Dergiler / Black Sea Journal of Agriculture / 2026 / Cilt: 9 Sayı: 3

Advancing Medicinal and Aromatic Plant Cultivation through Smart Greenhouse Technologies

Musa Türkmen(Hatay Mustafa Kemal Üniversitesi, Ziraat Fakülesi, Tarla Bitkileri Bölümü)0000-0001-9914-9523
Esra Nermin Ertekin(Hatay Mustafa Kemal University)0000-0002-5397-2239
Sayfa
486–501
Yayın Tarihi
2026-05-15
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

In conclusion, smart greenhouse technologies offer substantial potential to transform MAP cultivation by enhancing productivity, quality, and sustainability, thereby supporting the growing global demand for high-value plant-derived bioactive compounds.

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Amaç & Hipotez:Medicinal and aromatic plants (MAPs) are increasingly important in global agriculture due to their extensive use in pharmaceutical, nutraceutical, cosmetic, and food industries, where their value is largely determined by biomass yield and the concentration of bioactive secondary metabolites.
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Temel Bulgular & Veri:However, the production of MAPs under open-field conditions is often constrained by environmental variability, leading to inconsistent yield and phytochemical composition.
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Sonuç & Katkı:In conclusion, smart greenhouse technologies offer substantial potential to transform MAP cultivation by enhancing productivity, quality, and sustainability, thereby supporting the growing global demand for high-value plant-derived bioactive compounds.
🔬Tür:Literatür & Derleme Çalışması
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Medicinal and aromatic plants · Smart greenhouse technologies · Controlled environment agriculture

Özet

Medicinal and aromatic plants (MAPs) are increasingly important in global agriculture due to their extensive use in pharmaceutical, nutraceutical, cosmetic, and food industries, where their value is largely determined by biomass yield and the concentration of bioactive secondary metabolites. However, the production of MAPs under open-field conditions is often constrained by environmental variability, leading to inconsistent yield and phytochemical composition. In this context, controlled environment agriculture (CEA), particularly smart greenhouse technologies (SGTs), has emerged as a promising approach to enhance production efficiency and product quality. This review provides a comprehensive synthesis of recent advances in smart greenhouse technologies and their applications in MAP cultivation. It examines the role of key technological components, including Internet of Things (IoT)-based monitoring systems, automated irrigation and fertigation, artificial intelligence (AI) and machine learning (ML)–driven decision support systems, and light-emitting diode (LED) lighting technologies. These innovations enable real-time monitoring and precise control of environmental parameters such as temperature, humidity, light intensity, CO2 concentration, and nutrient availability, thereby optimizing plant growth conditions and metabolic processes. The findings indicate that SGTs significantly improve biomass yield, resource-use efficiency, and phytochemical consistency in MAPs. Controlled environmental manipulation enhances the biosynthesis of valuable secondary metabolites, including essential oils, phenolic compounds, and flavonoids, while reducing variability in product quality. Case studies on economically important species such as basil (Ocimum basilicum L.), peppermint (Mentha piperita), thyme (Thymus vulgaris L.), and lavender (Lavandula angustifolia Mill.) demonstrate that the integration of advanced lighting systems, sensor-based irrigation, and AI-driven management can substantially increase both yield and bioactive compound accumulation. Despite these advantages, several challenges remain, including high initial investment costs, energy consumption, complex data management requirements, and the need for technical expertise. Additionally, current research is still limited in fully elucidating the complex interactions between environmental factors and secondary metabolite biosynthesis under smart greenhouse conditions. Future perspectives highlight the increasing role of AI, robotics, digital agriculture platforms, and renewable energy integration in advancing smart greenhouse systems toward more autonomous, efficient, and sustainable production models. Further interdisciplinary research is needed to optimize species-specific cultivation strategies and improve the economic feasibility of these technologies. In conclusion, smart greenhouse technologies offer substantial potential to transform MAP cultivation by enhancing productivity, quality, and sustainability, thereby supporting the growing global demand for high-value plant-derived bioactive compounds.

Abstract

Medicinal and aromatic plants (MAPs) are increasingly important in global agriculture due to their extensive use in pharmaceutical, nutraceutical, cosmetic, and food industries, where their value is largely determined by biomass yield and the concentration of bioactive secondary metabolites. However, the production of MAPs under open-field conditions is often constrained by environmental variability, leading to inconsistent yield and phytochemical composition. In this context, controlled environment agriculture (CEA), particularly smart greenhouse technologies (SGTs), has emerged as a promising approach to enhance production efficiency and product quality. This review provides a comprehensive synthesis of recent advances in smart greenhouse technologies and their applications in MAP cultivation. It examines the role of key technological components, including Internet of Things (IoT)-based monitoring systems, automated irrigation and fertigation, artificial intelligence (AI) and machine learning (ML)–driven decision support systems, and light-emitting diode (LED) lighting technologies. These innovations enable real-time monitoring and precise control of environmental parameters such as temperature, humidity, light intensity, CO2 concentration, and nutrient availability, thereby optimizing plant growth conditions and metabolic processes. The findings indicate that SGTs significantly improve biomass yield, resource-use efficiency, and phytochemical consistency in MAPs. Controlled environmental manipulation enhances the biosynthesis of valuable secondary metabolites, including essential oils, phenolic compounds, and flavonoids, while reducing variability in product quality. Case studies on economically important species such as basil (Ocimum basilicum L.), peppermint (Mentha piperita), thyme (Thymus vulgaris L.), and lavender (Lavandula angustifolia Mill.) demonstrate that the integration of advanced lighting systems, sensor-based irrigation, and AI-driven management can substantially increase both yield and bioactive compound accumulation. Despite these advantages, several challenges remain, including high initial investment costs, energy consumption, complex data management requirements, and the need for technical expertise. Additionally, current research is still limited in fully elucidating the complex interactions between environmental factors and secondary metabolite biosynthesis under smart greenhouse conditions. Future perspectives highlight the increasing role of AI, robotics, digital agriculture platforms, and renewable energy integration in advancing smart greenhouse systems toward more autonomous, efficient, and sustainable production models. Further interdisciplinary research is needed to optimize species-specific cultivation strategies and improve the economic feasibility of these technologies. In conclusion, smart greenhouse technologies offer substantial potential to transform MAP cultivation by enhancing productivity, quality, and sustainability, thereby supporting the growing global demand for high-value plant-derived bioactive compounds.

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Bu Makaleye Atıf Yap

Türkmen, M., Ertekin, E. N. (2026). Advancing Medicinal and Aromatic Plant Cultivation through Smart Greenhouse Technologies. Black Sea Journal of Agriculture, Cilt: 9 Sayı: 3, 486–501. https://doi.org/10.47115/bsagriculture.1911694

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Kaynakça (126)

  1. Abdelhamid, M. A., Abdelkader, T. K., Sayed, H. A., Zhang, Z., Zhao, X., & Atia, M. F. (2025). Design and evaluation of a solar powered smart irrigation system for sustainable urban agriculture. Scientific Reports, 15(1), 11761. https://doi.org/10.1038/s41598-025-94251-3
  2. Abid, M., & Wajid, H. A. (2025). Next-gen agriculture: How AI-driven 3D farming builds resilience against global food crises. In Climate Resilient and Sustainable Agriculture: Volume 2: Social and Transformative Strategies (pp. 269-286). Cham: Springer Nature Switzerland.
  3. Abou-Mehdi-Hassani, F., Ait Bouh, H., Boudnaya, J., Chmaimi, M., Anar, E., & Mkhida, A. (2023). Design and remote monitoring of a wireless-controlled smart agricultural greenhouse. In E3S Web of Conferences.
  4. Aftab, T. (2019). A review of medicinal and aromatic plants and their secondary metabolites status under abiotic stress. Journal of Medicinal Plants, 7(3), 99-106.
  5. Agrawal, P. S., Chouksey, R. R., & Sharma, V. S. (2025). IoT-enabled smart greenhouses: reinforcement learning, predictive modeling, and disease detection for enhanced crop yield. In 2025 International Conference on Information, Implementation, and Innovation in Technology (I2ITCON). https://doi.org/10.1109/I2ITCON65200.2025.11210662
  6. Ahmadi, T., Shabani, L., & Sabzalian, M. R. (2021). LED light sources improved the essential oil components and antioxidant activity of two genotypes of lemon balm (Melissa officinalis L.). Botanical studies, 62(1), 9. https://doi.org/10.1186/s40529-021-00316-7
  7. Ajagekar, A., Mattson, N. S., & You, F. (2023). Energy-efficient AI-based control of semi-closed greenhouses leveraging robust optimization in deep reinforcement learning. Advances in Applied Energy, 9, 100119. https://doi.org/10.1016/j.adapen.2022.100119
  8. Akhilraj, B., & Raghul, S. (2023). An evaluation of impact of precision farming on the production of medicinal as well as aromatic crops. Environment and Ecology, 41, 2989-2996. https://doi.org/10.60151/envec/UMEK8872
  9. Ali, H. E., & Tong, Y. (2023). Volatile oil concentration and growth of thyme (Thymus vulgaris L.) plants responded to red to blue light ratios. Technology in Horticulture, 3(1), 2. https://doi.org/10.48130/TIH-2023-0002
  10. Ali, J. A., & Drăghici, E. M. (2023). Study on the Cultivation of ‘Marcela’and ‘Timijan’Thyme Varieties in the NFT System. In IOP Conference Series: Earth and Environmental Science.
  11. Ali, M., Gunawan, A. A. N., Prasetya, D. A., Ibrahim, M. Z. B., & Diyasa, I. G. S. M. (2024). Impact of Smart greenhouse using IoT for enhanced quality of plant growth. International Journal of Robotics & Control Systems, 4(3), 1473-1489. http://dx.doi.org/10.31763/ijrcs.v4i3.1277
  12. Al-Naemi, S., & Al-Otoom, A. (2023). Smart sustainable greenhouses utilizing microcontroller and IOT in the GCC countries; energy requirements & economical analyses study for a concept model in the state of Qatar. Results in Engineering, 17, 100889. https://doi.org/10.1016/j.rineng.2023.100889
  13. Appolloni, E., Orsini, F., Pennisi, G., Gabarrell Durany, X., Paucek, I., & Gianquinto, G. (2021). Supplemental LED lighting effectively enhances the yield and quality of greenhouse truss tomato production: Results of a meta-analysis. Frontiers in Plant Science, 12, 596927. https://doi.org/10.3389/fpls.2021.596927
  14. Appolloni, E., Pennisi, G., Zauli, I., Carotti, L., Paucek, I., Quaini, S., Orsini, F., & Gianquinto, G. (2022). Beyond vegetables: effects of indoor LED light on specialized metabolite biosynthesis in medicinal and aromatic plants, edible flowers, and microgreens. Journal of the Science of Food and Agriculture, 102(2), 472-487. https://doi.org/10.1002/jsfa.11513
  15. Aqeel, U., Aftab, T., Khan, M. M. A., & Naeem, M. (2023). Regulation of essential oil in aromatic plants under changing environment. Journal of Applied Research on Medicinal and Aromatic Plants, 32, 100441. https://doi.org/10.1016/j.jarmap.2022.100441
  16. Arad, B., Balendonck, J., Barth, R., Ben-Shahar, O., Edan, Y., Hellström, T., Hemming, J., Kurtser, P., Ringdahl, O., & van Tuijl, B. (2020). Development of a sweet pepper harvesting robot. Journal of Field Robotics, 37(6), 1027–1039. https://doi.org/10.1002/rob.21937
  17. Asane, S., Salve, S., Birajdar, S., Borkar, S., & Gawali, P. (2025). IoT-driven smart greenhouse system for real-time environmental monitoring. European Journal of Scientific Research and Reviews, 2(4), 220–220.
  18. Badji, A., Benseddik, A., Bensaha, H., Boukhelifa, A., & Hasrane, I. (2022). Design, technology, and management of greenhouse: A review. Journal of Cleaner Production, 373, 133753. https://doi.org/10.1016/j.jclepro.2022.133753
  19. Bagagiolo, G., Matranga, G., Cavallo, E., & Pampuro, N. (2022). Greenhouse robots: Ultimate solutions to improve automation in protected cropping systems—A review. Sustainability, 14(11), 6436. https://doi.org/10.3390/su14116436
  20. Beatrice, P., Saviano, G., Reguzzoni, M., Divino, F., Fantasma, F., Chiatante, D., & Montagnoli, A. (2023). Light spectra of biophilic LED-sourced system modify essential oils composition and plant morphology of Mentha piperita L. and Ocimum basilicum L. Frontiers in Plant Science, 14, 1093883. https://doi.org/10.3389/fpls.2023.1093883
  21. Benyezza, H., Bouhedda, M., Kara, R., & Rebouh, S. (2023). Smart platform based on IoT and WSN for monitoring and control of a greenhouse in the context of precision agriculture. Internet of Things, 23, 100830. https://doi.org/10.1016/j.iot.2023.100830
  22. Bersani, C., Ouammi, A., Sacile, R., & Zero, E. (2020). Model predictive control of smart greenhouses as the path towards near zero energy consumption. Energies, 13(14), 3647. https://doi.org/10.3390/en13143647
  23. Bersani, C., Ruggiero, C., Sacile, R., Soussi, A., & Zero, E. (2022). Internet of things approaches for monitoring and control of smart greenhouses in industry 4.0. Energies, 15(10), 3834. https://doi.org/10.3390/en15103834
  24. Bicamumakuba, E., Reza, M. N., Jin, H., Samsuzzaman, Lee, K. H., & Chung, S. O. (2025). Multi-sensor monitoring, intelligent control, and data processing for smart greenhouse environment management. Sensors, 25(19), 6134. https://doi.org/10.3390/s25196134
  25. Bisht, D., & Mittal, A. (2025). IoT-based design and simulation of smart greenhouse monitoring and control system. In 2025 7th International Conference on Inventive Material Science and Applications (ICIMA). https://doi.org/10.1109/ICIMA64861.2025.11073957
  26. Campana, E., Ciriello, M., Rouphael, Y., & De Pascale, S. (2025). A new paradigm in greenhouse horticulture: Integrating resource efficiency for sustainable intensification. Environment, Development and Sustainability, 1–40. https://doi.org/10.1007/s10668-025-06861-6
  27. Chahidi, L. O., Fossa, M., Priarone, A., & Mechaqrane, A. (2021). Energy saving strategies in sustainable greenhouse cultivation in the Mediterranean climate—A case study. Applied Energy, 282, 116156. https://doi.org/10.1016/j.apenergy.2020.116156
  28. Crișan, I., Ona, A., Vârban, D., Muntean, L., Vârban, R., Stoie, A., Mihăiescu, T., & Morea, A. (2023). Current trends for lavender (Lavandula angustifolia Mill.) crops and products with emphasis on essential oil quality. Plants, 12(2), 357. https://doi.org/10.3390/plants12020357
  29. Cuenca Cabrera, M. G., Rodas Rodríguez, R. R., Taipe Quilligana, S. V., & Pisco Vanegas, J. C. (2025). Intelligent automated monitoring and control system with IoT for climate management and irrigation in greenhouses. Revista Científica Multidisciplinar G-nerando, 6(1), 1-28. http://dx.doi.org/10.60100/rcmg.v6i1.526
  30. Cui, H., Hanafi, M., Fazlil Ilahi, W. F., Zamri, M. A. S., Shafie, S. M., & Mashohor, S. (2022). The effect of smart fertigation systems on chilli grown in a greenhouse for urban farming. Irrigation and Drainage, 71(4), 959–970. https://doi.org/10.1002/ird.2709
  31. de Jesús Morales-Becerril, C., Colinas-León, M. T., Soto-Hernández, R. M., Martínez-Damián, M. T., & Mendoza-Castelán, G. (2024). Growth and accumulation of phenolic compounds in thyme (Thymus vulgaris) based on the balance of red and blue LED lights. Agrociencia. https://doi.org/10.47163/agrociencia.v58i2.2624
  32. Disciglio, G., Stasi, A., Tarantino, A., & Frabboni, L. (2025). Microclimate modification, evapotranspiration, growth and essential oil yield of six medicinal plants cultivated beneath a dynamic agrivoltaic system in southern Italy. Plants, 14(15), 2428. https://doi.org/10.3390/plants14152428
  33. Dsouza, A., Dixon, M., Shukla, M., & Graham, T. (2025). Harnessing controlled-environment systems for enhanced production of medicinal plants. Journal of Experimental Botany, 76(1), 76–93. https://doi.org/10.1093/jxb/erae248
  34. Dudnyk, A., Pasichnyk, N., Yakymenko, I., Lendiel, T., Witaszek, K., Durczak, K., & Czekała, W. (2025). Smart resource management and energy-efficient regimes for greenhouse vegetable production. Energies, 18(17), 4690. https://doi.org/10.3390/en18174690
  35. Durmanov, A., Farmanov, T., Nazarova, F., Khasanov, B., Karakulov, F., Saidaxmedova, N., Mamatkulov, M., Madumarov, T., Kurbanova, K., Mamasadikov, A., & Kholmatov, Z. (2024). Effective economic model for greenhouse facilities management and digitalization. Journal of Human, Earth, and Future, 5(2), 187–204. http://dx.doi.org/10.28991/HEF-2024-05-02-04
  36. Elvanidi, A., Benitez Reascos, C. M., Gourzoulidou, E., Kunze, A., Max, J. F., & Katsoulas, N. (2020). Implementation of the circular economy concept in greenhouse hydroponics for ultimate use of water and nutrients. Horticulturae, 6(4), 83. https://doi.org/10.3390/horticulturae6040083
  37. Escamilla-García, A., Soto-Zarazúa, G. M., Toledano-Ayala, M., Rivas-Araiza, E., & Gastélum-Barrios, A. (2020). Applications of artificial neural networks in greenhouse technology and overview for smart agriculture development. Applied Sciences, 10(11), 3835. https://doi.org/10.3390/app10113835
  38. Esmaeil Zade, N. S., Sadeghi, A., & Moradi, P. (2019). Streptomyces strains alleviate water stress and increase peppermint (Mentha piperita) yield and essential oils. Plant and Soil, 434(1), 441–452. https://doi.org/10.1007/s11104-018-3862-8
  39. Farooq, M. S., Javid, R., Riaz, S., & Atal, Z. (2022). IoT-based smart greenhouse framework and control strategies for sustainable agriculture. IEEE Access, 10, 99394–99420. https://doi.org/10.1109/ACCESS.2022.3204066
  40. Farruggia, D., Di Miceli, G., Licata, M., Leto, C., Salamone, F., & Novak, J. (2024). Foliar application of various biostimulants produces contrasting response on yield, essential oil and chemical properties of organically grown sage (Salvia officinalis L.). Frontiers in Plant Science, 15, 1397489. https://doi.org/10.3389/fpls.2024.1397489
  41. Ferrante, A., & Mariani, L. (2018). Agronomic management for enhancing plant tolerance to abiotic stresses: High and low values of temperature, light intensity, and relative humidity. Horticulturae, 4(3), 21. https://doi.org/10.3390/horticulturae4030021
  42. Gandhi, S. G., Mahajan, V., & Bedi, Y. S. (2015). Changing trends in biotechnology of secondary metabolism in medicinal and aromatic plants. Planta, 241(2), 303–317. https://doi.org/10.1007/s00425-014-2232-x
  43. Ghiasi, M., Wang, Z., Mehrandezh, M., & Paranjape, R. (2023). A systematic review of optimal and practical methods in design, construction, control, energy management and operation of smart greenhouses. IEEE Access, 12, 2830–2853. https://doi.org/10.1109/ACCESS.2023.3346436
  44. Gill, A. R., Miller, T. K., Wijeweera, S., Herrero, E., Massa, G. D., Mortimer, J. C., Webb, A. A. R., Millar, A. H., & Gilliham, M. (2025). Turbocharging fundamental science translation through controlled environment agriculture. Trends in Plant Science, 2025, 0.
  45. Gong, L., Yu, M., & Kollias, S. (2023). Optimizing crop yield and reducing energy consumption in greenhouse control using PSO-MPC algorithm. Algorithms, 16(5), 243. https://doi.org/10.3390/a16050243
  46. Greco, C., Gaglio, R., Settanni, L., Sciurba, L., Ciulla, S., Orlando, S., & Mammano, M. M. (2025). Smart farming technologies for sustainable agriculture: A case study of a Mediterranean aromatic farm. Agriculture, 15(8), 810. https://doi.org/10.3390/agriculture15080810
  47. Hasan, M. M., Bashir, T., Ghosh, R., Lee, S. K., & Bae, H. (2017). An overview of LEDs’ effects on the production of bioactive compounds and crop quality. Molecules, 22(9), 1420. https://doi.org/10.3390/molecules22091420
  48. Hasan, M., Bhat, A. G., S, V. K., R, M., Yadav, A. K., Saji, A., Bharath, G., & Prakash, S. A. (2025). IoT-based smart fertigation scheduling and wireless microclimate monitoring for a greenhouse Dutch bucket hydroponic system. Irrigation and Drainage, 74(5), 1889–1903. https://doi.org/10.1002/ird.70012
  49. He, J., Nair, A., & Qin, L. (2025). The extended photoperiod impacts on sweet basil (Ocimum basilicum) in a natural tropical greenhouse. Horticulturae, 11(3), 324. https://doi.org/10.3390/horticulturae11030324
  50. Hemming, S., Zwart, F. D., Elings, A., Petropoulou, A., & Righini, I. (2020). Cherry tomato production in intelligent greenhouses—Sensors and AI for control of climate, irrigation, crop yield, and quality. Sensors, 20(22), 6430. https://doi.org/10.3390/s20226430
  51. Hoque, A., Mazumder, A. S., Roy, S., Saikia, P., & Kumar, K. (2025). Transformative approaches to agricultural sustainability: Automation, smart greenhouses, and AI. International Journal of Research in Applied Science and Engineering Technology, 13(1), 1011–1023.
  52. Hoseinzadeh, S., & Garcia, D. A. (2024). Can AI predict the impact of its implementation in greenhouse farming?. Renewable and Sustainable Energy Reviews, 197, 114423. https://doi.org/10.1016/j.rser.2024.114423
  53. Jan, R., Asaf, S., Numan, M., Lubna, & Kim, K. M. (2021). Plant secondary metabolite biosynthesis and transcriptional regulation in response to biotic and abiotic stress conditions. Agronomy, 11(5), 968. https://doi.org/10.3390/agronomy11050968
  54. Jin, T., & Han, X. (2024). Robotic arms in precision agriculture: A comprehensive review of the technologies, applications, challenges, and future prospects. Computers and Electronics in Agriculture, 221, 108938. https://doi.org/10.1016/j.compag.2024.108938
  55. Kachanova, T., Manushkina, T., & Kovalenko, O. (2023). Features of growth and development of Lavandula angustifolia when grown under drip irrigation conditions in the Southern Steppe zone of Ukraine. Scientific Horizons, 3(26), 81–91. https://doi.org/10.48077/scihor3.2023.81
  56. Kalabkin, A. A., Kuznetsov, E. A., Ivliyev, S. N., Ashryatov, A. A., Kalabkin, V. A., & Musatov, A. S. (2023). The development of LED grow light for greenhouse cultivation. Engineering Technologies and Systems, 33(4), 585–598. https://doi.org/10.15507/2658-4123.033.202304.585-598
  57. Karimi, A., & Meiners, T. (2021). Antifungal activity of Zataria multiflora Boiss. essential oils and changes in volatile compound composition under abiotic stress conditions. Industrial Crops and Products, 171, 113888. https://doi.org/10.1016/j.indcrop.2021.113888
  58. Kaur, N., & Ahmed, T. (2021). Bioactive secondary metabolites of medicinal and aromatic plants and their disease-fighting properties. In Medicinal and aromatic plants: Healthcare and industrial applications (pp. 113–142). Springer International Publishing.
  59. Kavga, A., Thomopoulos, V., Mangani, S., Kremmydas, S., & Petrakis, T. (2024). The impact of greenhouse integrated photovoltaics on Aloe vera cultivation. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 52(4), 14168. https://doi.org/10.15835/nbha52414168
  60. Kayadibi, İ. (2025). An IoT-driven framework based on sensor technology for smart greenhouses and precision agriculture. International Journal on Smart Sensing and Intelligent Systems, 18(1), 1-13. https://doi.org/10.2478/ijssis-2025-0005
  61. Kharraz, N., & Szabó, I. (2025). Hybrid plant growth: Integrating stochastic, empirical, and optimization models with machine learning for controlled environment agriculture. Agronomy, 15(1), 189. https://doi.org/10.3390/agronomy15010189
  62. Kim, J. S. G., Jeong, W., Park, S., & Yang, M. (2022). Development of a fuzzy logic-controlled system for home cultivation of sweet basil. Frontiers in Plant Science, 13, 999106. https://doi.org/10.3389/fpls.2022.999106
  63. Kirci, P., Ozturk, E., & Celik, Y. (2022). A novel approach for monitoring of smart greenhouse and flowerpot parameters and detection of plant growth with sensors. Agriculture, 12(10), 1705. https://doi.org/10.3390/agriculture12101705
  64. Kumar, V., Zadokar, A., Kumar, P., Sharma, R., Sharma, R., Siddiqui, M. W., ırfan, M., & Chandora, R. (2025). Advancing medicinal plant agriculture: Integrating technology and precision agriculture for sustainability. PeerJ, 13, e19058.
  65. Kumari, N., Prakash, S., Sharma, N., Puri, S., Thakur, M., Singh, J., & Kumar, M. (2024). Medicinal and aromatic plants as potential sources of bioactives along with health-promoting activities. Current Food Science and Technology Reports, 2(4), 359–376. https://doi.org/10.1007/s43555-024-00042-8
  66. Laftouhi, A., Eloutassi, N., Ech-Chihbi, E., Rais, Z., Abdellaoui, A., Taleb, A., Beniken, M., Nafidi, H. A., Salamatullah, A. M., & Taleb, M. (2023). The impact of environmental stress on the secondary metabolites and the chemical compositions of the essential oils from some medicinal plants used as food supplements. Sustainability, 15(10), 7842. https://doi.org/10.3390/su15107842
  67. Lee, H., Baek, J., Im, D., Heo, J., & Kim, T. (2025). Integrated smart farm system for Centella asiatica L. cultivation: Development and assessment of multi-tier cultivation effects on bioactive compound production. Frontiers in Plant Science, 16, 1646310. https://doi.org/10.3389/fpls.2025.1646310
  68. Lee, M. H., Yao, M. H., Kow, P. Y., Kuo, B. J., & Chang, F. J. (2024). An artificial intelligence-powered environmental control system for resilient and efficient greenhouse farming. Sustainability, 16(24), 10958. https://doi.org/10.3390/su162410958
  69. Li, H., Guo, Y., Zhao, H., Wang, Y., & Chow, D. (2021). Towards automated greenhouse: A state-of-the-art review on greenhouse monitoring methods and technologies based on internet of things. Computers and Electronics in Agriculture, 191, 106558. https://doi.org/10.1016/j.compag.2021.106558
  70. Li, Y., Hu, Y., Li, Z., Wu, W., Ma, M., & Guo, A. (2024). Intelligent decision-making for fertigation treatment of tomatoes cultivated in greenhouse: An experimental study. Irrigation and Drainage, 73(4), 1246–1261. https://doi.org/10.1002/ird.2957
  71. Li, Y., Kong, D., Fu, Y., Sussman, M. R., & Wu, H. (2020). The effect of developmental and environmental factors on secondary metabolites in medicinal plants. Plant Physiology and Biochemistry, 148, 80–89. https://doi.org/10.1016/j.plaphy.2020.01.006
  72. Liu, W., Li, Y., Yang, M., Pang, K., Xu, Z., Yao, M., Bai, Y., & Zhang, F. (2025). Microclimate prediction of solar greenhouse with pad–fan cooling systems using a machine and deep learning approach. Agriculture, 15(20), 2107. https://doi.org/10.3390/agriculture15202107
  73. Mahajan, M., Kuiry, R., & Pal, P. K. (2020). Understanding the consequence of environmental stress for accumulation of secondary metabolites in medicinal and aromatic plants. Journal of Applied Research on Medicinal and Aromatic Plants, 18, 100255. https://doi.org/10.1016/j.jarmap.2020.100255
  74. Mansinhos, I., Gonçalves, S., & Romano, A. (2024). How climate change-related abiotic factors affect the production of industrial valuable compounds in Lamiaceae plant species: A review. Frontiers in Plant Science, 15, 1370810. https://doi.org/10.3389/fpls.2024.1370810
  75. Maraveas, C. (2022). Incorporating artificial intelligence technology in smart greenhouses: Current state of the art. Applied Sciences, 13(1), 14. https://doi.org/10.3390/app13010014
  76. Maraveas, C., Karavas, C. S., Loukatos, D., Bartzanas, T., Arvanitis, K. G., & Symeonaki, E. (2023). Agricultural greenhouses: Resource management technologies and perspectives for zero greenhouse gas emissions. Agriculture, 13(7), 1464. https://doi.org/10.3390/agriculture13071464
  77. Maraveas, C., Piromalis, D., Arvanitis, K. G., Bartzanas, T., & Loukatos, D. (2022). Applications of IoT for optimized greenhouse environment and resources management. Computers and Electronics in Agriculture, 198, 106993. https://doi.org/10.1016/j.compag.2022.106993
  78. Marchev, A. S., Yordanova, Z. P., & Georgiev, M. I. (2020). Green (cell) factories for advanced production of plant secondary metabolites. Critical Reviews in Biotechnology, 40(4), 443–458. https://doi.org/10.1080/07388551.2020.1731414
  79. Meyer, G. E., Conley, M. E., & Paparozzi, E. T. (2017). Management and modeling of winter-time basil cultivars grown with a cap MAT system. In 2017 ASABE Annual International Meeting (p. 1). American Society of Agricultural and Biological Engineers.
  80. Mohamed, N., El Hanafy, E., Ibrahim, D. & Mahmoud, A. (2021). Effect of light intensity and water flow rate of hydroponic unit on thyme (Thymus vulgaris L.) production. Journal of Productivity and Development, 26(4), 955–970.
  81. Mondal, S., & Prashant, P. M. (2025). IoT-enabled smart greenhouses: Real-time environmental monitoring and climate control. In SHS Web of Conferences (Vol. 216, p. 01067). EDP Sciences.
  82. Nagarsheth, S., Agbossou, K., Henao, N., & Bendouma, M. (2025). The advancements in agricultural greenhouse technologies: An energy management perspective. Sustainability, 17(8), 3407. https://doi.org/10.3390/su17083407
  83. Oguntosin, V., Okeke, C., Adetiba, E., Abdulkareem, A., & Olowoleni, J. (2023). IoT-based greenhouse monitoring and control system. International Journal of Computing and Digital Systems, 14(1), 469. http://dx.doi.org/10.12785/ijcds/140137
  84. Özocak, M. (2020). Growing possibilities of medicinal and aromatic plants in greenhouses climatized by biogas potential in Tekirdağ region. Journal of Scientific Perspectives, 4(1), 71–82. https://doi.org/10.26900/jsp.4.006
  85. Pandita, D., & Pandita, A. (2021). Secondary metabolites in medicinal and aromatic plants (MAPs): Potent molecules in nature’s arsenal to fight human diseases. In Medicinal and aromatic plants: Healthcare and industrial applications (pp. 41–84). Springer International Publishing. https://doi.org/10.1007/978-3-030-58975-2_2
  86. Pant, P., Pandey, S., & Dall'Acqua, S. (2021). The influence of environmental conditions on secondary metabolites in medicinal plants: A literature review. Chemistry & Biodiversity, 18(11), e2100345. https://doi.org/10.1002/cbdv.202100345
  87. Paradiso, R., & Proietti, S. (2022). Light-quality manipulation to control plant growth and photomorphogenesis in greenhouse horticulture: The state of the art and the opportunities of modern LED systems. Journal of Plant Growth Regulation, 41(2), 742–780. https://doi.org/10.1007/s00344-021-10337-y
  88. Paucek, I., Appolloni, E., Pennisi, G., Quaini, S., Gianquinto, G., & Orsini, F. (2020). LED lighting systems for horticulture: Business growth and global distribution. Sustainability, 12(18), 7516. https://doi.org/10.3390/su12187516
  89. Pizzileo, G., Colizzi, L., Guerriero, E., Adamo, T., & Chiriacò, M. V. (2025). Resource use efficiency and environmental sustainability in greenhouse agriculture through IoT-based irrigation and fertilization management. Smart Agricultural Technology, 101180. https://doi.org/10.1016/j.atech.2025.101180
  90. Prashant, S. P., & Bhawana, M. (2024). An update on biotechnological intervention mediated by plant tissue culture to boost secondary metabolite production in medicinal and aromatic plants. Physiologia Plantarum, 176(4), e14400. https://doi.org/10.1111/ppl.14400
  91. Priya, G. L., Baskar, C., Deshmane, S. S., Adithya, C., & Das, S. (2023). Revolutionizing holy-basil cultivation with AI-enabled hydroponics system. IEEE Access, 11, 82624–82639. https://doi.org/10.1109/ACCESS.2023.3300912
  92. Qaderi, M. M., Martel, A. B., & Strugnell, C. A. (2023). Environmental factors regulate plant secondary metabolites. Plants, 12(3), 447. https://doi.org/10.3390/plants12030447
  93. Ramakrishna, A., Kothainayagi, B., Sundari, C. H., Sadik, M. M., & Jayashree, T. (2025). Smart greenhouse farming with Internet of Things (IoT) for cultivating and conserving Ayurvedic medicinal plants: A comprehensive review. International Journal of Ayurveda Research, 6(3), 198–206.
  94. Rasouli, F., Hassanpouraghdam, M. B., Pirsarandib, Y., Aazami, M. A., Asadi, M., Ercisli, S., Mehrabani, L. V., Puglisi, I., & Baglieri, A. (2023). Improvements in the biochemical responses and Pb and Ni phytoremediation of lavender (Lavandula angustifolia L.) plants through Funneliformis mosseae inoculation. BMC Plant Biology, 23(1), 252. https://doi.org/10.1186/s12870-023-04265-0
  95. Rayhana, R., Xiao, G., & Liu, Z. (2020). Internet of things empowered smart greenhouse farming. IEEE Journal of Radio Frequency Identification, 4(3), 195–211. https://doi.org/10.1109/JRFID.2020.2984391
  96. Sagheer, A., Mohammed, M., Riad, K., & Alhajhoj, M. (2020). A cloud-based IoT platform for precision control of soilless greenhouse cultivation. Sensors, 21(1), 223. https://doi.org/10.3390/s21010223
  97. Sánchez-Molina, J. A., Rodríguez, F., Moreno, J. C., Sánchez-Hermosilla, J., & Giménez, A. (2024). Robotics in greenhouses: Scoping review. Computers and Electronics in Agriculture, 219, 108750. https://doi.org/10.1016/j.compag.2024.108750
  98. Satpute, R., Gaikwad, H., Khan, S., Inamdar, A., & Dave, D. (2018). IoT-based greenhouse monitoring system. International Journal for Research in Applied Science & Engineering Technology (IJRASET), 6(4).
  99. Şekeroğlu, N., Cimen, G., Kulak, M., & Gezici, S. (2022). Plastic mulching or conventional cultivation of lavender flower: What influence on the yield, essential oil and their neuroprotective effects? Trakya University Journal of Natural Sciences, 23(1), 43–52. https://doi.org/10.23902/trkjnat.992275
  100. Selwal, N., Rahayu, F., Herwati, A., Latifah, E., Suhara, C., Suastika, I. B. K., Mahayu, W. M., & Wani, A. K. (2023). Enhancing secondary metabolite production in plants: Exploring traditional and modern strategies. Journal of Agriculture and Food Research, 14, 100702. https://doi.org/10.1016/j.jafr.2023.100702
  101. Sena, S., Kumari, S., Kumar, V., & Husen, A. (2024). Light-emitting diode (LED) lights for the improvement of plant performance and production: A comprehensive review. Current Research in Biotechnology, 7, 100184. https://doi.org/10.1016/j.crbiot.2024.100184
  102. Şenkal, B. C. (2020). The role of secondary metabolites obtained from medicinal and aromatic plants in our lives. ISPEC Journal of Agricultural Sciences, 4(4), 1071–1079. https://doi.org/10.46291/ISPECJASvol4iss4pp1069-1077
  103. Shahrajabian, M. H., & Sun, W. (2022). Sustainable approaches to boost yield and chemical constituents of aromatic and medicinal plants by application of biostimulants. Recent Advances in Food, Nutrition & Agriculture, 13(2), 72–92. https://doi.org/10.2174/2772574X13666221004151822
  104. Shirokova, A. V., Dzhatdoeva, S. A., Ruzhitskiy, A. O., Belopukhov, S. L., Dmitrieva, V. L., Luneva, V. E., Dmitriev, L. B., Kharchenko, V. A., Kochkarov, A. A., & Sadykhov, E. G. (2025). Treasures induced by narrow-spectrum: Volatile phenylpropanoid and terpene compounds in leaves of lemon basil (Ocimum × citriodorum Vis.), sweet basil (O. basilicum L.) and bush basil (O. minimum L.) under artificial light city farm conditions. Plants, 14(3), 403. https://doi.org/10.3390/plants14030403
  105. Silva, N. V., Lemes, A. C., Silva, F. G., Dário, B. M. M., Jesus, J. R. D., de Sousa, T. L., Fernandes, S. S., & Egea, M. B. (2024). Enhancing Pereskia aculeata Mill. cultivation with LED technology: A sustainable approach. Processes, 12(12), 2695. https://doi.org/10.3390/pr12122695
  106. Sipos, L., Balázs, L., Székely, G., Jung, A., Sárosi, S., Radácsi, P., & Csambalik, L. (2021). Optimization of basil (Ocimum basilicum L.) production in LED light environments—A review. Scientia Horticulturae, 289, 110486. https://doi.org/10.1016/j.scienta.2021.110486
  107. Soltanbeigi, A., Yıldız, M., Dıraman, H., Terzi, H., Sakartepe, E., & Yıldız, E. (2021). Growth responses and essential oil profile of Salvia officinalis L. influenced by water deficit and various nutrient sources in the greenhouse. Saudi Journal of Biological Sciences, 28(12), 7327–7335. https://doi.org/10.1016/j.sjbs.2021.08.034
  108. Soussi, A., Zero, E., Ouammi, A., Zejli, D., Zahmoun, S., & Sacile, R. (2025). Smart greenhouse farming: A review towards near zero energy consumption. Discover Cities, 2(1), 55. https://doi.org/10.1007/s44327-025-00096-w
  109. Stutte, G. W. (2016). Controlled environment production of medicinal and aromatic plants. In Medicinal and aromatic crops: Production, phytochemistry, and utilization (pp. 49–63). American Chemical Society.
  110. Tabbert, J. M., Schulz, H., & Krähmer, A. (2021). Increased plant quality, greenhouse productivity and energy efficiency with broad-spectrum LED systems: A case study for thyme (Thymus vulgaris L.). Plants, 10(5), 960. https://doi.org/10.3390/plants10050960
  111. Tabbert, J. M., Schulz, H., & Krähmer, A. (2022). Investigation of LED light qualities for peppermint (Mentha × piperita L.) cultivation focusing on plant quality and consumer safety aspects. Frontiers in Food Science and Technology, 2, 852155. https://doi.org/10.3389/frfst.2022.852155
  112. Tang, Y., Zhou, W., Dong, Y., Liu, N., & Xie, C. (2025). Design of solar greenhouse environmental monitoring and control on the basis of multinode data fusion. Revista Brasileira de Engenharia Agrícola e Ambiental, 29, e292624.
  113. Tran, D. T., Le, H. S., & Huh, J. H. (2023). Building an automatic irrigation fertilization system for smart farm in greenhouse. IEEE Transactions on Consumer Electronics, 70(2), 4685–4698. https://doi.org/10.1109/TCE.2023.3304554
  114. Truzzi, E., Bertelli, D., Catellani, B., Jazi, D. D., & Benvenuti, S. (2025). Recovery of bioactive compounds from the biomass of aromatic plants after distillation using NADES: A sustainable alternative extraction method. Molecules, 30(5), 1120. https://doi.org/10.3390/molecules30051120
  115. Villagran, E., Espitia, J. J., Rodriguez, J., Gomez, L., Amado, G., Baeza, E., Aguilar-Rodríguez, C. E., Flores-Velazquez4, J., Akrami, M., Gil, R., & Arias, L. A. (2025). Use of lighting technology in controlled and semi-controlled agriculture in greenhouses and protected agriculture systems—Part 1: Scientific and bibliometric analysis. Sustainability, 17(4), 1712. https://doi.org/10.3390/su17041712
  116. Vimal, P. V., & Shivaprakasha, K. S. (2017). IoT-based greenhouse environment monitoring and controlling system using Arduino platform. In 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT) (pp. 1514–1519). IEEE. https://doi.org/10.1109/ICICICT1.2017.8342795
  117. Viswanathan, P., Chaithanya, N., Shalin, M. S., & Prashanth, A. (2024). IoT technology for monitoring and control of smart greenhouses. IRO Journal on Sustainable Wireless Systems, 6(1), 17–27.
  118. Wang, C., & Gong, J. (2024). Intelligent agricultural greenhouse control system based on internet of things and machine learning. arXiv preprint arXiv:2402.09488.
  119. Wang, Q., Jia, Y., Pang, Z., Zhou, J., Scriber II, K. E., Liang, B., & Chen, Z. (2024). Intelligent fertigation improves tomato yield and quality and water and nutrient use efficiency in solar greenhouse production. Agricultural Water Management, 298, 108873. https://doi.org/10.1016/j.agwat.2024.108873
  120. Wittmann, S., Jüttner, I., & Mempel, H. (2020). Indoor farming marjoram production—Quality, resource efficiency, and potential of application. Agronomy, 10(11), 1769.
  121. Wu, W., Wu, H., Liang, R., Huang, S., Meng, L., Zhang, M., Xie, F., & Zhu, H. (2025). Light regulates the synthesis and accumulation of plant secondary metabolites. Frontiers in Plant Science, 16, 1644472.
  122. Yang, L., Wen, K. S., Ruan, X., Zhao, Y. X., Wei, F., & Wang, Q. (2018). Response of plant secondary metabolites to environmental factors. Molecules, 23(4), 762. https://doi.org/10.3390/molecules23040762
  123. Zamora-Izquierdo, M. A., Santa, J., Martínez, J. A., Martínez, V., & Skarmeta, A. F. (2019). Smart farming IoT platform based on edge and cloud computing. Biosystems Engineering, 177, 4–17. https://doi.org/10.1016/j.biosystemseng.2018.10.014
  124. Zhang, M., Yan, T., Wang, W., Jia, X., Wang, J., & Klemeš, J. J. (2022). Energy-saving design and control strategy towards modern sustainable greenhouse: A review. Renewable and Sustainable Energy Reviews, 164, 112602.
  125. Zhang, S., Liu, T., Li, X., Cai, C., Chang, C., & Xue, X. (2025). Key technologies of robotic arms in unmanned greenhouse. Agronomy, 15(11), 2498. https://doi.org/10.3390/agronomy15112498
  126. Zhang, S., Zhang, L., Zou, H., Qiu, L., Zheng, Y., Yang, D., & Wang, Y. (2021). Effects of light on secondary metabolite biosynthesis in medicinal plants. Frontiers in Plant Science, 12, 781236.