Modeling and Optimizing Culture Medium Mineral Composition for in vitro Propagation of Actinidia arguta

Impact of salt strength on in vitro propagation and rebaudioside A content in Stevia rebaudiana under semi-solid and liquid MS media

Stevia rebaudiana (Bertoni), commonly known as stevia, is a sought-after natural sweetener, but its conventional propagation methods are slow and inefficient. This study aims to enhance the in vitro culture for stevia by investigating the impact of different Murashige and Skoog (MS) medium salt strengths and plant growth hormones on growth and rebaudioside A content. Apical bud-containing shoot segments were used as explants and cultured on various semi-solid and liquid MS media formulations, incorporating cytokinins (BAP and Kin), auxins (NAA and IAA), and different MS major salt concentrations (MS full, ½ MS, and ¼ MS). Assessments of shoot growth parameters, root formation, and HPLC analysis for rebaudioside A content were conducted. The optimal conditions for in vitro growth was found to be in the ¼ MS + Kin 3 mg/L + NAA 0.1 mg/L (semi-solid) medium, resulting in significantly improved shoot growth and enhanced 30.04% rebaudioside A content. Genetic fidelity of regenerated plants was confirmed using RAPD and ISSR markers. These findings offer valuable insights for optimizing in vitro propagation of stevia and potentially enhancing rebaudioside A content.

Optimizing PGRs for in vitro shoot proliferation of pomegranate with bayesian-tuned ensemble stacking regression and NSGA-II: a comparative evaluation of machine learning models

BACKGROUND

The process of optimizing in vitro shoot proliferation is a complicated task, as it is influenced by interactions of many factors as well as genotype. This study investigated the role of various concentrations of plant growth regulators (zeatin and gibberellic acid) in the successful in vitro shoot proliferation of three Punica granatum cultivars ('Faroogh', 'Atabaki' and 'Shirineshahvar'). Also, the utility of five Machine Learning (ML) algorithms-Support Vector Regression (SVR), Random Forest (RF), Extreme Gradient Boosting (XGB), Ensemble Stacking Regression (ESR) and Elastic Net Multivariate Linear Regression (ENMLR)-as modeling tools were evaluated on in vitro multiplication of pomegranate. A new automatic hyperparameter optimization method named Adaptive Tree Pazen Estimator (ATPE) was developed to tune the hyperparameters. The performance of the models was evaluated and compared using statistical indicators (MAE, RMSE, RRMSE, MAPE, R and R2), while a specific Global Performance Indicator (GPI) was introduced to rank the models based on a single parameter. Moreover, Non‑dominated Sorting Genetic Algorithm‑II (NSGA‑II) was employed to optimize the selected prediction model.

RESULTS

The results demonstrated that the ESR algorithm exhibited higher predictive accuracy in comparison to other ML algorithms. The ESR model was subsequently introduced for optimization by NSGA‑II. ESR-NSGA‑II revealed that the highest proliferation rate (3.47, 3.84, and 3.22), shoot length (2.74, 3.32, and 1.86 cm), leave number (18.18, 19.76, and 18.77), and explant survival (84.21%, 85.49%, and 56.39%) could be achieved with a medium containing 0.750, 0.654, and 0.705 mg/L zeatin, and 0.50, 0.329, and 0.347 mg/L gibberellic acid in the 'Atabaki', 'Faroogh', and 'Shirineshahvar' cultivars, respectively.

CONCLUSIONS

This study demonstrates that the 'Shirineshahvar' cultivar exhibited lower shoot proliferation success compared to the other cultivars. The results indicated the good performance of ESR-NSGA-II in modeling and optimizing in vitro propagation. ESR-NSGA-II can be applied as an up-to-date and reliable computational tool for future studies in plant in vitro culture.

Embryo Rescue in Plant Breeding

Embryo rescue (ER) techniques are among the oldest and most successful in vitro tissue culture protocols used with plant species. ER refers to a series of methods that promote the development of an immature or lethal embryo into a viable plant. Intraspecific, interspecific, or intergeneric crosses allow the introgression of important alleles of agricultural interest from wild species, such as resistance or tolerance to abiotic and biotic stresses or morphological traits in crops. However, pre-zygotic and post-zygotic reproductive barriers often present challenges in achieving successful hybridization. Pre-zygotic barriers manifest as incompatibility reactions that hinder pollen germination, pollen tube growth, or penetration into the ovule occurring in various tissues, such as the stigma, style, or ovary. To overcome these barriers, several strategies are employed, including cut-style or graft-on-style techniques, the utilization of mixed pollen from distinct species, placenta pollination, and in vitro ovule pollination. On the other hand, post-zygotic barriers act at different tissues and stages ranging from early embryo development to the subsequent growth and reproduction of the offspring. Many crosses among different genera result in embryo abortion due to the failure of endosperm development. In such cases, ER techniques are needed to rescue these hybrids. ER holds great promise for not only facilitating successful crosses but also for obtaining haploids, doubled haploids, and manipulating the ploidy levels for chromosome engineering by monosomic and disomic addition as well substitution lines. Furthermore, ER can be used to shorten the reproductive cycle and for the propagation of rare plants. Additionally, it has been repeatedly used to study the stages of embryonic development, especially in embryo-lethal mutants. The most widely used ER procedure is the culture of immature embryos taken and placed directly on culture media. In certain cases, the in vitro culture of ovule, ovaries or placentas enables the successful development of young embryos from the zygote stage to maturity.

Development, Management and Utilization of a Kiwifruit (Actinidia spp.) In Vitro Collection: A New Zealand Perspective

The New Zealand Institute for Plant and Food Research Limited (PFR) supports a large kiwifruit breeding program that includes more than twenty Actinidia species. Almost all the kiwifruit accessions are held as field collections across a range of locations, though not all plants are at multiple locations. An in vitro collection of kiwifruit in New Zealand was established upon the arrival of Pseudomonas syringae pv. Actinadiae-biovar 3 in 2010. The value of an in vitro collection has been emphasized by restrictions on importation of new plants into New Zealand and increasing awareness of the array of biotic and abiotic threats to field collections. The PFR in vitro collection currently holds about 450 genotypes from various species, mostly A. chinensis var. chinensis and A. chinensis var. deliciosa. These collections and the in vitro facilities are used for germplasm conservation, identification of disease-free plants, reference collections and making plants available to users. Management of such a diverse collection requires appropriate protocols, excellent documentation, training, sample tracking and databasing and true-to-type testing, as well as specialized facilities and resources. This review also discusses the New Zealand biosecurity and compliance regime governing kiwifruit plant movement, and how protocols employed by the facility aid the movement of pathogen-free plants within and from New Zealand.

History, Phylogeny, Biodiversity, and New Computer-Based Tools for Efficient Micropropagation and Conservation of Pistachio (Pistacia spp.) Germplasm

The word "pstk" [pistag], used in the ancient Persian language, is the linguistic root from which the current name "pistachio", used worldwide, derives. The word pistachio is generally used to designate the plants and fruits of a single species: Pistacia vera L. Both the plant and its fruits have been used by mankind for thousands of years, specifically the consumption of its fruits by Neanderthals has been dated to about 300,000 years ago. Native to southern Central Asia (including northern Afghanistan and northeastern Iran), its domestication and cultivation occurred about 3000 years ago in this region, spreading to the rest of the Mediterranean basin during the Middle Ages and finally being exported to America and Australia at the end of the 19th century. The edible pistachio is an excellent source of unsaturated fatty acids, carbohydrates, proteins, dietary fiber, vitamins, minerals and bioactive phenolic compounds that help promote human health through their antioxidant capacity and biological activities. The distribution and genetic diversity of wild and domesticated pistachios have been declining due to increasing population pressure and climatic changes, which have destroyed natural pistachio habitats, and the monoculture of selected cultivars. As a result, the current world pistachio industry relies mainly on a very small number of commercial cultivars and rootstocks. In this review we discuss and summarize the current status of: etymology, origin, domestication, taxonomy and phylogeny by molecular analysis (RAPID, RFLP, AFLP, SSR, ISSR, IRAP, eSSR), main characteristics and world production, germplasm biodiversity, main cultivars and rootstocks, current conservation strategies of both conventional propagation (seeds, cutting, and grafting), and non-conventional propagation methods (cryopreservation, slow growth storage, synthetic seed techniques and micropropagation) and the application of computational tools (Design of Experiments (DoE) and Machine Learning: Artificial Neural Networks, Fuzzy logic and Genetic Algorithms) to design efficient micropropagation protocols for the genus Pistacia.

Micropropagation of plants of the genus Actinidia Lindl

Purpose. Analysis of plant micropropagation technologies for the creation of viable interspecific hybrids and varieties of Actinidia Lindl. Methods. General scientific – hypothesis, experiment, observation, analysis, synthesis method for drawing conclusions. Results. The introduction of in vitro technologies is now becoming the dominant commercial method of large-scale and rapid production of seedlings with stable inheritance of variety traits, high multiplication rate, preservation of economically valuable traits in the absence of production seasonality and time constraints. In addition to reproduction, the breeding process is also accelerated, including mutagenesis and hybridization. It is important to obtain not only a sterile explant, but also a morphogenically active one, that is, a plant that takes roots and subsequently regenerates in vitro. The best in terms of decontamination efficiency is the method of treatment with hypochlorite and the addition of PPM biocide to the nutrient medium, but under these conditions, the lowest survival of explants in all samples was noted. The efficiency of introduction into aseptic culture at the first stage of micropropagation is also affected by the biological characteristics of the primary explants. In studies with nutrient media for A. arguta, it was found that of the elements of mineral nutrition, only 11 ions are necessary for life: five macro- (N, K, P, Mg, S) and six microelements (Cl, Fe, B, Mo, Na, I). Plants in vitro have a lower dry matter content and a greater amount of moisture, including free moisture, which is quickly lost when the water balance is disturbed. Conclusions. The abi­lity to regenerate is more pronounced in the species A. chinensis and A. deliciosa, and to a lesser extent in A. arguta. For A. chinensis, the use of hydroponic technology for the adaptation of regenerants at the ex vitro stage is effective.

Incorporation of Organic Growth Additives to Enhance In Vitro Tissue Culture for Producing Genetically Stable Plants

The growing demand for native planting material in ecological restoration and rehabilitation for agro-silvo-pastoral ecosystems has resulted in a major global industry in their sourcing, multiplication, and sale. Plant tissue culture is used for producing high-quality, disease-free, and true-to-type plants at a fast rate. Micropropagation can help to meet the increasing demand for planting material and afforestation programs. However, in vitro plant propagation is an expensive technique compared to conventional methods using suckers, seeds, and cuttings. Therefore, adopting measures to lower production costs without compromising plant quality is essential. This can be achieved by improving the culture media composition. Incorporating organic growth additives can stimulate tissue growth and increase the number of shoots, leaves, and roots in culture media. Organic growth supplementation speeds up the formation and development of cultures and yields vigorous plants. Plant regeneration from meristems (shoot tips and axillary buds) is a reliable way to produce true-to-type plants compared with callus and somatic embryogenesis regeneration, but in vitro culture environments can be mutagenic. Therefore, detecting somaclonal variations at an early stage of development is considered crucial in propagating plants. The genetic stability of in vitro regenerated plants needs to be ascertained by using DNA-based molecular markers. This review aims to provide up-to-date research progress on incorporating organic growth additives to enhance in vitro tissue culture protocols and to emphasize the importance of using PCR-based molecular markers such as RAPD, ISSR, SSR, and SCoT. The review was assessed based on the peer-reviewed works published in scientific databases including Science Direct, Scopus, Springer, JSTOR, onlinelibrary, and Google Scholar.

Innovation in the Breeding of Common Bean Through a Combined Approach of in vitro Regeneration and Machine Learning Algorithms

Common bean is considered a recalcitrant crop for in vitro regeneration and needs a repeatable and efficient in vitro regeneration protocol for its improvement through biotechnological approaches. In this study, the establishment of efficient and reproducible in vitro regeneration followed by predicting and optimizing through machine learning (ML) models, such as artificial neural network algorithms, was performed. Mature embryos of common bean were pretreated with 5, 10, and 20 mg/L benzylaminopurine (BAP) for 20 days followed by isolation of plumular apice for in vitro regeneration and cultured on a post-treatment medium containing 0.25, 0.50, 1.0, and 1.50 mg/L BAP for 8 weeks. Plumular apice explants pretreated with 20 mg/L BAP exerted a negative impact and resulted in minimum shoot regeneration frequency and shoot count, but produced longer shoots. All output variables (shoot regeneration frequency, shoot counts, and shoot length) increased significantly with the enhancement of BAP concentration in the post-treatment medium. Interaction of the pretreatment × post-treatment medium revealed the need for a specific combination for inducing a high shoot regeneration frequency. Higher shoot count and shoot length were achieved from the interaction of 5 mg/L BAP × 1.00 mg/L BAP followed by 10 mg/L BAP × 1.50 mg/L BAP and 20 mg/L BAP × 1.50 mg/L BAP. The evaluation of data through ML models revealed that R2 values ranged from 0.32 to 0.58 (regeneration), 0.01 to 0.22 (shoot counts), and 0.18 to 0.48 (shoot length). On the other hand, the mean squared error values ranged from 0.0596 to 0.0965 for shoot regeneration, 0.0327 to 0.0412 for shoot count, and 0.0258 to 0.0404 for shoot length from all ML models. Among the utilized models, the multilayer perceptron model provided a better prediction and optimization for all output variables, compared to other models. The achieved results can be employed for the prediction and optimization of plant tissue culture protocols used for biotechnological approaches in a breeding program of common beans.

Efficient regeneration of mature castanopsis hystrix from in vitro stem explants

Castanopsis hystrix is one of the main timber trees grown in China. However, severe shortage of natural seeds and the difficulty of explant regeneration has limited seedling supply. As such, there is a need for research on asexual multiplication of C. hystrix. This study established a rapid propagation technology system for C. hystrix genotypes, including explant treatment, proliferation, and rooting. HZ (a modified MS medium) supplemented with 4.4 μM BA and 0.5 μM IBA was found to be the optimal medium for shoot sprouting. The maximum proliferation coefficient and the number of effective shoots was obtained on HZ medium supplemented with 2.6 μM BA and 1.0 μM IBA, were 3.00 and 5.63, respectively. A rooting rate of 83.33% was achieved using half-strength HZ medium supplemented with 3.2 μM NAA. Adding vitamin C (80 mg⋅l-1) for 7 days in a dark environment reduced the browning rate, while increasing the proliferation rate. Additionally, through cytological observation, we established how and where adventitious roots occur. The survival rate of transplanted plantlets was > 90%. This is the first report of an in vitro regeneration technique that uses stem segments of mature C. hystrix as explants.

Zinc Oxide Nanoparticles (ZnO NPs), Biosynthesis, Characterization and Evaluation of Their Impact to Improve Shoot Growth and to Reduce Salt Toxicity on Salvia officinalis In Vitro Cultivated

Green synthesis of zinc oxide nanoparticles (ZnO NPs) using plant extracts have recently attracted considerable attention due to their environmental protection benefits and their easy and low cost of fabrication. In the current study, ZnO NPS were synthesized using the aqueous extract of Ochradenus arabicus as a capping and reducing agent. The obtained ZnO NPs were firstly characterized using ultraviolet visible (UV-Vis) spectroscopy, Fourier transform infrared (FTIR), transmission electron microscope (TEM), X-ray diffraction (XRD), energy dispersive X-ray absorption (EDX), zeta potential, and zeta size. All these techniques confirmed the characteristic features of the biogenic synthesized ZnO NPs. Then, ZnO NPs were evaluated for their effects on morphological, biochemical, and physiological parameters of Salvia officinalis cultured in Murashige and Skoog medium containing 0, 75, 100, and 150 mM of NaCl. The results showed that ZnO NPs at a dose of 10 mg/L significantly increased the shoot number, shoot fresh weight, and shoot dry weight of Salvia officinalis subjected or not to the salt stress. For the shoot length, a slight increase of 4.3% was recorded in the plant treated by 150 mM NaCl+10 mg/L ZnO NPs compared to the plant treated only with 150 mM of NaCl. On the other hand, without NaCl, the application of both concentrations 10 mg/L and 30 mg/L of ZnO NPs significantly improved the total chlorophyll content by 30.3% and 21.8%, respectively. Under 150 mM of NaCl, the addition of 10 mg/L of ZnO NPs enhanced the total chlorophyll by 1.5 times, whilst a slight decrease of total chlorophyll was recorded in the plants treated by 150 mM NaCl + 30 mg/L ZnO NPs. Additionally, ZnO NPs significantly enhance the proline accumulation and the antioxidative enzyme activities of catalase (CAT), superoxide dismutase (SOD), and glutathione reductase (GR) in plants under salinity. Our findings revealed that green synthesized ZnO NPs, especially at a dose of 10 mg/L, play a crucial role in growth enhancement and salt stress mitigation. Hence, this biosynthesized ZnO NPs at a concentration of 10 mg/L can be considered as effective nanofertilizers for the plants grown in salty areas.

Artificial Neural Networks Elucidated the Essential Role of Mineral Nutrients versus Vitamins and Plant Growth Regulators in Achieving Healthy Micropropagated Plants

The design of an adequate culture medium is an essential step in the micropropagation process of plant species. Adjustment and balance of medium components involve the interaction of several factors, such as mineral nutrients, vitamins, and plant growth regulators (PGRs). This work aimed to shed light on the role of these three components on the plant growth and quality of micropropagated woody plants, using Actinidia arguta as a plant model. Two experiments using a five-dimensional experimental design space were defined using the Design of Experiments (DoE) method, to study the effect of five mineral factors (NH₄NO₃, KNO₃, Mesos, Micros, and Iron) and five vitamins (Myo-inositol, thiamine, nicotinic acid, pyridoxine, and vitamin E). A third experiment, using 20 combinations of two PGRs: BAP (6-benzylaminopurine) and GA₃ (gibberellic acid) was performed. Artificial Neural Networks (ANNs) algorithms were used to build models with the whole database to determine the effect of those components on several growth and quality parameters. Neurofuzzy logic allowed us to decipher and generate new knowledge on the hierarchy of some minerals as essential components of the culture media over vitamins and PRGs, suggesting rules about how MS basal media formulation could be modified to assess the quality of micropropagated woody plants.

Genetic resources and features of clonal micropropagation of Far Eastern species of Actinidia

The unique collection samples of the Far Eastern species of the genus Actinidia Lindley preserved in Federal Horticultural Center for Breeding, Agrotechnology and Nursery were analysed. The in vitro collection of Actinidia has been formed since 2005 in Tsitsin Main Botanical Garden of Russian Academy of Sciences and currently includes more than 40 cultivars belonging to 3 species of Actinidia: A. kolomikta (Rupr. еt Maxim) Maxim., A. arguta (Siebold et Zucc.) Planch. et Miq., and A. polygama (Siebold et Zucc.) Maxim. Easily reproducible, dependable method for clonal micropropagation of promising selected genotypes of Actinidia was optimized. It has been established regeneration features for the studied species of the genus Actinidia at the stage of micropropagation. A. kolomikta was characterized by a lower morphogenetic potential (multiplication coefficient 5.0) compared with other studied species. A. arguta and A. polygama were characterized by high multiplication coefficients, but no significant difference between them was present (8.0 and 7.7, respectively). The features of morphogenesis of male and female forms of A. kolomikta were revealed. The cultivars of the female forms had the highest multiplication coefficient (‘Universitetskaya’ 5.2, ‘Prelestnaya’ 5.2) compared with the male and bisexual forms (‘Adam’ 4.3 and ‘Dr. Szymanowski’ 4.3). The Quorin-Lepoivre nutrient medium supplemented with 6-Benzylaminopurine at a concentration of 0.5…1.0 mg L−1 was found to be effective at the micropropagation stage, and the use of β-indole acetic acid at a concentration 0.5…1.0 mg L−1 was better at the rooting stage.

The Combination of Untargeted Metabolomics and Machine Learning Predicts the Biosynthesis of Phenolic Compounds in Bryophyllum Medicinal Plants (Genus Kalanchoe)

Phenolic compounds constitute an important family of natural bioactive compounds responsible for the medicinal properties attributed to Bryophyllum plants (genus Kalanchoe, Crassulaceae), but their production by these medicinal plants has not been characterized to date. In this work, a combinatorial approach including plant tissue culture, untargeted metabolomics, and machine learning is proposed to unravel the critical factors behind the biosynthesis of phenolic compounds in these species. The untargeted metabolomics revealed 485 annotated compounds that were produced by three Bryophyllum species cultured in vitro in a genotype and organ-dependent manner. Neurofuzzy logic (NFL) predictive models assessed the significant influence of genotypes and organs and identified the key nutrients from culture media formulations involved in phenolic compound biosynthesis. Sulfate played a critical role in tyrosol and lignan biosynthesis, copper in phenolic acid biosynthesis, calcium in stilbene biosynthesis, and magnesium in flavanol biosynthesis. Flavonol and anthocyanin biosynthesis was not significantly affected by mineral components. As a result, a predictive biosynthetic model for all the Bryophyllum genotypes was proposed. The combination of untargeted metabolomics with machine learning provided a robust approach to achieve the phytochemical characterization of the previously unexplored species belonging to the Bryophyllum subgenus, facilitating their biotechnological exploitation as a promising source of bioactive compounds.

Machine Learning-Mediated Development and Optimization of Disinfection Protocol and Scarification Method for Improved In Vitro Germination of Cannabis Seeds

In vitro seed germination is a useful tool for developing a variety of biotechnologies, but cannabis has presented some challenges in uniformity and germination time, presumably due to the disinfection procedure. Disinfection and subsequent growth are influenced by many factors, such as media pH, temperature, as well as the types and levels of contaminants and disinfectants, which contribute independently and dynamically to system complexity and nonlinearity. Hence, artificial intelligence models are well suited to model and optimize this dynamic system. The current study was aimed to evaluate the effect of different types and concentrations of disinfectants (sodium hypochlorite, hydrogen peroxide) and immersion times on contamination frequency using the generalized regression neural network (GRNN), a powerful artificial neural network (ANN). The GRNN model had high prediction performance (R² > 0.91) in both training and testing. Moreover, a genetic algorithm (GA) was subjected to the GRNN to find the optimal type and level of disinfectants and immersion time to determine the best methods for contamination reduction. According to the optimization process, 4.6% sodium hypochlorite along with 0.008% hydrogen peroxide for 16.81 min would result in the best outcomes. The results of a validation experiment demonstrated that this protocol resulted in 0% contamination as predicted, but germination rates were low and sporadic. However, using this sterilization protocol in combination with the scarification of in vitro cannabis seed (seed tip removal) resulted in 0% contamination and 100% seed germination within one week.

Computer-Based Tools Unmask Critical Mineral Nutrient Interactions in Hoagland Solution for Healthy Kiwiberry Plant Acclimatization

The aim of this study was to better understand the response of ex vitro acclimatized plants grown to a set of mineral nutrient combinations based on Hoagland solution. To reach that, two computer-based tools were used: the design of experiments (DOE) and a hybrid artificial intelligence technology that combines artificial neural networks with fuzzy logic. DOE was employed to create a five-dimensional IV-design space by categorizing all macroelements and one microelement (copper) of Hoagland mineral solution, reducing the experimental design space from 243 (35) to 19 treatments. Typical growth parameters included hardening efficiency (Hard), newly formed shoot length (SL), total leaf number (TLN), leaf chlorophyll content (LCC), and leaf area (LA). Moreover, three physiological disorders, namely, leaf necrosis (LN), leaf spot (LS), and curled leaf (CL), were evaluated for each treatment (mineral formulation). All the growth parameters plus LN were successfully modeled using neuro-fuzzy logic with a high train set R 2 between experimental and predicted values (72.67 < R 2 < 98.79). The model deciphered new insights using different sets of "IF-THEN" rules, pinpointing the positive role of Mg2+ and Ca2+ to improve Hard, SL, TLN, and LA and alleviate LN but with opposite influences on LCC. On the contrary, TLN and LCC were negatively affected by the addition of NO3 - into the media, while NH4 + in complex interaction with Cu2+ or Mg2+ positively enhanced SL, TLN, LCC, and LA. In our opinion, the approach and results achieved in this work are extremely fruitful to understand the effect of Hoagland mineral nutrients on the healthy growth of ex vitro acclimatized plants, through identifying key factors, which favor growth and limit physiological abnormalities.

Comparative Analysis of Machine Learning and Evolutionary Optimization Algorithms for Precision Micropropagation of Cannabis sativa: Prediction and Validation of in vitro Shoot Growth and Development Based on the Optimization of Light and Carbohydrate Sources

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 analyzing 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 μmol/m2/s in combination with sucrose concentrations ranging from 1 to 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 (GA), biogeography-based optimization (BBO), interior search algorithm (ISA), and symbiotic organisms search (SOS)] 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 favorable 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.

Treasuring the computational approach in medicinal plant research

Medicinal plants serve as a valuable source of secondary metabolites since time immemorial. Computational Research in 21st century is giving more attention to medicinal plants for new drug design as pharmacological screening of bioactive compound was time consuming and expensive. Computational methods such as Molecular Docking, Molecular Dynamic Simulation and Artificial intelligence are significant Insilico tools in medicinal plant research. Molecular docking approach exploits the mechanism of potential phytochemicals into the target active site to elucidate its interactions and biological therapeutic properties. MD simulation illuminates the dynamic behavior of biomolecules at atomic level with fine quality representation of biomolecules. Dramatical advancement in computer science is illustrating the biological mechanism via these tools in different diseases treatment. The advancement comprises speed, the system configuration, and other software upgradation to insights into the structural explanation and optimization of biomolecules. A probable shift from simulation to artificial intelligence has in fact accelerated the art of scientific study to a sky high. The most upgraded algorithm in artificial intelligence such as Artificial Neural Networks, Deep Neural Networks, Neuro-fuzzy Logic has provided a wide opportunity in easing the time required in classical experimental strategy. The notable progress in computer science technology has paved a pathway for understanding the pharmacological functions and creating a roadmap for drug design and development and other achievement in the field of medicinal plants research. This review focus on the development and overview in computational research moving from static molecular docking method to a range of dynamic simulation and an advanced artificial intelligence such as machine learning.