Identification and quantification of allelopathic compounds released during crop residue decomposition and their effects on subsequent crops

Introduction

On one hand, leaving crop residues on the field after harvest is a cornerstone of conservation agriculture it protects soil from erosion, adds organic matter, and feeds microbial communities [1,2] . On the other hand, decomposing residues release a cocktail of organic compounds into the soil, some of which are directly toxic to germinating seeds and young roots [3] . This contradiction sits at the heart of allelopathy research in agricultural systems and remains a practical headache for farmers managing tight crop rotations. Allelopathy refers to the chemical inhibition of one plant species by another through the release of secondary metabolites into the environment [4] . In the context of crop residues, the main classes of allelochemicals include phenolic acids (ferulic, p-coumaric, vanillic, syringic), hydroxamic acids (DIMBOA, DIBOA), terpenoids, and short-chain organic acids [5, 6] . These compounds enter the soil through leaching from residue surfaces, root exudation from living plants, and microbial transformation of residue organic matter. Their concentrations in soil solution depend on residue type, decomposition rate, soil properties, temperature, and moisture [7] . The agronomic consequences can be significant. Wheat residues have been linked to poor emergence of following wheat crops a phenomenon sometimes called "wheat-on-wheat" decline [8] . Maize residues contain hydroxamic acids that inhibit seedling growth of sensitive species like lettuce and clover [9] . Oilseed rape releases glucosinolate breakdown products with documented biofumigant activity [10] . But the literature often treats these residue types separately, making it hard to compare their relative allelopathic potential under the same environmental conditions. Several gaps remain. First, most quantification work has relied on aqueous extraction of residues in the laboratory, which may not reflect the actual concentrations that develop under field decomposition conditions. Second, temporal profiles of allelochemical release are poorly characterized knowing when peak concentrations occur is just as important as knowing what compounds are present. Third, sensitivity data for common successor crops are scattered across different experimental systems, making direct comparisons difficult [11,12] . This research addressed these gaps by decomposing residues from three major European crops under field conditions in southern Germany, collecting soil leachates at four time points over 16 weeks, identifying compounds by HPLC-MS/MS, and testing four receiver species in standardized bioassays. The aim was to build a practical dataset that connects residue source, decomposition timing, chemical identity, and crop sensitivity within a single experimental framework.

Research Area Description

The field experiment was established at the research farm of Munich Institute of Applied Sciences, located 28 km northeast of Munich in Upper Bavaria, Germany (48°14′N, 11°48′E, 489 m above sea level). The site sits on a Haplic Luvisol developed from loess deposits over Tertiary gravel, with a plough layer (0-30 cm) containing 24.3% clay, 41.7% silt, and 34.0% sand. Soil organic carbon was 1.47%, total nitrogen 0.14%, and pH (CaCl₂) 6.3 at the start of the experiment. Mean annual temperature for the region is 8.7°C and mean annual precipitation is 834 mm, with most rainfall concentrated between May and August. The previous crop at the site was spring barley, harvested in July 2021, and the field was left fallow through winter before trial establishment in April 2022.

Materials and Methods

Materials

Crop residues were collected immediately after harvest from commercial fields within 15 km of the research station. Winter wheat straw (cv. Reform) was gathered in August 2021, maize stalks and leaves (cv. Ronaldinio) in October 2021, and oilseed rape stems and pods (cv. Avatar) in July 2021. All residues were air-dried at room temperature, chopped to 2-5 cm fragments, and stored in paper bags at ambient conditions until use. Residue carbon-to-nitrogen ratios were 82.4 for wheat, 54.7 for maize, and 37.2 for oilseed rape, determined by elemental analysis (vario MACRO cube, Elementar, Langenselbold, Germany). The four receiver crop species used in bioassays were lettuce (Lactuca sativa cv. Grise de Morges), winter wheat (Triticum aestivum cv. Julius), maize (Zea mays cv. Colisee), and soybean (Glycine max cv. Sultana), with certified seed obtained from regional suppliers.

Field Experimental Design

The trial followed a randomized complete block design with four replications. Each block contained four plots (3 × 4 m): wheat residue, maize residue, oilseed rape residue, and a bare soil control. Residues were incorporated at 6 t/ha (dry weight basis) by rotary tillage to a depth of 10 cm on 15 April 2022. Ceramic suction cup lysimeters (Ecotech, Bonn, Germany) were installed at 15 cm depth in the center of each plot for soil solution sampling. Leachate was collected under a tension of -60 kPa at 2, 4, 8, and 16 weeks after residue incorporation. Samples were filtered through 0.45 µm membranes, acidified to pH 2 with formic acid, and stored at -20 °C until analysis.

Methods

Allelochemical identification and quantification used an

Agilent 1290 Infinity II HPLC coupled to a 6470 Triple Quadrupole mass spectrometer (Agilent Technologies, Waldbronn, Germany). Separation was on a Zorbax Eclipse Plus C18 column (2.1 × 100 mm, 1.8 µm) with a gradient of 0.1% formic acid in water (A) and acetonitrile (B). Targeted analysis screened for 35 known allelopathic compounds with authentic standards. Quantification used external calibration curves (R² > 0.995 for all analytes). Detection limits ranged from 0.02 to 0.18 mg/L depending on the compound. Bioassays followed OECD Guideline 208 (Terrestrial Plant Test: Seedling Emergence). Filter paper germination tests were conducted in Petri dishes (25 seeds per dish, four replicates per treatment) using soil leachate at natural concentration and three dilutions (75%, 50%, 25%). Germination was scored after 7 days. Seedling root length and shoot length were measured on day 10. Parallel bioassays used synthetic solutions of individual phenolic acids (ferulic, p-coumaric, vanillic, syringic) at 10-500 mg/L to construct dose-response curves.

Seasonal Conditions during the Experiment

Mean air temperature during the 16-week decomposition period (April-August 2022) was 16.8°C, slightly above the 30-year average of 15.4°C. Total precipitation was 391 mm, distributed unevenly: April received only 28 mm, while June had 112 mm. Soil temperature at 10 cm depth ranged from 9.3 °C in mid-April to 22.1 °C in late July. Soil moisture content in the incorporation zone fluctuated between 18.4% and 31.7% (gravimetric). These conditions favored rapid microbial decomposition, particularly from late May onward when both temperature and moisture were high. Statistical analysis used two-way ANOVA (residue type × sampling time) with Tukey's HSD in R version 4.3.2; significance at p<0.05. Table 2 shows germination rates after 7 days of exposure to undiluted 4-week leachates. Lettuce was the most sensitive receiver species, with germination dropping from 89.2% in controls to 54.3% in wheat leachate (39.1% reduction).

Results

Maize was the most tolerant, declining from 93.4% to 76.8-82.1% depending on the leachate source. All three residue leachates produced statistically significant germination reductions in every receiver species compared to controls.

Comprehensive Interpretation

The dose-response relationships in Figure 2 reveal clear species-specific sensitivity thresholds. Lettuce showed measurable inhibition even at 50 mg/L total phenolics and reached 38.7% inhibition at 500 mg/L. Maize tolerated concentrations up to 200 mg/L with minimal effect, only showing clear suppression above 300 mg/L. The non-linear relationship suggests that a threshold concentration must be exceeded before allelopathic effects become biologically meaningful a pattern consistent with the concept of dosedependent phytotoxicity reported in allelopathy literature. The 4-week peak in allelochemical concentration means that timing of successor crop planting relative to residue incorporation is a practical lever farmers can use to reduce interference.

Discussion

The dominance of phenolic acids in decomposing crop residues matches the established literature [5,13] . Ferulic acid, the most abundant compound detected in wheat residues, is a well-characterized allelochemical known to inhibit root cell elongation by interfering with auxin transport and cell wall lignification [14] . The concentrations we measured (up to 387.4 mg/kg in wheat residue) fall within the range reported by Blum and colleagues [15] for field soils under wheat stubble, lending confidence to the ecological relevance of our findings. The sharp temporal profile of allelochemical releasepeaking at 4 weeks and declining substantially by 16 weeks-has direct practical implications. If farmers can delay planting the successor crop by even 6-8 weeks after residue incorporation, they would avoid the worst of the allelopathic window. This approach, however, conflicts with tight cropping calendars common in central European agriculture [16] . An alternative is to choose tolerant successor species. Our data show that maize tolerates residue leachates far better than lettuce or soybean, making it a safer option following heavy residue-producing crops.

The hydroxamic acids DIMBOA and DIBOA from maize residues deserve separate attention. Unlike phenolic acids, which peak later during residue breakdown, hydroxamic acids were already at high concentrations in 2-week leachates and declined rapidly afterward. This pattern reflects their origin as preformed plant defense compounds rather than microbial decomposition products [9,17] . The practical consequence is that the allelopathic risk from maize residues comes early and passes quickly, while wheat residues pose a longer-lasting threat. The species-specific sensitivity observed in bioassays likely reflects differences in detoxification capacity. Maize, which naturally produces hydroxamic acids itself, may possess enzymatic pathways to degrade or tolerate these compounds [18, 19] . Lettuce, a non-grass species without exposure history to cereal allelochemicals, lacks such defenses. This differential sensitivity must be considered when designing crop rotation sequences in conservation tillage systems [20] .

Conclusion

This research identified 23 allelopathic compounds released during the decomposition of wheat, maize, and oilseed rape residues under field conditions in southern Germany. Phenolic acids, led by ferulic acid and p-coumaric acid, were the most abundant compound class across all residue types. Wheat residues produced the highest total phenolic acid load, while maize residues were uniquely rich in hydroxamic acids, and oilseed rape released isothiocyanates not present in cereal residues. The temporal pattern of release proved as important as the chemical identity. Peak allelochemical concentrations occurred at 4 weeks post-incorporation for phenolic acids but at 2 weeks for hydroxamic acids, meaning the window of greatest phytotoxic risk differs between residue sources.

By 16 weeks, concentrations had fallen to near-background levels in all treatments.

Receiver crop sensitivity varied widely. Lettuce experienced the most severe germination suppression (up to 39% reduction), while maize showed strong tolerance even at high allelochemical concentrations. Wheat and soybean fell between these extremes. The dose-response data generated here provide threshold values that crop advisors can use when making planting timing recommendations following heavy residue incorporation. These findings support a practical management approach: matching the choice of successor crop and the planting interval to the specific residue type left on the field. Where tight rotations demand early planting, selecting a tolerant species like maize after wheat residue incorporation can reduce allelopathic losses without requiring residue removal. This approach preserves the soil health benefits of conservation tillage while minimizing the chemical interference that can undercut establishment of the following crop.

References

1. Lal R. Soil carbon sequestration impacts on global climate change and food security. Science. 2004;304(5677):1623-1627.
2. Palm C, Blanco-Canqui H, DeClerck F, et al. Conservation agriculture and ecosystem services: an overview. Agriculture, Ecosystems and Environment. 2014;187:87-105.
3. Inderjit, Weston LA, Duke SO. Challenges, achievements and opportunities in allelopathy research. Journal of Plant Interactions. 2005;1(2):69-81.
4. Rice EL. Allelopathy. 2nd ed. Orlando: Academic Press; 1984.
5. Li ZH, Wang Q, Ruan X, et al. Phenolics and plant allelopathy. Molecules. 2010;15(12):8933-8952.
6. Macías FA, Molinillo JM, Varela RM, Galindo JC. Allelopathy-a natural alternative for weed control. Pest Management Science. 2007;63(4):327-348.
7. Weston LA, Mathesius U. Flavonoids: their structure, biosynthesis and role in the rhizosphere, including allelopathy. Journal of Chemical Ecology. 2013;39(2):283-297.
8. Wu H, Pratley J, Lemerle D, Haig T. Crop cultivars with allelopathic capability. Weed Research. 1999;39(3):171-180.
9. Macias FA, Marin D, Oliveros-Bastidas A, et al. Allelopathy as a new strategy for sustainable ecosystems development. Biological Sciences in Space. 2003;17(1):18-23.
10. Mattner SW, Porter IJ, Gounder RK, et al. Factors that impact on the ability of biofumigants to suppress fungal pathogens and weeds. Crop Protection. 2008;27(8):1165-1173.
11. Tesio F, Ferrero A. Allelopathy, a chance for sustainable weed management. International Journal of Sustainable Development and World Ecology. 2010;17(5):377-389.
12. Farooq M, Jabran K, Cheema ZA, et al. The role of allelopathy in agricultural pest management. Pest Management Science. 2011;67(5):493-506.
13. Einhellig FA. Interactions involving allelopathy in cropping systems. Agronomy Journal. 1996;88(6):886893.
14. Blum U, Gerig TM, Worsham AD, King LD. Modification of allelopathic effects of p-coumaric acid on morning-glory seedling biomass by glucose, methionine, and nitrate. Journal of Chemical Ecology. 1993;19(12):2791-2811.
15. Blum U. Allelopathic interactions involving phenolic acids. Journal of Nematology. 1996;28(3):259-267.
16. Reckling M, Hecker JM, Bergkvist G, et al. A cropping system assessment framework-evaluating effects of introducing legumes into crop rotations. European Journal of Agronomy. 2016;76:186-197.
17. Niemeyer HM. Hydroxamic acids derived from 2hydroxy-2H-1,4-benzoxazin-3(4H)-one: key defense chemicals of cereals. Journal of Agricultural and Food Chemistry. 2009;57(5):1677-1696.
18. Schulz M, Marocco A, Tabaglio V, et al. Benzoxazinoids in rye allelopathy-from discovery to application in sustainable weed control and organic farming. Journal of Chemical Ecology. 2013;39(2):154174.
19. Wouters FC, Blanchette B, Gershenzon J, Vassao DG. Plant defense and herbivore counter-defense: benzoxazinoids and insect herbivores. Phytochemistry Reviews. 2016;15(6):1127-1151.
20. Liebman M, Dyck E. Crop rotation and intercropping strategies for weed management. Ecological Applications. 2003;3(1):92-122.