Seed storage proteins and seed coat compounds additively influence Callosobruchus maculatus Fab. tolerance in selected cowpea (Vigna unguiculata L. Walp.) varieties

The cowpea weevil, Callosobruchus maculatus, is a major threat to stable cowpea production, especially in storage, and has been reported to facilitate postharvest losses in cowpea grains. Host resistance has been suggested as the best control method but with conflicting knowledge on the source of resistance. Hence, the study seeks to evaluate seed storage proteins (SSPs) and seed coat compounds (SCCs) associated with tolerance to C. maculatus. SSPs and SCCs were assayed and associated with C. maculatus tolerance in 19 cowpea varieties with varied tolerance levels using a stepwise multiple regression analysis. Top C. maculatus tolerants were TVu‐2027, TVu‐11952, TVu‐11953, and TVu‐145. The protein fraction with a mass of 51 kDa was a significant predictor associated with percentage adult insect emergence (PAE) and host suitability index (H.S.I.), and 57 and 71 kDa were associated with mean development period (MDP) whereas 59 and 131 kDa were associated with seed damage tolerance (TolSD). Several SCCs identified were associated with the C. maculatus tolerant measures used in the study. However, Thiazole, tetrahydro‐ and Undecane were consistently identified with C. maculatus tolerance. Higher phenotypic variability was accounted for by SCC than SSP fractions associated with C. maculatus tolerance in the study indicating that SCCs contributed more to the C. maculatus tolerance than the SSPs identified. These compounds can be incorporated into breeding for C. maculatus tolerant in cowpea and biopesticide formulations whereas cowpea varieties with the high or significant amount of these compounds can also be recommended to the farmers or to the cowpea producers.


| INTRODUCTION
The major threat to stable cowpea production, especially in storage is the cowpea weevil, Callosobruchus maculatus.This crop pest has been reported as a menace facilitating postharvest losses in cowpea grains causing at least 60% loss because of perforations on the grain seeds (Amusa et al., 2019;Baoua et al., 2012;Ogunkanmi et al., 2018).As a result, the seeds' utility is reduced and no longer suitable for either consumption or cultivation, thus lowering their market value (Amusa et al., 2019).
Several methods for the management of the storage pest have been used to control C. maculatus in storage; among which, chemical treatment has proven to be the most effective.However, in addition to being costly, the use of synthetic insecticides in food grain storage has detrimental impacts on both man and animal health, as well as on beneficial organisms resulting in widespread environmental pollution and biodiversity loss (Isman, 2008).Farmers alternatively utilize inert materials such as kaolin dust and certain biopesticides derived from local items such as citrus zest, neem extract, and chili, including some botanicals such as Artemisia annua, Anacardium occidentale, and Ocimum gratissimum (Akunne et al., 2013;Brisibe et al., 2011;Ileke, 2019;Kpoviessi et al., 2019Kpoviessi et al., , 2017)).Although these local biopesticides have been shown to pose few health and environmental risks, their effectiveness is limited.Large quantities of such treatments are normally necessary to effectively control pests, and accessing such an amount may not always be possible.As a result, C. maculatus resistant or tolerant cowpea cultivars are the best alternatives for the effective protection of cowpea seeds from C. maculatus damage (Fawki et al., 2013;Tripathi et al., 2015).
Unfortunately, cowpea varieties resistant or tolerant to C. maculatus are not easily identified.Three accessions, TVu-2027, TVu-11952, and TVu-11953, from Nigerian landraces, were initially identified after screening more than 3000 germplasms at the International Institute of Tropical Agriculture (IITA), Ibadan; and TVu-2027 has been employed in the breeding and developing of other varieties in combination with other useful agronomical traits (Singh & Singh, 1990).However, resistance breakdowns have been reported among the elite varieties deployed by farmers to mitigate storage loss because of the C. maculatus (Amusa et al., 2014;Amusa & Ogunkanmi, 2021).
Understanding the nature and mechanisms of pest resistance is an important prerequisite for developing an effective and efficient strategy for breeding resistant varieties against C. maculatus damage (Miesho et al., 2017).Resistance encompasses biochemical, physiological, morphological, and/or responses that range from merely limiting the impact of insect assault to negatively influencing the insects' developmental processes and growth (Singh, 2002;Tripathi et al., 2013).Several authors have based the resistance of cowpea against C. maculatus to be morphologically induced, which includes wrinkling or smooth and dull color of seed coats deterring oviposition hence reducing seed damage (Mogbo et al., 2014;Murdock et al., 2003;Nwanze et al., 1975); seed size, the bigger the seed the more it provides nutrition for the growing larva.Hence, the smaller the size of seed the more resistant it is to C. maculatus (Soumia et al., 2017).However, reports from Amusa et al. (2013Amusa et al. ( , 2014) ) in the evaluation of selected tolerant cowpea varieties revealed that seed coat nature, seed color, and seed size did not influence the tolerance or resistance against the C. maculatus but favor a biochemical mechanism of resistance instead.Similarly, studies have shown that the texture, shape, seed coat thickness, or color of cowpea seeds were not related to resistance or susceptibility to C. maculatus (Cruz et al., 2016;Tripathi et al., 2020).
The biochemical mechanism is a more likely explanation for C. maculatus tolerance in cowpea (Sales et al., 2001(Sales et al., , 2005)), as both seed storage proteins (SSPs) and seed coat compounds (SSCs) have been associated with resistance against the C. maculatus in several studies (Amusa et al., 2014;Lattanzio et al., 2005;Miesho et al., 2017;Ojwang et al., 2012).However, there have been conflicting reports from several authors as to which of these is the actual source and/or compound(s) associated with C. maculatus tolerance in cowpea.
Although SSPs like trypsin inhibitors, α-amylase inhibitors, vicilin, and carbohydrates (Gatehouse et al., 1979;Lattanzio et al., 2005;Miesho et al., 2017) and seed compounds like phenolic acids, tannins, and flavonoids (Ojwang et al., 2012) have been linked to C. maculatus resistance in cowpea, there have been contrary findings annulling previous assertions (Baker et al., 1989;Edde & Amatobi, 2003;Lattanzio et al., 2005).Also, in most of these studies, especially using plant material models against C. maculatus infestation and/or damage, phytocompounds of potential plants are usually identified without necessarily trying to find out which of the compounds identified as the active agent against the C. maculatus (Ebadollahi & Taghinezhad, 2020;Ishola et al., 2017;Kpoviessi et al., 2017).Hence, the study seeks to evaluate SSPs and SCCs associated with C. maculatus tolerance in cowpea.We further evaluate the possible additive interaction between potential SCCs' and SSPs' influence on C. maculatus tolerance.

| Collection of samples
The study was conducted at the Central Research Laboratory, University of Lagos, Nigeria.A total of 19 cowpea samples were used for the study (Table 1).Samples were collected from the International Insti-  2027, TVu-11952, andTVu-11953 (Amusa &Ogunkanmi, 2021;Singh et al., 1985), were also included in the study, whereas Ife brown, an established C. maculatus susceptible variety, was used a susceptibility check.All varieties used in the study were first checked for seed damage and oven dried for 24 h at 60 C to destroy any C. maculatus egg or larvae present, as well as to dry the seeds to a uniform and safe moisture content before use.
Ife brown was used as a susceptible host for the C. maculatus culture.
This variety was infected with C. maculatus obtained from already established cultures.Insects used for the study were locally collected from infected field seeds and identified as C. maculatus at the Department of Zoology.The colony culture was established on Ife brown seeds at the Central Research Laboratory, University of Lagos, Nigeria.Emerged adult insects were re-introduced into fresh cultures of susceptible seeds setup culture jars (10 cm Â 17 cm filled with 700 g of susceptible seeds), from which emerged insects used for the study were drawn.Five days following their introduction, insects were carefully removed using tweezers to avoid damaging the laid eggs by shaking.The colonies that resulted were grown at a temperature of 25-30 C and relative humidity (RH) of 55-60% (Amusa et al., 2014;Amusa & Ogunkanmi, 2021).

| Bioassay for C. maculatus tolerance
The C. maculatus tolerance bioassay was conducted under a no-choice condition according to Amusa et al. (2014).Two pairs of recently emerging adult C. maculatus (two males and two females) were placed into a setup of pre-weighed seeds (n = 10) in a 90 mm Â 15 mm petri dish.The insects were left in the Petri dishes with the seeds for 3 days in the dark at 28 C and 60% RH, allowing for mating and oviposition before being removed.The experiment was set up in a randomized complete design with five replicates, and control was set up for each cowpea variety with no weevil introduction.After insect removal, oviposited eggs were counted and recorded for each replicate per variety.The experiment was left for 60 days while the number of adult emergences was counted and removed daily every 12 h.So also, the number of seeds damaged was counted at the end of the experiment.

| Extraction of seed proteins
Seed protein profiling was carried out with modifications to Sonker et al. (2018).Ten seeds of each variety evaluated were dehulled and then ground into a fine powder using a mortar and pestle.This was then mixed with 500 μL of extraction buffer (0.5 M Tris HCl pH 8.0, containing 0.2% sodium dodecyl sulphate [SDS], 5 M urea and 1% β-mercaptoethanol).The mixture was mixed by vortexing for 10 s and centrifuged at 15,000 rpm for 5 min.The supernatants of the samples were transferred into new Eppendorf tubes and stored at À20 C until required for use.stacking gel (0.9 mL 40% acrylamide, 1.3 mL 0.5 M Tris pH 6.3, 80 μL 10% APS, 5 μL TEMED, 3.0 ddH 2 O).All reagents used in the study were purchased from Carl Roth GmbH, Karlsruhe, Germany.The setup was run at 150 V for 2 h, and the resulting gel was then stained in silver nitrate before visualization.Protein bands were quantified using GelAnalyzer 19.1 (Lazar & Lazar, 2019).

| Preparation of seed coat
Seed coat extraction was performed with modification to Hudaib et al. (2017) procedure.Between 18 and 20 g of seeds of each variety were soaked in distilled water for 40-45 min, and seed coats were removed.Seed coats were then dried at room temperature before being milled into a fine powder and then soaked in 70% ethanol, in a ratio of 1:5 for the sample to solvent.The mixture was allowed to stand for 14 days.Extracts were suction-filtered and evaporated to dryness in a rotating evaporator under vacuum and kept at 4 C until required.

| Gas chromatography-mass spectrometry (GC-MS) analysis
The GC-MS analysis was carried out in a GC-MS instrument (Model GC Agilent Tech 7890 coupled with an MS Agilent Tech 5975, USA) equipped with a capillary column Model Agilent Tech HP5 M5, USA (30 m length Â 0.32 mm internal diameter Â 0.25 μm film).The oven temperature was initially programed at 80 C (isothermal for 2 mins and then increased to 240 C at a rate of 12 C/min (isothermal for 6 min).One microliter of the sample was injected and transported down the column into the port, and then vaporized and moved down the column using helium as the carrier gas at a flow rate of 1 mL/min.
The apparatus was run in electron impact mode with an ionization voltage of 70 eV and an injector temperature of 250 C. The identification of compounds from the data was based on the mass spectral records that were available (NIST MS 2.0 library).

| Analysis of data
All analysis was carried out using RStudio in R 4.2.1 (R Core Team, 2022).Data generated were subjected to descriptive analysis, and correlation analysis was carried out to assess relationships among evaluated parameters.

| Bioassay evaluation
To ascertain C. maculatus tolerance among the varieties evaluated, five (5) tolerance measures were used.These measures include the following: 1. Percentage adult insect emergence (PAE): This is the proportion of laid eggs that emerged as adult insects from the seeds (Amusa et al., 2018).

PAE ¼ Number of adult insects emerged
Total number of eggs laid Â 100 2. Mean development period (MDP) was evaluated according to Amusa et al. (2018) as shown below: where MDP is the mean development period (days), x is the average development period for cumulative adult insects in each experimental replicate setup and calculated as Where PAE is the percentage of adult insect emergence in relation to the number of eggs laid and PSD is the percentage of seeds damaged as shown below: PSD ¼ Total number of damged seeds Total number of initial seeds used Â 100 5. Seed damage tolerance (TolSD) was evaluated according to Amusa et al. (2014) as shown below: where PSD is the percentage seed damaged per petri dish.We considered one damaged seed as one damage in the study.
Data generated from bruchid tolerance measures were log transformed and standardized before being used to construct a heatmap performance dendrogram (Kolde, 2019).

| C. maculatus tolerance association analysis
Association between profiles and C. maculatus tolerance was carried out using the stepwise multiple regression analysis following the method of Vázquez-Ovando et al. (2018) as shown in the model below: where Y is the dependent variable (tolerance measure) as a linear function of the set of independent variables (mj) represented by the SSP profile markers or SCCs.The bj terms are the partial regression coefficients that specify the empirical relationships between Y and mj, d represents the residual values between varieties after regression, and e is the random error of Y that includes other variations not captured.To select the independent variables for the regression equation model, F values with .045and .099probabilities were used as "enter" and "removal" criteria, respectively.The relationship between identified predictors and bruchid tolerance measures was presented using a Chord Diagram function in R (Gu et al., 2014).

| C. maculatus tolerance of varieties evaluated
A description of the parameters used in the study is presented in    observed that the lower the PAE and H.S.I., the higher the C. maculatus tolerance among evaluated varieties, whereas the higher the MDP, Tol, and TolSD, the higher the C. maculatus tolerance in the study.

| Relationship between C. maculatus tolerance measures and other parameters recorded
Correlation analysis among evaluated traits in the study revealed diverse significant associated relationships (Table 4).There was a significant relationship between the number of eggs laid and initial seed

| Protein fractions associated with C. maculatus tolerance
In the present study, 64 unique seed protein fractions (bands) ranging from 21 to 169 kDa were identified among the samples evaluated.
The study further revealed six fractions, two fractions, three fractions, and eight fractions in a stepwise regression model associated with found to be associated with Tol in the study (Table 5).So also, thiazole, tetrahydro-was an associated compound in all C. maculatus tolerance measures used in the study except MDP (Table 6).
There was a positive significant correlation between MDP with Acet-

| Analysis of seed storage proteins and seed coat compounds that additively contribute to C. maculatus tolerance
In the present study, the C. maculatus tolerance variability accounted for by the combination of SSPs and SCCs ranged between 63% in Tol and 100% in PAE (Table 8).Another variety, TVu-145 with a poor performance in PAE but moderate performance with MDP and H.S.I., and high performance with Tol and TolSD measures, was clustered with the high C. maculatus tolerant varieties.Hence, the evaluated varieties were grouped into highly tolerant varieties (TVu-2027, TVu-145, TVu-11952, and TVu-11953), moderately tolerant/susceptible varieties (Drum, IT84S-2246-4, TVu-13076, TVu-3746, TVu-100, and TVu-11883), and susceptible varieties (BBR, TVu-12277, Ife brown, TVu-13868, TVu-14065, TVu-3629, Oloyin, and TVu-125113) using their combine C. maculatus tolerance performances.Some of these genotypic categories are similar to previously reported categories by Amusa and Ogunkanmi (2021).However, the present status for IT84S-2246-4 did not corroborate with Amusa et al. (2013) and Amusa and Ogunkanmi (2021) where it exhibited a poor performance using only seed damage as a C. maculatus tolerant measure.Dugje et al. (2009)  Hypothesis 1.There are some seed proteins involved in C. maculatus tolerance.
Plants have evolved extensive defense systems, the majority of which are concentrated in the seeds, which serve as carriers for the species' multiplication and survival.Seed tissues can accumulate a wide range of defensive chemicals that give resistance against phytophagous predators and infection by viruses, bacteria, fungi, nematodes, and so on, either constitutively or after induction (Carlini & Grossi-De-Sá, 2002).Hence, several SSPs which include lectin, protease inhibitors, alpha-amylase inhibitors, arcelin, trypsin inhibitors, ureases, and vicilin have been associated with tolerance against bruchid depending on the bruchid species and legume (Carlini & Grossi-De-Sá, 2002;Gatehouse et al., 1979;Guo et al., 2012;Lattanzio et al., 2005;Maro et al., 2022;Miesho et al., 2017).The current study revealed 18 protein fractions associated with the various C. maculatus tolerance measures evaluated accounting for varied C. maculatus tolerance phenotypic variations.However, studies have reported other protein fractions associated with C. maculatus resistance.A novel protein 40 kDa fraction was reported to be associated with C. chinensis resistance in urdbean (Umrao & Verma, 2003).Fractions ranging from 45 to 51 kDa have also been found associated with C. maculatus resistance in Phaseolus vulgaris (Brown et al., 1982), whereas Maro et al.
(2022) reported a 25 kDa seed storage protein associated with tolerant in common bean against Acanthoscelides obtectus and Zaborotes subfasciatus damage.Hence, different storage protein fractions associated with bruchid tolerance and/or resistance might be dependent on the legume and the bruchid species involved.
In the current study, only a 51 kDa fraction was observed to be associated with two C. maculatus tolerance measures, PAE and H.S.I., whereas other fractions were associated with one measure or the other singly.Not surprisingly, this fraction is associated with the vicilin family as mentioned by several authors (Saeed et al., 2022;Salgado et al., 2002).Other studies have also implicated vicilin as a protein that protects the cowpea seed against the damaging effect of the cowpea C. maculatus (Kpoviessi et al., 2021;Miranda et al., 2020;Rangel et al., 2003;Saeed et al., 2022).We infer that the presence of this protein plays a crucial role in C. maculatus tolerance in cowpea.
The suggested mechanism of action on the insect has been elucidated in the report of Miranda et al. (2020).
Hypothesis 2. There are some seed coat compounds involved in C. maculatus tolerance.
In most articles, compounds with insecticidal potential, especially from essential oils, leaf, bark, seed, or fruit extracts, are listed without further analysis of the likely compound(s) that possesses the insecticide potential (Abdelkhalek et al., 2022;Ishola et al., 2017;Li et al., 2018;Wang et al., 2014).Other times, authors depend on the abundance of compounds found in test substances to relate the effect of the compound on C. maculatus tolerance (Ebadollahi & Taghinezhad, 2020).Similarly, SCCs like phenolic acids, tannins, and flavonoids have also been associated with C. maculatus tolerance (Ojwang et al., 2012).Hence, they are unable to identify the actual compound with the insecticidal potential from the lot.There is therefore a need for further analysis and verification, narrowing the search down to potential compound(s) from the vast accumulations observed.
In the current study, of the SCCs revealed via the stepwise regression analysis to account for C. maculatus tolerance variability; both Thiazole, tetrahydro-and Undecane showed a more consistent significant influence on the various C. maculatus tolerance measures used in the study.Although a strong significant negative correlation was observed between these two compounds with PAE and H.S.I., a positive correlation relationship was also observed with Tol.This is an implication that the higher these compounds in the seed coat of cowpeas, the higher the tendency for the variety to be more tolerant to C. maculatus damage.This is so as more of these compounds were observed in the tolerant varieties than the susceptible varieties.Several compounds have been identified to confer resistance against C. maculatus in cowpea, which include alkaloids, flavonoids, phenols, phenolic acids, and tannins (Kpoviessi et al., 2021;Lattanzio et al., 2005;Ojwang et al., 2012).Hema et al. (2022)  The co-evolution of plants and their predators has resulted in phytophagous insects adaptation to the deterrent chemicals contained in the plants they feed on (Carlini & Grossi-De-Sá, 2002).Consequently, this may have led to the development of a more complex defense mechanism system against phytophagous insects such as the C. maculatus.As a result, seeds contain a diverse range of compounds that act either additively or synergistically against C. maculatus infestation (Msiska et al., 2018).
The present study showed that SSP prediction models explained more phenotypic variation than the SSCs in PAE and MDP when used alone as a predictor, whereas the reverse was observed with H.S.I., Tol, and TolSD for SCCs identified.However, SSPs and SCCs accounted for more phenotype variations when combined in the present study than using either alone as C. maculatus tolerance predictors.Consequently, cowpea tolerance or resistance to C. maculatus may be attributable to the interaction of SSPs and SCCs.An exception is H.S.I. and TolSD where SCCs accounted for more phenotypic variability than both predictors combined.The present study further revealed that SCCs accounted showed a greater effect on all C. maculatus tolerant measurements than the known related protein fractions.Additionally, the present study found that 51 kDa protein fraction as well as two compounds, Thiazole, tetrahydro-and Undecane, were substantial contributors to the C. maculatus tolerance measurements, thus showing that cowpea seeds do not rely on one type of biochemical defense.This is an implication that C. maculatus tolerance or resistance might be because of the accumulation of several biochemicals.
Studies have shown these two compounds, Thiazole, tetrahydro-, and Undecane, have insecticidal potentials (Wang et al., 2014;Yang et al., 2022).Thiazole is an important compound widely used in commercial pesticides, such as insecticides, nematicides, and fungicides.Furthermore, these compounds showed a significant positive correlation with C. maculatus tolerance.Hence, the more the compound within the seed coat of the variety, the more likely the variety would exhibit higher tolerance or resistance to C. maculatus damage.The significant positive correlation between these compounds, Thiazole, tetrahydro-and Undecane, might mean that the two variables maybe regulated by similar genetic loci, which would require further study (Acquaah, 2012;Miesho et al., 2017).However, because they exhibited high associations and contributed more to genetic variation for resistance to C. maculatus attack, the regression and correlation results suggest that the Thiazole, tetrahydro-and Undecane contents should be taken into account when selecting tolerant or resistant varieties to C. maculatus.Hence, this knowledge can be incorporated into breeding for C. maculatus resistant programs and should help breeders increase resistance in cowpea varieties.
presented in a chord diagram (Figure2).Compounds like 2-propanamine, acetamide, and benzenethanamine showed a single C. maculatus tolerance measure effect, whereas Thiazole, tetrahydroand Undecane showed multiple C. maculatus tolerance measures effects in the study.Seed storage protein fraction, 51 kDa, was observed to affect both PAE and H.S.I. in the study, whereas the other protein fractions represented in the additive model have a single C. maculatus tolerance measure effect.All C. maculatus tolerant measures showed more SCCs influence than the associated protein fractions identified.However, two compounds, Thiazole, tetrahydro-and Undecane, were identified as major contributors to the C. maculatus tolerance measures, whereas 51 and 57 kDa protein fractions also were major contributors in the study.
| C. maculatus tolerance measures and varietal performanceIn the present study, five C. maculatus tolerance measures were employed, and the weevil tolerance performance of the sampled cowpea varieties using the combination of these measures revealed the actual status of the varieties.These measures were used on the premise that C. maculatus tolerant varieties will have lower PAE and H.S.I. values, and higher MDP, Tol, and TolSD values while a reverse should be expected for susceptible varieties.This was obvious with the clustered C. maculatus tolerant measures into two groups, PAE T A B L E 6 Coefficient of determination (R 2 ) of seed coat compounds associated with C. maculatus tolerance measures used in the study.

T A B L E 8
Coefficient of determination (R 2 ) of seed storage protein and seed coat compounds associated with C. maculatus tolerance measures used in the study.and protein fractions with p < .05from the step-wise multiple regression models; PAE: percentage adult emergence; MDP: mean development period; H.S.I.: host suitability index; Tol: tolerance; TolSD: seed damage tolerance.*p < .05,and **p < .01.F I G U R E 2 Direct effect of identified compounds and protein fractions via path analysis model.Large values (without alphabets attached) signify protein fractions in kDa, and small numbers signify magnitude contribution from β value of the step-wise regression models; PAE: percentage adult emergence; MDP: mean development period; H.S.I.: host suitability index; Tol: tolerance; TolSD: seed damage tolerance; C73: 2-propanamine; C92: acetamide, N-(1-methylpropyl)-; C99: benzenethanamine, 3,4-dimethoxy-.alpha.-methyl-;C221: p-Dioxane-2,3-diol; C253: Thiazole, tetrahydro-; C267: Undecane.and H.S.I. in one group whereas MDP, Tol, and TolSD in another group.We initially thought that derived measures like H.S.I and Tol would perform similarly; however, the independence of these measures was explicit by the observed responses of varieties during the study.The need to use more than one C. maculatus tolerance measure when conducting C. maculatus tolerance research to avoid pseudotolerant outcomes from the varietal performance cannot be overemphasized.An example can be observed in the response of the TVu-100 variety which showed a low seed damage tolerance (TolSD) but moderate performance when PAE, H.S.I., and MDP were evaluated alongside.Hence, it was grouped as a moderate tolerant variety class.
also reported a moderate C. maculatus tolerance performance for IT84S-2246-4.Contrary to the present report, TVu-2027, TVu-11952, and TVu-11953 were categorized as moderate tolerance by Singh and Singh (1990), which contradicts the present study.The source of C. maculatus resistance or tolerance has been a subject of controversy among researchers.Although some schools of thought advocated for SSPs as the source for C. maculatus tolerance in cowpea, others suggested seed coats confer protection on the seeds against C. maculatus infestation.Hence, in this study, three hypotheses were raised which include (1) that storage protein only confers resistance against C. maculatus in cowpea seeds, (2) compounds within the seed coats limit the damaging effects of C. maculatus in cowpea seeds, and (3) C. maculatus resistance or tolerance results from the combine influence of some SSPs and SCCs.
Yang et al. (2022) highlighted that the derivatives of this compound, Thiazole, have been employed in controlling piercing and sucking pests, but are rare in their application to chewing pests, like bruchids.Hence, its potentials on insects like the C. maculatus need to be explored.Likewise,Wang et al. (2014) have identified Undecane as one of the active compounds of the essential oil from Amomum tsaoko against the red flour beetle, Tribolium castaneum (Herbst), and the cigarette beetle, Lasioderma serricorne (Fab.), an indication of the compound's protective potential.

Table 2 .
Seed weight, length, breadth, and thickness were least in the TVu-145 variety.The number of oviposited eggs ranges between T A B L E 2 Summary of traits evaluated in the study.

Table 3
) clustered the varieties into three groups.With PAE, three varieties were obtained with a PAE range of 0-45%, four varieties were moderately tolerant (PAE = 45-60%), and 12 varieties were considered susceptible (PAE > 60%).Two varieties with MDP > 40 days were considered highly tolerant when MDP was used as a C. maculatus tolerant measure.Eight varieties with MDP between 30 and 39 days were considered moderately tolerant, whereas nine varieties with MDP < 30 days were susceptible to C. maculatus infestation.H.S.I. measure of C. maculatus tolerant revealed four varieties, TVu-2027, TVu-11952, T A B L E 3 C. maculatus tolerant varieties as identified by tolerance parameters evaluated.Note: T: highly tolerant category; M: moderately tolerant/susceptible category; S: highly susceptible category; N: number of varieties in category; PAE: percentage adult emergence; MDP: mean development period; H.S.I.: host suitability index; Tol: tolerance; TolSD: seed damage tolerance.
Correlation relationship between identified compounds and C. maculatus tolerance measures.
into breeding for C. maculatus tolerant and biopesticide formulations to reduce the devastating effects of C. maculatus on cowpea production.