Physical factors increased quantity and quality of micropropagated shoots of Cannabis sativa L. in a repeated harvest system with ex vitro rooting

Murphy, R. P.; Adelberg, Jeffrey

doi:10.1007/s11627-021-10166-4

Cited by 8 publications

(10 citation statements)

References 27 publications

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“…However, some species perform better at higher fluence rates, for example, Actinidia deliciosa (Gago et al, 2014), Lippia gracilis (Lazzarini et al, 2018), and Solanum tuberosum (Kulchin et al, 2018). In general, cannabis is known to grow best in vivo under higher light levels (Murphy and Adelberg, 2021; Wróbel et al, 2020), with yields increasing linearly up to at least 1600 μmol/m 2 /s PAR (Chandra et al, 2008; Lata et al, 2016; Rodriguez-Morrison et al, 2021), depending on the culture system. As such, the prediction to use such high light levels may reflect the nature of the species.…”

Section: Discussionmentioning

confidence: 99%

Comparative analysis of machine learning and evolutionary optimization algorithms for precision tissue culture ofCannabis sativa: Prediction and validation ofin vitroshoot growth and development based on the optimization of light and carbohydrate sources

Pepe

Hesami

Small³

et al. 2021

Preprint

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Micropropagation techniques offer opportunity to proliferate, maintain, and study dynamic plant responses in highly controlled environments without confounding external influences, forming the basis for many biotechnological applications. With medicinal and recreational interests for Cannabis sativa L. growing, research related to the optimization of in vitro practices is needed to improve current methods while boosting our understanding of the underlying physiological processes. Unfortunately, due to the exorbitantly large array of factors influencing tissue culture, existing approaches to optimize in vitro methods are tedious and time-consuming. Therefore, there is great potential to use new computational methodologies for analysing data to develop improved protocols more efficiently. Here, we first tested the effects of light qualities using assorted combinations of Red, Blue, Far Red, and White spanning 0-100 umol/m2/s in combination with sucrose concentrations ranging from 1-6 % (w/v), totaling 66 treatments, on in vitro shoot growth, root development, number of nodes , shoot emergence, and canopy surface area. Collected data were then assessed using multilayer perceptron (MLP), generalized regression neural network (GRNN), and adaptive neuro-fuzzy inference system (ANFIS) to model and predict in vitro Cannabis growth and development. Based on the results, GRNN had better performance than MLP or ANFIS and was consequently selected to link different optimization algorithms (genetic algorithm, biogeography-based optimization, interior search algorithm, and symbiotic organisms search) for prediction of optimal light levels (quality/intensity) and sucrose concentration for various applications. Predictions of in vitro conditions to refine growth responses were subsequently tested in a validation experiment and data showed no significant differences between predicted optimized values and observed data. Thus, this study demonstrates the potential of machine learning and optimization algorithms to predict the most favourable light combinations and sucrose levels to elicit specific developmental responses. Based on these, recommendations of light and carbohydrate levels to promote specific developmental outcomes for in vitro Cannabis are suggested. Ultimately, this work showcases the importance of light quality and carbohydrate supply in directing plant development as well as the power of machine learning approaches to investigate complex interactions in plant tissue culture.

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Section: Discussionmentioning

confidence: 99%

Comparative analysis of machine learning and evolutionary optimization algorithms for precision tissue culture ofCannabis sativa: Prediction and validation ofin vitroshoot growth and development based on the optimization of light and carbohydrate sources

Pepe

Hesami

Small³

et al. 2021

Preprint

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“…The studies of Piunno et al [48], Grulichová and Mendel [63], Lata et al [54], and Lata et al [50] illustrate the application of charcoal for this purpose but, concomitant to this, charcoal leads to the adsorption of PGRs, changing the intracellular phytohormone balances of plants, encouraging the establishment of root initials and extension of lateral roots [64]. Unlike traditional micropropagation, this method re-uses the same rooted basal stem section of the initial explant over several apical tip removal cycles, resulting in a higher number of shoot tips None [67] Abbreviations: BA/BAP-6-benzylaminopurine, H2SO4-sulphuric acid, IAA-indole-3-acetic acid, IBA-indole-3-butyric acid, KIN-kinetin, MS-Murashige and Skoog, mT-meta-Topolin, NAA-1naphthaleneacetic acid, NaCl-sodium chloride, NaOCl-sodium hypochlorite, PGR-plant growth regulator, RITA-temporary immersion system for tissue culture, TDZ-thidiazuron, ZEA-zeatin, and 4-CPPU-forchlorfenuron. * The list in this table may not be completely exhaustive.…”

Section: Direct Organogenesis Of Cannabis Sativamentioning

confidence: 99%

“…Nowadays, the influence of physical conditions that may control organogenetic responses in tissue cultured plants of Cannabis, especially those that are associated with light conditions, is becoming more apparent. Ventilation of the culture vessels for micropropagation in Cannabis and other plant genera is thought to be important in producing true-to-type plantlets that are can be readily acclimatised [67,78]. The benefits of investigating physical factors are many.…”

Section: Indirect Organogenesis Of Cannabis Sativamentioning

confidence: 99%

“…The benefits of investigating physical factors are many. Some of these include Cannabis plantlets that are better able to maintain photosynthesis, grow in microenvironments with reduced humidity, and perform gaseous exchange more efficiently, thereby closely resembling plants that are grown ex vitro [67]. To investigate the influence of physical factors, Murphy and Adelberg [67] tested the hedging technique, which involves the removal of the apical meristem, over several subcultures using C. sativa 'US Nursery Cherry 1', and in this study, the medium was used without the inclusion of PGRs to prevent genetic drift over several continuous culture passages.…”

Section: Indirect Organogenesis Of Cannabis Sativamentioning

confidence: 99%

“…Some of these include Cannabis plantlets that are better able to maintain photosynthesis, grow in microenvironments with reduced humidity, and perform gaseous exchange more efficiently, thereby closely resembling plants that are grown ex vitro [67]. To investigate the influence of physical factors, Murphy and Adelberg [67] tested the hedging technique, which involves the removal of the apical meristem, over several subcultures using C. sativa 'US Nursery Cherry 1', and in this study, the medium was used without the inclusion of PGRs to prevent genetic drift over several continuous culture passages. In non-vented culture jars, higher light intensities were important to maintain a vigorously growing and regenerating culture stock but ventilation in vitro, allowing for better gaseous exchange, assisted with the production of healthier plantlets which could easily be acclimated that also had lower plantlet mortalities ex vitro.…”

Section: Indirect Organogenesis Of Cannabis Sativamentioning

confidence: 99%

See 2 more Smart Citations

Cannabis sativa: From Therapeutic Uses to Micropropagation and Beyond

Adams

Malatsi

Makunga

2021

Plants

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The development of a protocol for the large-scale production of Cannabis and its variants with little to no somaclonal variation or disease for pharmaceutical and for other industrial use has been an emerging area of research. A limited number of protocols have been developed around the world, obtained through a detailed literature search using web-based database searches, e.g., Scopus, Web of Science (WoS) and Google Scholar. This article reviews the advances made in relation to Cannabis tissue culture and micropropagation, such as explant choice and decontamination of explants, direct and indirect organogenesis, rooting, acclimatisation and a few aspects of genetic engineering. Since Cannabis micropropagation systems are fairly new fields, combinations of plant growth regulator experiments are needed to gain insight into the development of direct and indirect organogenesis protocols that are able to undergo the acclimation stage and maintain healthy plants desirable to the Cannabis industry. A post-culture analysis of Cannabis phytochemistry after the acclimatisation stage is lacking in a majority of the reviewed studies, and for in vitro propagation protocols to be accepted by the pharmaceutical industries, phytochemical and possibly pharmacological research need to be undertaken in order to ascertain the integrity of the generated plant material. It is rather difficult to obtain industrially acceptable micropropagation regimes as recalcitrance to the regeneration of in vitro cultured plants remains a major concern and this impedes progress in the application of genetic modification technologies and gene editing tools to be used routinely for the improvement of Cannabis genotypes that are used in various industries globally. In the future, with more reliable plant tissue culture-based propagation that generates true-to-type plants that have known genetic and metabolomic integrity, the use of genetic engineering systems including “omics” technologies such as next-generation sequencing and fast-evolving gene editing tools could be implemented to speed up the identification of novel genes and mechanisms involved in the biosynthesis of Cannabis phytochemicals for large-scale production.

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Novel approaches to micropropagation, rooting and acclimatization

Adelberg¹,

Aitken²

2023

Acta Hortic.

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Physical factors increased quantity and quality of micropropagated shoots of Cannabis sativa L. in a repeated harvest system with ex vitro rooting

Cited by 8 publications

References 27 publications

Comparative analysis of machine learning and evolutionary optimization algorithms for precision tissue culture ofCannabis sativa: Prediction and validation ofin vitroshoot growth and development based on the optimization of light and carbohydrate sources

Comparative analysis of machine learning and evolutionary optimization algorithms for precision tissue culture ofCannabis sativa: Prediction and validation ofin vitroshoot growth and development based on the optimization of light and carbohydrate sources

Cannabis sativa: From Therapeutic Uses to Micropropagation and Beyond

Novel approaches to micropropagation, rooting and acclimatization

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