Abstract
Given their long-lasting seed viability, 15–20-year lifespan and their high seed production levels, a significant impact of parasitic plant Striga spp. on African food production is inevitable. Over the last decades, climate change has increasingly favoured the adaptability, spread and virulence of major Striga species, S. hermonthica and S. asiatica, across arable land in Sub-Saharan Africa (SSA). These parasitic weeds are causing important yield losses on several staple food crops and endangering food and nutritional security in many SSA countries. Losses caused by Striga spp. are amplified by low soil fertility and recurrent droughts. The impact of Striga parasitism has been characterized through different phenotypic and genotypic traits assessment of their host plants. Among all control strategies, host-plant resistance remains the most pro-poor, easy-to-adopt, sustainable and eco-friendly control strategy against Striga parasitism. This review highlights the impact of Striga parasitism on food security in SSA and reports recent results related to the genetic basis of different agronomic, pheno-physiological and biochemical traits associated with the resistance to Striga in major African cereal food crops.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
1 Introduction
Africa south of the Sahara (sub-Saharan Africa, SSA) is extremely sensitive to food crises. In this region, agri-food production per capita has remained stagnant over the past decades. The high growth rate in SSA could, also, result in limited access to sufficient food from staple food crops (Giller, 2020; Van Ittersum et al., 2016). In such a fragile agri-food system, producing locally and sustainably is becoming central to building a sustainable African agri-food production systems and meeting food and nutritional security. Such a strategy however is challenged by multiple biotic constraints and abiotic stresses, which results in massive crop yield losses (Setimela et al., 2018). Several previous studies have reported that biotic constraints (i.e., diseases, pests, and parasitic weeds) caused about 30% crop yield loss worldwide (Savary et al., 2019). Striga spp. parasitism is considered as one of the most devastating agriculture problems across SSA countries. Over 50% of the arable land under cereals in these countries is infested by Striga spp. (Gressel et al., 2004; Rodenburg et al., 2016). Striga hermonthica (Benth.), S. asiatica (L.) Kuntze, S. forbessii (Benth.) and S. aspera (Willd.) Benth, were reported to parasitize and cause important yield losses on maize (Zea mays L.) (Nyakurwa et al., 2018), sorghum (Sorghum bicolor L.) (Gurney et al., 2002), finger millet (Eleusine coracana L.) (Nyongesa et al., 2018), pearl millet (Pennisetum glaucum L.) (Wilson et al., 2004), and rice (Oryza sativa L.) (Fig. 1), resulting in an increased food insecurity (Adewale et al., 2020; Rodenburg et al., 2016). With climate change and the ever-increasing new contaminated areas and infestation level, the negative effect of these parasitic weeds on crop production will become more pronounced. The long-term impact of these parasitic weeds is especially high because of their persistent seeds in soils and strong dispersal ability to uninfested fields.
Numerous studies indicated that under highly infested fields (Fig. 1) Striga parasitism can destroy the crop resulting in 100% yield loss (Nyakurwa et al., 2018; Pfunye et al., 2021; Yacoubou et al., 2021). Almost half century ago (1940s), Striga research began and since, many research national and international institutions gave more interest in conducting research activities on all aspects related to Striga management including agronomy, metabolomics, physiology, genomics and crop improvement. This resulted in generating a total number of 2 527 research article reported in the Web of Science and Scopus out of which, 320 were related to all aspects of genetics, breeding, and resistance mechanisms (Figs. 2 and 3).
Economically, maize grain yield losses caused by Striga are estimated to exceed 2.1 million tonnes representing US$ 7 billion (Gasura et al., 2021; Nyakurwa et al., 2018). In sorghum and millet, annual yield losses due to Striga parasitism were estimated to 8.6 million tons (Ejeta, 2007; Mallu et al., 2021). In rice, 300 thousand to half a million tons of grain yield is lost due to Striga infestation which is equivalent to US$ 117–200 million annually (Gressel et al., 2004; Rodenburg et al., 2016; Mwangangi et al., 2021). In Eastern and Northern Zimbabwe, Striga spp. affects 75.7% of farmers’ cereal fields costing about US$100 million annually (Mandumbu et al., 2019). In Nigeria’s Northern Guinea Savanna, and Kenya, sorghum production in Striga-infested fields decreased by more than 50% (Runo, 2019). In the whole West Africa, Striga infestation has a considerable economic impact on both maize and rice production, threatening the food security and livelihoods of millions of resource-poor farmers and consumers (Rodenburg et al., 2016). Failing to set up a long-term sustainable strategy for Striga management could lead to yield losses equivalent to US$ 30 million a year for each concerned country (Rodenburg et al., 2016).
The level of infestation as well as the parasitism impact on the crop are exacerbated by low soil fertility, and limited or erratic rainfall, which are respectively resulting from agricultural intensification and climate change (Berner et al., 1996). Remote sensing and geographic information systems (GIS) enabled identifying current and future Striga-risk and resources allocation priority areas, and scale out containment measures (Mudereri et al., 2020). The agronomic and economic impact of parasitic weeds as well as their distribution in SSA underlines the importance of designing different components of an integrated control strategy that could help overcoming this threat for food security in SSA.
Striga weeds have a large and long-lasting seed production (400–600 thousand seeds plant−1 year−1) and viability(15–20 years life-spans) that results in a very large and inevitable impacts on crop production (Chitagu et al., 2014; Dzomeku & Murdoch, 2007; Mandumbu et al., 2019). Breeding for resistance, the development of resistant varieties, and encouraging farmers to adopt and grow resistant varieties remains the most sustainable, environment friendly, long-term and economically benign method for successful control of Striga (Gasura et al., 2021; Makaza et al., 2021). This review takes a closer look at the morpho-physiological responses of host plants and potential resistant mechanisms involved in the resistance against Striga parasitism. We review the effects of Striga infestation on host growth and development, stomatal performance, water use efficiency, hormonal effects, and photosynthesis. These aspects are considered from the perspective of host plant resistance to Striga in cereal crops.
2 Morpho-physiological response of cereal host crops to Striga infestation
2.1 Striga parasitism effect on host plant growth
In response to Striga parasitism, chlorosis, withering/early wilting, and leaf rolling, are the most common symptoms in maize, rice, sorghum and millet (Badu-Apraku & Akinwale, 2011; Nyongesa et al., 2018; Rodenburg et al., 2016). Gasura et al. (2021) highlighted that the negative responses associated with Striga infestation are strongly correlated with the infection level and the number of emerged Striga per host plant which is considered as one of the resistance, tolerance or susceptibility parameters.
Nyakurwa et al. (2018) revealed that Striga-tolerant maize genotype experienced early maturation to escape Striga parasitism stress. This influenced plant anthesis, silking, grain filling, as well as seed production (Badu-Apraku et al., 2021a). Nyakurwa et al. (2018) indicated that Striga parasitism affected the anthesis-silking intervals in maize, resulting in the loss of male-female flower synchrony. Striga infestation forces, also, host plants to develop rapidly and complete their life cycle before the extreme stress level that occurs at the end of infection process (Runo, 2019). Such early maturing affects the photosynthates allocation which results with a decreased grain yield (Khan et al., 2001). This justifies the need to develop early maturing and short cycle resistant genotypes that can escape the Striga parasitism at the end of the crop cycle.
2.2 Host-physiological response to Striga parasitism
2.2.1 Stomatal closure
Research revealed that stomatal closure is the first line of defence in plants under stress conditions. It prevents further water loss through transpiration while increasing heat dissipation in the leaves (Fig. 4) (Cissoko et al., 2011; Frost et al., 1997). Stewart and Press (1990) found that witchweeds increased the transpiration rate, which may predispose hosts to water stress and thus stomatal closure. Gurney et al. (2002) reported that abscisic acid (ABA) is the main molecule that signals stomatal closure in plants under stress and may result in hormonal imbalance. Khan et al. (2001) showed that ABA from host plant roots could trigger stomatal closure even when leaf water potential is not affected. Previous studies ascertained that elevated ABA in sorghum and rice leaves could lead to decreased net photosynthesis limiting CO2 intake and an increasing O2 levels in the leaf cells (Ejeta, 2007; Gurney et al., 2002; Nyakurwa et al., 2018; Press & Stewart, 1987; Rodenburg et al., 2008).
2.2.2 Water use efficiency (WUE)
Compared to non-infected plants, Striga infected plants have lower water use efficiency (WUE) (Badu-Apraku et al., 2021b; Gebremedhin et al., 2000; Shah et al., 1987). Gebremedhin et al. (2000) showed that WUE of the SRN-39 sorghum genotype was reduced by around 24% under Striga infestation which resulted in a limited dry matter accumulation. The dynamic alterations in leaf morphology all with the allometric coefficient showed that Striga parasitism leads to an afflicted host plants' water balance (Shah et al., 1987).
The competitive parasitism effects, for water and nutrients requirement, between Striga plants and their host is usually attributed to Striga negative osmotic potential compared to the host (Watling & Press, 1997). Parker and Riches (1993) reported a clear change in the host root-shoot balance in response to Striga infestation. Such dynamic changes in morphology of Striga-infected plants is considered as an adaptive mechanism to Striga inflicted competition for water and nutrients.
2.2.3 Hormonal effect and photosynthesis under Striga parasitism
Sorghum experiments conducted by Rodenburg et al. (2005) postulated that Striga resistant sorghum genotypes showed higher cytokinins concentration compared to susceptible checks. Yang et al. (2016) reported that, in addition to their role in cell division and shoot-root morphogenesis, cytokinins are also involved in the stay-green and senescence traits with specific adjustments of the chloroplast structural changes, vacuolar collapse and loss of plasma membrane integrity (Watling & Press, 1997). It was reported that, in general, Striga-resistant plants maintain the stability and the composition of their cellular membranes under Striga parasitism (Gebremedhin et al., 2000; Watling & Press, 2000). This was confirmed by Mandumbu et al. (2019) who observed a poor cellular membrane stability in susceptible sorghum genotypes under both S. hermonthica and S. asiatica parasitism. Such behaviour was associated with a lower photosynthesis rate (Mandumbu et al., 2019). Nyakurwa et al. (2018) showed that, under Striga parasitism, stomatal closure decreased CO2 fixation. Wada et al. (2019) mentioned that Striga effects on host plant have a similar effect as drought stress, where the infection can cause stress-induced cellular alterations and reactive oxygen molecule overproduction (ROS). Gebremedhin et al. (2000) and Kanampiu et al. (2018) showed that under high Striga infestation, regressive signals such as 3′-phosphoadenosine-5′-phosphate are accumulated and transported from the chloroplast to the nucleus. Other studies showed that the photosynthetic pathways and their associated enzymes (RUBISCO, PEP carboxylase and NADP-malic enzymes) remain unaffected in leaves of Striga-infected sorghum (Gurney et al., 1995) and maize (Smith et al., 1995). Frost et al. (1997) found that susceptible sorghum genotypes showed high respiration rates, that increased reactive oxygen species (ROS) leading to cell damage. This affect the photoprotective metabolites such as carotenoids, flavonoids, glutathione, ascorbate, and tocopherols throughout the host cells and its organelles (Watling & Press, 1997).
2.2.4 Chlorophyll content
The chlorophyll content is another parameter negatively impacted by Striga infestation in host plants (Gwatidzo et al., 2020; Makani et al., 2020). Previous studies showed also that Striga parasitism causes distress in C production in host plants, which may limit N and Mg assimilation, resulting in low chlorophyll synthesis (Gurney et al., 2002; Mwangangi et al., 2021). Low chlorophyll content in host plant leaves is associated with reduced plant biomass production due to changes in photosynthetic activities (Rodenburg et al., 2016). Such decreases of chlorophyll content are usually associated with PSII quantum efficiency decreases (Amri et al., 2021; Gurney et al., 2006). Resistance genotypes, however, were able to keep a relatively high chlorophyll content, which promote photoprotective compounds biosynthesis, scavenge ROS and dissipate extra energy via xanthophyll-mediated non-photochemical quenching (Gurney et al., 1995; Watling & Press, 1997). High chlorophyll content postulates strong correlation with high photosynthetic rates (Amri et al., 2021; Nyakurwa et al., 2018). This indicates that the resistant host plants can produce photosynthates under Striga infestation and provide enough resources for their growth in addition to the parasite needs (Gasura et al., 2021; Mbuvi et al., 2017). Several previous studies highlighted that chlorophyll content can be used as an indirect indicator of sorghum (Ronald et al., 2016), maize (Nyakurwa et al., 2018), rice (Rodenburg et al., 2015) and millet (Mallu et al., 2021) tolerance to Striga as well as Orobanche resistance in faba bean (Vicia faba L.) (Amri et al., 2021). In addition, the first signals of Striga parasitism include the photochemical reactions changes in host leaves that might be used to estimate photosynthetic performance and could appear in the chlorophyll fluorescence kinetics (Frost et al., 1997). Olivier et al. (1991) showed that Striga exhibited low C assimilation rate, which is compensated by carbon transfer from their hosts. Cechin and Press (1994) has drawn attention to the obligate transfer of carbon when nitrogen moves as organic compounds from the host plant to the parasite. It has been shown that xylem sap of Striga is rich in organic and low in inorganic nitrogen (Berner et al., 1996), which suggest that part of the carbon transfer may occur in the form of amino acids or amides. If Striga is partially dependent on its host for carbon as well as nitrogen and other mineral elements, then the maintenance of high transpiration rates might be a key factor in determining its growth.
2.2.5 Chlorophyll fluorescence
Chlorophyll fluorescence (maximum quantum efficiency Fv/Fm ratio) characteristics which include electron transport rate (ETR) via PSII, photochemical (Pq) and non-photochemical quenching (NPq) are essential host plant parameters which are significantly affected by Striga parasitism and could be considered as early indicators of resistance against this parasite (Runo & Kuria, 2018). It is a non-destructive and rapid assessing tool of photochemical quantum yield and photo-inhibition that has been recommended as indirect practical screening tools for early parasitism detection, diagnosis, screening, and selection of high resistant genotypes against parasitic weeds (Amri et al., 2021; Gurney et al., 1995). Striga parasitism resulted in a continuous reduction in ETR and Pq in sorghum and rice since it is proportional to the energy transfer to the functional CO2 assimilation reaction centres (Rodenburg et al., 2008). Both ETR and Pq were strongly correlated with CO2 assimilation (Watling & Press, 2000). Carbon budget models suggest that low CO2 fixation rates by the host canopy may account for 80% of the difference in productivity between infected and non-infected host plants (Gurney et al., 2002; Khan et al., 2001). This is in harmony with the findings of Rodenburg et al. (2016) who highlighted that the rate of light saturating CO2 fixation in infected sorghum plants was limited to only 60%.
Although Striga is photosynthetic, 14C-feeding studies and measurements of stable carbon isotopes demonstrated that the parasite is partially heterotrophic with a host-derived carbon proportion varying between 5 and 35% (Gurney et al., 1995). Striga tolerant maize, sorghum, and millet genotypes have improved CO2 assimilation rate due to structural modifications (Press & Stewart, 1987; Watling & Press, 2000). The physiological response is coupled with metabolic reactions where phosphoenolpyruvate (PEP) is carboxylated to C4 acids concentrated in the mesophyll cells. The acids are then transferred, by diffusion, to the bundle sheath, where they are decarboxylated. The CO2 concentration in the bundle sheath is sufficient to suppress the oxygenase activity of Rubisco and improve photosynthesis in tolerant genotypes (Watling & Press, 1997). For C3 plants such as rice plant photorespiration results in substantial losses of fixed carbon, particularly under Striga infestation (Taniguchi et al., 2008; Watling & Press, 2000). Taniguchi et al. (2008) tried to develop a C4 photosynthetic pathway into rice, which resulted in an increased radiation use efficiency. However, previous attempts to introduce a single-cell C4 pathway into rice led to increased photosynthesis photoinhibition, leaf chlorophyll bleaching and stunting with no evidence of CO2 concentration in chloroplasts (Taniguchi et al., 2008).
3 Harnessing natural host crops resistance against Striga spp.
3.1 Genetic basis for host plant resistance and defence mechanisms
Host plant resistance remain the most sustainable, economically, and eco-friendly method to control the parasitic weeds. Striga-resistance is a polygenic trait that requires combining whole-genome information (Badu-Apraku et al., 2020a; Shaibu et al., 2021). Genotyping and phenotyping are therefore critical to correlate the resistance-associated traits with particular gene loci. This strategy was useful in many previous studies conducted on maize, sorghum and rice (Mbuvi et al., 2017; Mutinda et al., 2018). Several studies reported various resistance mechanisms associated with low striga infection and higher seed yield observed in resistant genotypes under Striga-afflicted environments (Gasura et al., 2019, 2021). these mechanisms includes the low production of germination stimulant, physical barriers (i.e. lignification of cell walls), inhibition of germ tube exo-enzymes by root exudates, phyto-alexine synthesis, post-attachment hypersensitive reactions or necrosis, incompatibility, antibiosis, i.e., reduced Striga development through unfavourable phytohormone supply by the host, insensitivity to Striga toxin like iridoid glycocides (i.e. maintenance of stomatal aperture and photosynthetic efficiency) and avoidance through root growth habit (i.e. fewer roots in the upper 15–20 cm soil depth) (Fig. 4) (Dayou et al., 2021; Mutinda et al., 2018; Yacoubou et al., 2021). Overall, genomic selection via omics and system biology, can models all markers in a framework that doesn’t only identify marker-trait associations but incorporates all markers’ effects to predict yield (Table 1).
Periodic genetic gains assessment for Striga resistance for SSA proved to be a key component to evaluate the effectiveness of breeding programs (Menkir & Meseka, 2019). Badu-Apraku et al. (2013) reported that the use of early maturing maize cultivars under Striga-inflicted conditions resulted in an annual genetic gain of 1.93% with an increased grain yield from 2 537 kg ha−1 (1988–2000) to 3 122 kg ha−1 (2007–2010). Similar results were reported by Badu-Apraku et al. (2019) who showed that bi-parental maize population yielded 498 kg ha−1 (16.9%) and 522 kg ha−1 (12.6%) under Striga-infested and non-infested conditions, respectively.
3.2 Pre-attachment resistance mechanisms
Host-parasite interaction is strongly dependent on germination stimulants (strigolactones; SLs) produced in host root exudates (Fig. 4). SLs are germination triggers and elicitors of the parasite attachment and the host-parasite interface. This array of signal exchanges between Striga and its hosts leading to successful parasitism is a fascinating biological phenomenon (Rich & Ejeta, 2008). Throughout their evolution, Striga have developed an adapted perception and signalling mechanisms to detect SLs in the rhizosphere of host root systems. Different genotypes of the same plant species may produce different SLs combinations, which determine their levels of resistance or susceptibility to Striga (Cardoso et al., 2011). The stereochemistry and the structural diversity of SLs influence the host biological activities and define the pre-and-post emergence host resistance levels (Yoneyama, 2020). Qualitative, quantitative, and functional differences in SLs production by different host plants raise the question of whether the resistance (or the susceptibility) in host plants depends on the quantity and/or the structural diversity of SLs. Low orobanchol biosynthesis that resulted in low Striga seed germination was reported in SRN39 sorghum variety, (Gebremedhin et al., 2000; Gobena et al., 2017). Yoneyama et al. (2010) postulated that 5-deoxystrigol was the main SL produced by Striga-susceptible sorghum cultivars, whereas sorgomol was mainly exuded by Striga-resistant cultivars.
SLs are responsible of breaking Striga seed dormancy, stimulating its germination, the development of a haustorium and radicle elongation in a chemotropic response to the concentration gradient of root exudates (Haussmann et al., 2000; Timko et al., 2012). Haustoria form a morphological and physiological graft with the host roots. They produce phytotoxins and hydrolytic enzymes to degrade the root cell walls and disrupt the host defence system (Ejeta, 2007; Rich & Ejeta, 2007). This specific host parasite interaction will stimulate the attachment, the inter and intra-cellular penetration and vascular connection between the parasitic and host plants (Mwangangi et al., 2021). Haustoria undergo rapid cell differentiation to develop tracheal elements in the cortical cells. These elements develop into xylem vessels that achieve xylem-xylem or phloem connections with the host root system and enable the parasite to take water and nutrients (Makaza et al., 2021; Shayanowako et al., 2018; Wada et al., 2019).
Pre-attachment resistance mechanisms depend on the quality and quantity of the SLs produced. Typically, plants detect SLs via the DWARF14 hydrolase receptor (D14) (Yoneyama et al., 2020). Pre-attachment resistance arises when a host produces low amounts of strigolactones or when Striga receptors are insensitive to SLs. Germination of Striga seeds require strigolactones that attach to hydrolase receptors. In a cytochemical study conducted by Olivier et al. (1991), on cell surface interactions between sorghum roots and S. hermonthica, the authors revealed that some cellulotyic enzymes from the haustoria were accompanied by secondary roots thickening of resistant plant. Mandumbu et al. (2019) also, reported that the pre-attachment resistance could be triggered by the failure of an effective development of haustorial initiation factors. Same authors mentioned that SLs production, could stimulate witchweed seed germination without a successful attachment of the parasite to the host roots. This suggested the potential use of bioactive SL analogues was proposed as good option to control and reduce Striga seed bank in the soil (Zwanenburg & Pospíšil, 2013). An Ex ante study conducted by Jamil et al. (2012) revealed that CG14, WAB56-104 and NERICA-1 rice varieties produced low amounts of SLs which was associated with low germination stimulant (LGS) genes. Similar findings were reported by Nyakurwa et al. (2018) in maize germplasm grown under SSA environments.
Pre-attachment resistance is, also, determined by Striga seeds’ germination percentage, radicle length, furthest germination distance (FGD) and the number of attachments on the host root plant. These parameters depend on the germination-stimulant production level, germination inhibition, and low haustorial initiation (Gasura et al., 2019; Mallu et al., 2021; Mandumbu et al., 2019; Shayanowako et al., 2018). Other mechanisms of pre-attachment resistance have been stated by Mbuvi et al. (2017) who revealed that pre-attachment resistance could be due to the lgs1 mutation. Mallu et al. (2021) reported single nucleotide polymorphisms (SNPs) in genes associated with lgs1 as well as in other loci based on sorghum GWAS study.
3.3 Post-attachment resistance
Post attachment Striga-resistance mechanisms occur after Striga connection to the host root system. Several traits associated with such resistance mechanism include post-attachment parasite necrosis, delayed Striga emergence, number of Striga attachment/shoots per host plant, number of emerged Striga plants, Striga severity index, damage rating, Striga biomass, Striga number progress curves, severity curves, host plant biomass and grain yield (Cissoko et al., 2011; Gasura et al., 2019; Mbuvi et al., 2017; Mutinda et al., 2018). Once connected to the host roots, Striga plants start producing enzymes and RNA-based effectors to destroy root host tissues (Mutinda et al., 2018). In response, the host develops physiological and/or metabolic barriers, that hinders the Striga haustorium attachment to host xylem (Gasura et al., 2019; Mbuvi et al., 2017; Mutinda et al., 2018). Other studies reported, also, the production of the resistant compounds in rice, maize, and sorghum roots, that inhibit the haustorium connection and stipulates post-attachment host resistance response (Gobena et al., 2017; Jamil et al., 2011). Post attachment resistance can also occur when Striga penetrate the host roots but cannot reach the not the endodermis to establish a vascular link (Fishman & Shirasu, 2021). Endodermis lignification was considered as a marker for pattern (PTI) and effector(ETI) triggered immunity (Cissoko et al., 2011; Fishman & Shirasu, 2021). Yoneyama et al. (2010) reported that the root physical barrier and the cortex lignification is related to callose and suberin compounds accumulation as well as protein cross-linking in the host cell walls.
4 Breeding for resistance to Striga in cereal crops
Conventional breeding approach combined with new advanced and molecular techniques were initiated in many national and international breeding programs to develop resistant germplasm against Striga spp. (Table 2; Fig. 5) (Badu-Apraku & Fakorede, 2017). Good understanding of specific mechanisms associated with resistance would facilitate the development of improved Striga resistance germplasm (Amusan et al., 2008). Many studies have been conducted on Striga resistance associated genetics of (Badu-Apraku et al., 2020a, b, c; Frost et al., 1997; Gasura et al., 2021). Badu-Apraku et al. (2010) mentioned that Striga resistance mechanisms are quantitative inherited traits controlled by an additive gene effect. these resistance traits/genes can be associated with low number of emerged Striga plants, limited host damage, and better grain yield. In a previous study, Kulkarni and Shinde (1985) reported that Striga resistance in sorghum was more associated with additive gene effects and epistasis. This allows effective identification and transmission of additive genes from examined parents and exploitation of heterosis as highlighted in maize (Akinwale et al., 2014; Gasura et al., 2021) and sorghum (Mrema et al., 2020). Badu-Apraku et al. (2010) reported an additive gene effect that control the number of emerged Striga in maize. In absence of complete resistance to striga, the genes pyramiding remains as the most promising breeding strategy for improving resistance against Striga in cereal crops (Ejeta et al., 2000; Menkir, 2006).
The multi-location screening has been recommended to develop germplasm with good and stable resistance level especially under a substantial genotype x environment interaction (GEI) effects and variability of Striga populations’ virulence.
4.1 Conventional breeding approach
The objective of conventional breeding is to increase individual selection chances from generated populations (Badu-Apraku et al., 2021b). the developed germplasm is then subjected to rigorous multi-environments’ selection process in order to identify well adapted Striga resistant genotypes with different associated genes. Different approaches such as single seed descent, recurrent selection, half-sib, full-sib and S1 family selection methods all with hybrid breeding have proven successful in the development of Striga resistant germplasm (Afolayan et al., 2019; Gasura et al., 2021; Ronald et al., 2016; Shayanowako et al., 2018; Yacoubou et al., 2021).
Recurrent selection was used to combine features in germplasm and develop resistant maize genotypes with low Striga infestation and damages (Badu-Apraku & Akinwale, 2011; Menkir & Kling, 2007). This increase the frequency of interesting alleles and improve the quantitatively inherited traits that may involve many gene loci with smaller effects. For open pollinated crops such as maize, the development of gene-pools with many potential resistant sources and various genetic makeup could be a good option for gene pyramiding and development of resistant germplasm. Open pollinated populations like Zea diplo SYNW-1 and TZL Comp SYNW-1 (Table 2) have significantly benefited from the high outcrossing level to transfer associated Striga resistance genes from Zea diploperennis and tropical maize (Adesina & Akinwale, 2014; Gethi & Smith, 2004). It promotes the accumulation of resistant genes for polygenic durable Striga resistance genotypes. Genotypes that combine early maturity and high yield would be good sources and potential recurrent parents for breeding to Striga resistance (Adewale et al., 2020). Kountche et al. (2013) reported a significant genetic variation in Striga resistance among 200 C5 full-sib pearl millet families (C5-FS) tested in different environments with 34% heritability.
Other studies reported that the development of genotypes with Striga resistant composite populations may be easier through the half sibling selection technique (Ejeta, 2007; Haussmann et al., 2000). (Afolayan et al., 2019) suggested the backcross approach as a good approach to develop maize and sorghum genotypes carrying polygenic resistance against Striga. Afolayan et al. (2019) used the backcross (up to BC3F1) to stabilize S. hermonthica resistance in sorghum. A sufficient number of backcrosses should be made to recover the desirable Striga resistant traits of recurrent parent (RP). Other previous studies showed a successful transfer S. hermonthica resistance QTLs from local cultivated maize populations and wild relatives by backcross breeding to new adapted maize germplasm (Mengesha et al., 2017; Shayanowako et al., 2018). The backcross breeding technique could be considered as the most effective approach if the donor has a high frequency of favourable genes associated with the Striga resistance.
Diallel analysis, also, clearly revealed the presence of quantitative genetic variation with a majority of additive effect for Striga seeds stimulation in sorghum (Haussmann et al., 2000). Potential resistance sources against Striga have been reported in maize, sorghum, rice and millet (Table 2) (Akinwale et al., 2014; Gasura et al., 2021). Crop wild relatives offers a diverse genetic pool for breeding (Shayanowako et al., 2018). Wild relatives such as Tripsacum dactyloides, Z. diploperennis, landraces, and synthetics are identified as the potential sources for Striga resistance genes (Tables 1 and 2) (Amusan et al., 2008; Gethi & Smith, 2004). Many genes associated with resistance to S. hermonthica were successfully introgressed from Z. diploperennis into cultivated maize, resulting in the development of resistant inbred lines and synthetics (Rich & Ejeta, 2008).
Difference in resistance levels observed in maize inbred lines/hybrids against Striga spp. could be related to different resistance mechanisms (Gethi & Smith, 2004). Gasura et al. (2019) reported that maize inbred lines (from LE and TZL pools) showed higher resistance level to S. hermonthica and S. asiatica compared to Diplo pool. Hybrid variety heterosis was also reported to be effective in reducing the impact of S. asiatica on crop productivity (Gasura et al., 2021).
4.2 Marker assisted breeding (MAB)
The use of molecular markers for genetic analysis and regulation of critical biophysical traits associated with striga resistance is becoming increasingly important in understanding the Striga-host interaction and the development of resistance genotypes (Fig. 5). This is determined by the type and number of genes associated with the desirable traits (Badu-Apraku et al., 2020b, c). Over the past two decades, considerable progress has been made where several studies have developed and reported molecular markers associated with Striga resistance in cereals (Table 1) (Grenier et al., 2007; Pfunye et al., 2021). Molecular markers and marker assisted selection (MAS) has substantially accelerated breeding progress for Striga resistance (Grenier et al., 2007; Yohannes et al., 2015). Through marker-assisted selection combined with advanced backcrossing (AB-QTLs), five Striga resistant QTLs were transferred from resistance donor N13 to Striga susceptible “Hugurtay” (Yohannes et al., 2015). The introgressed QTLs boosted Striga resistance and yield advantage of BC3F3 backcross progenies (Yohannes et al., 2015). In addition, QTL analysis can be integrated with transcriptomics for the identification of Striga resistant candidate genes (Fig. 5). Swarbrick et al. (2009) discovered three Striga resistance QTL associated with Striga resistance in rice through Koshihikari-Kasalath backcrossed inbred lines (BILs) study. Two of these QTLs were derived from the Kasalath allele while the other one was derived from the Koshihikari allele. The greatest QTL (Kasalath allele) was found on chromosome 4 and explained 16% of the variation in the mapping population (Swarbrick et al., 2009). Menkir and Meseka (2019) reported that the QTL of Striga resistance identified in rice has been confirmed and narrowed down and could be a tractable target for MAS.
Furthermore, genome wide association (GWAS) and marker-assisted selection studies confirmed efficacy ofthe identification and introgression of Striga resistance genes in highly adapted germplasm in maize and sorghum (Gasura et al., 2021; Grenier et al., 2007). For instance, Pfunye et al. (2021) identified markers in chromosomes 5, 6, and 7 associated with total S. asiatica emerged plants, which could be validated and used in future breeding programs. The three SNP markers found for total Striga emerged plants suggest the possibility of successful selection process at genomic level (Pfunye et al., 2021). Adewale et al. (2020) and Badu-Apraku et al. (2020a) identified a set of 24 SNP markers for various traits including S. hermonthica damage rating in maize on chromosome 1, 3, 7, 8, 9, and 10. An S9_154,978,426 locus on chromosomes 9 and 10 in maize found at 2.61 Mb close to ZmCCD1 and amt5 genes, respectively, could be associated with low strigolactone production in maize roots (Table 1) (Adewale et al., 2020). Other studies have also reported three markers associated with S. hermonthica resistance in maize physically located close to the putative genes GRMZM2G164743 (bin 10.05), GRMZM2G060216 (bin 3.06) and GRMZM2G103085 (bin 5.07) (Table 1) (Adewale et al., 2020; Gobena et al., 2017). Many candidate genes and QTLs identified were reported in Table 1 (Badu-Apraku et al., 2020b, c; Kavuluko et al., 2021; Satish et al., 2012; Stanley et al., 2021).
In addition, Gowda et al. (2021) have discovered through GWAS study, some candidate genes such as GRMZM2G018508, GRMZM2G075368, GRMZM2G015520, GRMZM2G074871 and GRMZM2G127230 highly associated with emerged Striga plants in maize. Same authors reported that these genes were involved in signal and stress-related transcriptomic factors pathways (Table 1). Badu-Apraku et al. (2020b, c) also reported candidate genes coding for transcription factor families involved in plant defence signaling in maize in response to Striga parasitism like WRKY, bHLH, AP2-EREBPs, MYB, and bZIP. These genes were involved in the ABA synthesis under Striga infection (Gowda et al., 2021). GRMZM2G074871 gene was involved in the metabolism of a wide range of exogenous and endogenous compounds, biosynthesis of pigments, volatiles, antioxidants, allelochemicals and defence compounds (Table 2). Metabolomic compounds associated with Striga resistance have been reported in rice (Mutuku et al., 2019; Swarbrick et al., 2009). The up-regulation of S. hermonthica defence genes, such as pathogenesis-related proteins, pleiotropic drug resistance ABC-transporter genes were involved in phenylpropanoid metabolism and WRKY transcription factors (Swarbrick et al., 2009) (Tables 1 and 2).
In review of MAB for Striga resistance in sorghum, Grenier et al. (2007) reported that two nuclear genes HR1 and HR2, which were associated with two different markers on the genetic linkage map, controlled Striga resistance in sorghum. Low germination stimulant (lgs) gene was discovered to code for a sulfotransferase enzyme, and when silenced, the sorghum root exudates changed from 5-deoxystrigol to orobanchol compounds (Gobena et al., 2017; Mbuvi et al., 2017). Other studies reported fourteen QTLs controlling Striga resistance in maize and were strongly associated with grain yield, ears per plant, Striga severity (Stanley et al., 2021). Badu-Apraku et al. (2020b, c) reported, also, 12 different QTLs associated with Striga resistance traits in maize, and accounting for 19.4, 34.9 and 14.2% of observed phenotypic variation for grain yield, ears per plant, and Striga severity, respectively.
Plant breeders via molecular markers, are able to offer a faster and easy introgression of desired genes into improved lines as it becomes easier to manipulate and transfer novel Striga resistance genes throughout the breeding process. Contrarily, phenotyping large pools of germplasm for Striga resistance is costly, making it difficult to collect enough data for high-resolution maker-trait-association and QTL finding. However, by minimizing yield losses owing to Striga infestation, the identification of SNP markers can cement conventional breeding procedures and revitalize cereal production in resource-poor African farmers in SSA (Mengesha et al., 2017; Stanley et al., 2021; Zebire et al., 2020). This information could help in stacking several genes associated with different resistance traits into a single genotype for better and durable resistance. This was the case of sorghum genotype developed from the cross between SRN39 and Framida which was reported to provide good resistance level to S. hermonthica (Adewale et al., 2020; Grenier et al., 2007; Kavuluko et al., 2021).
The genotypic prediction has been also widely applied in the breeding for Striga resistance. It is used to predict the best-performing lines speed up the breeding cycle by capturing all marker effects and avoiding the drawbacks of marker-assisted selection (Crossa et al., 2017; Ould Estaghvirou et al., 2013). Results of random cross-validation with genomic best linear unbiased predictor (GBLUP) indicate that genotypic prediction can increase the prediction accuracy for complex traits (Gowda et al., 2021)through the use of molecular markers for diversity analysis and heterotic grouping (Haussmann et al., 2000). Diverse studies conducted in different locations across SSA using a variety of markers confirmed the presence of relationships between geographic and genetic distances among the parasite populations which should be taken into consideration throughout the selection process and breeding pipeline (Badu-Apraku et al., 2020a; Gasura et al., 2019; McDonald & Stukenbrock, 2016; Mwangangi et al., 2021; Unachukwu et al., 2017).
5 Omics and system biology in cereal Striga resistance
The use of omics approaches such as genomics, transcriptomics, proteomics, metabolomics, and bioinformatics in conjunction with whole genome sequencing significantly accelerated the genetic gain for Striga resistance in target cereal crops (Bellis et al., 2020). Next Generation Sequencing (NGS), gene editing systems, gene silencing, and overexpression approaches has provided a limited amount of genetic information for the discovery of Striga stress response pathways in plants (Deshpande et al., 2013; Yoshida et al., 2019). Omics approaches create a platform networks of interaction between genes, proteins, and metabolites that are involved in stress response mechanisms. The gene expression investigations in parasitic plants were carried out using a targeted gene method, which was mostly based on previous plant stress research. This enabled the discovery of a small number of genes associated with Striga resistance defence (Fig. 5). The differential expression of these genes was elucidated using microarrays and RNA sequencing techniques (Samejima & Sugimoto, 2018).
Advances in genomics provide new discoveries of important Striga resistance genes in different cereal crops (Rich & Ejeta, 2008). Proteomics has been, also, successful in identifying and characterizing several proteins and their regulation in cereal crops under Striga infestation (Fig. 5). Despite the low levels of host-based genome-wide differentiation, Ichihashi et al. (2015) and Lopez et al. (2019) identified a set of parasite transcripts associated specifically with maize and sorghum resistance to Striga. The findings could be in line with the genes associated with nutrient transport, defence and pathogenesis, and plant hormone response (Stewart & Press, 1990; Yoneyama, 2020). These genes are significant in host-parasite interactions with varying expression level in different hosts (Deshpande et al., 2013).
In Furthermore, Scholes and Press (2008) reported a number of candidate transcripts that showed host-specific interactions were revealed in the vegetative tissues of emerged S. hermonthica shoots. Lopez et al. (2019) revealed the identification of Striga resistance or susceptible genes involved in haustoriogenesis through transcriptomics, proteomics and RNAseq. Yoshida and Shirasu (2012) and Yoshida et al. (2019) obtained S. hermonthica transcriptome data by sequencing cDNA using the Sanger method. There is consistency with the serendipitous findings by Westwood et al. (2012) who generated S. hermonthica sequences, which gave an immense reservoir of molecular markers for understanding population dynamics, as well as insight into parasitism biology and progress toward understanding parasite virulence and host resistance mechanisms.
The genome data provides a foundation for understanding the origins of parasitism during evolution (Deshpande et al., 2013; Yoshida et al., 2019). Striga-related transcriptome research has recently accelerated but the majority of investigations are centred on deciphering Striga's transcriptome and its evolutionary traits (Deshpande et al., 2013; Ichihashi et al., 2015; Mounde et al., 2020; Westwood et al., 2012).
The next generation sequencing (NGS) have also provided a large amount of transcriptome data from S. hermonthica plants at different development stages (Gobena et al., 2017). Mutuku et al. (2015) reported a new gene (WKRY45) associated with Striga resistance in rice. Yoshida and Shirasu (2012), also, reported an RNA-seq that could be associated with genes involved in Striga resistance in finger millet. Similarly, Mutuku et al. (2015) reported the abundance of genes in in finger millet plants during active Striga parasitism and that could be associated with nutrients and chemical flow between the host and the parasite.
In addition, according to preliminary analyses of gene expression changes in susceptible and resistant sorghum genotypes, Deshpande et al. (2013) and Tamir (2021) showed that many of the identified up-regulated genes are associated with defence responses to microbial pathogens, such as cytochrome P450s and WRKY transcription factors,. Two signal anchor proteins (XP 003627937 and XP 003616487) were found to be up-and-down-regulated under Striga parasitism in GuluE and IE2396 finger millet genotypes, respectively (Deshpande et al., 2013; Erick et al., 2019).
Erick et al. (2019) showed that most of the up-regulated proteins are involved in electron transport, photosynthesis, and oxidation-reduction processes, with the exception of cysteine protease 1 (hydrolase). Same authors showed that increased electron transport and photosynthesis are two of the counteractive responses of cereals against Striga infestation. During redox processes involved in plant-parasite interactions, the changes are catalyzed by quinone oxidoreductases to initiate haustorium induction in plant parasites (Ichihashi et al., 2015; Yoshida & Shirasu, 2012). Cytochrome P450 gene is one of the defence-related genes found as being up-regulated during ethylene or jasmonate treatment or during host plant infection by Striga (Mbuvi et al., 2017; Runo, 2019). Nevertheless, there are other up-regulated proteins in individual cereal genotypes, such as pathogenesis-related protein (PRB1-2-like) and glycine-rich RNA-binding protein 1-like (GrpA), could indicate resistance to the Striga invasion (Hiraoka et al., 2009). A GrpA gene (RAB15) was, also, reported to transmit signal to receptors and induce the activation of JA sensitive defence genes in maize (Erick et al., 2019; Rich & Ejeta, 2008).
Swarbrick et al. (2009) mentioned that specific genes and enzymes were involved in the phenylpropanoid metabolism in rice under Striga parasitism. Mutuku et al. (2019) and Lopez et al. (2019) reported, also, that enzymes groups, that include transferases, oxidoreductases, and hydrolases, were over-represented in finger millet transcriptome under Striga parasitism.
The development of a high-throughput microarray-based Diversity Arrays Technology (DArT) for several crop species, including sorghum, as well as Next Generation Sequencing (NGS) based Genotyping-by-Sequencing (GbS) tools could significantly accelerate Striga diversity knowledge. The development of Striga-specific assays would allow the simultaneous screening of hundreds of molecular markers and the comparison of Striga populations (Fig. 5) at micro (field) and macro (country and region) scales (Deshpande et al., 2013).
To date, no large-scale analysis of the metabolite recruited during parasitic infection have been performed, but targeted metabolic and cytological analyses have shown that numerous secondary metabolites are involved in the resistance to Striga. The breeding for high concentrations of these compounds in roots by either classical breeding or transgenesis is a promising approach (Fig. 5).
6 Conclusion
Most identified resistance sources need further exploration of the resistance mechanisms that are involved, the associated genes, and their potential introgression into well-adapted high yielding varieties. The knowledge of genome sequences is rapid, and so is that of the physiological and molecular roles of plant genes. The genetic engineering technologies and use of gene-editing and CRISP/Cas9 could help in developing new Striga resistant genotypes and exploring further the molecular and genetic mechanisms involved in the resistance to Striga in maize, sorghum, millet and rice. The genetic variation within and between Striga populations should also be considered in designing efficient management strategies involving different control components.
Data availability
All the data used in this review paper were generated from published and available material.
References
Adesina, G., & Akinwale, R. (2014). Response of Striga resistant maize varieties to natural weed conditions and weed control measures under rainforest condition. Annals of Plant Science Journal, 3(3), 631–637.
Adewale, S. A., Badu-Apraku, B., Akinwale, R. O., Paterne, A. A., Gedil, M., & Garcia-Oliveira, A. L. (2020). Genome-wide association study of Striga resistance in early maturing white tropical maize inbred lines. BMC Plant Biology, 20(1), 1–16. https://doi.org/10.1186/s12870-020-02360-0
Afolayan, G., Aladele, S., Deshpande, S., Oduoye, O., Nwosu, D., Michael, C., Blay, E., & Danquah, E. (2019). Marker assisted foreground selection for identification of Striga resistant backcross lines in Sorghum bicolor. Covenant Journal of Physical and Life Sciences, 7(1), 29–36.
Akinwale, R., Badu-Apraku, B., Fakorede, M., & Vroh-Bi, I. (2014). Heterotic grouping of tropical early-maturing maize inbred lines based on combining ability in Striga-infested and Striga-free environments and the use of SSR markers for genotyping. Field Crops Research, 156, 48–62. https://doi.org/10.1016/j.fcr.2013.10.015
Amri, M., Abbes, Z., Trabelsi, I., Ghanem, M. E., Mentag, R., & Kharrat, M. (2021). Chlorophyll content and fluorescence as physiological parameters for monitoring Orobanche foetida Poir. infection in faba bean. Plos One, 16(5), e0241527. https://doi.org/10.1371/journal.pone.0241527
Amusan, I. O., Rich, P. J., Menkir, A., Housley, T., & Ejeta, G. (2008). Resistance to Striga hermonthica in a maize inbred line derived from Zea diploperennis. New Phytologist, 178(1), 157–166. https://doi.org/10.1111/j.1469-8137.2007.02355.x
Badu-Apraku, B., Adu, G. B., Yacoubou, A.-M., Toyinbo, J., & Adewale, S. (2020a). Gains in genetic enhancement of early maturing maize hybrids developed during three breeding periods under Striga-infested and Striga-free environments. Agronomy, 10(8), 1188. https://doi.org/10.3390/agronomy10081188
Badu-Apraku, B., Adewale, S., Paterne, A., Gedil, M., & Asiedu, R. (2020b). Identification of QTLs controlling resistance/tolerance to Striga hermonthica in an extra-early maturing yellow maize population. Agronomy, 10(8), 1168. https://doi.org/10.3390/agronomy10081168
Badu-Apraku, B., Adewale, S., Paterne, A. A., Gedil, M., Toyinbo, J., & Asiedu, R. (2020c). Identification of QTLs for grain yield and other traits in tropical maize under Striga infestation. Plos One, 15(9), e0239205. https://doi.org/10.1371/journal.pone.0239205
Badu-Apraku, B., & Akinwale, R. (2011). Cultivar evaluation and trait analysis of tropical early maturing maize under Striga-infested and Striga-free environments. Field Crops Research, 121(1), 186–194. https://doi.org/10.1016/j.fcr.2010.12.011
Badu-Apraku, B., Akinwale, R., & Fakorede, M. (2010). Selection of early maturing maize inbred lines for hybrid production using multiple traits under Striga-infested and Striga-free environments. Maydica, 55(3), 261.
Badu-Apraku, B., & Fakorede, M. (2017). Maize in Sub-Saharan Africa: importance and production constraints. Advances in genetic enhancement of early and extra-early maize for Sub-Saharan Africa (pp. 3–10). Springer. https://doi.org/10.1007/978-3-319-64852-1
Badu-Apraku, B., Fakorede, M., Akinwale, R., Adewale, S., & Akaogu, I. (2021a). Developing high-yielding Striga-resistant maize in sub-Saharan Africa. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources. CABI Publishing. https://doi.org/10.1079/pavsnnr202116030
Badu-Apraku, B., Lum, A. F., Fakorede, M., Menkir, A., Chabi, Y., The, C., Abdulai, M., Jacob, S., & Agbaje, S. (2008). Performance of early maize cultivars derived from recurrent selection for grain yield and Striga resistance. Crop Science, 48, 99–112. https://doi.org/10.2135/cropsci2007.01.0060
Badu-Apraku, B., Obesesan, O., Abiodun, A., & Obeng-Bio, E. (2021b). Genetic gains from selection for drought tolerance during three breeding periods in extra-early maturing maize hybrids under drought and rainfed environments. Agronomy, 11(5), 831. https://doi.org/10.3390/agronomy11050831
Badu-Apraku, B., Talabi, A. O., Fakorede, M. A. B., Fasanmade, Y., Gedil, M., Magorokosho, C., & Asiedu, R. (2019). Yield gains and associated changes in an early yellow bi-parental maize population following genomic selection for Striga resistance and drought tolerance. BMC Plant Biology, 19, 1–17. https://doi.org/10.1186/s12870-019-1740-z
Badu-Apraku, B., & Yallou, C. G. (2009). Registration of Striga-resistant and drought-tolerant tropical early maize populations TZE-W Pop DT STR C4 and TZE-Y Pop DT STR C4. Journal of Plant Registrations, 3(1), 86–90. https://doi.org/10.3198/jpr2008.06.0356crg
Badu-Apraku, B., Yallou, C., & Oyekunle, M. (2013). Genetic gains from selection for high grain yield and Striga resistance in early maturing maize cultivars of three breeding periods under Striga-infested and Striga-free environments. Field Crops Research, 147, 54–67. https://doi.org/10.1016/j.fcr.2013.03.022
Bayu, W., Binor, S., & Admassu, L. (2001). Tolerance of sorghum landraces and varieties to Striga (Striga hermonthica) infestation in Ethiopia. Acta Agronomica Hungarica, 49(4), 343–349. https://doi.org/10.1556/AAgr.49.2001.4.5
Bellis, E. S., Kelly, E. A., Lorts, C. M., Gao, H., DeLeo, V. L., Rouhan, G., Budden, A., Bhaskara, G. B., Hu, Z., & Muscarella, R. (2020). Genomics of sorghum local adaptation to a parasitic plant. Proceedings of the National Academy of Sciences, 117(8), 4243–4251. https://doi.org/10.1073/pnas.1908707117
Berner, D., Carsky, R., Dashiell, K., Kling, J., & Manyong, V. (1996). A land management based approach to integrated Striga hermonthica control in sub-Saharan Africa. Outlook on Agriculture, 25(3), 157–164. https://doi.org/10.1177/003072709602500304
Cardoso, C., Ruyter-Spira, C., & Bouwmeester, H. J. (2011). Strigolactones and root infestation by plant-parasitic Striga, Orobanche and Phelipanche spp. Plant Science, 180(3), 414–420. https://doi.org/10.1016/j.plantsci.2010.11.007
Cechin, I., & Press, M. (1994). The influence of nitrogen on growth and photosynthesis of sorghum infected with Striga hermonthica from different provenances. Weed Research, 34(4), 289–298. https://doi.org/10.1111/j.1365-3180.1994.tb01997.x
Chitagu, M., Rugare, J. T., & Mabasa, S. (2014). Screening maize (Zea mays) genotypes for tolerance to witchweed (Striga asiatica L. Kuntze) infection. Journal of Agricultural Science, 6(2), 160. https://doi.org/10.5539/jas.v6n2p160
Cissoko, M., Boisnard, A., Rodenburg, J., Press, M. C., & Scholes, J. D. (2011). New Rice for Africa (NERICA) cultivars exhibit different levels of post-attachment resistance against the parasitic weeds Striga hermonthica and Striga asiatica. New Phytologist, 192(4), 952–963. https://doi.org/10.1111/j.1469-8137.2011.03846.x
Crossa, J., Pérez-Rodríguez, P., Cuevas, J., Montesinos-López, O., Jarquín, D., De Los Campos, G., Burgueño, J., González-Camacho, J. M., Pérez-Elizalde, S., & Beyene, Y. (2017). Genomic selection in plant breeding: Methods, models, and perspectives. Trends in Plant Science, 22(11), 961–975. https://doi.org/10.1016/j.tplants.2017.08.011
Dayou, O., Kibet, W., Ojola, P., Gangashetty, P. I., Wicke, S., & Runo, S. (2021). Two-tier witchweed (Striga hermonthica) resistance in wild pearl millet (Pennisetum glaucum) 29Aw. Weed Science, 69(3), 300–306. https://doi.org/10.1017/wsc.2021.12
Deshpande, S. P., Mohamed, A., & Hash, C. T., Jr. (2013). Molecular Breeding for Striga Resistance in Sorghum. Translational Genomics for Crop Breeding: Biotic Stress. (Vol. 1). John Wiley & Sons.
Dzomeku, I. K., & Murdoch, A. J. (2007). Modelling effects of prolonged conditioning on dormancy and germination of Striga hermonthica. Journal of Agronomy, 6(2), 235–249. https://doi.org/10.3923/ja.2007.235.249
Ejeta, G. (2007). Breeding for Striga resistance in sorghum: exploitation of an intricate host–parasite biology. Crop Science, 47, S-216–S−227. https://doi.org/10.2135/cropsci2007.04.0011IPBS
Ejeta, G., Tuinstra, M. R., Grote, E. M., & Goldsbrough, P. B. (2000). Genetic analysis of pre-flowering and post-flowering drought tolerance in sorghum. In J. M. Ribaut & D. Pland (Eds.), Molecular Approaches for the Genetic Improvement of Cereals for Stable Production in Water-Limited Environment (pp. 137–141). Mexico D.F.: CIMMYT. A Strategic Planning Workshop, El Batan, Mexico (Mexico), 21-25 Jun 1999.
Erick, M., Mark, W., Francesca, S., Richard, O., Mercy, M., & Damaris, O. (2019). De novo transcriptome analysis of finger millet and identification of genes involved in Striga infestation. Retrieved July 29, 2021, from https://mel.cgiar.org/reporting/download/hash/bfa034016ce7ab6c361783603ce7ae6e
Fishman, M. R., & Shirasu, K. (2021). How to resist parasitic plants: Pre-and post-attachment strategies. Current Opinion in Plant Biology, 62, 102004. https://doi.org/10.1016/j.pbi.2021.102004
Frost, D., Gurney, A., Press, M., & Scholes, J. (1997). Striga hermonthica reduces photosynthesis in sorghum: The importance of stomatal limitations and a potential role for ABA? Plant, Cell & Environment, 20(4), 483–492. https://doi.org/10.1046/j.1365-3040.1997.d01-87.x
Gasura, E., Nyandoro, B., Mabasa, S., Setimela, P. S., Kyalo, M., & Yao, N. (2021). Breeding strategy for resistance to Striga asiatica (L.) Kuntze based on genetic diversity and population structure of tropical maize (Zea mays L.) lines. Genetic Resources and Crop Evolution, 69(3), 987–996. https://doi.org/10.1007/s10722-021-01274-6
Gasura, E., Setimela, P., Mabasa, S., Rwafa, R., Kageler, S., & Nyakurwa, C. (2019). Response of IITA maize inbred lines bred for Striga hermonthica resistance to Striga asiatica and associated resistance mechanisms in southern Africa. Euphytica, 215(10), 1–15. https://doi.org/10.1007/s10681-019-2467-5
Gebremedhin, W., Goudriaan, J., & Naber, H. (2000). Morphological, phenological and water-use dynamics of sorghum varieties (Sorghum bicolor) under Striga hermonthica infestation. Crop Protection, 19(1), 61–68. https://doi.org/10.1016/S0261-2194(99)00077-0
Gethi, J. G., & Smith, M. E. (2004). Genetic responses of single crosses of maize to Striga hermonthica (Del.) Benth. and Striga asiatica (L.) Kuntze. Crop Science, 44(6), 2068–2077. https://doi.org/10.2135/cropsci2004.2068
Giller, K. E. (2020). The food security conundrum of sub-Saharan Africa. Global Food Security, 26, 100431. https://doi.org/10.1016/j.gfs.2020.100431
Gobena, D., Shimels, M., Rich, P. J., Ruyter-Spira, C., Bouwmeester, H., Kanuganti, S., Mengiste, T., & Ejeta, G. (2017). Mutation in sorghum Low Germination Stimulant 1 alters strigolactones and causes Striga resistance. Proceedings of the National Academy of Sciences, 114(17), 4471–4476. https://doi.org/10.1073/pnas.1618965114
Gowda, M., Makumbi, D., Das, B., Nyaga, C., Kosgei, T., Crossa, J., Beyene, Y., Montesinos-López, O. A., Olsen, M. S., & Prasanna, B. M. (2021). Genetic dissection of Striga hermonthica (Del.) Benth. Resistance via genome-wide association and genomic prediction in tropical maize germplasm. Theoretical and Applied Genetics, 134(3), 941–958. https://doi.org/10.1007/s00122-020-03744-4
Grenier, C., Ibrahim, Y., Haussmann, B. I., Kiambi, D., & Ejeta, G. (2007). Marker-assisted selection for Striga resistance in sorghum. Integrating new technologies for Striga control: towards ending the witch-hunt (pp. 159–171). World Scientific. https://doi.org/10.1142/9789812771506_0012
Gressel, J., Hanafi, A., Head, G., Marasas, W., Obilana, A. B., Ochanda, J., Souissi, T., & Tzotzos, G. (2004). Major heretofore intractable biotic constraints to African food security that may be amenable to novel biotechnological solutions. Crop Protection, 23(8), 661–689. https://doi.org/10.1016/j.cropro.2003.11.014
Gurney, A., Press, M., & Scholes, J. (2002). Can wild relatives of sorghum provide new sources of resistance or tolerance against Striga species? Weed Research, 42(4), 317–324.
Gurney, A., Slate, J., Press, M., & Scholes, J. (2006). A novel form of resistance in rice to the angiosperm parasite Striga hermonthica. New Phytologist, 169(1), 199–208. https://doi.org/10.1111/j.1469-8137.2005.01560.x
Gurney, A. L., Grimanelli, D., Kanampiu, F., Hoisington, D., Scholes, J., & Press, M. (2003). Novel sources of resistance to Striga hermonthica in Tripsacum dactyloides, a wild relative of maize. New Phytologist, 160(3), 557–568. https://doi.org/10.1046/j.1469-8137.2003.00904.x
Gurney, A. L., Press, M. C., & Ransom, J. K. (1995). The parasitic angiosperm Striga hermonthica can reduce photosynthesis of its sorghum and maize hosts in the field. Journal of Experimental Botany, 46(12), 1817–1823. https://doi.org/10.1093/jxb/46.12.1817
Gwatidzo, V., Rugare, J., Mabasa, S., Mandumbu, R., Chipomho, J., & Chikuta, S. (2020). In vitro and in vivo evaluation of sorghum (Sorghum bicolor L. Moench) genotypes for pre-and post-attachment resistance against witchweed (Striga asiatica L. Kuntze). International Journal of Agronomy, 2020, 9601901. https://doi.org/10.1155/2020/9601901
Harahap, Z., Ampong-Nyarko, K., & Olela, J. (1993). Striga hermonthica resistance in upland rice. Crop Protection, 12(3), 229–231. https://doi.org/10.1016/0261-2194(93)90114-X
Haussmann, B. I., Hess, D. E., Welz, H.-G., & Geiger, H. H. (2000). Improved methodologies for breeding Striga-resistant sorghums. Field Crops Research, 66(3), 195–211. https://doi.org/10.1016/S0378-4290(00)00076-9
Haussmann, B. I. G., Hess, D. E., Reddy, B. V. S., Mukuru, S. Z., Kayentao, M., Welz, H. G., & Geiger, H. H. (2001). Pattern analysis of genotype× environment interaction for Striga resistance and grain yield in African sorghum trials. Euphytica, 122(2), 297–308. https://doi.org/10.1023/A:1012909719137
Hiraoka, Y., Ueda, H., & Sugimoto, Y. (2009). Molecular responses of Lotus japonicus to parasitism by the compatible species Orobanche aegyptiaca and the incompatible species Striga hermonthica. Journal of Experimental Botany, 60(2), 641–650. https://doi.org/10.1093/jxb/ern316
Ichihashi, Y., Mutuku, J. M., Yoshida, S., & Shirasu, K. (2015). Transcriptomics exposes the uniqueness of parasitic plants. Briefings in Functional Genomics, 14(4), 275–282. https://doi.org/10.1093/bfgp/elv001
Jamil, M., Charnikhova, T., Houshyani, B., van Ast, A., & Bouwmeester, H. J. (2012). Genetic variation in strigolactone production and tillering in rice and its effect on Striga hermonthica infection. Planta, 235(3), 473–484. https://doi.org/10.1007/s00425-011-1520-y
Jamil, M., Rodenburg, J., Charnikhova, T., & Bouwmeester, H. J. (2011). Pre-attachment Striga hermonthica resistance of New Rice for Africa (NERICA) cultivars based on low strigolactone production. New Phytologist, 192(4), 964–975. https://doi.org/10.1111/j.1469-8137.2011.03850.x
Kanampiu, F., Makumbi, D., Mageto, E., Omanya, G., Waruingi, S., Musyoka, P., & Ransom, J. (2018). Assessment of management options on Striga infestation and maize grain yield in Kenya. Weed Science, 66(4), 516–524. https://doi.org/10.1017/wsc.2018.4
Karaya, H., Njoroge, K., Mugo, S., Ariga, E. S., Kanampiu, F., & Nderitu, J. (2014). Combining ability of maize (Zeamays) inbred lines resistant to Striga hermonthica (Del.) Benth evaluated under artificial Striga infestation. African Journal of Agricultural Research, 9(16), 1287–1295.
Kavuluko, J., Kibe, M., Sugut, I., Kibet, W., Masanga, J., Mutinda, S., Wamalwa, M., Magomere, T., Odeny, D., & Runo, S. (2021). GWAS provides biological insights into mechanisms of the parasitic plant (Striga) resistance in sorghum. BMC Plant Biology, 21(1), 1–15. https://doi.org/10.1186/s12870-021-03155-7
Kenyi, E. J., Babikri, A., Omer, S. M., & Wani, P. (2017). Evaluation of Sorghum Genotypes for Tolerance to Striga hermonthica (Del.) Benth.(Lamiales: Orobanchaceae) and Yield in the Rain Fed Areas of Damazin, Sudan. International Journal of Life-Sciences Scientific Research, 3(3), 1003–1006. https://doi.org/10.21276/ijlssr.2017.3.3.7
Khan, Z., Pickett, J., Wadhams, L., & Muyekho, F. (2001). Habitat management strategies for the control of cereal stemborers and Striga in maize in Kenya. International Journal of Tropical Insect Science, 21(4), 375–380. https://doi.org/10.1017/S1742758400008481
Kim, S. -K. (1994). Genetics of Maize Tolerance of Striga hermonthica. Crop Science, 34(4), 900–907. https://doi.org/10.2135/cropsci1994.0011183X003400040012x
Kim, S. K., Adetimirin, V. O., The, C., & Dossou, R. (2002). Yield losses in maize due to Striga hermonthica in West and Central Africa. International Journal of Pest Management, 48(3), 211–217. https://doi.org/10.1080/09670870110117408
Kim, S. K., Akintunde, A. Y., & Walker, P. (1994). Responses of maize, sorghum and millet host plants to infestation by Striga hermonthica. Crop Protection, 13(8), 582–590.
Kountche, B. A., Hash, C. T., Dodo, H., Laoualy, O., Sanogo, M. D., Timbeli, A., Vigouroux, Y., This, D., Nijkamp, R., & Haussmann, B. I. (2013). Development of a pearl millet Striga-resistant genepool: Response to five cycles of recurrent selection under Striga-infested field conditions in West Africa. Field Crops Research, 154, 82–90. https://doi.org/10.1016/j.fcr.2013.07.008
Kulkarni, N., & Shinde, V. (1985). Genetic analysis of Striga resistance in sorghum parameters of resistance. Indian Journal of Genetics and Plant Breeding (India). Retrieved August 15, 2021, from https://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=7551116
Lopez, L., Bellis, E. S., Wafula, E., Hearne, S. J., Honaas, L., Ralph, P. E., Timko, M. P., Unachukwu, N., DePamphilis, C. W., & Lasky, J. R. (2019). Transcriptomics of host-specific interactions in natural populations of the parasitic plant purple witchweed (Striga hermonthica). Weed Science, 67(4), 397–411. https://doi.org/10.1017/wsc.2019.20
Makani, K. W., Rugare, J. T., Mabasa, S., Gasura, E., Makaza, W., Gwatidzo, O. V., Moyo, R., & Mandumbu, R. (2020). Screening finger millet (Eleusine coracana L. Gaertn) genotypes for pre and post-attachment resistance to witchweed (Striga asiatica L. Kuntze) infection under controlled environments. African Journal of Rural Development, 5(2), 125–139.
Makaza, W., Rugare, J. T., Mabasa, S., Gasura, E., Gwatidzo, O. V., & Mandumbu, R. (2021). In vivo and in vitro performance studies on groundnut (Acharis hypogea L.) genotypes for yellow witchweed (Alectra vogelii Benth.) resistance. Journal of Current Opinion in Crop Science, 2(2), 165–177.
Mallu, T. S., Mutinda, S., Githiri, S. M., Achieng Odeny, D., & Runo, S. (2021). New pre-attachment Striga resistant sorghum adapted to African agro-ecologies. Pest Management Science, 77(6), 2894–2902. https://doi.org/10.1002/ps.6325
Mandumbu, R., Mutengwa, C., Mabasa, S., & Mwenje, E. (2019). Challenges to the exploitation of host plant resistance for Striga management in cereals and legumes by farmers in sub-Saharan Africa: A Review. Acta Agriculturae Scandinavica, Section B-Soil & Plant Science, 69(1), 82–88. https://doi.org/10.1080/09064710.2018.1494302
Mbuvi, D. A., Masiga, C. W., Kuria, E. K., Masanga, J., Wamalwa, M., Mohamed, A., Odeny, D., Hamza, N., Timko, M. P., & Runo, S. M. (2017). Novel sources of witchweed (Striga) resistance from wild sorghum accessions. Fronties in Plant Science, 8, 116. https://doi.org/10.3389/fpls.2017.00116
McDonald, B. A., & Stukenbrock, E. H. (2016). Rapid emergence of pathogens in agro-ecosystems: Global threats to agricultural sustainability and food security. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1709), 20160026.
Mengesha, W. A., Menkir, A., Unakchukwu, N., Meseka, S., Farinola, A., Girma, G., & Gedil, M. (2017). Genetic diversity of tropical maize inbred lines combining resistance to Striga hermonthica with drought tolerance using SNP markers. Plant Breeding, 136(3), 338–343. https://doi.org/10.1111/pbr.12479
Menkir, A. (2006). Assessment of reactions of diverse maize inbred lines to Striga hermonthica (Del.) Benth. Plant Breeding, 125(2), 131–139. https://doi.org/10.1111/j.1439-0523.2006.01175.x
Menkir, A., & Kling, J. (2007). Response to recurrent selection for resistance to Striga hermonthica (Del.) Benth in a tropical maize population. Crop Science, 47(2), 674–682. https://doi.org/10.2135/cropsci2006.07.0494
Menkir, A., Kling, J., Badu-Apraku, B., & Ibikunle, O. (2006). Registration of 26 tropical maize germplasm lines with resistance to Striga hermonthica. Crop Science, 46(2), 1007. https://doi.org/10.2135/cropsci2018.12.0749
Menkir, A., & Meseka, S. (2019). Genetic improvement in resistance to Striga in tropical maize hybrids. Crop Science, 59, 1–14. https://doi.org/10.2135/cropsci2018.12.0749
Mohamed, A., Ellicott, A., Housley, T., & Ejeta, G. (2003). Hypersensitive response to Striga infection in sorghum. Crop Science, 43(4), 1320–1324. https://doi.org/10.2135/cropsci2003.1320
Mohemed, N., Charnikhova, T., Bakker, E. J., van Ast, A., Babiker, A. G., & Bouwmeester, H. J. (2016). Evaluation of field resistance to Striga hermonthica (Del.) Benth. in Sorghum bicolor (L.) Moench. The relationship with strigolactones. Pest Management Science, 72(11), 2082–2090. https://doi.org/10.1002/ps.4426
Mounde, L. G., Anteyi, W. O., & Rasche, F. (2020). Tripartite interaction between Striga spp., cereals, and plant root-associated microorganisms: A review. CAB Rev, 15(005). https://doi.org/10.1079/PAVSNNR202015005
Mrema, E., Shimelis, H., & Laing, M. (2020). Combining ability of yield and yield components among Fusarium oxysporum f. sp. Strigae-compatible and Striga-resistant sorghum genotypes. Acta Agriculturae Scandinavica, Section B-Soil & Plant Science, 70(2), 95–108. https://doi.org/10.1080/09064710.2019.1674915
Mrema, E., Shimelis, H., Laing, M., & Bucheyeki, T. (2017). Screening of sorghum genotypes for resistance to Striga hermonthica and S. asiatica and compatibility with Fusarium oxysporum f.sp. Strigae. Acta Agriculturae Scandinavica, Section B - Soil & Plant Science, 67(5), 395–404. https://doi.org/10.1080/09064710.2017.1284892
Muchira, N., Ngugi, K., Wamalwa, L. N., Avosa, M., Chepkorir, W., Manyasa, E., Nyamongo, D., & Odeny, D. A. (2021). Genotypic Variation in Cultivated and Wild Sorghum Genotypes in Response to Striga hermonthica Infestation. Frontiers in Plant Science, 12, 671984. https://doi.org/10.3389/fpls.2021.671984
Mudereri, B. T., Abdel-Rahman, E. M., Dube, T., Landmann, T., Khan, Z., Kimathi, E., Owino, R., & Niassy, S. (2020). Multi-source spatial data-based invasion risk modeling of Striga (Striga asiatica) in Zimbabwe. Giscience & Remote Sensing, 57(4), 553–571. https://doi.org/10.1080/15481603.2020.1744250
Mutinda, S. M., Masanga, J., Mutuku, J. M., Runo, S., & Alakonya, A. (2018). KSTP 94, an open-pollinated maize variety has postattachment resistance to purple witchweed (Striga hermonthica). Weed Science, 66(4), 525–529. https://doi.org/10.1017/wsc.2018.24
Mutuku, J. M., Cui, S., Hori, C., Takeda, Y., Tobimatsu, Y., Nakabayashi, R., Mori, T., Saito, K., Demura, T., & Umezawa, T. (2019). The structural integrity of lignin is crucial for resistance against Striga hermonthica parasitism in rice. Plant Physiology, 179(4), 1796–1809. https://doi.org/10.1104/pp.18.01133
Mutuku, J. M., Yoshida, S., Shimizu, T., Ichihashi, Y., Wakatake, T., Takahashi, A., Seo, M., & Shirasu, K. (2015). The WRKY45-dependent signaling pathway is required for resistance against Striga hermonthica parasitism. Plant Physiology, 168(3), 1152–1163. https://doi.org/10.1104/pp.114.256404
Mwangangi, I. M., Büchi, L., Haefele, S. M., Bastiaans, L., Runo, S., & Rodenburg, J. (2021). Combining host plant defence with targeted nutrition: Key to durable control of hemiparasitic Striga in cereals in sub-Saharan Africa? New Phytologist, 230(6), 2164–2178. https://doi.org/10.1111/nph.17271
Nyakurwa, C. S., Gasura, E., Setimela, P. S., Mabasa, S., Rugare, J. T., & Mutsvanga, S. (2018). Reaction of new quality protein maize genotypes to Striga asiatica. Crop Science, 58(3), 1201–1218. https://doi.org/10.2135/cropsci2017.10.0639
Nyongesa, S. P., Simiyu, W. D., Chrispus, O., Achieng, O. D., & George, D. O. (2018). Molecular characterization of global finger millet (Eleusine coracana, L. Gaertn) germplasm reaction to Striga in Kenya. Asian Journal of Biochemistry, Genetics and Molecular Biology, 1(2), 1–14.
Olivier, A., Ramaiah, K., & Leroux, G. (1991). Selection of sorghum (Sorghum bicolor (L.) Moench) varieties resistant to the parasitic weed Striga hermonthica (Del.) Benth. Weed Research, 31(4), 219–225. https://doi.org/10.1111/j.1365-3180.1991.tb01761.x
Oswald, A., & Ransom, J. (2004). Response of maize varieties to Striga infestation. Crop Proctection, 23(2), 89–94. https://doi.org/10.1016/S0261-2194(03)00173-X
Ould Estaghvirou, S. B., Ogutu, J. O., Schulz-Streeck, T., Knaak, C., Ouzunova, M., Gordillo, A., & Piepho, H.-P. (2013). Evaluation of approaches for estimating the accuracy of genomic prediction in plant breeding. BMC Genomics, 14(1), 1–21. https://doi.org/10.1186/1471-2164-14-860
Parker, C., & Riches, C. R. (1993). Parasitic weeds of the world: biology and control. Wallingford (UK) CAB International. Retrieved September 11, 2021, from https://www.cabdirect.org/cabdirect/abstract/19942301534
Pfunye, A., Rwafa, R., Mabasa, S., & Gasura, E. (2021). Genome-Wide Association Studies for Striga asiatica Resistance in Tropical Maize. International Journal of Genomics, 2021, 9979146. https://doi.org/10.1155/2021/9979146
Press, M., & Stewart, G. (1987). Growth and photosynthesis in Sorghum bicolor infected with Striga hermonthica. Annals of Botany, 60(6), 657–662. https://doi.org/10.1093/oxfordjournals.aob.a087496
Ramaiah, K. (1983). Patterns of Striga resistance in sorghum and millets with special emphasis on Africa. ICRISAT. Conference Paper No. 186. Retrieved December 5, 2021, from http://oar.icrisat.org/4142/1/CP_186.pdf
Rich, P. J., & Ejeta, G. (2007). Biology of Host-Parasite Interactions in Striga species. Integrating New Technologies for Striga Control (pp. 19–32). World Scientific. https://doi.org/10.1142/9789812771506_0002
Rich, P. J., & Ejeta, G. (2008). Towards effective resistance to Striga in African maize. Plant Signaling & Behavior, 3(9), 618–621. https://doi.org/10.4161/psb.3.9.5750
Rich, P. J., Grenier, C., & Ejeta, G. (2004). Striga resistance in the wild relatives of sorghum. Crop Science, 44(6), 2221–2229. https://doi.org/10.2135/cropsci2004.2221
Rodenburg, J., Bastiaans, L., Schapendonk, A. H., van der Putten, P. E., van Ast, A., Dingemanse, N. J., & Haussmann, B. I. (2008). CO2-assimilation and chlorophyll fluorescence as indirect selection criteria for host tolerance against Striga. Euphytica, 160(1), 75–87. https://doi.org/10.1007/s10681-007-9555-7
Rodenburg, J., Bastiaans, L., Weltzien, E., & Hess, D. E. (2005). How can field selection for Striga resistance and tolerance in sorghum be improved? Field Crops Research, 93(1), 34–50. https://doi.org/10.1016/j.fcr.2004.09.004
Rodenburg, J., Cissoko, M., Kayeke, J., Dieng, I., Khan, Z. R., Midega, C. A., Onyuka, E. A., & Scholes, J. D. (2015). Do NERICA rice cultivars express resistance to Striga hermonthica (Del.) Benth. and Striga asiatica (L.) Kuntze under field conditions? Field Crops Research, 170, 83–94. https://doi.org/10.1016/j.fcr.2014.10.010
Rodenburg, J., Demont, M., Zwart, S. J., & Bastiaans, L. (2016). Parasitic weed incidence and related economic losses in rice in Africa. Agriculture, Ecosystems & Environment, 235, 306–317. https://doi.org/10.1016/j.agee.2016.10.020
Rodenburg, J., Cissoko, M., Kayongo, N., Dieng, I., Bisikwa, J., Irakiza, R., Masoka, I., Midega, C. A., & Scholes, J. D. (2017). Genetic variation and host–parasite specificity of Striga resistance and tolerance in rice: The need for predictive breeding. New Phytologist, 214(3), 1267–1280. https://doi.org/10.1111/nph.14451
Roger, Z. G., Ramaiah K. V., & Vasudeva Rao, M. J. (1981). Screening of pearl millet cultivars for resistance to Striga hermonthica. KV Ramaiah and MJ Vasudeva Rao, 83. International Crops Research Institute for the Semi-Arid Tropics. 1983. Proceedings of the Second International Workshop on Striga, 5–8 October 1981, IDRC/ICRISAT, Ouagadougou, Upper Volta. Patancheru, A.P., India: ICRISAT.
Ronald, M., Charles, M., Stanford, M., & Eddie, M. (2016). Existence of different physiological ‘strains’ of Striga asiatica (L.) Kuntze on sorghum species [Sorghum bicolor (L.) Moench and Sorghum arundinaceum (Desv.) Stapf] in Zimbabwe. Research on Crops, 17(3), 468–478. https://doi.org/10.5958/2348-7542.2016.00077.2
Runo, S. (2019). Modern Breeding Approaches for Durable Resistance Against the Parasitic Plant Striga . Afrika Focus, 32(2), 109–115.
Runo, S., & Kuria, E. K. (2018). Habits of a highly successful cereal killer, Striga. PLoS Pathogens, 14(1), e1006731. https://doi.org/10.1371/journal.ppat.1006731
Samejima, H., Babiker, A. G., Takikawa, H., Sasaki, M., & Sugimoto, Y. (2016). Practicality of the suicidal germination approach for controlling Striga hermonthica. Pest Management Science, 72(11), 2035–2042. https://doi.org/10.1002/ps.4215
Samejima, H., & Sugimoto, Y. (2018). Recent research progress in combatting root parasitic weeds. Biotechnology & Biotechnological Equipment, 32(2), 221–240. https://doi.org/10.1080/13102818.2017.1420427
Satish, K., Gutema, Z., Grenier, C., Rich, P. J., & Ejeta, G. (2012). Molecular tagging and validation of microsatellite markers linked to the low germination stimulant gene (lgs) for Striga resistance in sorghum [Sorghum bicolor (L.) Moench]. Theoretical and Applied Genetics, 124(6), 989–1003. https://doi.org/10.1007/s00122-011-1763-9
Savary, S., Willocquet, L., Pethybridge, S. J., Esker, P., McRoberts, N., & Nelson, A. (2019). The global burden of pathogens and pests on major food crops. Nature Ecology & Evolution, 3(3), 430–439. https://doi.org/10.1038/s41559-018-0793-y
Scholes, J. D., & Press, M. C. (2008). Striga infestation of cereal crops–an unsolved problem in resource limited agriculture. Current Opinion in Plant Biology, 11(2), 180–186. https://doi.org/10.1016/j.pbi.2008.02.004
Setimela, P., Gasura, E., Thierfelder, C., Zaman-Allah, M., Cairns, J. E., & Boddupalli, P. M. (2018). When the going gets tough: Performance of stress tolerant maize during the 2015/16 (El Niño) and 2016/17 (La Niña) season in southern Africa. Agriculture, Ecosystems & Environment, 268, 79–89. https://doi.org/10.1111/j.1399-3054.1987.tb01987.x
Shah, N., Smirnoff, N., & Stewart, G. (1987). Photosynthesis and stomatal characteristics of Striga hermonthica in relation to its parasitic habit. Physiologia Plantarum, 69(4), 699–703.
Shaibu, A. S., Badu-Apraku, B., & Ayo-Vaughan, M. A. (2021). Enhancing drought tolerance and Striga hermonthica resistance in maize using newly derived inbred lines from the wild maize relative. Zea Diploperennis. Agronomy, 11(1), 177. https://doi.org/10.3390/agronomy11010177
Shayanowako, A., Shimelis, H., Laing, M., & Mwadzingeni, L. (2018). Genetic diversity of maize genotypes with variable resistance to Striga asiatica based on SSR markers. Cereal Research Communications, 46(4), 668–678. https://doi.org/10.1556/0806.46.2018.044
Smith, L. H., Keys, A. J., & Michael, C. E. (1995). Striga hermonthica decreases photosynthesis in Zea mays through effects on leaf cell structure. Journal of Experimental Botany, 46(7), 759–765. https://doi.org/10.1093/jxb/46.7.759
Stanley, A., Menkir, A., Ifie, B., Paterne, A., Unachukwu, N., Meseka, S., Mengesha, W., Bossey, B., Kwadwo, O., & Tongoona, P. (2021). Association analysis for resistance to Striga hermonthica in diverse tropical maize inbred lines. Scientific Reports, 11(1), 1–14. https://doi.org/10.1038/s41598-021-03566-4
Stewart, G. R., & Press, M. C. (1990). The physiology and biochemistry of parasitic angiosperms. Annual Review of Plant Biology, 41(1), 127–151. https://doi.org/10.1146/annurev.pp.41.060190.001015
Swarbrick, P. J., Scholes, J. D., Press, M. C., & Slate, J. (2009). A major QTL for resistance of rice to the parasitic plant Striga hermonthica is not dependent on genetic background. Pest Management Science: Formerly Pesticide Science, 65(5), 528–532. https://doi.org/10.1002/ps.1719
Tamir, H. D. (2021). Application of Marker Assisted Selection for Striga Hermonthica Resistance on Sorghum (Sorghum bicolor (L.) Moench. Asian Plant Research Journal, 7(3), 15–26. https://doi.org/10.9734/APRJ/2021/v7i330155
Taniguchi, Y., Ohkawa, H., Masumoto, C., Fukuda, T., Tamai, T., Lee, K., Sudoh, S., Tsuchida, H., Sasaki, H., & Fukayama, H. (2008). Overproduction of C4 photosynthetic enzymes in transgenic rice plants: An approach to introduce the C4-like photosynthetic pathway into rice. Journal of Experimental Botany, 59(7), 1799–1809. https://doi.org/10.1093/jxb/ern016
Timko, M. P., Huang, K., & Lis, K. E. (2012). Host resistance and parasite virulence in Striga–host plant interactions: A shifting balance of power. Weed Science, 60(2), 307–315. https://doi.org/10.1614/WS-D-11-00039.1
Unachukwu, N., Menkir, A., Rabbi, I. Y., Oluoch, M., Muranaka, S., Elzein, A., Odhiambo, G., Farombi, E., & Gedil, M. (2017). Genetic diversity and population structure of Striga hermonthica populations from Kenya and Nigeria. Weed Research, 57(5), 293–302. https://doi.org/10.1111/wre.12260
Usman, A., Adagba, M. A., Olaniyan, G. O., & Adenihun, M. A. (2001). Preliminary evaluation of improved maize varieties for tolerance to Striga hermonthica at Mokwa, Nigeria. Acta Agronomica Hungarica, 48(4), 419–421. https://doi.org/10.1556/AAgr.48.2000.4.13
Van Ittersum, M. K., Van Bussel, L. G., Wolf, J., Grassini, P., Van Wart, J., Guilpart, N., Claessens, L., De Groot, H., Wiebe, K., Mason-D’Croz, D., & Yang, H. (2016). Can sub-Saharan Africa feed itself? Proceedings of the National Academy of Sciences, 113(52), 14964–14969.
Wada, S., Cui, S., & Yoshida, S. (2019). Reactive oxygen species (ROS) generation is indispensable for haustorium formation of the root parasitic plant Striga hermonthica. Frontiers in Plant Science, 10, 328. https://doi.org/10.3389/fpls.2019.00328
Watling, J., & Press, M. (1997). How is the relationship between the C4 cereal Sorghum bicolor and the C3 root hemi-parasites Striga hermonthica and Striga asiatica affected by elevated CO2? Plant, Cell and Environment, 20(10), 1292–1300. https://doi.org/10.1046/j.1365-2486.2000.00366.x
Watling, J. R., & Press, M. C. (2000). Infection with the parasitic angiosperm Striga hermonthica influences the response of the C3 cereal Oryza sativa to elevated CO2. Global Change Biology, 6(8), 919–930. https://doi.org/10.1046/j.1365-3040.1997.d01-19.x
Weerasuriya, Y., Siame, B. A., Hess, D., Ejeta, G., & Butler, L. G. (1993). Influence of conditions and genotype on the amount of Striga germination stimulants exuded by roots of several host crops. Journal of Agricultural and Food Chemistry, 41(9), 1492–1496. https://doi.org/10.1021/jf00033a026
Westwood, J. H., Depamphilis, C. W., Das, M., Fernández-Aparicio, M., Honaas, L. A., Timko, M. P., Wafula, E. K., Wickett, N. J., & Yoder, J. I. (2012). The parasitic plant genome project: New tools for understanding the biology of Orobanche and Striga. Weed Science, 60(2), 295–306. https://doi.org/10.1614/WS-D-11-00113.1
Wilson, J., Hess, D., Hanna, W., Kumar, K., & Gupta, S. (2004). Pennisetum glaucum subsp. monodii accessions with Striga resistance in West Africa. Crop Protection, 23(9), 865–870. https://doi.org/10.1016/j.cropro.2004.01.006
Yacoubou, A. M., Zoumarou Wallis, N., Menkir, A., Zinsou, V. A., Onzo, A., Garcia-Oliveira, A. L., Meseka, S., Wende, M., Gedil, M., & Agre, P. (2021). Breeding maize (Zea mays) for Striga resistance: Past, current and prospects in sub-saharan africa. Plant Breeding, 140(2), 195–210. https://doi.org/10.1111/pbr.12896
Yallou, C. G., Menkir, A., Adetimirin, V. O., & Kling, J. G. (2009). Combining ability of maize inbred lines containing genes from Zea diploperennis for resistance to Striga hermonthica (Del.) Benth. Plant breeding, 128(2), 143–148. https://doi.org/10.1111/j.1439-0523.2008.01583.x
Yang, D., Li, Y., Shi, Y., Cui, Z., Luo, Y., Zheng, M., Chen, J., Li, Y., Yin, Y., & Wang, Z. (2016). Exogenous cytokinins increase grain yield of winter wheat cultivars by improving stay-green characteristics under heat stress. Plos One, 11(5), e0155437. https://doi.org/10.1371/journal.pone.0155437
Yohannes, T., Abraha, T., Kiambi, D., Folkertsma, R., Hash, C. T., Ngugi, K., Mutitu, E., Abraha, N., Weldetsion, M., & Mugoya, C. (2015). Marker-assisted introgression improves Striga resistance in an eritrean farmer-preferred sorghum variety. Field Crops Research, 173, 22–29. https://doi.org/10.1016/j.fcr.2014.12.008
Yoneyama, K. (2020). Recent progress in the chemistry and biochemistry of strigolactones. Journal of Pesticide Science, 45(2), 45–53. https://doi.org/10.1584/jpestics.D19-084. D19–084.
Yoneyama, K., Xie, X., Nomura, T., & Yoneyama, K. (2020). Do phosphate and cytokinin interact to regulate strigolactone biosynthesis or act independently? Frontiers in Plant Science, 11, 438–447. https://doi.org/10.3389/fpls.2020.00438
Yoneyama, K., Awad, A. A., Xie, X., Yoneyama, K., & Takeuchi, Y. (2010). Strigolactones as germination stimulants for root parasitic plants. Plant and Cell Physiology, 51(7), 1095–1103. https://doi.org/10.1093/pcp/pcq055
Yoneyama, K., Arakawa, R., Ishimoto, K., Kim, H. I., Kisugi, T., Xie, X., Nomura, T., Kanampiu, F., Yokota, T., Ezawa, T., & Yoneyama, K. (2015). Difference in Striga-susceptibility is reflected in strigolactone secretion profile, but not in compatibility and host preference in arbuscular mycorrhizal symbiosis in two maize cultivars. New Phytologist, 206(3), 983–989. https://doi.org/10.1111/nph.13375
Yoshida, S., Kim, S., Wafula, E. K., Tanskanen, J., Kim, Y.-M., Honaas, L., Yang, Z., Spallek, T., Conn, C. E., & Ichihashi, Y. (2019). Genome sequence of Striga asiatica provides insight into the evolution of plant parasitism. Current Biology, 29(18), 3041–3052. https://doi.org/10.1016/j.cub.2019.07.086
Yoshida, S., & Shirasu, K. (2012). Plants that attack plants: Molecular elucidation of plant parasitism. Current Opinion in Plant Biology, 15(6), 708–713. https://doi.org/10.1016/j.pbi.2012.07.004
Zebire, D., Menkir, A., Adetimirin, V., Mengesha, W., Meseka, S., & Gedil, M. (2020). Effectiveness of yellow maize testers with varying resistance reactions to Striga hermonthica for evaluating the combining ability of maize inbred lines. Agronomy, 10(9), 1276. https://doi.org/10.3390/agronomy10091276
Zwanenburg, B., & Pospíšil, T. (2013). Structure and activity of strigolactones: New plant hormones with a rich future. Molecular Plant, 6(1), 38–62. https://doi.org/10.1093/mp/sss141
Acknowledgements
The present study is part of the activities of the African Integrated Plant and Soil Research Group (AiPLaS) at Mohammed VI Polytechnic University (UM6P).
Author information
Authors and Affiliations
Contributions
WM, MA: Conceptualized and designed the review. WM: investigated materials, performed formal analysis and drafted wrote the review paper. MA, YE: revised and edited the review paper. MA: review and editing, Supervision. All authors approved the final manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Makaza, W., En-nahli, Y. & Amri, M. Harnessing plant resistance against Striga spp. parasitism in major cereal crops for enhanced crop production and food security in Sub-Saharan Africa: a review. Food Sec. 15, 1127–1149 (2023). https://doi.org/10.1007/s12571-023-01345-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12571-023-01345-9