The Main Compounds of Bio-Fumigant Plants and Their Role in Controlling the Root-Knot Nematode Meloidogyne incognita (Kofoid and White) Chitwood

Abstract

Meloidogyne spp. are important parasitic nematodes affecting a variety of plants worldwide. We investigated the nematicidal properties of specific compounds found in bio-fumigant plants, particularly linalool, nonanal, methylene chloride, and 2-Decanal. Laboratory findings revealed that methylene chloride and 2-Decenal effectively reduced populations of second-stage juveniles (J2s). Additionally, the research explored the effects of tomato (Solanum lycopersicum L.) on M. incognita J2s, observing that tomato leaves significantly increased J2 mortality for all time measurements and different temperatures, while the opposite results were observed for root-stems. In the study, leaf treatment resulted in a maximum mortality response (MR_max) and half-maximal effective concentration (EC₅₀) of approximately 100% and 4.0 µg/mg, respectively, at a temperature of 35 °C by week 8. In contrast, the root-stems treatment showed an MR_max of 13.5% and an EC₅₀ of 3.0 ± 1.7 µg/mg. GC-MS analysis identified key compounds in tomato leaves and root-stems, such as α-pinene, d-limonene, and linalool. The results suggest that tomato leaves have potential as effective bio-fumigants for controlling root-knot nematodes.

1. Introduction

Tomato (Solanum lycopersicum L.) is one of the most important vegetables in the world, belonging to the very large Solanaceae family [1]. There are many pests and diseases, like plant parasitic nematodes, that damage the quality and quantity of tomato production [2].

All soil pathogens, including nematodes, significantly reduce the quality of agricultural products worldwide [3]. Although nematodes are not fatal most of the time, they can decrease the plant performance by feeding on it, disrupting water transfer and transmitting viruses [4]. Plant-parasitic nematodes are the most harmful roundworms, which are classified into four groups: (i) ectoparasites, (ii) semi-endoparasites, (iii) migratory endoparasites, and (iv) sedentary endoparasites [5]. Root-knot nematodes (RKNs) (Meloidogyne spp.) are the main species damaging Solanaceae plants all over the world [6]. The damage of the endoparasitic nematode Meloidogyne incognita (Kofoid and White) Chitwood (Tylenchida: Heteroderidae) is so serious in a wide range of agricultural products, such as tomatoes [2,7].

Since the effective control of nematodes is very difficult, various methods, including the use of fumigant and non-fumigant nematicides, cultural methods, biological control, and the use of resistant cultivars, have been used to control plant pathogenic nematodes [8]. The detrimental side effects of overusing synthetic chemicals have contributed to the study of new strategies and plant defense mechanisms against pathogenics by plant nematologists [9].

One of these plant defense mechanisms is the production of metabolites with anti-nematode activity, which have been named anti-nematode phytochemicals [10]. Plant metabolites are divided into primary and secondary groups. Primary metabolites are responsible for the formation of new cells, while secondary metabolites have no effect on plant growth, but they play an important role in the emergence of resistance to pests and diseases, attraction of pollinators, and abiotic stress tolerance [11,12]. For example, Eupatorium adenophorum Spreng (synonym: Ageratina adenophora (Spreng.)) has been gradually recognized as an anti-nematode and insecticide agent in recent years and it belongs to the Asteraceae family [13,14]. This bio-fumigant has diverse groups of secondary metabolites, including monoterpenes, sesquiterpenes, diterpenes, triterpenes, flavonoids, polysaccharides, pyrrolizidine alkaloids, and phenylpropanoids [15]. The study of bio-fumigant plants has revealed the fact that secondary metabolites extracted from some Solanaceae species reduce plant pathogens such as nematodes [9]. In contrast, the spread of chemical signals from some plant roots into the soil can absorb some nematodes which contribute to root infestation [16]. For example, some main compounds, such as tannic acids, flavonoids, glycosides, fatty acids, and volatile organic molecules, can attract second-stage juveniles (J2s), due to which the interaction between nematodes and host plants is regulated [17]. Because of this characteristic in some plant roots, a trap strategy can be applied to control RKNs. In this context, trap plants can grow among the main crops. These trap plants reduce nematode damage to the main crop by attracting and capturing RKNs. Trap plants have characteristics that are able to attract nematodes more than the main cultivated crops. This method of using a trap plant strategy may be a better alternative to chemical control. In addition, this strategy can be used in an integrated pest management (IPM) program alongside other methods to control RKNs [18].

Accordingly, our research aims are as follows: (1) continuing the study of the main compounds of dried leaves of E. adenophorum in the previous research [13], which caused an increase in the population of M. incognita J2, (2) studying tomato nematicide (S. lycopersicum L.) on RKN M. incognita, and (3) identifying the volatile compounds extracted from tomato S. lycopersicum L.

2. Materials and Methods

2.1. Bio-Fumigant Plants

Tomato plants (S. lycopersicum cv Zhongza 09) were purchased from (China Vegetable Seed Technology Co., Ltd., Beijing, China). The leaves, root, and stems of S. lycopersicum were placed separately for one week in a dark and dry place at room temperature (28 °C) to dry. Dried leaves and a dried combination of root-stems were powdered separately by a grinder (Qufu Shunyang Machinery Co. Ltd.; Jining, China), and then kept in special vacuum zipper bags.

2.2. Identification of Chemical Compounds

The headspace method was used to analyze the main compounds of tomato S. lycopersicum L., according to the Zhang et al. [19] method. Gas chromatography (GC) analysis was performed on the main compounds of the leaves, and the root-stems of the tomato in separate treatments at two temperatures of 25 °C and 35 °C and different times (e.g., 1, 2, 3, 4, and 8 weeks) were studied in three repetitions. Tomato samples were analyzed with gas chromatography–mass spectroscopy (GC-MS) analysis on a SHIMADZU GC-MS QP 2010 (SHIMADZU Co., Ltd.; Kyoto, Japan) in the select ion monitoring (SIM) mode. The (GC) conditions were as follows: RTS-5MS column (30 m long, 0.25 mm ID, 0.25 µm film thickness); helium carrier gas at a flow rate of 1.5 mL min⁻¹; 230 °C interface temperature, 350 °C ion source temperature. Mass acquisition parameters were as follows: ion source 180 °C, transfer line temperature 70 °C. The temperature programs of the GC were as follows: 40 °C (3 min hold), 6 °C min⁻¹ to 220 °C (5 min hold). Structures were confirmed by NISTAT library.

2.3. In Vitro Studies

Ten samples of soil and root were randomly selected from the tomato rhizosphere infested by M. incognita in different locations of a nematode-infested tomato greenhouse in Shunyi, Beijing, China. In order to sample the soil, firstly, the top layer of the soil was removed to a depth of about 3 to 5 cm and then 250 cm³ of soil and 10 g of fed roots were collected from a depth of 30 cm of the greenhouse soil [20]. A single egg mass was used to establish a population of RKNs on seedlings (3- or 4-true-leaf stage) of tomato (Solanum lycopersicum L. cv Aojinfutian) (Vegetable Seed Technology Co., Ltd., Beijing, China) in plastic pots. To collect the eggs, the galled roots of tomato plants were washed with tap water after 60 days of growth, cut into 2–3 cm pieces and shaken for 2 min in 1.5% NaOCl solution [21,22]. To collect the eggs, the nematode suspension was poured on a 25 µm mesh sieve and washed with tap water to eliminate the NaOCl residues. To hatch the J2s of nematode, the egg suspension was aerated for 7 to 10 days in the dark, and the Baermann funnel method was used to separate freshly hatched J2s from unhatched eggs [23]. The species were identified by studying M. incognita characteristics, morphometric attributes of the juveniles, and the perineal pattern of the females [13,24].

Another greenhouse soil set from Shunyi (Beijing, China) free of nematodes was used to study the bio-fumigant plant. The sampling was performed at 20 cm from the top of the greenhouse soil. First, the soil was wetted, then it was sterilized in an autoclave at 85 °C for 30 min. Physicochemical analysis showed that the soil comprised 12.3% sand, 64.4% silt, and 23.3% clay, with organic matter content of 33.5 g kg⁻¹ soil, pH 6.5, and moisture 17.8% (w/w) [13,25]. In the soil pH measurement method, 10 g of soil was poured into a flask and 10 mL of distilled water was added to it. The mixture was stirred and then stood still for 10 min. Filter paper was used to separate soil from water. A pH meter (Shanghai Inesa Scientific Instrument Co., Ltd., Shanghai, China) was placed in the filtrate to measure pH [26].

Gravimetric method was used to measure soil moisture. For Gravimetric method, first, different soil samples were collected from any depth of the greenhouse. The collected soil samples were weighed and then heated in an oven (electric constant-temperature blast-drying oven (DHG-9240A) produced by Beijing Luxi Technology Co., Ltd., Beijing, China) at a temperature of 105 ± 5 °C for 24 h. After this stage, there was no water in the soil samples [27].

To study M. incognita J2 mortality, sterilized greenhouse soil was sieved through a 2 mm mesh and mixed. For each treatment, 100 g of sterilized greenhouse soil was selected and concentrations of 0, 20, 40, 60, 80, and 100 mg of the dried powdered root-stems and leaves of tomato (Solanum lycopersicum L. cv Zhongza 09) were added to it. Each of the treatments was infested with 200 M. incognita J2s (2 juveniles/g soil) [28] and then transferred to 250 g capacity plastic test tubes. The control consisted of sterilized and wet greenhouse soil infested with nematodes, without tomato plants. The tubes were incubated at 25 and 35 °C for different times (e.g., 1, 2, 3, 4, and 8 weeks). The tubes were closed and incubated. They were incubated in the dark. Treatments and controls were studied in three replicates. The Hussey and Barker [22] method was used to extract the J2 stages of nematodes from the incubated soil treatments. A binocular microscope was used to examine the mortality of M. incognita J2s [13].

2.4. Chemical Compound Studies

Four chemical compounds, (E)-2-Decenal, 95% (Aladdin Biochemical Technology Co., Ltd., Shanghai, China), nonanal 96% purity, linalool 98% purity (Macklin Biochemical Co., Ltd., Shanghai, China), and methylene chloride 99.5% purity (Titan Scientific Co., Ltd., Shanghai, China), were used in this study.

First, to obtain a stock solution of 1000 µg/mL, each of the chemical compounds was weighed to 0.01 g and then dissolved in 10 mL of acetone. For the serial dilution, concentrations ranging from 800 to 50 µg/mL were created from the stock solution. In this process, 0.5% Tween 80 served as an emulsifier to adjust the final volume to 10 mL. The formula used for the serial dilution was as follows [29]:

Dilution factor (DF) = Final volume of the solution to be measured (V_f)/Original test portion (V_o) = V_f/V_o. And to dilute the volumes, this formula was used [29]:

C₁ · V₁ = C₂ · V₂

C_initial · V_initial = C_final · V_final

Second, 2 mL of nematode suspension, which contained distilled water with 200 J2s of M. incognita [28] inside, was poured into glass vials. Equal volumes of test solutions (volumes of 10 mL diluted 800, 400, 200, 100, and 50 µg/mL concentrations) were added to glass vials containing 2 mL of nematode suspension separately. Due to which, concentrations of (400, 200, 100, 50, and 25 µg/mL) were obtained. For each treatment, precisely 100 g of greenhouse soil in Shunyi, Beijing (12.3% sand, 64.4% silt, and 23.3% clay, organic matter content of 33.5 g kg⁻¹ soil, pH 6.5, and moisture 17.8% (w/w)) was transferred to plastic tubes, to which the glass vial’s content was added separately. Each treatment and control group was triplicated and incubated at 25 and 35 °C and at different times (e.g., 1, 2, 3, 4, and 8 weeks). The control was comprised of 100 g of greenhouse soil with 2 mL of nematode suspension containing 200 J2s of M. incognita without a chemical compound [30]. To calculate the mortality percentage of M. incognita J2s, the following formula was used [31].

2.5. Parameter Measurement

The nematode mortality in the in vitro experiments was calculated using the formula [31]:

Mortality (%) = number of dead nematodes/total number of nematodes × 100

A binocular microscope was used to assess the mortality of nematodes. A dissecting needle was used to distinguish dead from live nematodes [25]. When nematodes were touched with a dissecting needle, immobile nematodes were scored dead and moving nematodes were scored alive.

2.6. Data Analysis

All the assays were carried out in a completely randomized factorial design. Each treatment comprised three replicates. Analysis variance (ANOVA) and normality test of data use were performed by software SPSS 22. Principal component analysis (PCA) was performed by software R 4.3.2.1. In order to determine the regression trend of the mortality response of Meloidogyne incognita in nonlinear regression models, two kinds of software, sigma plot 12 and R 4.3.2.1. (packages: drc, tidyverse, ggplot2, and caret) were used. Models include:

$$\mathrm{Gompertz}: \mathrm{Y}={{\mathrm{M}\mathrm{R}}_{\mathrm{m}\mathrm{i}\mathrm{n}}+(\mathrm{M}\mathrm{R}}_{\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{M}\mathrm{R}}_{\mathrm{m}\mathrm{i}\mathrm{n}})\times \mathrm{e}\mathrm{x}\mathrm{p}(-\exp \left(\frac{-\left(\mathrm{X}-\mathrm{E}\mathrm{C}50\right)}{\mathrm{s}\mathrm{l}\mathrm{o}\mathrm{p}\mathrm{e}}\right)$$

Logistic: Y = MR_max/(1+ (−(X/EC₅₀)^slope))

Weibull:

$$\mathrm{Y}={\mathrm{M}\mathrm{R}}_{\mathrm{m}\mathrm{i}\mathrm{n}}\dots \dots \dots \dots \dots \dots \dots \dots \dots \dots \dots \dots \dots \dots \dots \dots \dots ....\mathrm{f}\mathrm{o}\mathrm{r} \mathrm{X}<={\mathrm{EC}}_{\max }-\mathrm{s}\mathrm{l}\mathrm{o}\mathrm{p}\mathrm{e}\times {(\mathrm{c}-1)/\mathrm{c})}^{\left(\frac{1}{\mathrm{c}}\right)}$$

$$\begin{gathered} \mathrm{Y}={{{\mathrm{M}\mathrm{R}}_{\mathrm{m}\mathrm{i}\mathrm{n}}+(\mathrm{M}\mathrm{R}}_{\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{M}\mathrm{R}}_{\mathrm{m}\mathrm{i}\mathrm{n}})\times \left(\frac{\mathrm{c}-1}{\mathrm{c}}\right)}^{\left(\frac{1-\mathrm{c}}{\mathrm{c}}\right)}\times {{\left(\mathrm{a}\mathrm{b}\mathrm{s}\right((\mathrm{x}-{\mathrm{E}\mathrm{C}}_{\mathrm{m}\mathrm{a}\mathrm{x}})/\mathrm{s}\mathrm{l}\mathrm{o}\mathrm{p}\mathrm{e}+\left(\right(\mathrm{c}-1)/\mathrm{c})}^{\left(\frac{1}{\mathrm{c}}\right)})}^{(\mathrm{c}-1)}\times \exp {{(-\mathrm{a}\mathrm{b}\mathrm{s}((\mathrm{x}- \\ {\mathrm{E}\mathrm{C}}_{\mathrm{m}\mathrm{a}\mathrm{x}})/\mathrm{s}\mathrm{l}\mathrm{o}\mathrm{p}\mathrm{e}+\left(\right(\mathrm{c}-1)/\mathrm{c})}^{\left(\frac{1}{\mathrm{c}}\right)})}^{\frac{\mathrm{c}(\mathrm{c}+1)}{\mathrm{c}}}\dots \dots .\mathrm{F}\mathrm{o}\mathrm{r} \mathrm{x}>{\mathrm{E}\mathrm{C}}_{\mathrm{m}\mathrm{a}\mathrm{x}} \end{gathered}$$

where MR_max is maximum mortality, MR_min is minimum mortality, EC₅₀ is the half-maximal effective concentration, EC_max is the maximal effective concentration, and c is the model coefficient. The authors used two types Gompertz model with 3 and 4 parameters. In 3 parameters, we typed MR_min as zero.

R², root mean square error (RMSE), and the Akaike information criterion (AICc) were applied to determine the best estimates of the parameters. R² was calculated using the following formula:

R² = RSS/TSS

where RSS denotes the sum of squares (SS) for regression (∑n i = 1 L − Ḹ) and SST the total SS (∑n i = 1 Li − Ḹ). Li is the observed value and Ḹ is the corresponding estimated value. In addition, RMSE and AICc were calculated using following the formulae:

$$\begin{array}{l}\mathrm{RMSE}=\surd (1/n)\sum ({\mathrm{Y}}_{\mathrm{obs}}-{\mathrm{Y}}_{\mathrm{pred}}{)}^2\\ \mathrm{AICc}=\mathrm{n}\ln \left(\frac{\mathrm{RSS}}{\mathrm{n}}\right)+2\mathrm{k}+\left(\frac{2\mathrm{k}(\mathrm{k}+1)}{\mathrm{n}-\mathrm{k}-1}\right)\end{array}$$

where Y_obs denotes the observed value, Y_pred the predicted value, and n is the number of samples [32].

3. Results

3.1. Chemical Compounds

The evaluation of the effects of four volatile compounds (linalool, nonanal, methylene chloride, and 2-Decenal) on the mortality response of M. incognita J2s showed that temperature, time, concentration, and the interactions of temperature × concentrations, time × temperature, and time × concentrations were significant, but time × temperature × concentration interaction was significant only in methylene chloride and 2-Decenal (

Table 1. In vitro analysis of variance of mortality response of Meloidogyne incognita J2s exposed to soil containing chemical compounds.

Source of Variation	DF	Means Square
		Linalool	Nonanal	Methylene Chloride	2-Decenal
Time	4	375.10 **	220.13 **	190.19 **	2449.24 **
Temperature	1	60.87 **	28.12 **	86.08 **	51.18 **
Concentration	5	137.89 **	426.18 **	1665.10 **	1340.18 **
Time × temperature	4	27.96 **	27.73 **	37.57 **	87.70 **
Time × concentration	20	20.39 **	14.84 **	41.42 **	515.5 **
Temp × concentration	5	7.25 **	5.84 **	14.35 **	6.00 **
Time × temperature × concentration	20	1.52 ns	4.38 ns	7.39 *	9.64 **
Error	120	2.44	4.41	4.24	3.45
Coefficient of Variation (%)	-	12.4	12.7	8.8	8.4

ns, *, and ** are non-significant and significant at 5% and 1%, respectively.

).

In order to analyze the changes in mortality response in different concentrations of main compounds, being influenced by the interaction of time or temperature, the nonlinear regression models were fitted. The results were indicated in

Table 2. Estimate parameters models of regression relationship between in vitro percentage mortality of M. incognita J2s with some main compounds at different times (e.g., 1, 2, 3, 4, and 8 weeks).

Chemical Compounds	Time (Weeks)	Model	Parameters Model						R2	RMSE	AICc
			MRmax (%)	slope	c	EC50 (µg/mL)	ECmax (µg/mL)	MRmin (%)
Linalool	1	W	20.6 ± 3.8	103.6 ± 8.3	1.02 ± 1.3	-	16.4 ± 1.9	12.8 ± 1.4	0.951	1.59	−6.8
	2	W	16.9 ± 1.2	109.1 ± 6.2	1.04 ± 0.3	-	14.0 ± 3.4	11.8 ± 0.2	0.999	0.39	−29.7
	3	W	16.0 ± 0.7	111.0 ± 6.8	1.33 ± 0.2	-	14.3 ± 2.0	9.6 ± 0.4	0.995	0.28	−14.1
	4	W	15.3 ± 1.5	66.3 ± 9.4	1.21 ± 0.2	-	7.7 ± 2.3	8.2 ± 0.3	0.998	0.28	−14.2
	8	W	15.1 ± 1.3	94.6 ± 11.9	1.01 ± 0.1	-	6.1 ± 1.4	5.4 ± 0.3	0.999	0.23	−16.3
Nonanal	1	W	23.0 ± 0.9	156.1 ± 37.3	1.07 ± 0.2	-	27.4 ± 7.8	13.8 ± 0.6	0.995	0.60	−5.0
	2	W	22.0 ± 0.7	170.0 ± 12.2	1.06 ± 0.1	-	24.5 ± 6.3	12.2 ± 0.2	0.999	0.21	−17.5
	3	W	21.9 ± 1.1	76.3 ± 22.5	1.05 ± 0.5	-	25.8 ± 8.6	11.2 ± 0.5	0.993	0.64	−4.1
	4	W	20.1 ± 3.4	85.2 ± 39.3	1.01 ± 0.5	-	18.9 ± 1.4	10.9 ± 1.3	0.978	1.14	2.8
	8	W	20.8 ± 2.3	75.2 ± 16.6	1.03 ± 0.2	-	15.6 ± 6.0	8.4 ± 0.9	0.993	0.92	0.2
Methylene chloride	1	G	28.5 ± 0.9	21.8 ± 5.6	-	10.2 ± 4.3	-		0.961	1.51	48.8
	2	G	25.2 ± 0.8	61.9 ± 6.4	-	11.9 ± 8.5	-		0.994	0.44	34.0
	3	G	31.0 ± 1.4	54.3 ± 9.6	-	23.1 ± 2.4	-		0.972	1.66	49.9
	4	G	36.4 ± 0.5	51.3 ± 3.3	-	28.1 ± 6.0	-		0.998	0.57	37.2
	8	G	33.2 ± 1.0	58.1 ± 8.3	-	33.9 ± 6.9	-		0.989	1.15	30.0
2-Decenal	1	G	20.6 ± 1.7	99.1 ± 7.2	-	36.8 ± 6.5	-		0.944	2.48	46.3
	2	G	22.8 ± 1.1	70.2 ± 30.2	-	35.4 ± 3.7	-		0.909	1.37	47.6
	3	G	23.4 ± 1.1	78.2 ± 30.2	-	31.0 ± 3.7	-		0.988	0.60	35.4
	4	G	35.1 ± 1.6	68.4 ± 9.0	-	15.6 ± 1.2	-		0.982	0.62	38.1
	8	G	62.3 ± 4.1	64.5 ± 12.8	-	95.7 ± 5.4	-		0.979	3.82	42.1

MR_max: upper mortality response, MR_min: lower mortality response, c: model coefficient, EC₅₀: half-maximal effective concentration, EC_max: maximal effective concentration, R²: coefficient of determination, RMSE: root mean square error, AIC: Akaike information criterion, W: Weibull, G: Gompertz with 3 parameters.

and

Table 3. Estimate parameters models of regression relationship between in vitro percentage mortality of M. incognita J2s with main compounds at different temperatures.

Chemical Compounds	Temperature (°C)	Model	Parameters Model						R2	RMSE	AICc
			MRmax (%)	slope	c	EC50 (µg/mL)	ECmax (µg/mL)	MRmin (%)
Linalool	25	W	15.2 ± 0.2	141.1 ± 8.1	1.18 ± 0.1	-	15.6 ± 2.8	9.7 ± 0.2	0.999	0.06	−33.0
	35	W	14.0 ± 1.4	119.5 ± 7.0	1.16 ± 0.2	-	10.1 ± 2.0	8.2 ± 0.4	0.998	0.22	−17.1
Nonanal	25	W	19.9 ± 2.5	76.5 ± 9.4	1.03 ± 0.9	-	20.4 ± 9.7	12.9 ± 0.5	0.991	0.65	−4.0
	35	W	21.3 ± 2.5	113.6 ± 12.6	1.02 ± 0.1	-	15.6 ± 7.6	13.1 ± 1.0	0.991	0.73	−2.6
Methylene chloride	25	G	30.5 ± 9.6	59.8 ± 7.3	-	18.1 ± 2.3	-	-	0.990	0.44	42.2
	35	G	33.5 ± 7.0	58.9 ± 6.1	-	21.9 ± 4.0	-	-	0.994	0.78	40.8
2-Decenal	25	G	30.9 ± 1.5	95.4 ± 10.6	-	12.3 ± 1.6	-	-	0.979	1.18	45.8
	35	G	32.4 ± 1.0	81.6 ± 11.3	-	18.7 ± 2.8	-	-	0.991	0.88	42.3

MR_max: upper mortality response, MR_min: lower mortality response, c: model coefficient, EC₅₀: half-maximal effective concentration, EC_max: maximal effective concentration, R²: coefficient of determination, RMSE: root mean square error, AIC: Akaike information criterion, W: Weibull, G: Gompertz 3 parameters.

and Figure 1 and Figure 2. The results indicated that the Gompertz model can be fitted as the best model to changes in mortality response influenced by time and concentrations of methylene chloride (R² = 0.961–0.998, RMSE = 0.57–1.66, and AICc = 30–48.8) and 2-Decenal (R² = 0.909–0.988, RMSE = 0.60–3.82, and AICc = 35.4–47.6). Furthermore, the Weibull models were good models to study the changes made by the linalool (R² = 0.951–0.999, RMSE = 0.23–1.59, and AICc = −6.8–16.3) and nonanal (R² = 0.978–0.999, RMSE = 0.21–1.14, and AICc = −17.5–2.8) compounds, respectively (Table 2 and Figure 1 and Figure 2).

The mortality percentage of M. incognita J2s increased in high concentrations of methylene chloride and 2-Decenal in all times. For example, a high mortality response (MR_max) was estimated at about 28.5% for methylene chloride and about 20.6% for 2-Decenal at week 1 after the study started. Half-maximal effective concentration (EC₅₀) was about 10.2 and 36.8 µL/mL for methylene chloride and 2-Decenal at this time, respectively (Figure 1 and Table 2). In addition, linalool and nonanal in lower concentrations resulted in an increase in mortality percentage, but in higher concentrations resulted in a decrease in mortality percentage at all times.

The MR_max and maximal effective concentration (EC_max) were estimated for these compounds at about 20.6% and 16.4–6.1 µg/mL for linalool and 23% and 27.4 µg/mL for nonanal at week 1 after the study started. The MR_max and EC_max decreased after the study started. For instance, at week 8, the MR_max was estimated at about 15.1% and 20.8% and the EC_max at about 6.1 and 15.6 µg/mL for linalool and nonanal, respectively (Figure 1 and Table 2).

The results of changes in mortality response were influenced by the temperatures and concentrations of the main compounds in the same times. The Gompertz was the best model for 2-Decenal (R² = 0.979–0.991, RMSE = 0.88–1.18, and AICc = −12.3–45.8) and methylene chloride (R² = 0.990–0.994, RMSE = 0.44–0.78, and AICc = −40.8–42.2). Also, the Weibull was a good model for the changes made by linalool (R² = 0.998–0.999, RMSE = 0.06–0.22, and AICc = −33.0–−17.1) and nonanal (R² = −0.991, RMSE = 0.65–0.73, and AICc = −4.0–2.6), respectively (Table 3 and Figure 2). The MR_max for 2-Decenal at temperatures of 25 °C and 35 °C were estimated at about 30.9% and 32.4%. For methylene chloride, it was about 30.5% and 33.5%. The EC₅₀ for these compounds were about 18.1 and 12.3 µg/mL at a temperature of 25 °C, and 21.9 and 18.7 µg/mL in temperatures of 35 °C (Figure 2 and Table 3).

The MR_max and the EC₅₀ for linalool were estimated at about 15.2% and 15.6 µg/mL in temperatures of 25 °C, and 14.0% and 10.1 µg/mL in temperatures of 35 °C. In nonanal, the MR_max was recorded at about 19.9% and 21.3% in temperatures of 25 °C and 35 °C, respectively. The EC_max was observed at about 20.4 µg/mL and 15.6 µg/mL at 25 °C and 35 °C, respectively. Considering this Weibull model, in higher concentrations of EC_max, the mortality percentage of M. incognita J2s was decreased remarkably (Figure 2 and Table 3).

The results of changes in mortality response influenced by interactions of time × temperature and concentrations of methylene chloride and 2-Decenal are shown in Figure 3 and

Table 4. Estimate parameters models of regression relationship between in vitro percentage mortality of M. incognita J2s with some main compounds at interaction different temperatures and times (e.g., 1, 2, 3, 4, and 8 weeks).

Chemical Compounds	Time (Weeks)	Temperature (°C)	Parameters Model				R2	RMSE	AICc
			MRmax (%)	Slope	EC50 (µg/mL)	MRmin (%)
Methylene chloride	1	25	25.3 ± 1.6	68.2 ± 35.0	28.0 ± 7.5	9.5 ± 8.4	0.984	0.90	−6.8
		35	27.0 ± 1.0	44.3 ± 11.1	26.2 ± 9.6	11.4 ± 3.5	0.998	0.36	−9.6
	2	25	29.7 ± 2.0	12.4 ± 6.8	36.1 ± 8.4	12.9 ± 2.2	0.960	2.23	−2.2
		35	32.4 ± 7.6	16.7 ± 6.3	35.6 ± 6.0	13.9 ± 1.6	0.980	1.63	−6.2
	3	25	30.9 ± 8.9	53.0 ± 23.3	56.6 ± 14.3	11.8 ± 3.8	0.981	1.62	−6.2
		35	35.6 ± 5.4	31.7 ± 12.9	70.6 ± 12.2	14.5 ± 1.7	0.979	2.08	−5.8
	4	25	33.3 ± 4.4	37.3 ± 8.6	75.4 ± 7.2	13.3 ± 1.0	0.994	1.09	−8.8
		35	36.0 ± 5.9	56.1 ± 20.8	58.7 ± 12.2	10.7 ± 4.8	0.987	1.70	−7.4
	8	25	34.9 ± 9.6	63.6 ± 29.1	62.5 ± 15.5	13.6 ± 5.0	0.981	1.79	−6.2
		35	43.1 ± 7.6	46.1 ± 4.0	54.6 ± 4.0	11.8 ± 1.0	0.998	0.55	−9.6
2-Decenal	1	25	19.6 ± 1.9	40.8 ± 5.4	81.9 ± 4.4	13.1 ± 0.2	0.998	0.18	−9.6
		35	21.4 ± 1.9	82.3 ± 18.9	93.2 ± 16.6	12.4 ± 0.7	0.995	0.32	−9.0
	2	25	21.1 ± 3.0	139.9 ± 16.2	65.0 ± 15.5	10.4 ± 4.3	0.995	0.36	−9.1
		35	22.7 ± 1.6	54.9 ± 19.8	74.5 ± 15.3	13.0 ± 1.3	0.969	0.89	−3.8
	3	25	22.6 ± 1.0	130.4 ± 15.8	48.3 ± 17.5	8.0 ± 5.7	0.989	0.85	−7.8
		35	24.8 ± 2.5	111.9 ± 12.3	53.5 ± 11.2	9.0 ± 6.1	0.991	0.64	−8.2
	4	25	31.6 ± 6.3	17.1 ± 7.7	35.5 ± 7.2	14.8 ± 1.9	0.971	1.84	−4.2
		35	41.6 ± 18.6	11.1 ± 6.5	37.0 ± 8.6	13.8 ± 3.5	0.967	3.49	−3.4
	8	25	62.4 ± 4.6	58.3 ± 3.2	83.0 ± 2.6	11.8 ± 0.8	0.999	0.60	−9.8
		35	70.5 ± 8.8	54.2 ± 1.4	110.5 ± 1.1	13.7 ± 0.2	0.999	0.33	−9.8

MR_max: upper mortality response, EC₅₀: half-maximal effective concentration, R²: coefficient of determination, RMSE: root mean square error, AIC: Akaike information criterion. Gompertz 4 parameters model use for both compounds.

. The Gompertz model was well fitted to the changes in both compounds (R² = −0.960–0.999, RMSE = 0.32–3.49, and AICc = −2.2–9.8).

The MR_max for methylene chloride and 2-Decenal were 25.3% and 19.6% at week 1 and at 25 °C, but reached 43.1% and 70.5% at week 8 and 35 °C. The EC₅₀ were estimated at about 28.0 and 81.9 µg/mL for methylene chloride and 2-Decenal at week 1 and 25 °C, respectively (Table 4). Over time and at higher temperatures, the EC₅₀ increased_. For example, the EC₅₀ for methylene chloride and 2-Decenal were 54.6 and 110.5 µg/mL at week 8 and 35 °C (Figure 3 and Table 4).

3.2. In Vitro Mortality of Second-Stage Juveniles

Results of the variance effect of soil containing two dried parts of S. lycopersicum on the mortality response of M. incognita J2s showed that temperature, time, concentration, and the interaction of temperature × concentrations in both parts of plants (leaves and root-stems) were significant. However, the temperature × time, time × concentration, and time × temperature × concentration interactions were significant in both parts (

Table 5. In vitro analysis of variance of mortality response of Meloidogyne incognita J2s exposed to soil containing dried root-stems and leaves of S. lycopersicum.

Source of Variation	DF	Means Square
		Leaves	Root-Stems
Time	4	9293.31 **	215.3 **
Temperature	1	10,298.5 **	249.3 **
Concentration	5	22,683.2 **	176.7 **
Time × temperature	4	1034.9 **	12.63 **
Time × concentration	20	687.3 **	17.73 **
Temp × concentration	5	409.4 **	16.51 **
Time × temperature × concentration	20	95.042 **	9.18 *
Error	120	38.15	3.561
Coefficient of Variation (%)	-	10.4	25.6

*, and ** are significant at 5% and 1%, respectively.

).

Based on the estimated parameters, the Gompertz model can well fit the changes in mortality response influenced by the interaction of time × temperature × concertation of soil containing dried leaves (R² = −0.940–0.999, RMSE = 1.50–5.14, and AICc = 16.3–68.5) of S. lycopersicum. Also, the Logistic models were good models for changes in theroot-stems (R² = −0.976–0.994, RMSE = 0.12–0.65, and AICc = 18.6–38.7) of S. lycopersicum (

Table 6. Estimate parameters models of regression relationship between percentage mortality of M. incognita J2s with leaves and root-stems of S. lycopersicum L. at interaction of different temperatures and times (e.g., 1, 2, 3, 4, and 8 weeks).

Parts	Time (Weeks)	Temperature (°C)	Parameters Model			R2	RMSE	AICc
			MRmax (%)	Slope	EC50 (µg/mg)
Leaves	1	25	47.6 ± 6.2	10.5 ± 3.7	71.6 ± 4.6	0.987	2.92	16.3
		35	91.9 ± 3.7	32.7 ± 2.4	28.0 ± 1.5	0.999	1.50	48.7
	2	25	73.1 ± 7.1	24.9 ± 7.1	25.7 ± 4.5	0.975	5.14	63.5
		35	95.4 ± 2.1	25.3 ± 3.9	21.9 ± 2.5	0.992	3.84	60.0
	3	25	83.8 ± 3.4	26.5 ± 8.4	22.3 ± 5.2	0.968	6.70	66.7
		35	97.5 ± 5.1	28.8 ± 4.3	21.5 ± 2.7	0.990	4.44	61.7
	4	25	86.1 ± 9.5	12.1 ± 2.7	7.1 ± 2.3	0.975	5.82	65.0
		35	99.9 ± 3.3	8.8 ± 2.3	5.2 ± 2.1	0.970	7.00	67.2
	8	25	89.5 ± 4.1	7.8 ± 2.5	5.2 ± 2.4	0.963	7.78	68.5
		35	100.2 ± 5.7	6.5 ± 1.3	4.0 ± 1.1	0.991	4.04	60.6
Root -stems	1	25	10.8 ± 0.2	0.9 ± 0.1	267.8 ± 8.3	0.994	0.12	18.6
		35	10.3 ± 0.2	1.1 ± 0.2	231.2 ± 24.9	0.988	0.27	25.7
	2	25	11.7 ± 0.5	1.2 ± 0.2	214.2 ± 17.3	0.976	0.22	2.8
		35	10.3 ± 0.2	1.1 ± 0.2	211.2 ± 14.9	0.976	0.22	25.7
	3	25	11.5 ± 0.3	0.6 ± 0.2	103.2 ± 5.3	0.987	0.31	29.6
		35	11.9 ± 0.4	0.7 ± 0.1	31.7 ± 4.8	0.991	0.38	32.1
	4	25	11.6 ± 0.3	0.6 ± 0.1	55.0 ± 6.4	0.992	0.29	29.1
		35	12.1 ± 0.7	0.9 ± 0.2	17.4 ± 4.8	0.983	0.65	38.7
	8	25	10.5 ± 0.1	0.8 ± 0.2	27.5 ± 5.3	0.984	0.54	36.4
		35	13.5 ± 0.3	0.7 ± 0.1	3.0 ± 1.7	0.997	0.32	30.1

MR_max: upper mortality response, EC₅₀: half-maximal effective concentration, R²: coefficient of determination, RMSE: root mean square error, AIC: Akaike information criterion. Gompertz 3-parameters model used for leaves, Logistic model used for root-stems.

and Figure 4).

The result of the nonlinear regression model fitted to the change in mortality response in the concentration of soil containing bio-fumigant plants influenced by temperature and time is indicated in Table 6 and Figure 4.

Based on the Logistic model, a concentration increase in the root-stems of S. lycopersicum decreased the mortality percentage in all times and both temperatures. The MR_max and EC₅₀ were estimated at about 10.8% and 267.8 µg/mg in week 1 and 25 °C, and 10.3% and 231.2 µg/mg in 35 °C, respectively. In addition, during the times of week 1 to week 8, the changes in MR_max were not noticeable. However, the EC₅₀ decreased remarkably. For instance, the EC₅₀ in week 8, at temperatures of 25 and 35 °C, was recorded at 27.5 µg/mg and 3.0 µg/mg, respectively (Figure 4 and Table 6).

Based on the Gompertz model, a concentration increase in the dried leaves of S. lycopersicum increased the mortality percentage of M. incognita J2 at all times and temperatures. For example, the MR_max for the leaves of S. lycopersicum at a temperature of 35 °C and at week 8 was estimated at about 100%. The EC₅₀ for this part of the plant was about 4.0 µg/mg in this condition (Figure 4 and Table 6).

3.3. Chemical Compounds Extracted

Results of (GC-MS) analysis of root-stems and leaves of S. lycopersicum are shown in the Supplementary Materials (Tables S1 and S2).

Results of GC-MS showed that 15 volatile compounds were identified in the dried leaves of S. lycopersicum. Methylene chloride (0.1–0.4 µg/mg), α-Pinene (1.1–2.1 µg/mg), d-Limonene (0.3–1.6 µg/mg), and butanol (7.4–3.4 µg/mg) were the main compounds extracted from dried leaves, influencing the mortality percentage of nematodes. Results of root-stems also showed that 18 volatile compounds were identified in the dried root-stems of S. lycopersicum. Linalool and methylene chloride were the main compounds. Linalool, methylene chloride, alanine ethylamide, carbon dioxide, butanol, and acetic acid were the main compounds extracted from the dried root-stems of S. lycopersicum.

3.4. Principal Component Analysis (PCA)

The (PCA) of volatile compounds extracted from leaves indicated that two principal components, PCA1 and PCA2, accounted for 41.1% and 25.1% of the variance, cumulatively explaining 67.2% of the total variation (Figure 5). The mortality responses of M. incognita J2s to methylene chloride, α-pinene, d-limonene, and cyclotetrasiloxane were notably similar, as evidenced by their grouping in the second quadrant of the PCA coordinate diagram. This pattern suggests that these specific volatile compounds in the plant contribute significantly to nematode mortality.

The PCA results, accounting for 68.5% of the variance in compounds extracted from dried root-stems, are illustrated in Figure 6. These findings indicate that using dried root-stems correlated with an increase in nematode survival. Specifically, the PCA of volatile compounds from root-stems revealed that the mortality responses of M. incognita J2s to alanine ethylamide and hexanol were notably similar, grouping them together in Quadrant III of the PCA coordinate diagrams. Conversely, linalool and butanol, also key compounds in root-stems, were associated with a decrease in nematode mortality, as reflected by their placement in Quadrant IV of the diagrams.

4. Discussion

Naturally extracted main compounds in plants play a crucial role in controlling plant parasitic nematodes [33]. In our study, we have focused on the main compounds of bio-fumigant plants and their nematicidal effects. In our previous research, it was assumed that four main compounds, methylene chloride, 2-Decenal, linalool, and nonanal, extracted from dried leaves of E. adenophorum, would increase the nematode population [13]. Previous study assumptions made us conduct research on methylene chloride, 2-Decenal, linalool, and nonanal in the present research. The results of the laboratory study showed that methylene chloride and 2-Decenal in the highest concentration and in week 8 of the study had the highest mortality percentage of M. incognita J2s; (EC₅₀) were about 34 and 96 µg/mL for methylene chloride and 2-Decenal, respectively. In another study, the nematicidal effects of methylene chloride-methanol extracted from Annona senegalensis and Nauclea latifolia were examined on the nematode Heligmosomoides bakeri [34]. Methylene chloride-methanol extracted from A. senegalensis, N. latifolia, and the mixture of the two plants at the highest concentration (5000 μg/mL) after 24 h, had a nematicidal effect on the L1 and L2 larval stages in the amount of 100%, 54.76%, and 96.77% against 98%, 51.44%, and 100% [34]. The nematicidal effect of (E)-2-decenal on M. incognita was also estimated. The results clarified that (E)-2-decenal did not cause any damage to the cuticle and somatic muscles of nematodes but degenerated the pseudocoel cells. (E)-2-Decenal caused somatic muscle abnormalities [35]. According to the PCA analysis, α-pinene, d-limonene, and methylene chloride were extracted from the leaves of S. lycopersicum (Figure 5). Wang et al. [36] reported α-pinene as a nematicidal chemical compound. They indicated that the pinewood nematode, Bursaphelenchus xylophilus was treated by α-pinene, and the results showed that the mortality percentage of nematodes increased slightly by the increase in α-pinene concentration. Further research documented that the nematicidal essential oil of Aloysia gratissima contains cadinol, caryophyllene oxide, limonene oxide, chrysanthenyl acetate, and β-caryophyllene [37]. In the present laboratory study with linalool and nonanal, the results proved that, in the highest concentrations, the mortality percentage of M. incognita J2 decreased; the EC_max of these compounds in week 8 was estimated at about 15.6 µg/mL for nonanal and 6.1 µg/mL for linalool. According to the PCA analysis, linalool and butanol were extracted from root-stems of S. lycopersicum. (Figure 6). The mixture of 3-methyl-1-butanol, (±)-2-methyl-1-butanol, 4-heptanone, and isoamyl acetate decreased the viability rate of J2s of M. javanica by 99% [38]. In a previous study, it was observed that J2s of potato cyst nematodes were attracted to linalool extracted from Globodera rostochiensis and G. pallida. As a result, linalool was not toxic to them [39]. Some chemical compounds extracted from essential oils increased the life span and stress tolerance of nematodes. Linalool increased heat stress tolerance and decreased fat accumulation in nematode Caenorhabditis elegans [40]. Moreover, female beetles of Callosobruchus maculatus were attracted to a mixture of nonanal, 3 carene, 1-pentanol, 1-octen-3-ol, and (E)-2-octenal [41].

To investigate the main compounds of tomato, we needed to study the nematicidal effects of dried root-stems and leaves of S. lycopersicum on M. incognita in the laboratory. The results proved that in the dried leaves treatment of S. lycopersicum at two temperatures, 25 and 35 °C, and at all times (e.g., 1, 2, 3, 4, and 8 weeks), as the concentration of leaves increased, the percentage mortality of M. incognita J2s increased. For example, the MR_max in week 8 and at temperatures of 25 and 35 °C was estimated at about 89.5% and 100%, respectively, and the EC₅₀ was about 5 and 4.0 µg/mg in this condition. Sari et al. [42] studied the effectiveness of bio-fumigant plants of Brassicaceae, Leguminoceae, and Solanaceae against Meloidogyne spp. The results proved that the combination of Brassicaceae and Solanaceae was effective in reducing the number of galls in potato plants, while the Solanaceae treatment alone improved the plant growth. Accordingly, in dried root-stems treatment of S. lycopersicum, increasing the concentration of root-stems decreased the mortality percentage of M. incognita J2s at 25 and 35 °C and at all times (e.g., 1, 2, 3, 4, and 8 weeks). For example, the MR_max in week 8 at temperatures of 25 and 35 °C was estimated at 10.5% and 13.5%, respectively. The EC₅₀ was about 27.5 and 3.0 µg/mg in this condition (Table 6). In our research, the root-stems of S. lycopersicum L. had very little nematicidal effects on the M. incognita control. Many studies clarified that the potential damage of RKNs to various tomato cultivars can reduce the yield between 25% and 100% [2].

In a recent study, the percentage of mortality of M. incognita J2s was decreased in the root-stems treatment of S. lycopersicum. One of the main compounds identified in the root-stems of S. lycopersicum was linalool. Previous studies indicated that linalool has attraction features. According to these findings, it can be assumed that tomato root-stems, due to having linalool, have the potentiality to attract M. incognita J2s. The different distances of M. incognita J2 migration inside tomato root systems planted in clay and sand were studied. In cylinders containing sand, more larvae were observed than cylinders containing clay soil. The mortality of J2s and their migration distance from the root systems were observed to be less in sand than in clay. Fewer J2s migrated through the sand to infested tomato roots. There was an interaction between reproduction, the number of egg masses, galls produced by M. incognita J2s, and soil texture. However, in cylinders containing sand, a further decrease in the reproduction of J2s was observed [43]. Plant roots stimulate the behavioral response of attracting parasitic nematodes near the root by emitting main chemical signals [44]. Chemical compounds may have an inhibitory effect on one organism while having an attraction effect on another organism. These compounds change nematodes’ behaviors in different ways; for example they attract, cause repellence, inhibit their movement, or even kill nematodes [16]. Eleven trap plants were studied in lettuce cultivation under greenhouse conditions to control RKNs. After six weeks, the RKNs recovered from the root systems of both trap plants and main crops were counted. A significant decrease in the population of nematodes and in the average gall numbers per gram of fresh roots in the cultivation of lettuce with planted traps like canola, B.G. pumpkin, mustard, and vetch cv. 976 was observed. These planted traps attracted more RKN nematodes and prevented them from contaminating the main product [18].

Based on these trap plants studies, it can be assumed that S. lycopersicum can be used as a trap plant in greenhouses. However, to prove this hypothesis, further laboratory and greenhouse studies are needed.

5. Conclusions

While RKNs significantly impact tomato yields, this study has uncovered a promising solution. We found that the dried leaves of Solanum lycopersicum, used as a bio-fumigant, effectively control the J2s of Meloidogyne incognita. Notably, two compounds identified in this research—methylene chloride and 2-Decenal—demonstrated substantial nematicidal properties. These compounds emerge as ideal candidates for developing non-chemical nematicides. Utilizing eco-friendly nematicides aligns seamlessly with IPM programs, offering a sustainable approach to mitigating the damage caused by RKNs in tomato cultivation.