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Article

Growth Characteristics of Dracocephalum moldavica L. in Relation to Density for Sustainable Cropping Technology Development

by
Cristina Moldovan
1,
Sorina Nițu (Năstase)
2,*,
Manuela Hermeziu
2,
Roxana Vidican
1,
Mignon Sandor
3,*,
Ștefania Gâdea
1,
Adriana David
4,*,
Valentina Ancuța Stoian
1,
Sorin Daniel Vâtcă
1 and
Vlad Stoian
1
1
Department of Plant Culture, Faculty of Agriculture, University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Calea Mănăstur 3-5, 400372 Cluj-Napoca, Romania
2
National Institute of Research and Development for Potato and Sugar Beet Brașov, 2 Fundăturii St., 500470 Brașov, Romania
3
Department of Engineering and Environmental Protection, Faculty of Agriculture, University of Agricultural Sciences and Veterinary Medicine, 400372 Cluj-Napoca, Romania
4
Department of Technical Sciences and Soil Sciences, Faculty of Agriculture, University of Agricultural Sciences and Veterinary Medicine, 400372 Cluj-Napoca, Romania
*
Authors to whom correspondence should be addressed.
Agriculture 2022, 12(6), 789; https://doi.org/10.3390/agriculture12060789
Submission received: 10 May 2022 / Revised: 26 May 2022 / Accepted: 27 May 2022 / Published: 30 May 2022
(This article belongs to the Section Crop Production)
Browse Figures
Versions Notes

Abstract

:
Medicinal and aromatic plants hold a high share of interest in Romania. To offset the harvesting of spontaneous flora and ensure the sustainable conservation of natural resources, the cropping of highly valuable plants of interest represents a priority for the current agricultural system. This study was conducted due to the need for more balance in species exploitation. Therefore, it assessed the emergence dynamics, leaf appearance, growth and development of the plants depending on row spacing and plant distance. The research was conducted at the INCDCSZ Brașov, within the Technology Department, Laboratory of Medicinal and Aromatic Plants. The density of planting is the most important factor. Plants sown in continuous rows showed the highest yields of fresh and dry herbs, especially when the distance between the rows was set to 25 cm. Row-by-row distances of 50 cm ensure average values for all growth and development parameters. An increase in the row-by-row distance up to 70 cm drastically reduced the dry biomass up to 7.89 t ha−1 in continuous rows, followed by a 2 and 2.5 t ha−1 decrease for 15 cm and 25 cm plant-by-plant distances, respectively. Continuous row planting and a 25 cm row-by-row distance negligibly reduce the climate impact on growth and development. Greater spaces between plants leads to an average increase in individual development, but with a decrease in the total potential yield.

1. Introduction

Medicinal plants impact our everyday existence by playing a vital role in the functioning of biochemical processes [1]. The market for medicinal plants in the European Union has experienced increased interest in terms of rapidly grown medicinal and aromatic plants (MAPs) over the past decade [2]. Approximately 80% of the world’s population depends on the secondary metabolites of different medicinal and aromatic plants [3]. Romania has shown significant interest in the MAP market, demonstrated by high demand for new, valuable, quality crops. This is because traditional medicine is very popular and is still commonly used, and herein MAPs have a central role [4]. Herbal species for cropping should be selected first due to their range of potential uses, and then the plants’ climatic requirements and different adaptation peculiarities to certain areas should be considered. With this in mind, increased interest has been shown in the development of Dracocephalum moldavica L. in Romania, including its specific requirements in terms of field conditions. Also known as dragonhead, Moldavian balm, or Moldavian dragonhead, D. moldavica belongs to the Lamiaceae family and is an annual herbaceous plant [5,6,7] with green foliage and the pleasant smell of aromatic balm [8]. Native to central regions of Asia, the plant is also found in central and eastern European areas [9]. Studies performed on the medicinal flora of Romania [10] showed that D. moldavica is a rare species in the spontaneous Romanian flora, being found in very small areas of Moldova, Transylvania, and southern Oltenia. The genus Dracocephalum comprises about 40 species [11]. Moldavian dragonhead is found in Siberia and the Himalayan massif (where it originates) as well as in North America [12,13]. D. moldavica has attractive blue or white flowers and aromatic lemon-scented foliage [14]. In Romania, monks used the leaves of the plant to obtain “lemon balm water” [15], from which the term “monastery basil” originated; it is traditionally used for medicinal and aromatic purposes [16]. D. moldavica is an annual, herbaceous, bushy-looking species: the roots are thin, hairy, and brown; the stem is straight, strongly branched at the base, slightly hairy, and reddish in color; the plants reach a height of 60–100 cm; the leaves are lanceolate elongated, opposite, with a short petiole and crenate edges; the flowers are blue-purple or white, are grouped in whorls (specific to the family Lamiaceae); and the fruits are tetranucleate, ovoid, and brown-colored.
In the last five years, Romania has experienced significant changes to areas cropped with medicinal plants; in 2016, the largest area cultivated with medicinal plants was around 4395 ha with a total production of 5627 t. These areas were reduced by 27% in 2017, with a drastic reduction of 61% between 2018 and 2020 [17]. The decrease in the cultivated area is due to the combined influence of several factors: primary producers of MAP receive small amounts of money for raw materials, which need to be further processed; MAP-specific technology is still underdeveloped and requires more studies in specific locations; and there are missing links in the processes between cultivation and the final consumer.
Most of the growth characteristics and the essential oils from D. moldavica are very much influenced by the distance between plants, which is typically around 40 cm, and the low biofertilization rate [8]. Linalool and geranial constitute the highest share in the essential oil composition [8]; moreover, a group of phenolic compounds make up the plant’s defense pathways, and are also relied upon for medicinal and food use [18]. The species is used in the manufacture of perfumes and soaps due to the high content of citral and geraniol, as well as in the flavoring of compotes and jams, spirits, syrups, and canned fish. Vitamin A can be obtained industrially from citral.
The plant is used in alternative medicine due to its sedative, analgesic, antirheumatic, antitumor, and antioxidant properties [19]. The plant is also used in the form of infusions or teas to calm colic and nervousness, induce peaceful sleep, and reduce vomiting in pregnant women. The establishment of D. moldavica is achieved using crop rotation, after the previous plants, which leaves the land free of weeds. Crop rotation for this species lasts 4–5 years, which can also assure the reduction of specific pests. A deep autumn plowing (25–30 cm) is recommended; the furrows are left under the action of frost and thawing, and in spring, a few days before sowing, the soil is crushed with a disc harrow, followed by a furrow harrow or combine [19].
Due to the current context of supplementing the increasing demand for MAPs, a study was conducted on technological factors over a period of three years. The main objective was the assessment of the row-by-row distance x plant-by-plant distance interaction on individual growth and development, and the potential fresh and dry matter yield. An additional objective of the study was to assess the stability of the cultivation of D. moldavica during all vegetation periods. The research was carried out to provide relevant technological information for both the increase of the cultivation efficiency and for the forecasting of the potential yield. The main argument is the need for the sustainable cultivation of MAP species in the context of newly emerging agricultural practices, which require more studies in the field.

2. Materials and Methods

2.1. Experimental Site

The experiment was conducted in the experimental field of the National Research and Development Institute for Potato and Sugar Beet, Brașov, in the Laboratory of Technology and Good Agricultural Practices at the Department of Medicinal and Aromatic Plants from Romania (45°42′ N and 25°45′ E, altitude 520 m) during the growth seasons 2016–2018. The soil type texture in the upper horizons is sandy and loamy-sandy, and at depth it is sandy-loamy, with a pH of 6.7. The soil of the experimental site contains 27% clay, 4.68% humus, total nitrogen 3.15%, P2O5 32.1 ppm (7.36 mg 100g soil−1), and K2O 105.1 ppm (12.67 mg 100g soil−1). The soil samples were analyzed using spectrophotometry and atomic absorption. The predominant soil is the cernoziomoid type, with a high humus content in the first horizon, a very high nitrogen supply in the first centimeters, and a moderate acid reaction of soil solution. The nitrification conditions are unbalanced because of the soil acid reaction.

2.2. Experimental Design and Biological Material

Before the experimental set-up, the soil was prepared by plowing, disking, shredding, and leveling before planting. These soil preparation techniques took place between 20 and 28 October 2015. Afterwards, in the spring of 2016, another milling cut was made to break the crust formed over the winter. The experiment was arranged in a split plot based on a randomized complete block design with three replications (Supplementary Figure S1). The seeds of D. moldavica were obtained from ARDS Secuieni (Neamț county, Romania). Factor A is considered to be the row-by-row distance (RR). D. moldavica was sown at 25 (A1), 50 (A2), and 70 (A3) cm RR. Factor B was the plant-by-plant distance for sowing on the same row (PP), which was: continuous rows (B1), 15 cm plant-by-plant (B2), and 25 cm plant-by-plant (B3). The combination of A × B factors resulted in nine variants, each of them showing a distinct number of plants emerged per m2: A1 × B1 = 60, A1 × B2 = 26.6; A1 × B3 = 16; A2 × B1 = 30; A2 × B2 = 13.33; A2 × B3 = 8; A3 × B1 = 21.5; A3 × B2 = 9.5; A3 × B3 = 5.7. The third factor considered was the experimental year when the sowing took place: 4 April 2016 (C1), 10 April 2017 (C2), and 4 April 2018 (C3). The interaction of the three factors resulted in a total of 27 variants being analyzed.
At the late flowering stage (85 days after planting), D. moldavica plant growth parameters such as plant height, number of stem branches, leaf dry weight, leaf area, and total biomass were recorded. At each sampling, all D. moldavica plants from a 50 cm length of the three middle rows of each plot were harvested by cutting at the soil surface. All plant parts were oven-dried at 70 °C for 48 h until a constant weight was reached to determine the dry weight (DW). At maturity (about four months after planting), the plants in an area of 1 m2 were harvested to determine the yield. The shoot length was measured: the roots and aerial parts were separated and the fresh shoot weight was immediately recorded.

2.3. Statistical Analysis

All data were analyzed using RStudio [20], under the platform RCore [21]. Prior to the data analysis, all values for each parameter were used to evaluate their normal distribution, with histogram functions being used for this procedure. ANOVA and post hoc LSD tests were performed with the solutions provided by the “agricolae” package [22], with the data being condensed into a combination of two-by-two factors—a method that permitted the full exploration of the data. This factor combination method was selected due to the technological requirements of the cultivated species, which were analyzed before the sowing procedures in each farm. Scatterplots were selected as a graphical procedure to analyze the overlap of the parameters in a one x one selection method. For each combination of parameters, the most probable cases were extracted, which were confirmed by the amount of data near to the regression linear model. These tests were performed by the “graphics” package (scatterplots) [21] and “Hmisc” [23] for the regression model. For the maximum visibility of the parameter assemblage, each factor’s influence was analyzed using clustering, a method that enables the comparison of multiple parameters due to their overall similarity. The package “ape” was used to perform the cluster analysis [24].

3. Results

3.1. Influence of Experimental Factors on D. moldavica Growth and Development Parameters

The ANOVA revealed a difference in the response of the plant parameters compared with the experimental factors (Supplementary Table S1). Plant height is sensitive to row-by-row and plant-by-plant distances, but it does not exhibit a significant reaction to the combined effect of the factors. The only exception, in this case, is the influence of climate (Factor C) when combined with the distance within rows. The branching potential of D. moldavica is affected slightly significantly by the climatic conditions. The plant’s particular weight and its potential to produce fresh and dry biomass are significantly affected by the planting distances. The most important factor for these three parameters is the within-rows distance, which has the maximum influence on the fresh biomass. All of these three parameters react differently to the combined effect of the experimental factors. Only climate affects weight in combination with within-rows distance. In contrast, fresh biomass production is influenced both by the distance of planting (row-by-row and plant-by-plant) and the RR distance in the context of different climatic conditions. For the dry biomass, the only other high-impact parameter is the planting distance.

3.2. Influence of Planting Density on D. moldavica Growth and Development Parameters

The further exploration of each bi-factor combination revealed the highest influence on the plant growth parameters (Table 1). As the ANOVA identified, the distance of planting (RR and PP) only affects the plant weight and its biomass production potential. The maximum weight recorded due to this factor combination is associated with the increase in the distance, both by RR and PP. The maximum recorded weight is over 352 g under the conditions of 70 cm × 25 cm RR × PP. Compared to this value, significantly lower values were recorded for plants planted continuously and at 15 cm (PP), but only in the case of 25 cm RR. Another interesting difference compared to this value is recorded in the case of 70 cm RR, but with continuous planting in rows. This combination decreases the weight potential by almost 1/3. Further analysis of the fresh biomass yield revealed that the plant’s individual weight is not relevant to producing a high biomass. The maximum recorded value in the field is 88.0 t ha−1 for the continuous planting in rows, and at 25 cm RR. Compared to this variant, a slightly lower value (14.0 t ha−1 decrease) is recorded in the same condition on row, but at 50 cm RR. The overall trend of this phenomenon shows a decrease of fresh biomass production as the distance within rows increases. The supplementary exploration of dry biomass production shows a similar trend, where plants in continuous rows perform better at any distance than almost all other within-row distances studied. The only exception is the 50 cm RR × 15 cm PP, which sustains a yield over 13.2 t ha−1, a value with no significant differences compared to the maximum.

3.3. Influence of Row-by-Row Distance and Experimental Year on D. moldavica Growth and Development Parameters

The three-year analysis of plant growth and yield potential is important to identify which is the most suitable row-by-row distance in different climatic conditions, or whether a specific distance will perform in a similar way independent of climate (Table 2). The plant height varies widely at intervals between 70.67 and 91.00 cm, with the maximum height recorded under the conditions of 25 cm RR in the third experimental year. In the same climatic conditions, only the plants with 50 cm RR show a similar height. The lowest value for height is recorded at the maximum row-by-row distance, under the conditions of the first experimental year. The overall assessment of this parameter shows the following suitability of row-by-row distances: 25 cm RR independent of the climatic conditions. The branching potential, even if the differences recorded are not significant, is important to assess the plant material stability independent of the climatic conditions. For this parameter, row-by-row distance is not important. Plant weight is a parameter for which the row-by-row distance and year has a reduced influence. There is only one variant (A3–C2) that has a weight over 370, significantly higher than plants at 25 cm RR, indifferent to the experimental year. In this case, all three years for 50 cm RR form a large group with insignificant differences. The case of 70 cm RR provides the average to highest values from the experiment, but this distance provides enough space for the development of the plants, which reduces the impact of climatic conditions. The analysis of fresh biomass variations, grouped by the interaction of row-by-row distance x year, shows a contrasting image compared to the weight analysis. The 25 cm RR stimulates the highest biomass yield, with an increasing trend from 2016 to 2018. The most stable group is the one planted at 50 cm RR, with the lowest differences between years. The 70 cm RR does not cross over with 40 t ha−1 fresh biomass, with a decrease lower than 30 t ha−1 under the 2018 conditions. The potential dry biomass yield follows the same trend as the fresh one, with an interval of more than 9.6 t ha−1 up to 12.7 t ha−1 for plants at 25 cm RR. The differences are 25% higher compared to the group of variants planted at 50 cm RR, and almost double compared to the 70 cm between-rows group. The lack of significant differences between years is an indicator of dry biomass yield stability in the context of specific planting distances.

3.4. Influence of Plant-by-Plant Distance and Experimental Year on D. moldavica Growth and Development Parameters

The number of branches is a well-established genetic characteristic, which was not influenced by the distance between rows, the distance between plants per row, or by climatic conditions (Table 3). Compared to this parameter, plant height is influenced by both factors, with a variation between different combinations of the factors. The maximum height is recorded at 50 cm PP, under the climatic conditions of 2018. An interesting observation is that this group has a medium height and is the lowest recorded in the entire experiment. The year 2017 is the most suitable for stimulating the maximum plant weight at 25 and 50 cm PP. The lowest values recorded are associated with continuous planting in rows, a technique that maintains this parameter at around 200 units independent of climatic conditions. Both years, 2016 and 2018, induce fluctuations in plant weight, which reduce the presence of clear significant differences compared to other variants. Both types of biomasses show differences induced by the combination of plant-by-plant distance and year of experimentation. The highest values recorded were for plants in continuous rows, with yields over 11.40 t ha−1 and a maximum of over 13.50 t ha−1 under the climatic conditions of the third year. For 25 and 50 cm PP, the climatic conditions of 2017 are the most suitable for biomass production, with up to 0.9 t ha−1 units compared to 2018 and almost 2 t ha−1 units compared to 2016.

3.5. Interrelations between D. moldavica Growth and Development Parameters

The scatterplots serve as a projection of two parameters for the detection of continuity in their relation and assessment of the entire stability (Figure 1a–d). Even if the branching is generally considered a stable characteristic, the height reached by plants is not stable, being highly influenced by the planting distance. The maximum height is reached by plants with only 9 branches, after this point decreasing by 5 cm on plants with 10–11 branches. The normal development (linear model) shows an increase of 2 cm in height for each branch developed by plants. The most stable area is 8–10 branches, where more than half of the data are organized around the linear model. The relation between the weight and height of plants shows a slightly decreasing trend as the height increases, with almost all data in the area of 70–85 cm in height. Values between 200 and 300 g for plant weight can be considered the closest to the general linear model. A similar projection between branching potential and plant weight shows that most samples analyzed in the area of 200–300 g per plant developed mostly on those with 8–10 branches. The process of fresh biomass drying shows a stable linear model, with a conversion factor of 17–18%, with normally distributed data for fresh biomass weights between 30,000 and 60,000 units.

3.6. Detection of Factor Importance on D. moldavica Growth and Development Based on Cluster Analysis

The application of cluster analysis permits the exploration of the full set of traits observed for each factor combination. The influence of row-by-row distance was analyzed through three clusters (Figure 2a–c), where the general impact of year and plant-by-plant distance was revealed. For the 25 cm RR (A1), the only stable group is determined as the 15 cm PP group, independent of the experimental year (Figure 2a). A distance of 25 cm PP produces similar data in the first two experimental years, but increases the height of the plants, which is still not associated with an increase in the other parameters related to yield potential. The continuous row planting shows a similar trend, with the first two years being very close, but a higher distance in the third experimental year. This was due to an increase of more than 20% in the biomass yield and the appearance of another supplementary branch on the plants. At 50 cm RR, there are some changes in the cluster image of the collected data (Figure 2b). There is a slight change between the first two years in the continuous (B1) planting and for the second and third year in the 15 cm PP variants. Both the B1_17 and B2_16 variants exhibit the lowest biomass yields and plant weight. An interesting case is the increase in plant height for samples taken in 2018 from the 25 cm PP variant, with 15–20 cm and one supplementary branch, which does not correlate with either biomass production or plant weight. The most representative cluster is the one that assembled variants at 70 cm RR (Figure 2c). There are two poles on the cluster: one that assembled the plants in continuous rows (B1) and one year from 15 cm PP (B2_17), and the second at 25 cm PP and the other two years from 15 cm PP. The first pole is associated with high yields and also the variants that developed the highest plant height and most branches. The second pole exhibits the lowest yields, associated with medium to low height. This pole is split into two areas by the variant with the highest plant weight (B3_17), which is not correlated with plant height or yield potential. Both 15 and 25 cm PP variants, in the same first and third experimental years, produced similar results in terms of plant height and individual weight.
The impact of distance within plants per row permits the analysis of row-by-row distance and climate impact (Figure 3a–c). Compared to the previous parameter (distance between rows), the cluster applied to the data reveals large differences between the variant combinations. All three variants planted at 70 cm RR produce similar results in terms of plant height and branching potential, with a slight increase in 2018, but a decrease of plant weight and yield potential. This year acts as a normalizer for variants planted at 25 and 50 cm between rows, with similar heights and branching potential, but a higher plant weight for 50 cm and higher biomass yields for the 25 cm variants. The most stable variants for the first two experimental years are 25 and 50 cm RR, with each recording lower differences from one year to another. The 15 cm PP distance (Figure 3b) is the most stable distance in terms of similar reactions. All of the variants from each row-by-row distance provide similar results independently of the experimental year. The highest plant height is recorded at 25 cm RR, correlating with the highest biomass yield. The 70 cm RR plants show the highest individual plant weights, but with the lowest biomass yields. The 50 cm RR distance shows its intermediary character, with 5–10% increases for all parameters recorded at 70 cm RR. The experimental increase in the plant-by-plant distance shown in Figure 3c does not act as an increasing factor for the observed parameters. Compared to 15 cm PP, the increase up to 25 cm PP acts as a reduction for biomass yield up to almost 20%. In contrast, there is a 30- to 80-unit increase in the individual weight, in the context of maintenance of the other (height and branching) parameters. The overall image of the cluster shows an almost 120° rotation compared to the previous planting distance.
The use of year as a cluster factor revealed the variation of parameters as a combination of technological factors applied on a specific climate (Figure 4a–c). For 2016, most of the combinations are grouped two-by-two, with the exception of 25 cm RR May it should be × 15 cm PP (A1 B3). This variant shows a potential of over 10 branches per plant, but with all other parameters in the average part of the intervals recorded. Both A3 B1 and A1 B2 produce over 45 t ha−1 of fresh biomass, with similar branching potential but with a more than 60 g difference in the plants’ individual weight. Both variants at 50 cm RR have similar heights and branching potential, but the 30 g individual weight recorded for A2 B2 is not visible in the biomass production, which is more than 8000 units of fresh biomass for A2 B3. The same trend is visible for A3, applied on the 15 and 25 cm PP variants, but with an overall increase of plants’ individual weight up to 10–20 g and a decrease of fresh biomass up to 3–5 t ha−1. Even the difference in individual weight between A2 B1 and A1 B1 is 100 g; the biomass yield is more similar, with only 5 t ha−1 for A1 B1 and only 1.5 t ha−1 for dry biomass. The trend identified in the first experimental year is not visible in the second (Figure 4b). The two productive variants registered in the first year remain the same (A1 B1 and A2 B1), and with the addition of A1 B2, all three record more than 11.5 t ha−1 of dry biomass. Their position in the cluster is median, due to the average values recorded for plant height, branching potential, and plant individual weight. The similarity of the plant height and branching recorded for A2 B2, A1 B3, and A3 B1 places them in the upper part of the cluster, with a similar plant weight between A2 B2 and A1 B3, but with more than 13.0 t ha−1 of fresh biomass for A1 B3, which makes it similar to A3 B1. The lower part of the cluster is associated with variants with the highest individual weights, but with the lowest biomass yields. This indicates that the plant height and branching have an effect on the yield parameters. The similar heights and branches produced in the variants A2 B1, A1 B1, and A1 B3 are not reflected in the biomass yield in the third year of the experimentation (Figure 4c). Planting at 50 cm RR compared to 25 cm RR (A2 B1 and A1 B1) produces an extra 80 g for each plant at 50 cm RR, but does not reflect the biomass yield, which is almost 20% higher in the context of 25 cm RR. Plants at 25 cm RR × 25 cm PP (A1 B3) exhibited the highest plant height, branching potential, and plant individual weight, but the biomass yield is almost half of that of A1 B1. Planting at 50 and 70 cm RR with 15 and 25 cm PP enabled the plants to grow to heights of 79–89 cm, grow more than nine branches, and achieve an individual weight of 267–327 g. However, these parameters do not correlate with the biomass yield, which is lower than 33.0 t ha−1 fresh, up to 15.0 t ha−1 in the case of A3 B3, which gave plants the maximum nutrition space. The two variants placed in the lower part of the cluster show almost the same nutrition space for the plants, but with 25,000 units of fresh biomass yield for the plants with 25 cm RR × 15 cm PP.

4. Discussion

After thousands of years of social and cultural evolution, humanity continues to identify herbal pharmaceutical resources and active substances that are effective in the treatment of many diseases, with phyto-pharmaceuticals being a viable alternative used in modern therapies such as physiotherapy, electrotherapy, and chemotherapy. The use of medicinal plants is growing in many countries, including Africa [25,26], China [27], Europe [28], and North America [29]. For this reason, the expansion of the range of medicinal and aromatic plants, through the diversification and identification of new plants and useful vegetative organs, is very important and useful. Over the last 30 years, mainly in Europe and America, there has been an increasing trend towards the adoption of a healthy diet using natural products. This trend has led to an increase in the demand for MAPs, which is partially satisfied by plants from the spontaneous flora, but also to an increasing extent by cultivated MAPs [30]. Currently, at least 28,187 plant species with medicinal properties have been described [31]. About 85% of the world’s population uses medicinal and aromatic plants as a primary health care approach [32]. Hundreds of years ago, people identified and selected medicinal plants based on organoleptic senses [33], and with the development of science and technology today, there are many studies on the chemical composition of medicinal plants. Most of the studies relate to plant sciences, agronomy, and biochemical and molecular biology, and provide results primarily for the pharmacology and pharmacy fields, along with plant sciences, biochemical molecular biology, and agricultural research. About 58% of these studies were conducted in China, India, the USA, and South Korea [33].
The annual plant Lamiaceae has drawn particular attention due to its beneficial characteristics. It is native to Central Asia and has acclimatized to eastern and central European regions [34]. The D. moldavica species, known for its sanogenic effects that give it superior phyto-therapeutic qualities [7,35], can be cultivated in ecosystems with favorable microclimates and optimized technology conditions. This species can be cultivated with high success in agroforestry systems in temperate areas, with a shade resistance up to 30% [36]. However, if the growth happens close to the Populus or Juglans species, the allelopathic pathways affect the growth and development of D. moldavica [37]. The chemical composition of the species has been extensively studied in recent years by various authors from Egypt, Iran, Turkey, and Ukraine [34]. The quantity and quality of the essential oils varies depending on genetics [38] and environmental conditions [18]. One of the most important issues is strongly related to weed management and control, which directly influence the biomass yield and essential oil content [39].
In contrast, the technological requirements of D. moldavica have not been fully assessed yet, and only sparse information is present in the international literature. Due to the current climate changes and the need for more sustainable agriculture, considerably more information is vital for the success of cropping. Although the experimental area is considered to have a stable climate, small changes in both temperature and amount of rainfall were identified during the experimental period [40]. The first experimental year had a temperature 1.3 °C higher than the multiannual average, and additional rainfall of 15.2 mm. The second year had the same thermal value, but the amount of rainfall was 6.2 mm lower than the average. The last experimental year had a temperature 2.4 °C higher than average and a supplementary amount of rainfall of 16.6 mm. These conditions explain the differences recorded between the experimental variants during the three years of experimentation and indicate more intense growth due to the small amount of rainfall in the context of the temperature increases. Several studies highlight the beneficial effect of D. moldavica intercropping with other MAPs and legumes [41]. Sowing and planting dates should be assessed from a dual perspective: the national system for testing new varieties, and from farm networks that deal with this crop. For Czech agricultural areas, sowing is recommended from mid-March and planting after two months (in mid-May) [42], while for Iranian areas, the dates are from 5 March up to 5 June, with the optimum dates for essential oil production from 5 April to 5 May [43] (May for shaded areas) [36]. This concept is sustained by the FAO, which compiled the Crop Calendar to provide the necessary parameters and information for the main crops [40], that is currently in development. Another category of information required for crop establishment relates to the seed and planting material and the varieties tested and recommended for a specific region. In most cases, the catalogs and regulations are difficult to harmonize due to the differences between the countries’ own regulations [44,45]. The final step necessary before the establishment of a crop is related to technological requirements, which are designed to offer for each plant optimum space and nutrition.
To date, a wider distance of 40 cm has not been shown to significantly differ from the medium distance of 30 cm [8]. Plant density’s effects on MAP growth, development, and yield were studied because of the increased interest in the numerous advantages. D. moldavica was studied at three different plant distances. The widest distance of 40 cm gave the highest fresh and dry herb weights in grams per plant compared to the other distance values of 20 and 30 cm. As a general trend, increased fresh and dry weights were observed as the plant-by-plant distance increased [8]. At a 10 cm planting density, the highest dry matter accumulation was observed in the aerial shoot part and the highest valuable oil content was obtained at a density of 30 cm [46]. Another study showed that a 70 cm row distance and 15 cm plant distance resulted in an increased branch number. Moreover, the other studied distances for this plant—50 cm and 70 cm row-by-row distance—had a significantly lower yield. Hereby, it was declared that a 25 cm row-by-row distance could represent a standard or rather a control treatment [47]. Other MAPs, such as Echinacea purpurea plants, cultivated at a plant spacing of 20, 40, and 60 cm, showed increased growth height with higher spacing, along with an increased biomass of dry shoots and roots [48]. Another relevant study of C. coronarium L. demonstrated that a 25 cm row-by-row distance determined the highest yield and the tallest plants in comparison with distances of 50 and 75 cm between plants [49]. The wider planting distance of 75 cm impacted the plants’ development in terms of providing the highest total dry weight, particularly for the flowers, and also the highest values for the plant thickness [49].
Plant density is an essential element of productivity in any agricultural crop that is expressed in the number of plants in a given area (generally the number of germinating grains/m2, number of plants/m2, number of ha−1) [50], the variable that allows the presence of the optimum number of individuals that permit the full expression of growth. In many agricultural crops, plant density has been clearly identified in studies according to the soil and climatic conditions and the morphological characteristics of the plant, for example, in maize and wheat (the most widespread crops at the national level). The main step for sustainable cultivation is represented by mitigating specific environmental stressors, by combining both conventional and biological inputs to ensure efficient growth and development [51]. On the other hand, in some cultivated plants, it is more difficult to determine the number of plants in a given area and there is no clear answer. For example, in potatoes, the number of stems resulting from the seed tuber influences the determination of the density in agricultural practice [52,53]. The optimal density of cultivated plants varies greatly between regions (zones), due to different soil and climatic conditions that require a certain sowing period and the use of certain varieties, hybrids, and local populations with different morphological features [54]. To ensure the site-specificity, the selection of D. moldavica cultivars is done in multiple fields, by exposing the individuals to differentiated ecological conditions [55]. Unlike other technological elements such as sowing date/planting date, plant density is under the complete control of the farmer or agronomist. The optimum density must ensure the harmonious development of the plants, leading to increased production. The improper use of crop density (wheat, for example) leads to the misuse of soil resources, reducing yields and, thus, profit [56]. Higher densities (above the optimum) lead to increased production costs and increased pressure of some diseases or insects [57]. From knowing the optimal density as well as the index of cultural value of the seed, it is possible to calculate the quantity of seed/ha (sowing norm). In order to satisfy the increased consumer demand for D. moldavica, cultivation is the main sustainable solution to produce higher and more technologically controlled yields [42,58]. All of the technological factors have a synergic effect on both the growth and development of individuals and their chemical content [59].

5. Conclusions

Planting distances, row-by-row and plant-by-plant, are the most important factors for the growth and development of D. moldavica. The biomass yield is more sensitive to plant-by-plant distance, a factor that also equally affects individual height and weight. The climate significantly influences the potential biomass yield, an effect amplified by plant densities. The maximum height of the plants is reached at a row-by-row distance of 25 cm, regardless of the plant-by-plant distances. Individual weight is over 320 g at a 25 cm plant-by-plant distance and a row-by-row distance of 50 cm. Continuous planting at a 25 cm row-by-row distance leads to potential fresh biomass of over 88 t ha−1. An increase in the row-by-row distance of 50 cm with continuous planting results in a fresh biomass yield of 74 t ha−1. The differences between plant heights at low planting densities compared to high densities are not significant, but significant biomass differences are observable.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture12060789/s1, Figure S1: Experimental field setup, growth, development and flowering stage, Table S1: The influence of experimental factors on D. moldavica parameters.

Author Contributions

Conceptualization, C.M., S.N., M.S. and A.D.; methodology, C.M., S.N., M.S. and A.D.; software, C.M. and V.S.; validation, C.M., S.N., M.H., R.V., M.S., Ș.G., A.D., V.A.S., S.D.V. and V.S.; formal analysis, C.M., S.N., M.H., R.V., M.S., Ș.G., A.D., V.A.S., S.D.V. and V.S.; investigation, C.M., S.N., M.H., R.V., M.S., Ș.G., A.D., V.A.S., S.D.V. and V.S.; data curation, C.M., S.N., M.S. and A.D.; writing—original draft preparation, C.M., S.N., M.H., R.V., M.S., Ș.G., A.D., V.A.S., S.D.V. and V.S.; writing—review and editing, C.M., S.N., M.H., R.V., M.S., Ș.G., A.D., V.A.S., S.D.V. and V.S.; supervision, C.M., S.N., M.S. and A.D. The first author and the corresponding authors (S.N., M.S. and A.D.) contributed equally to this paper, all being considered first authors. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by funds from the “Maintaining biodiversity in medicinal and aromatic plants by conserving and enriching the collection of genetic resources and producing seeds from higher biological categories for species representative of the hilly and mountainous areas”. Grant-ADER 2.4.1 granted by the Romanian Ministry of Research and Innovation.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available at request from the corresponding authors.

Conflicts of Interest

The authors declare no conflict of interest.

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Agriculture 12 00789 g001 550
Figure 1. Interdependence between D. moldavica growth and development parameters. (a) branch × height, (b) height × weight, (c) branch × weight, (d) fresh × dry biomass (herba).
Figure 1. Interdependence between D. moldavica growth and development parameters. (a) branch × height, (b) height × weight, (c) branch × weight, (d) fresh × dry biomass (herba).
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Figure 2. Cluster analysis of plant-by-plant distance May it should be × experimental year interaction, grouped by row-by-row distance. (a) 25 cm RR, (b) 50 cm RR, and (c) 70 cm RR. Factor B—plant-by-plant distance (PP): continuous rows (B1), 15 cm (B2), and 25 cm (B3); Factor C—experimental year 2016 (16), 2017 (17), and 2018 (18).
Figure 2. Cluster analysis of plant-by-plant distance May it should be × experimental year interaction, grouped by row-by-row distance. (a) 25 cm RR, (b) 50 cm RR, and (c) 70 cm RR. Factor B—plant-by-plant distance (PP): continuous rows (B1), 15 cm (B2), and 25 cm (B3); Factor C—experimental year 2016 (16), 2017 (17), and 2018 (18).
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Figure 3. Cluster analysis of row-by-row distance May it should be × experimental year interaction as grouped by plant-by-plant distance. (a) Continuous rows; (b) 15 cm PP, and (c) 25 cm PP. Factor A—distance between rows (RR): 25 (A1), 50 (A2), and 70 (A3); Factor C—experimental year 2016 (16), 2017 (17), and 2018 (18).
Figure 3. Cluster analysis of row-by-row distance May it should be × experimental year interaction as grouped by plant-by-plant distance. (a) Continuous rows; (b) 15 cm PP, and (c) 25 cm PP. Factor A—distance between rows (RR): 25 (A1), 50 (A2), and 70 (A3); Factor C—experimental year 2016 (16), 2017 (17), and 2018 (18).
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Figure 4. Cluster analysis of row-by-row distance × plant-by-plant distance interaction grouped by experimental year. (a) Experimental year 2016; (b) experimental year 2017; and (c) experimental year 2018. Factor A—row-by-row distance (RR): 25 (A1), 50 (A2), and 70 (A3) cm; Factor B—plant-by-plant distance (PP): continuous rows (B1), 15 cm (B2), and 25 cm (B3).
Figure 4. Cluster analysis of row-by-row distance × plant-by-plant distance interaction grouped by experimental year. (a) Experimental year 2016; (b) experimental year 2017; and (c) experimental year 2018. Factor A—row-by-row distance (RR): 25 (A1), 50 (A2), and 70 (A3) cm; Factor B—plant-by-plant distance (PP): continuous rows (B1), 15 cm (B2), and 25 cm (B3).
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Table
Table 1. Influence of row-by-row x plant-by-plant factors on D. moldavica parameters.
Table 1. Influence of row-by-row x plant-by-plant factors on D. moldavica parameters.
Factor CombinationHeight (cm)Branch (no.)Weight
(g)		Fresh Biomass
(t ha−1)		Dry Biomass
(t ha−1)
A1_B182.67 ± 2.23 a9.11 ± 0.39 a146.67 ± 9.88 d88.00 ± 5.93 a15.63 ± 0.99 a
A1_B281.33 ± 1.94 a9.00 ± 0.76 a210.44 ± 21.96 cd58.92 ± 6.15 bc10.24 ± 1.11 bc
A1_B383.78 ± 3.46 a10.11 ± 0.26 a295.22 ± 24.15 abc47.24 ± 3.86 cd8.54 ± 0.66 cd
A2_B178.56 ± 1.72 a8.78 ± 0.43 a246.89 ± 25.33 abcd74.07 ± 7.60 ab13.20 ± 1.37 ab
A2_B279.33 ± 2.77 a9.11 ± 0.31 a290.44 ± 25.46 abc34.70 ± 3.41 de61.84 ± 0.64 def
A2_B377.22 ± 3.34 a9.00 ± 0.33 a329.00 ± 30.78 ab26.32 ± 2.46 de46.12 ± 0.48 ef
A3_B177.00 ± 1.57 a8.89 ± 0.39 a213.11 ± 17.19 bcd45.67 ± 3.68 cd79.31 ± 0.74 cde
A3_B273.00 ± 1.79 a9.56 ± 0.41 a321.22 ± 19.44 abc32.12 ± 1.94 de54.55 ± 0.36 def
A3_B377.33 ± 2.57 a9.00 ± 0.33 a352.67 ± 38.78 a20.15 ± 2.22 e34.10 ± 0.38 f
Note: Factor A—distance between rows (RR): 25 (A1), 50 (A2), and 70 (A3) cm; Factor B—distance within rows: continuous rows (B1), 15 cm (B2), and 25 cm (B3). Means ± standard error followed by different letters were considered significant at p < 0.05 according to LSD test.
Table
Table 2. The influence of row-by-row distance x experimental year factors on D. moldavica parameters.
Table 2. The influence of row-by-row distance x experimental year factors on D. moldavica parameters.
Factor CombinationHeight (cm)Branch (no.)Weight
(g)		Fresh Biomass
(t ha−1)		Dry Biomass
(t ha−1)
A1_C178.89 ± 1.40 bcd9.11 ± 0.54 a180 ± 17.66 b54.32 ± 5.88 ab9.65 ± 1.05 ab
A1_C277.89 ± 1.47 bcde9.22 ± 0.57 a237.89 ± 28.32 b67.96 ± 4.34 a12.04 ± 0.74 a
A1_C391.00 ± 1.90 a9.89 ± 0.48 a234.44 ± 34.27 b71.88 ± 11.11 a12.73 ± 1.94 a
A2_C176.67 ± 1.62 cde8.89 ± 0.35 a262.33 ± 11.72 ab41.23 ± 7.12 ab7.31 ± 1.28 ab
A2_C272.67 ± 1.89 de8.44 ± 0.34 a306.67 ± 23.17 ab44.82 ± 5.44 ab7.93 ± 0.98 ab
A2_C385.78 ± 2.16 ab9.56 ± 0.29 a297.33 ± 42.99 ab49.03 ± 12.40 ab8.75 ± 2.24 ab
A3_C170.67 ± 1.22 e8.78 ± 0.46 a272.44 ± 14.80 ab31.62 ± 4.70 b5.41 ± 0.83 b
A3_C275.67 ± 1.78 cde9.11 ± 0.39 a373.33 ± 39.64 a39.67 ± 4.20 ab6.81 ± 0.81 ab
A3_C381.00 ± 1.54 bc9.56 ± 0.24 a241.22 ± 23.13 ab26.65 ± 3.53 b4.58 ± 0.65 b
Note: Factor A—distance between rows (RR): 25 (A1), 50 (A2), and 70 (A3) cm; Factor C—experimental year 2016 (C1), 2017 (C2), and 2018 (C3). Means ± standard error followed by different letters were considered significant at p < 0.05 according to LSD test.
Table
Table 3. The influence of plant-by-plant distance × experimental year factors on D. moldavica parameters.
Table 3. The influence of plant-by-plant distance × experimental year factors on D. moldavica parameters.
Factor CombinationHeight (cm)Branch (no.)Weight
(g)		Fresh Biomass
(t ha−1)		Dry Biomass
(t ha−1)
B1_C178.00 ± 1.64 bc8.67 ± 0.33 a195.00 ± 17.08 c64.86 ± 4.39 abc11.46 ± 0.83 abc
B1_C276.00 ± 1.40 bc8.33 ± 0.41 a199.78 ± 18.86 c66.59 ± 4.80 ab11.78 ± 0.92 ab
B1_C384.22 ± 1.82 ab9.78 ± 0.28 a211.89 ± 31.92 bc76.28 ± 13.08 a13.53 ± 2.33 a
B2_C175.33 ± 2.03 bc8.78 ± 0.57 a240.00 ± 20.61 bc35.70 ± 3.08 cd6.20 ± 0.54 cd
B2_C274.56 ± 1.80 c9.44 ± 0.56 a322.33 ± 21.33 ab49.12 ± 5.12 abcd8.52 ± 0.89 abcd
B2_C383.78 ± 2.34 ab9.44 ± 0.44 a259.78 ± 31.37 bc40.94 ± 7.80 bcd7.16 ± 1.41 bcd
B3_C172.89 ± 1.47 c9.33 ± 0.41 a279.78 ± 12.02 abc26.62 ± 3.37 d4.71 ± 0.66 d
B3_C275.67 ± 2.29 bc9.00 ± 0.29 a395.78 ± 28.19 a36.74 ± 4.16 bcd6.48 ± 0.80 bcd
B3_C389.78 ± 2.30 a9.78 ± 0.32 a301.33 ± 36.76 abc30.34 ± 6.41 d5.37 ± 1.16 d
Note: Factor B—distance within rows (PP): continuous rows (B1), 15 cm (B2) and 25 cm (B3); Factor C—experimental year 2016 (C1), 2017 (C2), and 2018 (C3). Means ± standard error followed by different letters were considered significant at p < 0.05 according to LSD test.
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Moldovan, C.; Nițu, S.; Hermeziu, M.; Vidican, R.; Sandor, M.; Gâdea, Ș.; David, A.; Stoian, V.A.; Vâtcă, S.D.; Stoian, V. Growth Characteristics of Dracocephalum moldavica L. in Relation to Density for Sustainable Cropping Technology Development. Agriculture 2022, 12, 789. https://doi.org/10.3390/agriculture12060789

AMA Style

Moldovan C, Nițu S, Hermeziu M, Vidican R, Sandor M, Gâdea Ș, David A, Stoian VA, Vâtcă SD, Stoian V. Growth Characteristics of Dracocephalum moldavica L. in Relation to Density for Sustainable Cropping Technology Development. Agriculture. 2022; 12(6):789. https://doi.org/10.3390/agriculture12060789

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Moldovan, Cristina, Sorina Nițu (Năstase), Manuela Hermeziu, Roxana Vidican, Mignon Sandor, Ștefania Gâdea, Adriana David, Valentina Ancuța Stoian, Sorin Daniel Vâtcă, and Vlad Stoian. 2022. "Growth Characteristics of Dracocephalum moldavica L. in Relation to Density for Sustainable Cropping Technology Development" Agriculture 12, no. 6: 789. https://doi.org/10.3390/agriculture12060789

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