Green inspired synthesis of zinc oxide nanoparticles using Silybum marianum (milk thistle) extract and evaluation of their potential pesticidal and phytopathogens activities

Introduction

The rapidly developing field of nanotechnology is considered a significant achievement in the agricultural sector for increasing pest mortality and crop production. Bacteria, weeds, insects, and fungi have an adverse effect on agricultural resources, resulting in poor product quality and yield. Therefore, chemical pesticides such as fumigants and insecticides have been commonly used to control pests worldwide. Many issues are associated with using chemical pesticides, including harmful effects on non-target species and the environment, non-biodegradable nature, pest resistance, and human health safety. As a result of these, there is a considerable demand for biopesticides that are both safe and environmentally friendly (Melanie et al., 2022; Shahbaz et al., 2023).

Bio-pesticides are organic compounds derived from naturally occurring sources such as microorganisms, fungi, and plants used to kill pests. They are preferred over synthetic pesticides because they are safe and biodegradable (Deka et al., 2022). Many compounds, including Clitoria ternatea extract, stilbenes of grape cane, oxymatrine (alkaloid compound), and olive mill oil, have recently been experienced as bio-pesticides to kill a variety of pests (Damalas & Koutroubas, 2018). However, due to fewer field applications, delivery issues, and lower stability, biopesticides only captured 5% ($3 billion) of the global crop protection market, failing to overtake synthetic pesticides (Balakrishnan et al., 2019; Damalas & Koutroubas, 2018). Therefore, to overcome the delivery problems of biopesticides, an advanced emerging field of nanotechnology has been introduced to improve bio-pesticide stability and delivery time. Different types of metal nanoparticles (gold, copper, silver, and zinc) have been utilized in combination with biopesticides owing to this increasing solubility of less soluble active ingredients, durability, efficacy, improved dissolution rate, the slow release of active ingredients, and reduced degradation of active ingredients, controlled release of active components, better stability, enhanced absorption and bioavailability (Narware et al., 2019). Therefore, it is considered that nanotechnology can provide a green and competent alternative for managing insect pests in agriculture without disturbing natural harmony (Bhattacharyya, Colombo & Sotiriou, 2016).

Among the metal oxide nanoparticles, ZnO-NPs have gained significant importance due to being nontoxic, multifunctional, low-cost, biocompatible, and eco-friendly materials with many applications in different fields like the food industry, medicines, anti-fungal and as antimicrobial agent (Espitia Rangel et al., 2012), paints, sunscreens, and coatings due to high UV protection, optoelectronics, and optics (Saha, Khlystov & Grieshop, 2018), elimination of heavy metals from water (Ishwarya et al., 2018), and finally in medical fields such as nano diagnostics, nanomedicine, drug delivery, and gene delivery (Patwekar et al., 2022). ZnO-based nano biopesticides have effectively controlled T. castaneum and S. oryzae with higher mortality rates. ZnO-NPs have recently been used as antibacterial agents in food packaging, textile fabrics, mouthwash, ointments, and lotions to stop microbial contamination (Jiménez-Rosado et al., 2022). ZnO-NPs have been synthesized using different physical and chemical approaches, including hydrothermal, co-precipitation, microwave-assisted, thermal decomposition, ultrasonic synthesis, sol-gel, and electrochemical methods. These methods are costly, toxic, require higher energy consumption, high temperature, and pressure, economic instability, long-term procedure, time-consuming, and employ poisonous solvents and chemicals that are harmful to public health and the environment (Aldeen, Mohamed & Maaza, 2022; Rafique et al., 2017). Therefore, as an alternative, green synthesis has been a preferred approach for synthesizing ZnO-NPs due to several significant characteristics, including safety, environmentally friendly protocols with nontoxic byproducts, mild reaction conditions, simple, reliable, single step, economical and the use of natural capping and reducing agents, it has attracted significantly more attention than the other contemporary techniques (both physical and chemical) (Prasad et al., 2019; Velsankar et al., 2022).

Different studies proposed that owing to the high synthesis rate, plant extracts are better nominees and more suitable for large-scale production of green nanoparticles than other organisms. Nanoparticles synthesized using plant extracts have more variations in size and shape than those synthesized from bacteria, fungi, and yeast (Swaminathan & Sharma, 2019). Therefore, plant-medicated green synthesis of metal nanoparticles is gaining popularity over the microorganism-mediated green synthesis methods because plants are easily accessible, safe to handle, and contain different physicochemical such as alkaloids, terpenoids, flavonoids, quinines, tannins, and phenols that act as a reducing and stabilizing agent (Baker et al., 2013). Green synthesis of ZnO-NPs by using Ocimum americanum, Abelmoschus esculentus, Pisonia grandis, Berberis aristata, Cuminnum cyminum, Cassia alata, Kumar, Zare & Ghosh (2017), Azedarach indica, Alestonias cholaris, Pongamia pinnata, Calotropis gigantea leaf extract, Mangifera indica (Rajeshkumar et al., 2018) and Aloe barbadensis mille and other phytocompounds (terpenoids, alkaloids, flavonoids, tannins, carotenoids, and chlorophylls) have been already demonstrated, but they have limitations to get desire results (Mahendiran et al., 2017; Sadiq et al., 2021).

Silybum Marianum (Milk thistle) is a plant of the Carduus Marianum family (Al-Hashem, Akbar & Morris, 2019). Silymarin is a flavonoid and obtained from Silybum Marianum; it is a mixture of different types of polyphenolic compounds, including silychristin (silydianin), flavonolignans (isosilybin A, silybin A, silybin B, isosilychristin, isosilybin B, and a taxifolin (flavonoid)). The presence of phytochemicals is the probable mechanism for the green synthesis of nanoparticles. Terpenoids, flavonoids, quinones, carboxylic acids, amides, ketones, and aldehydes are phytochemicals that act as reducing and capping agents for various metal ions; silymarin is nontoxic and can be used as a safe herbal medicine. The extract of Silybum marianum was used for the synthesis of ZnO nanoparticles through Keto-enol Tautomerization (Al-Hashem, Akbar & Morris, 2019).

However, the current study aimed to synthesize the zinc oxide nanoparticles (ZnO-NPs) from the seed extract of Silybum marianum (Milk thistle) using the precipitation method. Secondly, the optimization of synthesis parameters through RSM was performed. Then pesticide activity of NPs-ZnO-based biopesticides was analyzed against two pests, including Tribolium castaneum and Sitophilus oryzae. The present study also assessed the antibacterial (Clavibacter michiganensis and Pseudomonas syringae) and antifungal (Fusarium oxysporum and Aspergillums niger) activities of ZnO-NPs for better understanding.

Materials and Methods

Results

Characterization of green synthesized ZnO-NPs

Various techniques have been used to characterize the ZnO nanoparticles, such as UV visible, Zetasizer, FTIR, SEM, TEM, AFM, and XRD spectroscopy, but due to unavailability and high cost, only UV visible and Zetasizer analysis was performed in the current study. Zinc oxide nanoparticles (ZnO-NPs) formation was observed by vision when a salt solution was added to the plant extract of Silybum marianum. The color change from yellow to white milky confirmed the ZnO-NPs formation. Silybum marianum extract has a yellow color. The color change was due to the presence of the energetic molecule in Silybum marianum extract.

UV-visible spectroscopy

The maximum wavelength (λ max) for all the treatments (27) was determined using a UV-visible spectrophotometer (HITACHI U-2900) in a wavelength range from 200–600 nm. The results of UV-visible spectroscopy revealed that the absorption spectrum of ZnO-NPs was observed only for treatment (R₁₁) at 360.5 nm wavelength when the sample conditions were at a temperature of 80 °C, stirring time of 120 mins, pH of 12, and salt concentration of 0.06 M. Moreover, the absorption band at 360.5 nm confirmed the synthesis of ZnO-NPs through UV-visible spectroscopy (see Table 2).

Table 2:

The results of response (λ max) of different runs of prepared ZnO-NPs.

Run no.	Temperature (°C)	Stirring time (min)	pH	Salt concentration (M)	Response (nm) λ max
1	70	80	11	0.21	355
2	80	40	12	0.60	376
3	60	40	12	0.60	379
4	60	40	10	0.60	320
5	50	80	11	0.33	325
6	80	120	10	0.06	370
7	80	40	10	0.60	305
8	80	40	12	0.06	353
9	70	160	11	0.33	326
10	70	2.00	11	0.33	304
11	80	120	12	0.06	360.5
12	80	40	10	0.06	377
13	80	120	12	0.60	384
14	70	80	9	0.33	310
15	70	80	11	0.33	347
16	60	120	10	0.60	374
17	70	80	11	0.87	400
18	60	40	10	0.06	357
19	60	40	12	0.06	325.5
20	70	80	11	0.33	347
21	80	120	10	0.06	370
22	70	80	11	0.33	347
23	60	120	12	0.06	369
24	60	120	12	0.60	382
25	60	120	10	0.60	374
26	70	80	13	0.33	332
27	90	80	11	0.33	352

DOI: 10.7717/peerj.15743/table-2

Zetasizer measurement

A Zetasizer evaluated the average size and polydispersity of biosynthesized ZnO-NPs. The results showed the average particle size of about 51.80 nm for R₁₁ of ZnO-NPs at 80 °C, a stirring time of 120 min, a salt concentration of 0.06 M, and pH 12 (see Fig. 1). Results showed that particles are monodispersed in nature. The homogeneity among the size of particles was estimated by the polydispersity index (PDI). The results revealed the minimum PDI of about 0.443 for green synthesized R₁₁ of ZnO-NPs. Studies showed that if the PDI value is less than 0.7, different size distributions are monodispersed in the sample (Wong et al., 2020). The above results confirmed that ZnO-NPs were monodispersed with a PDI value of 0.44, less than 0.7.

Optimization of parameters for ZnO-NPs synthesis through response surface methodology (RSM)

Optimization by the conventional techniques was expensive, time-consuming, needed a large amount of experimental work, and involved a one-factor process. However, it did not explain the interaction effect between variables (Garai et al., 2022). A new statical technique was introduced called response surface methodology (RSM) to overcome this problem. It is a collection of techniques used to analyze and design various experiments and determine the effect of different variables on a response variable. The present research used the central composite design (CCD) of RSM. CCD optimized the synthesis parameters (temperature, pH, concentration, and stirring time) and reduced the time of experiment and cost by decreasing the number of runs performed in the laboratory (Usman & Aziz, 2018).

Selection of an adequate model

The selection of the model was the first step for the optimization of synthesis parameters. Its selection was based on p-value and F-value. If the probability value was smaller (less than 0.05), it was significant and considered highly significant if the p-value was less than 0.0001.

In Table 3, a smaller p-value of 0.0121 and a larger F-value of 5.12 for the quadratic model indicated that the model was significant. However, the lack of fit model was non-significant for the quadratic model with a p-value (0.1596) and F- value (5.65). Moreover, the R² value (0.7798), adjusted R² value (0.5230), and predicted R² values (−0.5040) for the quadratic model were determined from model summary statistics. The results revealed that the quadratic model gave an outstanding description of the relationship between independent variables and response variables (wavelength). Therefore, it was selected for the optimization of a parameter to synthesize the ZnO-NPs.

Table 3:

The results of analysis of variance of synthesized ZnO-NPs.

Source	Sum of squares	df	Mean squares	F value	p-value prob > F	Model
Mean vs total	3.352E + 006	1	3.352E + 006			Suggested
Linear vs mean	4,163.98	4	1,041.00	1.45	0.2505
2F1 vs linear	3,887.00	6	647.83	0.87	0.5361
Quadratic vs 2F1	7,493.01	4	1,873.25	5.12	0.0121	Suggested
Cubic vs quadra	4,237.51	9	470.83	9.35	0.0461	Aliased
Residual	151.00	3	50.33
Total	3.372E + 006	27	1.249E + 005

DOI: 10.7717/peerj.15743/table-3

Regression analysis

The adequate model for optimizing parameters was selected based on p and F values. The current study used multiple regression analysis to fit the response wavelength. This model represented the response (λ max) R as a function of (A) temperature, (B) stirring time, (C) pH, and (D) salt concentration. The relation between input variables and response variables in terms of a coded factor is given below in Eq. (2):

Quadratic equation in terms of coded factors:

(2) $$\begin{array}{l}\text{Wavelength }(\text{response})R=(+340.11+4.13\text{A}+10.82\text{B}+4.33\text{C}-2.00\text{D}\\ -0.88\text{AB}-0.56\text{AC}-3.33\text{AD}-5.56\text{BC}+4.94\text{BD}\\ +13.25\text{CD}+2.12\text{A}2-3.90\text{B}2-2.24\text{C}2+21.18\text{D}2)\end{array}$$

This equation explained the effect of a single variable or combination of two or more variables on response R. The Positive values of coefficients determined the positive interaction of variables and their effect on response R. Negative values indicated the interfering effect of input variables on response wavelength R.

The results revealed that a smaller p-value, such as 0.0121, and a larger F-value of 5.12 for the quadratic model indicated that the model was significant. However, the lack of fit model was non-significant for a quadratic model, confirming their maximum fitness on the effect of synthesis parameters (see Table 3). Moreover, the goodness of fit model or the coefficient of variation (C.V%) of the model was estimated by calculating the values of the coefficient of determination R², predicted R², and adjusted R². The higher R² value of 0.7798, adjusted R² value of 0.5230, and predicted R² values of −0.5040 for the quadratic model were good measures of overall accuracy and fitness (see Table 4). These results revealed that the quadratic model gave an excellent description of the relationship between independent variables (temperature, pH, stirring times, and salt concentration) and response (λ max). Therefore, it was selected to optimize conditions for the green synthesis of ZnO-NPs.

Table 4:

The model summary of synthesized ZnO-NPs.

Source	Std. Dev	R-squared	Adjusted R-squared	Predicted R-squared
Linear	26.77	0.2089	0.0651	−0.2460
2F1	27.25	0.4039	0.0314	−0.8646
Quadratic	19.12	0.7798	0.5230	−0.5040
Cubic	7.09	0.9924	0.9343	—

DOI: 10.7717/peerj.15743/table-4

The statistical importance of the quadratic equation was determined by analysis of variance for the response surface quadratic model for (response wavelength, R). However, p-values were used as a significant tool for each coefficient. If it was less than 0.05, it was significant, and if it was less than 0.0001 considered highly significant. Moreover, if it was higher than 0.05, model terms were estimated as non-significant. In Table 5, the F-value of a model (3.04) and Prob > F value of 0.0305 indicated that the model was significant. The F-value for the lack and fit model was 5.65, and the Prob > F value was 0.1596, confirming that the lack and fit model was non-significant (see Table 5).

Table 5:

Analysis of variance for interactive effect of parameters of synthesized ZnO-NPs.

Source	Sum of squares	df	Mean square	F-value	p-value Prob > F	Model
Model	1,554,399	14	1,110.29	3.04	0.0305	Significant
A-Temperature	408.38	1	408.38	1.12	0.3114
B-Stirring time	2,783.74	1	2,783.74	7.61	0.0173
C-Ph	450.67	1	450.67	1.23	0.2887
D-Salt concentration	69.37	1	69.37	0.19	0.6709
AB	12.25	1	12.25	0.033	0.8578
AC	5.06	1	5.06	0.014	0.9083
AD	175.56	1	175.56	0.48	0.5016
BC	495.06	1	495.06	1.35	0.2672
BD	390.06	1	390.06	1.07	0.3221
CD	2,809.00	1	2,809.00	7.68	0.0169
A^2	107.48	1	107.48	0.29	0.5977
B^2	341.30	1	341.30	0.93	0.3531
C^2	117.33	1	117.33	0.32	0.5816
D^2	6,397.34	1	6,397.34	17.49	0.0013
Residual	4,388.51	12	365.71
Lack of fit	4,238.511	10	423.85	5.65	0.1596	Non-significant
Pure error	150.00	2	75.00	—	—
CCR total	1,9932.50	26	—	—	—

DOI: 10.7717/peerj.15743/table-5

Diagnostic plots

The analysis of the relation between predicted and actual values data was evaluated as presented in Fig. 2. From a normal plot of residual, predicted vs actual plot, and residual vs run plot, it was determined that the quadratic model was significant for estimating response over input variables. A normal probability plot of the studentized residuals checked the normality of residuals. A constant error was checked by studentized residuals vs predicted values. A residual vs run plot was used to check the outlier’s values in the data.

Factor affecting the synthesis of ZnO-NPs

Various yield-affecting conditions for the synthesis of ZnO-NPs, including temperature, pH, salt concentration, and stirring time, were optimized (see Fig. 3). The absorption spectra of ZnO-NPs were recorded in the wavelength range of 250–378 nm. The results showed that a maximum amount of ZnO-NPs were synthesized at a wavelength of 360.5 nm and 80 °C. The λmax showed that when the temperature increased, the λ max was also increased, which influenced the synthesis of ZnO-NPs. Similarly, pH of the solution was another factor that influenced the synthesis of ZnO-NPs. A UV-visible study showed that basic pH (12) was favorable for forming ZnO-NPs because it abruptly changed the color of the solution from yellow to milky white. The 3D graph showed that the maximum yield of ZnO-NPs was obtained at pH 12 and a temperature of 80 °C.

In contrast, the response wavelength λ max was 360.5 nm. An increase in pH cause to enhance the nucleation center, which increased λ max and promoted the synthesis of ZnO-NPs. Furthermore, stirring time and salt concentration influenced the shape, size, and synthesis rate of ZnO-NPs. UV-visible spectroscopy showed that the synthesis of ZnO-NPs was maximum when stirring time optimized as 120 min and salt concentration as 0.06 M at λ max of 360.5 nm. At this stirring, the collision frequency of particles was high, which promoted the reduction of Zn ions into Zn metal nanoparticles.

Discussion

Globally, each year grain yield is wasted during storage due to insects and pests (Rani et al., 2021). Tribolium castaneum and Sitophilus oryzae are destructive wheat, rice, and maize pests worldwide. Clavibacter michiganensis and Pseudomonas syringes are gram-positive and gram-negative phytopathogenic bacterial strains responsible for canker (Atiq et al., 2022) and wilting in tomatoes, ring rot in potatoes, and bacterial apical necrosis (BAN) in mango trees (Miller et al., 2019). Similarly, Fusarium oxysporum and Aspergillus niger also cause black mold disease in vegetables and fruits such as apricots, onions, grapes, and peanuts (Tolossa & Shibeshi, 2022). These pests have majorly been managed using synthetic pesticides. However, many serious concerns are associated with using chemical pesticides, including harmful effects on non-target species and the environment, non-biodegradable nature, pest resistance, and human health safety. It was estimated that many people get poisoned by pesticides in a year due to inappropriate use, and 75% of these are agricultural workers (Singh, Kaur & Aggarwal, 2022). Based on these facts, there is a considerable demand for safe and environmentally friendly pesticides. Therefore, researchers are trying to develop biocompatible, sustainable, and nontoxic biopesticides that have encouraging applications in different fields of agriculture and medicine (Palermo et al., 2021). In this regard, ZnO-NPs have proved to be a promising source of safe insecticides, very effective in controlling store grain pests and phytopathogenic bacterial and fungal strains at environmentally friendly and very low dosages (Jasrotia et al., 2022). This study aimed to synthesize zinc oxide nanoparticles (ZnO-NPs) with seeds extract of Silybum marianum, which have been used as novel green pesticides to replace present synthetic pesticides. Green synthesized ZnO-NPs has unique properties such as small size, high surface area to volume ratio, biodegradability, less toxicity and remarkable stability that enhances their use in drug delivery as an antifungal, antibacterial, and pesticidal agent.

The temperature was the most significant factor for the synthesis of nanoparticles, which controls the rate of growth and size of nanoparticles by affecting nucleation. This study optimized the temperature as 80 °C at λ max of 360.5 nm. Karam & Abdulrahman (2022) reported the synthesis of ZnO nanoparticles from the leaf extract of a thyme plant by using a green method at different temperatures of 150 °C, 250 °C, 350 °C, and 450 °C. Similarly, pH was optimized as 12. At this pH, maximum ZnO-NPs were synthesized.

Further, increase in pH to 13, the aggregation and deformation of biomolecules occurred, which decreased the response wavelength and is responsible for forming larger ZnO-NPs. Shabaani et al. (2020) reported the synthesis of ZnO-NPs using plant extracts of Eriobotrya japonica and Musa acuminata at various pH values. They found that basic pH 12 was important for the production of ZnO-NPs. Similarly, Umamaheswari et al. (2021) synthesized ZnO-NPs from the Raphanus sativus extract at pH 14,12, 10, and 8. They observed that no absorption peak was reported at pH 8-10 or 14, but a characteristic absorption peak of 369 nm was found at pH value of 12.

Stirring time and salt concentrations were other factors that influenced the shape, size, and synthesis rate of ZnO-NPs. The optimized stirring time was 120 min, and the salt concentration of 0.06 M for the maximum synthesis of ZnO-NPs. At this stirring, the collision frequency of particles was high, which promoted the reduction of Zn ions to Zn metal particles. Manzhi et al. (2019) reported that the variation in time occurred in different ways, such as aggregation and shrinkage of particles due to long storage time. It also affected the crystal structure and shape of ZnO-NPs. Rasli, Basri & Harun (2020) observed the effect of salt concentration on the morphology of ZnO-NPs synthesized using aloe vera extract. Abdullah et al. (2020) reported the synthesis of ZnO-NPs using peel extract of Musa acuminata at 0.01 M/L concentration. It was found that maximum nanoparticles were formed at the lowest salt concentration. Moreover, Jamdagni, Khatri & Rana (2018) synthesized ZnO-NPs using plant extract of Cassia auriculata at different reaction times 0.5, 1, and 2 h. It was examined from the results that a higher yield of ZnO-NPs was formed when the reaction time was 2 h.

Zetasizer analysis of green synthesized ZnO-NPs revealed that particles were monodispersed with a minimum size of 51.80 nm. Nano size provides a larger surface area for actions and greater availability of ions that improve the activity of ZnO-NPs. Kamarajan et al. (2022) reported that Acalypha indica extract-based ZnO-NPs showed a particle size of 46 nm at different conditions. It was found that these nanoparticles were monodispersed and showed maximum (96%) degradation efficiency.

Results of the pesticide activity of ZnO-NPs revealed that maximum pesticide activity was observed at 6% concentration of ZnO-NPs and seed extract of Silybum marianum after 72 h against both pests as Tribolium castaneum and Sitophilus oryzae. Our results are in accordance with the result of Haider et al. (2020), who found that a toxicity bioassay of Tribolium castaneum was carried out by the plant extracts of three different concentrations (5%, 10%, and 15%) after a time interval of 24, 48 and 72. They reported the minimum mortality rate of pests of about 15.10% and the highest mortality rate of 46.12% against Tribolium castaneum. However, in the case of nanoparticles, the maximum mortality rate of 66.32% was noticed against Tribolium castaneum.

Moreover, the study was conducted on the therapeutic potential of CuNPs for curing bovine mastitis. For this purpose, various groups of rats were taken, and 6.25 g/mL (25 nm) CuNPs were chosen as the intramammary (IM) treatment for S. aureus-induced mastitis in rats since the in vitro sensitivity test revealed a significant zone of inhibition at this dose and negligible cell damage on fibroblast cell lines (Taifa et al., 2022). Similarly, vancomycin-based silver nanoparticles were synthesized as nano-drug complexes (van@AgNPs), and their synergetic antibacterial efficacy against Staphylococcus aureus and Escherichia coli was evaluated by Well Diffusion Method. The antibacterial potential of both bacteria was considerably increased. The present study revealed that ZnO-NPs showed better pesticide results than seed extract of Silybum marianum.

The results of antibacterial activity demonstrated that ZnO-NPs exhibited higher antibacterial activity against Clavibacter michigannessis (18 ± 0.4 mm) and Pseudomonas syringes (25 ± 0.4 mm) at a sample concentration of 3%. It was estimated that increased ZnO-NPs concentration enhanced the release of reducing sugar, proteins, and DNA from the extracellular cytosol of the cell membrane. It also increased the reactive oxygen species (ROS) that destroyed the bacterial cells owing to these showing greater zone of inhibition and greater antibacterial activity. Moreover, the above results clarified that ZnO-NPs had greater antimicrobial activity (p < 0.001) against gram-negative bacteria (Pseudomonas syringae) as compared to Gram-positive bacteria (Clavibacter michiganensis). The reason is that gram-negative bacteria have an outer membrane that changes the hydrophobic properties or causes mutations. On the other hand, Gram-positive bacteria lack this important membrane, making them vulnerable. Obeizi et al. (2020) found that ZnO-NPs synthesized from the essential oil of Eucalyptus globulus exhibited a maximum inhibitory effect of 19.35 ± 0.45 mm against Stymphilococus pneumoniae at a concentration of 100 μg/mL. Moreover, the SeNPs were synthesized from the leaf extract of Elaeagnus indica, and their antimicrobial potential was evaluated. These green synthesized nanoparticles (10–15nm) showed significant antibacterial potential against the strains of Salmonella typhimurium and Fusarium oxysporum. The concentration (10 µg/mL) was noted as the lowest minimum inhibitory concentration against both pathogens (Indhira et al., 2023).

Furthermore, antifungal activity results revealed that ZnO-NPs showed more activity than seed extract. The zone of inhibition for Aspergillus niger was noted as 19 ± 0.8 and 21 ± 0.57 mm against Fusarium oxysporum at a sample concentration of 3%. The results of the present study showed that the antifungal activity of ZnO-NPs was concentration-dependent. The maximum inhibitory effect of ZnO-NPs was conducted at a higher concentration of 3% for both strains. Madan, Wasewar & Kumar, 2017 reported that the availability of ions increased due to higher concentration. More Zn⁺² ions attached to pathogen biomolecules caused DNA destruction and produced reactive oxygen species and oxidative stress in the fungal cell membrane. However, due to the high availability of (H and O) atoms, the synthetic drug voriconazole showed a greater inhibition zone than seed extract and ZnO-NPs. Horue et al. (2020) found that ZnO-NPs synthesized from Pongamia glabra extract exhibited a maximum inhibitory effect of 18 ± 0.6 mm against Rhizopus nigricans.

Moreover, Nassar (2018) reported that Azadirachta indica based ZnO-NPs exhibited a maximum zone of inhibition of 17.80 ± 4.52 mm against Sclerotium rolfsii and Rhizoctonia solani. However, there are some limitations of our study concerned with the complexity of plant components, their seasonal and geographical distribution, and low purity and yield. Several plant materials are available for the green synthesis of NPs, and different investigators have explored locally present and abundantly available plants. Such studies provide the opportunity to fully use native plants, but large-scale worldwide production of green-synthesized nanoscale metals is difficult to achieve. The plant synthesizing silver nanoparticles is found in India, the Philippines, Sri Lanka, Malaysia, and South China (Roopan et al., 2019). Au-NPs were synthesized from Fenugreek, which was widely distributed on the east coast of the Mediterranean and China, while peppermint is native to West Asia and Central Europe (Aromal & Philip, 2012). Similarly, the synthesis process concerns long reaction time, use of other industrial chemical reagents, and excessive energy consumption. For example, Cu NPs were synthesized at 80 °C for 2 h (Muthuvel, Jothibas & Manoharan, 2020), and Au NPs were synthesized from Cystoseira baccata (brown algae) at −24 °C, which also consumed a large amount of energy and intensive equipment such that freezer (Khatami et al., 2018).

Conclusions

Green ZnO-based NPs of Silybum marianum exhibited a promising potential to be used as a substitute for the more harmful insecticides. Although the environmental effects of using ZnO nanoparticles as an insecticide should be investigated further, one obvious advantage of using them as insecticides is the low risk of insect resistance developing over the course of time. Additionally, Zn is one of the micronutrients found in both human and animal diets, so when consumed by either of them, it tends to be beneficial rather than harmful. The results of this research demonstrate the potential for using ZnO nanoparticles to not only remove Tribolium castaneum and Sitophilus oryzae but also significantly decrease their population in the ecosystem by causing deformations, reduce oviposition, reduce fecundity, and egg hatchability. It is a useful tool for integrated pest management. Moreover, it is suggested that Silybum marianum plant could be used in combination with another plant and would show more efficient activity for other pests like an aphid.

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