Physiological and biochemical markers associated with root lignification and micronutrient uptake in wheat genotypes with contrasting resistance to Gaeumannomyces tritici

Abstract

Take-all disease, caused by Gaeumannomyces tritici, is one of the most destructive root diseases of wheat (Triticum aestivum) worldwide. This study aimed to clarify the physiological and biochemical mechanisms underlying take-all resistance through analysis of root lignification, manganese and iron concentration in roots and seeds, and defense enzyme activities. In the first step, 17 bread wheat genotypes were evaluated under controlled greenhouse conditions in both control and infected treatments. Resistant genotypes showed higher mean root lignin content, root manganese and iron concentration, and root dry weight, which were significantly correlated with lower disease severity under greenhouse conditions. Seed Mn levels were positively correlated with root lignin (r = 0.579, p = 0.015) and negatively correlated with disease severity (r = –0.601, p = 0.011), suggesting that inherent seed nutrient reserves influence early defense activation. In the second step, five representative genotypes (two resistant and three susceptible) were analyzed for defense-related enzymes. G. tritici infection significantly induced phenylalanine ammonia lyase and peroxidase activities and total protein content in resistant genotypes, suggesting that enzymatic activity contributes to enhanced lignin biosynthesis. Stepwise regression identified root manganese concentration and total protein as the strongest predictors of lignin content, highlighting their potential role in structural defense. These findings suggest a possible dual role for manganese and iron in cell wall lignification and defense-related metabolism. The integration of seed and root micronutrient levels, lignin deposition, and enzyme activity provides a comprehensive framework for understanding take-all resistance and offers practical biochemical markers for breeding resistant wheat cultivars.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-39324-7.

Introduction

Plant mineral nutrients play a critical role in plant defense influencing cell wall compositions, metabolic activity, ad immune related pathways. Among these nutrients, micronutrients such as manganese (Mn) and iron (Fe) are particularly important due to their involvement in phenolic metabolism, lignin biosynthesis, and redox regulation. Mineral nutrients affect plant vigor by modulating the activity of defense enzymes and influencing root exudates. These nutrients also alter rhizosphere conditions, including soil nutrient content, pH fluctuations, lignin deposition, and phytoalexin biosynthesis¹. Lignin is major structural polymer of the plant secondary cell wall, contributing to mechanical strength and acting as a physical and biochemical barrier against pathogen infection. Secondary cell walls consist of a complex network of cellulose microfibrils, glucans, and heteroxylans that are linked to interwoven lignin polymers through arabinose and ferulic acid^2,3.

Mn is an essential micronutrient that can facilitate phenolic and lignin compound synthesis and may influence plant resistance to pathogens^1,4. Fe is an essential nutrient for plant growth and development. The availability of iron influences disease resistance in plants⁵.

Following pathogen infection and incompatible interaction with resistance genotypes, the defense mechanism of the plant is activated, creating a barrier to pathogen invasion. The reinforcement of the cell wall can be rapidly activated in response to pathogen penetration and may involve callose, silicon, and lignin deposition between the cell wall and membrane^6–10. The cell wall is a structure that regulates inducible defense mechanisms and is a source of signaling molecules that trigger immune responses¹¹. Enzymes are an important group of intracellular proteins that are affected by disease stress¹². Peroxidases (POD) are involved in various primary and secondary metabolic functions, including higher plant respiration through the oxidation of metabolites mediated by hydrogen peroxide as an electron acceptor, regulation of cell elongation, lignification, phenol oxidation, and deposition of phenolic substances on cell walls during resistance reactions^13–16. The enzyme phenylalanine ammonia lyase (PAL) is indirectly involved in the formation of phenolic compounds, which play a fundamental role as sensitive indicators of environmental changes and biochemical markers of plant defense against environmental stresses^17,18.

The disease known as take-all, caused by the necrotrophic fungus Gaeumannomyces tritici, is one of the most destructive root diseases of wheat worldwide. Breeding resistant cultivars is an effective way to protect wheat from take-all^19,20. Resistance to take-all disease is associated with mineral nutrients such as Mn, Fe, and copper; that Mn is directly related to lignin synthesis in roots²¹. Research has reported lignin biosynthesis in wheat roots by Mn efficiency and resistance to take-all disease. The results showed that Mn causes the accumulation of lignin in the roots of the resistant variety²¹. In another study, two genotypes (resistant and susceptible) of maize were compared at the root level based on their reaction to the fungal pathogen Fusarium verticillioides (Sacc.) Nirenberg. The results showed that phenylpropanoid biosynthesis, biosynthetic and catabolic processes, pectin biosynthesis, cell wall biosynthesis and organization, and lignification in the first cellular layers are mechanisms in resistant genotypes²². Research has showed that wheat seeds with higher Mn content exhibit greater resistance to take-all disease. Increasing nutrient content in grains enhances plant resistance to diseases²³. These observations suggest that root lignification and micronutrients status may constitute ken physiological determinates of resistance to take-all disease.

Based on the background, the present study was designed with the following hypotheses:

1. Interaction between wheat roots and Gaeumannomyces tritici induces lignin biosynthesis and contributes to resistance against take-all disease;

2. Inherent differences in seed Mn and Fe reserves, as well as their root uptake, influence lignification processes and defense responses.

3. Evaluate whether differences in lignification and micronutrient status are reflected at the enzymatic level by analyzing the activity of key defense-related enzymes PAL, POD, and total protein content in selected resistant and susceptible genotypes.

Materials and Methods

Fungus resource and purification and storage fungus

Gaeumannomyces tritici (T-41 isolate) was obtained from the fungal collection of Vali-e-Asr University of Rafsanjan, Iran. The fungus was cultured on potato dextrose agar (PDA) supplemented with streptomycin to prevent bacterial contamination. Cultures were purified every 20 days by transferring the actively growing margin to fresh PDA plates. Pure cultures were stored at 4°C until use^24,25.

Molecular identification of Gaeumannomyces tritici

Three specific primers used for Gaeumannomyces tritici are Ggtfwd, GgtArev, and GgtBrev2. Ggtfwd and GgtArev target the ITS2 region of ribosomal DNA, while GgtBrev2 is derived from the region between ITS2 and the large subunit of the rRNA gene. Originally designed by Freeman et al.²⁶, these primers are capable of distinguishing between type A and type B isolates. Sequence details of these primers can be found in Table 1. Genomic DNA was extracted from freeze-dried mycelia of Gaeumannomyces tritici using the CTAB method²⁷. Mycelia were obtained from actively growing cultures in potato dextrose broth, harvested by vacuum filtration, washed twice with sterile distilled water, and ground in liquid nitrogen before extraction. DNA quality and concentration were checked by spectrophotometry and agarose gel electrophoresis. To visualize the PCR product and analyze the amplified ribosomal DNA fragments, electrophoresis is performed using a 1.5% agarose gel. The size of the amplified fragments in the polymerase chain reaction is determined using a 50–1500 bp DNA marker.

Table 1.

Sequence specific primers for molecular identification of Gaeumannomyces tritici.

Sequence	Primer
5ˈ-AAGAACATCGGCGGTCTCGCC-3ˈ	Ggtfwd
5ˈ-TAGCGGCTGGAGCCCGCCG-3ˈ	GgtArev
5ˈ-CTACCTGATCCGAGGTCAACCTAAGG-3ˈ	GgtBrev2

Fungus Inoculum Preparation

Millet seeds were used as a substrate for inoculum preparation due to their high colonization efficiency and uniform propagules production. A mixture of 100 g cooked millet seeds and 100 g wet sand was autoclaved twice at 120°C for 20 min each. Small agar plugs (~ 1 cm diameter) from actively growing fungal cultures were inoculated into the sterilized millet-sand mixture. Flasks were incubated at 20–25°C for 15 days in darkness, followed by an additional 15 days under laboratory lighting (natural and fluorescent) at 20–28°C with periodic shaking to ensure aeration. Inoculum was stored at 4°C until use^24,25.

Step 1. Evaluation of lignin content and micronutrient concentration (Fe and Mn) in roots and seeds of selected wheat genotypes

Genetic Resources

In the present study, 17 genotypes (63, 483, 725, 918, 964, 1457, 1458, 1526, 1527, 1546, 1622, 1629, 1879, 2179, 2192, 9021, and 9046) were selected based on their contrasting reactions to take-all disease following cluster analysis of a larger panel of 100 genotypes evaluated under both greenhouse and field conditions²⁸.

Greenhouse experiment

The experiment was conducted under controlled greenhouse conditions as a factorial experiment arranged in a completely randomized design (CRD) with three replications. The experimental factors consisted of wheat genotype (17 genotypes) and pathogen inoculation (infected and control).

Seeds were surface-sterilized with 1% sodium hypochlorite, rinsed thoroughly with sterile distilled water, and sown (four seeds per pot) in plastic pots containing 1 kg of sandy loam soil (pH 7.84, EC 1.75 mS cm⁻¹). The soil was sterilized by autoclaving at 121°C for 1 h on three consecutive occasions.

Inoculation occurred 10 days after sowing by mixing fungal inoculum into the soil. Plants were grown at 20–25°C, 70% relative humidity, and a 16-h photoperiod.

Six weeks post-inoculation, disease severity was assessed using a 0–5 scale based on root necrosis and crown blackening, and root dry weight was measured after drying at 72°C for 48 h. Disease severity was assessed based on the percentage of necrosis in the roots and scored on a scale from 0 to 5 as follows:

0 = Roots and crowns without necrotic spots;

1 = Roots with one or more necrotic spots and crowns without symptoms;

2 = Roots with continuous necrotic spots (more than 25% and less than 50% necrosis of roots) and crowns without symptoms;

3 = More than 50% necrosis of the roots and blackened crowns;

4 = Roots nearly black with 75% blackened crowns;

5 = Roots and crowns completely black and drying.

Disease severity was further calculated using the following equation:^29,30.

1

Quantification of lignin by the acetyl bromide method

To measure the amount of lignin in the roots, the soft powder of the cell wall was extracted using a modified method to eliminate the interference of cell wall proteins and other UV-absorbing materials^31–35.

• 1. A precise weight of 1.0 to 1.5 mg of lignocellulosic powder was measured and transferred into a test tube.

• 2. To facilitate the precipitation of cell wall materials at the bottom of the test tube, 250 µL of acetone was added to each tube.

• 3. Fresh acetyl bromide solution (25% acetyl bromide in chilled acetic acid, v/v) was carefully added at a volume of 100 µL to each test tube.

• 4. The test tubes were incubated at 50°C for 2 h, with vortexing every 15 min.

• 5. After incubation, the test tubes were cooled on ice.

• 6. 400µL of 2M sodium hydroxide and 70 µL of 0.5 M hydroxylamine hydrochloride were added to each sample and vortexed.

• 7. Each tube was brought to a final volume of 2 mL with acetic acid, vortexed, and centrifuged. The lignin content of each sample was then measured using a spectrophotometer at 280 nm. The concentration of acetyl bromide-soluble lignin (ABSL) was calculated using Eq. 2^32,35:

Absorbance = Measured optical density at 280 nm.

Total volume = 2 mL.

Weight = 1.5 mg.

Coefficient = 17.75.

2

Quantification of micronutrients of root and seed

Seed Fe and Mn concentrations were measured only in the non-inoculated treatment to determine whether inherent genetic differences among genotypes contribute to take-all disease resistance, independently of pathogen-induced changes. For Mn and Fe analysis, 0.5 g of each root sample was ashed in a furnace at 550 °C for 5 h. The resulting ash was dissolved in 5 mL of 2 N HCl and diluted to a final volume of 50 mL with deionized water. The extracts were then analyzed for Mn and Fe using atomic absorption spectrometry (BS Avanta Atomic, Australia)^36,37:

3

Step 2. Evaluation of defense-related enzymes and total protein levels in representative genotypes from Step 1

Genetic resources

Based on the grouping patterns observed in Step 1, five representative wheat genotypes (1622, 1879, 725, 1526, and 1546) were selected for further biochemical analyses. In this step, the activities of the key defense related enzymes—PAL and POD along with total soluble protein content were quantified in both control and infected treatments. This step aimed to establish a direct link between enzymatic defense responses and the levels of lignin and micronutrients identified in Step 1, thereby providing a comprehensive understanding of the physiological mechanisms underlying take all disease resistance.

Greenhouse experiment

The experiment was conducted as a factorial experiment arranged in a completely randomized design (CRD) with three replications. The experimental factors included wheat genotype (5 genotypes) and pathogen inoculation (control and infected). For each genotype, six pots were used: three non-inoculated controls and three pots inoculated with Gaeumannomyces tritici (isolate T-41). Soil preparation, sterilization, planting, and inoculation procedures followed the same protocol as the greenhouse experiment used for disease evaluation, ensuring consistency between experiments. Briefly, seeds were surface-sterilized in 1% sodium hypochlorite for 3 min, rinsed thoroughly with sterile distilled water, and four seeds were sown per pot. Ten days after sowing, inoculation was performed by thoroughly mixing millet-based fungal inoculum into the soil of designated pots, while control pots received sterile millet without fungal growth. Plants were maintained under controlled greenhouse conditions with day/night temperatures of 20–25°C, relative humidity of approximately 70%, and a 16-h photoperiod. Pots were irrigated regularly to maintain optimal soil moisture and prevent drought stress. Six weeks after inoculation, leaf tissues were collected from both inoculated and non-inoculated plants, immediately frozen in liquid nitrogen, and stored at –80°C until biochemical analysis. Total soluble protein was extracted from leaf tissues and used to normalize enzymatic assays, while the activities of PAL and POD were measured in the same leaf protein extracts.

Quantification of defense enzymes

Protein extraction and total protein content

Leaf tissue (0.5 g) was ground in 3–5 mL of 50 mM potassium phosphate buffer (pH 7.5) containing 1% PVP and 1 mM EDTA on ice. The homogenate was centrifuged at 4000 rpm for 20–30 min at 4°C, and the supernatant was stored at − 20°C. Total protein content was determined using the Bradford method with bovine serum albumin as a standard³⁸.

Phenylalanine ammonia-lyase

In this method, phenylalanine was used as the enzyme precursor, and enzyme activity was estimated based on the amount of cinnamic acid produced³⁹. To begin, 1 ml of extraction buffer, 0.5 ml of 10 mM phenylalanine, 0.4 ml of double-distilled water, and 0.1 ml of enzyme extract were mixed and kept at 37°C for 1 h. The reaction was terminated by the addition of 0.5 mL of 6 M hydrochloric acid, and the sample absorbance was subsequently measured at 260 nm. One unit of enzyme activity was defined as 1 μmol of cinnamic acid produced in 1 min per mg of protein. To determine the amount of cinnamic acid produced, a standard curve of cinnamic acid was utilized at concentrations of 0, 10, 15, 20, 25, 30, and 35 micromolar.

Peroxidase

The reaction mixture contained 2.77 mL of 50 mM potassium phosphate buffer (pH 7), 100 μL of 1% H₂O₂, 100 μL of 4% guaiacol, and 30 μL of enzyme extract. The increase in absorbance at 470 nm was recorded for 3 min. Enzyme activity was calculated using the extinction coefficient of tetraguaiacol (5.25 mM⁻¹ cm⁻¹)⁴⁰.

Statistical analysis

Data normality was verified using the Kolmogorov–Smirnov test, and square root transformation was applied where necessary. Analysis of variance (ANOVA) was conducted under a factorial completely randomized design (CRD) using SAS software (SAS Institute Inc., SAS® version 9.0; https://www.sas.com) and Minitab Statistical Software (Minitab LLC, Version 19; https://www.minitab.com). For the initial screening experiment (Step 1), differences between inoculated and control treatments were compared using Fisher’s protected least significant difference (LSD) test at P ≤ 0.05. In the subsequent experiment (Step 2), comparisons among wheat genotypes within each treatment were performed using Tukey’s test at P ≤ 0.05. Pearson’s correlation coefficients and principal component analysis (PCA) were conducted using Minitab Statistical Software (Version 19) to assess relationships among traits under both inoculated and control conditions.

Results

The result of molecular identification of Gaeumannomyces tritici

DNA amplification using specific primers successfully differentiated between Gaeumannomyces types (A) and (B). Type (A) isolates were distinguished by the amplification of a 93 base pair fragment, whereas type (B) isolates produced a 123 base pair fragment. The isolate used in this study was identified as type (A); previous reports associate type (A) isolates with higher pathogenicity and variable sensitivity to silthiofam., which is used for controlling take-all disease²⁸. Figure 1 illustrates the results of Gaeumannomyces DNA amplification using specific primers on a 1.5% agarose gel.

Fig. 1.

Specific identification of Gaeumannomyces tritici (type A) and amplification of the 93 base pair fragment with specific primers Ggtfwd, GgtArev and Ggtrev2 (Cropped sections originate from the same gel; full-length gel images are provided in Supplementary Figure S1).

ANOVA and mean comparisons

ANOVA was conducted for all studied traits (Mn, Fe, and lignin content in root, root dry weight, and disease severity), and the results showed significant effects of treatment (G. tritici and control), genotype, and their interaction at the 1% probability level (result not shown). Mean differences for genotype × treatment interactions were assessed using the least significant difference (LSD) test, and corresponding results are presented in Tables 2, 3, and 4.

Table 2.

Comparison of root Fe and Mn concentrations between G. tritici‑infected and control wheat genotypes.

Genotype	Fe in root (mg.kg-1)			Mn in root (mg.kg-1)
	G. tritici	Control	Difference	G. tritici	Control	Difference
63	36.335	27.687	8.648**	10.709	9.073	1.636**
483	38.082	17.156	20.926**	12.173	5.895	6.278**
725	27.374	28.348	-0.974ns	7.815	9.106	-1.291**
918	18.694	18.226	0.467ns	7.388	6.581	0.807*
964	47.923	48.615	-0.691ns	16.644	14.276	2.368**
1457	13.442	24.389	-10.947**	3.308	6.906	-3.598**
1458	39.652	26.938	12.714**	11.159	8.058	3.101**
1526	32.240	39	-6.759**	8.442	11.048	-2.606**
1527	42.128	42.044	0.084ns	15.149	14.024	1.125**
1546	28.597	40.3	-11.703**	8.294	11.035	-2.741**
1622	50.736	32.210	18.526**	12.175	11.110	1.064**
1629	10.172	10.115	0.057ns	3.179	3.382	-0.202ns
1879	52.209	28.922	23.287**	16.087	8.055	8.032**
2179	40.432	22.184	18.248**	9.534	5.098	4.436**
2192	30.167	17.951	12.216**	10.825	4.94	5.885**
9021	20.585	14.969	5.616**	7.759	5.098	2.660**
9046	46.882	19.918	26.964**	11.928	6.155	5.773**
LSD 0.05	1.072			0.699
LSD 0.01	1.440			0.939

*, **, and ^ns: Significant at 0.05, 0.01 probability, and no significant, respectively

Table 3.

Comparison of root lignin content between G. tritici‑infected and control wheat genotypes.

Genotype	Lignin (ug.mg-1 cell wall unit)
	G. tritici	Control	Difference
63	68.41	51.68	16.73**
483	104.15	62.48	41.67**
725	49.54	57.52	-7.98ns
918	95.50	58.27	37.23**
964	87.89	53.59	34.3**
1457	59.91	87.80	-27.89**
1458	95.61	47.33	48.28**
1526	35.38	58.28	-22.89**
1527	49.35	51	-1.64ns
1546	47.95	78.30	-30.35**
1622	72.52	49.15	23.37**
1629	68.04	77.73	-9.68*
1879	73.44	34.03	39.41**
2179	78.81	59.39	19.42**
2192	100.48	60.18	40.29**
9021	82.19	61.70	20.48**
9046	94.75	62.33	32.41**
LSD 0.05	9.331
LSD 0.01	12.527

*, **, and ^ns: Significant at 0.05, 0.01 probability, and no significant, respectively

Table 4.

Comparison of root dry weight and disease severity between G. tritici‑infected and control wheat genotypes.

Genotype	Root dry weight (gr)				Disease Severity
	G. tritici	Control	Difference		G. tritici	Control	Difference
63	0.340	0.347	−0.007ns		0.195	0	0.195**
483	0.336	0.316	0.02ns		0.14	0	0.14**
725	0.377	0.402	−0.024*		0.875	0	0.875**
918	0.512	0.337	0.174**		0.022	0	0.022ns
964	0.335	0.312	0.023ns		0.215	0	0.215**
1457	0.330	0.352	−0.021ns		0.585	0	0.585**
1458	0.421	0.315	0.105**		0.35	0	0.35**
1526	0.362	0.368	−0.005ns		0.95	0	0.95**
1527	0.308	0.317	−0.009ns		0.73	0	0.73**
1546	0.124	0.304	−0.180**		0.99	0	0.99**
1622	0.487	0.328	0.159**		0.05	0	0.05**
1629	0.313	0.303	0.01ns		0.575	0	0.575**
1879	0.534	0.438	0.096**		0.1	0	0.1**
2179	0.455	0.407	0.048**		0.145	0	0.145**
2192	0.588	0.360	0.228**		0.075	0	0.075**
9021	0.427	0.264	0.163**		0.395	0	0.395**
9046	0.4145	0.280	0.134**		0.385	0	0.385**
LSD (0.05)	0.0236				0.0248
LSD (0.01)	0.0316				0.0334

*, **, and ^ns: Significant at 0.05, 0.01 probability, and no significant, respectively

The analysis of Fe and Mn concentrations in wheat roots revealed significant genotypic variation under G. tritici infection (Table 2). Resistant genotypes generally showed higher Fe and Mn accumulation under G. tritici treatment compared with susceptible genotypes, whereas an opposite trend was observed under control conditions. In particular, genotypes 483, 1622, 1879, 2179, and 9046 exhibited the highest root Fe concentrations, while genotypes 483, 1879, 2192, and 9046 showed the highest Mn concentrations.

Lignin content was significantly affected by genotype and treatment interaction (Table 3). The highest lignin accumulation under G. tritici treatment was observed in genotypes 483, 918, 1458, 1879, and 2192.

Root dry weight and disease severity were also significantly influenced by genotype × treatment interaction (Table 4). Under G. tritici infection, genotypes 918, 1458, 1622, 1879, 2192, 9021, and 9046 maintained higher root weight compared to the control, while disease severity varied markedly among genotypes. The lowest disease severity was observed in genotypes 1879, 2192, 1622, and 918.

Figure 2 illustrates the root systems of resistant and susceptible wheat genotypes under infected (B) and control (A) conditions. In resistant genotypes, infection with G. tritici induced the formation of secondary roots (indicated by the red arrow), which appeared thicker and more branched compared to controls. These morphological changes suggest a compensatory adaptive response aimed at maintaining nutrient and water uptake despite pathogen-induced damage. In contrast, susceptible genotypes showed severe root decay, reduced branching, and a loss of fine root structure under infection, indicating limited capacity for structural recovery. This study further observed that plants showing relative resistance to take-all disease (e.g., genotype 1458) exhibit increased lignification in their roots, evident through color changes and enhanced nutrient absorption. Resistant genotypes like genotype 1622 prevent pathogen penetration through their defense mechanisms and systemic resistance, effectively suppressing initial pathogen attacks upon root contact (Fig. 3).

Fig. 2.

Root system of resistant wheat genotypes under control (A) and G. tritici-infected (B) conditions. The red arrow highlights secondary root formation induced by infection, indicating a compensatory response to maintain nutrient and water uptake.

Fig. 3.

Lignin content changes in two wheat genotypes (1458 and 1622) with contrasting reactions to take-all disease under infected and control treatments.

Principal Component Analysis

Principal component analysis (PCA) was employed to identify key components with high variance, making it a suitable multivariate technique for assessing independent principal components that affect traits individually. In this analysis, the average difference between infected and control conditions (infected—control) was examined to accurately determine influential traits and genotype groupings. It’s important to note that Fe and Mn in seeds were only measured under control conditions.

Based on the biplot from the first and second components (Fig. 4), Fe and Mn ions in roots, lignin content, and root weight exhibited strong correlations, particularly with genotypes 918, 2179, 483, 1622, and 1458. PCA revealed that two components, PC1 and PC2, accounted for 78% of the total variance among traits in bread wheat genotypes (Table 5). PC1 and PC2 contributed 63% and 15% to the total variation, respectively.

Fig. 4.

The biplot chart derived from the first and second components based on mean difference of infected-control in wheat genotypes ((A): Biplot chart based on genotypes, (B): Biplot chart based on trait).

Table 5.

Principal component analysis of different traits in 17 wheat genotypes.

Variable	PC 1	PC 2
Disease severity	0.402	−0.336
Fe in root (mg.kg-1)	0.427	−0.140
Mn in root (mg.kg-1)	0.459	0.052
Lignin (%)	0.344	−0.317
Root weight	−0.430	−0.002
Fe in seed (μ.g-1)	0.209	0.799
Mn in seed (μ.g-1)	0.316	0.354
Eigen value	4.407	1.048
Proportion (%)	63	15
Cumulative	63	78

The first PC1 showed high positive loadings for five traits, including Fe and Mn ions in roots, root weight, disease severity, and lignin content, collectively influencing diversity and grouping. Hence, PC1 was labeled as the "resistance component." The PC2 generally related to a decrease in traits associated with resistance, such as Fe and Mn ions in roots, lignin content, root weight, and disease severity, and was named the “sensitivity component”.

According to the results, the 17 genotypes clustered into two main groups based on their PCA scores (Fig. 4). The first group comprises genotypes 964, 1879, 2179, 918, 483, 2192, 1622, 1458, 9046, and 9021, characterized by high positive values on the first principal component. The second group includes genotypes 1546, 1526, 1457, 725, 1527, 1629, and 63, located where the first component scores low and the second component scores high.

To confirm the grouping, an analysis of variance was performed based on a completely random unbalanced design. In this analysis, the groups were considered as treatments, and the genotypes within the groups were considered as replicates. ANOVA on different traits revealed significant differences between the two groups for all traits except Fe in seeds (Table 6). According to comparisons of mean differences (infected—control) based on Tukey’s test, the first group showed a positive and significant difference compared to the control treatment. Additionally, this group was significantly different from the second group in all traits except Fe in seeds (Table 7). The negative coefficient in the averages of the second group indicates that these traits are higher in the control treatment (sensitive to disease).

Table 6.

Analysis of variance for traits between two groups derived from PCA.

Source	df	MS
		Disease Severity	Fe in root	Mn in root	Lignin	Root weight	Fe in seed	Mn in seed
Group	1	1.080**	1177.77**	108.681***	7302.2***	0.0831**	1237.3ns	1149.4*
Error	15	0.042	75.08	5.126	177.7	0.0055	342.9	138.6
Total	16

*, **, ***, and ^ns: Significant at 0.05, 0.01 probability, and no significant, respectively

Table 7.

Mean comparisons of traits among PCA-derived groups using Tukey’s test.

Genotypes/traits	Groups
	1	2
Genotypes	964, 1879, 2179, 918, 483, 1622, 1458, 9021, 2192, 9046	1546, 1526, 1457, 725, 1527, 1629, 63
Disease severity	0.18b	0.7a
Fe in root (mg.kg-1)	13.827a	−3.085b
Mn in root (mg.kg-1)	4.040a	−1.096b
Lignin (ug.mg-1 cell wall unit)	30.42a	−11.68b
Root weight (gr)	0.1081a	−0.0340b
Fe in seed (mg.kg-1)	36.72a	19.385a
Mn in seed (mg.kg-1)	91.350a	74.642b

In each row (traits), Means followed by the same letters are not significantly different (HSD test, P < 0.05)

Correlation

The degree of association among traits in wheat genotypes under control and infected conditions was assessed using Pearson correlation analysis (Fig. 5). Significant relationships were observed among the measured traits. Disease severity showed strong positive correlations with nutrient availability in plants. Specifically, Fe concentration in root exhibited a strong positive correlation with Mn concentration in root (0.887, p = 0.000), lignin content (0.770, p = 0.000), and root weight (0.536, p = 0.026). Similarly, Mn concentration in root correlated positively with lignin (0.852, p = 0.000) and root weight (0.542, p = 0.024). Lignin content also positively correlated with root weight (0.718, p = 0.001) and Mn concentration in seed (0.579, p = 0.015).

Fig. 5.

Matrix Plot of different traits in Pearson correlation.

Conversely, negative correlations were found between Fe concentration in root and disease severity (-0.688, p = 0.002), Mn concentration in root and disease severity (-0.713, p = 0.001), lignin content and disease severity (-0.847, p = 0.000), and disease severity and Mn concentration in seed (-0.601, p = 0.011). The matrix plot demonstrated the distribution of resistant and sensitive groups identified through principal component analysis. Generally, negative correlations suggest that reduced levels of nutrients (Fe and Mn) increase the severity of take-all disease, implying that heightened disease severity may decrease the availability of these essential nutrients in wheat plants. This research determined that Mn concentration in seeds shows a direct and positive interaction with lignin content (0.579, p = 0.015) and a direct and negative interaction with disease severity (-0.601, p = 0.011).

Defensive enzyme changes and their relationship with lignin content and resistance to take-all disease

Activity levels of three defense‑related biochemical markers (total soluble protein, POD, and PAL) were quantified in five representative wheat genotypes: two resistant (1622 and 1879) and three susceptible (725, 1526, and 1546). Significant differences were observed among genotypes for all three traits (P ≤ 0.05) (result not shown).

The G. tritici treatment had a differential effect on the genotypes for total protein content. Genotypes 1622 and 1879 showed a significant increase in total protein compared to the control, with 1622 exhibiting the highest value (151.222 mg/gr fresh weight) and 1879 the second highest (145.389 mg/gr fresh weight). In contrast, genotype 1526 under G. tritici treatment exhibited the lowest protein content (115.944 mg/gr fresh weight), indicating a strong suppressive effect of the pathogen. The control treatments of genotypes 1546 and 1526, as well as 1546 under G. tritici, formed an intermediate group with no significant differences among them. Genotype 725 showed no significant difference between control and inoculated treatments, suggesting limited responsiveness of total protein content to pathogen infection. Overall, these results demonstrate a clear genotype-specific regulation of total protein accumulation in response to G. tritici, with resistant genotypes maintaining or enhancing protein levels, while susceptible genotypes, particularly 1526, exhibited pronounced reductions (Fig. 6).

Fig. 6.

Interaction effect of genotype and treatment on total protein content. Mean comparisons were performed using Tukey’s honestly significant difference (HSD) test, and means not significantly different (P < 0.05) are indicated by shared letters.

The G. tritici treatment induced significant, genotype-dependent changes in POD activity (Fig. 7). Under pathogen treatment, genotype 1879 exhibited the highest POD activity (1.78808 unit/mg protein) and was statistically grouped among the top responders. Genotype 1526 under G. tritici treatment also showed a strong induction of POD activity (1.74456 unit/mg protein) and did not differ significantly from genotype 1879. Moderate POD activity levels were observed in the control treatment of genotype 1526 (1.45781 unit/mg protein) and in genotype 1879 under control conditions (1.3762 unit/mg protein), which formed intermediate statistical groups. Genotype 725 under G. tritici treatment (1.3421 unit/mg protein) and genotype 1546 under control conditions (1.32054 unit/mg protein) also showed intermediate responses. In contrast, genotype 1622 under G. tritici treatment exhibited a lower POD activity (1.20179 unit/mg protein) compared with the highly responsive genotypes, while genotype 1546 under G. tritici treatment showed a pronounced reduction (0.92567 unit/mg protein). The lowest POD activity was observed in genotype 725 under control conditions (0.39251 unit/mg protein). Overall, these results demonstrate a strong genotype-specific regulation of peroxidase activity in response to G. tritici, with some genotypes showing marked induction, while others exhibited limited or suppressive responses.

Fig. 7.

Interaction effect of genotype and treatment on POD activity. Mean comparisons were performed using Tukey’s honestly significant difference (HSD) test, and means not significantly different (P < 0.05) are indicated by shared letters.

The G. tritici treatment exhibited a genotype-specific effect on PAL activity. Genotype 1622 showed the highest increase under treatment (0.0000272 unit/mg protein), followed by 1879 with a moderate increase (0.0000262 unit/mg protein). Genotypes 1546 and 725 remained largely unchanged (0.0000247 unit/mg protein and 0.0000245 unit/mg protein), while genotype 1526 exhibited a decrease in PAL activity (0.0000209 unit/mg protein). These results indicate that PAL induction by G. tritici is highly dependent on genotype (Fig. 8).

Fig. 8.

Interaction effect of genotype and treatment on PAL activity. Mean comparisons were performed using Tukey’s honestly significant difference (HSD) test, and means not significantly different (P < 0.05) are indicated by shared letters.

Correlation analysis

Correlation analysis among the traits revealed a strong and highly significant positive relationship between PAL activity and total protein content (r = 1.000, p < 0.001), as well as between PAL and lignin content (r = 0.919, p < 0.05). Total protein was also highly correlated with lignin (r = 0.919, p < 0.05). Mn and Fe concentrations in roots showed a very strong and significant correlation (r = 0.932, p < 0.05). POD activity did not show any significant correlation with the other measured traits. PAL, total protein, and lignin content exhibited moderate positive, though non-significant, correlations with Mn and Fe in roots (Table 8).

Table 8.

Correlation matrix among enzyme activities (PAL, POD), total protein, lignin content, and Mn and Fe concentrations in roots.

Traits	PAL	POD	Total protein	Lignin content	Mn in root	Fe in Root
PAL	1
POD	−0.352ns p-value = 0.561	1
Total protein	1.000*** p-value = 0.000	−0.352ns p-value = 0.561	1
Lignin content	0.919* p-value = 0.027	0.024ns p-value = 0.970	0.919* p-value = 0.027	1
Mn in root	0.611ns p-value = 0.274	0.448ns p-value = 0.449	0.611ns p-value = 0.274	0.858ns p-value = 0.063	1
Fe in root	0.656ns p-value = 0.230	0.339ns p-value = 0.577	0.656ns p-value = 0.230	0.886* p-value = 0.045	0.932* p-value = 0.021	1

*, *** and ^ns: Significant at 0.05, 0.001 probability, and no significant, respectively

Pearson’s correlation coefficients (r) are shown, with corresponding p-values provided below each coefficient

Stepwise regression analysis

The stepwise regression analysis identified two key predictors for root lignin content: root Mn concentration and total protein content. Both variables were retained in the final model based on their statistical significance (p < 0.05). Root Mn showed a positive and significant effect on lignin accumulation (β = 0.2222, p = 0.047), indicating that for every 1-unit increase in root Mn, lignin content increased by approximately 0.22 units when total protein was held constant. Similarly, total protein exhibited a strong positive association with lignin content (β = 0.0784, p = 0.027), suggesting that higher protein levels are linked to greater lignification. The regression model (Table 9) indicates that both Mn and total protein collectively explain a substantial portion of the variability in lignin content among genotypes. The low variance inflation factor (VIF = 1.60 for both predictors) suggests no multicollinearity between the independent variables, supporting the reliability of the model (Table 9).

Table 9.

Stepwise regression analysis of lignin content in wheat roots based on multiple physiological and biochemical traits.

Term	Coef	SE Coef	T-Value	P-Value	VIF
Constant	−7.52	1.56	−4.83	0.040
Mn in Root	0.2222	0.050	4.44	0.047	1.60
Total protein	0.0784	0.013	5.91	0.027	1.60
Regression Equation	Lignin content = -7.52 + 0.2222 Mn in Root + 0.0784 Total protein

Discussion

To the best of our knowledge, this is the first study to simultaneously integrate root lignification, seed and root micronutrient concentrations (Mn and Fe), and defense‑related enzymes (POD, PAL, and total protein) to elucidate resistance mechanisms against take‑all disease in bread wheat. This multi‑layered approach provides new insights into both physiological resistance mechanisms and practical selection strategies for breeding programs. Resistance to take‑all disease is a complex, multigenic trait influenced by multiple physiological, biochemical, and environmental factors.

Step 1: Root and seed nutrient profiles, lignification, and resistance

The result of this step showed that lignin content was highest in genotypes 483, 918, 1458, 1879, and 2192. In other words, the level of lignin in resistant genotypes was higher than that in susceptible genotypes. It is possible that lignin acts as a defensive barrier against pathogen penetration. Based on these result, probably lignin emerged as a central component of wheat defense against G. tritici, with resistant genotypes exhibiting significantly higher lignin content upon infection. Lignin accumulation the root cell wall, creating a physical and biochemical barrier that hinders pathogen penetration and hyphal expansion^11,41,42. Upon pathogen attack, lignification is rapidly induced via activation of the phenylpropanoid pathway, facilitating deposition of phenolic polymers that strengthen mechanical resistance and limit enzymatic degradation. Upon pathogen invasion, plants often activate lignification pathways as part of their early immune signaling, leading to the reinforcement of the cell wall structure through deposition of complex phenolic polymers. This structural enhancement restricts pathogen advancement and provides mechanical resilience to affected tissues. Several studies have reported that resistant cultivars, particularly in cereals, tend to exhibit higher lignin accumulation in infected tissues, often dominated by syringyl-rich lignin units that are more recalcitrant to enzymatic degradation^43–46.

The observed positive correlations between root Fe/Mn concentrations and lignin content, together with negative correlations with disease severity, are consistent with a potentially synergistic contribution to root defense and warrant further functional investigation. These relationships suggest that optimal micronutrient nutrition not only enhances lignification but also helps stabilize redox balance and maintain enzymatic activity essential for localized defense. Beyond its structural role, lignification interacts with the oxidative burst, characterized by the rapid accumulation of reactive oxygen species (ROS) such as hydrogen peroxide, which facilitates cross‑linking of lignin precursors during pathogen attack^47,48. The conserved nature of this response across plant taxa underscores its universal role in defense. Our findings are consistent with studies reporting PAL upregulation as a central defense response in wheat, rice, potato, and chickpea under fungal infection^49–54. Recent transcriptomic analyses further support the importance of phenylpropanoid metabolism in disease resistance, where higher expression of PAL, HCT, COMT, and CCoAOMT correlates with enhanced lignin accumulation and host immunity^52–54. The role of micronutrients extends beyond enzyme activation. In wheat infected with G. tritici, elevated root Fe and Mn concentrations appear to directly reinforce root structural integrity while supporting other defense-related functions such as PR protein synthesis, systemic acquired resistance signaling, and antioxidant defenses^25,55–58. Interaction studies between wheat and take-all pathogen have identified over 1400 genes involved in redox regulation, lipid metabolism, cell wall fortification, and hypersensitive responses during infection⁵⁹, suggesting multilayered defense networks involving both metabolic and hormonal regulation. The present study provides novel insight by simultaneously analyzing both root and seed Fe/Mn concentrations as resistance determinants. Genotypes with higher seed Fe and Mn exhibited superior resistance post-infection, suggesting that seed nutrient reserves may serve as predictive markers for early-stage genotype selection^60,61. Our findings revealed that seed Mn levels showed a significant positive correlation with root lignin content (r = 0.579) and a significant negative correlation with disease severity (r = -0.601). This suggests that genotypes with higher inherent Mn reserves in seeds may possess an enhanced capacity to initiate lignification processes and activate defense pathways upon pathogen attack, ultimately reducing disease progression. These results highlight the potential of seed Mn concentration as an early biochemical marker for predicting take-all resistance and guiding breeding strategies. These observations are in agreement with previous research showing the pivotal role of Mn in plant defense. McCay-Buis et al. (1995)⁶⁰ reported that wheat cultivars with higher seed Mn content exhibited significantly lower take-all incidence and greater vigor compared to cultivars derived from seeds with lower Mn levels. Consistent with our findings, these results suggest that seed Mn serves as a foundational resource for early root defense, particularly by promoting lignification and the activation of key defense-related enzymes such as PAL and peroxidases⁶⁰. Consequently, selecting genotypes with naturally higher Mn reserves in seeds, or implementing agronomic practices to increase seed Mn content, may represent a practical strategy for enhancing take-all resistance in wheat breeding and management programs.

Step 2: Validation through defense enzyme activity

The second step of this study was conducted as a complementary experiment to validate the findings from Step 1. In this step, five representative wheat genotypes (two resistant and three susceptible) were selected based on their contrasting resistance to take-all disease, as determined in step 1. The objective was to determine whether the activity of key defense-related enzymes directly influences lignin biosynthesis and, in turn, contributes to resistance. This step was intended to establish a mechanistic link between biochemical defense responses and the structural reinforcement observed in resistant genotypes. G. tritici treatment caused genotype-specific changes in total protein content. Genotypes 1622 and 1879 showed the highest increase (151.222 mg.g^-1 fresh weight and 145.389 mg.g^-1 fresh weight, respectively). In other hand POD activity increased significantly in all genotypes after infection, with 1879 and 1526 showing the highest levels (1.78808 unit/mg protein and 1.74456 unit/mg protein). Also PAL activity exhibited strong genotype dependence. Genotype 1622 recorded the highest activity (0.0000272 unit/mg protein), followed by 1879 (0.0000262 unit/mg protein). A strong positive relationship between PAL and total protein (r = 1.000^***), as well as between PAL and lignin content (r = 0.919^***). Mn and Fe concentrations in roots were also highly correlated (r = 0.932^***). Additionally, the results of stepwise regression showed a direct relationship between root lignin levels, root total protein, and manganese content. Lignin accumulates in cell walls and serves as a physical and biochemical barrier to pathogen invasion. Our findings are consistent with previous studies, such as those by Lee et al.⁶² and Vanholme et al.⁶³, which highlight the role of lignification in enhancing disease resistance. Lignin biosynthesis is regulated by multiple enzymes including PAL, polyphenol oxidase (PPO), and POD, whose activities are closely tied to micronutrient availability. Mn functions as a cofactor for PAL and POD enzymes critical for monolignol synthesis and polymerization, while Fe supports oxidative polymerization through peroxidase activation^64–66.

Functional studies in various systems indicate that PAL suppression can reduce lignin accumulation and increase susceptibility; however, system-specific validation is needed for wheat–G. tritici. Thus, PAL-mediated metabolic flux appears to act as a central hub, linking micronutrient availability to downstream lignification and resistance outcomes^5,67. Mn acts as a cofactor for enzymes such as PAL and POD involved in monolignol polymerization, while Fe supports oxidative polymerization via POD activation. Mn activates phytoalexins and other molecular compounds to stimulate plant defense reactions⁶¹. Furthermore, it was observed that Fe levels in roots exhibit strong positive interactions with lignin content and manganese levels in roots. Fe is a component of POD, which in turn stimulates enzymes crucial for lignin biosynthesis pathways^64–66,68. This offers a practical advantage for breeding programs by incorporating biochemical markers into selection pipelines alongside conventional phenotypic screening. Multivariate analysis using PCA further confirmed the integrated contribution of biochemical and morphological traits to take-all resistance. PCA revealed that lignin content, root weight, root Fe and Mn levels, and disease severity were the primary factors driving genotype separation. Resistant genotypes formed distinct clusters within PCA space, highlighting the value of combining multiple physiological indicators for robust resistance classification. These findings build upon our previous screening of 100 genotypes by providing biochemical validation of the observed genotype groupings²⁸.

Comparative studies across wheat ploidy levels have shown that enhanced resistance to Fusarium crown rot in synthetic hexaploid wheat is associated with the upregulation of multiple defense-related pathways. Notably, PAL-mediated biosynthetic routes for lignin and salicylic acid (SA) appear to play a central role, corresponding with increased PAL activity, lignin deposition, and SA accumulation at stem bases⁵⁴.

Transcriptome and metabolite profiling of resistant and susceptible wheat lines under stripe rust infection have highlighted the critical role of phenylpropanoid metabolism in disease resistance. In particular, TaPAL, a key gene encoding PAL, has been shown to positively regulate the biosynthesis of both lignin and phenolic compounds during pathogen challenge⁵².

Integration of both steps

Combining the findings from both steps, a comprehensive defense model emerges in which high seed Mn content primes genotypes for rapid activation of PAL and POD following pathogen attack. This enzymatic cascade drives lignin biosynthesis, reinforcing the root cell wall as a physical and biochemical barrier to fungal invasion. Resistant genotypes maintain higher root biomass and secondary root proliferation, which enhances nutrient uptake and systemic defense signaling.

Additionally, this study observed that resistant genotypes demonstrated greater secondary root development under infection, particularly in high Mn lines, further enhancing nutrient uptake capacity and contributing to systemic resistance. The role of secondary roots in nutrient acquisition and hydraulic signaling may represent an adaptive trait enhancing defense readiness under pathogen stress^69,70. Taken together, our findings suggest that lignin accumulation, regulated by micronutrient-mediated activation of phenylpropanoid metabolism, forms a key resistance mechanism against G. tritici. The present results indicate that wheat genotypes exhibiting higher intrinsic concentrations of Fe and Mn are associated with enhanced resistance to G. tritici-induced take‑all disease. In our study, resistant genotypes showed elevated seed Fe and Mn reserves (Fe ≈ 36.72 mg.kg^-1, Mn ≈ 91.35 mg.kg^-1) compared to sensitive genotypes (Fe ≈ 19.38 mg.kg^-1, Mn ≈ 74.64 mg.kg^-1), and the highest root accumulation in resistant lines was observed at Fe ≈ 38–52 mg.kg^-1 and Mn ≈ 12–16 mg.kg^-1. Consistent with these observations, plants with inadequate Mn nutrition have been reported to be less able to restrict fungal hyphal penetration into root tissues, whereas adequate Mn nutrition enhances lignification and limits pathogen colonization, likely through the activation of phenylpropanoid metabolism and associated defense enzymes (e.g., PAL, POD). This aligns with studies showing that sufficient Mn status improves synthesis of phenolic and lignin compounds, contributing to physical and biochemical barriers against fungal invasion⁷¹.

Iron’s role in plant–pathogen interactions is complex, but it can contribute to host defense by modulating redox homeostasis and enhancing oxidative burst responses upon infection. These responses are associated with the induction of defense-related genes and metabolites that limit pathogen establishment. Our results suggest that genotypes with higher Fe allocation may better sustain these defense processes, although the dual requirement of Fe by both plant and pathogen highlights the importance of maintaining balanced micronutrient homeostasis⁷².

Generally our previous field study, which evaluated six bread wheat genotypes and two wild relatives (Ae. tauschii and T. boeticum), revealed that increased lignin deposition and higher concentrations of Fe, Mn, and potassium in the crown tissues were associated with reduced take-all disease severity under non-autoclaved soil conditions⁷³. These results highlight the importance of micronutrient-mediated lignification in the root–crown region as a key barrier to pathogen penetration. In the present greenhouse study, sterilized (autoclaved) soil was used to isolate intrinsic genotypic differences in lignin synthesis and micronutrient uptake, independent of soil microbial influence. The consistency between experiments conducted under natural and sterile soil conditions strongly supports the hypothesis that lignin formation and micronutrient accumulation are genetically regulated traits that contribute to take-all resistance in wheat. Collectively, the identified physiological traits, particularly lignin content and micronutrient accumulation, serve as non-destructive, quantitative indicators for pre-breeding screening. Integrating these traits into breeding pipelines may accelerate the identification of genotypes with inherent resistance to take-all disease. Figure 9 illustrates the proposed resistance pathway to take-all based on our results and enzyme activity analyses.

Fig. 9.

The pathway of resistance to take-all disease. Recognition of pathogen-associated molecular patterns (PAMPs) by pattern recognition receptors (PRRs) at the root surface triggers an oxidative burst and the production of reactive oxygen species (ROS). These early defense signals activate intracellular signaling pathways, leading to the induction of defense-related genes and enzymes, including phenylalanine ammonia-lyase (PAL) and peroxidases. Activation of the phenylpropanoid pathway promotes lignin biosynthesis, followed by lignification and lignin deposition in the cell wall, thereby reinforcing a physical barrier against pathogen penetration. Simultaneously, enhanced uptake of micronutrients such as iron (Fe) and manganese (Mn) supports phenylpropanoid metabolism and further contributes to lignin accumulation. Collectively, these cellular and physiological responses strengthen cell wall integrity, limit fungal colonization, and contribute to resistance against take-all disease.

Conclusion

Building on these findings, the present greenhouse experiment was carried out using 17 genotypes grown in sterile (autoclaved) soil to investigate the intrinsic role of genotypes in lignin synthesis and micronutrient uptake, independent of soil microbial effects. In our study, resistant genotypes showed elevated seed Fe and Mn reserves (Fe ≈ 36.72 mg.kg^-1, Mn ≈ 91.35 mg.kg^-1) compared to sensitive genotypes (Fe ≈ 19.38 mg.kg^-1, Mn ≈ 74.64 mg.kg^-1), and the highest root accumulation in resistant genotypes was observed at Fe ≈ 38–52 mg.kg^-1 and Mn ≈ 12–16 mg.kg^-1. These observations suggest that higher elemental reserves in seeds may enhance the plant’s ability to initiate lignification and strengthen root defense responses against the pathogenic fungus. The analysis of defense-related enzymes in five selected genotypes (resistant and susceptible) further revealed that the activities of POD and PAL were positively correlated with lignin content, suggesting that these enzymes play a key role in the biochemical defense pathway underlying take-all resistance.

Overall, the greenhouse results are consistent with previous field observations and reinforce the view that iron, manganese, and potassium, together with lignin biosynthesis, collectively contribute to take-all resistance. Therefore, selecting genotypes with intrinsically higher seed reserves of micronutrients—particularly manganese and iron—combined with balanced nutrient management in the soil, may represent an effective strategy to enhance the durability of wheat resistance to this disease. In addition, the resistant genotype 1879, which is characterized by a high root iron concentration (52.209 mg.kg^-1), elevated root manganese (16.087 mg.kg^-1), substantial root lignin content (73.44 µg/g cell wall unit), and enhanced POD enzyme activity (1.788 unit mg⁻¹ protein), can be considered a superior genotype combining multiple desirable defense-related traits. From a plant breeding perspective, this genotype represents an ideal parental line, as the concurrent presence of traits associated with efficient micronutrient accumulation, lignification, and defense enzyme activity suggests a coordinated genetic defense mechanism. Such simultaneous integration of favorable defense attributes is valuable for the development of wheat cultivars with durable resistance to take-all disease.

However, certain limitations of the study should be acknowledged. The greenhouse experiment was conducted in sterile soil, which, while appropriate for examining intrinsic genotypic differences, excluded the effects of beneficial soil microorganisms and thus may not fully represent field conditions. Furthermore, the molecular regulation of genes associated with lignin biosynthesis and micronutrient uptake was not extensively examined; future work focusing on gene expression could clarify the mechanistic links between molecular regulation and physiological resistance.

Future studies should focus on the following directions to build upon the current findings:

1. Validation under diverse conditions: Validate these findings across a broader range of wheat genetic backgrounds and environmental conditions to confirm the stability and generality of the observed relationships.

2. Molecular and functional analysis: Identify and characterize key regulatory genes involved in lignin biosynthesis and micronutrient transport using functional genomics approaches such as transcriptome profiling and gene-editing techniques.

3. Marker development for breeding: Develop and validate molecular markers linked to lignin synthesis and micronutrient uptake pathways for use in marker-assisted selection programs aimed at improving take-all resistance.

4. Nutrient-based management strategies: Assess the effectiveness of Mn- and Fe-enriched fertilizers under field conditions as complementary tools to genetic resistance, with the goal of integrating physiological and agronomic strategies for sustainable disease control.

5. In conclusion, the complementary field and greenhouse investigations presented here provide a comprehensive framework for understanding the synergistic role of lignin and micronutrients in wheat resistance to take-all disease. These insights offer a valuable foundation for both breeding and nutrient management strategies aimed at improving wheat health and productivity across diverse environments.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

Conceptualization: Roohallah Saberi Riseh, Hossein Dashti, and Mozhgan Gholizadeh Vazvani. Data curation: Mozhgan Gholizadeh Vazvani. Formal analysis: Mozhgan Gholizadeh Vazvani. Investigation: Mozhgan Gholizadeh Vazvani. Methodology: Hossein Dashti, Roohallah Saberi Riseh, and Mozhgan Gholizadeh Vazvani. Project administration: Roohallah Saberi Riseh and Hossein Dashti. Resources: Mozhgan Gholizadeh Vazvani. Software: Mozhgan Gholizadeh Vazvani. Supervision: Roohallah Saberi Riseh. Validation: Roohallah Saberi Riseh and Hossein Dashti, Visualization: Mozhgan Gholizadeh Vazvani. Writing—original draft: Mozhgan Gholizadeh Vazvani. Writing—review & editing: Roohallah Saberi Riseh, Hossein Dashti, and Mozhgan Gholizadeh Vazvani.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Competing Interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.