Introduction

Mulberry is a high biomass producing, fast-growing, perennial, woody plant belonging to the genus Morus under the family Moraceae (Pan and Lou 2008; Yang et al. 2010). Mulberry leaves, especially those of the Morus alba L. (white mulberry) is agriculturally more important, serving as sole food for monophagous insect Bombyx mori (silkworm larvae), the product of which (raw silk) puts impact on economy of a country like India. It is estimated that almost 90% of global raw silk production depends upon mulberry silk and in India mulberry silk culture was performed mainly by moriculture (mulberry plant culture). According to Food and Agriculture Organization of the United Nations (FAO), sericulture provides gainful employment, helping significantly to the livelihood of many people across the globe, plays an important role in anti-poverty program especially in the rural areas. Propagation of Mulberry depends upon vegetative method, seed germination, grafting and rarely by tissue culture. Propagation through stem cutting is the most simplest and cost effective vegetative proliferation practice used for mass production. However, this propagation method shows major delay in appearance of first leaf and sometimes in root succession, which ultimately delaying the harvesting time. Succession and rooting of cuttings greatly depends upon several factors like time of preparation of cuttings, cultivar chosen to obtain cuttings, physiological condition of the cuttings, environmental condition, application of hormones, fertilizers and nutritional supplement etc. (Hartmann et al. 2002). As suggested previously by various researchers for appropriate root establishment, growth and leaf production, a proper nutrient management system is required (Lu et al. 2003). Though micronutrients like iron, copper, zinc, manganese are required in very low amount, but presence of correct balance of these elements is essential for growth and quality leaf production as they play vital role in development of plants (Hänsch and Mendel 2009; Noor-Ul-Din 2012). As stated by Geetha et al. (2017), in case of multi micronutrient deficiency in Mulberry, yield can be reduced even up to fifty percent. Among all these, to date, iron deficiency and its remediation were found to be the biggest agronomic challenges (Tagliavini et al. 2000; Li and Lan 2017). Though in the earth’s crust, iron is the fourth most abundant element but a large proportion of this remain in the insoluble Fe+3 form, but as plants usually absorb iron in Fe+2 form from the soil, deficiency occur (Kobayashi and Nishizawa 2012; Mimmo et al. 2014; Bindraban et al. 2015; Ye et al. 2015). Its availability is also highly restricted to the plants grown in neutral to basic pH of aerobic soil (Straub et al. 2001). Due to low solubility of oxidized ferric form in aerobic atmosphere, iron is the third most limiting nutrient for growth and metabolism of a plant (Zuo and Zhang 2011; Samaranayake et al. 2012). However, iron is an indispensable nutrient for all organisms as it is the key determinant of various cellular metabolism such as electron transport system, biosynthesis of chlorophyll and cytochrome, respiration (Kim and Rees 1992), nutrient uptake, nitrogen fixation, DNA and protein synthesis (Rout and Sahoo 2015). Deficiency of iron is frequent in mulberry, growing in alkaline soils and exhibits symptoms of chlorosis. To address the deficiency, application of chemical and chelated iron fertilizers is adopted. Chelated fertilizers are quite costly and often applied for high value crops. Besides this, over or improper application of fertilizers under aerobic condition can generate reactive oxygen species (ROS) as by-products of Fenton reaction that may damage vital cellular components of plants (Rout and Sahoo 2015). Use of chemical fertilizer is an age long practice leads to soil mineral imbalance, destroy soil fertility, soil texture and shows long term effect to the ecosystem (Elemike et al. 2019). Biofertilizers to some extend play potential roles in improvement of soil fertility and crop production (Bhardwaj et al. 2014) but large-scale productions of biofertilizers are not easy and in some cases, they are pH and temperature dependent.

To deal with all the associated problems, incorporation of nanotechnology in agriculture arises which serves as the latest technology for precision agriculture. Nanomaterials consist of nano-scale particles having a diameter of less than 100 nm (Auffan et al. 2009). Because of their unique properties, novel features such as inherent biocompatibility, super-paramagnetism, enhanced surface to volume ratio, nanoparticles have been extensively used in many aspects of daily life of which agriculture holds an important position (Rastogi et al. 2017). Several earlier reports suggested the ability of nanoparticles in seed germination encouragement, degradation of pesticide residue and improvement of soil quality (Ghrair et al. 2010; El-Temsah et al. 2014). Our current study deals with the hypothesis that both soil and foliar application of iron oxide nanoparticles and EDTA functionalized iron oxide nanoparticles on mulberry propagation will improve the overall growth parameters.

Our study mainly emphasizes on enhancing the spouting percentage, decreasing the duration of leaf appearance and improving the overall vigour of Mulberry by application of phyto-synthesized iron oxide nanoparticles (FeNP) and EDTA functionalized iron oxide nanoparticles (FeNP EDTA).

Materials and Methods

Collection of Plant Materials

Mature, diseases free Tea [Camellia sinensis (L.) Kuntze] leaves for biosynthesis of iron oxide nanoparticles were collected from Tea garden, University of North Bengal, Siliguri, West Bengal, India (26°42′41″N, 88°20′50″E). Mulberry stem cuttings of S1 cultivar were procured from Matigara Sericulture Complex (26°72′40″N and 88°35′37″E), Siliguri, West Bengal, India.

Preparation and Characterization of Iron Oxide Nanoparticles

Iron nanoparticles were synthesized by adding mature tea leaves extracts (aqueous decoction prepared through refluxing) to 0.01 M FeCl3 (SRL, Batch #T/829638) with a volume ratio of 10:1 at room temperature with continuous uniform stirring for 30 min using magnetic stirrer (REMI EQUIPMENTS). EDTA functionalized iron oxide nanoparticles were prepared by the addition of 25 ml EDTA (0.02 M) with freshly prepared 55 ml iron oxide nanoparticles solution, following the method of Magdalena et al. (2018). The formed particles were removed from reaction medium through precipitation using a strong external magnet and were rinsed thrice with double distilled water and 95% ethanol. After washing, the particles were dehydrated using a hot air oven (Lab Instruments, India, Model-0949) at 65 °C until complete drying.

Characterization of nanoparticles was initially done using UV–Vis spectrophotometer (SYSTRONICS-2201). The size and morphology of the synthesized iron oxide nanoparticles were investigated on a PHILIPS CM 200 transmission electron microscope (TEM). Hydrodynamic size was also measured using dynamic light scattering (DLS) through ZETASIZER NANO ZS90 ZEN3690. The crystalline structure and phase purity of the biosynthesized particles were determined with the help of XRD analysis using a BRUKER AXS D8 ADVANCE (BRUKER KAPPA APEX II).

Experimental Design

The pot experiment was conducted using plastic zipper bag in Mulberry germplasm garden (26°42′34″N and 88°21′06″E, altitude 400 feet) of Department of Botany, University of North Bengal, Siliguri, West Bengal, India in the period of January-June, 2019. Agro-climatic data as collected in that period were average temperature range of about 17.35 °C–23.23 °C, average precipitation of 170.33 mm, average moisture content of 69.16%, normal wind speed of 7.5 Kmph and sun exposure duration of 240.75 h.

Soils after collection from mulberry germplasm garden were air dried and sieved through a 2 mm mesh to get soils of uniform size. According to soil analysis prior to plantation, pH, electrical conductivity (EC), bulk density and moisture content of soil was measured as 4.5, 26.5 μS/cm, 1.25 g/cm3 and 14.33%, respectively and soil texture was evaluated as sandy loam. Some other biochemical attributes of the tested soil as noted was 1.35%, 2.32%, 0.11%, 22 ppm, 55.43 ppm and 38 ppm for organic carbon, organic matter, available nitrogen, available phosphorus, available potassium and available sulphur, respectively.

The experiment was carried out with six treatments in randomized complete block design with 20 replications of each. Treatment plots were sufficiently spaced for minimizing adjacent influences. Among them, 10 plants were used for above ground growth analysis and 3 plants were sacrificed at each time of evaluation for measuring underground root attributes, biomass analysis along with determination of antioxidant attributes. Treatments were control (distilled water, abbreviated as Con), ferrous sulphate at 10 mg/kg soil dose (abbreviated as FeSO4), iron oxide nanoparticles at two different dosage of 10 mg/kg soil (FeNP 10) and 50 mg/kg soil (FeNP 50) and EDTA functionalized iron oxide nanoparticles at 10 and 50 mg/kg soil dosage (symbolized as FeNP EDTA 10 and FeNP EDTA 50). Each pot (inside length: 10.5 cm, breadth: 7.5 cm and height: 19 cm) was filled with 1.25 kg of soil and the different treatments in solution form were applied to the respective pots. Mulberry stem cuttings after collection was obliquely cut under water and these obliquely cut stem cuttings of equal length (20 cm each) was planted inside pot. Soil application was done initially after plantation (one time) and foliar applications were done by spraying at 30th, 45th and 60th days after plantation at the rate of 5 ppm (for FeNP 10 and FeNP EDTA 10) and 10 ppm (for FeNP 50, FeNP EDTA 50 and FeSO4).

Growth Parameters Evaluation

Best ten plants (replicates) from each treatment were selected to estimate growth parameters of treated mulberry stem cuttings. Leaf length, leaf breadth, maximum shoot length, root lengths were measured using a centimeter scale at 30, 45, 60 and 75th days after plantation. For estimation of shoot biomass and root growth, three plants from each treatment at each time (30, 45, 60 and 75th days after plantation) were harvested, washed with tap water three times and again washed thoroughly with deionized water to remove impurities absorbed on the surface of plant parts. Root growth was evaluated specifically in terms of maximum root length, root branching number and root biomass. Fresh weight of shoots and roots were measured using digital weight balance (QUINTIX 224-10 IN, Sartorius Lab Instruments GmbH & Co. KG). Spouting percentages were calculated using following formula:

$$ {\text{Sprouting percentage}} = \left[ {\left( {{\text{number of buds sprouted}}/{\text{number of buds present during plantation}}} \right) \times {\text{1}}00} \right]. $$

Biochemical Evaluation

Leaves sample from each treatment (three replication) was collected at 30th, 45th, 60th and 75th after plantation, crushed in cold condition according to the respective methodology, centrifuged and biochemical analysis were performed.

Estimation of Chlorophyll Content

Chlorophyll was extracted in 80% acetone and the amount of total chlorophyll was estimated by standard method described by Arnon (1949).

Estimation of Total Protein Content

Total protein content was estimated following the methodology given by Lowry et al. (1951). The blue-colored complex was formed after well mixing 5 ml alkaline copper solution and Folin-ciocalteu reagent (FCR) with 1 ml protein sample and the absorbance was measured at 660 nm.

Estimation of Total Carbohydrate (Soluble Sugars) and Reducing Sugar Content

0.1 gm of leaf samples were crushed in 10 ml of 80% hot ethanol and filtered using filter paper. After evaporation of existing ethanol by heating the sample, final volume of filtrate was made up to 10 ml by adding distilled water.

Total soluble sugars content was determined by Anthrone method (Thimmaiah 2004). Intensity of resultant blue color mixture was measured at 620 nm. Using sucrose standard curve, total soluble sugar present in the extract was calculated.

DNSA method (Sadasivam and Manickam 1996) was used for reducing sugar estimation. To 1 ml alcohol free extract, 1 ml DNSA reagent was mixed and incubated in a water bath for 5 min. After the development of the colored product, 1 ml 40% Rochelle salt solution was added and mixed well and absorbance was read at 510 nm.

Estimation of Total Phenol Content

Method prescribed by Kadam et al. (2013) was followed for estimating total phenol content with slight modifications. For estimating, 95% ethanol, 5 ml distilled water, 50% Folin–ciocalteau reagent and 5% Na2CO3 was added to 1 ml sample extract and incubated for 1 h. Absorbance was measured at 725 nm and phenol content was estimated using Gallic acid standard curve.

Estimation of Ortho-Dihydric Phenol

Ortho-dihydric phenol was estimated according to the method prescribed by Mahadevan and Sridhar (1986). Arnow’s reagent (0.5 ml), 5 ml distilled water and 1 ml 1(N) NaOH was added to 0.5 ml methanolic extract of the sample. Ortho-phenol content was calculated concerning Catechol as standard and the absorbance of the reaction mixture was taken at 515 nm.

Estimation of Flavonoid Content

Flavonoid content was estimated following the method of Atanassova et al. (2011). To 0.5 ml extract, 4 ml distilled water, 5% NaNO2, 10% AlCl3 and 2 ml 1(M) NaOH was added and the absorbance was taken at 510 nm. Flavonoid content was estimated using standard curve prepared from Quercetin.

Study of Antioxidant Enzyme Activity

For estimation of antioxidant enzymes, leaf samples from each treatment (three replicates) were collected at 30th, 45th, 60th and 75th days after plantation. Liquid nitrogen mediated cryo-crushing was done followed by cold centrifugation and the supernatant was used for further analysis.

Estimation of Catalase (CAT) Activity

CAT (EC 1.11.1.5) activity was measured according to Hasanuzzaman et al. (2011). To 40 µl of enzyme, H2O2-Potassium phosphate buffer (1:2) combination was mixed and decomposition of hydrogen peroxide was monitored at 240 nm. Enzyme activity was expressed as unit mg protein−1 (1 unit = mmole H2O2 reduced per minute) using extinction coefficient of 39.4 M−1 cm−1.

Estimation of Peroxidase (POD) Activity

POD (EC 1.11.1.7) enzyme activity was determined using the method of Rani et al. (2004). To 3 ml of pyrogallol solution, 1 ml of the enzyme extract was added and the spectrophotometer was adjusted to read 0 at 430 nm. H2O2 (0.5 ml) was directly added to the test cuvette and mixed well. The change in absorbance was recorded every 30 s up to 3 min. One unit of peroxidase is defined as the change in absorbance per minute at 430 nm and was expressed as U.ml−1.

Estimation of Polyphenol Oxidase (PPO) Activity

PPO (EC 1.14.18.1) was estimated according to the method given by da Silva and Koblitz (2010) with some modifications. The reaction mixer contains 2.5 ml of potassium phosphate buffer (0.1 M, pH 6.5), 0.3 ml catechol solution (0.01 M) and 0.2 ml of enzyme extract. Absorbance was taken at 495 nm after 5 min of reaction. Activity was expressed as U.ml−1, where one unit of PPO was defined as the amount of enzyme required for increasing unit absorption of the reaction mixture in each minute.

Estimation of Glutathione Reductase (GR) Activity

GR (EC 1.6.4.2) activity was measured by Hasanuzzaman et al. (2011). The reaction mixture comprising 2.7 ml potassium phosphate buffer (0.1 M, pH 7.8), 1 mM EDTA (prepared within buffer), 0.1 ml of NADPH solution (0.2 mM) and 1.0 ml of enzyme source. The reaction was initiated by adding 0.1 ml of GSSG (Glutathione disulphide, 1 mM) and decrease in absorbance due to NADPH oxidation was recorded at 340 nm for 1 min. Activity was expressed as unit (U) (1U = µmol NADPH oxidized per minute) per milligram protein using an extinction coefficient of 6.2 mM−1 cm−1.

Estimation of Glutathione S-Transferase (GST) Activity

With slight modifications, spectrophotometric method prescribed by Hasanuzzaman et al. (2011) was followed for determination of GST (EC 2.5.1.18) activity. The reaction mixer contained 2.7 ml Tris HCl buffer (100 mM, pH 6.5), 1 mM GSH, 1 mM 1-chloro-2, 4-dinitrobenzene (CDNB) and 100 µl of enzyme solution. The reaction was initiated by the addition of CDNB and the increasing absorbance was recorded for 1 min at 340 nm. Extinction coefficient of 9.6 mM−1 cm−1 was used to calculate the enzyme activity.

Estimation of NADPH Oxidase (NOX) Activity

Determination of NOX (EC 1.6.3.1) was done by adding 0.4 ml of enzyme extract to the 2 ml of Tris HCl buffer containing 0.5 mg/ml NBT and 134 mM NADPH and absorbance was taken at 470 nm. Extinction coefficient of 21.6 mM−1 cm−1 was used to calculate enzyme activity (Zhang et al. 2018).

Data Analysis and Program Used

Data of 10 replicates were collected for evaluation of morphological attributes and results were expressed as mean ± standard deviation (SD), however for plant biomass, root growth, biochemical and antioxidant enzymes parameters evaluation, three replicates were taken. Tests of statistical differences were carried out by Tukey’s Honestly Significant Difference (HSD) test at p ≤ 0.05, where the treatments differ significantly were denoted with different letters (a, b, c etc.). Excel macros DSAASTAT, version 1.022 (DSAA, Italy) extension has been used to calculate this. Principal component analysis (PCA) and heat map was performed based on 75th day’s data different variables and treatments under study. PCA analysis was carried out using web enabled Clustvis program (Metsalu and Vilo 2015) and to make biplots first two components (PC1 and PC2) were used. Heat map was prepared using web enabled Heatmapper (Babicki et al. 2016) based on Pearson distance measurement method by preparing percentile rank.

Results and Discussion

Characterization of Iron Oxide Nanoparticles

Color change of ferric chloride solution, from pale yellow to dark black, was the first and foremost indication of nanoparticles synthesis. However, formation was confirmed by UV–Visible spectra analysis, showed absorption maxima at 254 nm (Fig. 1a), which is in agreement with the previous findings (Vadivel et al. 2012; Eslami et al. 2018). TEM images (Fig. 1b) confirmed that formed nanoparticles are of spherical in shape with an average size of 13.10 nm. However, the hydrodynamic size obtained through DLS (Fig. 1c) is quite higher (59.24 nm) than the size acquired through TEM. XRD analysis showed prominent peaks at 29.81°, 35.10°, 41.57°, 53.11°, 56.69°, 62.57° corresponding to (hkl) values of (220), (311), (400), (422), (511), (440) Bragg’s reflections plane (Fig. 1d). The obtained peaks match with existing standard JCPDS library (card no 39-1346), representing standard cubic structure of γ-Fe2O3 (maghemite) nanoparticles. However, as some extra small peaks were also appeared in the obtained XRD spectra, it could be the magnetite or other form of iron oxide nanoparticles or rather to say it might be the mixture of different phase of iron oxide nanoparticles. Average crystalline size of the formed nanoparticles was calculated using Debye–Scherrer’s equation and was found to be 11.98 nm, which was in close proximity with the average particle diameter obtained through TEM analysis.

Fig. 1
figure 1

Characterization of biosynthesized iron oxide nanoparticles, a UV–visible spectra analysis, b transmission electron micrograph (TEM), c dynamic light scattering (DLS), d X-ray diffraction (XRD) analysis

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Effect of Iron Oxide Nanoparticles on the Sprouting Percentage and Days to Appear First Leaf

Mulberry stem cuttings responded variably towards different concentrations of normal and EDTA functionalized iron oxide nanoparticles. As shown in Table 1, application of both the iron oxide nanoparticles and its chelated form significantly improved sprouting percentage and also helped to reduce the days to appear first leaf. Results of sprouting percentage showed a clear statistical differentiation among different concentrations of iron oxide nanoparticles and its EDTA functionalized form. FeNP EDTA 50 showed almost 82% sprouting percentage which was 166% improvement over control. Iron nanoparticles showed a noteworthy response in quick appearance of leaves. Cuttings treated with FeNP 10 took only twelve days to appear its first leaf in comparison to control which took almost twenty-seven days.

Table 1 Effect of iron oxide nanoparticles and EDTA functionalized iron oxide nanoparticles on the sprouting percentage and days to appear first leaves of Mulberry
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Effect of Iron Oxide Nanoparticles on the Growth Parameters

The phenotypic traits of plants showed dramatic effects on the resulting plants’ growth and development upon exposure to the FeNPs treatments. The plants exposed to FeNPs-EDTA have significantly longer shoots and bigger leaves in comparison to the control and plants treated with normal iron salt supplementation (FeSO4). The morphological appearance of the treated plants is presented in Fig. 2a. Results pertaining to shoot height showed that maximum increase in height of about 78.28% by FeNP EDTA 50 treatments at 75th days after plantation against control. This result is in conformity with Ju’s study (Ju et al. 2019); where they showed that 20 nm size ranged iron oxide nanoparticles-EDTA conjugate had positive growth potential in Lepidium sativam. Yuan et al. (2018) also reported significant influence of iron oxide nanoparticles on plant height in comparison to control and Fe2+ ions treatment. From Table 2 it was observed that both the nano-micronutrient fertilizer was effective in escalating the number of leaves per plants. After 75th days of plantation, the highest number of leaves belongs to the cuttings treated with FeNP 10 which showed an increment of 52.73% over control. Cuttings exposed to FeNP EDTA 50 had 53.48% larger leaf area compared to the non-treated groups (control). Yoon et al. (2019) reported similar sorts of results where they found 53% leaf area increment on application of nanoscale zero valent iron (nZVI) nanoparticles. No significant changes were observed in branching number in iron oxide nanoparticles treated cuttings compared to control. According to Elanchezhiana et al. (2017), application of Fe3O4 nano-micronutrient in maize significantly improved shoot length, leaf area, root and shoot dry biomass and other biochemical parameters. Both maximum shoot length and average number of branching showed optimum value at FeNP EDTA 50 at final day of observation (75th day after plantation) shared a ratio of 4.20:1. On the other hand at the same dose maximum shoot length and number of leaves showed almost 1:1 ratio. Increment of growth attributes can be explained by high level of photo assimilates synthesis and accumulation. Photo-assimilates plays central role in plant growth, development (Allsopp 1954), flowering (Kraus and Kraybill 1918) and apical dominance (Loeb 1924). Small sugars were considered as important in signaling pathway of plants (Moore et al. 2003). Ende (2014) speculated that, internal sugar/IAA proportion within the buds or within the adjoining stem may somehow be connected prior to initiation of bud outgrowth. Sprouting percentage increment, early leaf appearance and evenness in branching number depicted not only the accumulation but also the effective mobilization of photo-assimilates. Increase in leaf area recorded in our study in association with better utilization of iron oxide nanoparticles might be a kind of adaptation towards proficient photosynthesis as stated by Fernández et al. (2008).

Fig. 2
figure 2

Effect of iron oxide nanoparticles EDTA functionalized iron oxide nanoparticles on morphological appearance and root growth (a and b). For morphological appearance of the plant: (i) FeNP EDTA 50, (ii) FeNP 10, (iii) FeNP 50, (iv) FeNP EDTA 10, (v) FeSO4, (vi) Control. For root appearance: (i) FeNP10, (ii) FeNP EDTA 10, (iii) FeNP EDTA 50, (iv) FeNP 50, (v) FeSO4, (vi) Control

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Table 2 Effect of iron oxide nanoparticles and EDTA functionalized iron oxide nanoparticles on different growth parameters of Mulberry at different growth stage
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Figure 2b represents the root appearance of treated mulberry cuttings after 75 days of plantation. Both FeNP and FeNP EDTA showed a noticeable change on the development of roots over control and normal iron salt supplementation (Table 3). A prominent increase in root length and root branching number was observed in low concentration of both FeNP and FeNP-EDTA, supports the findings of Palchoudhury et al. (2018). On evaluating root branching number, it was found that except FeNP 10, there was no significant difference among different dosage of iron oxide nanoparticles and EDTA functionalized iron oxide nanoparticles. Maximal significant root length improvement was recorded in FeNP 10 after 75th days of plantation which showed almost 34% of increment over control. Formation of adventitious roots in cuttings is governed by various morphological and physiological processes and generally triggered by several external factors including mineral nutrition. Previous studies by various researchers have indicated the accumulation of several micronutrients including iron and copper at the base of stem cuttings (Svenson and Davies 1995; Rowe et al. 1999). Iron specifically acts locally in the meristematic cells of adventitious root primordia and enhances root growth by promoting cell division (Hilo et al. 2017). Roschzttardtz et al. (2011) observed a high accumulation of iron in nucleolus of plant cells, suggesting the possible involvement of this element in ribosomal RNA biosynthesis. Indeed, biogenesis of ribosome appears to be correlated with rate of cell proliferation, which is becoming a vital factor in actively dividing cells (Manzano et al. 2013). In this study, on application of iron oxide nanoparticles externally, maximum length of the root and its branching number showed utmost value at FeNP 10 dosage with a ratio of 1:4.10, which is almost similar to the ratio of shoot branching number and maximum shoot length. Enhanced root length and branching number helps in proper succession of cuttings as adventitious root formation is a prerequisite for the vegetative propagation in horticulture, agriculture and forestry (Hartmann et al. 2011). Higher numbers of roots observed in present study help the plants to access more water and nutrients (Khan et al. 2012). In fact, high water availability assists plants to maintain cell turgidity (Majeed et al. 2020). Turgid cells enhanced the leaf size to harvest more light which ultimately increased yield and biomass of the plants (Zayed et al. 2011).

Table 3 Effect of iron oxide nanoparticles and EDTA functionalized iron oxide nanoparticles on maximum root length and branching number of Mulberry at different growth stage
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Evaluation of plant biomass is a primary criterion in the study of functional plant biology which might predict the resource capture, usages and bioavailability of a plant (Wilson et al. 1999; Poorter and Nagel 2000). The obtained results for mean fresh biomass (shoot and root) of various treatments were presented in Table 4. The obtained results for mean fresh shoot and root biomass of two different dosages of both the iron oxide and EDTA functionalized iron oxide nanoparticles showed no significant variation among them; however, exhibited an increased value over control and ferrous sulphate treated cuttings. As a whole, application of iron nanoparticles at the rate of 10 mg/kg soil (FeNP 10) has resulted in improvement of both shoot and root fresh biomass of the cuttings by 37% and 90% respectively in comparison with control. With increasing days after plantation, shoot and root biomass at optimum dose (FeNP EDTA 50 for shoot and FeNP 10 for root) showed a positive correlation (r2 = 0.778) sharing a ratio of 3:1. In soybean crops, it was established that magnetite nanoparticles were able to increase the leaf and pod dry weights (Sheykhbaglou et al. 2010). Askary et al. (2017) reported that iron nanoparticles treatment on Mentha piperita L. under salinity stress increased fresh and dry weight values as compared to control. Enhancement of biomass by application of iron oxide nanoparticles can be correlates with improved chlorophyll production, as photosynthesis is the most crucial process for plant growth, development and biomass production (Raines 2011; Khan et al. 2017). Root length, branching number and its succession may also played a stimulatory role in plant biomass improvement as reported by Zhang et al. (2017) who showed a positive correlation between shoot biomass and root length density. Improvement in leaf area and plant height may also be the driving force in plant biomass increment (Majeed et al. 2020).

Table 4 Effect of iron oxide nanoparticles and EDTA functionalized iron oxide nanoparticles on biomass of Mulberry at different growth stage
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Effect on Biochemical Content

Besides biomass improvement, iron oxide nanoparticles treatment significantly enhanced leaf chlorophyll content over control as well as normal iron supplementation; however, there was no significant variation among different concentrations of iron oxide and EDTA functionalized iron oxide nanoparticles (Fig. 3). Compared with control, chlorophyll content was found to be higher in Capsicum annuum treated with 0.05 mM/L iron nanoparticles (Yuan et al. 2018). Alfalfa grown in nanoscale zero valent iron (nZVI) amended soil contained more chlorophyll than control and normal Fe-EDTA treated groups (Kim et al. 2019). In plants iron acts as a key element playing vital role in electron transfer process to operate photosynthetic system (López-Millán et al. 2016). Typically, in photosynthetic cells 80% of iron is found to be involved in the synthesis of cytochrome and other heme containing molecules as well as chlorophyll and construction of Fe-S clusters (Briat et al. 2007). Both chlorophyll a and chlorophyll b are helpful in absorption of light and consequent electron transport mostly enabled by Fe–S protein (Senge et al. 2014). These Fe–S proteins (consisting of Fe–S clusters) through Fe+2/Fe+3 oxidation states transfer electrons in photosystem and its role in chlorophyll production are the crucial steps in the process of production of energy in plants, growth and development (Balk and Lobréaux 2005). Previous reports suggest that 30% improvement in photosynthesis can increase 10% relative growth (Kirschbaum 2011). Application of iron oxide nanoparticles enhanced chlorophyll content, possibly by influencing both enzymatic and biochemical activities during photosynthesis (Ghafariyan et al. 2013). In our studies, higher concentration of chlorophyll a relative to chlorophyll b was also observed, which is comparable with the findings reported by Ju et al. (2019).

Fig. 3
figure 3

Effect of iron oxide nanoparticles EDTA functionalized iron oxide nanoparticles on different biochemical parameters, A chlorophyll content, B total protein content, C total sugar, D reducing sugar, E total phenol, F ortho-di-hydric phenol, G flavonoid content.Each vertical bar above the means indicates standard deviation of three replicates (n = 3)

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Protein and sugar content of all the plants increased with increasing days after plantation. Increment rate was higher in plants treated with iron oxide nanoparticles (FeNP) or EDTA functionalized iron oxide nanoparticles (FeNP EDTA) in comparison with control. On the other hand, phenolic content exhibited contrary results, where with increasing days after plantation the phenolics phytochemicals gradually declined. High phenolic contents belonging to the cuttings treated with FeNP EDTA 50, showed improvement of 67.18%, 18.45% and 42.75% over control for total phenol, ortho-dihydric phenol and flavonol, respectively. Enhancement of total phenol content in radish root was recorded by application of combined dosage of zinc oxide and iron oxide nanoparticles (Mahmoud et al. 2019). Lopez-Vargas et al. (2018) also observed improvement of flavonoid content by 36.14% over control by application of copper nanoparticles in tomato plants. Furthermore, the higher initial phenolic content observed in present study attributed to young leaves, buds and young branches, which get matured with increasing days (Raya et al. 2015). Our results was also in conformity with Ghasemzadeh et al. (2014), who showed higher phenolic content in early growth stage of Clinacanthus nutans compared to mature one. Except FeNP EDTA 50 treated cuttings, no significant variation among different treatments in sugar content was observed. Application of FeNP EDTA 50 enhanced both total sugar and reducing sugar by 17.99% and 42.29%, respectively, in comparison with control. The final ratio of total soluble sugar and reducing sugar was observed as 127:1. This increase in sugar content is perhaps due to increased rate of photosynthesis and better accumulation of photo-assimilates (Yoon et al. 2019). Tobacco plants treated with 5 nm size ranged Fe3O4 nanoparticles have shown an increment in sugar content compared with control and other treated plants (Alkhatib et al. 2019). When Arabidopsis thaliana was exposed to nZVI, Yoon et al. (2019) observed significant enhancement of 52%, 27% and 44% of different carbohydrate metabolites like starch, sucrose and glucose content, respectively. However, on iron oxide nanoparticles exposure, Kim et al. (2019) and Wang et al. (2016) reported no significant changes in sugar accumulation compared with control. Also in current study, no such improvement in protein content was observed except FENP EDTA 50, where only 8% improvement over control was observed which supports the findings of Yoon et al. (2019).

Antioxidant Enzyme Activity

Reactive oxygen species (ROS) is normally generated as a by-product of plant cellular metabolism. When stem cuttings were isolated from main plants, certain mechanical injury was imposed; this caused biotic stress in plants. Antioxidant enzymes and biochemical defense responses are very common under the conditions of wounding (Prasad et al. 2020). A series of local response get activated to repair the damages, which includes deposition of suberin, callose, synthesis of defensive proteins, various phenolics etc. (Savatin et al. 2014). Applying an increasing amount of micro-element is known to affect the efficiency of several antioxidant enzymes which are the major ROS scavenger in plant cells and organs. Nanoparticles primarily interact with plant systems through chemical processes which generate ROS, creates oxidative damage and lipid peroxidation. According to previous reports nanoparticles generally increased the activity of antioxidant enzymes such as CAT, SOD and POD etc. (Laware and Raskar 2014). In our present study, with respect to control, significant consequence of nanoparticles interaction based on exposure time and treatment concentration were observed on the activity of all the studied enzymes (Fig. 4).

Fig. 4
figure 4

Effect of iron oxide nanoparticles EDTA functionalized iron oxide nanoparticles on different antioxidant enzymes attribute, A catalase, B peroxidase, C polyphenol oxidase, D glutathione reductase, E glutathione-s-transferase, F NADPH oxidase activity. Each vertical bar above the means indicates standard deviation of three replicates (n = 3)

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Catalase is an important heme containing enzyme in redox cycle (Shigeokaet al. 2002), showed highest activity in the plants treated with FeNP EDTA 10 at 30th DAP and following the trend up to 75th DAP. NOX also followed the same trend with an increment of 2.58-fold over control. In agreement with our observations, Rui et al. (2016) by applying different dosage of maghemite and Fe-EDTA in peanut shoots observed increased CAT activity in all the treatments exceeding control. POD is a heme protein belongs to oxido-reductases which catalyze the oxidation of a wide range of inorganic and organic substances. FeNP EDTA 50 treated plants showed highest activity of POD, which surpassed the control by 71%. In case of PPO and GR, no significant variation among two different dosages of FeNP EDTA was observed. The GST activity of plant tissue increased after exposure with different Fe treatment, being highest in FENP 10, which surpassed control by 81.93%. Control and normal iron salt supplementation (FeSO4) showed no significant variation for GR, CAT and NOX. Activities of all the studied enzymes except POD, however, increased along with the plant growth.

Higher activity of POD, CAT and protein content was observed in mung bean treated with 10 ppm nano iron-chelate which supports our findings. Similar results were also observed by applying nano-Fe oxide in wheat. Ghafari and Razmjoo (2013) observed increased content of chlorophyll, carbohydrate and protein along with higher antioxidant enzyme activities. Through lipid peroxidation assay, Hu et al. (2017) showed excess ROS production in Fe2O3 induced Citrus maxima, also showed increased production of antioxidant enzymes like CAT and POD. This might have indicated higher production of ROS and thereby increased scavenging potential of ROS to reduce oxidative stress and difficulties in plants. Becana et al. (1998) explained that, in the structures of antioxidant enzymes, shortage of iron as a cofactor leads to lowering the efficacy of antioxidant enzymes and elevating the plant’s susceptibility towards environmental stresses. According to Asl et al. (2019), even under optimal condition, different metabolic processes create ROS. This enhanced activity of antioxidant enzymes as observed in our present experiment can increase the tolerance level of plants to oxidative stress (Mittler 2002). By comparing the activities of all the studied enzymes, it is evident that the accumulation of treated particles induced strong antioxidant responses in Morus alba.

Understanding Interactions Between Various Treatments and Variables Through PCA and Heatmap-Based Clustering Approach

PCA and Heat map was used to assess the effect of application of different dosage of iron oxide and EDTA functionalized nanoparticles on mulberry propagation, to avail maximum amount of data variability and to draw an interaction between variables and treatments. First two principal components i.e. PC1 (70.37%) and PC2 (18.38%) accounted for a total of 88.75% overall data variability (Fig. 5). On the basis of factor loading values, it was observed that lower right plot mainly represents control and FeSO4 treatments (PC1 loadings are positive but PC2 loadings are negative). Higher concentration of both the iron oxide nanoparticles i.e. FeNP 50 and FeNP EDTA 50 were placed together in the lower left plot with both negative values, indicating a positive correlation. Whereas, FeNP 10 and FeNP EDTA 10 i.e. lower dose of iron oxide nanoparticles occupied the upper left plot (positive factor loadings are associated with second component and negative factor loadings are associated with first component). Presence of these two groups in different plots clearly depicted the concentration dependent effect of both the iron oxide nanoparticles on mulberry. Short distance between control and normal iron salt supplementation (FeSO4) confirmed the rather small impact of FeSO4 on the morpho-physiochemical attributes of mulberry.

Fig. 5
figure 5

Ordination diagram as obtained through principal component analysis (PCA), showing similarities between experimental treatments on 75th day dataset of overall variables

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PCA of different variables showed two major clusters (Fig. 6). First cluster grouped root attributes (root length, branching number and biomass), number of leaves per plant, most of the antioxidant enzymes (catalase, NADPH oxidase, glutathione reductase, glutathione s transferase) along with some biochemical parameters (reducing sugar, chlorophyll). That indicate shoot length, branching number and biomass were positively correlated. Increment of chlorophyll and reducing sugar in plants and placement of these two together in same cluster might be due to increment in photo-assimilates accumulation accelerated with the production of active metabolites like reducing sugar which helps in energy production. Enhancement in active metabolism leads to generation of ROS which ultimately leads to activation of antioxidant enzymes like catalase, glutathione reductase, NADPH oxidase and glutathione-s-transferase. Panda and Sarkar (2012) also showed a significant positive correlation between chlorophyll content and activities of antioxidant enzymes. Another major cluster mainly represents above ground growth parameters together with polyphenols associated with defense system and antioxidant enzymes like polyphenol oxidase and peroxidase. Initially the content of total phenol, ortho di-hydric phenol and flavonol was maximum, which gradually decreases with increasing days after plantation. The reason behind this might be due to the fact that initially the cuttings were susceptible to environmental stresses which gradually got acclimatized with increasing days after plantation. The enzyme peroxidase, using phenols played role in oxidative stress mitigation. Polyphenol oxidase also converts polyphenols to quinones group of compounds to facilitate defense system (Taranto et al. 2017). Heatmap is another data visualizing technique used, in which treatment and variables were arranged in row and column, respectively (Fig. 7). Hierarchical clustering was formed based on the proximity of relationship among attributes and treatments. Clusters obtained through heatmap were in conformity with the PCA clustering. Presence of days required for appearing first leaf and protein content were out grouped which was also observed in PCA depicted that these two attributes somehow are unique and showed different trends than the others.

Fig. 6
figure 6

Ordination diagram as obtained through principal component analysis (PCA), showing similarities between various growth and biochemical attributes, performed using the data of 75th days after plantation DRAL days required for appearing first leaf, PC protein content, NOX NADPH oxidase, SP sprouting percentage, LB leaf breadth, POD peroxidase, LL leaf length, TS total sugar, FV flavonol, PPO polyphenol oxidase, OP ortho dihydric phenol, SB shoot biomass, TP total phenol, GST glutathione s transferase, MSL minimum shoot length, RBN root branching number, CHL chlorophyll, GR glutathione reductase, RS reducing sugar, CAT catalase, MRL maximum root length, LPP number of leaves per plant, RB root biomass

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Fig. 7
figure 7

Heat map analysis of different treatments and variables. 1 = FeNP 10, 2 = FeNP EDTA 10, 3 = FeNP 50, 4 = FeNP EDTA 50, 5 = FeSO4, 6 = Control. DRAL days required for appearing first leaf, PC protein content, NOX NADPH oxidase, SP sprouting percentage, LB leaf breadth, POD peroxidase, LL leaf length, TS total sugar, FV flavonol, PPO polyphenol oxidase, OP ortho dihydric phenol, SB shoot biomass, TP total phenol, GST glutathione s transferase, MSL minimum shoot length, RBN root branching number, CHL chlorophyll, GR glutathione reductase, RS reducing sugar, CAT catalase, MRL maximum root length, LPP number of leaves per plant, RB root biomass

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Probable Mechanism of Action

The overall results obtained indicated strong potential of iron oxide nanoparticles and EDTA functionalized iron oxide nanoparticles to serve as a leading Fe-enriching micronutrients fertilizer for enhanced agricultural production. However, understanding the method of these nanoparticles uptake and accumulation in plant tissue is important for both practical applicability and safety. It is difficult to investigate interaction of nanoparticles with complex biological system like plants through a single experiment or via a single independent material characterization technique because of presence of low concentration of nanoparticles in the plant tissue and the similarity of nanoparticles with naturally occurring nanoparticles and metal ions (Boutchuen et al. 2019). Uptake of nanoparticles greatly depends upon nature of nanoparticles itself, its size, shape, chemical composition etc. (Rico et al. 2011). Judy et al. (2012) suggested that functionalization and surface modification of the nanoparticles can change and alter its absorption properties and accumulation by the plants. Because of reported favorability of cheated Fe fertilizer uptake and transportation in plants, we engineered our iron oxide nanoparticles by surface functionalization using EDTA to investigate the efficacy of chelated iron nanoparticles.

Plant follows two mechanism viz. reduction-based strategy and chelation-based strategy for uptake of iron. Reduction-based strategy involves in acidification of rhizosphere; thereby increases available Fe (III) in roots’ surroundings. Prior to its uptake by the iron-regulated transporter 1 (IRT1), root surface-localized ferric reductase oxidase 2 (FRO2) reduced Fe(III) to Fe(II) (Robinson et al. 1999; DiDonato et al. 2004). IRT1 is an Fe(II) transporter located at epidermal cells that eventually facilitates iron uptake in plants (Thomine and Vert 2013). The problem is that IRT1 has a broad specificity which also uptakes other divalent cations (zinc, cadmium, manganese, cobalt) thereby competing with iron absorption (Meda et al. 2007; Pineau et al. 2012; Lešková et al. 2017). On the other side, in chelation-based strategy plants release some phyto-siderophores (PS) in the root surroundings which forms Fe-PS chelate. These chelators are using yellow stripe-like (YSL) family of transporter protein to transport iron across the root plasma membrane.

For absorption of iron oxide nanoparticles, plant responses by acidification of rhizosphere through activation of H+-ATPase, and secretion of different organic acids and phenolics for chelation of iron, and reduction of Fe(III) to Fe(II) by ferric reductase. In response to iron deficiency, AHA (plasma membrane localized H+-ATPase) is known to pump protons across the plasma membrane (Jeong and Connolly 2009). The gene FRO2, which encodes ferric chelate reductase had an over-expression in Citrus maxima by application of Fe2O3 nanoparticles. However, the expression level of AHA was not influenced by maghemite application (Hu et al. 2017).

Plants have well developed mechanism for uptake, transportation, storage and remobilization of Fe+2 ions (Roschzttardtz et al. 2009). Roschzttardtz et al. (2013) confirmed that, in the apoplast of central cylinder, plant roots mainly accumulate iron. But problem is that like Fe+2 ions, FeNPs are not present in soluble form. By compiling all the evidence observed, Yuan et al. (2018) concluded that applied FeNPs may somehow converted into bio-available form (for example, Fe+3/Fe+2) and afterward transported towards the vascular tissues. These findings are also supported by Keller et al. (2012), who by application of FeNPs observed substantial increase in Fe+3 and/or Fe+2 concentrations. The apoplastic location and movement of FeNPs was previously supported by various viewpoints that typically nanoparticles of larger size (more than 20 nm) can’t penetrate through cell walls (Rico et al. 2013; Martínez-Fernández and Komárek, 2016). Figure 8 shows a diagrammatic representation of the root strategies and possible routes for iron uptake and translocation into aerial plant parts.

Fig. 8
figure 8

Probable mechanism of iron nanoparticles uptake and translocation in plants, A iron oxide nanoparticles, B EDTA, C EDTA functionalized iron oxide nanoparticles, D mulberry plant, E foliar uptake, F root strategy to uptake iron, G translocation of uptaken nanoparticles through vascular system. CT cuticle, EP epidermis, PM palisade mesophyll, SM spongy mesophyll, VB vascular bundle, ST Stoma, CX cortex, ES epidermis, CS casparian strip, PL phloem, CC companion cell, XM xylem

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Once the iron nanoparticles penetrate into the plants, they can follow two different paths to move through tissues i.e. apoplast or symplast. Apoplastic transport involve movement of water and substances through the extracellular spaces, xylem vessels and cell walls of adjacent cells and takes place outside the plasma membrane (Sattelmacher 2001), whereas in symplastic movement transportation takes place through the specialized structure called plasmodesmata (Roberts and Oparka 2003). Radial movement of nanoparticles within plant tissues was mainly triggered by apoplastic pathway which assists nanomaterials to reach the root central cylinder and the vascular tissues (Larue et al. 2012; Zhao et al. 2012; Sun et al. 2014). Once it reaches the central cylinder, following the transpiration stream nanoparticles can further move upward to the aerial part through xylem (Cifuentes et al. 2010; Wang et al. 2012; Sun et al. 2014). However, through apoplastic pathway transportation can be stopped at casparian strip (Larue et al. 2012; Sun et al. 2014; Lv et al. 2015) and some nanomaterials can be accumulated there. To overcome this hydrophobic layer, they have to follow symplastic pathway via endodermal cells (Robards and Robb 1972). Symplastic transport is also possible in the phloem using sieve tube elements, which allow distribution towards non photosynthetic tissues and organs (Wang et al. 2012; Raliya et al. 2016).

On the other hand, in case of foliar applications, nanoparticles have to cross cuticular barrier following the lipophilic or hydrophilic pathway (Schönherr 2002). In lipophilic pathway diffusion takes place trough cuticular waxes, whereas the hydrophilic pathway involves dispersion through polar aqueous pores of cuticle or stomata (Eichert et al. 2008; Eichert and Goldbach, 2008). In comparison to cuticular pores (pore diameter-2 nm), the stomatal diffusion pathway appears as more appropriate route for nanomaterials penetration with a size exclusion limit of more than 10 nm (Eichert et al. 2008). Nanoparticles after entering the leaf apoplast through stomatal pathway may undergo long distance transport through vascular system. Previous reports suggested that sugars, photosynthate and other macromolecules reside in the leaf can be transported downward to the shoot and root through phloem (Lough and Lucas, 2006). Wang et al. (2013) by applying four metal oxide nanoparticles (size ranges 24–47 nm) in watermelon plant observed that small sized nanoparticles can penetrate the leaf and can reached the shoots and roots. The results indicated the ability of nanoparticles uptake by leaf to reach the roots through phloem sieve tubes.

Conclusion

In summary, this work reports the effects of iron oxide nanoparticles and EDTA functionalized iron oxide nanoparticles on the phenotypic characteristics of Morus alba, showing enhancement in biomass and different growth attributes. Applied nanoparticles also exhibited greater impact on several biochemical and antioxidant enzymes attributes. These nanoparticles might be an ideal substitution for the traditional iron fertilizer and will be helpful in fortification of plants with nutritional value. However, some points like the mechanism behind the transformation of FeNP into available form, mobilization, sequestration and accumulation of nanoparticles should be investigated and improvement in understanding the toxicological effects like generations of ROS through FeNPs oxidation will require further study.