algafeed of Jupiter, FL), who are keenly interested in automation for cost-reduction purposes. What do you plan to do during the next reporting period to accomplish the goals?In the first reporting period a new sensor was developed to automatically measure the biomass density in algae cultures in a lab setting. In the next reporting period, the sensor will be tested outdoors in photobioreactors under real life conditions. The dual sensor will be installed in a semi-commercial bioreactor already developed by Culture BioSystems and installed at the University of South Florida (Tampa, FL). The algae bioreactor has a capacity of 110 liters and a productivity of 15-20 g dry mass/m2/day. Two experiments will be performed: After inoculation of the bioreactor, growth will be regularly monitored to show that the new sensor has the capability to accurately measure algae biomass density/growth over the full range of biomass densities (in our case from ca. 0.1 g/l up to 4 g/l). The inline (real time) readings of the sensor will be compared to those of samples analyzed offline. After recording the full growth curve, the reactor will be operated for a few weeks under outdoor production conditions. Regular sensor readings will be compared with traditional measurements of biomass densities. In this experiment we will show that new sensor will deliver stable and reproducible data readings under production conditions.

Impacts
What was accomplished under these goals? IMPACT: There is compelling value to feeding live algae in fish hatcheries as the current survival rate of larvae fed frozen paste is relatively low resulting in higher costs for consumers. However the complexity and costs of existing photo-bioreactors and the logistical costs of shipping live material over distances are barriers to the widespread deployment of live algae as feed. Culture BioSystems has successfully grown and sold live concentrated Nannochloropsis to Florida hatcheries using an innovative low cost photobioreactor. Further reduction in production cost requires automating functions in the bio-reactor operation. With this goal in mind, thus far as part of this SBIR Phase I we have successfully developed and tested in the laboratory a light sensor which measures in real time (in line) the density of the algae culture inside the reactor. We will now test this sensor in real-world, outdoor conditions and compare to the traditional manual methods of measuring algae density (off line). We anticipate that automation of algae concentration measurements will significantly reduce operating (labor) costs, eliminate human error, and optimize the harvest/refill cycles during algae cultivation, hence reducing the cost of produced algae for hatcheries and fish farms. The development of an automated and modular photo-bioreactor which can produce low cost algae will provide benefit to hatchery farmers who will have access to feed of higher nutritional value at a lower cost than they pay today. This will increase the survival rate of harder to grow fish species like snapper, grouper and barramundi. By providing these fish with higher quality, live algae the aquaculture industry will be better able to provide protein to a growing world population. ACCOMPLISHMENTS Goal 1: Develop a light sensor Major activities completed / experiments conducted: Objective was to create a short list of light sensor options that worked in the lab Variables were: type of sensor (optical, chemical, other), light wavelength (red or green light), distance between light emitter and sensor, angle between light emitter and sensor, accuracy with increasing algae density. We tested 3 angles between the light emitter and sensor (0 degree, 90 degrees, 180 degrees) for both red and green light using a glass algae container. We measured the output voltage of the sensor at different algae densities. 2) Data collected: Graphs of algae density versus output voltage for 6 different combination of light angle and color of lights 3) Summary statistics and discussion of results: All the graphs were curves that were steepest (most sensitive) at lower algae density and shallower (less sensitive) at highest algae density. We sought curves which had the highest sensitivity at highest density, since the primary purpose is to know when the algae is ready to harvest. 4) Key outcomes or other accomplishments realized: The most promising system was red light at a 90 degree angle to the light emitter. That is, the light beam aimed downwards, whereas the light sensor was positioned to the side of the light beam picking up the light that has been scattered by the algae culture. This combination had the highest sensitivity at high algae density. Goal 2: Real world outdoor test Major activities completed / experiments conducted: Objective: Construct a sensor that can operate in outdoor conditions and then demonstrate. Worked with a local manufacturer (Pi Designs) to develop a design and manufacture our lab-scale sensor. There was close interaction between the manufacturer and our technical team. We purchased the components and Pi Designs created a molded sensor. We tested this sensor in an indoor lab unit. Installed the sensor in the outdoor bioreactor. After a number of runs we concluded that we needed additional sensitivity at the lower algae density as well, so we added a second light sensor at a different angle calibrated for lower density. Currently running outdoors cultivation with the new system (dual sensor). Data collected: Multiple graphs using the original single sensor in the laboratory and then outdoors. Multiple graphs using the final dual sensor in the laboratory and then outdoors. Summary statistics and discussion of results: Initial results show that the dual sensor outdoors is working well and reproducibly. The graph follows the same curve as that established indoors. By monitoring the voltage of the sensor, through the established "algae concentration-voltage" curve, we can derive the algae density and therefore initiate harvesting at the appropriate density. Key outcomes or other accomplishments realized: Realized that although the sensor is inside the enclosed manifold of the bioreactor, there is still some background ambient light which interferes with the readings. After trying several ways to shield from the light, we realized that the simplest solution is to take the readings at night! This methodology seems to work well. Continuing to test the dual sensor with this methodology, but we have already accomplished our technical goal of developing an in-situ sensor, whose voltage output is correlated to algal density. This is a significant technical development that will automate algae cultivation and hence reduce operating costs thus benefitting the entire aquaculture and agricultural supply chain by allowing more reliable and lower cost production of live algae as a feedstock.

Publications

Progress 08/01/19 to 06/30/20

Outputs
Target Audience:Since the start of the grant we have had a number of personal communications with Florida hatcheries and farm operators about their interest in increased automation of algal cultivation. All contacted see the value in having access to high quality algae, but yet have been unable to dedicate the resources required to develop this as algae feed is not their focus area. The current status quo is frozen algae paste which offers consistent and suitable results. However, with frozen algae the survival rate of larvae is still poor and first experiments show that a fresh algae provided by our system will increase survival rate. Developing a technology to produce live algae at the cost of frozen paste due to lower operating costs has been well received by all. If this technology has the potential to be positioned on site is even better. All stakeholders contacted would prefer to have a fully automated cultivation solution available that includes media production. Though this need is not fully addressed with the SBIR Phase 1 low cost biomass sensor we are developing, the sensor is seen by all as a significant improvement to the current methods. The developed sensor used in conjunction with our high productivity reactor is a desirable addition to the stakeholders contacted. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?In order to operate the low cost biomass probe, a correlation between the optical data (voltage from light sensors) and the target metric (optical density at specific wavelengths and biomass density) had to be established. The correlation is species dependent and needs to be established in the lab before starting any type of algae based aquaculture farm. Analyzing the samples to create the correlation can be readily performed by someone trained in common analytical chemistry techniques. In order to accomplish this, the technician at Dr. Philippidis' laboratory received a refresher training led by Dr. Meiser (co-PI of Culture Fuels). ). After becoming familiar with the operation of the biomass probe in situ, the technician was able to train one other person in its operation to assist in data. In the future, while automation of reactor operation will lower the amount of required manual labor, it will increase the technical requirements for such operation. The operator will still require training in the various aspects of reactor operation to include: setup and assembly, fluid control, cooling system maintenance, fluid management, and extensive troubleshooting for multiple systems. We expect this can come from both on-the-job training as well as some specialized technical education. How have the results been disseminated to communities of interest?Dissemination has targeted students (workforce development), scientists, and industry. The results of the work have been shared by Dr. George Philippidis with the scientific community at the University of South Florida (USF) and in class as part of the module on algae technologies in his graduate course "Renewable Transportation Fuels" (IDS 6207) at USF's Patel College of Global Sustainability. He has also held discussion on the subject of automation in algae cultivation with (1) algae colleagues during a visit to the Arizona Center for Algae Technology and Innovation at Arizona State University and (2) other companies in the algae industry (Algafeed of Jupiter, FL), who are keenly interested in automation for cost-reduction purposes. What do you plan to do during the next reporting period to accomplish the goals?In the first reporting period a new sensor was developed to automatically measure the biomass density in algae cultures in a lab setting. In the next reporting period, the sensor will be tested outdoors in photobioreactors under real life conditions. The dual sensor will be installed in a semi-commercial bioreactor already developed by Culture BioSystems and installed at the University of South Florida (Tampa, FL). The algae bioreactor has a capacity of 110 liters and a productivity of 15-20 g dry mass/m2/day. Two experiments will be performed: After inoculation of the bioreactor, growth will be regularly monitored to show that the new sensor has the capability to accurately measure algae biomass density/growth over the full range of biomass densities (in our case from ca. 0.1 g/l up to 4 g/l). The inline (real time) readings of the sensor will be compared to those of samples analyzed offline. After recording the full growth curve, the reactor will be operated for a few weeks under outdoor production conditions. Regular sensor readings will be compared with traditional measurements of biomass densities. In this experiment we will show that new sensor will deliver stable and reproducible data readings under production conditions.

Impacts
What was accomplished under these goals? IMPACT: There is compelling value to feeding live algae in fish hatcheries as the current survival rate of larvae fed frozen paste is relatively low resulting in higher costs for consumers. However the complexity and costs of existing photo-bioreactors and the logistical costs of shipping live material over distances are barriers to the widespread deployment of live algae as feed. Culture BioSystems has successfully grown and sold live concentrated Nannochloropsis to Florida hatcheries using an innovative low cost photobioreactor. Further reduction in production cost requires automating functions in the bio-reactor operation. With this goal in mind, thus far as part of this SBIR Phase I we have successfully developed and tested in the laboratory a light sensor which measures in real time (in line) the density of the algae culture inside the reactor. We will now test this sensor in real-world, outdoor conditions and compare to the traditional manual methods of measuring algae density (off line). We anticipate that automation of algae concentration measurements will significantly reduce operating (labor) costs, eliminate human error, and optimize the harvest/refill cycles during algae cultivation, hence reducing the cost of produced algae for hatcheries and fish farms. The development of an automated and modular photo-bioreactor which can produce low cost algae will provide benefit to hatchery farmers who will have access to feed of higher nutritional value at a lower cost than they pay today. This will increase the survival rate of harder to grow fish species like snapper, grouper and barramundi. By providing these fish with higher quality, live algae the aquaculture industry will be better able to provide protein to a growing world population. ACCOMPLISHMENTS Goal 1: Develop a light sensor Major activities completed / experiments conducted: Objective was to create a short list of light sensor options that worked in the lab Variables were: type of sensor (optical, chemical, other), light wavelength (red or green light), distance between light emitter and sensor, angle between light emitter and sensor, accuracy with increasing algae density. We tested 3 angles between the light emitter and sensor (0 degree, 90 degrees, 180 degrees) for both red and green light using a glass algae container. We measured the output voltage of the sensor at different algae densities. 2) Data collected: Graphs of algae density versus output voltage for 6 different combination of light angle and color of lights 3) Summary statistics and discussion of results: All the graphs were curves that were steepest (most sensitive) at lower algae density and shallower (less sensitive) at highest algae density. We sought curves which had the highest sensitivity at highest density, since the primary purpose is to know when the algae is ready to harvest. 4) Key outcomes or other accomplishments realized: The most promising system was red light at a 90 degree angle to the light emitter. That is, the light beam aimed downwards, whereas the light sensor was positioned to the side of the light beam picking up the light that has been scattered by the algae culture. This combination had the highest sensitivity at high algae density. Goal 2: Real world outdoor test Major activities completed / experiments conducted: Objective: Construct a sensor that can operate in outdoor conditions and then demonstrate. Worked with a local manufacturer (Pi Designs) to develop a design and manufacture our lab-scale sensor. There was close interaction between the manufacturer and our technical team. We purchased the components and Pi Designs created a molded sensor. We tested this sensor in an indoor lab unit. Installed the sensor in the outdoor bioreactor. After a number of runs we concluded that we needed additional sensitivity at the lower algae density as well, so we added a second light sensor at a different angle calibrated for lower density. Currently running outdoors cultivation with the new system (dual sensor). Data collected: Multiple graphs using the original single sensor in the laboratory and then outdoors. Multiple graphs using the final dual sensor in the laboratory and then outdoors. Summary statistics and discussion of results: Initial results show that the dual sensor outdoors is working well and reproducibly. The graph follows the same curve as that established indoors. By monitoring the voltage of the sensor, through the established "algae concentration-voltage" curve, we can derive the algae density and therefore initiate harvesting at the appropriate density. Key outcomes or other accomplishments realized: Realized that although the sensor is inside the enclosed manifold of the bioreactor, there is still some background ambient light which interferes with the readings. After trying several ways to shield from the light, we realized that the simplest solution is to take the readings at night! This methodology seems to work well. Continuing to test the dual sensor with this methodology, but we have already accomplished our technical goal of developing an in-situ sensor, whose voltage output is correlated to algal density. This is a significant technical development that will automate algae cultivation and hence reduce operating costs thus benefitting the entire aquaculture and agricultural supply chain by allowing more reliable and lower cost production of live algae as a feedstock.

Publications

Progress 08/01/19 to 03/31/20

Outputs
Target Audience:Since the start of the grant we have had a number of personal communications with Florida hatcheries and farm operators about their interest in increased automation of algal cultivation. All contacted see the value in having access to high quality algae, but yet have been unable to dedicate the resources required to develop this as algae feed is not their focus area. The current status quo is frozen algae paste which offers consistent and suitable results. However, with frozen algae the survival rate of larvae is still poor and first experiments show that a fresh algae provided by our system will increase survival rate. Developing a technology to produce live algae at the cost of frozen paste due to lower operating costs has been well received by all. If this technology has the potential to be positioned on site is even better. All stakeholders contacted would prefer to have a fully automated cultivation solution available that includes media production. Though this need is not fully addressed with the SBIR Phase 1 low cost biomass sensor we are developing, the sensor is seen by all as a significant improvement to the current methods. The developed sensor used in conjunction with our high productivity reactor is a desirable addition to the stakeholders contacted. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?In order to operate the low cost biomass probe, a correlation between the optical data (voltage from light sensors) and the target metric (optical density at specific wavelengths and biomass density) had to be established. The correlation is species dependent and needs to be established in the lab before starting any type of algae based aquaculture farm. Analyzing the samples to create the correlation can be readily performed by someone trained in common analytical chemistry techniques. In order to accomplish this, the technician at Dr. Philippidis' laboratory received a refresher training led by Dr. Meiser (co-PI of Culture Fuels). ). After becoming familiar with the operation of the biomass probe in situ, the technician was able to train one other person in its operation to assist in data. In the future, while automation of reactor operation will lower the amount of required manual labor, it will increase the technical requirements for such operation. The operator will still require training in the various aspects of reactor operation to include: setup and assembly, fluid control, cooling system maintenance, fluid management, and extensive troubleshooting for multiple systems. We expect this can come from both on-the-job training as well as some specialized technical education. How have the results been disseminated to communities of interest?Dissemination has targeted students (workforce development), scientists, and industry. The results of the work have been shared by Dr. George Philippidis with the scientific community at the University of South Florida (USF) and in class as part of the module on algae technologies in his graduate course "Renewable Transportation Fuels" (IDS 6207) at USF's Patel College of Global Sustainability. He has also held discussion on the subject of automation in algae cultivation with (1) algae colleagues during a visit to the Arizona Center for Algae Technology and Innovation at Arizona State University and (2) other companies in the algae industry (Algafeed of Jupiter, FL), who are keenly interested in automation for cost-reduction purposes. What do you plan to do during the next reporting period to accomplish the goals?In the first reporting period a new sensor was developed to automatically measure the biomass density in algae cultures in a lab setting. In the next reporting period, the sensor will be tested outdoors in photobioreactors under real life conditions. The dual sensor will be installed in a semi-commercial bioreactor already developed by Culture BioSystems and installed at the University of South Florida (Tampa, FL). The algae bioreactor has a capacity of 110 liters and a productivity of 15-20 g dry mass/m2/day. Two experiments will be performed: After inoculation of the bioreactor, growth will be regularly monitored to show that the new sensor has the capability to accurately measure algae biomass density/growth over the full range of biomass densities (in our case from ca. 0.1 g/l up to 4 g/l). The inline (real time) readings of the sensor will be compared to those of samples analyzed offline. After recording the full growth curve, the reactor will be operated for a few weeks under outdoor production conditions. Regular sensor readings will be compared with traditional measurements of biomass densities. In this experiment we will show that new sensor will deliver stable and reproducible data readings under production conditions.

Impacts
What was accomplished under these goals? IMPACT: There is compelling value to feeding live algae in fish hatcheries as the current survival rate of larvae fed frozen paste is relatively low resulting in higher costs for consumers. However the complexity and costs of existing photo-bioreactors and the logistical costs of shipping live material over distances are barriers to the widespread deployment of live algae as feed. Culture BioSystems has successfully grown and sold live concentrated Nannochloropsis to Florida hatcheries using an innovative low cost photobioreactor. Further reduction in production cost requires automating functions in the bio-reactor operation. With this goal in mind, thus far as part of this SBIR Phase I we have successfully developed and tested in the laboratory a light sensor which measures in real time (in line) the density of the algae culture inside the reactor. We will now test this sensor in real-world, outdoor conditions and compare to the traditional manual methods of measuring algae density (off line). We anticipate that automation of algae concentration measurements will significantly reduce operating (labor) costs, eliminate human error, and optimize the harvest/refill cycles during algae cultivation, hence reducing the cost of produced algae for hatcheries and fish farms. The development of an automated and modular photo-bioreactor which can produce low cost algae will provide benefit to hatchery farmers who will have access to feed of higher nutritional value at a lower cost than they pay today. This will increase the survival rate of harder to grow fish species like snapper, grouper and barramundi. By providing these fish with higher quality, live algae the aquaculture industry will be better able to provide protein to a growing world population. ACCOMPLISHMENTS Goal 1: Develop a light sensor Major activities completed / experiments conducted: Objective was to create a short list of light sensor options that worked in the lab Variables were: type of sensor (optical, chemical, other), light wavelength (red or green light), distance between light emitter and sensor, angle between light emitter and sensor, accuracy with increasing algae density. We tested 3 angles between the light emitter and sensor (0 degree, 90 degrees, 180 degrees) for both red and green light using a glass algae container. We measured the output voltage of the sensor at different algae densities. 2) Data collected: Graphs of algae density versus output voltage for 6 different combination of light angle and color of lights 3) Summary statistics and discussion of results: All the graphs were curves that were steepest (most sensitive) at lower algae density and shallower (less sensitive) at highest algae density. We sought curves which had the highest sensitivity at highest density, since the primary purpose is to know when the algae is ready to harvest. 4) Key outcomes or other accomplishments realized: The most promising system was red light at a 90 degree angle to the light emitter. That is, the light beam aimed downwards, whereas the light sensor was positioned to the side of the light beam picking up the light that has been scattered by the algae culture. This combination had the highest sensitivity at high algae density. Goal 2: Real world outdoor test Major activities completed / experiments conducted: Objective: Construct a sensor that can operate in outdoor conditions and then demonstrate. Worked with a local manufacturer (Pi Designs) to develop a design and manufacture our lab-scale sensor. There was close interaction between the manufacturer and our technical team. We purchased the components and Pi Designs created a molded sensor. We tested this sensor in an indoor lab unit. Installed the sensor in the outdoor bioreactor. After a number of runs we concluded that we needed additional sensitivity at the lower algae density as well, so we added a second light sensor at a different angle calibrated for lower density. Currently running outdoors cultivation with the new system (dual sensor). Data collected: Multiple graphs using the original single sensor in the laboratory and then outdoors. Multiple graphs using the final dual sensor in the laboratory and then outdoors. Summary statistics and discussion of results: Initial results show that the dual sensor outdoors is working well and reproducibly. The graph follows the same curve as that established indoors. By monitoring the voltage of the sensor, through the established "algae concentration-voltage" curve, we can derive the algae density and therefore initiate harvesting at the appropriate density. Key outcomes or other accomplishments realized: Realized that although the sensor is inside the enclosed manifold of the bioreactor, there is still some background ambient light which interferes with the readings. After trying several ways to shield from the light, we realized that the simplest solution is to take the readings at night! This methodology seems to work well. Continuing to test the dual sensor with this methodology, but we have already accomplished our technical goal of developing an in-situ sensor, whose voltage output is correlated to algal density. This is a significant technical development that will automate algae cultivation and hence reduce operating costs thus benefitting the entire aquaculture and agricultural supply chain by allowing more reliable and lower cost production of live algae as a feedstock.

Publications