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An Analytical Framework on Utilizing Various Integrated Multi-Trophic Scenarios for Basil Production
Here, we aim to improve the overall sustainability of aquaponic basil (Ocimum basilicum L.)-sturgeon (Acipenser baerii) integrated recirculating systems. We implement new AI methods for operational management together with innovative solutions for plant growth bed, consisting of Rapana venosa shells...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9920146/ https://www.ncbi.nlm.nih.gov/pubmed/36771624 http://dx.doi.org/10.3390/plants12030540 |
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author | Petrea, Ștefan-Mihai Simionov, Ira Adeline Antache, Alina Nica, Aurelia Oprica, Lăcrămioara Miron, Anca Zamfir, Cristina Gabriela Neculiță, Mihaela Dima, Maricel Floricel Cristea, Dragoș Sebastian |
author_facet | Petrea, Ștefan-Mihai Simionov, Ira Adeline Antache, Alina Nica, Aurelia Oprica, Lăcrămioara Miron, Anca Zamfir, Cristina Gabriela Neculiță, Mihaela Dima, Maricel Floricel Cristea, Dragoș Sebastian |
author_sort | Petrea, Ștefan-Mihai |
collection | PubMed |
description | Here, we aim to improve the overall sustainability of aquaponic basil (Ocimum basilicum L.)-sturgeon (Acipenser baerii) integrated recirculating systems. We implement new AI methods for operational management together with innovative solutions for plant growth bed, consisting of Rapana venosa shells (R), considered wastes in the food processing industry. To this end, the ARIMA-supervised learning method was used to develop solutions for forecasting the growth of both fish and plant biomass, while multi-linear regression (MLR), generalized additive models (GAM), and XGBoost were used for developing black-box virtual sensors for water quality. The efficiency of the new R substrate was evaluated and compared to the consecrated light expended clay aggregate—LECA aquaponics substrate (H). Considering two different technological scenarios (A—high feed input, B—low feed input, respectively), nutrient reduction rates, plant biomass growth performance and additionally plant quality are analysed. The resulting prediction models reveal a good accuracy, with the best metrics for predicting N-NO(3) concentration in technological water. Furthermore, PCA analysis reveals a high correlation between water dissolved oxygen and pH. The use of innovative R growth substrate assured better basil growth performance. Indeed, this was in terms of both average fresh weight per basil plant, with 22.59% more at AR compared to AH, 16.45% more at BR compared to BH, respectively, as well as for average leaf area (LA) with 8.36% more at AR compared to AH, 9.49% more at BR compared to BH. However, the use of R substrate revealed a lower N-NH(4) and N-NO(3) reduction rate in technological water, compared to H-based variants (19.58% at AR and 18.95% at BR, compared to 20.75% at AH and 26.53% at BH for N-NH(4); 2.02% at AR and 4.1% at BR, compared to 3.16% at AH and 5.24% at BH for N-NO(3)). The concentration of Ca, K, Mg and NO(3) in the basil leaf area registered the following relationship between the experimental variants: AR > AH > BR > BH. In the root area however, the NO(3) were higher in H variants with low feed input. The total phenolic and flavonoid contents in basil roots and aerial parts and the antioxidant activity of the methanolic extracts of experimental variants revealed that the highest total phenolic and flavonoid contents were found in the BH variant (0.348% and 0.169%, respectively in the roots, 0.512% and 0.019%, respectively in the aerial parts), while the methanolic extract obtained from the roots of the same variant showed the most potent antioxidant activity (89.15%). The results revealed that an analytical framework based on supervised learning can be successfully employed in various technological scenarios to optimize operational management in an aquaponic basil (Ocimum basilicum L.)-sturgeon (Acipenser baerii) integrated recirculating systems. Also, the R substrate represents a suitable alternative for replacing conventional aquaponic grow beds. This is because it offers better plant growth performance and plant quality, together with a comparable nitrogen compound reduction rate. Future studies should investigate the long-term efficiency of innovative R aquaponic growth bed. Thus, focusing on the application of the developed prediction and forecasting models developed here, on a wider range of technological scenarios. |
format | Online Article Text |
id | pubmed-9920146 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99201462023-02-12 An Analytical Framework on Utilizing Various Integrated Multi-Trophic Scenarios for Basil Production Petrea, Ștefan-Mihai Simionov, Ira Adeline Antache, Alina Nica, Aurelia Oprica, Lăcrămioara Miron, Anca Zamfir, Cristina Gabriela Neculiță, Mihaela Dima, Maricel Floricel Cristea, Dragoș Sebastian Plants (Basel) Article Here, we aim to improve the overall sustainability of aquaponic basil (Ocimum basilicum L.)-sturgeon (Acipenser baerii) integrated recirculating systems. We implement new AI methods for operational management together with innovative solutions for plant growth bed, consisting of Rapana venosa shells (R), considered wastes in the food processing industry. To this end, the ARIMA-supervised learning method was used to develop solutions for forecasting the growth of both fish and plant biomass, while multi-linear regression (MLR), generalized additive models (GAM), and XGBoost were used for developing black-box virtual sensors for water quality. The efficiency of the new R substrate was evaluated and compared to the consecrated light expended clay aggregate—LECA aquaponics substrate (H). Considering two different technological scenarios (A—high feed input, B—low feed input, respectively), nutrient reduction rates, plant biomass growth performance and additionally plant quality are analysed. The resulting prediction models reveal a good accuracy, with the best metrics for predicting N-NO(3) concentration in technological water. Furthermore, PCA analysis reveals a high correlation between water dissolved oxygen and pH. The use of innovative R growth substrate assured better basil growth performance. Indeed, this was in terms of both average fresh weight per basil plant, with 22.59% more at AR compared to AH, 16.45% more at BR compared to BH, respectively, as well as for average leaf area (LA) with 8.36% more at AR compared to AH, 9.49% more at BR compared to BH. However, the use of R substrate revealed a lower N-NH(4) and N-NO(3) reduction rate in technological water, compared to H-based variants (19.58% at AR and 18.95% at BR, compared to 20.75% at AH and 26.53% at BH for N-NH(4); 2.02% at AR and 4.1% at BR, compared to 3.16% at AH and 5.24% at BH for N-NO(3)). The concentration of Ca, K, Mg and NO(3) in the basil leaf area registered the following relationship between the experimental variants: AR > AH > BR > BH. In the root area however, the NO(3) were higher in H variants with low feed input. The total phenolic and flavonoid contents in basil roots and aerial parts and the antioxidant activity of the methanolic extracts of experimental variants revealed that the highest total phenolic and flavonoid contents were found in the BH variant (0.348% and 0.169%, respectively in the roots, 0.512% and 0.019%, respectively in the aerial parts), while the methanolic extract obtained from the roots of the same variant showed the most potent antioxidant activity (89.15%). The results revealed that an analytical framework based on supervised learning can be successfully employed in various technological scenarios to optimize operational management in an aquaponic basil (Ocimum basilicum L.)-sturgeon (Acipenser baerii) integrated recirculating systems. Also, the R substrate represents a suitable alternative for replacing conventional aquaponic grow beds. This is because it offers better plant growth performance and plant quality, together with a comparable nitrogen compound reduction rate. Future studies should investigate the long-term efficiency of innovative R aquaponic growth bed. Thus, focusing on the application of the developed prediction and forecasting models developed here, on a wider range of technological scenarios. MDPI 2023-01-25 /pmc/articles/PMC9920146/ /pubmed/36771624 http://dx.doi.org/10.3390/plants12030540 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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/). |
spellingShingle | Article Petrea, Ștefan-Mihai Simionov, Ira Adeline Antache, Alina Nica, Aurelia Oprica, Lăcrămioara Miron, Anca Zamfir, Cristina Gabriela Neculiță, Mihaela Dima, Maricel Floricel Cristea, Dragoș Sebastian An Analytical Framework on Utilizing Various Integrated Multi-Trophic Scenarios for Basil Production |
title | An Analytical Framework on Utilizing Various Integrated Multi-Trophic Scenarios for Basil Production |
title_full | An Analytical Framework on Utilizing Various Integrated Multi-Trophic Scenarios for Basil Production |
title_fullStr | An Analytical Framework on Utilizing Various Integrated Multi-Trophic Scenarios for Basil Production |
title_full_unstemmed | An Analytical Framework on Utilizing Various Integrated Multi-Trophic Scenarios for Basil Production |
title_short | An Analytical Framework on Utilizing Various Integrated Multi-Trophic Scenarios for Basil Production |
title_sort | analytical framework on utilizing various integrated multi-trophic scenarios for basil production |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9920146/ https://www.ncbi.nlm.nih.gov/pubmed/36771624 http://dx.doi.org/10.3390/plants12030540 |
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