Biotic Stressors of Legumes: History
Please note this is an old version of this entry, which may differ significantly from the current revision.
Subjects: Plant Sciences

Leguminous crops such as Arachis hypogaea (groundnut), Glycine max (soybean), Phaseolus vulgaris (common bean), Pisum sativum (common pea), Cicier arietinum (chickpea), Vigna anguiculata (cowpea), Vicia faba (faba bean), Lens culinaris (lentil), Cajanus cajan (pigeon pea), Lupinus spp. (lupin), and Vigna subterranean (bambara bean) contribute to the improvement of ecosystems, nutrition and food security. 

  • legumes
  • stress
  • insect pests

1. Insect Pests

Insect pests attack legume crops by boring, webbing and damaging plant parts such as the leaves, pods, stems and roots [31,32]. In addition to attacking plants, insect pests may also act as vectors for pathogens that negatively impact crop production systems [33]. Insect pests such as aphids [33,34], pod borers [31,35], thrips [36,37] and whiteflies [38,39] have been reported to feed on legume crops, among others. The use of biological enemies of pests, cultural control (crop rotation, mulching, intercropping, etc.), mechanical control (water hosing at high pressure), chemical application and integrated pest management strategies have been recommended for the control of insect pests in legumes [39,40,41,42]. These efforts have been found to be effective in reducing insect severity in legumes [39,43]. However, the insects are constantly adapting to control measures used in production systems [44]. Breeding for tolerance to insect pests is the most sustainable approach and this requires an understanding of the plant’s signal pathways that respond to insect attack [45].
Pathways expressed in rice infested with caterpillars included flavonoids, phenolic acids, amino acids and derivatives. These improved the production of cytosolic calcium ions that signal herbivore attack to the plant [46]. Maize infested with Monolepta hieroglyphica revealed significant up-/down-regulation of metabolites derived from sugar and amino acid pathways that might be responsible for resistance. Similar results were reported in cabbage infested with aphids [47]. Insect–plant metabolomic response of leguminous crops has been conducted for red clover, pea and alfalfa in a composite study with aphid infestation. Triterpene, flavonoid and saponin enriched pathways were found to be responsive to aphid attack [34]. Flavonoids and amino acids have also been found to be significantly enriched in alfalfa infested with thrips [48]. However, limited studies have been conducted on the host-plant metabolomic response of leguminous crops to insects, as well as to other biotic stressors. These studies could have far-reaching impacts on stress biomarker identification with potential benefits in legume improvement programmes.

2. Diseases of Legumes

2.1. Bacterial Diseases

Bacterial diseases of legumes can be categorised into leaf blights, leaf spots/bacterial wilts and other multiple symptoms of sprout rot and dwarfism [49]. Their symptoms are based on the tissues that they infiltrate (leaves, stems and roots) [50]. Legume bacterial diseases are known to cause yield losses of up to 50%, which negatively impacts economic gains and food security [51]. The two plant bacterial pathogens Xanthomonas axonopodis and Pseudomonas syringae are known worldwide for causing bacterial blight [49,52]. Symptoms of infection usually occur on all aerial parts of the plant, and in severe incidences, defoliation and wilting occur [52,53]. Like bacterial blight, another disease that threatens legume production is bacterial wilt, caused by Curtobacterium flaccumfaciens pv. Flaccumfaciens [54]. The pathogen has created new variants that cause damage to legume crops worldwide by causing leaf chlorosis in plants. In fields where the disease occurs, upon plant maturation and shattering of seeds, the infected seed replants itself and allows the pathogen to thrive from generation to generation [54,55]. The control of bacterial diseases has relied on integrated approaches that limit the survival of pathogens. This includes crop rotation and the use of pathogen free certified seed [52]. These measures are only effective to a limited extent, and detecting pathogens in seed is not an easy task for farmers. A promising and more long-term method for the control of bacterial diseases would be the utilisation/breeding of tolerant varieties [56,57].
The evaluation of metabolite profiles in citrus infected with huanlongbing caused by the bacterium ‘Candidatus Liberibacter asiaticus’ reported distinct sugars as well as amino and organic acids expressed in the roots, thus giving insight on resistance [58]. Metabolomic compounds synthesized from flavonoids, amino and phenolic acids act as protective agents in the xylem of oat plants when infected with halo blights caused by P. syringae pv. by repairing the cell wall [59]. Similar metabolomic pathways including phenols and acetates have been reported in tomato infected with bacterial wilt caused by Ralstonia solanacearum [60]. To date, there is little to no information from metabolomic studies on the response of leguminous crops to bacterial disease infection to aid breeders with biomarker discovery.

2.2. Fungal Diseases

The occurrence of fungal diseases in legume production areas is known to cause substantial yield losses of up to 100% [59]. Fungal pathogens can cause infection at any plant growth stage (emergence, seedling, vegetative and reproductive stage) by attacking organs and tissues that are involved in the transportation of water and nutrients [61,62]. Upon infection, these pathogens degrade the plant cell wall, which consequently results in the death of the plant, especially if the variety grown does not have any resistant genes [63]. Root rot caused by Rhizoctonia solaniFusarium solaniFusarium oxysporum and Aphanomyces euteiches and fungal wilt caused by Formae speciales are some of the most destructive fungal diseases that limit the productivity of legume crops worldwide [64]. The pathogen R. solani is considered one of the most destructive fungal pathogens that usually infects the roots and hypocotyl of the plant through penetration of the appressoria [63]. At pre-emergence and post-emergence plant growth stages, R. solani causes symptoms of damping-off, root rot and stem canker [65]. Under greenhouse conditions, the seedling survival of some leguminous crops may be less than 5% [66]. The pathogen may further infect the plant’s fruits in highly humid conditions, thus reducing crop quality and yield [67]. Fusarium spp. are also predominant pathogens that interfere with plant growth by causing damping off and root rot [68]. In African small-scale farms, yield losses of up to 100% caused by the F. solani pathogen in common bean have been reported [69]. In addition, A. euteiches is a soil-borne fungal pathogen that poses a threat to legume production by causing wilting, root rot and consequently yield losses of up to 80% [70,71].
The management of fungal diseases is problematic due to the complexity of these pathogens [72]. Over the years, management has been implemented by integrating conventional methods such as crop rotations, increased greenhouse temperatures, biological enemies and chemical use [73]. The use of fungicides has been a promising avenue for the control of fungal pathogens. However, chemicals used to control pathogens have an immense economic and environmental impact [74]. This has led to the exploration of using biological control measures such as bacterium and fungal strains as environmentally friendly alternatives to control pathogens that attack plants [75]. Trichoderma spp. are widely used strains for the biological control of fungal diseases. Beneficial strains of T. velutinum have been found to be an effective biological control measure that promotes the accumulation of metabolites that are responsible for defence in common bean infected with F. solani. Even though numerous strains have been found to be effective in controlling fungal diseases, legislation in many countries regarding the use of biopesticides and their shelf life is still a challenge [76,77]. The development of disease-resistant cultivars using genomic technologies can aid in improving legume productivity worldwide [54]. Legume metabolomics focussed on breeding for disease resistance can be beneficial to breeding programmes by increasing the availability of resistant genotypes that are released to farmers [78].
The metabolomic profiling of leguminous crops has been conducted in common bean and provided major findings in relation to metabolomic pathways including amino acids, flavonoids, isoflavanoids, purines and proline metabolism, which were shown to promote plants’ potential for defence against Fusarium pathogens [79]. In addition, Mayo-Prieto et al. [80] also reported amino acids, peptides, carbohydrates, flavonoids, lipids, phenols, terpenes and glycosides that were up-/down-regulated as a defence mechanism by the common bean plant against the pathogen R. solani. Similar results have been reported in other leguminous crops including chickpea infected with F. oxysporum, soybean infected with Aspergillus oryzae/Rhizopus oligosporus, pea infected with Dydymella pinodes and R. solani (Table 1) [81,82]. Intensifying the fungal–legume metabolomic research worldwide will aid in understanding the biochemical properties of these leguminous crops in response to disease stress.

2.3. Viral Diseases

Viral pathogens attack many crops, including legumes, by causing the yellowing of leaves, stunting and poor pod setting, which result in poor yields [65]. Major viral diseases causing production losses in legumes belong to the NanoviridaeLuteovridae and Poltyvridae families. These diseases cause the necrosis of plants, and their identification requires molecular techniques. Over the years, the accurate identification of viruses has improved because of an increasing number of available genomic platforms. [49,66]. Viruses attach themselves to specific sites of vectors such as insects (aphids, beetles, etc.) and remain there until transmission to their host occurs [67]. The control of viral diseases is difficult and thus requires adherence to quarantine prescripts, removal of inoculum sources, adjustments of planting dates, intercropping, crop rotation, chemical application aimed at controlling pests (elimination of vectors) and the use of tolerant/resistant genotypes [68].
Utilising metabolomic techniques on the Citrus tristeza virus of Mexican lime Citrus aurantifolia revealed up-/down-regulation of amino acids, alkaloids and phenols during infection, thus signalling pathogen defence when different strains of the virus were utilised [83]. In stems of Amarathus hypochondriacus L. infected with Ageratum enation virus, alkaloids, amino acids, dicarboxylic acids, glutamine and sugars may increase or decrease in concentration as a mechanism to improve overall respiratory metabolism [84]. Studies on the response of leguminous crops to viral disease infection are limited, thus requiring more research in order to fully understand the underlying information relating to metabolites expressed under virus pressure.

3. Parasitic Weeds

Unlike “normal” weeds that disadvantage the plant greatly, parasitic weeds on the other hand extensively extract moisture, nutrients, photosynthates and other resources from the host plant [69]. When parasitic weeds are not controlled, the extraction of resources continues, consequently extinguishing the crop [70]. Roomrape species, Striga gesnerioides and Alectra vogelii are problematic parasitic weeds that cause yield losses in many legume production areas in Sub-Saharan Africa [71]. Biological control [69], intercropping [72], chemical application and cultural practices (timely planting) are recommended for the control of parasitic weeds [73]. However, these are often not successful, and the fight against parasitic weeds lies within breeding for resistance [71,73]. Although breeding for resistance will aid in controlling parasitic weeds, the complexity and low heritability is a challenge that breeders face when breeding for parasitic weed resistance [71,73,74]. Initiatives to use breeding prediction tools such as metabolomic techniques for parasitic weed resistance have been explored in rice to study and dissect S. hermonthica resistance [85]. This study reported the phenylpropanoid pathway, which contributes to the formation of lignin in rice, to be an important pathway that can be utilised for resistance to S. hermonthica. There is a deficit on metabolomic experiments that evaluate the performance of legumes under parasitic weed conditions.

4. Parasitic Nematodes

Legumes are famous for their ability to fix nitrogen by using rhizobium, which is a mutualist bacterium [75]. However, the presence of parasitic nematodes reduces rhizobia activity, which leads to poor nodulation [76]. Parasitic nematodes invade the roots of plants and form an indefinite feeding area, which, in turn, can affect root development, thus leading to poor plant growth [77]. Heterodera and Globodera spp. are root knot and cyst nematodes that affect many crops including legumes, resulting in over 12% yield losses [78]. The presence of parasitic nematodes often leads to infection by other pathogens including fusarium spp.; therefore, the utilisation of sustainable control strategies for other pathogens is essential for legumes [74]. Soybean evaluated under Melodegyne pinodes and Heterodera glycines pressure exhibited phenylpropanoids, cysteine, methionine, alkaloid and tropane pathways that can be attributed to resistance properties of the crop to nematodes [86]. The in-depth exploration of metabolites of other crops including legumes would be beneficial to understanding nematode–crop biological interactions.
Table 1. Summary of metabolomic studies conducted in response to biotic stress in leguminous crops using different platforms such as GC-MS, LC-QqQ-MS, LC-MS, LC-obitrap-MS, UHPLC-MS, 1H NMR and GC-MS/TOF.
Legume Biotic Stress Classification Method Total
C. arietinum Fusarium oxysporum Fungal GC-MS 72 [87]
G. max Aspergillus oryzae/Rhizopus oligosporus Fungal LC-QqQ-MS 489 [88]
Heterodera glycines Nematode GC-MS 20 [86]
M. sativa Thysanoptera spp. Insect LC-MS 772 [48]
Acyrthosiphon pisum Harris Insect LC-Obitrap-MS/UHPLC-MS 107 [34]
P. sativum Acyrthosiphon pisum Harris Insect LC-Obitrap-MS/UHPLC-MS 57 [34]
Didymella pinodes Fungal LC-MS/MS 31 [89]
Rhizoctonia solani Fungal 1H NMR 126 [81]
Didymella pinodes Fungal GC-MS/TOF 39 [82]
P. vulgaris Fusarium solani Fungal UPLC 743 [79]
Trichoderma velutinum/Rhizoctotonia solani Fungal LC-MS 216 [80]
T. pratense Acyrthosiphon pisum Harris Insect LC-Obitrap-MS/UHPLC-MS 103 [34]
V. faba Acyrthosiphon pisum Harris Insect LC-Obitrap-MS/UHPLC-MS 13 [34][1]

This entry is adapted from the peer-reviewed paper 10.3390/plants11131756


  1. Penny Makhumbila; Molemi Rauwane; Hangwani Muedi; Sandiswa Figlan; Metabolome Profiling: A Breeding Prediction Tool for Legume Performance under Biotic Stress Conditions. Plants 2022, 11, 1756, 10.3390/plants11131756.
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