Open access peer-reviewed chapter

Use of Plant Secondary Metabolites to Reduce Crop Biotic and Abiotic Stresses: A Review

Written By

Ziming Yue, Varsha Singh, Josiane Argenta, Worlanyo Segbefia, Alyssa Miller and Te Ming Tseng

Submitted: 10 March 2022 Reviewed: 17 March 2022 Published: 26 June 2022

DOI: 10.5772/intechopen.104553

From the Edited Volume

Secondary Metabolites - Trends and Reviews

Edited by Ramasamy Vijayakumar and Suresh Selvapuram Sudalaimuthu Raja

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Abstract

Plant secondary metabolites (PSM) are small molecules of organic compounds produced in plant metabolism that have various ecological functions, such as defense against pathogens, herbivores, and neighboring plants. They can also help to reduce abiotic stresses, such as drought, salinity, temperature, and UV. This chapter reviewed the ecological functions of the PSM and how people utilize these metabolites to reduce crop biotic and abiotic stresses in agriculture. Specific topics covered in this review are (1) extraction of PSM from plant parts and its application on crops; (2) screening of crop/cover crop germplasms for high PSM content and with resistance to pathogens, herbivores, and/or neighboring plants; (3) regulation of PSM biosynthesis (including plant hormones and defense activators) to increase plant readiness for defense; (4) transcriptome and genome technology improvements in the last decade leading to valuable tools to characterize differential gene expression and gene composition in a genome, and lineage-specific gene family expansion and contraction. In addition, there is a critical need to understand how the biosynthesis and release of allelochemicals occur. Filling this knowledge gap will help us to improve and encourage sustainable weed control practices in agriculture.

Keywords

  • allelopathy
  • pathogen defense
  • herbivore defense
  • plant defense
  • cover crops
  • sustainable pest management
  • organic farming

1. Introduction

Plant secondary metabolites (PSM) are small organic molecules produced during plant metabolism that can function as a plant defense against herbivores, pathogens, neighboring plants, or environmental stresses [1, 2, 3]. Although proven to be incorrect, PSM [4, 5] used to be defined as (1) the part of metabolites not present in nonplant organisms or as (2) the part of plant metabolites not required for simple growth and development. These outdated PSM definitions still reflected some properties of PSM—they are widespread in the plant kingdom and are beyond the highly conserved primary metabolites, which are required in plant growth and development, such as proteins, carbohydrates, lipids, and nucleic acids. Hence, they represent plant diversity. The description of PSM often starts from the sessile property of terrestrial plants [1, 26], where they cannot flee from the threat or stress from the environment and hence have to develop strategies to defend or reduce the threat or stress. PSM are their strategies.

Environmental factors, such as temperature, salinity, and water, are also called abiotic stresses [7]. The herbivores, pathogens, and neighboring plants are also called biotic stresses. Plant metabolites can be classified into primary metabolites, secondary metabolites, and plant hormones [3]. The defense function of secondary metabolites is often realized by integration with physical structures, such as cell wall, cutin, suberin, wax, and bark. According to Hartman [1], plant secondary metabolites are often lineage-specific and aid plants in interacting with the biotic and abiotic environment. For example, pine trees and mint plants often contain terpenes, peppers often contain capsaicin, and sicklepod contains anthraquinone derivatives for defense. The production of secondary metabolites can be constitutive or induced. Some plant secondary metabolites, such as anthraquinone derivatives, in sicklepod are routinely produced, and they are called constitutive secondary metabolites. The production of secondary metabolites demands a high metabolic cost on the host plant; thus, many of these compounds are not produced in large quantities until after insects have begun to feed. These secondary metabolites are called induced secondary metabolites [7].

The number of secondary metabolites reported is vast, and they have widespread applications. The most prominent application of the plant secondary metabolites is in the pharmaceutical industry, where about 25% of the drugs in use by humans are derived from medicinal plants [8]. The type and concentration(s) of the secondary molecule(s) produced by a plant are determined by the species, genotype, physiology, developmental stage, and environmental factors during its growth [2].

The application of plant secondary metabolites in agriculture is the focus of this chapter. In standard agricultural practices, the species, physiology, and development stages usually follow biological laws, and we cannot do much to change them. The genotype and environmental factors are currently where most work has been focused on in agriculture. According to Hartman [1], the functions of plant secondary metabolites could fall into three categories—(1) defense and competition involving herbivores (arthropods, vertebrates, and invertebrates), pathogens (viruses, bacteria, and fungi), and plants (allelopathy); (2) attraction and stimulation (pollination, seed dispersal, food-plant recognition, oviposition, sequestration, and symbiosis); and, (3) abiotic stresses defense. Compared to other reviews on secondary metabolites, this review chapter focuses on the agricultural applications of plant secondary metabolites, specifically categories (1) and (3).

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2. Secondary metabolites as resources to reduce crop biotic stresses

2.1 Main groups of plant secondary metabolites

PSM are widely spread in the whole plant kingdom. As they are lineage-specific, the total number of PSM is much more than the number of primary metabolites [5]. PSM derive from primary metabolites using a limited number of key pathways. Their functional diversity is gained by adding diverse combination of reactive functional groups [9]. Terpenoids are the largest group of PSM and occur in all plants, including over 22,000 compounds. The simplest terpenoid is isoprene (C5H8), a volatile gas produced during photosynthesis in leaves. Terpenoids are classified into monoterpenoids consisting of two isoprene units, sesquiterpenoids (three units), diterpenoids (four units), and triterpenoids (six units), depending on how many isoprene units are in their structures [7]. Mint plants (Mentha spp.) produce large quantities of the monoterpenoids menthol and menthone stored in glandular trichomes on the epidermis [7]. Pyrethrins are monoterpenoid esters produced by chrysanthemum plants that act as insect neurotoxins (Saxona 1988). Gossypol (Gossypium hirsutum) from cotton is a diterpenoid [7]. The fresh scent of lemon and orange peel results from a class of triterpenoids called limonoids. The active ingredient of neem oil, azadirachtin, is a powerful limonoid isolated from neem trees (Azadirachta indica) [10]. Phenolics are another large group of PSM, which includes a wide variety of defense-related compounds, such as flavonoids, anthocyanins, phytoalexins, tannins, lignin, and furanocoumarins [7]. Flavonoids are one of the largest classes of phenolics. Soybean contains a large amount of isoflavone [7]. Tannins are water-soluble flavonoid polymers produced by plants and stored in vacuoles. Tannins are toxic to insects because they bind to salivary proteins and digestive enzymes, including trypsin and chymotrypsin, resulting in protein inactivation. Alkaloids are a large class of bitter-tasting nitrogenous compounds found in many vascular plants and include caffeine, cocaine, morphine, and nicotine [7]. Capsaicin and related capsaicinoids produced by members of the genus Capsicum are the active components of chili peppers and have their characteristic burning sensation in hot and spicy foods [7]. Anthraquinones are present in different plant families, such as Leguminosae, Polygonaceae, Rubiaceae, Rhamnaceae, Scrophulariaceae, Liliaceae, Verbenaceae, and Valerianaceae [11]. Anthraquinone derivatives from sicklepod (Leguminosae) have been used to repel deer from browsing soybean [12]. Chlorogenic acid (CGA) or caffeoylquinic acid (CQA) exists in all plants [13], suggesting they are among the oldest PSMs.

2.2 PSM as resources to reduce crop biotic and abiotic stresses

Crop biotic stresses come from microbial pathogens, nematodes, insects, and mammalian herbivores. Crop abiotic stresses come from drought, salinity, temperature, ultraviolet, etc. Plant secondary metabolites can help to reduce these stresses. For example, some secondary metabolites containing benzene rings can absorb ultraviolet (UV) light and release the energy in the visible light range as fluorescence to avoid crop damage from UV light.

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3. Use of secondary metabolites to reduce biotic and abiotic stresses

3.1 Extraction of secondary metabolites

Secondary metabolites have a defense function in plants [1, 2]. The simplest way to utilize secondary metabolites for crop protection is to extract the secondary metabolites and apply them to crops for protection against pathogens, insects, and mammalian herbivores.

3.1.1 Secondary metabolites used as a deer repellent

Deer is the primary pest in row crop production in the US. This was first concerned in the 1960s and gradually confirmed by the agricultural community during the following 40 years [14, 15]. The annual loss of row crops in the US was estimated to be up to $4.53 billion [14]. Deer repellent is one of the primary strategies to solve crop deer damage. Among them, deer repellent with putrescent egg solids as active ingredients occurred in the 1990s and still dominates the deer repellent market today. Deer acceptance of food is dependent on the concentration of secondary metabolites present [16]. They usually avoid plants containing high concentrations of terpenes, tannins [17], and gossypol (cotton). Sicklepod (Senna obtusifolia L.) is one of the southern US’s top ten most troublesome weeds [18]. It belongs to the Leguminosae family and is famous for its high concentrations of anthraquinone derivatives [19], another group of secondary metabolites. Anthraquinone was reported as a mammalian animal repellent since the 1940s [20, 21]. To protect soybean damage from deer, deer repellents were developed using sicklepod fruits [12]. After several modifications of the extraction protocol, the sicklepod extract matched the deer repelling efficacy of Liquid Fence® Deer & Rabbit Repellent, a popular commercial deer repellent with putrescent egg solids as active ingredients. Besides the anthraquinone derivatives, some other plant secondary metabolites were used as deer repellents, such as capsaicin in pepper plants, and monoterpenoids menthol and menthone in peppermint (the active ingredients in Deer Out™, a commercial deer repellent).

3.1.2 Secondary metabolites as insecticides

One of the best examples of secondary metabolites used as an insecticide was the development of the popular insecticide bifenthrin. The pyrethrins from chrysanthemum (Chrysanthemum cinerariaefolium) flower extract were used to develop this insecticide. The safety of this product is, however, questionable. Sesbania extracts developed using a similar extraction method were applied on soybean leaves and exposed to soybean loopers in a 40 mm rearing cup for 24 hours. The looper mortality reached 60% in cups containing sesbania extract-treated soybean leaves.

3.2 Germplasm screening for secondary metabolites

3.2.1 Cotton germplasm screening for gossypol

Gossypol is a unique diterpenoid in the cotton genus Gossypium. Cotton germplasm is not as big as soybean and rice, but variations in gossypol content in cotton leaves are still significant. Low gossypol variety suffering heavy insect defoliation was observed (Dr. Saha personal communication). Unlike food crops, genetically modified cotton is not debated so critically, so Bt-based GMO method was adopted early to prevent insect defoliation. Gossypol screening is still a cultivar selection and breeding direction to defend insects and nematodes.

3.2.2 Allelopathic crop screening

Allelopathy is another term introduced to the science of plant ecology to describe the addition of chemical compounds (toxic or nontoxic) from a plant into the environment that affects the germination, growth, health, development, and population biology or behavior of another plant species [22]. Weeds are considered the most severe biotic constraint on crop production, with yield losses ranging from 45 to 95%, depending on environmental conditions and agronomic practices [23].

3.2.2.1 Rice allelopathy

Rice (Oryza sativa) is the most important grain crop cultivated in the world. More than half of the world’s population has rice as their primary food source [24]. Weed infestation is the main reason for rice yield loss. The most common weeds found in rice fields worldwide are Echinochloa species, such as Echinochloa cruss-galli and Echinochloa colona, and weedy rice species (Oryza sativa) [25]. According to Oerke [26], weed species account for more than one-third of the losses in global rice production. Therefore, using integrated pest management (IPM), including the use of allelopathic varieties, can be an important tool to control weed species and manage weed resistance to synthetic herbicides.

A diversity of allelochemical compounds, such as fatty acids, phenolic acids, indoles, steroids, and others were found to be released by different parts of the plants, in root exudates, and rice soil [27]. Yet, rice inhibits weed growth primarily by secreting momilactone B, a diterpene produced from geranylgeranyl diphosphate (GGPP) [28]. It has been shown that momilactones A and B released by allelopathic rice varieties inhibit shoot and root growth of E. crus-galli (Figure 1). Additionally, weed species growing near rice deficient in momilactone biosynthesis produced more biomass when compared to the ones growing near wild-type rice [29].

Figure 1.

Chemical structure of momilactones A and B, allelopathic molecules released by rice plants.

The rice germplasm has a large variation when testing for allelopathy. However, it was found that among the Brazilian and Asian cultivars tested, only about 3–4% showed greater allelopathic potential [30]. Similar results were found when testing allelopathic cultivars able to suppress the growth of weeds, such as E. crus-galli, Cyperus difformis, and several aquatic weeds [31]. Thus, allelopathy is still an area to be investigated since this information can be used to improve rice production.

3.2.2.2 Cotton allelopathy

  1. Weeds are a continuous hazard to agriculture in the United States, costing farmers up to $20 billion each year [32]. Herbicide resistance in weeds influences the long-term effectiveness of weed management practices globally [33]. Pesticide residues in food and the environment, as a result, are a significant public health hazard [34]. The use of weed suppressive traits in crop types, commonly known as allelopathy, is one of the potential weed control techniques in cotton production [35]. Several studies have reported using allelopathic crop varieties in weed management, including rice, wheat, sunflower, and canola [36, 37]. However, there is limited research on the direct allelopathic effect of cotton on weeds. A few research studies have established that cotton produces allelochemicals, which can impede the growth of pigweeds in other investigations [38]. According to preliminary studies on cotton allelopathy [39], cotton root showed significant quantities of four phenolic chemicals, including p-hydroxybenzoic acid, ferulic acid, gallic acid, and vanillin. A greenhouse study was conducted using eleven cotton chromosome substitution (CS) lines for allelopathy screening against Palmer amaranth (Amaranthus palmeri) (PA) [40]. The cotton lines were tested using a modified stair-step assay. Reductions in PA height and chlorophyll concentration were measured for each cotton line. Variations in PA height among the CS lines were more prominent 21 days after establishment. CS-B22sh and T26lo were most effective in reducing Palmer amaranth height; 77 and 68% height reduction, respectively. A multivariate cluster analysis revealed that CS-B22sh and CS-T26lo were clustered in one group, suggesting similar allelopathic potential against Palmer amaranth. Allelochemicals, produced by the allelopathic cotton CS lines, are a potential bioherbicide and a possible alternative to synthetic herbicides.

3.2.2.3 Sweetpotato allelopathy

Sweetpotato [Ipomoea batatas (L.) Lam.] is a nutrition-rich food with high fiber, vitamins, and antioxidants. Weed management is a major concern for sweetpotato producers [41] as weeds result in significant crop yield loss and higher production costs [42]. Being a plant of vine nature, sweetpotato grows close to the soil surface, and hand-weeding is one of the most effective mechanical options for weed management in sweetpotato fields [43]. To maintain and promote crop productivity and reduce labor requirements, chemical herbicides have been widely applied for weed control. However, long-term and large-scale herbicide applications have increased the number of herbicide-resistant weeds, environmental issues, loss of biodiversity, and threats to ecosystem safety [44]. Allelopathy can be a possible strategy for integrated, sustainable, and ecological weed management. Allelopathic properties of sweetpotato have been demonstrated to reduce the growth and development of weeds, such as alfalfa, yellow nutsedge, Palmer amaranth, and Mikania micrantha (Figure 2) [45, 46]. Alfalfa root growth was inhibited by methanol and aqueous extracts from sweetpotato leaves, stems, and roots [47]. Aqueous extracts from sweetpotato leaves or roots reduced the biomass, root and shoot length, and inhibited the germination of Lactuca sativa [42]. Leaf leachates from sweetpotato cultivars, Sinyulmi, Sinhwangmi, Purple, and Jami demonstrated an inhibitory effect on alfalfa [47]. Palmer amaranth growth was inhibited when they were irrigated with water-containing root exudates from different sweetpotato varieties [46].

Figure 2.

Allelochemicals are released by above- and belowground parts of sweetpotato (donor) plants suppressing the surrounding receiver plants.

Some sweetpotato varieties produce several allelochemicals, such as coumarin, chlorogenic acid, caffeic acid, hydroxycinnamic and trans-cinnamic acids [48] which were weed suppressive in rice. In terms of concentration, sweetpotato leaves were found to have the highest concentration of phenolic compounds, followed by stems and roots [47]. The allelopathic effect of sweetpotato on cowpea was reported when cowpea was grown as the following crop on the same field due to the presence of leaf litters and decaying residues of sweetpotato. Allelopathic varieties with the potential to suppress weed growth may be useful for breeding cultivars designed for organic production systems.

3.2.2.4 Sorghum allelopathy

Sorghum [Sorghum bicolor (L.)] is an annual grass belonging to the family Poaceae and subfamily Panicoideae. It originated in Africa and migrated to other continents [49]. Accounting for more than 22% of the world’s sorghum production, the United States leads in the production globally [50]. Sorghum has wide-ranging utilization as food, fodder, technology, and construction [51]. The importance of sorghum is increasing globally due to its high functional value and ability to acclimatize to changing environmental conditions, especially drought [52]. Allelopathic or weed suppressive potential of sorghum has been documented in the past four decades. Several allelochemicals, such as sorgoleone and its analogs (Figure 3), phenolic acids, and their aldehyde derivatives, determine sorghum’s allelopathic potential [53]. The amount of allelochemical production depends on the plant part and age of the sorghum plant, environmental conditions, and the receiver plant. Sorgoleone, a lipophilic secondary metabolite, is the primary allelochemical produced by sorghum which consists of a quinone ring and aliphatic chain [54]. Its analogs contain aliphatic side chains or additional methoxy groups in the ring [55, 56].

Figure 3.

Structures of sorgoleone and dihydrosorgoleone (reduced analog).

Phenolic acids (Figure 4) with phytotoxic activities, such as gallic, syringic, p-hydroxybenzoic, benzoic, vanillic, p-coumaric, and benzoic acids are also produced by sorghum [57]. However, the amount of production of these compounds depends on the type of cultivar [58] and the development stage of the sorghum plant [59].

Figure 4.

Chemical structure of allelopathic phenolic compounds.

Weed suppressing potential of sorghum on several weed species has been explored by using it as a cover crop, intercrop, crop rotation, sorghum water extract, soil incorporation of sorghum residue, and allele-herbicides derived from sorghum [60, 61]. Sorghum extracts can be combined with lower herbicide doses to effectively manage the weeds and reduce the overall herbicide introduction into the environment. Sorghum residues combined with 50% of the labeled rate of trifluralin were effective in preventing yield loss in broad beans [62]. Aqueous extracts from Brassica–sunflower–sorghum reduced weed biomass of several species, such as Purple nutsedge, bermudagrass, crowfoot grass, horse purslane, field bindweed, jungle rice, and goosegrass. The extent of suppression was comparable with the full rate of atrazine or S-metolachlor with half rate of atrazine [63]. Sorghum water extract combined with a reduced rate of herbicides such as isoproturon and metsulfuron-methyl demonstrated similar weed control as the full rate of these herbicides in the wheat field [64, 65]. A combination of water extracts from sunflower, rice, and sorghum can reduce the rates by 27–67% for herbicides such as ethoxysulfuron, butachlor, and pretilachlor in rice fields [66]. The utilization of allelopathy in agriculture can be a more sustainable and cost-effective strategy for weed management.

3.2.2.5 Allelopathic cover crops

The method of using cover crops in agricultural fields has been a widespread practice among a broad range of farms. Cover crops are crops that are grown prior to harvested crops to help increase the potential of the harvested crops [67]. In agricultural systems, the practice of using cover crops is shown to improve the quality of the soil by virtue of incorporating crop residues (organic matter) [68], Using a cover crop approach can also be beneficial via enhanced hydro-availability, decrease evaporation from the soil, as well as escalate the biodiversity of the soil.

An additionally impactful use for using the cover crop method in agricultural systems is its ability to suppress weeds due to either physical biomass of the terminated cover crop essentially smothering the weedy plants, physical shading of the cover crop causing inhibition of sunlight to the weeds, as well as via the production of allelochemicals from the cover crop. Allelochemicals are the product of allelopathy, which is positive or negative impact of one plant (the allelopathic plant) on another plant. Allelochemicals can increase or decrease the nutrient availability to surrounding plants by virtue of the symbiotic microbes [69]. It is appropriately thought that the use of cover crops with allelopathic properties in an agricultural field can have positively novel effects on the growth, ability to thrive, and production yields of so-called “cash crops”.

During a study in a semiarid area of Texas, USA, during a 3-year period, cotton that was cultivated following cover crop termination showed a shorter plant height and seed and lint yields. Simultaneously, the plant density did not affect the cover crops. Benzoxaziones concentrations in the soil were 2 to 3-fold higher under the cover crop treatments than in the fallow (control) plot. Though allelopathy may not be the only factor to cause these findings, it is likely to have played a significant role [70].

During a study on non-chemical weed suppression in vegetable fields, it was shown that there was a correlation between the quantity of cover crop biomass with the level of weed suppression (Figures 5 and 6). An 8 t ha−1 or greater cover crop biomass is possibly a significant enough level to have sufficient weed suppression [71]. Although this level of weed suppression may not have everything to do with allelopathy from the cover crops, it certainly played a critical role [72].

Figure 5.

Effects of various cereal cover crops in different vegetable production systems on the dry biomass production (g m−2) of weed species at the time of cover crop termination in 2005 (gray bars) and 2006 (white bars). Vertical lines represent standard errors of the means (p < 0.05).

Figure 6.

Effects of various legume cover crops in different vegetable production systems on the dry biomass production (g m−2) of weed species at the time of cover crop termination in 2005 (gray bars) and 2006 (white bars). Vertical lines represent standard errors of the means (p < 0.05).

In a study focused on weed germination and the growth of IdaGold mustard, a seed germination bioassay technique was used. Phenol (allelochemical) concentrations were measured during this study. The total concentration of phenols in the soil was negatively correlated with the level of weed germination (Figure 7). Also, there were low concentrations of phenol in the soil that contained live microbes (<20 ng). Additionally, the germination rates were lower when compared to a nonmicrobe-containing soil with the same concentrations of phenol [73].

Figure 7.

Germination is inhibited by high concentrations of soil phenols.

Numerous studies have demonstrated the weed suppressive property of allelopathic cover crops, which is a piece of good news for farmers [74]. There is a need for more research on the possible positive growth effects of allelopathic cover crops on the cash crops’ ability to thrive.

3.3 Secondary metabolites biosynthesis regulation

While PSMs have a constitutive part, i.e., routinely produced, they are also induced. This is mainly reflected in pathogen-induced resistance (including PSM production) and herbivore-induced resistance (including PSM production) [75]. The former can be traced back to 120 years ago, while the latter be traced back to 50 years ago. Recently it was realized that both were similar in nature and were controlled by plant hormones, salicylic acid, and jasmonic acid, respectively [75].

Another group of PSMs, allelochemicals, is generally thought of as constitutive, i.e., routinely produced. Compared to PSM induced by pathogens and herbivores, allelochemical induction is a big gap in our knowledge, although the study of allelopathy can be traced back 90 years ago. A primary reason for the difference is that for pathogen/herbivore-induced PSM production, the PSM may (or may not) need activation upon induction (they do not need to be expelled out of the plant body to defend), while in allelopathy, the PSM needs to be expelled out of the plant body to be effective. Sporadic information on the induction of root exudation exists in the literature; for example, Dineli et al. [76] studied the translocation and root exudation of herbicide after foliar treatment of wheat and ryegrass using 14C-labeled diclofop-methyl and triasulfuron. The results showed the presence of untreated plants (wheat or ryegrass) in the same pot as triasulfuron-treated ryegrass or wheat induced the exudation of the herbicide 7 to 32 times more. In the case of diclofop, the induced root exudation of the herbicide was 3 to 6 times more in the presence of untreated wheat or ryegrass. The root exudated herbicides suppressed the adjacent plants, indicating a form of allelopathy. This study demonstrated that the presence of adjacent plants induces the release of allelopathic compounds. An immediate question following this case study is—could the biosynthesis of allelopathic compounds (PSM) be induced? If so, how were the signals transmitted during these processes, including the release of the compounds?

As we reviewed previously, PSMs are biopesticides widely used in agriculture. As the PSM are lineage-specific, the selection of a specific crop cultivar or cover crop is similar to selecting what kind of biopesticides to use. Similarly, understanding and application of PSM induction is the dose control of the selected biopesticides. Furthermore, in the pathogen and herbivore-induced resistance (expressed as PSM), the resistance was often called systematic acquired resistance, meaning the resistance was expressed as normal PSM for toxicity and included thickening of cell wall lignin, etc. Hence such systemic acquired resistance is more effective and lasts longer than toxic PSM increase. In this context, filling the knowledge gap of induction of allelopathic compound biosynthesis and release is similar to understanding the dose control of bioherbicide.

3.3.1 Use of plant hormones to regulate secondary metabolite biosynthesis

Generally, it has been accepted that salicylic acid (SA) and jasmonic acid (JA) or methyl jasmonate (MeJA) are recognized plant hormones specialized for defense. These defense hormones have been used to induce PSM production to defend pathogens and herbivores in agricultural studies [77]. This method has not been used in allelopathy.

3.3.2 Use of plant extracts to induce secondary metabolites production

A field study looked at the deer and insect repelling efficacy of coffee senna extract on soybean [12]. After 40 days, the soybean leaf holes were significantly lower than the control or other treatments. This was in contrast to the leaf disc assay results, where soybean loopers were exposed to both coffee senna and sesbania extracts for 24 hours. The soybean looper mortality for sesbania extract was higher than that of coffee senna. A possible explanation for the difference between the field and leaf disc results is that leaf disc experiments used detached leaves. In contrast, field experiments used living soybean plants where the coffee senna extract might have induced defense response in soybean plants. The active ingredient of coffee senna extract may be SA and JA, or a new type of defense response inducer, which is to be determined.

3.3.3 Other chemicals for crop defense activation

Besides plant hormones and plant extracts, some inorganic chemicals have also been used as crop defense activators. Juric et al. [78] reported that Ca2+ and Cu2+ increased secondary metabolites contents in lettuce. Such chemical crop activator is much less toxic for humans and their defense effects last much longer than insecticides or fungicides, hence they are more preferable to the agriculture community.

3.4 Use of transcriptomic and genomic tools to employ secondary metabolites to reduce crop stresses

During the past ten years, the transcriptome was widely used to study the gene expression of secondary metabolites [79]. While plant secondary metabolites are thought to be the readouts of plant defense activation, usually PSM quantity increase can be detected around 20 days or more after treatment (defense activation). PSM increase can be detected from several hours to 40 hours by transcriptome analysis (qPCR). Senna tora is a medicinal plant in Asia, and it is also a close relative to the weed sicklepod (Senna obtusifolia) in the US. Both sicklepod and Senna tora fruits contain high contents of anthraquinone secondary metabolites. Kang et al. [80] used differential expression analysis and showed that the expression level of genes involved in the anthraquinone biosynthetic pathway regulates differently depending on the degree of tissues and seeds development.

With improvements in sequencing technology, the sequencing cost has plunged during the past decades. Crop or cultivar genome is not far from being available. One discovery with the available genome sequences is that plants devote a significant amount of their genes to secondary metabolites, implying plant ecological functions are equivalent to its growth and development. Kang et al. [80] sequenced the genome of S. tora, and found that the CHS-L gene family expanded most notably in S. tora. This might explain in part why S. tora was rich in anthraquinones.

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4. Conclusions

Compared to the estimated number of primary metabolites of 10,000, PSMs are estimated to be more than 200,000 in the plant kingdom. These PSMs function in various ecological roles, including defending pathogens, herbivores, and neighboring plants. Use of these PSM in agriculture includes (1) extraction of the PSM and applying it directly to the crop to reduce biotic stresses, (2) use of PSM in vivo/in situ by screening crop cultivars with desired PSM profiles to achieve better resistance to pests, (3) use of PSM biosynthesis regulation or plant defense activators to achieve defense readiness, (4) filling the knowledge gap on allelochemical induction, biosynthesis, and release, as it will be helpful in improving weed management practices in agriculture, and (5) employing transcriptomic and genomic tools to understand PSM biosynthesis and pathways.

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Acknowledgments

The authors appreciate the funding from the Mississippi Soybean Promotion Board (MSPB) and Cotton Incorporated. This work is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch project under accession number 230100, and is a contribution of the Mississippi Agricultural and Forestry Experiment Station.

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Conflict of interest

The authors declare that this work was presented in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. 1. Hartmann T. From waste products to ecochemicals: Fifty years research of plant secondary metabolism. Phytochemistry. 2007;68:2831-2846
  2. 2. Isah T. Stress and defense responses in plant secondary metabolites production. Biological Research. 2019;52:39
  3. 3. Matthias E, Kliebenstein DJ. Plant secondary metabolites as defenses, regulators, and primary metabolites: The blurred functional trichotomy. Plant Physiology. 2020;184(1):39-52
  4. 4. Fraenkel GS. The raison d’Etre of secondary plant substances: These odd chemicals arose as a means of protecting plants from insects and now guide insects to food. Science. 1959;129:1466-1470
  5. 5. Pichersky E, Lewinsohn E. Convergent evolution in plant specialized metabolism. Annual Review of Plant Biology. 2011;62:549-566
  6. 6. Hartmann T. Plant-derived secondary metabolites as defensive chemicals in herbivorous insects: A case study in chemical ecology. Planta. 2004;219:1-4
  7. 7. Freeman BC, Beattie GA. An Overview of Plant Defenses against Pathogens and Herbivores. The Plant Health Instructor. 2008. DOI: 10.1094/PHI-I-2008-0226-01
  8. 8. De Luca V, Salim V, Atsumi SM, Yu F. Mining the biodiversity of plants: A revolution in the making. Science. 2012;336:1658-1661
  9. 9. Wink M. Evolution of secondary plant metabolism. In: Wiley, Encyclopedia of Life Sciences. Chichester: Wiley; 2016. DOI: 10.1002/9780470015902.a0001922.pub3
  10. 10. Saxena RC. Insecticides from neem. In: Anason JT, Philogene MP, editors. Insecticides of Management. Boca Raton: Lewis Publishers; 1988
  11. 11. Han Y-S, van der Heijden R, Verpoorte R. Biosynthesis of anthraquinones in cell cultures of the rubiaceae. Plant Cell Tissue and Organ Culture. 2001;67:201-220
  12. 12. Yue Z, Tseng TM, Lashley M. Characterization and deer-repellent property of chrysophanol and emodin from sicklepod weed. American Journal of Plant Sciences. 2018;9:266-280
  13. 13. Constabel CP. A survey of herbivore-inducible defensive proteins and phytochemicals. In: Agrawal AA, Tuzun S, Bent E, editors. Induced Plant Defenses against Pathogens and Herbivores. St. Paul: APS Press; 2000. pp. 137-166
  14. 14. Conover MR. Resolving human-wildlife conflicts: The science of wildlife damage behavior in aquatic environments. ACS Symposium Series. 2002;991:3-25
  15. 15. Flyger VF, Thoerig T. Crop damage caused by Maryland deer. In: Proceedings Annual Conference, Southeastern Association of Game and Fish Commissioners. 1962;16:45-52
  16. 16. Wagner KK, Nolte DL. Comparison of active ingredients and delivery systems in deer repellents. Wildlife Society Bulletin. 2001;29
  17. 17. Nolte DL, Kimball BA, Perry KR, Villalba JJ, Provenza FD. Effects of forage nutritional quality (energy and protein) on deer acceptance of foods containing secondary metabolites. USDA National Wildlife Research Center - Staff Publications; 2004. p. 374. https://digitalcommons.unl.edu/icwdm_usdanwrc/374
  18. 18. Webster TM et al. Weed survey-southern states. Proceedings, Southern Weed Science Society. 2013;66:275-287
  19. 19. Crawford L, McDonald GM, Friedman M. Composition of Sicklepod (Cassia obtusifolia) Toxic Weed Seeds. Journal of Agriculture and Food Chemistry. 1990;38:2169-2175
  20. 20. Avery ML, Humphrey JS, Decker DG. Feeding deterrence of anthraquinone, anthracene, and anthrone to rice-eating birds. Journal of Wildlife Management. 1997;61:1359-1365
  21. 21. Deliberto ST, Werner SJ. Review of anthraquinone applications for pest management and agricultural crop protection. Pest Management Science. 2016;72:1813-1825
  22. 22. Qasem JR, Foy CL. Weed allelopathy, its ecological impacts and future prospects. Journal of Crop Production. 2001;4(2):43-119
  23. 23. Scavo A, Mauromicale G. Crop allelopathy for sustainable weed management in agroecosystems: Knowing the present with a view to the future. Agronomy. 2021;11:2104
  24. 24. Muthayya S, Sugimoto JD, Montgomery S, Maberly GF. An overview of global rice production, supply, trade, and consumption. Annals of the New York Academy of Sciences. 2014;1324(1):7-14
  25. 25. Kraehmer H, Jabran K, Mennan H, Chauhan BS. Global distribution of rice weeds–a review. Crop Protection. 2016;80:73-86
  26. 26. Oerke EC. Crop losses to pests. The Journal of Agricultural Science. 2006;144(1):31-43
  27. 27. Khanh TD, Xuan TD, Chung IM. Rice allelopathy and the possibility for weed management. Annals of Applied Biology. 2007a;151(3):325-339
  28. 28. Serra Serra N, Shanmuganathan R, Becker C. Allelopathy in rice: A story of momilactones, kin recognition, and weed management. Journal of Experimental Botany. 2021;72(11):4022-4037
  29. 29. Xu M, Galhano R, Wiemann P, Bueno E, Tiernan M, Wu W, et al. Genetic evidence for natural product-mediated plant–plant allelopathy in rice (Oryza sativa). New Phytologist. 2012;193(3):570-575
  30. 30. Olofsdotter M, Jensen LB, Courtois B. Improving crop competitive ability using allelopathy—an example from rice. Plant Breeding. 2002;121(1):1-9
  31. 31. Belz RG. Allelopathy in crop/weed interactions—An update. Pest Management Science: Formerly Pesticide Science. 2007;63(4):308-326
  32. 32. Basu C, Halfhill MD, Mueller TC, Stewart CN Jr. Weed genomics: New tools to understand weed biology. Trends in Plant Science. 2004;9(8):391-398
  33. 33. Gage KL, Krausz RF, Walters SA. Emerging challenges for weed management in herbicide-resistant crops. Agriculture. 2019;9(8):180
  34. 34. Riyaz M, Shah RA, Sivasankaran K. Pesticide Residues: Impacts on Fauna and the Environment. IntechOpen; 2021
  35. 35. Jabran K, Mahajan G, Sardana V, Chauhan BS. Allelopathy for weed control in agricultural systems. Crop Protection. 2015;72:57-65
  36. 36. Alsaadawi IS, Sarbout AK, Al-Shamma LM. Differential allelopathic potential of sunflower (Helianthus annuus L.) genotypes on weeds and wheat (Triticum aestivum L.) crop. Archives of Agronomy and Soil Science. 2012;58(10):1139-1148
  37. 37. Kong CH, Chen XH, Hu F, Zhang SZ. Breeding of commercially acceptable allelopathic rice cultivars in China. Pest Management Science. 2011;67(9):1100-1106
  38. 38. Hoffman ML, Weston LA, Snyder JC, Regnier EE. Separating the effects of sorghum (Sorghum bicolor) and rye (Secale cereale) root and shoot residues on weed development. Weed Science. 1996;1996:402-407
  39. 39. Chen ZJ, Sreedasyam A, Ando A, et al. Genomic diversifications of five Gossypium allopolyploid species and their impact on cotton improvement. Nature Genetics. 2020;52:525-533
  40. 40. Fuller GA, Saha S, Stelly DM, Jenkin J, Tseng TM. Assessing the weed-suppressing potential of cotton chromosome substitution lines using the stair-step assay. Plants. 2021;10(11):2450
  41. 41. Nwosisi S, Nandwani D, Hui D. Mulch treatment effect on weed biomass and yields of organic sweetpotato cultivars. Agronomy. 2019;9(4):190
  42. 42. Shen S, Xu G, Li D, Clements DR, Jin G, Liu S, et al. Allelopathic potential of sweet potato (Ipomoea batatas) germplasm resources of Yunnan Province in southwest China. Acta Ecologica Sinica. 2018;38(6):444-449
  43. 43. Treadwell DD, Creamer NG, Schultheis JR, Hoyt GD. Cover crop management affects weeds and yield in organically managed sweetpotato systems. Weed Technology. 2007;21(4):1039-1048
  44. 44. Norsworthy JK, Ward SM, Shaw DR, Llewellyn RS, Nichols RL, Webster TM, et al. Reducing the risks of herbicide resistance: Best management practices and recommendations. Weed Science. 2012;60(SP1):31-62
  45. 45. Harrison HF, Peterson JK. Allelopathic effects of sweet potatoes (Ipomoea batatas) on yellow nutsedge (Cyperus esculentus) and alfalfa (Medicago sativa). Weed Science. 1986;34(4):623-627
  46. 46. Varsha V, Werle IS, Shankle MW, Tseng TM. Allelopathic effects of sweetpotato varieties on palmer amaranth growth. Proceedings of Southern Weed Science Society. 2021;74:18
  47. 47. Chon SU, Boo HO. Difference in allelopathic potential as influenced by root periderm colour of sweet potato (Ipomoea batatas). Journal of Agronomy and Crop Science. 2005;191(1):75-80
  48. 48. Soni B, Tseng TMP, Yue Z. Identification and quantification of allelochemicals from selected sweet potato (Ipomoea batatas (L.) lam.) cultivars. American Journal of Plant Sciences. 2019;10(12):2354
  49. 49. Sène M, Gallet C, Doré T. Phenolic compounds in a Sahelian sorghum (Sorghum bicolor) genotype (CE145-66) and associated soils. Journal of Chemical Ecology. 2001;27(1):81-92
  50. 50. Głąb L, Sowiński J, Bough R, Dayan FE. Allelopathic potential of sorghum (Sorghum bicolor (L.) Moench) in weed control: A comprehensive review. Advances in Agronomy. 2017;145:43-95
  51. 51. Sowiński J, Szydełko-Rabska E. Comparison of sorghum type yielding in Polish conditions. Annales Universitatis Mariae Curie-Skłodowska. Agricultura. 2013;68(1):30-40
  52. 52. Sowiński J, Liszka-Podkowa A. Fresh and dry matter yield quantity and quality of maize (Zea mays L.) and sweet sorghum (Sorghum bicolor (L.) Moench.) on sandy soil depending on nitrogen fertilization. Acta Scientiarum Polonorum Agricultura. 2008
  53. 53. Czarnota MA, Paul RN, Weston LA, Duke SO. Anatomy of sorgoleone-secreting root hairs of Sorghum species. International Journal of Plant Sciences. 2003;164(6):861-866
  54. 54. Netzly DH, Butler LG. Roots of sorghum exude hydrophobic droplets containing biologically active components 1. Crop Science. 1986;26(4):775-778
  55. 55. Dayan FE, Duke SO. Trichomes and root hairs: Natural pesticide factories. Pesticide Outlook. 2003;14(4):175-178
  56. 56. Kagan IA, Rimando AM, Dayan FE. Chromatographic separation and in vitro activity of sorgoleone congeners from the roots of Sorghum bicolor. Journal of Agricultural and Food Chemistry. 2003;51(26):7589-7595
  57. 57. Al-tawaha ARM, Nidal ODAT. Use of sorghum and maize allelopathic properties to inhibit germination and growth of wild barley (Hordeum spontaneum). Notulae Botanicae Horti Agrobotanici Cluj-Napoca. 2010;38(3):124-127
  58. 58. Cheema ZA, Khaliq A, Abbas M, Farooq M. Allelopathic potential of sorghum (Sorghum bicolor L. Moench) cultivars for weed management. Allelopathy Journal. 2007;20(1):167
  59. 59. Won OJ, Uddin MR, Park KW, Pyon JY, Park SU. Phenolic compounds in sorghum leaf extracts and their effects on weed control. Allelopathy Journal. 2013;31(1):147
  60. 60. Alsaadawi IS, Dayan FE. Potentials and prospects of sorghum allelopathy in agroecosystems. Allelopathy Journal. 2009;24(2)
  61. 61. Cheema ZA, Farooq M, Khaliq A. Application of allelopathy in crop production: Success story from Pakistan. In: Allelopathy. Berlin, Heidelberg: Springer; 2013. pp. 113-143
  62. 62. Alsaadawi IS, Khaliq A, Lahmod NR, Matloob A. Weed management in broad bean (Vicia faba L.) through allelopathic Sorghum bicolor (L.) Moench residues and reduced rate of a pre-plant herbicide. Allelopathy Journal. 2013;32(2)
  63. 63. Mahmood A, Khaliq A, Ihsan MZ, Naeem M, Daur I, Matloob A, et al. Estimation of weed dry biomass and grain yield as a function of growth and yield traits under allelopathic weed management in maize. Planta Daninha. 2015;33:23-31
  64. 64. Jamil MU, Ata ZAHID, Khaliq ABDUL. Increasing the efficiency of sorghum water extract (sorgaab) by mixing with lower doses of isoproturon to control weeds in wheat. International Journal of Agricultural Biology. 2005;7(8):712-718
  65. 65. Sharif MM, Cheema ZA, Khaliq A. Reducing herbicide dose in combination with sorghum water extract for weed control in wheat (Triticum aestivum L.). International Journal of Agricultural Biology. 2005;7(4):560-563
  66. 66. Rehman A, Cheema ZA, Khaliq A, Arshad M, Mohsan S. Application of sorghum, sunflower and rice water extract combinations helps in reducing herbicide dose for weed management in rice. International Journal of Agricultural Biology. 2010;12(6):901-906
  67. 67. Stratton, Anne Elise, Comin, Jucinei José, Siddique, Ilyas, Zak, Donald R., Dambroz Filipini, Letícia, Rodrigues Lucas, Blesh, Jennifer, 2021, Assessing Cover Crop and Intercrop Performance Along a Farm Management Gradient. SSRN Available from: https://ssrn.com/abstract=3964460 or http://dx.doi.org/10.2139/ssrn.3964460
  68. 68. Dias T, Dukes A, Antunes PM. Accounting for soil biotic effects on soil health and crop productivity in the design of crop rotations. Journal of the Science of Food and Agriculture. 2014;95:447-454
  69. 69. Ana Luisa A. Allelopathy as a tool in the management of biotic resources in agroecosystems. Critical Reviews in Plant Sciences. 1999;18(6):697-739
  70. 70. Li Y, Allen VG, Chen J, Hou F, Brown CP, Green P. Allelopathic influence of a wheat or rye cover crop on growth and yield of no-till cotton. Agronomy Journal. 2013;105:1581-1587
  71. 71. Mirsky SB, Ryan MR, Teasdale JR, Curran WS, Reberg-Horton CS, Spargo JT, et al. Overcoming weed management challenges in cover crop–based organic rotational no-till soybean production in the eastern United States. Weed Technology. 2013;27:193-203
  72. 72. Mennan H, Jabran K, Zandstra BH, Pala F. Non-chemical weed management in vegetables by using cover crops: A review. Agronomy. 2020;2:257
  73. 73. Lou Y, Davis AS, Yannarell AC. Interactions between allelochemicals and the microbial community affect weed suppression following cover crop residue incorporation into soil. Plant Soil. 2016;399:357-371
  74. 74. Sturm DJ, Peteinatos G, Gerhards R. Contribution of allelopathic effects to the overall weed suppression by different cover crops. Weed Research. 2018;58(5):331-337
  75. 75. Kaeban R, Kuc J. Induced resistance against pathogen and herbivore: An overview. In: Agrawal AA, Tuzun S, Bent E, editors. Induced Plant Defenses against Pathogens and Herbivores: Biochemistry, Ecology and Agriculture. St. Paul, MN, USA: APS Press; 2000
  76. 76. Dinelli G, Bonetti A, Marottii M, Busi S, Catizone P. Root exudation of diclofop-methyl and triasulfuron from foliar-treated durum wheat and ryegrass. Weed Research. 2007;47:25-33
  77. 77. Beyer SF, Bel PS, Flors V, et al. Disclosure of salicylic acid and jasmonic acid-responsive genes provides a molecular tool for deciphering stress responses in soybean. Scientific Reports. 2021;11:20600
  78. 78. Jurić S, Stracenski SK, Król-Kilińska Ż, Žutić I, Uher SF, Đermić E, et al. The enhancement of plant secondary metabolites content in Lactuca sativa L. by encapsulated bioactive agents. Scientific Reports. 2020;10:3737. DOI: 10.1038/s41598-020-60690-3
  79. 79. Kang S-H, Lee W-H, Lee C-M, Sim J-S, Won SY, Han S-R, et al. De novo transcriptome sequence of Senna tora provides insights into anthraquinone biosynthesis. PLoS ONE. 2020b;15(5):e0225564
  80. 80. Kang SH, Pandey RP, Lee CM, et al. Genome-enabled discovery of anthraquinone biosynthesis in Senna tora. Nature Communications. 2020a;11:5875

Written By

Ziming Yue, Varsha Singh, Josiane Argenta, Worlanyo Segbefia, Alyssa Miller and Te Ming Tseng

Submitted: 10 March 2022 Reviewed: 17 March 2022 Published: 26 June 2022